Changes in monthly surface area, water level, and storage of 194 lakes and reservoirs in the Yangtze River Basin during 1990-2021 using multisource remote sensing data.

Long-term, high spatiotemporal resolution of surface water area, water level, and storage changes in the Yangtze River Basin (YRB) has great scientific and practical importance for improving the management of water resources. Here, three distinct area estimations were first derived using the water classification enhancement method, automated water extraction method based on random forest, and the modified normalized difference water index. The optimized area data was determined by comparing against Sentinel-2 with the minimum root mean square error. A new area data was constructed with the optimized area as the primary data, while the remaining datasets were employed to fill in gaps. The elevation-area relationship was used to derive monthly water level. Changes in water storage were calculated by applying the pyramidal frustum formula from surface water area and water level data. Finally, a new comprehensive dataset of the monthly area, level, and storage changes in the 119 lakes and 75 reservoirs across the YRB with area larger than 10 km2 from 1990 to 2021 were first reconstructed. The spatiotemporal trends of surface water area/level/storage in lakes and reservoirs over 11 sub-basins of the YRB were quantified from 1990 to 2021, as well as before (1990-2003) and after (2003-2021) the construction of the Three Gorges Dam (TGD). During 1990-2021, there was a marked decrease in surface water area/level/storage in most of the YRB sub-basins, which contain 79 % of the lakes and 30 % of the reservoirs. After TGD was constructed, the surface water in lakes decreased by 10 %, while that of reservoirs remained consistent with the pre-construction. The surface water area/level/storage in the lower sub-basins of YRB exhibited a decline to an upward trend before and after the construction of TGD. This study provides a new comprehensive dataset for understanding the dynamic changes of water resource and climate change.

Detection of extreme hydrological droughts in the poyang lake basin during 2021-2022 using GNSS-derived daily terrestrial water storage anomalies.

Poyang Lake is the largest freshwater lake in China, serving as a natural reservoir and playing a paramount role in climate regulation, ecological environment, and water resource management. However, in recent years, Poyang Lake has approached desiccation multiple times, with severe droughts becoming increasingly common. Consequently, precise quantification and analysis of the terrestrial water storage anomalies (TWSA) and drought characteristics of the Poyang Lake basin (PLB) are of profound scientific and practical significance. This paper, for the first time, utilizes data for the period 2021-2022 from 77 newly-established GNSS observation stations in the PLB to precisely determine its vertical crustal displacement, invert daily and monthly TWSA, and investigate extreme hydrological drought. The results reveal the following: 1) The annual amplitude range of vertical surface displacements at GNSS stations in the Poyang Lake basin is from 7 to 14 mm, with the most substantial seasonal vertical displacements occurring during the months of June and July; 2) monthly GNSS-TWSA maintains a commendable consistency with TWSA data obtained from the Gravity Recovery and Climate Experiment (GRACE), the Global Land Data Assimilation System (GLDAS), and precipitation, with correlation coefficients of 0.67, 0.55, and 0.62, respectively; 3) at daily scale, the GNSS-derived Drought Severity Index (GNSS-DSI) accurately recorded the severity and intensity of eight drought events in the PLB during 2021-2022, in particular the period of extensive drought between October 2021 and February 2022, when drought intensity reaching a notable 1.03, which is classified as an extreme and prolonged drought event. Additionally, at local temporal scales, daily GNSS-DSI exhibits heightened sensitivity to drought signals. This study provides novel technological tools and datasets for multi-source satellite-based drought monitoring in the PLB.

Divergent spatiotemporal variability of terrestrial water storage and eight hydroclimatic components over three different scales of the Yangtze River basin.

Terrestrial water storage anomaly (TWSA) from Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-on was first exacted by using the forward modeling (FM) method at three different scales over the Yangtze River basin (YRB): whole basin, three middle sub-basins, and eleven small sub-basins (total 15 basins). The spatiotemporal variability of eight hydroclimatic variables, snow water storage change (SnWS), canopy water storage change (CnWS), surface water storage anomaly (SWSA), soil moisture storage anomaly (SMSA), groundwater storage anomaly (GWSA), precipitation (P), evapotranspiration (ET), and runoff (R), and their contribution to TWSA were comprehensively investigated over the YRB. The results showed that the root mean square error of TWS change after FM improved by 17 %, as validated by in situ P, ET, and R data. The seasonal, inter-annual, and trend revealed that TWSA over the YRB increased during 2003-2018. The seasonal TWSA signal increased from the lower to the upper of YRB, but the trend, sub-seasonal, and inter-annual signals receded from the lower to the upper of YRB. The contribution of CnWS to TWSA was small over the YRB. The contribution of SnWS to TWSA occurs mainly in the upper of YRB. The main contributors to TWSA were SMSA (~36 %), SWSA (~33 %), and GWSA (~30 %). GWSA can be affected by TWSA, but other hydrological elements may have a slight impact on groundwater in the YRB. The primary driver of TWSA over the YRB was P (~46 %), followed by ET and R (both ~27 %). The contribution of SMSA, SWSA, and P to TWSA increased from the upper to the lower of YRB. R was the key driver of TWSA in the lower of YRB. The proposed approaches and results of this study can provide valuable new insights for water resource management in the YRB and can be applied globally.

Using GRACE to Detect Groundwater Variation in North China Plain after South-North Water Diversion.

The gravity recovery and climate experiment (GRACE) and its Follow-On mission provide a versatile tool for monitoring groundwater depletion in North China Plain (NCP). However, intermittent data gaps and inherent coarse spatial resolution have restricted the continuous detection of regional groundwater storage anomaly (GWSA) after 2014, the period of interest during the implementation of the south-to-north water diversion middle route project (SNWDP). Here, we investigated the spatiotemporal changes of GWSA in the NCP during 2004 to 2020 based on continuous downscaled GRACE data. First, we derived the continuous terrestrial water storage anomaly from six GRACE and Follow-On solutions (i.e., spherical harmonics (SH) and mass concentration [mascon] solutions). Second, we employed a long short-term memory (LSTM) model and water balance equation to downscale GWSA (i.e., 0.25° × 0.25°). Lastly, we investigated its spatiotemporal characteristics before (2004 to 2014) and after (2015 to 2020) the SNWDP operation. We show the applicability of the continuous downscaled GWSA to capture the characteristics of in situ measurements. The GWSA detects groundwater depletion at a significant (p < 0.05) rate of -17.09 ± 1.80 (SH) and -17.87 ± 1.65 (mascon) mm/a during 2004 to 2014, but a recovering trend of 7.18 ± 3.98 (SH) and 8.23 ± 4.99 (mascon) during 2015 to 2018. The subsequent groundwater extraction and precipitation reduction from 2019 to 2020, resulted in the decreasing trend of GWSA from 2015 to 2020, which is -19.11 ± 8.75 (SH) and -19.72 ± 9.08 mm/a (mascon), respectively. Spatially, the overall depletion trends become nonsignificant along the canals of SNWDP compared to the period 2004 to 2014, and groundwater recovering with trends <6 mm/a near Beijing and Tianjin are detected by the mascon solution during 2015 to 2020.

Groundwater Storage Change in the Jinsha River Basin from GRACE, Hydrologic Models, and In Situ Data.

Groundwater plays a major role in the hydrological processes driven by climate change and human activities, particularly in upper mountainous basins. The Jinsha River Basin (JRB) is the uppermost region of the Yangtze River and the largest hydropower production region in China. With the construction of artificial cascade reservoirs increasing in this region, the annual and seasonal flows are changing and affecting the water cycles. Here, we first infer the groundwater storage changes (GWSC), accounting for sediment transport in JRB, by combining the Gravity Recovery and Climate Experiment mission, hydrologic models and in situ data. The results indicate: (1) the average estimation of the GWSC trend, accounting for sediment transport in JRB, is 0.76 ± 0.10 cm/year during the period 2003 to 2015, and the contribution of sediment transport accounts for 15%; (2) precipitation (P), evapotranspiration (ET), soil moisture change, GWSC, and land water storage changes (LWSC) show clear seasonal cycles; the interannual trends of LWSC and GWSC increase, but P, runoff (R), surface water storage change and SMC decrease, and ET remains basically unchanged; (3) the main contributor to the increase in LWSC in JRB is GWSC, and the increased GWSC may be dominated by human activities, such as cascade damming and climate variations (such as snow and glacier melt due to increased temperatures). This study can provide valuable information regarding JRB in China for understanding GWSC patterns and exploring their implications for regional water management.

Detecting Water Diversion Fingerprints in the Danjiangkou Reservoir from Satellite Gravimetry and Altimetry Data.

The Danjiangkou Reservoir (DJKR) is the freshwater source for the Middle Route of the South-to-North Water Diversion Project in China, and its water level and storage changes are important for water resource management. To maximize the potential capacity of the Gravity Recovery and Climate Experiment (GRACE) mission, an improved Lagrange multiplier method (ILMM) is first proposed to detect terrestrial water storage anomalies (TWSA) in the small-scale basin (DJKR). Moreover, for the first time, water diversion fingerprints are proposed to analyze the spatiotemporal pattern of the TWSA in the DJKR. The results indicate that the increased water level and storage signals due to the DJKR impoundment in 2014 can be effectively detected by using the ILMM, and they agree well with the results from altimetry and in situ data. Additionally, the water diversion fingerprints due to the DJKR impoundment are inferred, and describe the progression of spatiotemporal variability in water storage. The results show that water storage decreased in the upper Hanjiang River and increased in the DJKR as well as to the east of it during the period 2013-2015. Our research provides a scientific decision-making basis for monitoring the water resources of the DJKR and managing the South-to-North Water Diversion Project.

Retrieving Groundwater Depletion and Drought in the Tigris-Euphrates Basin Between 2003 and 2015.

Quantitative estimates of the groundwater depletion and droughts in the Tigris-Euphrates Basin (TEB) can be useful for sustainably managing its water resources. Here, data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission are used to infer the monthly changes in the total water storage of the TEB from January 2003 to December 2015. Additionally, the data of altimetry and output from land surface models are used to remove the contributions from lake water changes and other hydrological factors to obtain the total groundwater depletion (TGWD), human-driven groundwater depletion (HGWD), and climate-driven groundwater depletion. We conclude that an alarming rate of decrease in the total water storage and the loss of TGWD have an "accelerating" trend, as the trend during 2007 to 2015 was 3.6 times that during 2003 to 2006. Moreover, the HGWD is 116.09 Gt, which accounts for 98% of the TGWD. Finally, the total storage deficit index (TSDI) is derived from the GRACE data to characterize the drought of the TEB. The results show that TSDI agrees well with the actual drought rather than the Palmer drought severity index (PDSI) and that the TEB has been undergoing a severe drought since September 2007 according to both the TSDI and PDSI. The research in this study provides an effective and unique method for understanding the hydrological processes and sustainable use of water resources in regions or countries with little data, which is essential for more efficient, sustainable, and cross-boundary cooperative water resource management.

Annual variations of monsoon and drought detected by GPS: A case study in Yunnan, China.

The Global Positioning System (GPS) records monsoonal precipitable water vapor (PWV) and vertical crustal displacement (VCD) due to hydrological loading, and can thus be applied jointly to diagnose meteorological and hydrological droughts. We have analyzed the PWV and VCD observations during 2007.0-2015.0 at 26 continuous GPS stations located in Yunnan province, China. We also obtained equivalent water height (EWH) derived from the Gravity Recovery And Climate Experiment (GRACE) and precipitation at these stations with the same period. Then, we quantified the annual variations of PWV, precipitation, EWH and VCD and provided empirical relationships between them. We found that GPS-derived PWV and VCD (positive means downward movement) are in phase with precipitation and GRACE-derived EWH, respectively. The annual signals of VCD and PWV show linearly correlated amplitudes and a two-month phase lag. Furthermore, the results indicate that PWV and VCD anomalies can also be used to explore drought, such as the heavy drought during winter/spring 2010. Our analysis results verify the capability of GPS to monitor monsoon variations and drought in Yunnan and show that a more comprehensive understanding of the characteristics of regional monsoon and drought can be achieved by integrating GPS-derived PWV and VCD with precipitation and GRACE-derived EWH.