Water Storage Changes Research Articles

Subsurface structure regulates water storage in the alpine critical zone on the Qinghai-Tibet Plateau

The subsurface critical zone (CZ) structure in alpine regions has a profound influence on water storage that is not well understood due to a lack of available accurate spatiotemporal measurements. This work is to reveal that the organic layer (A), leaching-deposit layer (B), saprolite layer (C) and freeze–thaw processes regulate changes in subsurface liquid water storage (CSWS). We performed in situ field surveys, ground-penetrating radar (GPR) and electrical resistivity tomography (ERT) along an elevation gradient (4221–3205 m) in the Qinghai Lake Basin Critical Zone Observatory (QLBCZO) on the Qinghai-Tibet Plateau. The results showed that the saprolite layer (thickness of 0.84–41.85 m) and the liquid water storage (SWS) increased along the decreasing elevation. The saprolite layer was the main subsurface liquid water storage reservoir, with average value of 595.49 ± 729.87 mm, which occupied 76.10 % of the total water storage of layers A, B and C. The SWS of the saprolite layers increased the most, by 39.41 mm and 45.88 mm in the thawing and nonfreezing periods, respectively, and that of layer B decreased maximally by 52.50 mm in the freezing period. The subsurface layer and elevation had the contribution to SWS at 68.07 % during the nonfreezing period. Comparing other climate and environmental factors, the seasonal frozen thickness (SFT) and precipitation contributed most to CSWS during the thawing and freezing period (27.95 % and 19.87 %), respectively. This study contributes to advancing the mechanistic understanding of the interactions between the subsurface CZ structure and water storage processes and provides high-quality data with which coupled ecohydrological models can be developed.

Spatiotemporal Changes in Water Storage and Its Driving Factors in the Three-River Headwaters Region, Qinghai–Tibet Plateau

Water storage (WS) is a crucial terrestrial ecosystems service function. In cold alpine regions (CAR), the cryosphere elements are important solid water resources, but the existing methods for quantitatively assessing WS usually ignore cryosphere elements. In this study, a revised Seasonal Water Yield model (SWY) in the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST), which considers the effects of frozen ground (FG) and snow cover (SC) on WS, was employed to estimate the spatiotemporal distribution and changes in WS in the Three-Rivers Headwaters region (TRHR) from 1981 to 2020. Sensitivity analyses were conducted to understand the overall effects of multiple factors on WS, as well as the dominant driving factors of WS change at the grid scale in the TRHR. The results show that (1) the WS in the TRHR generally increased from 1981 to 2020 (0.56 mm/year), but the spatial distribution of WS change varied greatly, with a significant increasing trend in the northwest part and a significant decreasing trend in the southeast part. (2) In the last 40 years, increased precipitation (Pre) positively affected WS, while increased potential evapotranspiration (ET0) reduced it. Increased permeability caused by degradation of frozen ground increased WS, while snow cover and LULC changes reduced it. (3) In the TRHR, Pre primarily affected the WS with the largest area ratio (32.62%), followed by land use/land cover (LULC) (19.69%) and ET0 (18.49%), with FG being fourth (17.05%) and SC being the least (6.64%). (4) The highly important and extremely important zones generally showed a decreasing trend in WS and should be treated as key and priority conservation regions. It is expected that this research could provide a scientific reference for water management in the TRHR.

Evaluating the weekly changes in terrestrial water storage estimated by two different inversion strategies in the Amazon River Basin

In this study, we estimated the weekly Gravity Recovery and Climate Experiment (GRACE) spherical harmonic (SH) solutions and regional mascon solutions using GRACE-based Geopotential Difference (GPD) data and investigated their abilities in retrieving terrestrial water storage (TWS) changes over the Amazon River Basin (ARB) from January 2003 to February 2013. The performance of the weekly GPD-SH and GPD-mascon solutions was evaluated by comparing them with the weekly GFZ-SH solutions, Global Land Data Assimilation Systems (GLDAS)-NOAH hydrological model outputs, and monthly GFZ-SH, GPD-SH, and CSR-mascon solutions in the spatio-temporal and spectral domains. The results demonstrate that the weekly GPD-SH and GPD-mascon present good consistency with the weekly GFZ-SH solutions and GLDAS-NOAH estimates in the spatio-temporal domains, but GPD-mascon presents stronger signal amplitudes and more spatial details. The comparison of the monthly average of weekly estimates and monthly solutions demonstrates that the weekly GPD-mascon and GFZ-SH with DDK1 filtering are close to the monthly CSR-mascon and GFZ-SH solutions, respectively. However, the signal amplitudes of TWS changes from GPD-SH and GFZ-SH with 650 km Gaussian filtering are smaller than the monthly solutions, and the corresponding Root Mean Square Errors between the TWS change time series from the monthly average of weekly solutions and monthly estimates are 18.12 mm (GPD-mascon), 18.81 mm (GFZ-SH-DDK1), 24.93 mm (GPD-SH-G650km), and 33.07 mm (GFZ-SH-G650km), respectively. Additionally, the TWS change time series derived from weekly solutions present more high-frequency time-varying information than monthly solutions. Furthermore, the 300 km Gaussian filtering can improve the signal amplitudes of TWS changes from the weekly GPD-SH solutions more than those with 650 km Gaussian filtering, but the corresponding noise level is higher. The weekly GPD-SH and GPD-mascon solutions can extend the application scopes of GRACE and provide good complements to the current GRACE monthly solutions.

Continuing Severe Water Shortage in the Water‐Receiving Area of the South‐To‐North Water Diversion Eastern Route Project From 2002 to 2020

AbstractThe water‐receiving area of the South‐to‐North Water Diversion Eastern Route Project (SNWDP‐ER) is one of the most severely affected water‐shortage areas in China, and no previous study has been conducted on the changes in water storage in this area. In this study, we combined the latest Gravity Recovery and Climate Experiment (GRACE) And GRACE Follow‐On products with global models for the first time to analyze changes in water storages in this area from 2002 to 2020, and to investigate the effects of climate change and human activity on changes in water storage. We found that SNWDP‐ER aided the recovery of surface water (nongroundwater) with a recovery rate of 9.44 ± 1.65 mm/yr after its implementation, but had little effect on the recovery of groundwater and terrestrial water storage in the water‐receiving area. Before the SNWDP‐ER was implemented, the rates of decrease of groundwater and terrestrial water storage were only −1.59 ± 0.58 and −5.18 ± 0.75 mm/yr, respectively. After implementation, the rates of decrease of groundwater and terrestrial water storage were −17.7 ± 1.27 and −8.16 ± 1.18 mm/yr, respectively. Groundwater decline, accelerated by human activity and climate change, has led to an accelerated decline in terrestrial water storage. Effects of SNWDP‐ER and stringent policies reducing groundwater use, along with largely increased precipitation in North China on groundwater storage after year 2020 need to be examined in the future. Our results have important implications for the management and evaluation of SNWDP‐ER.

Seasonal Variations of Recharge–Storage–Runoff Process over the Tibetan Plateau

Abstract The Tibetan Plateau (TP) is a vital and vulnerable water tower that supports the livelihoods of billions of people. The use of a data-driven recharge–storage–runoff perspective enables a more comprehensive estimation of multiple aspects of the water cycle. Through an analysis of the diagnostic net water flux from ERA5, water storage changes (dS/dt) from GRACE, runoff estimations (R) from the land–atmosphere water balance, and river discharge measurements (Rd), the annual cycle of recharge–storage–runoff has been studied over the TP and its basins. The net water flux determines a recharge of 326 mm yr−1 over the TP. Recharge in coupled storages, leading to an increase in water mass (dS/dt > 0) and runoff (R > 0) during the wet season, is considered the fast response and is measured using the ratio of runoff to net water flux (r1). Conversely, the slow response determined by the water storage release (dS/dt < 0) during the dry season is quantified by the ratio of storage release to runoff (r2). The ratios of r1 and r2 are influenced by climatic and terrain drivers, indicating specific characteristics of recharge–storage–runoff at the basin scale. Small r1 values and large r2 values suggest high buffer capacity, while the basin of Amu Darya (Salween) is characterized by the highest (lowest) buffer capacity over the TP. However, measurements of river discharge at Amu Darya suggest an uncoupled recharge–storage–runoff. The imbalance between river discharge and runoff estimation was most severe in the first decade of the twenty-first century but has been mitigated since 2012. River discharge at Amu Darya is likely constrained by energy during summer.

Response of vegetation to terrestrial water storage in Southwest China

To explore the responses of vegetation growth to change in terrestrial water storage in Southwest China, we analyzed the change trend and relationship between vegetation and terrestrial water storage anomaly (TWSA) in Southwest China from January 2003 to December 2021 by using TWSA data of Gravity Recovery and Climate Experi-ment (GRACE) satellite and normalized differential vegetation index (NDVI) data. The results showed that NDVI in Southwest China during the study period showed an overall upward trend. Meanwhile, TWSA showed a significant downward trend in central and southern Tibet, and a significant upward trend in northwest Tibet and southeast region of Southwest China. Results of Pearson correlation analysis showed that there were significant spatial differences in responses of NDVI to TWSA changes in Southwest China. NDVI had a significant negative response to TWSA changes in most regions of Tibet, but a significant positive response to TWSA changes in most regions of southeast region of Southwest China. Such differences were driven by climate change and topography.

Lake Evaporation and Its Effects on Basin Evapotranspiration and Lake Water Storage on the Inner Tibetan Plateau

AbstractEffects of lake evaporation (EW) on basin evapotranspiration (ETB) and lake water storage change (LWSC) at lake‐basin scale have never been reported for most basins on the inner Tibetan Plateau (IB). In this study, EW of 118 large lakes in 95 closed lake‐basins were estimated, and its effects on ETB and LWSC over 2001–2018 were examined using a derivative‐guided framework from the aspects of EW amount, rate, trend slope and inter‐annual variability. We found that EW amount has a high effect (17%) on regional ETB amount compared to the average lake area ratio (α) (∼5%), and the effect has increased significantly (2%/10 a). The spatial pattern of the effect is mainly controlled by α, and the increasing trend of α (0.6%/10 a) also dominated the increasing trend in regional ETB rate (0.30 mm/a) though with large spatial heterogeneity. Variance in α and EW rate have a minor effect (∼3%) on ETB variance, especially for the basins with lower α. The combination of quasi lake inflow (RL, 41%) and lake surface precipitation (PW, 16%) offset the depletion of EW (−43%), resulting in the surplus of regional lake water (LWSC > 0). The increase in EW mount, which is mainly from lake area expansion (90%), caused a decreasing trend in LWSC (i.e., slower growth rate) with a contribution of −59%. This suggests a negative feedback between lake area expansion and EW amount in the IB, and the feedback may continue with the predicted area increases.

The Influence of ENSO on the Long‐Term Water Storage Anomalies in the Middle‐Lower Reaches of the Yangtze River Basin: Evaluation and Analysis

AbstractRecent extreme events in the Middle‐Lower reaches of the Yangtze River basin (MLYRB) are proven to be possibly linked to the El Niño‐Southern Oscillation (ENSO) events as indicated by terrestrial water storage anomaly (TWSA). But the relatively short observation time of Gravity Recovery and Climate Experiment series missions (2002–2017; 2018–present) affects the robustness of the evaluation of TWSA. Here, the applicability of four long‐term TWSA data sets (since 1979) in the MLYRB is evaluated first using an evaluation framework including two completely independent tests. After selecting the optimal one, we investigate the effects of ENSO on TWSA in the MLYRB at the basin, subbasin, and grid cell scales, respectively. Results show that ENSO, especially the Eastern Pacific type ENSO has had a significant impact on TWSA variations in the MLYRB and its two subbasins (the Dongting Lake basin and the Poyang Lake basin) since 1979 with correlation coefficients at 0.56–0.65 and time lags at 5–6 months. However, TWSAs in the other two subbasins (the Hanjiang River basin and the Mainstream River basin) have almost no correlation with ENSO. Further analysis reveals that compared with human activity that has a limited impact on TWSA, precipitation is one of the key inducements for regional water storage changes in these two subbasins, and the no correlation between ENSO and TWSA is mainly caused by the weak link between ENSO and precipitation.

A shrinkage-free approach for fusing GRACE-based total water storage changes with models using wavelet multiresolution analysis

The observations from Gravity Recovery and Climate Experiment (GRACE) satellites provide total water storage changes (TWSC) at ∼300 km or larger spatial scales. To obtain information at a higher spatial resolution, suitable for management purposes, previous studies combined GRACE TWSC maps with information from hydrological models via assimilation techniques (e.g. CLSM-DA), or with external observations via scaling and machine learning approaches. Both techniques may introduce shrinkage errors, a reduction in amplitude of long spatial wavelength signals, and distorting water budgets at basin scale best observed by GRACE. Here, we present a fusion approach based on wavelet multiresolution analysis to combine long-wavelength GRACE TWSC observations with short-wavelength measurements of TWSC from the GLDAS Noah model in the contiguous United States (CONUS). We decompose TWSC maps into building blocks at different spatial wavelengths, examine their statistical characteristics, and combine complementary components at wavelet coefficient levels. The fused TWSC is then obtained by inverse wavelet transform. A spectral analysis indicates that the fused TWSC comprises frequency content that balances spectral characteristics of both input datasets. The fused TWSC dataset possesses enhanced details in the spatial domain, while it accurately quantifies the water budget and its long-term spatial trend at basin scale during 2003–2015, showing a good agreement with GRACE estimates. Independent validation against elastic hydrologic loading deformation measured at ∼2000 GNSS stations across CONUS shows similar overall performance for GRACE and fused datasets, while it outperforms GRACE in modeling groundwater storage changes in CONUS when compared to CLSM-DA.

A spatially promoted SVM model for GRACE downscaling: Using ground and satellite-based datasets

Satellite-based terrestrial water storage changes have been recorded using the Gravity Recovery and Climate Experiment (GRACE) satellite which causing it an important dataset in hydrology and other related fields. GRACE dataset is widely utilized in many studies, but its coarse spatial resolution is a limiting drawback. Machine-learning approaches (e.g., ANN and SVM) are commonly applied in spatially downscaling. However, their input formation, which is in vector form, is a limitation of considering neighbor relations between the gridded-based inputs, specifically in spatial downscaling. Thus, developing an appropriate, simple, fast, and novel model to spatially downscale GRACE resolution is initially necessary for its utilizations. In this study, a Spatially Promoted Support Vector Machine (SP-SVM) model is innovatively proposed for GRACE downscaling from 0.5° to 0.25°. This promotion is investigated utilizing the distances between the unknown target points (with 0.25°) and their surrounding GRACE-valued points (0.5°), called their Distance Effect Coefficient (DEC), as the SP-SVM model input. In addition, the efficiencies of different in-situ and satellite-based datasets (fifteen variables from May 2005 to August 2020) are evaluated as the inputs of the GRACE downscaling models. After finding the most influential datasets, showing the best correlation with the GRACE, their best combinations in GRACE downscaling are identified. Based on the results, the set of PERSIANN-CDR without delay, the in-situ evaporation with a 1-month delay, and the soil moisture in 0–10 cm depth with a 1-month delay show the best performance in GRACE downscaling. The results of GRACE downscaling by the SP-SVM approach are also compared with the ones based on a usual statistical SVM (S-SVM) model, consisting of an intermediate bias interpolation to improve the estimations through a bias correction step. The results show that the SP-SVM model outperforms the common statistical SVM-based. Thus, compared with the usual S-SVM approach, the proposed SP-SVM (linear) model could be used as a simpler and more accurate model for downscaling any variable in a hierarchical process.

Monitoring terrestrial water storage changes and drought in Jiangxi Province using GRACE and GRACE Follow-on data

Monitoring terrestrial water storage changes and drought in Jiangxi Province using GRACE and GRACE Follow-on data

Estimating runoff from pan-Arctic drainage basins for 2002–2019 using an improved runoff-storage relationship

The Arctic is undergoing dramatic climate and environmental changes. The long-term alterations in river discharges from the boreal catchments, which serve as vital links between the ocean and land, are having a profound impact on various environmental factors, particularly ocean circulation and sea-ice content. However, comprehensive and continuous monitoring of Arctic river discharge at seasonal or higher temporal resolutions remains challenging. In this study, we propose a new approach to estimate runoff by generating monthly runoff time series at the basin scale. Our method is based on changes in water storage observed by the gravimetric satellites Gravity Recovery and Climate Experiment (GRACE) and its follow-on mission since 2002. The method utilizes an empirical runoff-storage (R-S) relationship, offering simplicity and low computational burden while maintaining good accuracy in estimating runoff. To validate our method, we utilize in-situ runoff measurements from the seven largest boreal drainage basins spanning the period from 2002 to 2019, encompassing a total of 18 years. We divide these 18 years of observations into two phases: a training phase (8 years) and a testing phase (10 years). The results indicate that the R-S method established during the training phase yields monthly Nash-Sutcliffe efficiency (NSE) values ranging from 0.65 to 0.92 when compared to in-situ runoff measurements. Moreover, the method demonstrates a consistent performance in estimating runoff during the testing phase (monthly NSE: 0.67–0.84). With the exception of the Ob and Mackenzie basins, which exhibit distinct climatic conditions and hydrological networks, the R-S models are interchangeable across basins. This makes it suitable for both temporal and spatial extrapolation to fill data gaps, provided that accurate water and snow storage data are available. All in all, our method enables the reconstruction of monthly surface runoff across the entire boreal basins between 2002 and 2019. The results indicate an average annual runoff of 3200 ± 160 Gt over the study area of 1.58 × 107 km2. To evaluate the accuracy of our estimates, we compare the total runoff estimates obtained using the R-S method with those from 12 model estimates. Our estimates exhibit the highest correlation with available in-situ runoff measurements and yield monthly NSE values >0.57 for five out of the twelve model estimates. This study presents a convenient method to address the urgent need for comprehensive, continuous, and monthly temporal resolution of runoff estimates throughout the entire boreal region.

Assessing Terrestrial Water Storage Variations in Southern Spain Using Rainfall Estimates and GRACE Data

This paper investigates the relationship between rainfall, groundwater and Gravity Recovery and Climate Experiment (GRACE) data to generate regional-scale estimates of terrestrial water storage variations in the Andalucía region of southern Spain. These estimates can provide information on groundwater depletion (caused by periods of low rainfall or droughts) and groundwater recovery. The spatial distribution of groundwater bodies in southern Spain is complex and current in situ groundwater monitoring methods are deficient, particularly in terms of obtaining representative samples and in implementing and maintaining groundwater monitoring networks. The alternative approach proposed here is to investigate the relationship between precipitation time series and changes in the terrestrial water storage estimated from GRACE observations. The results were validated against the estimated fluctuation in regional groundwater. The maximum correlation between the mean groundwater level and the GRACE observations is 0.69 and this occurs at a lag of one month because the variation in gravity is immediate, but rainfall water requires around one month to travel across the vadose zone before it reaches the groundwater table. Using graphical methods of accumulated deviations from the mean, we show that, in general, groundwater storage follows the smooth, multi-year trends of terrestrial water storage but with less short-term trends; the same is true of rainfall, for which the local trends are more pronounced. There is hysteresis-like behaviour in the variations in terrestrial water storage and in the variations of groundwater. In practical terms, this study shows that, despite the abnormal dryness of the Iberian Peninsula during the 2004–2010 drought, the depleted groundwater storage in Andalucía recovered almost to its pre-drought level by 2016. In addition, groundwater storage and terrestrial water storage show very similar trends but with a delay in the groundwater trend.

A deep learning model for reconstructing centenary water storage changes in the Yangtze River Basin

Since 2002, the Gravity Recovery and Climate Experiment (GRACE) and its Follow-On mission (GRACE-FO) have facilitated highly accurate observations of changes in total water storage anomalies (TWSA). However, limited observations of TWSA derived from GRACE in the Yangtze River Basin (YRB) have hindered our understanding of its long-term variability. In this paper, we present a deep learning model called RecNet to reconstruct the climate-driven TWSA in the YRB from 1923 to 2022. The RecNet model is trained on precipitation, temperature, and GRACE observations with a weighted mean square error (WMSE) loss function. The performance of the RecNet model is validated and compared against GRACE data, water budget estimates, hydrological models, drought indices, and existing reconstruction datasets. The results indicate that the RecNet model can successfully reconstruct historical water storage changes, surpassing the performance of previous studies. In addition, the reconstructed datasets are utilized to assess the frequency of extreme hydrological conditions and their teleconnections with major climate patterns, including the El Niño-Southern Oscillation, Indian Ocean Dipole, Pacific Decadal Oscillation, and North Atlantic Oscillation. Independent component analysis is employed to investigate individual climate patterns' unique or combined influence on TWSA. We show that the YRB exhibits a notable vulnerability to extreme events, characterized by a recurrent occurrence of diverse extreme dry/wet conditions throughout the past century. Wavelet coherence analysis reveals significant coherence between the climate patterns and TWSA across the entire basin. The reconstructed datasets provide valuable information for studying long-term climate variability and projecting future droughts and floods in the YRB, which can inform effective water resource management and climate change adaptation strategies.

One‐Parameter Analytical Derivation in Modified Budyko Framework for Unsteady‐State Streamflow Elasticity in Humid Catchments

AbstractThe changes in climate and catchment properties have altered the hydrological processes significantly at different spatiotemporal scales around the world. In particular for finer time scales, changes in water storage, which has been commonly neglected for long‐term temporal scales, may play an important role on hydrological processes. Nevertheless, few studies addressed this question in modifying the Budyko framework, with most of them remaining a steady‐state assumption on catchment characteristics. Here, we derive new analytical formulas of unsteady‐state streamflow elasticity in a modified Budyko framework, incorporating both storage change and one specific parameter for catchment properties. We study 78 humid catchments in the USA with simulation data of daily hydrological processes from a probability‐distribution‐based hydrological model (the modified HyMOD). As indicated by results, the annual storage change ratio is linearly correlated with the annual aridity index, and this relationship can be used to estimate elasticity coefficients with our formulas. The estimated elasticity coefficients perform well in simulating the annual streamflow with the power‐law model. For different catchments, variability of the unsteady‐state elasticity is higher than that of the steady‐state elasticity. Unsteady‐state streamflow coefficients show significant linear correlation with catchment properties, such as the average slope, average elevation, and catchment area. This study provides a new analytical approach to investigate the interannual stability of catchments with varying climate and catchment properties.

Detection of the nonlinear response of vegetation to terrestrial water storage changes in central Asian endorheic basins

The terrestrial water storage anomaly (TWSA) is an important parameter for assessing the land water budget, and it interacts well with terrestrial ecosystems via complex hydrological processes. Recently, the decline in central Asian terrestrial water storage (TWS) has threatened the health of local ecosystems. Therefore, it is of great significance to adopt an efficient approach to explore and identify the nonlinear relationship between two important indicators, i.e., the TWSA and normalized difference vegetation index (NDVI) in the arid central Asian endorheic basins. In this study, we analysed the long-term trends of the TWSA and NDVI, and identified the lag month (1 month) as the optimal moving window of the nonlinear Granger causality test embedded in random forest to detect the nonlinear NDVI change response of NDVI changes in vegetation to the TWSA from 2003 to 2015. There are decreasing trends in TWSAs over approximately 81.7% of the study area and the NDVI generally decreased resulting in approximately 36% vegetation browning in the study area. The nonlinear Granger unidirectional causes of the TWSA were responsible for 97.9% of the NDVI variation in the study area considering the optimal response time for moving windows. The causes of vegetation browning in the central Asian Aral Sea basin and vegetation greening in the basins of Northwest China could be mostly explained by the changes in TWS. Our findings contribute to understanding the nonlinear causal linkages between vegetation and the TWSA in endorheic basins, and these findings provide insights for obtaining terrestrial water consumption patterns and water resource management under the joint influence of climate change and human activities.

Monitoring Terrestrial Water Storage, Drought and Seasonal Changes in Central Oklahoma With Ambient Seismic Noise

AbstractSignificant imbalances in terrestrial water storage (TWS) and severe drought have been observed around the world as a consequence of climate changes. Improving our ability to monitor TWS and drought is critical for water‐resource management and water‐deficit estimation. We use continuous seismic ambient noise to monitor temporal evolution of near‐surface seismic velocity, dv/v, in central Oklahoma from 2013 to 2022. The derived dv/v is found to be negatively correlated with gravitational measurements and groundwater depths, showing the impact of groundwater storage on seismic velocities. The hydrological effects involving droughts and recharge of groundwater occur on a multi‐year time scale and dominate the overall derived velocity changes. The thermoelastic response to atmospheric temperature variations occurs primarily on a yearly timescale and dominates the superposed seasonal velocity changes in this study. The occurrences of droughts appear simultaneously with local peaks of dv/v, demonstrating the sensitivity of near‐surface seismic velocities to droughts.

Making the Best Use of GRACE, GRACE‐FO and SMAP Data Through a Constrained Bayesian Data‐Model Integration

AbstractThe Gravity Recovery and Climate Experiment (GRACE, 2003–2017) and its Follow‐On mission GRACE‐FO (2018‐now) provide global estimates of the vertically integrated Terrestrial Water Storage Changes (TWSC). Since 2015, the Soil Moisture Active Passive (SMAP) radiometer observes global L‐band brightness temperatures, which are sensitive to near‐surface soil moisture. In this study, we introduce our newly developed Constrained Bayesian (ConBay) optimization approach to merge the TWSC of GRACE/GRACE‐FO along with SMAP soil moisture data into the ∼10 km resolution W3RA water balance model. ConBay is formulated based on two hierarchical multivariate state‐space models to (I) separate land hydrology compartments from GRACE/GRACE‐FO TWSC, and (II) constrain the estimation of surface soil water storage based on the SMAP data. The numerical implementation is demonstrated over the High Plain (HP) aquifer in the United States between 2015 and 2021. The implementation of ConBay is compared with an unconstrained Bayesian formulation, and our validations are performed against in‐situ USGS groundwater level observations and the European Space Agency (ESA)'s Climate Change Initiative (CCI) soil moisture data. Our results indicate that the single GRACE/GRACE‐FO assimilation improves particularly the groundwater compartment. Adding SMAP data to the ConBay approach controls the updates assigned to the surface storage compartments. For example, correlation coefficients between the ESA CCI and the ConBay‐derived surface soil water storage (0.8) that are considerably higher than those derived from the unconstrained experiment (−0.3) in the North HP. The percentage of updates introduced to the W3RA groundwater storage is also decreased from 64% to 57%.

Understanding the balance between soil conservation and soil water storage capacity during the process of vegetation restoration in semi‐arid watersheds in the Loess Plateau, China

AbstractIn the Loess Plateau, gaining insights into the water storage and soil retention functions of diverse vegetation types, especially, in the semi‐arid watersheds is crucial for identifying the key factors necessary to ensure sustainable development and achieve land degradation neutrality. In this study, five different land use types such as forest, shrub, artificial grass, and natural grasslands were surveyed from 2014 to 2020. Meanwhile, bare land was also used as a control plot. The trade‐off between erosion mitigation and water consumption indicator was quantified based on the ecosystem services perspective benefits. Our results showed that there are significant differences among different land use types (p < 0.05): natural grassland > shrubs > artificial grassland > forests. Vegetation restoration was able to change the soil particle size distribution, increasing clay and silt content, and decreasing sand particles. During the growing season, surface soil water storage decreased in all land use types coinciding with the higher decrease in the control plot. The change in surface water storage in the forest was the most stable, with a decrease of 0.13 mm. The trade‐off between erosion mitigation and water consumption indicator was less than 0 for all vegetation types, which indicates a synergistic effect on soil conservation and water storage benefit. Our results demonstrated that shrubs can register the most balanced benefit of water storage and soil preservation. This is a solid basis for the selection of specific vegetation types and the optimization of the watershed landscape in the middle reaches of the Yellow River, characterized by vulnerable areas due to aridification.

The Influence of the South-to-North Water-Diversion Project on Terrestrial Water-Storage Changes in Hebei Province

The lack of water resources has emerged as a major factor limiting the high-quality economic and ecological development in Hebei Province. Therefore, it is of great significance to understand the dynamic changes in terrestrial water storage for effectively managing water resources in Hebei Province. The evolution pattern and spatial distribution of TWS anomalies (TWSA) were analyzed utilizing gravity recovery and climate experiment (GRACE) solutions and the water balance method from 2003 to 2020, and the missing monthly data during GRACE and GRACE-FO missions were filled by combining the climate-driven model and meteorological products. Moreover, the impact of the south-to-north water-diversion (SNWD) project on alleviating the water-storage deficit was quantified. The results revealed that the water-balance method on the strength of the combination of CMA precipitation and Noahv2.1-simulated evapotranspiration and runoff data matches well with the TWSA data derived from GRACE, with a correlation coefficient up to 0.95. However, the accuracy was unsatisfactory during the process of characterizing the spatial characteristics of TWSA. After the SNWD project, GRACE-derived results showed that the downtrends of TWSA were reduced by 10.93%, especially in mountainous areas: by 79.78%. Concerning the spatial scale, the deficit trends were reduced to a certain extent in northern Hebei Province, while the decreasing trends cannot be reversed for a short time in southern areas where human activities are intensive.