Water Storage Changes Research Articles

Global evaluation of the “dry gets drier, and wet gets wetter” paradigm from a terrestrial water storage change perspective

Abstract. The “dry gets drier, and wet gets wetter” (DDWW) paradigm has been widely used to summarize the expected trends of the global hydrologic cycle under climate change. However, the paradigm is largely conditioned by choice of different metrics and datasets used and is still comprehensively unexplored from the perspective of terrestrial water storage anomalies (TWSAs). Considering the essential role of TWSAs in wetting and drying of the land system, here we built upon a large ensemble of TWSA datasets, including satellite-based products, global hydrological models, land surface models, and global climate models to evaluate the DDWW hypothesis during the historical (1985–2014) and future (2071–2100) periods under various scenarios with a 0.05 significance level (for trend estimates). We find that 11.01 %–40.84 % (range by various datasets) of global land confirms the DDWW paradigm, while 10.21 %–35.43 % of the area shows the opposite pattern during the historical period. In the future, the DDWW paradigm is still challenged, with the percentage supporting the pattern lower than 18 % and both the DDWW-validated and DDWW-opposed proportion increasing along with the intensification of emission scenarios. We show that the different choices of data sources can reasonably influence the test results up to a 4-fold difference. Our findings will provide insights and implications for global wetting and drying trends from the perspective of TWSA under climate change.

High-resolution water level and storage variation datasets for 338 reservoirs in China during 2010–2021

Abstract. Reservoirs and dams are essential infrastructure in water management; thus, information of their surface water area (SWA), water surface elevation (WSE), and reservoir water storage change (RWSC) is crucial for understanding their properties and interactions in hydrological and biogeochemical cycles. However, knowledge of these reservoir characteristics is scarce or inconsistent at the national scale. Here, we introduce comprehensive reservoir datasets of 338 reservoirs in China, with a total of 470.6 km3 storage capacity (50 % Chinese reservoir storage capacity). Given the scarcity of publicly available gauged observations and operational applications of satellites for hydrological cycles, we utilize multiple satellite altimetry missions (SARAL/AltiKa, Sentinel-3A and Sentinel-3B, CroySat-2, Jason-3, and ICESat-2) and imagery data from Landsat and Sentinel-2 to produce a comprehensive reservoir dataset on the WSE, SWA, and RWSC during 2010–2021. Validation against gauged measurements of 93 reservoirs demonstrates the relatively high accuracy and reliability of our remotely sensed datasets. (1) Across gauge comparisons of RWSC, the median statistics of the Pearson correlation coefficient (CC), normalized root mean square error (NRMSE), and root mean square error (RMSE) are 0.89, 11 %, and 0.021 km3, with a total of 91 % validated reservoirs (83 of 91) having good RMSE from 0.002 to 0.31 km3 and NRMSE values smaller than 20 %. (2) Comparisons of WSE retracked by six satellite altimeters and gauges show good agreement. Specifically, the percentages of reservoirs having good and moderate RMSE values smaller than 1.0 m for CryoSat-2 (validated in 30 reservoirs), SARAL/AltiKa (9), Sentinel-3A (34), Sentinel-3B (25), Jason-3 (11), and ICESat-2 (26) are 77 %, 75 %, 79 %, 87 %, 81 %, and 82 %, respectively. By taking advantages of six satellite altimeters, we are able to densify WSE observations across spatiotemporal scales. Statistically, around 96 % of validated reservoirs (71 of 74) have RMSE values below 1.0 m, while 57 % of reservoirs (42 of 74) have good data quality with RMSE values below 0.6 m. Overall, our study fills such a data gap with regard to comprehensive reservoir information in China and provides strong support for many aspects such as hydrological processes, water resources, and other studies. The dataset is publicly available on Zenodo at https://doi.org/10.5281/zenodo.7251283 (Shen et al., 2021).

Unrevealing past and future vegetation restoration on the Loess Plateau and its impact on terrestrial water storage

Vegetation restoration attributed to China’s Grain to Green Program (GTGP) exerts noticeable impact on the ecological-hydrological nexus. However, the vegetation restoration status associated with GTGP has been insufficiently studied and its effect on water availability remains controversial. This holistic study involved investigation of long-time satellite observations, outputs of a land surface model, and future projections to quantify the historical and future variations of gross primary productivity (GPP) on the Loess Plateau (China) and the associated effect on terrestrial water storage change (TWSC). The ensemble empirical mode decomposition (EEMD) model was employed to characterize the nonlinearity of interannual variability. Satellite-derived observations revealed a trend of increase of 8.162 TgC/year in GPP during 2003–2016, with the largest proportion attributable to grassland owing to its extensive coverage. Increased GPP is related to TWSC decline, as evidenced by both Gravity Recovery and Climate Experiment satellite observations and simulations from the modified Noah land surface model. In descending order, the magnitude of such negative impact varies with coverage of grassland, cropland, and trees. Ecological restoration is manifested as a critical anthropogenic stressor altering TWSC, which is further reinforced by prominent inverse correlation (R = − 0.31) after removing climatic impacts. The bias-corrected Coupled Model Intercomparison Project phase 6 dataset illustrates that increased GPP and reduced TWS are projected in the twenty-first century when considering the climate change and human interventions. Considering that past ecological benefits associated with revegetation measures could represent short-term gains and that TWS decline is most likely to continue, the government and local stakeholders should reconsider the current hydrological condition from the perspective of balanced socioeconomic benefit and terrestrial water storage cost.

Characterization of hydrological droughts in Brazil using a novel multiscale index from GNSS

Drought severity is not only related to drought intensity but also depends on drought duration. To accurately characterize short- and long-term droughts and comprehend drought propagation mechanisms, it is essential to ascertain the multiscale features of drought extremes. Here, we estimate terrestrial water storage changes (TWSC) using Global Navigation Satellite System (GNSS) vertical crustal displacement and then develop a novel Multiscale GNSS-based Drought Index (MGDI) to characterize hydrological droughts in Brazil from 2010 to 2021. MGDI is a probability-based drought index, and we employ a normal distribution to fit the TWSC result. The comparisons of temporal variations indicate that the MGDI is similar to other multiscale drought indices (i.e., standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI), and standardized terrestrial water storage index (STI)) at different time scales. Due to the longer response time to meteorological variables, hydrological drought indicators (i.e., MGDI and STI) generally lag behind meteorological drought indicators (i.e., SPI and SPEI) but with less noise on the short scale. The spatial distribution of MGDI-derived drought frequency reveals that hydrological droughts are most frequent in northeastern Brazil and near the Parana River Basin, with a frequency of up to 0.38 (about 55 months) on the 1-month scale. The spatiotemporal evolutions of the 2015–2016 drought event imaged by 3-month MGDI and 12-month SPI are generally consistent, and 3-month MGDI shows good temporal continuity of evolution. Investigation of drought propagation in various basins shows that 1-month MGDI correlates well with SPI on the specific time scales (e.g., 6-month, 11-month, 13-month, and 14-month), with all correlation coefficients above 0.55. In the Amazon Basin, we also find that MGDI on the 1.5–3 years scale is strongly correlated with El Niño-Southern Oscillation (ENSO) events, suggesting hydrological droughts are likely to be modulated by ENSO. Our findings imply that MGDI can characterize hydrological deficits more comprehensively and offer some critical insights for multiscale drought research.

Evaluation of Terrestrial Water Storage Changes and Major Driving Factors Analysis in Inner Mongolia, China.

Quantitative assessment of the terrestrial water storage (TWS) changes and the major driving factors have been hindered by the lack of direct observations in Inner Mongolia, China. In this study, the spatial and temporal changes of TWS and groundwater storage (GWS) in Inner Mongolia during 2003-2021 were evaluated using the satellite gravity data from the Gravity Recovery and Climate Experiment (GRACE) and the GRACE Follow On combined with data from land surface models. The results indicated that Inner Mongolia has experienced a widespread TWS loss of approximately 1.82 mm/yr from 2003-2021, with a more severe depletion rate of 4.15 mm/yr for GWS. Meteorological factors were the driving factors for water storage changes in northeastern and western regions. The abundant precipitation increased TWS in northeast regions at 2.36 mm/yr. Anthropogenic activities (agricultural irrigation and coal mining) were the driving factors for water resource decline in the middle and eastern regions (especially in the agropastoral transitional zone), where the decrease rates were 4.09 mm/yr and 3.69 mm/yr, respectively. In addition, the severities of hydrological drought events were identified based on water storage deficits, with average severity values of 17 mm, 18 mm, 24 mm, and 33 mm for the west, middle, east, and northeast regions, respectively. This study established a basic framework for water resource changes in Inner Mongolia and provided a scientific foundation for further water resources investigation.

Gravity yearly transient change around the epicenter of 2022 MS 6.9 Menyuan earthquake, China and seismotectonic implications

The MS 6.9 Menyuan earthquake occurred in the northeastern Tibetan Plateau on 8 January 2022. High-precision absolute gravity observations provide a unique perspective on seismotectonic feature of strong continental earthquakes. An obvious and coincident gravity increase about 5 years before the Menyuan earthquake with the rate up to 3.94 μGal/yr is observed at four absolute gravity stations within 350 km away from the epicenter. These four stations have been carried out repeat gravity observations by the Crustal Movement Observation Network of China (CMONOC) for more than a decade. The observed gravity changes could not be reasonably explained by the land water storage change nor crustal vertical deformation and thus might be related to the processes in the crust. A disc-shaped equivalent source region with a radius of 175 km is then modeled, based on the residual gravity rates. We find that the seismicity increases gradually in the modeled source region from about 2017 to 2021, similar to the pattern of absolute gravity change. Furthermore, the spatiotemporal distribution of epicenters is consistent with the fluids diffusion model, indicating that this could be related to the redistribution of deep fluid mass. With consideration of the near-surface processes, regional crustal structure, and seismicity, multiple lines of evidence consistently refer to the presence of deep fluids migration before the Menyuan earthquake. Our results suggest that high-precision absolute gravimetry can be used to monitor crustal fluid environment and determine mass changes in the source regions of potential large earthquakes.

Flow regime changes in the Lancang River, revealed by integrated modeling with multiple Earth observation datasets

The flow regime change of rivers, especially transboundary rivers, affected by reservoir regulations is evident worldwide and has received much attention. Investigating dam-induced flow regime alterations is essential for understanding potential adverse downstream effects and facilitating dialogue around coordinated water use in transboundary basins, such as the Lancang River Basin (LRB). This study explored the value of combining several types of satellite Earth observation (EO) datasets that monitor different water balance components to constrain the parameter space of lumped conceptual hydrological models. Thus, we aimed to reconstruct the natural flow regimes upstream and downstream of the cascade reservoirs. Specifically, reservoir water storage changes were first estimated using satellite imagery and altimetry datasets. Then, storage changes were combined with hydrological model simulations of reservoir inflow to estimate the regulated flow regime downstream. Our results showed that integrated hydrological modeling combined with EO datasets exhibited better overall performance. Continuous warming and drying of the LRB resulted in a decrease in discharge of approximately 47 %. By comparing the simulated natural and regulated flow regimes, we revealed the pivotal role of the Xiaowan and Nuozhadu reservoirs in regulating natural flows. The wet season shortens (approximately 45 days), the flood peak flattens, and the low flow in the dry season has primarily increases. The two reservoirs attenuated 50 % of the flood peaks in the wet seasons and mitigated droughts by releasing up to 100 % of the natural flows in the dry seasons at the China–Laos border. Overall, these results enhance the understanding of upper reservoir operation, and the approaches can be applied to studies of dammed basins under climate change scenarios when knowledge of the upstream area is limited.

Mass Variations in Terrestrial Water Storage over the Nile River Basin and Mega Aquifer System as Deduced from GRACE-FO Level-2 Products and Precipitation Patterns from GPCP Data

Changes in the terrestrial total water storage (TWS) have been estimated at both global and river basin scales from the Gravity Recovery and Climate Experiment (GRACE) mission and are still being detected from its GRACE Follow-On (GRACE-FO) mission. In this contribution, the sixth release of GRACE-FO (RL06) level-2 products applying DDK5 (decorrelation filter) were used to detect water mass variations for the Nile River Basin (NRB) in Africa and the Mega Aquifer System (MAS) in Asia. The following approach was implemented to detect the mass variation over the NRB and MAS: (1) TWS mass (June 2018–June 2021) was estimated by converting the spherical harmonic coefficients from the decorrelation filter DDK 5 of the GRACE-FO Level-2 RL06 products into equivalent water heights, where the TWS had been re-produced after removing the mean temporal signal (2) Precipitation data from Global Precipitation Climatology Project was used to investigate the pattern of change over the study area. Our findings include: (1) during the GRACE-FO period, the mass variations extracted from the RL06-DDK5 solutions from the three official centers—CSR, JPL, and GFZ—were found to be consistent with each other, (2) The NRB showed substantial temporal TWS variations, given a basin average of about 6 cm in 2019 and about 12 cm in 2020 between September and November and a lower basin average of about −9 cm in 2019 and −6 cm in 2020 in the wet seasons between March and May, while mass variations for the MAS had a relatively weaker temporal TWS magnitude, (3) the observed seasonal signal over the NRB was attributed to the high intensity of the precipitation events over the NRB (AAP: 1000–1800 mm yr−1), whereas the lack of the seasonal TWS signal over the MAS was due to the low intensity of the precipitation events over the MAS (AAP: 180–500 mm yr−1).

Multisource remote sensing data facilitate ecohydrological simulations without runoff calibration

AbstractObserved runoff is typically the only variable applied to calibrate ecohydrological models, which can simulate runoff well but cannot guarantee reliable reproduction of other hydrological components (e.g., evapotranspiration (ET) and total terrestrial water storage change (TWSC)). This study explores the potential of estimating hydrological components (runoff, ET, TWSC, groundwater, and root‐zone water storage.) using a conceptual model driven and calibrated by multisource remote sensing data only. The performances of the model were evaluated in 13 catchments with different geological, climatic and vegetation conditions. Results show that the model was encouraging in simulating monthly runoff (median KGE, 0.71; RMSE, 19.4 mm/mon), ET (median KGE, 0.86; RMSE, 9.0 mm/mon), and TWSC (median KGE, 0.58; RMSE, 26.6 mm/mon). The good positive correlation between root‐zone water storage and gross primary productivity also indicates the effectiveness of the model in simulating root‐zone water storage. This study offers new prospects for estimating key ecohydrological components precisely, especially in catchments that are difficult to monitor (e.g., karst regions) and catchments with limited observation data (e.g., ungauged regions).

Hydrologic Model Calibration With Remote Sensing Data Products in Global Large Basins

AbstractParameters of hydrologic models are typically calibrated using in situ runoff observations. This calibration strategy cannot be implemented when runoff observations are not available. Additionally, the high accuracy of runoff simulation does not guarantee high simulation accuracy of other hydrologic variables, such as evaporation (ET) and terrestrial water storage change (TWSC), leading to uncertainties in hydrologic predictions. To overcome the shortcomings of the runoff‐based calibration strategy, ET and TWSC products from remote sensing were used to design parameter calibration schemes in 59 large basins worldwide. Runoff observations were used to evaluate the effects of different calibration schemes. Results show that single‐objective calibration schemes using the ET or TWSC products for parameter calibrations cannot obtain acceptable runoff simulations. Multi‐objective calibration schemes using the combination of ET and TWSC products for parameter calibrations had better runoff simulation accuracy. The multi‐objective calibration scheme using the combination of ET product adjusted by the Budyko formula and TWSC product as the calibration objective had the best runoff simulation accuracy. It is necessary to adjust ET products before using them for parameter calibrations of hydrologic models. The Budyko formula can be used to reduce the bias in remote sensing ET products, thereby providing better constraints on hydrologic simulations. We also find that different precipitation products used as inputs to hydrologic models can significantly affect the accuracy of runoff simulations. The results are expected to promote the application of remote sensing products in hydrologic simulations and predictions.

Assessment of JSBACHv4.30 as a land component of ICON-ESM-V1 in comparison to its predecessor JSBACHv3.2 of MPI-ESM1.2

Abstract. We assess the land surface model JSBACHv4 (Jena Scheme for Biosphere Atmosphere Coupling in Hamburg version 4), which was recently developed at the Max Planck Institute for Meteorology as part of the effort to build the new Icosahedral Nonhydrostatic (ICON) Earth system model (ESM), ICON-ESM. We assess JSBACHv4 in simulations coupled with ICON-A, the atmosphere model of ICON-ESM, hosting JSBACHv4 as land component to provide the surface boundary conditions. The assessment is based on a comparison of simulated albedo, land surface temperature (LST), leaf area index (LAI), terrestrial water storage (TWS), fraction of absorbed photosynthetic active radiation (FAPAR), net primary production (NPP), and water use efficiency (WUE) with corresponding observational data. JSBACHv4 is the successor of JSBACHv3; therefore, another purpose of this study is to document how this step in model development has changed model biases. This is achieved by also assessing, in parallel, the results of coupled land–atmosphere simulations with the preceding model ECHAM6 hosting JSBACHv3. Large albedo biases appear in both models over ice sheets and in central Asia. The temperate to boreal warm bias observed in simulations with JSBACHv3 largely remained in JSBACHv4, despite the very good agreement with observed LST in the global mean. For the assessment of changes in land water storage, a novel procedure is suggested to compare the gravitational data from the Gravity Recovery And Climate Experiment (GRACE) satellites to simulated TWS. It turns out that the agreement of the changes in the seasonal cycle of TWS is sensitive to the representation of precipitation in the atmosphere model. The LAI is generally too high, which is partly caused by too high soil moisture and also by the parameterization of the phenology itself. The pattern of WUE is, for both models, largely as observed. In India, WUE is too high, probably because JSBACH does not incorporate irrigation in our simulations. WUE differences between the two models can be traced back to differences in precipitation patterns in the two coupled land–atmosphere simulations. For both models, most NPP biases can be associated with biases in water stress, LAI, and FAPAR. In particular, the NPP bias of the Eurasian steppes has switched from positive in JSBACHv3 to negative in JSBACHv4. This difference is mainly caused by weaker precipitation and lower FAPAR of ICON-A–JSBACHv4 in July, which is most probably caused by a feedback loop between too little soil moisture, evaporation, and clouds. While the size and patterns of biases in albedo and LST are largely similar between the two model versions, they are less well correlated for precipitation- and vegetation-related variables like FAPAR. Overall, the biases found in the different assessment variables are either already known from the previous implementation in the Max Planck Institute Earth System Model (MPI-ESM) or have changed because of the coupling with the new atmospheric component ICON-A. Accordingly, this study demonstrates the technically successful completion of the re-implementation of JSBACH into ICON-ESM-V1. As discussed, there is a good perspective on mitigating the biases by an improved representation of the processes.

Delineation of Aquifer Boundary by Two Vertical Superconducting Gravimeters in a Karst Hydrosystem, France

Mass distribution on Earth is continuously changing due to various physical processes beneath the Earth's surface or on the surface. Some of the primary sources for these mass displacements are tidal forces, atmospheric and oceanic loading, and seasonal changes in continental water distribution. The development of relative cryogenic gravimeters, the Superconducting Gravimeters (SGs), has made it possible to characterize and monitor such mass variations at orders of magnitudes as small as a few nm/s2 (1 nm/s2–10–10 g where g is the mean gravity at the Earth’s surface). Our study focuses on the hydrodynamics of the 900 m thick unsaturated zone of the low-noise underground research laboratory (Laboratoire Souterrain à Bas Bruit, LSBB) located in Rustrel (France) using a unique configuration of two SGs vertically arranged 520 m depth apart. The installation of an SG (iGrav31) at the site surface several years after installing the first (iOSG24) inside a tunnel has provided several new insights into the understanding of the hydrological processes occurring in the LSBB. By comparing differential and residual gravity time-series together with global hydrological loading models, we find that most water-storage changes occur in the unsaturated zone between both SGs. The misfit between the observed gravity time-series and the gravity effect corresponding to local hydrological contribution calculated from global hydrological models can be explained by large lateral fluxes and rapid runoff occurring in the LSBB site. Finally, we implement a rectangular prism method to compute forward gravity responses to water storage changes for a homogeneous water-layer following the site topography using a 5-m digital elevation model. In particular, we analyse the sensitivity of the differential record from both SGs to the extent and depth of the water storage changes by computing the corresponding 2D admittances. This gravity difference is sensitive to an extension up to about 2500 m laterally before tending towards an asymptotic value corresponding to the Bouguer plate approximation. We show that the zone of water-storage changes that best fits observed differential gravity signal is located at depths larger than 500 m (below iOSG24). This fitting is improving when the integration radius increases with depth. This is the first time that hydrological processes are investigated when the baseline configuration of two SGs is vertical.

Attribution of runoff variance in the alpine basin of Northwest China at multiple timescales

ABSTRACT Attributions of runoff variability have been widely conducted under the Budyko framework; however, the effects of snow water equivalent change (∆swe) have not been considered by this framework in alpine basins. Considering the Heihe upstream basin of Northwest China as an example, we derived runoff variance () from the variance and covariance of precipitation (P), soil water storage change (∆soil), ∆swe, potential evapotranspiration (E 0), and land surface condition (represented by Budyko’s parameter, n) on seasonal and annual scales. The results showed that P variance mainly controlled in autumn and winter. The n variance ranked first in spring and summer. The effects of P and n variance on annual were enhanced compared to their seasonal values. However, was alleviated by the interaction between factors, especially by ∆soil and n, P and ∆soil with negative contributions. The effects of ∆swe variance could not be ignored, especially in spring.

Terrestrial Water Storage Changes over the Last 20 Years in the Amazon Basin

Terrestrial Water Storage Changes over the Last 20 Years in the Amazon Basin

Spatial and Temporal Characteristics of NDVI in the Weihe River Basin and Its Correlation with Terrestrial Water Storage

The Weihe River Basin (WRB) of China is located in an arid and water-scarce semi-arid region with a fragile ecological environment, and it is meaningful to study the spatial and temporal changes in vegetation and terrestrial water storage changes in a small-scale inland basin. This study uses normalized difference vegetation index (NDVI) data and Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) time-variable gravity field models to derive changes in vegetation cover and water storage in the WRB from 2002 to 2020. Firstly, taking NDVI as the breakthrough point, the temporal and spatial characteristics of vegetation were analyzed by trend analysis method and F-test. Then, GRACE and GRACE-FO were used to derive water storage variations. Finally, the correlation between NDVI and water storage variations is discussed using the Pearson correlation analysis. The results show that the overall trend of NDVI is increasing, and the increasing trend is more evident before 2014, and after that, there is a significant fluctuation. The spatial distribution shows a large spatial variability, but the growing area still accounts for the majority, and the change varies by vegetation type, among which the cultivated vegetation is more influential. The overall change in terrestrial water storage showed a decreasing trend of −0.09 cm/yr, and also reflected a solid intra-annual regular cycle, i.e., reaching a trough from October to November and a peak from May to June each year. The correlation is 0.6 on the time scale, and there was a 3-month lag between NDVI and TWS. On the spatial scale, the percentage of areas with a negative correlation was about 95.4%, probably due to increased water consumption and evapotranspiration. The study’s results can help to understand the relationship between vegetation and water storage in the WRB and provide scientific support for local environmental management.

Assessment of Model-Derived Mass Flux Relative to Satellite Gravimetry via a Water Balance in North America

Abstract GRACE and GRACE Follow-On (GRACE-FO) mission data are utilized to assess mass flux derived from the North American Regional Reanalysis (NARR) and the NLDAS-2 Noah land surface model via multiple water balance formulations. Water balances are computed for 18 medium size basins in North America at the USGS Watershed Boundary Dataset HU2 level over the span of the GRACE and GRACE-FO missions (2002–21). Performance of model-derived mass flux is presented in the context of statistical agreement to changes in terrestrial water storage (ΔTWS) derived from Center for Space Research (CSR) GRACE RL06 mass concentrations (mascons), and GRACE and NARR uncertainty is estimated against comparable datasets. The land surface water balance method utilizing NLDAS-2 Noah consistently outperforms the total column method utilizing NARR, which is likely due to enhanced precipitation forcing and an updated Noah model version used in NLDAS-2. The surface approach to the calculation of atmospheric moisture flux divergence is carried through the presented analyses and is demonstrated to be comparable in performance to the more common volume approach. Mass balance methodology, basin characteristics, and ΔTWS signal characteristics are assessed to quantify effects on model performance and while factors such as basin size, basin average topography gradient, and ΔTWS annual amplitude are shown to have a measurable effect on model performance, no single factor exhibited a dominant or consistent effect. Drought conditions are shown to have a significant temporally localized effect on model-derived mass flux accuracy, with NARR being particularly susceptible to this effect. Significance Statement Measurements of Earth’s gravity field from the GRACE and GRACE-FO satellite missions are utilized to create estimates of water storage changes in 18 North American river basins that are compared to changes in water storage calculated from an atmospheric model reanalysis (NARR) and a land surface model (NLDAS-2 Noah). The resulting comparison demonstrates that certain basin characteristics can have a slight effect on model accuracy, while climatic conditions such as drought can have a major impact on model accuracy. This work provides useful quantification of when and where modeled water transport loses accuracy, which is integral to our understanding of the present and future distribution of this crucial resource and the natural processes that affect it.

Water use dynamics of trees in a Pinus tabuliformis plantation in semiarid sandy regions, Northeast China

Quantifying tree water use and its environmental controlling mechanisms are significantly important for understanding of adaptation strategy of trees and plantation management in semiarid and arid regions. Here, tree water consumption and tree conductance of Chinese pine (Pinus tabuliformis) plantation were quantified using sap flow measurements. Environmental variables were measured concurrently during the growing seasons of 2019 and 2020. Results showed that daily, daytime and nighttime tree water consumption averaged 27.4, 24.7, and 2.7 kg d-1 across two years, respectively. Nighttime tree water consumption accounted for 10% of the daily’s, which was mainly used for recharging stem water storage deficit caused by daytime transpiration to avoid hydraulic failure. Daytime tree water consumption was more driven by solar radiation than by vapor pressure deficit. Moreover, daytime tree conductance was 0.9 mm s-1, and significantly decreased with increasing vapor pressure deficit and decreasing soil moisture, indicating that trees had strict stomatal regulation on tree transpiration. Scaling-up from tree to stand transpiration, daytime stand transpiration averaged 1.1 mm d-1 across two years, while accumulated stand transpiration was 112.8 mm and 126.8 mm in 2019 and 2020, respectively, accounting for 33% and 37% of precipitation. However, soil evaporation occupied 35% and 51% of precipitation in 2019 and 2020, respectively. This indicated that most of water in the plantation was consumed by soil evaporation. Difference between precipitation and sum of daytime stand transpiration, canopy interception, soil evaporation, and change in soil water storage was positive in two years, indicating that water budget was balanced. These findings indicated that Chinese pine trees had strict stomatal regulation on tree transpiration, and could recharge stem water storage deficit by nighttime sap flow. Moreover, stand transpiration occupied a small part of the water balance, and thus water supply was surplus, resulting in maintaining the stability of Chinese pine plantation.

An optimized hydrological drought index integrating GNSS displacement and satellite gravimetry data

Space geodetic techniques are rapidly emerging as powerful tools for drought monitoring, including the Global Navigation Satellite System (GNSS) positioning data, and the gravimetric data from Gravity Recovery And Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) satellite missions. However, while GNSS-based 3D displacements have high temporal resolution, they are impacted by diverse local effects especially for tectonically active regions. Satellite gravimetry derived terrestrial water storage changes (ΔTWS) are continuous in temporal sampling, however, at much coarser spatial resolutions, and there are systematic noise and a large 11-month data gap between GRACE and GRACE-FO observations. Here for the first time, we developed an Optimized GNSS/GRACE/GRACE-FO Hydrological Drought Index (OGHDI), by optimally combining two drought indices derived from GNSS vertical displacements (VDs) and GRACE/GRACE-FO ΔTWS, to better characterize decadal evolution of droughts over Southwest China, 2011–2020. The optimal relative weights of the two drought indices are determined through maximizing the correlations with the Composite Index (CI) commonly used in the study region. Then OGHDI is compared to the self-calibrating Palmer Drought Severity Index (scPDSI). The results show that VDs agree well with ΔTWS at most of the 30 analyzed GNSS sites, with a mean correlation of −0.44. Compared to the drought index developed using only GNSS data, the optimized technique improved the OGHDI-scPDSI correlations at 90% (27 sites) of the sites, with the highest correlation reaches 0.73. Further, more significant improvement is found at the regional scale than at individual sites, and the regional mean OGHDI-CI and OGHDI-scPDSI correlations increase from 0.37 to 0.57 and from 0.42 to 0.68, respectively. All drought indices show that Southwest China experienced two sustained and excessive drought periods from 2011 to mid-2013, and after 2019. We conclude that the novel integration of two distinct contemporary and complemenatry geodetic datasets, GNSS and GRACE/GRACE-FO, improved the ability of drought monitoring in Southwest China.

The interactive feedback mechanisms between terrestrial water storage and vegetation in the Tibetan Plateau

A component of terrestrial water storage, vegetation is also an influential driver of changes in terrestrial water storage. In the context of warming on the Tibetan Plateau, it is essential to explore the relationship between changes in terrestrial water storage and vegetation in this region to understand further the role of vegetation in the changes of water systems in alpine mountains. Our study combines terrestrial water storage anomalies data and vegetation indices to determine how their interact. The results indicate a warming rate of 0.44°C/decade (p<0.01) over the Tibetan Plateau from 1980–2020, while evapotranspiration trended upward (12.9 mm/decade, p<0.01), which is slower than precipitation (15 mm/decade, p<0.01). On the Tibetan Plateau, spatial-temporal differences in temperature, precipitation, and evapotranspiration dominate the variations in terrestrial water storage. The change in terrestrial water storage was relatively stable from 2003 to 2011, but decreased from 2012 to 2016. Terrestrial water storage increased in endorheic basins while decreasing in exorheic basins. Partial correlation analysis indicates a negative correlation between the terrestrial water storage anomaly and the temperature. It is found that terrestrial water storage and net precipitation are positively correlated in the Yangtze River Basin and the northeast of the endorheic basins. However, the Qaidam Basin and the north part of the Yellow River Basin are negatively correlated. Under the current climate change state (the increased rate of precipitation is faster than actual evapotranspiration), vegetation change has an insignificant impact on the changes in terrestrial water storage. In contrast, changes in terrestrial water storage (surplus/deficit) significantly affect vegetation changes (greening/browning) in parts of the Tibetan Plateau. The study contributes to a deeper understanding of the relationship between water system changes and vegetation on the Tibetan Plateau.

Impacts of sea-level rise on groundwater inundation and river floods under changing climate

Rising sea levels increase coastal extreme events of inundation along the global coastlines. Existing hydrologic and groundwater models simulate inundation processes but simplify groundwater-surface water interactions, a key control on flood generation in coastal areas. Here we apply a coupled surface–subsurface hydrologic model to evaluate the sensitivity of shallow groundwater to sea-level rise across three watersheds in Southeast China. It was found that historical decrease of annual rainfall resulted in no changes in total water storage but lower streamflow. Sea-level rise can increase low flow and local groundwater inundation, without changes in total water storage. GIS analysis of elevation can give a first approximation of vulnerability to marine inundation. Our physics-based modeling approach helped capture the temporal dynamics of water table and improved process understanding on coastal flooding. This study provides a new insight to quantify the spatiotemporal dynamics of groundwater inundation and river floods across coastal watersheds.