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Hydrologic variation affects many functions of wetlands. Rapidly and accurately measuring hydrologic dynamics in a wetland watershed has become a fundamental need for estimating functional changes of wetlands. The satellite altimeters have become good data sources that can complement the measurements of gauge stations. As a case project applied in...
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... Since the 1990s the use of remote sensing techniques in monitoring of water level variations has become a powerful tool, considering the amount of ungauged waterbodies all over the world. Satellite Altimetry has been successfully used to measure in oceans (Birol et al., 2006;Gómez-Enri et al., 2007;Laiz et al., 2012;López-García et al., 2019), lakes (Medina et al., , 2010, rivers (Koblinsky et al., 1993;Da Silva et al., 2010;Becker et al., 2014;Sulistioadi et al., 2015;Chembolu et al., 2019;Apaéstegui et al., 2009;Fassoni-Andrade et al., 2021) and wetland stages (Cai and Ji, 2009;Lee et al., 2009;Da Silva et al., 2012;Ovando et al., 2018). The progress achieved by this methodology in the fields of global and coastal oceanography, hydrology, geodesy, and cryospheric sciences has been very important to advancing scientific knowledge in ocean dynamics and the Earth observation from space (International Altimetry Team, 2021;Aviso, 2022aAviso, , 2022b. ...
The present work aims to analyze the variability of the sea level of the Peruvian coast with time series over a long observation period (Seventy-eight years, from 1942 to 2019). Data came from the Talara, Callao and Matarani tide gauge stations located at the north, center and south of the coast. Variations of sea level as well as air and seawater surface temperature were analyzed. Among the different scenarios studied, a sea level rise of 6.79, 4.21 and 5.16 mm/year for Talara, Callao and Matarani, respectively was found during the 1979–1997 nodal cycle. However, these results decreased significantly during the next cycle (1998–2016) until values of 1.53, 2.16 and 1.0 mm/year for Talara, Callao and Matarani, respectively. Thus, it has been demonstrated that sea level rise are highly dependent on the time interval chosen. Moreover, large interannual changes of up to 200 mm/year are observed, due to recurring phenomena, such as “El Niño”. On the other hand, the trends obtained are slightly lower than those shown by the IPCC up until 2006 but significantly higher values have been observed. Finally, the results presented herein show the necessity of a local study of the sea level variability at the coastal areas.
... Since the 1990s the use of remote sensing techniques in monitoring of water level variations has become a powerful tool, considering the amount of ungauged waterbodies all over the world. Satellite Altimetry has been successfully used to measure in oceans (Birol et al., 2006;Gómez-Enri et al., 2007;Laiz et al., 2012;López-García et al., 2019), lakes (Medina et al., , 2010, rivers (Koblinsky et al., 1993;Da Silva et al., 2010;Becker et al., 2014;Sulistioadi et al., 2015;Chembolu et al., 2019;Apaéstegui et al., 2009;Fassoni-Andrade et al., 2021) and wetland stages (Cai and Ji, 2009;Lee et al., 2009;Da Silva et al., 2012;Ovando et al., 2018). The progress achieved by this methodology in the fields of global and coastal oceanography, hydrology, geodesy, and cryospheric sciences has been very important to advancing scientific knowledge in ocean dynamics and the Earth observation from space (International Altimetry Team, 2021;Aviso, 2022aAviso, , 2022b. ...
The present work aims to analyze the variability of the sea level of the Peruvian coast with time series over a long observation period (Seventy-eight years, from 1942 to 2019). Data came from the Talara, Callao and Matarani tide gauge stations located at the north, center and south of the coast. Variations of sea level as well as air and seawater surface temperature were analyzed. Among the different scenarios studied, a sea level rise of 6.79, 4.21 and 5.16 mm/year for Talara, Callao and Matarani, respectively was found during the 1979–1997 nodal cycle. However, these results decreased significantly during the next cycle (1998–2016) until values of 1.53, 2.16 and 1.0 mm/year for Talara, Callao and Matarani, respectively. Thus, it has been demonstrated that sea level rise are highly dependent on the time interval chosen. Moreover, large interannual changes of up to 200 mm/year are observed, due to recurring phenomena, such as “El Niño”. On the other hand, the trends obtained are slightly lower than those shown by the IPCC up until 2006 but significantly higher values have been observed. Finally, the results presented herein show the necessity of a local study of the sea level variability at the coastal areas.
... Lake Poyang is located in the north of Jiangxi Province, China (Fig. 1). As its water level is higher in the south, Lake Poyang usually flows northward and discharges to the Yangtze River from Hukou (Cai and Ji 2009;Wu and Liu 2014). The main water supply of the lake includes local precipitation, inflows from five main tributaries (i.e. ...
Understanding water storage changes in Lake Poyang, the largest freshwater lake in China, is essential for local hydro-ecological assessments and water resource management. The integration of multi-mission satellite data, hydrological models, and in situ measurements allows for a comprehensive estimate of Lake Poyang’s storage variations. We here estimated Lake Poyang water storage changes during the recent decade by using inundation areas mapped from optical satellite imagery and water levels measured by satellite radar altimetry and gauging stations. The amplitudes of seasonal variation from altimetry data are smaller than those from station measurements. This is likely attributed to their low temporal resolutions and limited footprint coverage, together with a complex surface gradient over Lake Poyang. The residual fields between land water storage changes assessed by the GRACE satellites and simulated by two hydrological models (GLDAS Noah and WGHM) were applied to estimate Poyang water storage changes. Leakage errors in the GRACE-model residuals are further corrected by a constrained forward modeling method, resulting in recovered water storage trends ∼66 times of the uncorrected signals. Water level changes estimated by different methods are then compared. Results show that level changes inverted from recovered storage variations by GRACE-GLDAS and GRACE-WGHM are significantly larger than those from satellite altimetry and in situ measurements. This indicates that the combination of GRACE observation and global hydrological modeling is likely insufficient to estimate accurate water storage changes in Lake Poyang. Our methods and results provide a valuable example of using integrated methods for monitoring water storage changes in highly dynamic fluvial lake systems.
... Poyang Lake wetland is recognized to be among the most important wetlands of the world for its extraordinary biodiversity and conservation value. Different types of remote sensing data have been applied to reveal the spatial and temporal patterns of water extents and levels and the responses of vegetation and habitats, as well as the effects of sand dragging, sedimentation, and the contamination of this unique floodpath lake/wetland combination [66][67][68][69][70][71][72][73][74][75][76][77][78][79]. ...
Monitoring of changing lake and wetland environments has long been among the primary focus of scientific investigation, technology innovation, management practice, and decision-making analysis. Floodpath lakes and wetlands are the lakes and associated wetlands affected by seasonal variations of water level and water surface area. Floodpath lakes and wetlands are, in particular, sensitive to natural and anthropogenic impacts, such as climate change, human-induced intervention on hydrological regimes, and land use and land cover change. Rapid developments of remote sensing science and technologies, provide immense opportunities and capacities to improve our understanding of the changing lake and wetland environments. This special issue on Remote Sensing of Floodpath Lakes and Wetlands comprise featured articles reporting the latest innovative research and reflects the advancement in remote sensing applications on the theme topic. In this editorial paper, we review research developments using state-of-the-art remote sensing technologies for monitoring dynamics of floodpath lakes and wetlands; discuss challenges of remote sensing in inventory, monitoring, management, and governance of floodpath lakes and wetlands; and summarize the highlights of the articles published in this special issue.
... Gao et al., 2014) and shortage of long-term measurements, sediment input from these tributaries to the Poyang Lake are not considered in our study. The flow direction through Hukou is mainly from Poyang Lake to the Changjiang River, with approximately 14 days of inverse directed flows occurring approximately 2-3 times per year (Cai & Ji, 2009), which is around 7% of the sediment output and has a limited effect on the net sediment output. ...
Lakes, as key recorders of sedimentation regime variations, have undergone dramatic erosion/deposition worldwide in response to global warming and increasing anthropogenic interference. Poyang Lake, China's largest freshwater lake, has not escaped these variations. Herein, we show that the sedimentation in Poyang Lake has likely undergone a unique phase shift from sediment sink (annually storing 421 × 10⁴ t) during 1960–1999 to sediment source (yearly losing 782 × 10⁴ t) during 2000–2012, with respect to the Changjiang (Yangtze) River. In comparison with sedimentation during 1960–1999, Poyang Lake sedimentation during the period 2000–2012 is characterized by no deposition during the flood season and enhanced erosion during the dry season. Furthermore, Poyang Lake's largest delta, the Ganjiang Delta, prograded at a rate of 32.7 m/a from 1983 to 1996, which increased to 52.8 m/a from 1996 to 2005 but dropped significantly to 1.7 m/a from 2005 to 2015. A sediment core collected in the shallow-water shoal of the central lake indicates a stable increase in sedimentation flux from 1960 to 2002, with a mean value of 0.27 g/(cm²·a), followed by a decline in sedimentation flux after 2002. Our findings show that the tributary sediment input from the lake catchment dominated the sedimentation of Poyang Lake prior to 2000, when it was significantly larger than the sediment output to the Changjiang River. However, thereafter, the contribution of tributary sediment to the output dropped by 50%, and the rest has been provided by the lake itself. Namely, channels along Poyang Lake's waterway became the additional source of the lake's sediment output in the 2000s.
... Their results are promising but a comprehensive validation of the results is missing. Moreover, some dedicated studies exist for the Louisiana wetlands (e.g., Lee et al. [20] and Khajeh et al. [21]) and Poyang Lake watershed [22]. Most of these studies do not provide satisfying results or lack comprehensive validations. ...
Wetlands are important ecosystems playing an essential role for continental water regulation and the hydrologic cycle. Moreover, they are sensitive to climate changes as well as anthropogenic influences, such as land-use or dams. However, the monitoring of these regions is challenging as they are normally located in remote areas without in situ measurement stations. Radar altimetry provides important measurements for monitoring and analyzing water level variations in wetlands and flooded areas. Using the example of the Pantanal region in South America, this study demonstrates the capability and limitations of ENVISAT radar altimeter for monitoring water levels in inundation areas. By applying an innovative processing method consisting of a rigorous data screening by means of radar echo classification as well as an optimized waveform retracking, water level time series with respect to a global reference and with a temporal resolution of about one month are derived. A comparison between altimetry-derived height variations and six in situ time series reveals accuracies of 30 to 50 cm RMS. The derived water level time series document seasonal height variations of up to 1.5 m amplitude with maximum water levels between January and June. Large scale geographical pattern of water heights are visible within the wetland. However, some regions of the Pantanal show water level variations less than a few decimeter, which is below the accuracies of the method. These areas cannot be reliably monitored by ENVISAT.
... Satellite altimetry was used for monitoring water level variations across the Lake Chad basin comprising a region of permanent water of about 2000 km 2 surrounded by seasonally inundated marshlands that may occupy nearly 10000 km 2 during the wet season (Birkett 2000, Coe andBirkett 2004). Cai and Ji (2009) reported that the altimetry heights have a good accuracy and can supplement the ungauged area in Poyang lake wetlands having surface area of nearly 4078 km 2 . Salami and Nnadi (2012) reported that the altimetric levels extracted for Kainji reservoir, one of the Africa's largest reservoir with a surface area of 1270 km 2 showed RMSE errors ranged between 0.50 to 0.83 m for both the seasons. ...
... ICE-I products that uses a robust retracking can improve the quality of water level heights for the most cases (Schwatke et al. 2015). The altimetric height of the water surface S h was derived using the following formula (Cai and Ji 2009): S h = S a -(R m + I + W tm od + D t + P t + E t ) -G ...
Reservoir water levels extracted from SARAL/AltiKa GDR data for the period 2013-2014 and water spread areas delineated from Resourcesat P6-AWiFS sensor and RISAT 1 microwave data corresponding to SARAL/AltiKa cycles were used for assessment of reservoir capacity in the Mayurakshi reservoir, Jharkhand state, India. It was found that the reservoir capacity based on the SARAL is around 474.62 Mm3 in comparison to in situ based estimate i.e. around 486.6 Mm3, indicating variation of < 3%. Further, comparison of these estimates computed using SARAL and in situ with original reservoir capacity (547.59 Mm3) indicated loss of reservoir capacity is around 13.33% and 11.14% respectively within a span of 59 years. The hydrographic survey in the year 1999-2000 also proved that the storage capacity has reduced from 547.6 Mm3 in 1955 to 474.8 Mm3 indicating loss of nearly 13.3% of total live capacity over period of 45 years.
... Radar altimeter satellites provide a significantly high temporal resolution (10-35 days) and vertical accuracy (centimeter-level) and can provide fairly good information about water levels (Cai and Ji, 2009;Frappart et al., 2006;Lu et al., 2009;Zakharova et al., 2014). The nominally 18-Hz ENVISAT altimetry is employed to validate water-level changes obtained from interferometric phase measurements. ...
... km during the wet season (Birkett 2000 andCoe andBirkett 2004). Cai and Ji (2009) reported that the altimeter derived water level have a good accuracy and can supplement the ungauged area in Poyang lake wetlands having surface of nearly 4078 sq.km. Salami and Nnadi (2012) reported that the altimetric levels extracted for Kainji reservoir, one of the Africa's largest reservoirs with a surface area of 1270 km 2 showed RMSE errors ranged between 0.50 and 0.83 m for both the seasons. ...
... In this study, archived radar altimetric range measurements for the period 2013-2014 (archived in the Geophysical Data Records) from the SARAL/AltiKa together with various geophysical corrections were used to make a full reconstruction of altimetric water levels for the study reservoir. For processing altimetry data, the water surface height S h was derived following Cai and Ji (2009): ...
Present study aims at monitoring of water levels for Mayurakshi reservoir (~68 sq. km) located in the Jharkhand
state, India using Geophysical Data Records (GDR) data from SARAL/AltiKa launched in February, 2013. Reservoir water levels for the period April, 2013 to December 2014 were derived from space using SARAL/AltiKa data. The absolute average difference, standard deviation and the Root Mean Square Error (RMSE) between altimetric data and gauge read ings were 0.49, 0.29 and 0.56 m respectively. The accuracy of the relative water levels ranges between 0.008 and 0.8 m with a mean of 0.34 m, standard deviation of 0.27 m and RMSE of 0.44 m. Resulting time series of relative height changes and the amplitude variations are identical for most of the study period except during low stage, linked to the fact that some reservoir waveforms are season dependent. The results highlight the applicability of the SARAL/AltiKa data for monitoring small to medium reservoirs having surface area less than 100 sq. km.
... There is a significant difference in benthic topography among the different areas of the lake. The average topography elevation generally decreases from the south (>16 m) to the north (<12 m) (Cai and Ji, 2009). In addition, the varying discharges from upstream catchments into Poyang Lake and lake discharge into Yangtze River add further complexity to the variation in lake area (Guo et al., 2012). ...
... Zone III (west branch of the Ganjiang and Xiushui alluvial delta zone), Zone IV (central and south branches of the Ganjiang and Fuhe alluvial delta zone) and Zone V (Raohe alluvial delta zone) are separated by five tributaries (Wu and Liu, 2014). Normally, the water level in the south is higher than in the north (Cai and Ji, 2009). However, from July to September, the elevated water level of the Yangtze River may impede the south-north water flow and the water level becomes similar across the lake's extent (Shankman et al., 2006). ...
Keywords: Poyang Lake Inundation frequency Water variation rate MODIS Geographical Information System s u m m a r y Poyang Lake is the largest freshwater lake in China, with high morphological complexity from south to north. In recent years, the lake has experienced expansion and shrinkage processes over both short-and long-term scales, resulting in significant hydrological, ecological and economic problems. Exactly how and how rapidly the processes of spatial change have occurred in the lake during the expansion and shrinkage periods is unknown. Such knowledge is of great importance for policymakers as it may help with flood/drought prevention, land use planning and lake ecological conservation. In this study, we investigated the spatial–temporal distribution and changing processes of inundation in Poyang Lake based on Moderate Resolution Imaging Spectroradiometer (MODIS) Level-1B data from 2000 to 2011. A defined water variation rate (WVR) and inundation frequency (IF) indicator revealed the water surface submersion and exposure processes of lake expansion and shrinkage in different zones which were divided according to the lake's hydrological and topographic features. Regional differences and significant seasonality variability were found in the annual and monthly mean IF. The monthly mean IF increased slowly from north to south during January–August but decreased quickly from south to north during Sep-tember–December. During the lake expansion period, the lake-type water body zone (Zone II) had the fastest expansion rate, with a mean monthly WVR value of 34.47% in February–March, and was followed by the channel-type water body zone (Zone I) in March–May (22.47%). However, during the lake shrink-age period, rapid shrinkage first appeared around the alluvial delta zones in August–October. The sequence of lake surface shrinkage from August to December is exactly opposite to that of lake expansion from February to July. These complex inundation characteristics and changing process were driven by the high temporal variability of the river flows, the morphological diversity of the benthic landforms and the patterns of water movement. These results provide a foundation for basic hydrological and ecological studies and are valuable for the conservation and management of water resources in Poyang Lake.
