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A meta-analysis based review of quantifying the contributions of runoff components to streamflow in glacierized basins
Abstract
Quantifying the contributions of runoff components (CRCs) to streamflow is of significant importance for understanding the dynamics of water resources under changing climate in glacierized basins. This article presents a meta-analysis on different approaches for quantifying runoff components in glacierized basins, including the tracer-based end-member mixing method and the hydrological modeling approach. We collected estimated CRCs from 312 glacierized basin cases, as well as values of five characteristics in these basins including mean basin elevation (MBE), mean annual air temperature (MAT), mean annual precipitation (MAP), winter precipitation fraction (WPF) and glacierized area ratio (GAR). Relations between CRCs and the basin characteristics were assessed using a random forest (RF) algorithm. The review showed that CRCs were most often quantified by the hydrological modeling approach (73% of the basin cases). Compared to hydrological modeling, the tracer-based approach (applied in 19% of the basin cases) was more likely to be used in smaller basins <50 km², rather at the seasonal than annual time scale and with shorter study periods of <=5 years. Meta-analysis results indicate that: (1) At the annual time scale, the most important influencing basin characteristics were GAR and MBE for the ice melt contribution, WPF and MAP for the snow melt contribution, and GAR and WPF for the rainfall contribution. RF algorithm based on the five basin characteristics was able to explain 56%, 40%, and 40% of the variability of the reported annual contributions of ice melt, snowmelt and rainfall, respectively; the variability of seasonal CRCs and annual contribution of groundwater could be less well explained by the five basin characteristics. (2) Comparing different definitions of runoff components based on water-input or flow-pathway indicated that the ice melt contribution to total water input (sum of rainfall and melt water) based on the water-input definition was close to the contribution of ice melt-induced surface flow to total runoff based on the flow-pathway definition. In contrast, based on the reviewed studies, rainfall and snowmelt contributions based on the water-input definition were around 9%-14% higher than the contributions of rainfall and snowmelt induced surface flow to total runoff. (3) The tracer-based end-member mixing method tended to estimate larger uncertainties of CRCs than hydrological modeling, but uncertainties of modeled CRCs were likely underestimated as often only one or two of the three uncertainty sources of model parameter, model input and model structure were considered in the modeling studies. We propose that more efforts are required to cross validate CRCs estimated by the tracer-based and hydrological modeling methods, and to reduce uncertainties of CRCs by integrations of hydro-meteorological data and water tracer data.
... Comprehensive measurements of hydrological processes in glacierized basins are predominantly executed in small experimental headwater catchments, typically less than 10 km 2 (Pradhananga et al., 2021;Rets et al., 2019b;Strasser et al., 2018, etc.), while water resources management and economic activity is most often carried out in catchments exceeding 100-1000 km 2 . Tracer-based approach to estimation of contributions of runoff components to streamflow has been preferentially utilized in smaller basins, specifically those under 50 km 2 (He et al., 2021). This prompts an inquiry regarding the extent to which descriptions of hydrological processes, based on detailed measurements at a smaller catchment scale, can be representative for hydrological response of larger watersheds (Guastini et al., 2019;Zimmer and Gannon, 2018). ...
... The Caucasus region remains markedly underreported in terms of hydrometeorological data and studies (Barry, 1992;Bobrovitskaya and Kokorev, 2014;Shahgedanova et al., 2005). Tracer-based approach to estimation of contributions of runoff components in glacierized basins has been primarily utilized for catchments located in the Himalaya mountains, Tianshan in Central Asia, European Alps, Rocky Mountains and Andes (He et al., 2021). Previously in the Caucasus isotopic-based estimation of different runoff sources contributions was performed only for the Djankuat Research Catchment situated in the headwaters of the Baksan basin (Rets et al., 2017;Vasil'chuk et al., 2016) where isotopic studies have been carried out since 2013 (Rets et al., 2019b). ...
As glacier degradation is intensifying worldwide, understanding how and when glacial runoff is important becomes imperative for economic planning and societal adaptation in response to climate change. This research highlights a probable emergence of new low-flow periods, ranging from one to several weeks, with an anticipated 50-90% reduction in runoff even in major rivers originating in glacierized mountains by the mid to late 21th century. While the predicted decline in annual and monthly runoff appears moderate for most glaciated regions globally, the emergence of new deglaciation-induced summer low flow periods could create critical “bottle necks” constraining effective water resources management.
In this study, a nested catchment approach (7.6 – 2259 km2) in conjunction with an isotopic tracer method (D, 18O), was employed to quantify the seasonal dynamics of snow and glacial meltwater and rainfall contribution to runoff across various scales of river catchments for the underreported Caucasus Mountains. Although the contribution of meltwater was predictably dominant in the headwaters (75–100%), it still constituted a substantial 50–60% of river runoff in the lower reaches most of the time from June to September. While the relative capacity for rainwater storage was found to significantly increase with watershed scale, during weeks devoid of noteworthy rainfall, the runoff in river basins with a mere 7% glaciation basically entirely consists of what is formed in the glacierized headwaters. The glacial runoff was prevalent in the melt component from late July/early August to mid-September: not less than 30–60% to the total runoff in the headwaters and 30–40% in the lower reaches.
An approach is proposed to account for the spatial heterogeneity of stable water isotopic content within snow cover and glacier ice. Sources of uncertainties and soundness of assumptions typically used for isotopic hydrograph separation are discussed with particular consideration given to the study objectives.
... Issues of high uncertainty and parameter equifinality are widely recognized in hydrological modeling (Gupta et al., 2008), especially in cold mountainous regions where multiple runoff components and large spatiotemporal variabilities in runoff generation processes enhance the hydrological complexity (Li et al., 2019;He et al., 2021). The hydrological model is the commonly used method to estimate the contribution of runoff components, which is, however, subject to several challenges, including the model conceptualizations of water mixing and propagation (Nepal et al., 2014) and the notable compensatory effects of different components inadequately constrained by the commonly used streamflow data (Duethmann et al., 2015). ...
... The THREW-T model quantifies the contributions of runoff components to the streamflow based on two definitions, as reviewed in He et al. (2021). One is based on the water sources of the total water input triggering runoff processes, including rainfall, snowmelt and glacier melt. ...
Uncertainty and parameter equifinality are important issues for hydrological models, especially in cold mountainous regions where multiple runoff components enhance the hydrological complexity. Tracer-aided hydrological models integrating water isotope modules are helpful for improving the physical representation of the model structure and parameter identification. Under the common complete-mixing assumption in the distributed tracer-aided model, the simulation time step reflects the water movement velocity at the hydrological unit scale and influences the model performance, which has yet to be addressed in previous studies. Consequently, the question of how the simulation time step influences the performance of tracer-aided hydrological models is poorly understood. In this study, we utilized a tracer-aided model THREW-T for a mountainous basin on the Tibetan Plateau to explore the above questions. The results showed that (1) the simulated variations in streamflow, snow cover area and stream water isotopes were similar among different time scales, but the isotope simulation performance worsened when adopting longer time steps. Simulation time steps ranging from 1 to 24 h led to a 10% difference in the estimated contribution of subsurface runoff, which decreased with increasing time scale. (2) A longer simulation time step yielded a lower simulated variability of stream water isotopes because of the lower water velocity within hydrological units. To offset this effect, the model characterized quicker water movement at the catchment scale by estimating a lower contribution of the slow runoff component. (3) Despite the additional uncertainty resulting from the simulation time step, the involvement of isotopes in the calibration objective still improved the model confidence by increasing the parameter sensitivity to the partitioning among the different runoff components, resulting in more reasonable water apportionment estimates. This study addresses the influence of the time scale on the performance of tracer-aided hydrological models and highlights the importance of adopting a suitable time step when applying these models, rather than the daily scale commonly adopted in most existing modeling practices.
... The THREW-T model defined the runoff components based on the runoff generation flow-pathway as reviewed by He et al. (2021). The total runoff was divided into surface and subsurface runoff (baseflow). ...
Understanding the hydrological processes on the Tibetan Plateau (TP) under climate change is an important scientific question. The frequent multiphase transfer exacerbates the complexity of hydrological processes on the TP, which brings equifinality problem to hydrological models and causes large uncertainties in quantifying the contributions of runoff components. Tracer‐aided hydrological models are helpful for improving model performances and have been adopted in cryospheric regions, but the influence of frozen soil has yet to be considered. This study adopted the Tracer‐aided Tsinghua Representative Elementary Watershed model (THREW‐T) in a typical cold basin with widespread frozen soil on the TP. The model structure was diagnosed with isotope by identifying the influences of frozen soil. A simplified catchment‐scale frozen soil module was incorporated into the model. Results showed that: (a) The THREW‐T model cannot simultaneously simulate baseflow and stream water isotope well. The imbalance of simulations on two objectives could be attributed to the influence of frozen soil, resulting in seasonal variation of soil‐related parameters, which was not considered in the model. (b) Incorporating the frozen soil module significantly improved the balance of baseflow and isotope simulation, simultaneously producing low baseflow and high contribution of subsurface runoff during wet seasons. (c) The frozen soil had little influence on the annual streamflow, but changed the runoff seasonality by reducing baseflow during dry seasons and increasing subsurface runoff during wet seasons. The frozen soil module was still simplified, and further work is needed to improve the physical representation of soil freeze‐thaw process. This study highlights the value of tracer‐aided hydrological modeling method on diagnosing model structure by identifying the influence of specific processes such as frozen soil.
... A meta-analysis based review of glacio-hydrological studies estimated that about 94% used the temperature-index method for modelling purposes, and only 6% used the energy-balance approach (He et al., 2021). One of the reasons for the widespread use of temperature-index and degree-day models is their requirement for relatively minimal input data, which makes them practical and accessible for various applications (Martinec and Rango, 1986;Hock, 2003). ...
Accurately quantifying runoff sources and understanding hydrological processes in glaciated mountain basins is essential for effective water resource management in the face of climate change. This study aimed to determine the contributions from various runoff sources in glaciated basins within the inner Tien-Shan mountains of Kyrgyzstan by utilizing integrated land surface, glacier energy-mass balance, and river routing models. To account for local topographic influences on solar radiation and cloud transmissivity processes, gridded meteorological forcing data were downscaled. The integrated models were then evaluated against observed discharge, glacier mass balance, and snow water equivalent, with a focus on the Kara-Batkak glacier reference site. Shortwave radiation correction was particularly important for improving the accuracy of model simulations. The results indicate that the peak glacier melt contribution occurs in July and August, with some basins reaching up to 54%. On an annual basis, the average contribution from glaciers across the basins was found to be 19%, while the ratios of snowmelt and rainfall were 58% and 23%, respectively. This study highlights the utility of integrated modelling approaches in understanding and quantifying runoff components in data-scarce high mountain regions. The incorporation of observed glacier data proved to be crucial for accurately representing hydrological processes under current climatic conditions. These findings underscore the significance of considering glacier dynamics and their influence on water resources to inform effective water management strategies in glaciated mountain basins.
... Pu et al., 2017). To date, only limited research has been conducted on the analysis of supra-permafrost groundwater, while a systematic and quantitative investigation of sub-permafrost groundwater remains lacking (He et al., 2021;Y. G. Li et al., 2020;. ...
Supra‐ and sub‐permafrost groundwater are the two main components of groundwater in permafrost regions. However, due to the lack of groundwater observational data, the spatial‐temporal differentiation of these groundwater components in permafrost basins remains unclear. Based on flow data from 17 hydrological stations in five permafrost rivers within the Eurasian Arctic and Qinghai‐Tibet Plateau permafrost regions, this study tries to determine the proportion of supra‐ and sub‐permafrost groundwater through the corresponding relationship between baseflow separation and baseflow index. The results showed that the annual average contribution of supra‐ and sub‐permafrost groundwater in river runoff to total streamflow in the Yangtze River source basin was 36.81% and 14.56%, respectively. Correspondingly, the Yellow River source basin was 36.58% and 24.46%, the Ob River basin was 37.05% and 26.83%, the Yenisei River basin was 28.80% and 36.56%, and the Lena River basin was 39.13% and 9.54%. Over the past 50–80 years, the ratio of sub‐permafrost groundwater discharge to river runoff and the flux of sub‐permafrost groundwater have shown an increasing trend in all study basins, which was significantly affected by air temperature and permafrost area. Relative contribution of supra‐permafrost groundwater exhibits a significant positive correlation with precipitation and permafrost area. Air temperature has both positive and negative effects on supra‐permafrost groundwater discharge, leading to a rising or falling trend of supra‐permafrost groundwater discharge. In the future, it is necessary to further explore the complex effects of groundwater discharge variations on streamflow in permafrost regions under climate warming.
... The THREW-T model quantified the contributions of multiple runoff sources based on the flow-pathway definition as reviewed by He et al. (2021). The total runoff was first divided into surface runoff and subsurface runoff (baseflow), and the surface runoff was further divided into three components induced by different water sources (rainfall, snowmelt, and glacier melt). ...
Keywords: Tracer-aided hydrological model Soil moisture Stable isotope Runoff source apportionment Mountainous basin A B S T R A C T Multiple-objective calibration helps constrain the parameter uncertainties and improve the performances of hydrological models. Previous studies have indicated that calibration toward soil moisture data could improve the streamflow simulation, but its influence on the runoff source apportionment quantification still needs to be analyzed. Meanwhile, although isotope calibration has proved to improve the representation of internal hydrological processes, the value of isotope on the simulation of internal state variables such as soil moisture has yet to be examined. This study utilized the tracer-aided hydrological model THREW-T (Tsinghua Representative Elementary Watershed-Tracer-aided version) in two mountainous basins on the Tibetan Plateau (The Upper Brahmaputra and Upper Yangtze basins) to evaluate the value of soil moisture and isotope data on model calibration. The result shows that: (1) The THREW-T model produced good simulation on streamflow, snow cover area, soil moisture, and stream water isotope simultaneously in the two study areas. Calibration toward soil moisture and isotope caused slight (~0.03) but statistically significant (p < 0.01) decrease on the Nash-Sutcliffe coefficient of streamflow simulation compared to the baseline calibration variant only toward streamflow. (2) Calibration toward soil moisture brought no improvement to streamflow simulation for the validation period and stations in both basins, only improving soil moisture simulation. However, calibration toward the isotope improved the simulations of internal streamflow and soil moisture's spatiotemporal variation. (3) Different calibration variants resulted in different estimations of the runoff source apportionment, and independent evidence indicated that the results obtained by isotope calibration were most reasonable. Calibrations toward streamflow and soil moisture underestimated and overestimated the contributions from subsurface runoff, respectively. Isotope was the most sensitive objective to the runoff source apportionment and significantly reduced the uncertainty. Our study found a lower value of soil moisture data than the isotope on model calibration. However, we believe that the full potential of soil moisture data was not utilized due to the current limitations in soil moisture simulation and measurement methods, and the development of relevant technologies will make the soil moisture data more valuable for model calibration.
... The range of climate perturbation is assumed based on the possible change range projected by an ensemble of GCMs, providing a possible runoff change range accordingly (Su et al., 2023;. The climate perturbation method also allows for a deeper analysis of the separate effect of each climatic factor and the compensation effects among them (He and Pomeroy, 2023). ...
The major rivers on the Tibetan Plateau supply important freshwater resources to riparian regions but have been undergoing significant climate change in recent decades. Understanding the sensitivities of hydrological processes to climate change is important for water resource management, but large divergences exist in previous studies because of the uncertainties of hydrological models and climate projection data. Meanwhile, the spatial pattern of local hydrological sensitivities was poorly explored despite the strong heterogeneity on the Tibetan Plateau. This study adopted the climate perturbation method to analyze the hydrological sensitivities of a typical large mountainous basin (Yarlung Tsangpo River, YTR) to climate change. We utilized the tracer-aided hydrological model Tsinghua Representative Elementary Watershed-Tracer-aided version (THREW-T) to simulate the hydrological and cryospheric processes in the YTR basin. Multiple datasets and internal stations were used to validate the model to provide confidence in the base-line simulation and the sensitivity analysis. Results indicated that (1) the THREW-T model performed well in simulating the streamflow, snow cover area (SCA), glacier mass balance (GMB) and stream water isotope, ensuring good representation of the key cryospheric processes and a reasonable estimation of the runoff components. The model performed acceptably in simulating the streamflow at eight internal stations located in the mainstream and two major tributaries , indicating that the spatial pattern of hydrological processes was reflected by the model. (2) Increasing temperature led to decreasing annual runoff, smaller inter-annual variation , more even intra-annual distribution and an earlier maximum runoff. It also influenced the runoff regime by increasing the contributions of rainfall and glacier melt overland runoff but decreasing the subsurface runoff and snowmelt overland runoff. Increasing precipitation had the opposite effect to increasing temperature. (3) The local runoff change in response to increasing temperature varied significantly, with a changing rate of − 18.6 % to 54.3 % for 5 • of warming. The glacier area ratio (GAR) was the dominant factor in the spatial pattern of hydrological sensitivities to both perturbed temperature and precipitation. Some regions had a non-monotonic runoff change rate in response to climate perturbation, which represented the most dynamic regions within the basin, as they kept shifting between energy-and water-limited stages. The GAR and mean annual precipitation (MAP) of the non-monotonic regions had a linear relation and formed the boundary of regions with different runoff trends in the GAR-MAP plot.
... Currently, there are growing concerns about the influence of global warming on river hydrology in Central Asia, particularly on the different responses of each hydrologic component to climate change (Gan et al., 2015;Immerzeel et al., 2010;He et al., 2021). Previous studies indicated that the ice melt runoff may demonstrate a transitory increase resulting from retreating glaciers caused by warmer temperatures and reinforced melting, until reaching a maximum (peak water), followed by a decrease due to reduction of the available ice volumes (Jansson et al., 2003;Gleick and Palaniappan, 2010;Baraer et al., 2012;Huss and Hock, 2018;Ayala et al., 2020). ...
... To our knowledge, the present study is the first large-scale assessment of the impact of multiple sources of uncertainty 630 (both historical and future) from a perspective beyond future glacier mass loss. In order to advance with climate change adaptation plans for the long-term sustainability of local ecosystems, future studies should address sources of uncertainty not considered in this study (e.g., parameterization of frontal ablation, climate downscaling and surface mass balance and ice-flow models), and the relative contribution of non-glacial water sources (Drenkhan et al., 2022;He et al., 2021). The latter will improve our understanding of the potential relative contribution of glaciers (e.g., Kaser et al., 2010), and the fluxes between 635 the different water stores. ...
Glaciers are retreating globally and are projected to continue to lose mass in the coming decades, directly affecting downstream ecosystems through changes in glacier runoff. Estimating the future evolution of glacier runoff involves several sources of uncertainty in the modelling chain, which to date have not been comprehensively assessed on a regional scale. In this study, we used the Open Global Glacier Model (OGGM) to estimate the glacier evolution of each glacier (area > 1 km2) in the Patagonian Andes (40–56° S), which together represent 82 % of the glacier area of the Andes. We used different glacier inventories (n = 2), ice thickness datasets (n = 2), historical climate datasets (n = 4), general circulation models (GCMs; n = 10), emission scenarios (SSPs; n = 4), and bias correction methods (BCMs; n = 3) to generate 1,920 possible scenarios over the period 1980–2099. For each scenario and catchment, glacier runoff and melt on glacier time series were characterized by ten glacio-hydrological signatures (i.e., metrics). We used the permutation feature importance of random forest regression models to assess the relative importance of each source on the signatures of each catchment. Considering all scenarios, 61 % ± 14 % of the catchment area (30 % ± 13 % of glacier area) has already peaked in terms of glacier melt (year 2020), and 43 % ± 8 % of the catchment area (18 % ± 7 % of glacier area) will lose more than 80 % of its volume this century. Considering the melt on glacier signatures, the future sources of uncertainty (GCMs, SSPs and BCMs) were the main source in only 18 % ± 21 % of the total catchment area. In contrast, the reference climate was the most important source in 78 % ± 21 % of the catchment area, highlighting the importance of the choices we make in the calibration procedure. The results provide a basis for prioritizing future efforts (e.g., improve reference climate characterization) to reduce glacio-hydrological modelling gaps in poorly instrumented regions, such as the Patagonian Andes.
... Distributed hydrological models are often calibrated using the observed streamflow at the outlet of a catchment (Gupta and Govindaraju, 2022). However, this approach may mislead landscape features that significantly affect runoff generation, because the streamflow embeds contributions from several hydrological components in natural catchments (He et al., 2021;Taia et al., 2023). Moreover, relying simply on a single point for calibrating distributed models may not provide correct simulations in every part of the study area (Sirisena et al., 2020). ...
The mitigation of uncertainties in the identification of natural systems is a fundamental aspect in the development of hydrological models, and represents a major challenge for the improvement of modelling techniques. In particular, the calibration of hydrological models based on streamflow measurements at the outlet of a catchment is exposed to significant sources of uncertainty, such as the impact of landscape features on runoff generation. Remote sensing-based actual evapotranspiration (AET) data can be incorporated with streamflow to improve model accuracy and reduce the uncertainty in hydrological modelling, resulting in a significant enhancement of the model performance. The selection of the right AET dataset for hydrological modelling is a crucial task, in front of the availability of multi-source datasets that differ in methods, parameters, and spatiotemporal resolution. Despite the existence of a few studies proposing the usage of remote sensing-based AET data, there is a lack of systematic comparisons between different products, in terms of performance for hydrological modelling. This paper aims to compare the efficacy of different remote sensing-based AET products in improving the simulation of hydrological responses, both in single and in multi-variable scenarios. In this investigation, the Soil and Water Assessment Tool (SWAT) hydrological model was calibrated with observed streamflow data by experimenting with eight different AET datasets. The findings of our study suggest that the incorporation of remote sensing-based AET data in the calibration process of a hydrological model can significantly enhance the accuracy and reliability of model predictions. Thus, the proposed approach can contribute to improving the effectiveness of hydrological modelling as a quantitative tool for the management of water resources. Another finding of this study is that the calibration of the model based solely on AET yields reasonable simulation results of the streamflow, which is an advantageous and promising feature for ungauged basins.
... Therefore, in this study, we coupled the degree-day factor algorithm (Hock, 2003) to the VIC model to simulate the contribution of glacier runoff to total runoff; the extended model is called VIC-Glacier. It is very important to define runoff components clearly (He et al., 2021). In this study, the runoff component is defined as the proportion of each component in the streamflow, and the total runoff is divided into three components: glacier, rainfall, and snowmelt runoff. ...
The Three-River Source Region (TRSR), which is known as “China's Water Tower” and affects the water resources security of 700 million people living downstream, has experienced significant hydrological changes in the past few decades. In this work, we used an extended variable infiltration capacity (VIC) land surface hydrologic model (VIC-Glacier) coupled with the degree-day factor algorithm to simulate the runoff change in the TRSR during 1984–2018. VIC-Glacier performed well in the TRSR, with Nash–Sutcliffe efficiency (NSE) above 0.68, but it was sensitive to the quality of the limited ground-based precipitation. This was especially marked in the source region of the Yangtze River: when we used Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks – Climate Data Record (PERSIANN-CDR), which has better spatial details, instead of ground-based precipitation, the NSE of Tuotuohe station increased from 0.31 to 0.86. Using the well-established VIC-Glacier model, we studied the contribution of each runoff component (rainfall, snowmelt, and glacier runoff) to the total runoff and the causes of changes in runoff. The results indicate that rainfall runoff contributed over 80 % of the total runoff, while snowmelt runoff and glacier runoff both contributed less than 10 % in 1984–2018. Climate change was the main reason for the increase in runoff in the TRSR after 2004, accounting for 75 %–89 %, except in the catchment monitored by Xialaxiu station. Among climate change factors, precipitation had the greatest impact on runoff. Finally, through a series of hypothetical climate change scenario experiments, we found that a future simultaneous increase in precipitation and temperature would increase the total runoff, rainfall runoff, and glacier runoff. The snowmelt runoff might remain unchanged because the increased precipitation, even with seasonal fluctuations, was basically completely compensated for by the decreased solid-to-liquid precipitation ratio. These findings improve our understanding of hydrological processes and provide insights for policy-makers on how to optimally allocate water resources and manage the TRSR in response to global climate change.
... So far, most studies have focused on modern hydroclimate based on instrumental data during recent decades, including the spatio-temporal characteristics of hydroclimate (e.g., temperature, precipitation, glacier and runoff, ect.), the coupling relationships between hydroclimatic parameters and the associated modulating mechanisms Chen et al. 2016;Guan et al. 2022;He et al. 2021;Leng et al. 2021;Shen et al. 2020;Wang et al. 2013;Yang et al. 2021;Zheng et al. 2021). However, the hydroclimatic information beyond the instrumental period is also key issue in understanding long-term hydrological responses to climate change, and the detailed information of hydrological changes over longer time period in the TMs is still scarce (Feng et al. 2022;Lan et al. 2019). ...
Numerous studies have focused on modern hydroclimate and the modulated mechanisms in the Tianshan Mountains (TMs), arid central Asia. However, the detailed information of hydroclimatic processes beyond the instrumental period is still scarce. This paper reconstructed a hydrology history from core sediments of the Dalongchi Lake in the Tianshan Mountains. The comparability between end-members (EMs) of grain size and ICP-AES based geochemical elements in the lake sediments highlighted their availability for hydrological reconstructions. Hydrodynamic forces (EM1, EM4, Ti/Al and Li/Al), chemical weathering intensity [(Mg+Ca+K)/Al], salinity proxy (Mg/Ca) and redox-sensitive proxy (Fe/Mn) highly correlated with the first principal component (P<0.01), whereas paleoproductivity proxies (TN, TOC, Ba/Al, Zn/Al and Cu/Al) and C/N showed high loadings on the second principal component (P<0.05). The inferred hydrology progress was nonlinearly responded to temperature, precipitation and climate-dictated glaciers. Specifically, the water level didn’t always covary with the humidity because of glaciers. The maximum water level was the comprehensive result of glaciers melting and high humidity around 1830 CE. Thereafter, water level continually decreased with declining moisture at high temperature, implying a limited buffering capacity of glaciers in the Dalongchi Lake basin. EM3-indicated eolian activity intensity was caused by the behaviors of Siberian High because the latter intensified surface wind and the dust transportation. The hydrothermal patterns were characterized by warm/dry and cold/wet alternations in a long run although warm/wet pattern was identified from a short-term view.
... Many scholars have discussed the evolution and driving mechanisms of hydrological processes under conditions of change. Most studies concentrate on watersheds, and analyze the evolution characteristics and internal relations of hydrological processes such as extreme precipitation (Tan et al. 2021), drought evolution (Mukherjee et al. 2018) and runoff monitoring (He et al. 2021). Such research only focuses on the evolution of hydrometeorological characteristics under climate change and considers changes in circulation and geographical factors when discussing underlying causes. ...
The Huaihe River Basin (HRB) is located in the north-south climate transition zone of China and is highly susceptible to climate change. Analysis of the evolution pattern and potential causes of extreme hydrometeorological events is of great significance for flood prevention, mitigation and water resource planning in the basin. Based on the measured meteorological data in the HRB for 1963–2018, statistical analysis methods were used to test variations on extreme hydrometeorological events (precipitation and drought). Possible effects of global warming, atmospheric circulation patterns and sunspots on the spatiotemporal variability of hydrological events were also explored, effectively identifying the common influencing factors of extreme precipitation and drought events. The results show that (1) Extreme hydrometeorological events in the upper reaches are serious, but extreme precipitation tends to slow with time; the increase in extreme precipitation indices in the middle reaches deserves attention, while drought conditions are relatively mild; the drought trend in the lower reaches is significant, and extreme precipitation has improved. (2) Each inactive image for different periods is loaded onto the canvas, and a dynamic graph is used to display the temporal and spatial evolution pattern of extreme hydrometeorological events. (3) Global mean near-surface temperature anomalies (GTEM) are positively correlated with most extreme precipitation indices but negatively correlated with drought indices. The increase in the number of sunspots eased extreme precipitation and worsened drought.
... The temperature index method was employed to simulate snow and glacier melting (Gao et al., 2017(Gao et al., , 2020He et al., 2021). We used a snow reservoir (S w ) to account for the snow accumulating, melting (M w ), and water balance (Eq. ...
Increased attention directed at frozen soil hydrology has been prompted by climate change. In spite of an increasing number of field measurements and modeling studies, the impact of frozen soil on hydrological processes at the catchment scale is still unclear. However, frozen soil hydrology models have mostly been developed based on a bottom-up approach, i.e., by aggregating prior knowledge at the pixel scale, which is an approach notoriously suffering from equifinality and data scarcity. Therefore, in this study, we explore the impact of frozen soil at the catchment scale, following a top-down approach, implying the following sequence: expert-driven data analysis → qualitative perceptual model → quantitative conceptual model → testing of model realism. The complex mountainous Hulu catchment, northeast of the Qinghai–Tibet Plateau (QTP), was selected as the study site. First, we diagnosed the impact of frozen soil on catchment hydrology, based on multi-source field observations, model discrepancy, and our expert knowledge. The following two new typical hydrograph properties were identified: the low runoff in the early thawing season (LRET) and the discontinuous baseflow recession (DBR). Second, we developed a perceptual frozen soil hydrological model to explain the LRET and DBR properties. Third, based on the perceptual model and a landscape-based modeling framework (FLEX-Topo), a semi-distributed conceptual frozen soil hydrological model (FLEX-Topo-FS) was developed. The results demonstrate that the FLEX-Topo-FS model can represent the effect of soil freeze–thaw processes on hydrologic connectivity and groundwater discharge and significantly improve hydrograph simulation, including the LRET and DBR events. Furthermore, its realism was confirmed by alternative multi-source and multi-scale observations, particularly the freezing and thawing front in the soil, the lower limit of permafrost, and the trends in groundwater level variation. To the best of our knowledge, this study is the first report of LRET and DBR processes in a mountainous frozen soil catchment. The FLEX-Topo-FS model is a novel conceptual frozen soil hydrological model which represents these complex processes and has the potential for wider use in the vast QTP and other cold mountainous regions.
... We used the moving average method to remove the noise of the original precipitation time series data (Xie et al. 2016). We also used the Fourier transform method to fit precipitation time series data after noise removal (He et al. 2021;Manju and Mavi 2021). The Fourier function after fitting was defined as the periodic component of precipitation in the YRB. ...
Precipitation is a main part of the regional hydrological cycle, and global warming affects the hydrological cycle because regional precipitation is impacted by mechanistic changes in the hydrological cycle under global warming. This study presents an exploration of the composition variation characteristics of precipitation time series under global climate change. Twelve CMIP6 models were used to forecast precipitation changes in the Yellow River Basin (YRB). Climatic Research Unit (CRU) data were applied in the analysis of historical precipitation. Trend analysis, precipitation bias correction, and Fourier functions were used to analyze the future precipitation change characteristics. Our results showed that the IPSL-CM6A-LR and EC-Earth3-CC models had excellent performances in simulating precipitation in the YRB. Most CMIP6 models showed that precipitation under the SSP5-8.5 scenario had a higher increasing trend and was higher than that under the SSP2-4.5 scenario. The multimodel ensemble means (MEM) of CMIP6 precipitation showed that the future trend and stochastic component of precipitation had a higher degree of contribution than the historical trend and stochastic component of precipitation. However, the future periodic component of precipitation had a lower degree of contribution than the historical component. Most models showed that the degree of contribution of the periodic component of precipitation in Period IV (2015–2057) was higher than that in Period V (2058–2100). Most models showed similar degrees of contribution in Period I (1901–1938), Period II (1939–1976), and Period III (1977–2014). However, the degree of contribution of the stochastic component in 2058–2100 was lower than that in 2015–2057. This study improves the understanding of future precipitation change characteristics and provides a reference for disaster prevention and mitigation in the YRB.
Snow and glacier melt are significant contributors to streamflow in Himalayan catchments, and their increasing contributions serve as key indicators of climate change. Consequently, the quantification of these streamflow components holds significant importance for effective water resource management. In this study, we utilized the spatio‐temporal variability of isotopic signatures in stream water, rainfall, winter fresh snow, snowpack, glaciers, springs, and wells, in conjunction with hydrometeorological observations and Snow Cover Area (SCA) data, to identify water sources and develop a conceptual understanding of streamflow dynamics in three catchments (Lidder, Sindh, and Vishow) within the western Himalayas. The following results were obtained: (a) endmember contributions to the streamflow exhibit significant spatial and seasonal variability across the three catchments during 2018–2020; (b) snowmelt dominates streamflow, with average contributions across the entire catchment varying: 59% ± 9%, 55% ± 4%, 56% ± 6%, and 55% ± 9% in Lidder, 43% ± 6%, 38% ± 6%, 32% ± 4%, and 33% ± 5% in Sindh and 45% ± 8%, 40% ± 6%, 39% ± 6%, and 32% ± 5% in Vishow during spring, summer, autumn, and winter seasons, respectively; (c) glacier melt contributions can reach ~30% to streamflow near the source regions during peak summer; (d) The primary uncertainties in streamflow components are attributed to the spatiotemporal variability of tracer signatures of winter fresh snow/snowpack (±1.9% to ±20%); (e)regarding future streamflow components, if the glacier contribution were to disappear completely, the annual average streamflow in Lidder and Sindh could decrease up to ~20%. The depletion of the cryosphere in the region has led to a rapid increase in runoff (1980–1900), but it has also resulted in a significant streamflow reduction due to glacier mass loss and changes in peak streamflow over the past three decades (1990–2020). The findings highlight the significance of environmental isotope analysis, which provides insights into water resources and offers a critical indication of the streamflow response to glacier loss under a changing climate.
Climate warming exacerbates the degradation of the mountain cryosphere, including glacier retreat, reduction in snow cover area, and permafrost degradation. These changes dramatically alter the local and downstream hydrological regime, posing significant threats to basin-scale water resource management and sustainable development. However, there is still a lack of systematic research that evaluates the variation of cryospheric elements in mountainous catchments and their impacts on future hydrology and water resources. In this study, we developed an integrated cryospheric-hydrologic model, referred to as the FLEX-Cryo model. This model comprehensively considers glaciers, snow cover, frozen soil, and their dynamic impacts on hydrological processes in the mountainous Hulu catchment located in the Upper Heihe river of China. We utilized the state-of-the-art climate change projection data from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) to simulate the future changes in the mountainous cryosphere and their impacts on hydrology. Our findings showed that the two glaciers in the Hulu catchment will completely melt out around the years 2045–2051. By the end of the 21st century, the annual maximum snow water equivalent is projected to decrease by 41.4 % and 46.0 %, while the duration of snow cover will be reduced by approximately 45 and 70 days. The freeze onset of seasonal frozen soil is expected to be delayed by 10 and 22 days, while the thaw onset of permafrost is likely to advance by 19 and 32 days. Moreover, the maximum freeze depth of seasonal frozen soil is projected to decrease by 5.2 and 10.9 cm per decade, and the depth of the active layer will increase by 8.2 and 15.5 cm per decade. Regarding hydrology, runoff exhibits a decreasing trend until the complete melt-out of glaciers, resulting in a total runoff decrease of 15.6 % and 18.1 %. Subsequently, total runoff shows an increasing trend, primarily due to an increase in precipitation. Permafrost degradation causes the duration of low runoff in the early thawing season to decrease, and the discontinuous baseflow recession gradually transitions into linear recessions, leading to an increase in baseflow. Our results highlight the significant changes expected in the mountainous cryosphere and hydrology in the future. These findings enhance our understanding of cold-region hydrological processes and have the potential to assist local and downstream water resource management in addressing the challenges posed by climate change.
The major rivers on the Tibetan Plateau supply important freshwater resources to riparian regions, but are undergoing significant climate change in recent decades. Understanding the sensitivities of hydrological processes to climate change is important for water resource management, but large divergences existed in previous studies because of the uncertainties of hydrological models and climate projection data. Meanwhile, the spatial pattern of local hydrological sensitivities was poorly explored despite the strong heterogeneity on the Tibetan Plateau. This study adopted the climate perturbation method to analyze the hydrological sensitivities of a typical large mountainous basin (Yarlung Tsangpo River, YTR) to climate change. We utilized the tracer-aided hydrological model Tsinghua Representative Elementary Watershed-Tracer-aided version (THREW-T) to simulate the hydrological and cryospheric processes in the YTR basin. Datasets of multiple objectives and internal stations were used to validate the model, to provide confidence to the baseline simulation and the sensitivity analysis. Results indicated that: (1) The THREW-T model performed well on simulating the streamflow, snow cover area (SCA), glacier mass balance (GMB), and stream water isotope, ensuring good representation of the key cryospheric processes and a reasonable estimation of runoff components. The model performed acceptably on simulating the streamflow at eight internal stations located in the mainstream and two major tributaries, indicating that the spatial pattern of hydrological processes was reflected by the model. (2) Increasing temperature led to decreasing annual runoff, smaller inter-annual variation, more even intra-annual distribution, and an earlier maximum runoff. It also influenced the runoff regime by increasing the contributions of rainfall and glacier melt overland runoff, but decreasing the subsurface runoff and snowmelt overland runoff. Increasing precipitation had the opposite effect to increasing temperature. (3) The local runoff change in response to increasing temperature varied significantly, with changing rate of -18.6 % to 54.3 % for 5 °C of warming. The glacier area ratio (GAR) was the dominant factor of the spatial pattern of hydrological sensitivities to both perturbed temperature and precipitation. Some regions had a non-monotonic runoff change rate in response to increasing temperature, the GAR and mean annual precipitation (MAP) of which showed linear relation, and formed the boundary of regions with different trends in response to climate warming in the GAR-MAP plot.
Understanding the main drivers of runoff components and contributions of precipitation and temperature have important implications for water-limited inland basins, where snow and glacier melt provide essential inputs to surface runoff. To quantify the impact of temperature and precipitation changes on river runoff in the Tarim River basin (TRB), the Hydrologiska Byrans Vattenbalansavdelning (HBV)-light model, which contains a glacier routine process, was applied to analyze the change in runoff composition. Runoff in the headstream parts of the TRB was more sensitive to temperature than to precipitation. In the TRB, overall, rainfall generated 41.22% of the total runoff, while snow and glacier meltwater generated 20.72% and 38.06%, respectively. These values indicate that temperature exerted more major effects on runoff than did precipitation. Runoff compositions were different in the various subbasins and may have been caused by different glacier coverages. The runoff volumes generated by rainfall, snowmelt, glacier melt was almost equal in the Aksu River subbasin. In the Yarkand and Hotan River subbasins, glacier meltwater was the main supplier of runoff, accounting for 46.72% and 58.73%, respectively. In the Kaidu-Kongque River subbasin, 80.86% was fed by rainfall and 19.14% was fed by snowmelt. In the TRB, runoff generated by rainfall was the dominant component in spring, autumn, winter, while glacier melt runoff was the dominant component in summer. Runoff in the TRB significantly increased during 1961–2016; additionally, 56.49% of the increase in runoff was contributed by temperature changes, and 43.51% was contributed by precipitation changes. In spring, the runoff increase in the TRB was mainly caused by the precipitation increase, opposite result in summer and autumn. Contribution of temperature was negative in winter. Our findings have important implications for water resource management in high mountainous regions and for similar river basins in which melting glaciers strongly impact the hydrological cycle.
Global hydrological models have become a valuable tool for a range of global impact studies related to water resources. However, glacier parameterization is often simplistic or non-existent in global hydrological models. By contrast, global glacier models do represent complex glacier dynamics and glacier evolution, and as such, they hold the promise of better resolving glacier runoff estimates. In this study, we test the hypothesis that coupling a global glacier model with a global hydrological model leads to a more realistic glacier representation and, consequently, to improved runoff predictions in the global hydrological model. To this end, the Global Glacier Evolution Model (GloGEM) is coupled with the PCRaster GLOBal Water Balance model, version 2.0 (PCR-GLOBWB 2), using the eWa-terCycle platform. For the period 2001-2012, the coupled model is evaluated against the uncoupled PCR-GLOBWB 2 in 25 large-scale (> 50 000 km 2), glacierized basins. The coupled model produces higher runoff estimates across all basins and throughout the melt season. In summer, the runoff differences range from 0.07 % for weakly glacier-influenced basins to 252 % for strongly glacier-influenced basins. The difference can primarily be explained by PCR-GLOBWB 2 not accounting for glacier flow and glacier mass loss, thereby causing an underestimation of glacier runoff. The coupled model performs better in reproducing basin runoff observations mostly in strongly glacier-influenced basins, which is where the coupling has the most impact. This study underlines the importance of glacier representation in global hydrological models and demonstrates the potential of coupling a global hydrological model with a global glacier model for better glacier representation and runoff predictions in glacier-ized basins.
Tracer-aided hydrological models integrating water isotope modules into the
simulation of runoff generation are useful tools to reduce uncertainty of
hydrological modeling in cold basins that are featured by complex runoff
processes and multiple runoff components. However, there is little guidance
on the strategy of field water sampling for isotope analysis to run
tracer-aided hydrological models, which is especially important for large
mountainous basins on the Tibetan Plateau (TP) where field water sampling
work is highly costly. This study conducted a set of numerical experiments
based on the THREW-T (Tsinghua Representative Elementary Watershed -
Tracer-aided version) model to evaluate the reliance of the tracer-aided
modeling performance on the availability of site measurements of water
isotope in the Yarlung Tsangpo river (YTR) basin on the TP. Data conditions
considered in the numerical experiments included the availability of glacier meltwater isotope measurement, quantity of site measurements of
precipitation isotope, and the variable collecting strategies for stream
water samples. Our results suggested that (1) in high-mountain basins where
glacier meltwater samples for isotope analysis are not available, estimating glacier meltwater isotope by an offset parameter from the precipitation isotope is a feasible way to force the tracer-aided hydrological model. Using a set of glacier meltwater δ18O that were 2 ‰–9 ‰ lower than the mean precipitation δ18O resulted in only small changes in the model performance and the quantifications of contributions of runoff components (CRCs, smaller than 5 %) to streamflow in the YTR basin. (2) The strategy of field sampling for site precipitation to correct the global gridded isotope product of isoGSM (isotope-incorporated global spectral model) for model forcing should be carefully designed. Collecting precipitation samples at sites falling in the same altitude tends to be worse at representing the ground pattern of precipitation δ18O over the basin than collecting precipitation samples from sites in a range of altitudes. (3) Collecting weekly stream water samples at multiple sites in the wet and warm seasons is the optimal strategy for calibrating and evaluating a tracer-aided hydrological model in the YTR basin. It is highly recommended to increase the number of stream water sampling sites rather than spending resources on extensive sampling of stream water at a sole site for multiple years. These results provide important implications for collecting site measurements of water isotopes for running tracer-aided hydrological models to improve quantifications of CRCs in high-mountain basins.
Precipitation is one of the most important atmospheric inputs to hydrological models. However, existing precipitation datasets for the Third Pole (TP) basins show large discrepancies in precipitation magnitudes and spatiotemporal patterns, which poses a great challenge to hydrological simulations in the TP basins. In this study, a gridded (10 km × 10 km) daily precipitation dataset is constructed through a random-forest-based machine learning algorithm (RF algorithm) correction of the ERA5 precipitation estimates based on 940 gauges in 11 upper basins of TP for 1951–2020. The dataset is evaluated by gauge observations at point scale and is inversely evaluated by the Variable Infiltration Capacity (VIC) hydrological model linked with a glacier melt algorithm (VIC-Glacier). The corrected ERA5 (ERA5_cor) agrees well with gauge observations after eliminating the severe overestimation in the original ERA5 precipitation. The corrections greatly reduce the original ERA5 precipitation estimates by 10%–50% in 11 basins of the TP and present more details on precipitation spatial variability. The inverse hydrological model evaluation demonstrates the accuracy and rationality, and we provide an updated estimate of runoff components contribution to total runoff in seven upper basins in the TP based on the VIC-Glacier model simulations with the ERA5_cor precipitation. This study provides good precipitation estimates with high spatiotemporal resolution for 11 upper basins in the TP, which are expected to facilitate the hydrological modeling and prediction studies in this high mountainous region.
Significance Statement
The Third Pole (TP) is the source of water to the people living in the areas downstream. Precipitation is the key driver of the terrestrial hydrological cycle and the most important atmospheric input to land surface hydrological models. However, none of the current precipitation data are equally good for all the TP basins because of high variabilities in their magnitudes and spatiotemporal patterns, posing a great challenge to the hydrological simulation. Therefore, in this study, a gridded daily precipitation dataset (10 km × 10 km) is reconstructed through a random-forest-based machine learning algorithm correction of ERA5 precipitation estimates based on 940 gauges in 11 TP basins for 1951–2020. The data eliminate the severe overestimation of original ERA5 precipitation estimates and present more reasonable spatial variability, and also exhibit a high potential for hydrological application in the TP basins. This study provides long-term precipitation data for climate and hydrological studies and a reference for deriving precipitation in high mountainous regions with complex terrain and limited observations.
Past studies on concentration‐discharge (C‐Q) relationships have focused on short‐term or low‐temporal resolution data. While advancing understanding of catchment processes, these studies provided limited insight on catchment response over time or to climate change. Using 15 solutes from 1992‐2015 at Sleepers River Research Watershed, Vermont, we compared C‐Q relationships over decades, years, and seasons to elucidate controls on stream chemical variation. We applied end‐member mixing analysis (EMMA) to identify solute sources and flow path routing. EMMA identified three end‐members: near‐surface runoff (NSR), riparian groundwater, and hillslope hollow groundwater. Shifting mixing proportions of these end‐members accounted for the temporal variability of conservative (no chemical reaction en route from source to stream) solutes in streamflow. For example, an increase in NSR fraction, typical of high flow, caused flushing (increased concentrations) of NO3‐, DOC, Al, and Fe, which were greatest in NSR, dilution of specific conductance and base cation, SO42‐, Si, Sr, Ba, and Mn concentrations, which were greatest in the two groundwater end‐members. This behavior is reflected in the b‐coefficient of the C‐Q relation (C=aQb), which indicates the strength of dilution (b < ‐0.1) and flushing (b > 0.1) effects. For conservative solutes, the b‐coefficient decreased significantly (p < 0.01) with an increase in the groundwater to NSR concentration ratio. Solutes that are conservative and have relatively constant concentrations in end‐members over time, showed consistent annual C‐Q patterns over years and decades. Furthermore, the strength of dilution or flushing was stronger during the snowmelt period, when the NSR fraction peaked, than during the dormant and growing seasons. With shorter snowmelt periods and snow to rain shifts, the flushing or dilution power of snowmelt runoff will weaken and alter catchment response to climate change. These insights provide more tools for the interpretation of catchment processes and responses to climate change. This article is protected by copyright. All rights reserved.
Precipitation retrieval is a challenging topic, especially in high latitudes (HL), and current precipitation products face ample challenges over these regions. This study investigates the potential of the Advanced Very High-Resolution Radiometer (AVHRR) for snowfall retrieval in HL using CloudSat radar information and machine learning (ML). With all the known limitations, AVHRR observations should be considered for HL snowfall retrieval because (1) AVHRR data have been continuously collected for about four decades on multiple platforms with global coverage, and similar observations will likely continue in the future; (2) current passive microwave satellite precipitation products have several issues over snow and ice surfaces; and (3) good coincident observations between AVHRR and CloudSat are available for training ML algorithms. Using ML, snowfall rate was retrieved from AVHRR’s brightness temperature and cloud probability, as well as auxiliary information provided by numerical reanalysis. The results indicate that the ML-based retrieval algorithm is capable of detection and estimation of snowfall with comparable or better statistical scores than those obtained from the Atmospheric Infrared Sounder (AIRS) and two passive microwave sensors contributing to the Global Precipitation Measurement (GPM) mission constellation. The outcomes also suggest that AVHRR-based snowfall retrievals are spatially and temporally reasonable and can be considered as a quantitatively useful input to the merged precipitation products that require frequent sampling or long-term records.
This study performs a comparison of two model calibration/validation approaches and their influence on future hydrological projections under climate change by employing two climate scenarios (RCP2.6 and 8.5) projected by four global climate models. Two hydrological models (HMs), snowmelt runoff model + glaciers and variable infiltration capacity model coupled with a glacier model, were used to simulate streamflow in the highly snow and glacier melt–driven Upper Indus Basin. In the first (conventional) calibration approach, the models were calibrated only at the basin outlet, while in the second (enhanced) approach intermediate gauges, different climate conditions and glacier mass balance were considered. Using the conventional and enhanced calibration approaches, the monthly Nash-Sutcliffe Efficiency (NSE) for both HMs ranged from 0.71 to 0.93 and 0.79 to 0.90 in the calibration, while 0.57–0.92 and 0.54–0.83 in the validation periods, respectively. For the future impact assessment, comparison of differences based on the two calibration/validation methods at the annual scale (i.e. 2011–2099) shows small to moderate differences of up to 10%, whereas differences at the monthly scale reached up to 19% in the cold months (i.e. October–March) for the far future period. Comparison of sources of uncertainty using analysis of variance showed that the contribution of HM parameter uncertainty to the overall uncertainty is becoming very small by the end of the century using the enhanced approach. This indicates that enhanced approach could potentially help to reduce uncertainties in the hydrological projections when compared to the conventional calibration approach.
Wildfire is a major concern worldwide and particularly in Australia. The 2019-2020 wildfires in Australia became historically significant as they were widespread and extremely severe. Linking climate and vegetation settings to wildfires can provide insightful information for wildfire prediction, and help better understand wildfires behavior in the future. The goal of this research was to examine the relationship between the recent wildfires, various hydroclimatological variables, and satellite-retrieved vegetation indices. The analyses performed here show the uniqueness of the 2019-2020 wildfires. The near-surface air temperature from December 2019 to February 2020 was about 1 • C higher than the 20-year mean, which increased the evaporative demand. The lack of precipitation before the wildfires, due to an enhanced high-pressure system over southeast Australia, prevented the soil from having enough moisture to supply the demand, and set the stage for a large amount of dry fuel that highly favored the spread of the fires.
Abstract Accurate quantification of snowfall rate from space is important but has remained difficult. Four years (2007–2010) of NOAA‐18 Microwave Humidity Sounder (MHS) data are trained and tested with snowfall estimates from coincident CloudSat Cloud Profiling Radar (CPR) observations using several machine learning methods. Among the studied methods, random forest using MHS (RF‐MHS) is found to be the best for both detection and estimation of global snowfall. The RF‐MHS estimates are tested using independent years of coincident CPR snowfall estimates and compared with snowfall rates from Modern‐Era Retrospective analysis for Research and Applications Version 2 (MERRA‐2), Atmospheric Infrared Sounder (AIRS), and MHS Goddard Profiling Algorithm (GPROF). It was found that RF‐MHS algorithm can detect global snowfall with approximately 90% accuracy and a Heidke skill score of 0.48 compared to independent CloudSat samples. The surface wet bulb temperatures, brightness temperatures at 190 GHz, and 157 GHz channels are found to be the most important features to delineate snowfall areas. The RF‐MHS retrieved global snowfall rates are well compared with CPR estimates and show generally better statistics than MERRA‐2, AIRS, and GPROF products. A case study over the United States verifies that the RF‐MHS estimated snowfall agrees well with the ground‐based National Center for Environmental Prediction (NCEP) Stage‐IV and MERRA‐2 product, whereas a relatively large underestimation is observed with the current GPROF product (V05). MHS snowfall estimated based on RF algorithm, however, shows some underestimation over cold and snow‐covered surfaces (e.g., Greenland, Alaska, and northern Russia), where improvements through new sensors or retrieval techniques are needed.
Employing a fully distributed hydrological model of SPHY (spatial processes in hydrology), we assessed the future water
availability from a highly glacierized basin of Hunza in the western Karakoram under plausible climates as projected by the
representative concentration pathways (RCPs). We successfully calibrate and validate the SPHY model for the periods 1994–
1997 and 1997–2000 respectively using three high-altitude representative meteorological stations from the Water and Power
Development Authority (WAPDA), Pakistan. Then, we run the model for near- (2007–2036), mid- (2037–2066), and far-future
(2067–2096) climate projections under three different RCP scenario, i.e., RCP2.6, RCP4.5, and RCP8.5. Each scenario includes
four high-resolution (~ 50 km) climate experiments that are obtained from dynamically downscaling the Coupled Model Intercomparison
Project Phase 5 (CMIP5) experiments under the framework of the Coordinated Regional Climate Downscaling
Experiments (CORDEX) for South Asia. The SPHY model projects a substantial increase in the ensemble mean discharges
throughout the 21st century under all RCP scenarios. Such an increase is dominated by the enhanced glacier melt contribution
under the high warming scenario of RCP8.5. Besides featuring a declining trend, snowmelt contribution will also remain higher
than that of the historical period throughout the 21st century and under all RCPs. Our flow duration curve analysis suggests that
high and median flows are projected to increase while low flows are projected to decrease in the future. These findings provide
invaluable insights into the uncertainty spectrum of the water availability from the western
Glaciers are essential for downstream water resources. Hydrological modeling is necessary for a better understanding and for future projections of the water resources in these rapidly changing systems, but modeling glacierized catchments is especially challenging. Here we review a wealth of glacio‐hydrological modeling studies (145 publications) in catchments around the world. Major model challenges include a high uncertainty in the input data, mainly precipitation, due to scarce observations. Consequently, the risk of wrongly compensating input with model errors in competing snow and ice accumulation and melt process parameterization is particularly high. Modelers have used a range of calibration and validation approaches to address this issue. The review revealed that while a large part (~35%) of the reviewed studies used only streamflow data to evaluate model performances, most studies (~50%) have used additional data related to snow and glaciers to constrain model parameters. These data were employed in a variety of calibration strategies, including stepwise and multi‐signal calibration. Although the primary aim of glacio‐hydrological modeling studies is to assess future climate change impacts, long‐term changes have rarely been taken into account in model performance evaluations. Overall, a more precise description of which data are used how for model evaluation would facilitate the interpretation of the simulation results and their uncertainty, which in turn would support water resources management. Moreover, there is a need for systematic analyses of calibration approaches to disentangle what works best and why. Addressing this need will improve our system understanding and model simulations of glacierized catchments.
This article is categorized under: Science of Water > Hydrological Processes
Science of Water > Methods
In contrast to widespread glacier retreat evidenced globally, glaciers in the Karakoram region have exhibited positive mass balances and general glacier stability over the past decade. Snow and glacier meltwater from the Karakoram and the western Himalayas, which supplies the Indus River Basin, provide an essential source of water to more than 215 million people, either directly, as potable water, or indirectly, through hydroelectric generation and irrigation for crops. This study focuses on water resources in the Upper Indus Basin (UIB) which combines the ranges of the Hindukush, Karakoram and Himalaya (HKH). Specifically, we focus on the Gilgit River Basin (GRB) to inform more sustainable water use policy at the sub-basin scale. We employ two degree-day approaches, the Spatial Processes in Hydrology (SPHY) and Snowmelt Runoff Model (SRM), to simulate runoff in the GRB during 2001-2012. The performance of SRM was poor during July and August, the period when glacier melt contribution typically dominates runoff. Consequently, SPHY outperformed SRM, likely attributable to SPHY's ability to discriminate between glacier, snow, and rainfall contributions to runoff during the ablation period. The average simulated runoff revealed the prevalent snowmelt contribution as 62%, followed by the glacier melt 28% and rainfall 10% in GRB. We also assessed the potential impact of climate change on future water resources, based on two Representative Concentration Pathways (RCP) (RCP 4.5 and RCP 8.5). We estimate that summer flows are projected to increase by between 5.6% and 19.8% due to increased temperatures of between 0.7 and 2.6 °C over the period 2039-2070. If realized, increased summer flows in the region could prove beneficial for a range of sectors, but only over the short to medium term and if not associated with extreme events. Long-term projections indicate declining water resources in the region in terms of snow and glacier melt.
The Aconcagua river basin (Chile, 32 • S) has suffered the effects of the megadrought over the last decade. The severe snowfall deficiency drastically modified the water supply to the catchment headwaters. Despite the recognized snowmelt contribution to the basin, an unknown streamflow buffering effect is produced by glacial, periglacial and groundwater inputs, especially in dry periods. Hence, each type of water source was characterized and quantified for each season, through the combination of stable isotope and ionic analyses as natural water tracers. The δ 18 O and electric conductivity were identified as the key parameters for the differentiation of each water source. The use of these parameters in the stable isotope mixing "simmr" model revealed that snowmelt input accounted 52% in spring and only 22-36% during the rest of the year in the headwaters. While glacial supply contributed up to 34%, both groundwater and periglacial exhibited a remarkable contribution around 20% with some seasonal variations. Downstream, glacial contribution averaged 15-20%, groundwater seasonally increased up to 46%, and periglacial input was surprisingly high (i.e., 14-21%). The different water sources contribution quantification over time for the Aconcagua River reported in this work provides key information for water security in this territory.
Glaciers are important freshwater storage systems in the Tianshan Mountains. Under the context of climate change, quantifying changes in glacier mass balance, the melt-season (June–September) runoff and its key runoff component (glacier runoff) is of importance for understanding the discharge composition and ensuring adequate management of water resources. In this study, the modified HBV-D (Hydrologiska Byrans Vattenbalansavdelning-D) hydrological model was used to simulate hydrological processes for a data-sparse glacierized watershed, the headwater catchment of Manas River basin (MRB) in the Tianshan Mountains. Meanwhile, the roles of three modified elements of HBV-D in simulating glacier dynamics are identified. Sequently, the glacier mass balance and runoff during 1984–2006 are reconstructed and their responses to climate change are investigated. The analysis showed (1) the snow/glacier melt method makes more contribution to improving the performance of HBV-D model in simulating historical change of glacier volume, followed by the glacier dynamic method. (2) The reconstructed mass balance follows a decreased trend in the MRB. The maximum accumulation of glacier mass balance occurs in June. Snowmelt over the surface of glacier and glacier melt reach peak in June and August, respectively. Furthermore, sensitivity experiments showed increased mass balance induced by a 10% increase in precipitation cannot compensate for the decreased mass balance due to a 1 °C temperature rise. (3) Significant contribution (about 41.5%) of runoff in glacierized area to the melt-season total runoff of the catchment is identified. Both the glacier runoff and its contribution to melt-season total runoff show increased trends during the simulation period. Compared with the melt-season mean temperature and annual precipitation over glaciers, the melt-season positive accumulated temperature over glaciers played the most important role in influencing changes in glacier runoff in MRB. The findings in this study are beneficial for implementing adaptive countermeasures for water resources management in the data-scarce glaciated high-mountainous region.
Tracer data have been successfully used for hydrograph separation in glacierized basins. However, in these basins uncertainties of the hydrograph separation are
large and are caused by the spatiotemporal variability in the tracer signatures of water sources, the uncertainty of water sampling, and
the mixing model uncertainty. In this study, we used electrical conductivity (EC) measurements and two isotope signatures (δ18O and
δ2H) to label the runoff components, including groundwater, snow and glacier meltwater, and rainfall, in a Central Asian glacierized
basin. The contributions of runoff components (CRCs) to the total runoff and the corresponding uncertainty were quantified by two mixing
approaches, namely a traditional end-member mixing approach (abbreviated as EMMA) and a Bayesian end-member mixing approach. The performance of the two
mixing approaches was compared in three seasons that are distinguished as the cold season, snowmelt season, and glacier melt season. The results show the following points. (1) The
Bayesian approach generally estimated smaller uncertainty ranges for the CRC when compared to the EMMA. (2) The Bayesian approach tended to be less
sensitive to the sampling uncertainties of meltwater than the EMMA. (3) Ignoring the model uncertainty caused by the isotope fractionation
likely led to an overestimated rainfall contribution and an underestimated meltwater share in the melt seasons. Our study provides the first
comparison of the two end-member mixing approaches for hydrograph separation in glacierized basins and gives insight into the application of
tracer-based mixing approaches in similar basins.
As glaciers adjust their size in response to climate
variations, long-term changes in meltwater production can be expected,
affecting the local availability of water resources. We investigate glacier
runoff in the period 1955–2016 in the Maipo River basin (4843 km2,
33.0–34.3∘ S, 69.8–70.5∘ W), in the semiarid Andes of Chile.
The basin contains more than 800 glaciers, which cover 378 km2 in total (inventoried
in 2000). We model the mass balance and runoff contribution of 26 glaciers
with the physically oriented and fully distributed TOPKAPI (Topographic Kinematic Approximation and Integration)-ETH
glacio-hydrological model and extrapolate the results to the entire basin.
TOPKAPI-ETH is run at a daily time step using several glaciological and
meteorological datasets, and its results are evaluated against streamflow
records, remotely sensed snow cover, and geodetic mass balances for the
periods 1955–2000 and 2000–2013. Results show that in 1955–2016 glacier mass balance had
a general decreasing trend as a basin average but also had differences between
the main sub-catchments. Glacier volume decreased by one-fifth (from
18.6±4.5 to 14.9±2.9 km3). Runoff from the initially
glacierized areas was 177±25 mm yr−1 (16±7 % of the
total contributions to the basin), but it shows a decreasing sequence of
maxima, which can be linked to the interplay between a decrease in
precipitation since the 1980s and the reduction of ice melt. Glaciers in the
Maipo River basin will continue retreating because they are not in
equilibrium with the current climate. In a hypothetical constant climate
scenario, glacier volume would reduce to 81±38 % of the year 2000
volume, and glacier runoff would be 78±30 % of the 1955–2016
average. This would considerably decrease the drought mitigation capacity of
the basin.
Glaciers and snow cover are important constituents of the surface of the Tibetan Plateau. The responses of these phenomena to global environmental changes are sensitive, rapid, and intensive due to the high altitudes and arid cold climate of the Tibetan Plateau. Based on multisource remote sensing data, including Landsat images, MOD10A2 snow product, ICESat, Cryosat‐2 altimetry data, and long‐term ground climate observations, we analyzed the dynamic changes of glaciers, snow melting, and lake in the Paiku Co basin using extraction methods for glaciers and lake, the degree‐day model, and the ice and lake volume method. The interaction among the climate, ice‐snow, and the hydrological elements in Paiku Co is revealed. From 2000 to 2018, the basin tended to be drier, and rainfall decreased at a rate of −3.07 mm/a. The seasonal temperature difference in the basin increased, the maximum temperature increased at a rate of 0.02°C/a, and the minimum temperature decreased at a rate of −0.06°C/a, which accelerated the melting from glaciers and snow at rates of 0.55 × 107 m3/a and 0.29 × 107 m3/a, respectively. The rate of contribution to the lake from rainfall, snow and glacier melted water was 55.6%, 27.7%, and 16.7%, respectively. In the past 18 years, the warmer and drier climate has caused the lake to shrink. The water level of the lake continued to decline at a rate of −0.02 m/a, and the lake water volume decreased by 4.85 × 108 m3 at a rate of −0.27 × 108 m3/a from 2000 to 2018. This evaluation is important for understanding how the snow and ice melting in the central Himalayas affect the regional water cycle. This article is protected by copyright. All rights reserved.
The impact of surface melt patterns and the Indian summer monsoon (ISM) is examined on the varying contributions of end member (snow, glacier ice and rain) to proglacial streamflow during the ablation period (June‐October) in the Chhota Shigri glaciated basin, western Himalaya. Isotopic seasonality observed in the catchment precipitation was generally reflected in surface runoff (supraglacial melt and proglacial stream), and shows a shift in major water source during the melt season. Isotopically correlated (δ18O‐ δD) high deuterium intercept in the surface runoff suggests that westerly precipitation acts as the dominant source, augmenting the other snow‐ and ice‐melt sources in the region. The end member contributions to the proglacial stream were quantified using a three‐component mixing. Overall, glacier ice melt is the major source of proglacial discharge. Snowmelt is the predominant source during the early ablation season (June) and the peak ISM period (August and September), whereas ice melt reaches a maximum in the peak melt period (July). The monthly contribution of rain is on the lower side and shows a steady rise and decline with onset and retreat of the monsoon. These results are persistent with the surface melt pattern observed in Chhota Shigri glacier, Upper Chandra basin (UCB), Moreover, the role of the ISM in Chhota Shigri glacier is unvarying to that observed in other glacierised catchments of Upper Ganga basin (UGB). Thus, this study augments the significant role of the ISM in glacier mass balance up to the boundary of the central‐western Himalayan glaciated region. This article is protected by copyright. All rights reserved.
Himalayan glaciers are the major source of fresh water supply to the Himalayan Rivers, which support the livelihoods of more than a billion people living in the downstream region. However, in the face of recent climate change, these glaciers might be vulnerable, and thereby become a serious threat to the future fresh water reserve. Therefore, special attention is required in terms of understanding moisture sources for precipitation over the Himalayan glaciers and the hydrograph components of streams and rivers flowing from the glacierized region. We have carried out a systematic study in one of the benchmark glaciers, "Sutri Dhaka" of the Chandra Basin, in the western Himalayas, to understand its hydrograph components, based on stable water isotopes (δ 18 O and δ 2 H) and field-based ablation measurements. Further, to decipher moisture sources for precipitation and its variability in the study region, we have studied stable water isotopes in precipitation samples (rain and snow), and performed a back-trajectory analysis of the air parcel that brings moisture to this region. Our results show that the moisture source for precipitation over the study region is mainly derived from the Mediterranean regions (>70%) by Western Disturbances (WDs) during winter (October-May) and a minor contribution (<20%) from the Indian Summer Monsoon (ISM) during summer season (June-September). A three-component hydrograph separation based on δ 18 O and d-excess provides estimates of ice (65 ± 14%), snowpack (15 ± 9%) and fresh snow (20 ± 5%) contributions, respectively. Our field-based specific ablation measurements show that ice and snow melt contributions are 80 ± 16% and 20 ± 4%, respectively. The differences in hydrograph component estimates are apparently due to an unaccounted snow contribution 'missing component' from the valley slopes in field-based ablation measurements, whereas the isotope-based hydrograph separation method accounts for all the components, and provides a basin integrated estimate. Therefore, we suggest that for similar types of basins where contributions of rainfall and groundwater are minimal, and glaciers are often inaccessible for frequent field measurements/observations, the stable isotope-based method could significantly add to our ability to decipher moisture sources and estimate hydrograph components.
Gridded datasets are of paramount importance to globally derive precipitation quantities for a multitude of scientific and practical applications. However, as most studies do not consider the impacts of temporal and spatial variations of included measurements in the utilized datasets, we conducted a quantitative assessment of the ability of several state of the art gridded precipitation products (CRU, GPCC Full Data Product, GPCC Monitoring Product, ERA-interim, ERA5, MERRA-2, MERRA-2 bias corrected, PERSIANN-CDR) to reproduce monthly precipitation values at climate stations in the Pamir mountains during two 15 year periods (1980–1994, 1998–2012) that are characterized by considerable differences in incorporated observation data. Results regarding the GPCC products illustrated a substantial and significant performance decrease with up to four times higher errors during periods with low observation inputs (1998–2012 with 2 stations on average per 124,000 km2) compared to periods with high quantities of regionally incorporated station data (1980–1994 with 14 stations on average per 124,000 km2). If independent stations were considered, the coefficient of efficiency indicated that only three of the gridded datasets (MERRA–2 bias corrected, GPCC, GPCC MP) performed better than the long term station mean for characterizing surface precipitation. Error patterns and magnitudes show that in complex terrain, evaluation of temporal and spatial variations of included observations is a prerequisite for using gridded precipitation products for scientific applications and to avoid overly optimistic performance assessments.
In a context of climate change and water demand growth, understanding the origin of water flows in the Himalayas is a key issue for assessing the current and future water resource availability and planning the future uses of water in downstream regions. Two of the main issues in the hydrology of high-altitude glacierized catchments are (i) the limited representation of cryospheric processes controlling the evolution of ice and snow in distributed hydrological models and (ii) the difficulty in defining and quantifying the hydrological contributions to the river outflow. This study estimates the relative contribution of rainfall, glaciers, and snowmelt to the Khumbu River streamflow (Upper Dudh Koshi, Nepal, 146 km2, 43 % glacierized, elevation range from 4260 to 8848 m a.s.l.) as well as the seasonal, daily, and sub-daily variability during the period 2012–2015 by using the DHSVM-GDM (Distributed Hydrological Soil Vegetation Model – Glaciers Dynamics Model) physically based glacio-hydrological model. The impact of different snow and glacier parameterizations was tested by modifying the snow albedo parameterization, adding an avalanche module, adding a reduction factor for the melt of debris-covered glaciers, and adding a conceptual englacial storage. The representation of snow, glacier, and hydrological processes was evaluated using three types of data (MODIS satellite images, glacier mass balances, and in situ discharge measurements). The relative flow components were estimated using two different definitions based on the water inputs and contributing areas. The simulated hydrological contributions differ not only depending on the used models and implemented processes, but also on different definitions of the estimated flow components. In the presented case study, ice melt and snowmelt contribute each more than 40 % to the annual water inputs and 69 % of the annual stream flow originates from glacierized areas. The analysis of the seasonal contributions highlights that ice melt and snowmelt as well as rain contribute to monsoon flows in similar proportions and that winter outflow is mainly controlled by the release from the englacial water storage. The choice of a given parametrization for snow and glacier processes, as well as their relative parameter values, has a significant impact on the simulated water balance: for instance, the different tested parameterizations led to ice melt contributions ranging from 42 % to 54 %. The sensitivity of the model to the glacier inventory was also tested, demonstrating that the uncertainty related to the glacierized surface leads to an uncertainty of 20 % for the simulated ice melt component.
The water-runoff in the plateau mountainous areas is mainly contributed by precipitation, snowmelt and glacial meltwater; the different runoff components result from different mechanism of runoff generation. Plateau mountainous areas have not only a unique hydrological cycle mechanism but also are sensitive to climate change. Glacier and snow meltwater in the plateau mountainous areas have a large proportion in runoff and are a main water resources for industrial, agricultural and domestic water use in the basin. Two commonly used model, HBV and SRM, were selected for the quantitative analysis of snowmelt runoff contribution and the hydrological response to climate change scenarios in the Nyang River Basin in the southeastern part of the Qinghai-Tibet Plateau. Based on the characteristics of the models, the HBV model was used to analyze the runoff composition, while the SRM model was used to analyze the runoff in climate change scenarios. The results showed that both models have a good performance in modeling the hydrological processes in the basin. The snow melts mainly concentrate in May, in the average annual precipitation, rainfall and snowfall accounted for 85% and 15%, respectively. From the results of sensitivity analysis, the increase in temperature would accelerate the melting of snow in April and May and turns the snowfall into rainfall in October. However, the change in precipitation mainly affects the runoff in July, August and September, when precipitation is dominated by rain. The results indicate that the timing of the effects of temperature and precipitation on the runoff process is different.
Change in glacier area in the Kuksu and Kunes river basins, which are tributaries to the internationally important Ile River, were assessed at two different time steps between 1962/63, 1990/93, and 2010/12. Overall, glaciers lost 191.3 ± 16.8 km2 or 36.9 ± 6.5% of the initial area. Glacier wastage intensified in the latter period: While in 1962/63–1990/93 glaciers were losing 0.5% a−1, in 1990/93–2010/12, they were losing 1.2% a−1. Streamflow of the Ile River and its tributaries do not exhibit statistically significant change during the vegetative period between May and September. Positive trends were observed in the Ile flow in autumn, winter, and early spring. By contrast, the calculation of the total runoff from the glacier surface (including snow and ice melt) using temperature-index method and runoff forming due to melting of multiyear ice estimated from changes in glacier volume at different time steps between the 1960s and 2010s, showed that their absolute values and their contribution to total river runoff declined since the 1980s. This change is attributed to a strong reduction in glacier area.
To study hydrological regime over Marshyangdi (area: 3006.77 km²) and Tamor River basins (area: 4005.22 km²), an integrated approach was performed in particular to emphasize glacio-hydrological model development. Glacio-hydrological degree-day model (GDM) version 1.0, a physical-based gridded glacio-hydrological model, developed on C-Sharp (C#) and Python-programming language is developed. GDM is calibrated for the period 2004–2007 for Marshyangdi River basin (MRB) and from 2001 to 2005 for Tamor River basin (TRB) with Nash–Sutcliffe Efficiency (NSE) of 0.81 and 0.64, respectively. Furthermore, the model is validated for the period 2008–2009 for MRB and from 2006 to 2010 for TRB with NSE of 0.84 and 0.68, respectively. The snow and ice melt contribution to total discharge in MRB during calibration period is found to be 12.3% and 11.2%, respectively, whereas, during validation period, it is 9.9% and 11.8%, respectively. In case of TRB, contribution during calibration period is found to be 14.5% and 7.3%, respectively, and during validation period 12.9% and 10.6%, respectively. The highest rate of increment in minimum temperature trend over TRB and MRB is 0.027 °C/year and 0.008 °C/year. In case of maximum temperature trend, both basins show an increment rate of 0.018 °C/year. The morphometric analysis shows low drainage densities and length of overland flows of 3.66 km and 3.73 km over MRB and TRB, respectively. In Representative Concentration Pathways (RCPs) 4.5 scenario for the period 2021–2050, an average decrease in simulated discharge as − 0.087 m³/year and − 0.366 m³/year for MRB and TRB, respectively, is seen.
The potential impact of glacier recession on river discharge from the Hunza river basin was estimated as an indicator for downstream changes in the Indus river system. The J2000 model was used to analyze the water balance in the basin and simulate the contribution of snow and ice melt to total discharge at present and under three scenarios of glacier recession. Precipitation was corrected using virtual weather stations created at a higher elevation and a precipitation gradient. Snowmelt from the whole basin contributed, on average, 45% of the total river discharge during the modeling period and 47% of the ice melt from the glacier area. Total ice melt declined by 55%, 81%, and 96% under scenarios of glacier recession to 4000, 4500, and 5000 masl, respectively. The contribution of ice melt to river discharge decreased to 29%, 14%, and 4% under the three scenarios, while total discharge from the Hunza river decreased by 28%, 40%, and 46%. The results suggest that glacier recession in the Hunza river basin could have serious implications for downstream water availability. Understanding melt contribution in the basin based on ongoing and projected future climatic change can play a crucial role in future water resource management.
Glaciers draining to the Hornsund basin (southern Spitsbergen, Svalbard) have experienced a significant retreat and mass volume loss over the last decades, increasing the input of freshwater into the fjord. An increase in freshwater input can influence fjord hydrology, hydrodynamics, sediment flux and biota, especially in a changing climate. Here, we describe the sources of freshwater supply to the fjord based on glaciological and meteorological data from the period 2006 to 2015. The average freshwater input from land to the Hornsund bay is calculated as 2517 ± 82 Mt a−1, with main contributions from glacier meltwater runoff (986 Mt a−1; 39%) and frontal ablation of tidewater glaciers (634 Mt a−1; 25%). Tidewater glaciers in Hornsund lose ca. 40% of their mass by frontal ablation. The terminus retreat component accounts for ca. 30% of the mass loss by frontal ablation, but it can vary between 17% and 44% depending on oceanological, meteorological and geomorphological factors. The contribution of the total precipitation over land excluding winter snowfall (520 Mt a−1), total precipitation over the fjord area (180 Mt a−1) and melting of the snow cover over unglaciated areas (197 Mt a−1) to the total freshwater input appear to be small: 21%, 7% and 8%, respectively.
The flow regimes of glacier-fed rivers are sensitive to climate change due to
strong climate–cryosphere–hydrosphere interactions. Previous modelling
studies have projected changes in annual and seasonal flow magnitude but
neglect other changes in river flow regime that also have socio-economic and
environmental impacts. This study employs a signature-based analysis of
climate change impacts on the river flow regime for the deglaciating Virkisá
river basin in southern Iceland. Twenty-five metrics (signatures) are derived from 21st century projections of river flow time series to evaluate changes in
different characteristics (magnitude, timing and variability) of river flow
regime over sub-daily to decadal timescales. The projections are produced by
a model chain that links numerical models of climate and glacio-hydrology.
Five components of the model chain are perturbed to represent their
uncertainty including the emission scenario, numerical climate model,
downscaling procedure, snow/ice melt model and runoff-routing model. The
results show that the magnitude, timing and variability of glacier-fed river
flows over a range of timescales will change in response to climate change.
For most signatures there is high confidence in the direction of change, but
the magnitude is uncertain. A decomposition of the projection uncertainties
using analysis of variance (ANOVA) shows that all five perturbed model chain
components contribute to projection uncertainty, but their relative
contributions vary across the signatures of river flow. For example, the
numerical climate model is the dominant source of uncertainty for projections
of high-magnitude, quick-release flows, while the runoff-routing model is
most important for signatures related to low-magnitude, slow-release flows.
The emission scenario dominates mean monthly flow projection uncertainty, but
during the transition from the cold to melt season (April and May) the
snow/ice melt model contributes up to 23 % of projection uncertainty.
Signature-based decompositions of projection uncertainty can be used to
better design impact studies to provide more robust projections.
Energy budget-based distributed modeling at high-altitude glacio-nival watersheds is essential to accurately describe hydrological processes and quantify the flow rates. In this study, SNOWPACK model and its distributed version Alpine3D are applied for the first time in Pakistan to simulate the runoff response of a high altitude glaciated catchment. The basic aim was to explore the feasibility of this modeling system and its future applications in the region. Final results demonstrated satisfactory performance of the model between measured and modeled discharges with Nash-Sutcliff Efficiency of 0.54. However, total simulated flow volume differs only 1.3 times as compared to measured discharge of the lake, located at the glacier snout. Flow composition analysis revealed that the runoff regime of the study site is strongly influenced by the snow and glacier melt runoff representing 53% snowmelt and 38% glacier melt contribution. Low model efficiency has been observed during glacier melting season due to inaccurate wind speed distribution and biased input met-data. It is concluded that high performance of this model can be achieved if the model is optimized over the catchment similar to the study site provided with long term data sets. This study leaves a firm foundation for the potential application of a highly accurate distributed energy balance model in the entire Karakoram and Himalaya region to understand the melt dynamics of such a rugged terrain glacier rich mountains.
Understanding glacio-hydrological processes is crucial to water resources management, especially under increasing global warming. However, data scarcity makes it challenging to quantify the contribution of glacial melt to streamflow in highly glacierized catchments such as those in the Tienshan Mountains. This study aims to investigate the glacio-hydrological processes in the SaryDjaz-Kumaric River (SDKR) basin in Central Asia by integrating a degree-day glacier melt algorithm into the macro-scale hydrological Soil and Water Assessment Tool (SWAT) model. To deal with data scarcity in the alpine area, a multi-objective sensitivity analysis and a multi-objective calibration procedure were used to take advantage of all aspects of streamflow. Three objective functions, i.e., the Nash–Sutcliffe efficiency coefficient of logarithms (LogNS), the water balance index (WBI), and the mean absolute relative difference (MARD), were considered. Results show that glacier and snow melt-related parameters are generally sensitive to all three objective functions. Compared to the original SWAT model, simulations with a glacier module match fairly well to the observed streamflow, with the Nash–Sutcliffe efficiency coefficient (NS) and R2 approaching 0.82 and an absolute percentage bias less than 1%. Glacier melt contribution to runoff is 30–48% during the simulation period. The approach of combining multi-objective sensitivity analysis and optimization is an efficient way to identify important hydrological processes and recharge characteristics in highly glacierized catchments.
Climate-impact projections are subject to uncertainty arising from climate models, greenhouse gases emission scenarios, bias correction and downscaling methods (BCDS), and the impact models. We studied the effects of hydrological model parameterization and regionalization (HM-P and HM-R) on the cascade of uncertainty. We developed a new, widely-applicable approach that improves our understanding of how HM-P and HM-R along with other uncertainty drivers contribute to the overall uncertainty in climate-impact projections. We analyzed uncertainties arising from general circulation models (GCMs), representative concertation pathways, BCDS, evapotranspiration calculation methods, and specifically HM-P and HM-R. We used the Soil and Water Assessment Tool, a semi-physical process-based hydrologic model with a high capability of parameterization, to project blue and green water resources for historical (1983–2007), near future (2010–2035) and far future (2040–2065) periods in Alberta, a western province of Canada. We developed an Analysis of Variance (ANOVA)-Sequential Uncertainty Fitting Program approach, to decompose the overall uncertainty into contributions of single drivers using the projected blue and green water resources. The monthly analyses of projected water resources showed that HM-P and HM-R contribute 21–51% and 15–55% to the blue water, and 20–48% and 15–50% to the green water overall uncertainty in near future and far future, respectively. Overall, we found that in spring and summer seasons uncertainty arising from HM-P and HM-R dominates other uncertainty sources, e.g. GCMs. We also found that global climate models are another dominant source of uncertainty in future impact projections.
Climate models predict amplified warming at high elevations in low latitudes,
making tropical glacierized regions some of the most vulnerable hydrological
systems in the world. Observations reveal decreasing streamflow due to
retreating glaciers in the Andes, which hold 99 % of all tropical
glaciers. However, the timescales over which meltwater contributes to
streamflow and the pathways it takes – surface and subsurface – remain
uncertain, hindering our ability to predict how shrinking glaciers will
impact water resources. Two major contributors to this uncertainty are the
sparsity of hydrologic measurements in tropical glacierized watersheds and
the complication of hydrograph separation where there is year-round glacier
melt. We address these challenges using a multi-method approach that employs
repeat hydrochemical mixing model analysis, hydroclimatic time series
analysis, and integrated watershed modeling. Each of these approaches
interrogates distinct timescale relationships among meltwater, groundwater,
and stream discharge. Our results challenge the commonly held conceptual
model that glaciers buffer discharge variability. Instead, in a subhumid
watershed on Volcán Chimborazo, Ecuador, glacier melt drives nearly all
the variability in discharge (Pearson correlation coefficient of 0.89 in
simulations), with glaciers contributing a broad range of 20 %–60 %
or wider of discharge, mostly (86 %) through surface runoff on hourly
timescales, but also through infiltration that increases annual groundwater
contributions by nearly 20 %. We further found that rainfall may enhance
glacier melt contributions to discharge at timescales that complement glacier
melt production, possibly explaining why minimum discharge occurred at the
study site during warm but dry El Niño conditions, which typically
heighten melt in the Andes. Our findings caution against extrapolations from
isolated measurements: stream discharge and glacier melt contributions in
tropical glacierized systems can change substantially at hourly to
interannual timescales, due to climatic variability and surface to subsurface
flow processes.
We present a field‐data rich modelling analysis to reconstruct the climatic forcing, glacier response and runoff generation from a high elevation catchment in central Chile over the period 2000‐2015, to provide insights into the differing contributions of debris‐covered and debris‐free glaciers under current and future changing climatic conditions. Model simulations with the physically‐based glacio‐hydrological model TOPKAPI‐ETH reveal a period of neutral or slightly positive mass balance between 2000‐2010, followed by a transition to increasingly large annual mass losses, associated with a recent mega drought. Mass losses commence earlier, and are more severe, for a heavily debris‐covered glacier, most likely due to its strong dependence on snow avalanche accumulation, which has declined in recent years. Catchment runoff shows a marked decreasing trend over the study period, but with high interannual variability directly linked to winter snow accumulation, and high contribution from ice melt in dry periods and drought conditions. The study demonstrates the importance of incorporating local‐scale processes such as snow avalanche accumulation and spatially variable debris thickness, in understanding the responses of different glacier types to climate change. We highlight the increased dependency of runoff from high Andean catchments on the diminishing resource of glacier ice during dry years.
Flooding, one of the most serious natural disasters, poses a significant threat to people’s lives and property. At present, the forecasting method uses simple snowmelt accumulation and has certain regional restrictions that limit the accuracy and timeliness of flood simulation and prediction. In this paper, the influence of accumulated temperature (AT) and maximum temperature (MT) on snow melting was considered in order to (1) reclassify the precipitation categories of the watershed using a separation algorithm of rain and snow that incorporates AT and MT, and (2) develop a new snow-melting process utilizing the algorithm in the Soil and Water Assessment Tool Model (SWAT) by considering the effects of AT and MT. The SWAT model was used to simulate snowmelt and flooding in the Tizinafu River Basin (TRB). We found that the modified SWAT model increased the value of the average flood peak flow by 43%, the snowmelt amounts increased by 45%, and the contribution of snowmelt to runoff increased from 44.7% to 54.07%. In comparison, we concluded the snowmelt contribution to runoff, flood peak performance, flood process simulation, model accuracy, and time accuracy. The new method provides a more accurate simulation technique for snowmelt floods and flood simulation.
Across High Asia, the amount, timing, and spatial patterns of snow and ice melt play key roles in providing water for downstream irrigation, hydropower generation, and general consumption. The goal of this paper is to distinguish the specific contribution of seasonal snow versus glacier ice melt in the major basins of High Mountain Asia: Ganges, Brahmaputra, Indus, Amu Darya, and Syr Darya. Our methodology involves the application of MODIS-derived remote sensing products to separately calculate daily melt outputs from snow and glacier ice. Using an automated partitioning method, we generate daily maps of (1) snow over glacier ice, (2) exposed glacier ice, and (3) snow over land. These are inputs to a temperature index model that yields melt water volumes contributing to river flow. Results for the five major High Mountain Asia basins show that the western regions are heavily reliant on snow and ice melt sources for summer dry season flow when demand is at a peak, whereas monsoon rainfall dominates runoff during the summer period in the east. While uncertainty remains in the temperature index model applied here, our approach to partitioning melt from seasonal snow and glacier ice is both innovative and systematic and more constrained than previous efforts with similar goals.
The glacierized Tien Shan – Pamir – Karakoram mountain complex supplies water to about 42 million people. Yet, the knowledge about future glacial runoff in response to future climate is limited. Here, we address this issue using a hydrological model, that includes the three components of glacial runoff: ice melt, snowmelt and the runoff of rainfall over ice. The model is forced by climate projections of the CMIP5 models. We find that the three components exhibit different long-term trajectories, sometimes opposite in sign to the long-term trend in glacier impacts. For the eastern slope basins, streamflow is projected to increase by 28% (ranging from 9 to 44%, from climate model variation (CMV)) by the late 21st century, under the representative concentration pathway, RCP8.5. Ice melt contributes 39% (25 to 65%, CMV) of the total streamflow increase. However, streamflow from the western slopes is projected to decrease by 5% (−24 to 16%, CMV), due to the smaller contribution of ice melt, less precipitation and higher evapotranspiration. Increasing water supply from the eastern slopes suggests more water availability for currently degraded downstream ecosystems in the Xinjiang province of China, while the likely decreasing streamflow in Central Asian rivers on the western slopes indicates new regulations will be needed.
The heavily debris-covered Inylchek glaciers in the central Tian Shan are the largest glacier system in the Tarim catchment. It is assumed that almost 50% of the discharge of Tarim River are provided by glaciers. For this reason, climatic changes, and thus changes in glacier mass balance and glacier discharge are of high impact for the whole region. In this study, a conceptual hydrological model able to incorporate discharge from debris-covered glacier areas is presented. To simulate glacier melt and subsequent runoff in the past (1970/1971–1999/2000) and future (2070/2071–2099/2100), meteorological input data were generated based on ECHAM5/MPI-OM1 global climate model projections. The hydrological model HBV-LMU was calibrated by an automatic calibration algorithm using runoff and snow cover information as objective functions. Manual fine-tuning was performed to avoid unrealistic results for glacier mass balance. The simulations show that annual runoff sums will increase significantly under future climate conditions. A sensitivity analysis revealed that total runoff does not decrease until the glacier area is reduced by 43%. Ice melt is the major runoff source in the recent past, and its contribution will even increase in the coming decades. Seasonal changes reveal a trend towards enhanced melt in spring, but a change from a glacial-nival to a nival-pluvial runoff regime will not be reached until the end of this century.
Hydrologiska Byrans Vattenbalansavdeling (HBV) Light model was used to evaluate the performance of the model in response to climate change in the snowy and glaciated catchment area of Hunza River Basin. The study aimed to understand the temporal variation of streamflow of Hunza River and its contribution to Indus River System (IRS). HBV model performed fairly well both during calibration (R²=0.87, Reff=0.85, PBIAS=−0.36) and validation (R²=0.86, Reff=0.83, PBIAS=−13.58) periods on daily time scale in the Hunza River Basin. Model performed better on monthly time scale with slightly underestimated low flows period during both calibration (R²=0.94, Reff=0.88, PBIAS=0.47) and validation (R²=0.92, Reff=0.85, PBIAS=15.83) periods. Simulated streamflow analysis from 1995–2010 unveiled that the average percentage contribution of snow, rain and glacier melt to the streamflow of Hunza River is about 16.5%, 19.4% and 64% respectively. In addition, the HBV-Light model performance was also evaluated for prediction of future streamflow in the Hunza River using future projected data of three General Circulation Model (GCMs) i.e. BCC-CSM1.1, CanESM2, and MIROCESM under RCP2.6, 4.5 and 8.5 and predictions were made over three time periods, 2010–2039, 2040–2069 and 2070–2099, using 1980–2010 as the control period. Overall projected climate results reveal that temperature and precipitation are the most sensitive parameters to the streamflow of Hunza River. MIROC-ESM predicted the highest increase in the future streamflow of the Hunza River due to increase in temperature and precipitation under RCP4.5 and 8.5 scenarios from 2010–2099 while predicted slight increase in the streamflow under RCP2.6 during the start and end of the 21th century. However, BCCCSM1.1 predicted decrease in the streamflow under RCP8.5 due to decrease in temperature and precipitation from 2010–2099. However, CanESM2 predicted 22%-88% increase in the streamflow under RCP4.5 from 2010–2099. The results of this study could be useful for decision making and effective future strategic plans for water management and their sustainability in the region.
Compared with arctic and subarctic catchments, our knowledge about the hydrological functions of glaciers and porous aquifers is still limited for the partly glacierized alpine-gorge headwaters in the Qinghai-Tibet Plateau. Here we examine the impact of glacial and groundwater storage on the variability of warm-season (June to September) discharge from the Hulugou catchment, an alpine-gorge headwater with 3% glacial coverage, by quantifying the timing and magnitude of contributions of glacier-snow meltwater, baseflow, and rainwater to streamflow using a three-component hydrograph separation model. It is found that baseflow was the largest component (55 ± 2%) of warm-season streamflow while glacier-snow meltwater also contributed significantly (30 ± 10%) despite of the very low glacial coverage. We suggest that the water flowing out of glaciers was mainly supplied by the melting short- and intermediate-term storages (i.e., snow over glaciers), which led to the high meltwater contribution to streams during the warm season and the high peaks of meltwater discharge following heavy precipitation events. The porous aquifers in piedmont plain may serve as major reservoirs that store a growing body of groundwater during the warm season, which explains the general increasing trend of baseflow contribution during this period. The moraine and talus deposits in high mountains, by contrast, allow groundwater to pass through them quickly and therefore being responsible for the obvious responses of baseflow contribution amount to heavy rainfall events. Our findings suggest that small mountain glaciers and porous aquifers may play a greater role than expected in hydrological regulation in the alpine-gorge catchments of northeastern Qinghai-Tibet Plateau.
The Pacific Northwest is the most highly glacierized region in the conterminous United States (858 glaciers; 466 km²). These glaciers have displayed ubiquitous patterns of retreat since the 1980s mostly in response to warming air temperatures. Glacier melt provides water for downstream uses including agricultural water supply, hydroelectric power generation, and for ecological systems adapted to cold reliable streamflow. While changes in glacier area have been studied within the region over an extended period of time, the hydrologic consequences of these changes are not well defined. We applied a high-resolution glacio-hydrological model to predict glacier mass balance, glacier area, and river discharge for the period 1960–2099. Six river basins across the region were modeled to characterize the regional hydrological response to glacier change. Using these results, we generalized past and future glacier area change and discharge across the entire Pacific Northwest using a k-means cluster analysis. Results show that the rate of regional glacier recession will increase, but the runoff from glacier melt and its relative contribution to streamflow display both positive and negative trends. In high-elevation river basins enhanced glacier melt will buffer strong declines in seasonal snowpack and decreased late summer streamflow, before the glaciers become too small to support streamflow at historic levels later in the 21st century. Conversely, in lower-elevation basins, smaller snowpack and the shrinkage of small glaciers result in continued reductions in summer streamflow.
Glacier changes are driven by glacier melt, which in turn affects streamflow. This paper describes an accounting scheme for glacier area change distribution across elevation profiles for application in the glacier module of the Soil and Water Assessment Tool (SWAT) model. In addition to volume-area scaling relationship in the module, the paper introduced volume-length scaling relations to estimate changing glacier terminus and update glacier area changes between equilibrium line altitude (ELA) and the terminus. The improved scheme was used in the nested Urumqi Glacier No. 1 catchment and Urumqi River Basin in Tienshan Mountains, China. Comparison of the simulated and observed data suggested that the new scheme accurately reproduced the length and area changes of Glacier No. 1. The contributions of glacier melt and ice melt to runoff were estimated at 71% and 38% for Glacier No. 1 Hydrological Station and 11.1% and 5.8% for Yingxiongqiao Hydrological Station, respectively. This helped to better interpret long-term monitored glacio-hydrological processes of Glacier No. 1 and the variation of glacier melt contribution to streamflow at the catchment scale.
Snowmelt is a major driver of the hydrological cycle in cold regions, as such, its accurate representation in hydrological models is key to both regional snow depth and streamflow prediction. The choice of a proper method for snowmelt representation is often improvised; however, a thorough characterization of uncertainty in such process representations particularly in the context of climate change has remained essential. To fill this gap, this study revisits and characterizes performance and uncertainty around the two general approaches to snow-melt representation, namely Energy-Balance Modules (EBMs) and Temperature-Index Modules (TIMs). To account for snow depth simulation and projection, two common Snow Density formulations (SNDs) are implemented that map snow water equivalent (SWE) to snow depth. The major research questions we address are twofold. First, we examine the dominant controls of uncertainty in snow depth and streamflow simulations across scales and in different climates. Second, we evaluate the cascade of uncertainty of snow depth projections resulting from impact model parameters, greenhouse gas emission scenarios, climate models and their internal variability, and downscaling processes. We enable the Soil and Water Assessment Tool (SWAT) by coupling EBM, TIM, and two SND modules for examination of different snowmelt representation methods, and Analysis of Variance (ANOVA) for uncertainty decomposition and attribution. These analyses are implemented in mountainous , foothill, and plain regions in a large snow-dominated watershed in western Canada. Results show, rather counter-intuitively, that the choice of SND is a major control of performance and uncertainty of snow depth simulation rather than the choice between TIMs and EBMs and of their uncertain parameters. Also, analysis of streamflow simulations suggest that EBMs generally overestimate streamflow on main tributaries. Finally, uncertainty decompositions show that parameter uncertainty related to snowmelt modules dominantly controls uncertainty in future snow depth projections under climate change, particularly in mountainous regions. However, in plain regions, the uncertainty contribution of model parameters becomes more variable with time and less dominant compared with the other sources of uncertainty. Overall, it is shown that the hydro-climatic and topographic conditions of different regions, as well as input data availability, have considerable effect on reproduction of snow depth, snowmelt and resulting streamflow, and on the share of different uncertainty sources when projecting regional snow depth.
The Mendoza River streamflow, South America (∼32°S), derives almost exclusively from winter snow precipitation falling in the Andes. Almost 70% of the water feeding the river originates in the Cordillera Principal geological province. In addition to the snow that precipitates in this area, there are 951 cryoforms providing meltwater to the upper catchment. Given the high inter-annual variability of snowfall and the megadrought affecting the region since 2010, it is crucial to quantify the contribution from different water sources buffering the Mendoza River runoff. Combining instrumental records of streamflow from glaciers and rivers, meteorological data, remote sensing of snow-covered areas and ionic and stable isotope analysis of different water sources, this study attempts to understand the hydrological contribution of different water sources to the basin. We demonstrated for the first time the relevance of different water sources in addition to snow in a dry period. During the melting season, 65% of the streamwaters originated from the glaciers (i.e. 50 and 15% from glaciers and rock glaciers, respectively), representing a higher proportion compared to snowmelt (17%). Groundwater input showed relatively large contributions, averaging 18%. This work offers information to develop adaptation strategies for future climate change scenarios in the region.
Glacier-wide mass balances and runoffs are reconstructed over 1969-2016 for Chhota Shigri Glacier catchment (India) applying a glacio-hydrological model. The model is forced using in-situ daily air-temperature and precipitation records from the meteorological stations at Bhuntar Observatory (1092 m a.s.l.), glacier base camp (3850 m a.s.l.) and glacier side moraine (4863 m a.s.l.). The modelled mean annual mass balance is −0.30 ± 0.36 m w.e.a −1 (meter water equivalent per year), while the mean catchment-wide runoff is 1.56 ± 0.23 m w.e.a −1 over 1969-2016. Three periods are distinguished in the reconstructed mass balance and runoff series. Periods I (1969-1985) and III (2001-2016) show glacier mass wastage at rates of −0.36 and −0.50 m w.e.a −1 , respectively, corresponding to catchment-wide runoffs of 1.51 and 1.65 m w.e.a −1 , respectively. Conversely, period II (1986-2000) exhibits steady-state conditions with average mass balances of −0.01 m w.e.a −1 , and corresponding runoff of 1.52 m w.e.a −1. The reduced ice melt (0.20 m w.e.a −1) over period II, in agreement with steady-state conditions, is compensated by the increased snow melt (1.03 m w.e.a −1), providing almost similar catchment-wide runoffs for period I and II. The increased runoff after 2000 is mainly governed by increased ice melt (0.32 m w.e.a −1) over period III. Snow accumulation in winter and summer seasons together control the glacier-wide mass balances as well as catchment-wide runoffs. Snow melt contributes the maximum to the total mean annual runoff with 63% share while glacier melt and rain contribute 17% and 20% respectively over the whole period.
Glacier retreat and runoff increases in the last few decades characterize conditions in the Kumalak River Basin, which is a headwater basin of the Tarim River with a catchment area of 12,800 km2. To address the scientific question of whether, and to what extent, the observed runoff increase can be attributed to enhanced glacier melt and/or increased precipitation, a glacier evolution scheme and precipitation-runoff model are developed. Using the glacio-hydrological model, we find that both glacier cover area and glacier mass in the study area have decreased from 1971 to 2010. On average, the contribution to total runoff from rainfall, glacier melt and snowmelt are 60.6%, 28.2% and 11.2%, respectively. Despite covering only 21.3% of the basin area, glacier areas contributed 43.3% (including rainfall, snowmelt and glacier melt) to the total runoff from our model estimates. Furthermore, as primary causes of increased runoff in response to the warmer and wetter climate over the period 1971–2010, contribution from increases in rainfall and glacier melt are 56.7% and 50.6%, respectively. In comparison to rainfall and glacier melt, snowmelt has a minor influence on runoff increase, accounting for −7.3%. The research has important implications for water resources development in this arid region and for some similar river basins in which glacial melt forms an important part of the hydrological cycle.
Accelerating multiphase water transformation affects runoff processes and components greatly and have changed the spatiotemporal patterns of water resources in the Third Polar Region. The source region of the Yangtze River is one location where accelerated warming has resulted in the gradual extension of the ablation period since 1990. This has caused the acceleration of multiphase water transformation, characterized by increases in the rate of glacial retreat, maximum freezing depth, and annual actual evapotranspiration and by decreased snowfall. In response, the total runoff increased by 53% at the Tuotuohe national hydrological station (TTH) and 6% at the Zhimenda national hydrological station (ZMD) during the periods 1961–1990 and 1991–2017, respectively. Under these conditions, runoff components were being determined based on stable isotope tracing. Substantial seasonal differences in δ¹⁸O (δD) among precipitation, river water, supra-permafrost water, and glaciers snow meltwater indicate that the runoff has been replenished by multiple components, and that these first infiltrate the ground, becoming part of the groundwater, and then recharge river water. Supra-permafrost water rather than precipitation now dominates river water. Based on the end-member mixing analysis model, supra-permafrost water, precipitation, and glaciers snow meltwater accounted for 51%, 26%, and 23% of river water at the TTH station from June 2016 to May 2018; the corresponding values at the ZMD station were 49%, 34%, and 17%. Additionally, there are also differences in the seasonal contributions of runoff components to river water. Seasonal variations in the freezing and thawing of the active layer directly trigger the runoff process. Future research should be focused on determining the mechanisms underlying the dynamics of precipitation-supra-permafrost water-runoff, which will aid the assessment of the impacts of an unstable Asian Water Tower on water resources.
This paper presents an assessment of the Soil and Water Assessment Tool (SWAT) on a glaciated (Qugaqie) and a non-glaciated (Niyaqu) subbasin of the Nam Co Lake. The Nam Co Lake is located in the southern Tibetan Plateau, two subbasins having catchment areas of 59 km2 and 388 km2, respectively. The scores of examined evaluation indices (i.e., R2, NSE, and PBIAS) established that the performance of the SWAT model was better on the monthly scale compared to the daily scale. The respective monthly values of R2, NSE, and PBIAS were 0.94, 0.97, and 0.50 for the calibration period while 0.92, 0.88, and −8.80 for the validation period. Glacier melt contribution in the study domain was simulated by using the SWAT model in conjunction with the Degree Day Melt (DDM) approach. The conjunction of DDM with the SWAT Model ensued improved results during both calibration (R2=0.96, NSE=0.95, and PBIAS=−13.49) and validation (R2=0.97, NSE=0.96, and PBIAS=−2.87) periods on the monthly time scale. Average contribution (in percentage) of water balance components to the total streamflow of Niyaqu and Qugaqie subbasins was evaluated. We found that the major portion (99.45%) of the streamflow in the Niyaqu subbasin was generated by snowmelt or rainfall surface runoff (SURF_Q), followed by groundwater (GW_Q, 0.47%), and lateral (LAT_Q, 0.06%) flows. Conversely, in the Qugaqie subbasin, major contributor to the streamflow (79.63%) was glacier melt (GLC_Q), followed by SURF_Q (20.14%), GW_Q (0.13%), and LAT_Q (0.089%). The contribution of GLC_Q was the highest (86.79%) in July and lowest (69.95%) in September. This study concludes that the performance of the SWAT model in glaciated catchment is weak without considering glacier component in modeling; however, it performs reasonably well in non-glaciated catchment. Furthermore, the temperature index approach with elevation bands is viable in those catchments where streamflows are driven by snowmelt. Therefore, it is recommended to use the SWAT Model in conjunction with DDM or energy base model to simulate the glacier melt contribution to the total streamflow. This study might be helpful in quantification and better management of water resources in data scarce glaciated regions.
Reliable precipitation data in the Himalayas are essential for the study of the water resources, the evolution of glaciers, and the present and future climate. Although several types of precipitation datasets are available for the Himalayan region, all of them have limitations, which hamper the quantification of the precipitation fluxes at high elevations. This study compares different types of precipitation datasets issued from (i) in situ data, (ii) satellite-based data [TRMM, Climate Hazards Group Infrared Precipitation with Station Data (CHIRPS)], and (iii) a reanalysis product [High Asia Refined analysis (HAR)] for a small headwater catchment at high elevations (Upper Dudh Koshi, Nepal) and assesses the impact of the precipitation uncertainty on the result of the modeling of the glacio-hydrological system. During the analyzed period from 2010 to 2015, large differences between the precipitation datasets occur regarding annual amounts (ranging from 410 to 1190 mm yr ⁻¹ ) as well as in seasonal and diurnal cycles. The simulations with the glacio-hydrological model Distributed Hydrological Soil Vegetation Model–Glaciers Dynamics Model (DHSVM-GDM) show that the choice of a given precipitation dataset greatly impacts the simulated snow cover dynamics and glacier mass balances as well as the annual, seasonal, and diurnal streamflows. Due to the uncertainty in the precipitation, the simulated contribution of the ice melt to the annual outflow also remains uncertain and simulated fractions range from 29% to 76% for the 2012–13 glaciological year.
With global warming, hydrological regimes in the headwater basins of the Tibetan Plateau (TP) have significantly changed. Investigating the responses of hydrological processes to climate change in TP has become more and more important to make robust strategies for water resources management. However, using just a few GCMs may constrain the uncertainty in assessment of climate impacts. Therefore, a framework is proposed in this study to generate ensemble climate change scenarios and then investigate changes of hydrological processes under climate change in the upper reaches of Yarlung Zangbo River basin (UYZR) and Lancang River basin (ULR). Firstly, the Latin Hypercube Simulation (LHS) is used to generate an ensemble of future climate change scenarios by resampling change factors of meteorological variables from 18 GCMs under emission scenarios RCP2.6 and RCP8.5. The inherent dependence structures of change factors, i.e. the correlations of change factors among 12 months for different meteorological variables, are also considered in ensembles. Secondly, the HBV hydrological model coupled with a degree-day snowmelt model is applied to explore the potential change of runoff in the future period 2041–2070. Results show that: 1) the resampling method is effective and can provide a wide ensemble of climate change scenarios. 2) Precipitation, temperature and potential evapotranspiration in the UYZR and ULR basins are expected to increase under the two scenarios, particularly under RCP8.5. 3) The total runoff also shows a moderately upward trend in two basins, both mainly due to increased precipitation. In the UYZR basin, fast runoff accounts for a larger proportion in total runoff than slow runoff, while in ULR, both almost play the same role in total runoff. Furthermore, snowmelt-induced runoff in both basins would be less and rainfall-induced runoff will probably become more important in the future.
This study investigated the contributions of snow/glacier meltwater to river runoff in the northern and central Tianshan Mountains (Central Asia). Based on end- member mixing analysis (EMMA), the hydrograph separation was carried out in six benchmark catchments with different glacier area ratios (GARs) and snow area ratios (SARs) during a typical snow melt period (TSMP) and a typical glacier melt period (TGMP). The results indicate that the contribution of snow/glacier meltwater to river runoff is positively correlated with GARs or maximum SARs. The contribution ratios of snowmelt water vary from 22% to 49% in TSMP. The contribution ratios of glacier meltwater vary from 12% to 59% in TGMP. The contribution ratios of snow meltwater in the northern Tianshan Mountains (36%) are higher than central Tianshan Mountains (31%), while the contribution ratios of glacier meltwater in the northern Tianshan Mountains (36%) are lower than central Tianshan Mountains (42%). The contribution of rainfall to river runoff is higher in TGMP (9%–23%) than in TSMP (5%–9%). Baseflow is the most important recharge source to river runoff, with the contribution ratios vary from 44% to 73% in TSMP, and vary from 30% to 75% in TGMP. The spatial and temporal variations in tracer concentrations in streamflow components were found to be responsible to the uncertainties in hydrograph separation.
While studies over retreat (reduction in glacier mass and snow cover area) of the Gangotri Glacier have received worldwide attention; no research has so far been conducted to quantify the contributions of snowmelt and glacier melt to the total flow of the Bhagirathi (upper Ganga) River emanating from the Gangotri Glacier. In the present study, the fractional contributions of snowmelt, glacier melt and direct runoff to the Bhagirathi River were estimated on ten daily and monthly time intervals for the ablation period (May to September) of 2005 using environmental isotope (δ²H, δ¹⁸O and ³H) techniques. Hydrograph separation was carried out using a two-component and three-component isotope mixing models. The estimated average seasonal (ablation period) contributions of snowmelt, glacier melt and direct runoff to the Bhagirathi River were 59.6%, 36.8% and 3.6%, respectively. Also, the significant temporal variations in their contributions were observed. The monthly proportions of snowmelt in the river flow varied from 42.9% (July) to 91.9% (May), while the monthly ratios of glacier melt ranged between 8.1% (May) and 47.4% (July). The observed temporal variability in the estimated contributions of the snowmelt could be linked to the Snow Cover Area (SCA) of the catchment. The results of the hydrograph separation indicate that the snowmelt dominates the river flow during the ablation period. Environmental tritium (³H) data also supports this finding. The presence of ³H in the river (average value: 8.8TU) endorse that it is mainly derived from the melting of relatively modern snow (average value: 12.4TU). These results suggest that the stable isotopes of oxygen and hydrogen in combination with radioactive ³H can be effectively used for the identification of the sources of water that sustains the river flow in the glaciated catchment of the Gangotri Glacier, and may contribute to a more robust assessment of the hydrological budget in the glaciated catchments of the Himalayan Region.
Hydro-geochemical study of small catchment provides important information to identify water and solute sources, understand chemical weathering processes and their controlling factors. In this work, 44 small catchments on the southeastern Tibetan Plateau were investigated. Stream, precipitation, glacier and spring waters in both high and low flow seasons and bed rocks samples were analyzed with a main purpose to understand the processes controlling the stream water chemistry and quantify the weathering rates. The stream waters are mainly recharged by precipitation and glacier meltwater. Glacier meltwater and precipitation account for 25.8% and 73.9% of the total discharge in high flow season, and 44.4% and 54.1% in low flow season on average. Hydrograph separation and chemical mass balance are jointly used to estimate the contributions of major reservoirs (precipitation, glacier, spring, carbonates and silicates) to the total dissolved loads of the streams. Rock weathering accounts for ~90% of the total dissolved cations for most streams. Silicate and carbonate weathering account for 15.9% and 75.2% of total dissolved cations in high flow season, and 9.5% and 77.2% in low flow season on average. Lack of basic hydrological data in the ungauged remote area is a problem for quantified weathering study. The Noah LSM model is applied to obtain the annual runoff of these un-gauged catchments in this study. Based on these approaches, the chemical weathering rates and total denudation rates (TDR) are calculated for each of the small catchments. The silicate cation weathering rates (SCWR) range between 0.6 and 5.2 t/km²/yr, with the area-weighted mean value about 1.8 t/km²/yr. The TDR range between 8.9 and 1907.9 t/km²/yr. The comparisons between the small catchments and with other river basins in different tectonic and climatic environments indicate that lithology, climatic factors (temperature and runoff) and physical erosion rate are the key parameters controlling chemical weathering rate. The average SCWR of the small catchments is about 6 times higher in high flow season than in low flow season, which could be attributed to the higher temperature and runoff in high flow season. Meanwhile, the positive relationship between SCWR and TDR supports the view that physical erosion has an important effect on chemical weathering in the Tibetan Plateau.
Rivers originating from the Tianshan Mountains, known collectively as the “water tower of Central Asia”, are a key source of fresh water to the densely populated lowlands. Despite of the significance of water resources, our knowledge on the discharge regime in the alpine regions is limited, due to the paucity of in situ measurements and the complexity of contributing sources including rainfall, snowmelt and glacier-melt. In this study, the streamflow regime for the headwater catchment of Manas River basin (MRB) in the Tianshan Mountains is investigated through application of a hydrologic modeling framework, which is based upon an appropriate modification of the hydrological model HBV-D (Hydrologiska Byrans Vattenbalansavdelning-D). The daily precipitation and average temperature are reconstructed based on meteorological station data and remote-sensing observations for the period 1967–2007. Thereafter, the modified hydrological model is evaluated and the temporal distribution of runoff components is quantified via the model simulation. Our primary results include the following: (1) our modified version of the HBV-D model, with stronger physics basis in snow/glacier module and higher spatial resolution, is superior to the original HBV-D model in simulating daily streamflow processes and is capable of reproducing the variations of glacier area and glacier volume during the historical period. (2) Snowmelt is shown to dominate runoff processes in pre-monsoon season, accounting for approximately 61%, 76% and 74% of streamflow in April, May and June, respectively. The monthly contributions from glacier-melt, occurring in the region above 3000 m a.m.s.l (above mean sea level), range from 27% to 44% during the July–September period. (3) The average annual discharge in the MRB is sourced to 48% by snowmelt, 27% by glacier-melt, and the rest by rainfall. Particularly in 1981 when rainfall and snowmelt runoff were substantially reduced, the contribution of the glacier-melt to the river discharge reached 40%, suggesting that the glacier melt contributions to the streamflow in the MRB are especially significant during the dry years in ensuring a sustained water supply. The modified HBV-D model is expected to provide a useful modeling tool in simulating runoff regime in high-altitude mountainous regions and the results constitute a highly significant initial contribution to the formulation of effective adaptation strategies for water resource management under climate change.
Water resources are essential to ecosystems and social economies worldwide, especially in the deserts and oases of the Tarim River Basin, whose water originates largely from alpine mountains characterized by complicated hydrological processes and scarce hydrometeorological observations. This paper presents multisite and multiobjective modeling of hydrological processes in the whole Tarim River Basin, covering 32 catchments in total. The study uses the Soil and Water Assessment Tool, extended by incorporating a degree-day glacier melt module to enable modeling of glacier melt in the alpine mountains. The multiobjective calibration approach of ε-Nondominated Sorting Genetic Algorithm-II was implemented with the two objective functions of the Nash-Sutcliffe value of daily streamflow and the bias of simulated glacier melt contribution to streamflow. Based on the combined use of the Morris sensitivity technique and hierarchy cluster, the 32 catchments in the study area are divided into six groups according to their dominating hydrological processes, for example, glacier melt, snowmelt, groundwater, and routing. The multiobjective calibration was satisfactory, with 22 of the 32 catchments showing Nash-Sutcliffe values of daily streamflow larger than 0.6 and the bias of simulated glacier melt contribution to streamflow values smaller than 0.05. Model performance was highly dependent on meteorological data availability, in that low data availability led to poor model performance, while factors such as catchment area and mean annual snowfall had little influence on model performance. The results indicate that multisite and multiobjective calibration enables consistent and comprehensive examination of the spatially different hydrological processes in a large basin and provides information for further assessment of the impact of climate change on water availability.