Model estimates of China's terrestrial water storage variation due to reservoir operation

Understanding the role of reservoirs in the terrestrial water cycle is critical to support the sustainable management of water resources especially for China where reservoirs have been extensively built nationwide. However, this has been a scientific challenge due to the limited availability of continuous, long-term reservoir operation records at large scales, and a process-based modeling tool to accurately depict reservoirs as part of the terrestrial water cycle is still lacking. Here, we develop a continental-scale land surface-hydrologic model over the mainland China by explicitly representing 3,547 reservoirs in the model with a calibration-free conceptual operation scheme for ungauged reservoirs and a hydrodynamically based two-way coupled scheme. The model is spatially calibrated and then extensively validated against streamflow observations, reservoir storage observations and GRACE-based terrestrial water storage anomalies. A 30-year simulation is then performed to quantify the seasonal dynamics of China’s reservoir water storage (RWS) and its role in China\u27s terrestrial water storage (TWS) over recent decades. We estimate that, over a seasonal cycle, China\u27s RWS variation is 15%, 16%, and 25% of TWS variation during 1981–1990, 1991–2000, and 2001–2010, respectively, and one-fifth of China’s reservoir capacity are effectively used annually. In most regions, reservoirs play a growing role in modulating the water cycle over time. Despite that, an estimated 80 million people have faced increasing water resources challenges in the past decades due to the significantly weakened reservoir regulation of the water cycle. Our approaches and findings could help the government better address the water security challenges under environmental changes

Estimation of component contributions to total terrestrial water storage change in the Yangtze River basin

Terrestrial water storage (TWS) is a key variable in global and regional hydrological cycles. In this study, the TWS changes in the Yangtze River Basin (YRB) were derived using the Lagrange multiplier method (LMM) from Gravity Recovery and Climate Experiment (GRACE) data. To assess TWS changes from LMM, different GRACE solutions, different hydrological models, and in situ data were used for validation. Results show that TWS changes from LMM in YRB has the best performance with the correlation coefficients of 0.80 and root mean square error of 1.48 cm in comparison with in situ data. The trend of TWS changes over the YRB increased by 10.39 ± 1.27 Gt yr-1 during the 2003−2015 period. Moreover, TWS change is disintegrated into the individual contributions of hydrological components (i.e., glaciers, surface water, soil moisture, and groundwater) from satellite data, hydrologic models, and in situ data. The estimated changes in individual TWS components in the YRB show that (1) the contribution of glaciers, surface water, soil moisture, and groundwater to total TWS changes is 15%, 12%, 25% and 48%, respectively; (2) Geladandong glacier melt from CryoSat-2/ICESat data has a critical effect on TWS changes with a correlation coefficients of −0.51; (3) the Three Gorges Reservoir Impoundment has a minimal effect on surface water changes (mainly lake water storage), but it has a substantial effect on groundwater storage (GWS), (4) the Poyang and Doting Lake water storage changes are mainly caused by climate change, (5) soil moisture storage change is mainly influenced by surface water, (6) human-induced GWS changes accounted for approximately half of the total GWS. The results of this study can provide valuable information for decision-making in water resources management

Applying autoregressive models in analysis of GRACE-Mascon time-series

This study discusses how to model the noise in a Gravity Recovery and Climate Experiment (GRACE)-Mascon derived Equivalent Water Thicknesses (EWT) time-series. GRACE has provided unique information for monitoring variations in EWT of continents in regional or basin scale since 2002. To analyze a GRACE EWT time-series, a standard harmonic regression model is used, but usually assuming white noise-only stochastic model. However, like almost all kinds of geodetic time-series, it has been shown that the GRACE EWT time-series contains temporal correlations causing colored noise in the data. As well known in geodetic modelling studies, neglecting these correlations leads to underestimating the uncertainties, and so misinterpreting the significancy of the parameter estimates such as trend rate, amplitudes of signals etc. In this study, autoregressive noise modeling, which has some advantageous compared to the approaches and methods frequently applied in geodetic studies, is considered for GRACE EWT time series. For this aim, three important basins, namely theYangtze, Murray–Darling and Amazon basins have been examined. Among some applied autoregressive models, the ARMA(1,1) model is obtained as the best-fitting noise model for analyzing the EWT changes in each basin. The obtained results are discussed in terms of forecasting, significancy and consistency with GRACE-FO mission

Human-Induced and Climate-Driven Contributions to Water Storage Variations in the Haihe River Basin, China

Terrestrial water storage (TWS) can be influenced by both climate change and anthropogenic activities. While the Gravity Recovery and Climate Experiment (GRACE) satellites have provided a global view on long-term trends in TWS, our ability to disentangle human impacts from natural climate variability remains limited. Here we present a quantitative method to isolate these two contributions with reconstructed climate-driven TWS anomalies (TWSA) based on long-term precipitation data. Using the Haihe River Basin (HRB) as a case study, we find a higher human-induced water depletion rate (−12.87 ± 1.07 mm/yr) compared to the original negative trend observed by GRACE alone for the period of 2003–2013, accounting for a positive climate-driven TWSA trend (+4.31 ± 0.72 mm/yr). We show that previous approaches (e.g., relying on land surface models) provide lower estimates of the climate-driven trend, and thus likely underestimated the human-induced trend. The isolation method presented in this study will help to interpret observed long-term TWS changes and assess regional anthropogenic impacts on water resources

Assessment of pluri-annual and decadal changes in terrestrial water storage predicted by global hydrological models in comparison with the GRACE satellite gravity mission

The GRACE (Gravity Recovery And Climate Experiment) satellite gravity mission enables global monitoring of the mass transport within the Earth's system, leading to unprecedented advances in our understanding of the global water cycle in a changing climate. This study focuses on the quantification of changes in terrestrial water storage with respect to the temporal average based on an ensemble of GRACE solutions and two global hydrological models. Significant changes in terrestrial water storage are detected at pluri-annual and decadal timescales in GRACE satellite gravity data that are generally underestimated by global hydrological models though consistent with precipitation. The largest differences (more than 20 cm in equivalent water height) are observed in South America (Amazon, São Francisco and Paraná River basins) and tropical Africa (Congo, Zambezi and Okavango River basins). Smaller but significant (a few centimetres) differences are observed worldwide. While the origin of such differences is unknown, part of it is likely to be climate-related and at least partially due to inaccurate predictions of hydrological models. Pluri-annual to decadal changes in the terrestrial water cycle may indeed be overlooked in global hydrological models due to inaccurate meteorological forcing (e.g. precipitation), unresolved groundwater processes, anthropogenic influences, changing vegetation cover and limited calibration/validation datasets. Significant differences between GRACE satellite measurements and hydrological model predictions have been identified, quantified and characterised in the present study. Efforts must be made to better understand the gap between methods at both pluri-annual and decadal timescales, which challenges the use of global hydrological models for the prediction of the evolution of water resources in changing climate conditions.</p

Estimating GRACE terrestrial water storage anomaly using an improved point mass solution

The availability of terrestrial water storage anomaly (TWSA) data from the Gravity Recovery and Climate Experiment (GRACE) supports many hydrological applications. Five TWSA products are operational and publicly available, including three based on mass concentration (mascon) solutions and two based on the synthesis of spherical harmonic coefficients (SHCs). The mascon solutions have advantages regarding the synthesis of SHCs since the basis functions are represented locally rather than globally, which allows geophysical data constraints. Alternative new solutions based on SHCs are, therefore, critical and warranted to enrich the portfolio of user-friendly TWSA data based on different algorithms. TWSA data based on novel processing protocols is presented with a spatial re-sampling of 0.25 arc-degrees covering 2002–2022. This approach parameterizes the improved point mass (IPM) and adopts the synthesized residual gravitational potential as observations. The assay indicates that the proposed Hohai University (HHU-) IPM TWSA data reliably agree with the mascon solutions. The presented HHU-IPM TWSA data set would be instrumental in regional hydrological applications, particularly enabling improved assessment of regional water budgets

Spatio temporal pattern in the changes in availability and sustainability of water resources in Afghanistan

Water is gradually becoming scarce in Afghanistan like in many other regions of the globe. The objective of this study was to evaluate the spatial changes in the availability and sustainability of water resources in Afghanistan. The Terrestrial Water Storage (TWS) data of the Gravity Recovery and Climate Experiment (GRACE) satellite obtained from three different institutes, having 1° × 1° spatial resolutions for the period 2002–2016 was used for this purpose. Sen’s slope method was used to assess the rate of change, and the Modified Mann–Kendall test was used for the evaluation of the significance of trends in TWS. After, the concept of reliability–resiliency–vulnerability (RRV) was used for assessing the spatial distribution of sustainability in water resources. The results revealed a significant decrease in water availability in the country over the last 15 years. The decrease was found to be highest in the central region where most of the population of the country resides. The reliability in water resources was found high in the northeast Himalayan region and low in the southwest desert; resilience was found low in the central region, while vulnerability was found high in the south and the southeast. Overall, the water resources of the country were found most sustainable in the northeast and southwest and least in the south and the central parts. The maps of water resource sustainability and the changes in water availability produced in the present study can be used for long-term planning of water resources for adaptation to global changes. Besides, those can be used for the management of water resources in a sustainable and judicious manner