No full-text available
To read the full-text of this research,
you can request a copy directly from the author.
Characteristics of low flows.
Abstract
A Task Committee of the Surface Water Hydrology Committee was organized in 1976 to determine the types of low-flow information needed, to describe available methods of characterizing low flows, and to identify needed analyses and data collection. Available analytical methods are described and evaluated, sources of low- flow information are given, and some recently proposed techniques are reported. -from ASCE Publications Abstracts
... Previous studies have introduced an index of n-day, T-year low flow (nQT) for the purpose of estimating design low flows. It is defined as the annual minimum average n-day low flow that recurs, on average, once every T years (ASCE Task Committee, 1980). The most widely used low flow index is 7Q10, and methods for calculating it for gauging stations and ungauged sites have been studied extensively over the past decades. ...
... Procedures from relationship formulation to curve construction can be found in Kroll (1990, 1992) and Gustard et al. (1992). Despite the long-standing recognition that data collection and targeted analyses are needed in order to obtain reliable estimates of low-flow characteristics at ungauged sites (ASCE Task Committee, 1980), the progress up until recent times has been limited, in particular with respect to small basins (Whitfield, 2008). Also, the common practice rarely considers the impact of climate change on low flows. ...
Changes in winter low flow (WLF) in cold-region rivers affect engineering design, water quality, and river ecosystem health. This paper aims to quantify to what extent WLF will change under climate warming and to propose a practical forecasting model for WLF predictions. The new concept of cumulative watershed temperature (CWT) is used as a convenient lumped surrogate for complicated hydrological processes that influence WLF. Statistical analyses of century-long flow data from the Fraser River in British Columbia, Canada show a strong dependence of WLF on CWT. In winter season, time series of CWT and WLF are shown to each divide into a falling and a rising limb at the data point of their lowest values, being −358 °C and 827 m³/s (historical averages), respectively. The falling and rising limbs describe the cumulative freezing and thawing effects of air temperatures fluctuating around the freezing point on WLF changes. The correlation between CWT and WLF (time series) data points on the rising limbs forms the forecasting model, expressing WLF as a function of CWT in terms of their z-scores. The model takes input of Global Circulation Model (GCM) projections of temperature increases by the end of 21st century under different Representative Concentration Pathways (RCPs), and predicts changes of Fraser River WLF from the historical average. RCP4.5 causes a 22.6% increase (ensemble average from six GCMs). RCP8.5 increases WLF by 20% (for some future years) to 44% (for others). The methods reported in this paper can be adapted to other cold regions.
... Despite this scenario, two related issues are raised: 1) the UTW does not have yet a general estimation of aquifer recharge that considers the whole territory (urban and rural areas) and all the nuances of the several types of anthropic occupation; and 2) there needs to be a method for estimating groundwater availability in complex urban areas. Thus, this paper aims to solve these questions for the UTW based on the association of classic techniques, including water budget calculation (Thornthwaite 1948;Thornthwaite and Mather, 1955;Fenn et al., 1975), estimation of 7-day, 10-year (Q 7,10 ) low-streamflow discharge (Riggs 1980;DAEE 2012), structured in a GIS through a weighted ranking system. ...
... The main one is the maintenance of the base flow of rivers and streams. Thus, a criterion for establishing available water flow is to subtract from the aquifer recharge the flow Q 7-10 of the hydrographic basin (Riggs 1980;DAEE 2012). Q 7-10 is the minimum daily flow for 7 days in a row from the main river that drains the basin over a 10-year recurrence period (Reilly and Kroll 2003). ...
Extensive urbanized areas, characterized by waterproofed soils, increase runoff, which reduces the rainwater infiltration into the ground. However, water, sewer, and rainwater distribution systems leak, as there is excess irrigation in green areas, resulting in anthropic recharging in urban aquifers larger than in rural areas with equivalent climates. This scenario occurs in the Upper Tietê Watershed (UTW), an area of 5,868 km² that drains the principal rivers of the São Paulo's metropolitan region in Brazil, where groundwater plays a complementary role for domestic, industrial, and agricultural supplies, totalizing extraction rates higher than 11 m³/s. In this paper, a Geographical Information System (GIS) was established to assess regional groundwater availabilities using adaptations of classic recharge methods such as soil water budget calculations and estimation of minimum sustainable river flow. For this, a surface runoff map, based on soil and slope terrain data, was evaluated using the information on water and sanitation infrastructure and meteorological data. We found that recharge in urban areas (with water and sewer mains) was 437 mm/yr and 106–407 mm/yr in rural areas. Considering the need to maintain a minimum historical flow of 20 m³/s in the hydrographic basin of the Tietê River, the total exploitable groundwater is 33 m³/s. The compilation of various GIS methods can help decision-makers develop alternative water security management plans in complex urbanized-regions such as in the metropolis of São Paulo.
... Low flow at a site is often characterized by an index of low flow. A widely used index of low flow in the United States is the 7-day, 10-year low flow, which is the discharge having a 10-year return period derived from a frequency curve of the lowest average flow for seven consecutive days in a year (Riggs et al. 1980). Usually time series of low flows are time dependent due to factors such as ground water, lake regulations, wetland storage, and channel storage. ...
... However, for low-flow studies it is better to use calendar years or climatic years (April 1-March 31, in the northern hemisphere) to avoid breaking the low-flow season into separate years. This criteria has been used by the USGS for analyzing low flows and has been recommended by some authors (Riggs et al. 1980). The series used in this example correspond to climatic years (April-March for the Upper Colorado basins, and September-August for the Parana River). ...
A mathematical formulation to estimate return periods and risks of failure of complex hydrologic events such as those arising from dependent floods and droughts have been examined in the first part of this paper. Specifically, some relationships and algorithms for computing return periods and associated risks for runs arising from independent and dependent events assuming that dependence is represented by a two-state Markov chain have been proposed. The applicability of these procedures is illustrated herein, considering several types of hydrological events with emphasis on those where dependence is important. First, meteorological droughts based on annual precipitation are considered as examples of events consisting of runs in independent trials. Then, minimum streamflows and maximum annual lake outflows are included as examples of dependent events, assuming that dependence is represented by a simple Markov chain. Also, hydrological droughts based on annual streamflow series are considered. In addition, the estimation of return period and risk are illustrated by data generation.
... As 233 such, we choose this duration for our analysis as a robustness check on our optimized reservoir 234 operating policies. Seven-day low flows are also used frequently to define environmental droughts 235 such as the most commonly used low flow index in the United States: the seven-day, ten-year low 236 flow, or 7Q10, defined as the annual minimum seven-day low flow that occurs, on average, once 237 every ten years(Riggs 1980).238 Gao et al. (2009) use flow indicators like annual seven-day minima to calculate indices of 239 hydrological alteration, quantified as the integrated difference between the distribution of these 240 variables before and after infrastructure development. ...
Climate change is projected to increase the intensity and frequency of extremes in river basins around the world. Water infrastructure such as reservoirs are often used to buffer against these extremes, enabling more reliable water supply for human uses like irrigation. Yet this can have negative impacts on the system’s ecological flows. In designing water infrastructure for human adaptation to climate change, it is important to consider whether the infrastructure is mitigating or exacerbating climate change impacts on ecological systems. Prior work has found that dams mitigate long-duration extremes but exacerbate short-duration extremes. In this study, we investigate whether reservoir operations can be designed to also yield beneficial climate adaptation outcomes for short-duration high and low flow extremes while still improving average socioeconomic and ecological objectives compared to uncontrolled conditions. We explore this research question
... We quantify the timing of low flows and their climatic drivers using the same directional statistics (Bayliss & Jones, 1993;Burn, 1997) that have been widely used to characterize the seasonality and climatic drivers of floods (e.g., Berghuijs et al., 2016;Blöschl et al., 2017;Köplin et al., 2014), and have also been applied in previous low-flow analyses (e.g., Tian et al., 2011;Wehren et al., 2010;Young et al., 2000). We define the annual low flows by the lowest 7-day average streamflow each year (Q min ), which is a commonly used indicator of low flows (e.g., Jenicek et al., 2016;Laaha et al., 2017;Riggs, 1980;Van Lanen et al., 2016;Vogel & Kroll, 1992). The Q min dates analyzed here are the centers of these 7-day lowest streamflow periods in each year and each catchment. ...
Low river flows can negatively impact society and the riverine environment. Thus, it is useful to predict their seasonal timing and reveal their main drivers. The typical timing of low flows varies between regions, yet systematic overviews across Europe and the United States are rare. Here, we identify regional patterns of the seasonal timing of annual minimum flows, and the consistency of that timing, across 1860 European and US catchments. Catchments where low flows typically occur during late summer or winter tend to have more consistent low-flow timings.
We compare the timing of annual low flows with that of potential climatic drivers. Low flows in 89% of the European and 86% of the US catchments exhibit statistically significant (p<0.05) overlap in timing with at least one potential climatic driver. In most catchments, low flows tend to occur during the warm season, reflecting a period of high potential evapotranspiration exceeding precipitation. In the higher-elevation European Alps, Scandinavia, the Rocky Mountains, and the Upper Midwest and Plains states, low flows mostly occur during winter as a result of freezing temperatures which inhibit snowmelt. Binomial statistics also enabled us to statistically exclude individual climatic drivers for certain regions. The regional patterns of timings and drivers of low flows across Europe and the contiguous US can inform low-flow management, provide context for the evolution of low flows under climate change, and point to processes that require attention in future low-flow research.
... We follow the same strategy to calculate the changes for low flow analysis. Among different low flow metrics, we present in this study low flow events associated with the 7-day 10-year (Q 7,10 ) low flow which can be defined as minimum 7-day average of flows that can recur, on average, once in every 10 years (Riggs, 1980). Q 7,10 is one of the most widely used low flow metrics in water resources applications, i.e. water quality monitoring, hydropower, irrigation, water supply etc. (Eslamian et al., 2010;Tasker, 1987). ...
Study region
The Commonwealth of Massachusetts, United States.
Study focus
The Commonwealth of Massachusetts is projected to experience significant impacts from future climate change and these impacts include but are not limited to increases in extreme precipitation, flooding and droughts. This study investigates the potential impacts of climate change and uncertainties on future floods and low flow conditions in the rivers and streams of Massachusetts. Fourteen downscaled GCM projections under two greenhouse gas concentration pathways (RCP4.5 and RCP8.5) are used as inputs into a distributed hydrological model to obtain future streamflow conditions.
New hydrological insights for the region
Seasonal change projections of 100-year flood and a measure of drought (the seven-day, ten-year low flow - Q7,10) are estimated through the near-term (years 2021−2060) and the far-term (years 2060−2099) relative to the base period (years 1981–2016). The median estimates of 100-year flood during winter report a 15 % or higher increases in many watersheds at the far-term. In contrast, flood magnitudes in spring show decreases for most of the watersheds during both near- and far-term. For seven-day, ten-year low flow estimates, largest decreases are projected during the fall and this trend is found to be consistent across future time periods. Two emission scenarios have shown similar trends for most cases although change projections are seen to be more prominent for RCP8.5 when compared to RCP4.5.
... Hydrologic drought is often characterized by low streamflow statistics. Common low streamflow statistics include the 7-day, 10-year low streamflow (7Q10), which is the 7-day annual minimum streamflow with a nonexceedance probability of 10% (Riggs 1980), and the daily streamflow with an exceedance probability of 95% (Q95) (Smakhtin 2001). Other common low streamflow statistics employed in practice include the 7Q2, 30Q10, 30Q2, Q99, and Q90 (Hughes 1981;Armentroutand and Wilson 1987;Zalants 1992;Atkins and Pearman 1995;Smakhtin 2001). ...
... Low streamflow estimates are used to assist water managers in planning for low flow conditions for river ecology and flow management, wastewater treatment plants, water withdrawal limitations and discharge permitting, and hydropower operations (Smakhtin, 2001). Often, these estimates are represented by low streamflow statistics such as 7Q10, the annual average 7-day minimum flow that is not exceeded on average once every 10 years (Riggs, 1980), or a quantile from an annual or monthly flow duration curve, such as the Q95, the daily average streamflow that is exceeded 95% of the time (Susquehanna River Basin Commission, 2012). The U.S. Geological Survey (USGS) has over 20,000 gauged locations across the United States, and one can relatively easily generate low streamflow statistics from the data provided at these sites. ...
Low streamflow statistic estimators at ungaged river sites generally have large errors and uncertainties. This can be due to many reasons, including lack of data, complex hydrologic processes, and the inadequate or improper characterization of watershed hydrogeology. One potential solution is to take a small number of streamflow measurements at an ungaged site to either estimate hydrogeologic indices or transfer information from a nearby site using concurrent streamflow measurements. An analysis of four low streamflow estimation techniques, regional regression, regional plus hydrogeologic indices, baseflow correlation, and scaling, was performed within the Apalachicola-Chattahoochee-Flint watershed, a USGS WaterSMART region in the southeastern United States. The latter three methods employ a nominal number of spot measurements at the ungaged site to improve low streamflow estimation. Results indicate that baseflow correlation and scaling methods, which transfer information from a donor site, can produce improved low streamflow estimators when spot measurements are available. Estimation of hydrogeologic indices from spot measurements improve regional regression models, with the baseflow recession constant having more explanatory power than the aquifer time constant, but these models are generally outperformed by baseflow correlation and scaling.
... Low flow is a relative term, suggesting that river discharge falls below a particular level of expectation: there is no one single characterization of low flow that is suitable for all purposes (Riggs, 1980). The several common techniques devised for low flow investigations have been well summarized by Smakhtin (2001). ...
Most northern rivers experience recurrent low flow conditions in the summer (June to September), and rivers of the Mackenzie Basin are no exception. Low flow affects water supply, poses problems for river traffic, and can adversely affect aquatic ecology. Factors that affect summer low flow, which encompasses flows below specified discharge thresholds of concern, include evapotranspiration that leads to water loss from flow-contributing areas, antecedent high flow in which peak discharge is followed by gradual recession to low flow, rainfall and local glacier melt events that interrupt low discharge, replenishments of flow from upstream drainage networks, and arbitrary termination of summer low flow at the end of September. The storage mechanism of large lakes and the regulation effect of reservoirs can produce low flow regimes that differ from those exhibited by rivers without such storage functions. For most rivers, low flow events of longer duration cause larger deficits, and events with large deficits are accompanied by lower minimum discharge. The deficit-to-demand ratio measures the extent to which river flow fails to satisfy water needs. Applying this index to rivers of the Mackenzie drainage shows the hazard of streamflow drought in the basin. Low flow attributes can be summarized by their probability distributions: Gumbel distribution for minimum discharge of events and generalized exponential distribution for event duration. By fitting theoretical distributions to recorded events, one can estimate the probability of occurrence of low flow events that did not occur in the historical past.
... Fernandez and Salas (1999) stated that the estimation of return periods of hydrological events and the corresponding risks of failure of hydraulic structures that are associated with such events are important aspects in many water resources studies. Riggs (1980) imply that the most widely employed low flow statistic in the United States is Q reference discharge. Stahl and Demuth (1999) emphasis that temporal variability in annual low flows arise from climate variability. ...
The most true selection probability distribution is important to describe the low flow statistics for the studies related to drought analysis. The aim of this study is to derive appropriate probability distributions for frequency analysis of 7-day annual low flows at three gauging stations of the Cekerek Stream. The lowest 7-day flow series were constituted from daily flow data for 7-day periods of each year. A minimum 7-day flow is the lowest flow that occurred within a 7-consecutive day period. L-moment technique was used to predict the parameters of the selected distributions. Two goodness of fit indices, including MADI and MSDI, were used to compare the performances of the probability distributions for fitting. According to results, the best performance was obtained for generalized pareto (GPA) distribution. The distributions produced negative values were discarded. The predicted low flows obtained from the distributions that produced positive values (except Log Pearson type three) for empirical probability levels (Gringorten formula) sufficiently represent the actual low flows for probability levels higher than 75%. The statistics having reoccurrence interval of ten years (Q7,10) based on GPA distribution were predicted as 0.29, 1.27 and 2.11 m 3 /s for gauging stations 1424, 1409 and 1404, respectively.
... Fernandez and Salas (1999) stated that the estimation of return periods of hydrological events and the corresponding risks of failure of hydraulic structures that are associated with such events are important aspects in many water resources studies. Riggs (1980) imply that the most widely employed low flow statistic in the United States is Q reference discharge. Stahl and Demuth (1999) emphasis that temporal variability in annual low flows arise from climate variability. ...
... T=2600). The modeling of the aforesaid parameters on a weekly basis stems as an offshoot of low flow studies in which a minimum 7-day average flow is regarded as a rational descriptor of drought conditions in United States [1] and United Kingdom [2]. A weekly time provide satisfactory results. ...
At times hydrological droughts are defined using Q90 or Q95 (90% or 95% flow being equaled or exceeded) as truncation levels regardless of their seasonal variations. Truncation at a constant level of flow compared to a variable level (i.e. mean or median level for each season) postures unique statistical problems in modeling of drought durations and magnitudes (deficit volumes). This paper develops a procedure for predicting a T-week drought duration, E(L T) for a weekly flow sequence based on the concept of standardized hydrological index (SHI). The SHI series were modeled using the first order Markov chain model (MC-1) while being truncated at a constant flow level such as Q90 or Q95. A T-week drought magnitude (standardized) was predicted using the relationship E(M T) = α × I × E(L T), where α is a scaling factor to account for the difference between averaged out (week-by-week) standard deviation and the overall standard deviation of the weekly flows, I is the drought intensity whose characteristics are assumed to resemble a truncated normal distribution of weekly deficits, and E(L T) is based on the zero order Markov chain model (MC-0) of drought lengths. This analytical approach can be construed as distribution free, since simple and first order conditional probabilities of droughts are empirically estimated from the SHI series derived from weekly flow records irrespective of their underlying probability distribution function. Predictive ability of the proposed procedure has been found to be satisfactory for E(L T) and E(M T) at Q90 to Q95 truncation levels.
... Moreover, the number of days with low flows in Northern European rivers is expected to increase due to climate change (Middelkoop et al., 2001; De Wit et al., 2007; Te Linde et al., 2008). Elaborative studies on low flows started in 1976 when a Task Committee on Low Flow was organized by the American Society of Civil Engineers (Riggs, 1980). This committee drew attention to the consequences of hydrological droughts and to the need for further studies using standard low flow indexes. ...
This study investigates the selection of an appropriate low flow forecast model for the Meuse
River based on the comparison of output uncertainties of different models. For this purpose, three data
driven models have been developed for the Meuse River: a multivariate ARMAX model, a linear regression
model and an Artificial Neural Network (ANN) model. The uncertainty in these three models is assumed to
be represented by the difference between observed and simulated discharge. The results show that the ANN
low flow forecast model with one or two input variables(s) performed slightly better than the other statistical
models when forecasting low flows for a lead time of seven days. The approach for the selection of an
appropriate low flow forecast model adopted in this study can be used for other lead times and river basins
as well.
... Low flows also are associated with low dissolved oxygen and/or high contaminant concentrations, with negative consequences for aquatic habitat. For these reasons, state and local municipalities establish regulatory limits on the basis of estimated low-flow characteristics, such as the estimated 7-day, 10-year low flow,Q 7,10 [Riggs, 1980]. TheQ 7,10 is defined as the estimated annual minimum 7-day average flow that is expected to be exceeded on average in 9 out of 10 years and, equivalently, as the 10th percentile of the distribution of annual minimum 7-day average streamflows. ...
Estimates of low-flow characteristics from regional regression equations have been shown to benefit from use of basin-specific information on baseflow recession. In applications to date, the measures of baseflow recession have been estimated from continuous streamflow records. This seriously limits their usefulness as predictors of low-flow characteristics at sites without continuous streamflow records. A method is proposed herein for obtaining such information for sites with very few streamflow measurements ("partial-record sites"). Simulation of one to four pairs of low flow values at each partial-record site is done by a "random bootstrapping-Monte Carlo method" using continuous record sites. These low-flow values are used to compute up to four estimates of the baseflow-recession measure. The constants of the regression models are calculated from the data at continuous record sites, and evaluated at simulated partial-record sites. This method is tested with data from 93 continuously gaged rural basins in the southeast United States. The introduction of a baseflow-recession time constant as a predictor approximately halved the root-mean-square estimation error relative to a conventional drainage-area regression. This result is more realistic than one assuming that a continuously monitored site is available for evaluation.
... Low flows also are associated with low dissolved oxygen and/or high contaminant concentrations, with negative consequences for aquatic habitat. For these reasons, state and local municipalities establish regulatory limits on the basis of estimated low-flow characteristics, such as the estimated 7-day, 10-year low flow,Q 7,10 [Riggs, 1980]. TheQ 7,10 is defined as the estimated annual minimum 7-day average flow that is expected to be exceeded on average in 9 out of 10 years and, equivalently, as the 10th percentile of the distribution of annual minimum 7-day average streamflows. ...
Base flow recession information is helpful for regional estimation of low-flow characteristics. However, analyses that exploit such information generally require a continuous record of streamflow at the estimation site to characterize base flow recession. Here we propose a simple method for characterizing base flow recession at low-flow partial record stream gauges (i.e., sites with very few streamflow measurements under low-streamflow conditions), and we use that characterization as the basis for a practical new approach to low-flow regression. In a case study the introduction of a base flow recession time constant, estimated from a single pair of strategically timed streamflow measurements, approximately halves the root-mean-square estimation error relative to that of a conventional drainage area regression. Additional streamflow measurements can be used to reduce the error further.
... [2] Knowledge of the magnitude and frequency of lowflow events is required in order to plan water-supply systems, wastewater discharges, reservoirs, and irrigation systems, and to maintain the quality of water for wildlife and recreation [Smakhtin, 2001]. In the United States, the 7-day, 10-year low flow (Q 7,10 ) is a commonly used lowflow statistic [Riggs, 1980]. The Q 7,10 is the average annual 7-day minimum flow that is expected to be exceeded on average in 9 out of every 10 years, which is equivalent to the tenth percentile of the distribution of 7-day annual minimum streamflows. ...
[1] Estimators of low-streamflow statistics are often required for water quality and quantity management at gauged and ungauged sites. Here the technique of baseflow correlation is investigated as an estimator of the 7-day, 10-year low-streamflow statistic at ungauged sites. This method uses an information transfer technique to estimate streamflow statistics at an ungauged site by correlating a nominal number of measured streamflow discharges during baseflow conditions at the ungauged site with those at a nearby gauged site. A regional assessment of baseflow correlation estimators is made by employing daily streamflow values at more than 1300 USGS HCDN stream gauge sites. A jackknife simulation is performed in each of the 18 USGS water resource regions located within the conterminous United States. Potential gauged sites are selected using a variety of watershed, geographic, topographic, and geologic classification systems. The results of this study indicate that baseflow correlation performs well in the United States when baseflow measurements are nearly independent and potential gauged sites are located within 200 km. The method is improved as the number of baseflow measurements is increased, although some leveling off of performance was observed with more than 15 baseflow measurements. A comparison of baseflow correlation with regional regression shows that baseflow correlation is the preferred method for estimating low flows in much of the United States.
... The most widely used index of low flow in the United States is the seven-day, ten-year low flow (Q1.IO), defined as the annual minimum average seven-day low flow that recurs, on average, once every ten years (Riggs et al. 1980). Estimation of the Q1.IO from streamflow records consists of detern1ination of a probability distribution of the annual minimum seven-day low flows and selection of a statistically efficient parameter-estimation procedure, Statisticians tern1 these tasks distributional hypothesis testing and point estimation, respectively. ...
Although a vast amount of literature exists on the selection of an appropriate probability distribution for annual maximum floodflows, few studies have examined which probability distributions are most suitable to fit to sequences of annual minimum streamflows. Probability plots have been used widely in hydrology as a graphical aid to assess the goodness of fit of alternative distributions. Recently, probability-plot correlation-coefficient (PPCC) tests were introduced to test the normal, two-parameter lognormal and Gumbel hypotheses. Those procedures are extended here to include both regional and at-site tests for the two-parameter Weibull and lognormal distributional hypotheses. In theory, PPCC-hypothesis tests can only be developed for two-parameter distributions that exhibit a fixed shape. Nevertheless, the PPCC is a useful goodness-of-fit statistic for comparing three-parameter distributions. The PPCC derived from fitting the two- and three-parameter lognormal, two- and three-parameter Weibull, and log-Pearson type III distributions to sequences of annual minimum seven-day low flows at 23 sites in Massachusetts are compared. How the PPCC can be used to discriminate among both competing distributional hypotheses for the distributions of fixed shape and competing parameter-estimation procedures for the distributions with variable shape is described. An approximate regional PPCC test is developed and used to show that there is almost no evidence to contradict the hypothesis that annual minimum seven-day low flows in Massachusetts are two-parameter lognormal.
... This study is more general as record augmentation procedures are evaluated for estimating quantiles of the distribution of annual minimum d day low-flows (d = 1, 3, 7, 14, and 30 days) and annual maximum flood-flows. The 7-day 10-year low-flow statistic, QT. 10, is the most widely used index of low-flow in the United States (Riggs et al., 1980). ...
Streamflow record augmentation procedures exploit the cross-correlation among streamflows at two or more streamgages to obtain improved estimates of the mean and variance of the flows at a short-record gage. Recent improvements in these procedures provide unbiased estimates of the mean and variance of the flows at the short-record site which always have equal or lower variance than simple at-site sample estimates. Essentially, record augmentation procedures increase the effective record length at a short-record site in proportion to the additional length of the nearby longer record and the cross-correlation of the concurrent streamflows at the two sites. An experiment documents the effective increase in record lengths on a site-by-site basis and on a regional basis using a network of 23 streamgages in or near Massachusetts. The increases in effective record lengths owing to the use of streamflow record augmentation procedures are substantial for the very-short-record sites for both flood-flow and low-flow statistics. However, the serial correlation associated with both flood-flow and low-flow sequences reduces those gains considerably.
... The daily streamflow records were used to obtain estimates of the 7-day annual minimum streamflow which is on average exceeded nine out of every ten years, Q 7,10 . The Q 7,10 is the most widely used low-flow statistic in the United States Riggs 1980. In general, the USGS uses a log-Pearson type 3 LP3 distribution to describe annual minimum streamflow series, as evidenced by its use in a variety of USGS studies Barnes 1986;Wandle and Randall 1993;Rumenik and Grubbs 1996. ...
Information regarding topographic, meteorologic, geologic, and geomorphic characteristics is increasingly available in spa-tially explicit digital formats. Of interest is whether enhanced spatial processing of newly available digital grids can lead to new estimators of watershed characteristics which may in turn, improve our ability to predict extreme hydrologic events. Regional hydrologic models of low-flow processes often produce estimators with unacceptably large errors. Using a continuous digital elevation model DEM of the conterminous United States, watershed boundaries were developed for the streamflow gauges of the USGS's Hydro-Climatic Data Network. Using these watershed boundaries, many watershed characteristics were developed from digital grids, including: the original DEM, the USDA's State Soil Geographic grids, and the Spatial Climate Analysis Service's orographically weighted precipitation and temperature grids of varying spatial and temporal resolution. Digital processing of grids leads to improvements in estimation and reproducibility of spatial statistics over traditional manual processing approaches. Low-flow regional regression models were developed for regions across the conterminous United States. Inclusion of the new watershed characteristics led to improvements in regional regression models for all regions. The inclusion of hydrogeologic indices, in particular a new smoothed baseflow recession constant estimator, led to dramatic improvements in low-flow prediction.
The water stress indicator represents the water withdrawal rate with respect to the available water excluding the environmental flow and is designed to provide an overview of a country's water management. To use this indicator in various regions during the dry season when water problems may arise, items are modified and applied with a low flow, an environmental flow, and stream water use. This method conforms to Korea's water use permit and instream flow system thus, it can be used practically. In addition, since stream water during the dry season is more vulnerable to use than water from reservoirs, a water resource development indicator is introduced. Based on this water resource development indicator and the water stress indicator, the Yeongsangang River area is the most susceptible to water shortage during the dry season. These two indicators are effective because only a few data types are needed to identify areas that are vulnerable during the dry season.
For mitigating negative effects of floods and droughts, estimates of flow indicators and their uncertainties are essential. The recently introduced concept of the representative parameter sets (RPSs) enables modelling uncertainty to be represented in the flow frequency space at low computational cost, using a small subset of pre-selected model parameter sets. This concept is here adapted to assess hazards of three flow indicators: annual maximal flow, annual 7-day-average low flow, and annual mean flow. An additional in-depth analysis assesses the RPS transferability to other flow indicators and to hydrological signatures. RPS-based simulations are benchmarked with a random selection of parameter sets. The results show that i) RPSs can be successfully transferred between flow indicators with only a small drop in model performance; and ii) RPSs can be used to represent modelling uncertainty in hydrological signatures. The RPS concept has thus great potential for delineating modelling uncertainty of any environmental model.
The paper deals with the long-term and seasonal variability of low flows using the example of a mountain river. The study covers the Laborec River in the eastern part of Slovakia, and the main aim of the research is to identify and establish long-term fluctuations of low flows on this river. The analysis aims to indicate trends of low flows and seasonal variability of outflows based on various measures and research methods as well as the links between them. Basic data on daily flow and precipitation series were collected from 1980 to 2019. Low flow periods were identified in relation to the fitting of the threshold level method to the 70th and 95th percentile on the flow duration curve as a constant, multi-annual cut-off (Q70%, Q95%). The longest lasting flows were those below q70%, which were determined in the shallow cut-offs that occurred for most of the year, i.e. from June to December and in January. The greatest culmination of flows below q95% was in August and September. The range of minimal unit outflow is the smallest in the summer-autumn period and results from long periods without precipitation and with increased evapotranspiration. The highest range of unit outflow was recorded from December to April. Knowledge of low river flows should be one of the important elements of advanced planning, which in the future may help to reduce conflicts between water users during the peak demand period.
Streamflow gives rivers and streams their distinctive character, influencing virtually every physical, chemical, and biological process within fluvial ecosystems. Measurement of streamflow characterizes stream or river size, variability across all time scales and among seasons and river types, and the response to human intervention. Because rivers have enormous value to society as a source of drinking water and means of transport, as well as for hydropower, waste removal, and irrigation, humans have extracted, diverted, and impounded river flows since earliest civilizations. Yet, freshwater ecosystems also need enough water, in the right amounts and at the right time, to remain ecologically intact and provide economically valuable commodities and services to society. Stream gages exist at many locations, some with daily records extending a century or more, providing a rich database for analysis of streamflow variability, quantification of natural variation, and detection of human alteration due to dams, land-use change, and climate. From knowledge of the relationship between streamflow and ecology over a wide range of flows and species, river scientists are beginning to develop the tools to recommend a hydrologic regime that can achieve desired ecological outcomes within a framework that also includes social and economic responses.
The increasing magnitude and frequency of undesirable events, driven by climate and anthropogenic changes, have given rise to various approaches for quantifying the resilience of regional water resource systems. However, the deficiencies of these approaches in describing linkages among subsystems and disturbance-dependent resilience have hindered the assessment and prediction of resilience in water resource management. The nexus approach enables the propagation of a disturbance to be simulated (a process called surrogate disturbance generation). An approach analogous to a unit hydrograph is developed, and resilience routing (strain flow routing), which is a novel framework and model of the dynamic resilience process, is proposed for the evaluation of a regional water resource system. The proposed framework and model are applied to the Jinghong regional water resource system. Taking a pollution event as a disturbance, the responses of the water supply, fishery and electricity subsystems are simulated to test the validity of the proposed methods. The linkages among subsystems are determined according to the sink-source dynamic using the nexus approach, and the levels of surrogate disturbance transformed from the disturbance event can be quantified by the processes of dynamic resilience evaluation. The shape of the dynamic resilience process is quantified by the parameters of unit resilience routing with disturbance independence and reflects the characteristics of the system responding to the disturbance. The proposed method helps to assess the adaptive capacity of a water system to alleviate and regulate disturbances. Furthermore, after the calibration and validation of the assumptions of linearity inherent in the method, it can also be used to predict the dynamic resilience processes of every subsystem in response to any disturbance event affecting a regional water resource system.
O trabalho versa sobre propostas de revisão de critérios ambientais de enquadramento para o licenciamento de obras de saneamento no estado de Minas Gerais, com vistas à otimizar os procedimentos em função de impactos potenciais previstos para os empreendimentos e capacidades de diluição dos corpos receptores.
This study investigates the selection of an appropriate low flow forecast model for the Meuse River based on the comparison of output uncertainties of different models. For this purpose, three data driven models have been developed for the Meuse River: a multivariate ARMAX model, a linear regression model and an Artificial Neural Network (ANN) model. The uncertainty in these three models is assumed to be represented by the difference between observed and simulated discharge. The results show that the ANN low flow forecast model with one or two input variables(s) performed slightly better than the other statistical models when forecasting low flows for a lead time of seven days. The approach for the selection of an appropriate low flow forecast model adopted in this study can be used for other lead times and river basins as well.
Most rivers in the world have been modified in their structure, form, composition or function, which has caused severe ecological and environmental alterations, such as pollution, a dramatic reduction in flow, and less environmental and recreational services. To reduce the human impact on the hydrological systems, new policies of sustainability are being developed worldwide. The aim is the sustainable and responsible use of water resources. One of them is the development and implementation of techniques to estimate environmental flows (EF) and environmental regimen flow regime (EFR). In this article, some hydrological methods used to determine EF and EFR are explained, and their implementation in the Tuluá River (Valle del Cauca-Colombia). Simulation on HEC-RAS of the given flows was performed in order to examine flow and level variability. The result showed that most hydrological methods demand constant flows over time, and are specific for certain places and aquatic species, but some others calculate a variable EFR throughout the year and with some modifications can be used in Colombian Rivers.
The natural flow hydrological characteristics (such as the magnitude, frequency,
duration, timing, and rate of change of discharge) of Alpine streams, dominated
by snowmelt and glacier melt, have been established for many years. More
recently, the ecosystems that they sustain have been described and explained.
However, natural Alpine flow regimes may be strongly modified by hydroelectric
power production, which impacts upon both river discharge and sediment transfer,
and hence on downstream flora and fauna. The impacts of barrages or dams
have been well studied. However, there is a second type of flow regulation, associated
with flow abstraction at intakes where the water is transferred laterally,
either to another valley for storage, or at altitude within the same valley for eventual
release downstream. Like barrages, such intakes also trap sediment, but
because they are much smaller, they fill more frequently and so need to be
flushed regularly. Downstream, while the flow regime is substantially modified,
the delivery of sediment (notably coarser fractions) remains. The ecosystem
impacts of such systems have been rarely considered. Through reviewing the
state of our knowledge of Alpine ecosystems, we outline the key research questions
that will need to be addressed in order to modify intake management so as
to reduce downstream ecological impacts. Simply redesigning river flows to
address sediment management will be ineffective because such redesign cannot
restore a natural sediment regime and other approaches are likely to be required
if stream ecology in such systems is to be improved.
Hydrological frequency analysis has been conducted to estimate minimum ecological flow and gage height for protection of the ecosystem in Suwannee River, Florida, USA. By comparing to observations, results indicate that both Log Pearson Type Ill and Weibull distributions provide reasonable predictions of low flow frequency curves. However, Log Pearson Type III distribution provides more accurate predictions than Weibull distribution in low flow analysis in Suwannee River. The 7Q10 method, which has been used by United States Geological Service in USA, is defined as the lowest 7-day average flow that occurs on average once every 10 years, which has been used by some water management agencies in USA for river ecological study. Based on 7Q10 method and frequency analysis, the minimum ecological flow and gage height in Suwannee River are proposed for water resources and river ecosystem managements. The study may provide a good reference for minimum ecological flow analysis in other river study sites.
The present paper investigates the effects of flow regulation on low flow conditions in the Savannah River at Augusta, GA before and after the construction of major dams and reservoirs. The Savannah River flow upstream of Augusta, GA is regulated by the operation of three large federal multipurpose projects: Hartwell Dam, Richard B. Russell Dam, and J. Strom Thurmond (also known as Clarks Hill) Dam. During low-flow periods, the operation of the dams is controlled by the drought contingency plan of the Savannah River basin. Analyses of low flow statistics at the Augusta water level gauge indicate that trends in the low flow volumes and frequencies are significantly modified after the construction of the dams. Although water level data collected before and after the construction of the dams show homogeneous properties, the data show considerable heterogeneity because of flow regulation when the full data record is considered. Low flow statistics for the period after the construction of all three dams show the Log Pearson Type 3 distribution to be the most suitable. Flow distribution also shows a considerable increase in annual minimum daily-mean flow rate compared to that prior to the construction of the dams.
Many investigators have sought to develop regional multivariate regression models which relate low-flow statistics to watershed characteristics. Normally, a multiplicative model structure is imposed and multivariate statistical procedures are employed to select suitable watershed characteristics and to estimate model parameters. Since such procedures have met with only limited success, we take a different approach. A simple conceptual stream-aquifer model is extended to a watershed scale and evaluated for its ability to approximate the low-flow behavior of 23 unregulated catchments in Massachusetts. The conceptual watershed model is then adapted to estimate low-flow statistics using multivariate regional regression procedures. Our results indicate that in central western Massachusetts, low-flow statistics are highly correlated with the product of watershed area, average basin slope and base flow recession constant, with the base flow recession constant acting as a surrogate for both basin hydraulic conductivity and drainable soil porosity.
Reliable regional low flow frequency relations were developed for central Ontario using two easily determined parameters: basin area and a dimensionless baseflow index. Regression models were developed for two measures of low flow: the median 7-day low flow and the ratio of the 20-year to the median 7-day low flow. The dependent variables were determined from single station low flow frequency analyses of 7-day low flow series at 38 hydrometric stations in central Ontario that are classified as natural flow. A second model for predicting median 7-day low flow was derived using three physically based parameters as predictor variables: area, mean basin slope and the area of permeable soil. Use of these physically based parameters is a promising alternative to using the baseflow index. While the models described apply only to the region for which they were developed, and only within specific ranges of predictor variables, the approach described could be used in other areas.
This study presents a framework to evaluate the performance of rainfall-runoff models for the estimation of low flow at sites with limited streamflow data. Estimates of low flow statistics are important for water supply, waste-load allocation, irrigation, hydropower, and ecological and habitat assessment. Paradoxically most rainfall-runoff models focus on flood simulations and use oversimplified representations of baseflow processes resulting in poor performance simulating low flow statistics. Such baseflow models cannot account for variations in topography and hydrogeology that impact baseflow processes and have limited applicability to evaluate land use and climate change impacts on low flow. Both a hillslope-storage Boussinesq model (hsB) and a kinematic wave hillslope-storage model (kw) have shown good results in simulating baseflow in synthetic hillslopes; one major challenge is how to apply these models in real watersheds. In this study hsB and kw are coupled to the Sacramento Soil Moisture Accounting (SAC-SMA) model and tested at two similarly sized watersheds in North Carolina with different watershed slopes. The partitioned kw and hsB models are also compared to the original SAC-SMA model (Sac) and SAC-SMA applied to a partitioned watershed (Sacm). Both 5 years and 1 year of full and reduced ranges of streamflow data are employed for model calibration. All partitioned models improved their estimation of low flow when calibrated to a lower range of streamflows but with kw and hsB performing slightly better at the steeper sloped watershed. The performance of the coupled models with limited streamflow data is encouraging and can potentially improve the estimation of low flow statistics at sites with limited streamflow data.
Low flow selections are essential to water resource management, water supply planning, and watershed ecosystem restoration. In this study, a new approach, namely the frequent-low (FL) approach (or frequent-low index), was developed based on the minimum frequent-low flow or level used in minimum flows and/or levels program in northeast Florida, USA. This FL approach was then compared to the conventional 7Q10 approach for low flow selections prior to its applications, using the USGS flow data from the freshwater environment (Big Sunflower River, Mississippi) as well as from the estuarine environment (St. Johns River, Florida). Unlike the FL approach that is associated with the biological and ecological impacts, the 7Q10 approach could lead to the selections of extremely low flows (e.g., near-zero flows) that may hinder its use for establishing criteria to prevent streams from significant harm to biological and ecological communities. Additionally, the 7Q10 approach could not be used when the period of data records is less than 10 years by definition while this may not the case for the FL approach. Results from both approaches showed that the low flows from the Big Sunflower River and the St. Johns River decreased as time elapsed, demonstrating that these two rivers have become drier during the last several decades with a potential of salted water intrusion to the St. Johns River. Results from the FL approach further revealed that the recurrence probability of low flow increased while the recurrence interval of low flow decreased as time elapsed in both rivers, indicating that low flows occurred more frequent in these rivers as time elapsed. This report suggests that the FL approach, developed in this study, is a useful alternative for low flow selections in addition to the 7Q10 approach. Published by Elsevier B.V.
In 2003, Reilly and Kroll examined the baseflow correlation method at river sites throughout the United States. The current study reexamines Reilly and Kroll's baseflow correlation experiment by investigating the use of different performance metrics, experi- mental parameters, and model assumptions that were not investigated by Reilly and Kroll. The goal of this study is to provide additional guidance on how to implement the baseflow correlation method in practice. The results confirm that baseflow measurements should be obtained during low flow seasons and as far as possible from runoff events. When one has only five baseflow measurements at the low-flow partial-record site, the correlation coefficient between baseflows at gauged and low-flow partial-record sites should be at least 0.9; when the number of baseflow measurements is 10 or more, the method performs adequately if the correlation coefficient is greater than 0.6. The performance of the baseflow correlation method improves as the number of baseflow measurements increases, but levels off dramatically when one has more than 10 measurements.
The effects of drought on stream invertebrates have been reviewed, but the effects of artificially reduced flows have not. We addressed this knowledge gap by reviewing the literature on the effects of natural low flows and artificially reduced flows (without complete cessation of flow). We considered the effects of low water volume on habitat conditions and on invertebrate community structure, behavior, and biotic interactions. Decreases in discharge usually cause decreased water velocity, water depth, and wetted channel width; increased sedimentation; and changes in thermal regime and water chemistry. Invertebrate abundance increases or decreases in response to decreased flow, whereas invertebrate richness commonly decreases because habitat diversity decreases. Invertebrates differ in their environmental tolerances and requirements, and any loss of habitat area or alteration of food resources from decreased flow can influence organism behavior and biotic interactions. Invertebrate drift often increases immediately after flow reduction, although some taxa are more responsive to changes in flow than others. Natural low flows and artificially reduced flows have similar effects on invertebrates, but the severity (duration and magnitude) of the flow decrease can influence invertebrate responses. Certain invertebrate taxa are especially sensitive to flow decreases and might be useful indicators for reduced flows or flow restoration. The effect of low flow on streams is an important issue, but few empirical studies of the impacts of decreased flow on stream ecosystems have been done, and more manipulative experiments are needed to understand the ecological consequences of decreased flow.
7Q10 streamflow estimates used to support modeling and data analysis under the Clean Water Act national pollution discharge elimination system and total maximum daily load programs can have direct environmental and economic impacts. Thus it is important that 7Q10 streamflow always be reported together with confidence limits indicating the reliability of the estimate. In practice this is rarely done. This technical note presents a bootstrap approach for computing 7Q10 confidence limits from data and compares it to an empirical method. A case study using randomly selected subsets of data from five rivers in Idaho is used to evaluate the two methods. While both methods exhibit the expected increase in confidence interval as fewer years of data used, the bootstrap approach generally results in wider confidence intervals than does the empirical method. The opposite appears to be true in cases where fewer than 15years of data are used or when the data are positively skewed. As most streamflow data are positively skewed short records, the bootstrap approach can generally be thought of as a more conservative means for estimating 7Q10 confidence intervals.
Although the Pearson type 3 (P3) is one of the basic models in
statistical hydrology, its use to model untransformed data has been
restrained because of difficulties encountered in fitting this
distribution by traditional methods. In this paper an adaptive
estimation procedure of mixed moments for the P3 family is introduced
which is based on several fractional moments of the exponentially
transformed data and the mean of the original data. The procedure is
easy to implement in small samples and is valid over the entire
parameter space. Explicit formulae for the variances and covariances of
parameter estimators and of the variance of the T-year event are
derived. In addition, two variants of the new procedure are compared
with two versions of the method of moments and a version of the method
of conditional moments via Monte Carlo simulation. With samples
generated from P3 populations, it is found that one of the variants of
the new procedure is the best overall method in estimating 100-year
flood events, and the other variant is best in estimating the median and
10-year low-flow events. The good performance of these two variants is
also observed in samples generated from alternatives to P3
distributions. A modification of the procedure is also introduced and
investigated when a prior assumption of positive skewness is adopted.
Design stream flows are frequently used in water pollution control programs to provide adequate protection against pollutant exposure periods of a given duration. An analysis of the effect that simple stream flow dilution has on the x-day average concentration of a pollutant demonstrates that the x-day harmonic mean flow is a more meaningful statistic to use in computing design flows than is the customary arithmetic mean flow. The significance of this result was examined by computing design flows for 60 rivers throughout the country. Substantial differences were found for the mean daily flow a design flow suggested for water quality criteria based on protecting human health against lifetime exposures. The harmonic mean daily flow is typically 20-60% of the arithmetic mean daily flow. Data from the 60 rivers showed very good agreement with a theoretical relationship between the arithmetic, harmonic, and geometric means of a lognormal distribution.
We propose a probabilistic framework for modeling extreme events such as annual maximum floods, and annual low flows. The model assumes that the underlying data sequence exhibits abrupt changes or shifts in the mean, and the data are skewed and autocorrelated. Thus, the stochastic model is assumed to shift abruptly from one "stationary" state to another one around a long-term mean. The proposed modeling framework is based upon the previously suggested shifting mean (SM) models, where the process was assumed to be autocorrelated but the marginal distribution was normally distributed and as a result the model skewness was zero. The main objective of the research reported herein has been to further extend the referred SM models to incorporate skewed marginal distributions so that they can be applicable for frequency analysis of extreme events. For this purpose, two SM models and alternative estimation procedures were developed using the generalized extreme value, Pearson III, and Gumbel distributions. The proposed models utilizing skewed distributions are successfully applied for determining extreme quantiles of the quarter-monthly maximum annual out-flows of Lake Ontario and the 7 day annual low flows for the Paraná River in Argentina. Journal of Hydrologic Engineering
The volume and duration of low-flow events in river channels are important characteristics for water management and the design of hydraulic structures. These extreme low-flow characteristics were studied separately, as identically distributed random variables, on a time interval of 1 year. A statistical analysis was performed on the low-flow data series of Lepreau River, station 01AQ001 (New-Brunswick, Canada). The observed characteristics were compared with the theoretical results using the Kolmogorov-Smimov and (or) χ2 tests. It was generally concluded that the proposed model adequately fits the low-water phenomenon.
Estimates of low streamflow statistics are required for a variety of water resource applications. At gauged river sites, the estimation of low streamflow statistics requires estimation of annual n-day minimum streamflows, selection of a probability distribution to describe annual minimums, and estimation of the distribution's parameters. Using L-moment diagrams, the ability of various probabil- ity distributions to describe low streamflow series was examined at 1,505 gauged river sites in the United States. A weighted distance statistic was developed to compare the goodness-of-fit of different probability distributions for describing low streamflow series. Com- pared to perennial streamflow sites, a shift of L-moments ratios was observed at intermittent river sites where discharge is sometimes reported as zero. An analytical experiment compared the observed shifts in L-moment ratios at intermittent sites with theoretical L-moment ratio shifts for a number of real- and log-spaced probability distributions. Results of these experiments indicate that Pearson Type III and the 3-parameter lognormal distributions should be the recommended distributions for describing low streamflow statistics in the United States at intermittent and nonintermittent ~perennial! sites, respectively.
A regional hydrologic model is developed for estimating flow-duration curves at ungauged and unregulated basins in Massachusetts. Flow-duration curves often exhibit complex shapes, requiring probability density functions with three or more parameters. This study approximates the lower half of daily flowduration curves using a two-parameter lognormal probability density function. A conjugate gradient algorithm is employed to fit lognormal density functions to the lower half of observed flow-duration curves at 23 basins. Regional regression equations are developed to describe the lognormal model parameters in terms of easily measured basin characteristics. The resulting regional flow-duration model only requires estimates of the watershed area, and a basin relief parameter, both of which are easily obtained from U.S. Geological Survey 7.5-min quadrangle maps. In addition, confidence intervals are derived for flow-duration curves estimated at ungauged sites. A validation experiment reveals that the resulting regional hydrologic model can provide remarkably precise estimates of a flow-duration curve at an ungauged site, considering the simplicity of the model and its ease of application.
Low-flow studies ore needed to quantify the effects of water consumption on stream flow, water quality, groundwater resources, and contaminant transport. The low-flow water balance of a river in a cold region is simplified in winter because evapotranspiration is negligible, irrigation water withdrawals and diversions are halted, and precipitation occurs largely as snow, minimizing the spatial arid temporal variability of runoff. We investigated the monthly low-flow water balance of White River (Neb. and S. Dak.) reaches over seven consecutive winters. Water going into or out of storage as ice or melt, obtained with an air temperature index model, can be a dominant component of the water balance. The point estimate method is used to account for parameter uncertainty and variability, providing the mean, variance, and limits of dependent variables such as water storage as ice and inflow from a subbasin. Negative surface water yield from several-thousand-square-kilometer subbasins occurred regularly through the period, indicating a significant flow from the river to the alluvial aquifers. The winter water balance results suggest either a perched river or a coupled surface water-groundwater hydrologic system in particular subbasins, consistent with the field investigations of Rothrock (1942). The winter flow exchange between The surface and subsurface can be used to estimate the annual exchange for both hydrologic conditions.
The climate sensitive analysis of potential climate change on streamflow has been conducted using a hydrologic model to identify hydrologic variability associated with climate scenarios as a function of perturbed climatic variables (e.g. carbon dioxide, temperature, and precipitation). The interannual variation of water resources availability as well as low flow frequency driven by monsoonal time shifts have been investigated to evaluate the likelihood of droughts in a changing climate. The results show that the timing shift of the monsoon window associated with future climate scenarios clearly affect annual water yield change of − 12 and − 8% corresponding to 1-month earlier and 1-month later monsoon windows, respectively. Also, a more severe low flow condition has been predicted at 0·03 m3/s as opposed to the historic 7Q10 flow of 1·54 m3/s given at extreme climate scenarios. Copyright © 2011 John Wiley & Sons, Ltd.
Regional hydrologic procedures such as generalized least squares regression and streamflow record augmentation have been advocated for obtaining estimates of both flood-flow and low-flow statistics at ungaged sites. While such procedures are extremely useful in regional flood-flow studies, no evaluation of their merit in regional low-flow estimation has been made using actual streamflow data. This study develops generalized regional regression equations for estimating the d-day, T-year low-flow discharge, Qd, t, at ungaged sites in Massachusetts where d = 3, 7, 14, and 30 days. A two-parameter lognormal distribution is fit to sequences of annual minimum d-day low-flows and the estimated parameters of the lognormal distribution are then related to two drainage basin characteristics: drainage area and relief. The resulting models are general, simple to use, and about as precise as most previous models that only provide estimates of a single statistic such as Q7,10. Comparisons are provided of the impact of using ordinary least squares regression, generalized least squares regression, and streamflow record augmentation procedures to fit regional low-flow frequency models in Massachusetts.
Four methods for estimating the 7-day, 10-year and 7-day, 20-year low flows for streams are compared by the bootstrap method. The bootstrap method is a Monte Carlo technique in which random samples are drawn from an unspecified sampling distribution defined from observed data. The nonparametric nature of the bootstrap makes it suitable for comparing methods based on a flow series for which the true distribution is unknown. Results show that the two methods based on hypothetical distributions (Log-Pearson III and Weibull) had lower mean square errors than did the Box-Cox transformation method or the Log-Boughton method which is based on a fit of plotting positions.
ResearchGate has not been able to resolve any references for this publication.