Evaluation of groundwater sustainability in the arid Hexi Corridor of Northwestern China, using GRACE, GLDAS and measured groundwater data products

Long-term spatiotemporal dynamics of groundwater storage in the data-scarce region: Tana sub-basin, Ethiopia

Imprudent extraction of groundwater tends to undue stress and portends its sustainability. Spatiotemporal analysis of groundwater storage anomaly (GWSA) is imperative for the judicious use, management, and sustainable development of a region. This study aimed to examine the changes in groundwater storage over the past 20 years in the Tana sub-basin using Gravity Recovery and Climate Experiment (GRACE) assimilated into Global Land Data Assimilation Systems (GLDAS). Validation analysis was carried out to evaluate the accuracy of GWSA against anomalies of Lake Tana water level, precipitation, and in-situ groundwater level. Modified Mann-Kendal test and Sen's slope estimator were applied for trend analysis of the GWSA. The results exhibited that GWSA strongly correlated (Pearson's correlation coefficient, R ranges from 0.75 to 0.96) with the three validation above variables, which elucidated in general, credible GWSA estimation. The net annual GWSA curve showed a non-significant (p > 0.05) decreasing trend from 2003 to 2012. However, years including 2005, 2006, and 2009 were drought periods, which caused 0.49 billion cubic meters (BCM) groundwater loss. In the entire study period (2003-2022), on the other hand, the net annual GWSA revealed a significant increasing trend (p < 0.05) with a rate of 0.333 cm/year. Generally, the Tana sub-basin was nurtured with a net 4.87 BCM groundwater gain in the study period. The most sensitive parts of the study area to large fluctuations of groundwater storage were mainly the nearby southern and eastern directions of Lake Tana.

Spatial and temporal downscaling schemes to reconstruct high-resolution GRACE data: A case study in the Tarim River Basin, Northwest China

Climate change and excessive exploitation of water resources exert pressure on groundwater supply and the ecosystem in drylands. Although The Gravity Recovery and Climate Experiment (GRACE) satellites has demonstrated the feasibility of quantifying global groundwater storage variations, monitoring regional-scale groundwater has been challenging due to the coarse resolution of GRACE. Previous GRACE downscaling studies focused on develop new algorithms based on the perspective of pixel spatial correlation to improve resolution, which cannot better capture the temporal evolution of GRACE data effectively. In this study, we employ the semi-supervised variational autoencoder (SSVAER) algorithm and the multi-scale geographically weighted regression (MGWR) model to establish two different downscaling schemes: pixel temporal continuity downscaling and pixel spatial correlation downscaling. These schemes achieve spatial resolution downscaling of GRACE-derived groundwater storage anomalies (GWSA) from 0.5° to 0.1°. Additionally, the applicability of the PCR-GLOBWB model in drylands is verified. Furtherly, the spatiotemporal distribution patterns of GWSA are analyzed. The results show that (1) Both the temporal and spatial downscaling methods produced consistent results, with data correlations ranged from 0.94 to 0.98 observed in over 80 % of the range before and after downscaling; (2) The groundwater storage change rate in the northern Tarim River Basin (TRB) is 25 times greater than the model results, while in other regions, the average deviation is 2.6 times; (3) The two schemes enhance the correlation (0.27) between GWSA and groundwater level anomaly (GWLA) to 0.59 and 0.52, respectively, with a three-month lag in GWSA relative to GWLA. The temporal downscaling approach exhibited higher CC and lower RMSE, outperforming the spatial downscaling approach. The high-resolution results in this study can well complement groundwater level prediction efforts in arid regions and provide quantitative information for local water resource management.

Evaluating the Hydrological Components Contributions to Terrestrial Water Storage Changes in Inner Mongolia with Multiple Datasets

In this study, multiple remote sensing data were used to quantitatively evaluate the contributions of surface water, soil moisture and groundwater to terrestrial water storage (TWS) changes in five groundwater resources zones of Inner Mongolia (GW_I, GW_II, GW_III, GW_IV and GW_V), China. The results showed that TWS increased at the rate of 2.14 mm/a for GW_I, while it decreased at the rate of 4.62 mm/a, 5.89 mm/a, 2.79 mm/a and 2.62 mm/a for GW_II, GW_III, GW_IV and GW_V during 2003-2021. Inner Mongolia experienced a widespread soil moisture increase with the rate of 4.17 mm/a, 2.13 mm/a, 1.20 mm/a, 0.25 mm/a and 1.36 mm/a for the five regions, respectively. Significant decreases were detected for regional groundwater storage (GWS) with the rate of 2.21 mm/a, 6.76 mm/a, 6.87 mm/a, 3.01 mm/a, and 4.14 mm/a, respectively. Soil moisture was the major contributor to TWS changes in GW_I, which accounted 58% of the total TWS changes. Groundwater was the greatest contributor to TWS changes in other four regions, especially GWS changes, which accounted for 76% TWS changes in GW_IV. In addition, this study found that the role of surface water was notable for calculating regional GWS changes.

Groundwater recharge estimation using in-situ and GRACE observations in the eastern region of the United Arab Emirates

The intensive agricultural expansion and rapid urban development in Abu Dhabi Emirate, United Arab Emirates (UAE) have resulted in a major decline in local and regional groundwater levels. By using the latest release (RL06) of Gravity Recovery and Climate Experiment (GRACE) satellite measurements and Global Land Data Assimilation System (GLDAS) products, the groundwater storage change was computed and compared with the time series of in-situ monitoring wells over the period of 2010-2016. The RL06 GRACE products from Jet Propulsion Laboratory (JPL), University of Texas Center for Space Research (CSR), German Research Center for Geosciences (GFZ), and JPL mass concentrations (MASCON) were assessed and have shown satisfactory agreements with the monitoring wells. The JPL MASCON reflected the in-situ groundwater storage change better than the other GRACE products (R = 0.5, lag =1 month, RMSE = 13 mm). The groundwater recharge is estimated for the study area and compared with the in-situ recharge method that considers multi recharge components from the rainfall, irrigation return flow and internal fluxes. The results show that the agreements between in-situ and GRACE-derived recharge estimates are highly agreeable (e.g., R² = 0.91, RMSE = 1.5 Mm³ to 7.8 Mm³, and Nash-Sutcliff Efficiency = 0.7). Using the Mann-Kendall trend test and Sen's slope, the analyses of policies, number of wells, and farm areal expansion with groundwater time series derived from GRACE helped to validate GRACE and emphasize the importance of regulations for sustainable development of groundwater resources. The impacts of subsidy cuts after 2010 can be captured from the GRACE data in the eastern region of Abu Dhabi Emirate. The linear trend of groundwater storage anomaly obtained from GRACE over the period from 2003 to 2010 is -6.36 ± 0.6 mm/year while it showed a decline trend of -1.2 ± 0.6 mm/year after the subsidy cut. The proposed approach has a potential application for estimating groundwater recharge in other arid regions where in-situ monitoring wells are limited or absent.

The role of land use change in affecting ecosystem services and the ecological security pattern of the Hexi Regions, Northwest China

The land use and land cover change (LUCC) associated with climate change and human activities is supposed to exert a significant effect on ecosystem functions in arid inland regions. However, the role of LUCC in shaping the spatio-temporal patterns of ecosystem services and ecological security remain unclear, especially under different future LUCC scenarios. Here, we evaluated dynamic changes of ecosystem services and ecological security pattern (ESP) in the Hexi Regions based on LUCC and other environment variables by integrating morphological spatial pattern analysis (MSPA), entropy weight method and circuit theory. Our result showed that the LUCC was generally stable from 1980 to 2050. Compare to 2020, the land conversion under natural growth (NG), ecological protection (EP) and urban development (UD) scenarios in 2050 has changed by 10.30 %, 10.10 %, and 10.31 %, respectively. The forest, medium-cover grassland and water increased in the EP scenario, and construction land and cropland greatly expanded in the other two scenarios. Ecosystem services grew larger in the EP scenario by 2050 in comparison with the NG and UD scenarios. The ESP in the Hexi Regions has obvious spatial differences during 1980-2050. The larger ecological sources and less resistance corridors were mainly distributed in the central and eastern of the Hexi Regions with high ecosystem services. Conversely, fragmented ecological sources and larger resistance corridors were mostly located in the western regions blocked by sandy land, bare land or mountains. Compared to 2020, the area of ecological sources and pinch points under the EP scenario in 2050 increased by 4.10 × 10³ km² and 0.31 × 10³ km², respectively. The number of ecological corridors reduced while the length and resistance increased apart from the EP scenario. Our results highlighted the importance of ecological protection in shaping the LUCC, which further enhances the integrity of ecosystem and ecological security.

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.

Evaluating aquifer stress and resilience with GRACE information at different spatial scales in Cambodia

Groundwater exploitation for different sectors in Cambodia is expanding. Groundwater levels have already begun to decline in some parts of the country. Monitoring and assessing groundwater storage (GWS) change, aquifer stress and aquifer resilience will support the proper planning and management of the country's groundwater resources; however, information regarding groundwater in Cambodia is currently scarce. Thus, GWS change in Cambodia over the 15 years from April 2002 to March 2017 was assessed using remote-sensing-based Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) datasets, with a comprehensive validation of the GRACE-derived groundwater storage anomaly (GWSA) with respect to in-situ field-based observations. The current study also investigated the impact of surface water storage (SWS) change in Tonle Sap Lake, South-East Asia's largest freshwater lake, on deriving the GWS change in Cambodia. The groundwater aquifer stresses (GAS), and aquifer resilience (AR) were also evaluated. The validation results were promising, with the correlation coefficient between satellite-based estimations and ground-based measurements ranging from 0.82 to 0.88 over four subbasins. The overall decreasing rate of GWS was found to be -0.63 mm/month, with two basins having the highest declining rate of more than 1.4 mm/month. Meanwhile, the aquifer experiencing stress during the dry season had a very low ability to quickly recover from these stresses. These findings emphasise that appropriate management is urgently needed to ensure the sustainability of the groundwater resource system in this country.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10040-022-02570-w.

Combining downscaled-GRACE data with SWAT to improve the estimation of groundwater storage and depletion variations in the Irrigated Indus Basin (IIB)

The growth of agricultural production systems is a major driver of groundwater depletion worldwide. Balancing groundwater supply and food production requires localized understanding of groundwater storage and depletion variations in response to diverse cropping systems and surface water availability for irrigation. While advances through Gravity Recovery and Climate Experiment (GRACE) have facilitated estimating the groundwater storage (GWS) changes in recent years, the coarse resolution of GRACE data hinders the characterization of GWS variation hotspots. Herein, we present a novel spatial water balance approach to improve the distributed estimation of groundwater storage and depletion changes at a spatial scale that can detect the hotspots of GWS variation. We used a mixed geographically weighted regression (MGWR) model to downscale GRACE Level-3 data from coarse resolution (1° × 1°) to fine scale (1 km × 1 km) based on high resolution environmental variables. We then combined the downscaled GRACE-based GWS variations with results from a calibrated Soil and Water Assessment Tool (SWAT) model. We demonstrate an application of the approach in the Irrigated Indus Basin (IIB). Between 2002 and 2019, total loss of groundwater reserves varied in the IIB's 55 canal command areas with the highest loss observed in Dehli Doab by >50 km³ followed by 7.8-49 km³ in the upstream, and 0.77-7.77 km³ in the downstream canal command areas. GWS declined by -325.55 mm/year at Dehli Doab, followed by -186.86 mm/year at BIST Doab, -119.20 mm/year at BARI Doab, and -100.82 mm/year at JECH Doab. The rate of groundwater depletion is increasing in the canal command areas of Delhi Doab and BIST Doab by 0.21-0.35 m/year. Larger groundwater depletion in some canal command areas (e.g., RACHNA, BIST Doab, and Delhi Doab) is associated with the rice-wheat cropping system, low rainfall, and low flows from tributaries.

Oasis sustainability assessment in arid areas using GRACE satellite data

An oasis is an important habitat for humans, plants, and wildlife in arid desert areas. The sustainability of an oasis is crucial for a smooth regional ecological functioning and healthy economic development. However, the overexploitation of groundwater will result in unsustainable oasis development. Due to the lack of long-term groundwater monitoring data, the impact of groundwater level changes on the sustainability of an oasis has not been studied extensively. In the present study, we used the ground water storage anomaly (GWSA) in combination with the Gravity Recovery and Climate Experiment (GRACE) and the Global Land Data Assimilation System (GLDAS) for the rapid identification of oasis sustainability, which has been tested and evaluated in Hotan and Qira oasis located in arid areas. The results showed that (1) the GWSA is a suitable and reliable indicator for trend change analysis in small-scale oasis and, (2) additionally, M-K test results for long-term trend change of GWSA showed a positive correlation with water resource carrying capacity (WRCC). These results suggest that GWSA can be used as a reliable index for the rapid assessment of oasis sustainability status in arid areas. Moreover, the potential applicability of GRACE satellite data in evaluating the groundwater sustainability in arid areas lacking proper data has also been proved in this study. These findings have provided a foundation to evaluate the sustainability status of an oasis and set a reference point to formulate future policies for the oasis.

Evaluation of Groundwater Storage Depletion Using GRACE/GRACE Follow-On Data with Land Surface Models and Its Driving Factors in Haihe River Basin, China

Groundwater storage (GWS) in the Haihe River Basin (HRB), which is one of the most densely populated and largest agricultural areas in China, is of great importance for the ecosystem environment and socio-economic development. In recent years, large-scale overexploitation of groundwater in HRB has made it one of the global hotspots of GWS depletion. In this study, monthly GWS variations in HRB from 2003 to 2020 were estimated using the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) data in combination with three land surface models (LSMs) from the Global Land Data Assimilation System (GLDAS). The results show the following: (1) HRB suffered extensive GWS depletion from 2003 to 2020, which has been aggravated since 2014, with a mean rate of 1.88 cm·yr−1, which is equivalent to a volume of 6 billion m3·yr−1. The GWS depletion is more serious in the plain zone (−2.36 cm·yr−1) than in the mountainous zone (−1.63 cm·yr−1). (2) Climate changes are excluded from the reasons for GWS depletion due to annual precipitation and evaporation being close to normal throughout the period. In addition, GWS changes show a low correlation with meteorological factors. (3) The consumption of groundwater for irrigation and land use/cover changes have been confirmed to be the dominant factors for GWS depletion in HRB. (4) The effects of inter-basin water transfer projects cannot be obviously observed using the GRACE and GRACE-FO; more inter-basin water transfers are needed for recovering the GWS in HRB. Therefore, it is imperative to control groundwater exploitation and develop a more economical agricultural irrigation structure for the sustainability of groundwater resources in HRB.

Improving the Accuracy of Groundwater Storage Estimates Based on Groundwater Weighted Fusion Model

It is an effective measure to estimate groundwater storage anomalies (GWSA) by combining Gravity Recovery and Climate Experiment (GRACE) data and hydrological models. However, GWSA results based on a single hydrological model and GRACE data may have greater uncertainties, and it is difficult to verify in some regions where in situ groundwater-level measurements are limited. First, to solve this problem, a groundwater weighted fusion model (GWFM) is presented, based on the extended triple collocation (ETC) method. Second, the Shiyang River Basin (SYRB) is taken as an example, and in situ groundwater-level measurements are used to evaluate the performance of the GWFM. The comparison indicates that the correlation coefficient (CC) and Nash-Sutcliffe efficiency coefficient (NSE) are increased by 9–40% and 23–657%, respectively, relative to the original results. Moreover, the root mean squared error (RMSE) is reduced by 9–28%, which verifies the superiority of the GWFM. Third, the spatiotemporal distribution and influencing factors of GWSA in the Hexi Corridor (HC) are comprehensively analyzed during the period between 2003 and 2016. The results show that GWSA decline, with a trend of −2.37 ± 0.38 mm/yr from 2003 to 2010, and the downward trend after 2011 (−0.46 ± 1.35 mm/yr) slow down significantly compared to 2003–2010. The spatial distribution obtained by the GWFM is more reliable compared to the arithmetic average results, and GWFM-based GWSA fully retain the advantages of different models, especially in the southeastern part of the SYRB. Additionally, a simple index is used to evaluate the contributions of climatic factors and human factors to groundwater storage (GWS) in the HC and its different subregions. The index indicates that climate factors occupy a dominant position in the SLRB and SYRB, while human factors have a significant impact on GWS in the Heihe River Basin (HRB). This study can provide suggestions for the management and assessments of groundwater resources in some arid regions.

Overview of terrestrial water storage changes over the Indus River Basin based on GRACE/GRACE-FO solutions

Water resources are under severe stress in the highly populated Indus River Basin due to the increased consumption of water across different sectors and climate change. Coping with these challenges, requires a clear understanding on hydrological processes and anthropogenic activities, and how these are influencing recharging and spatiotemporal availability of groundwater in the basin. The present study aims to investigate the natural and anthropogenic impact on Terrestrial Water Storage (TWS) over the Indus River Basin by using a series of statistical methods and the observation data from the Gravity Recovery and Climate Experiment (GRACE) and Follow-On (GRACE-FO). Our results show that (i) TWS Anomaly (TWSA) experienced a significant decrease from 2002 to 2020, particularly in the MUIP; (ii) the UIB showed a weak decreasing trend in TWSA as a result of the accelerated glacier melting; (iii) there was significant loss of groundwater (1.57 mm/month) caused by ineffective water management and over-exploitation; and (iv) assisted by favorable meteorological conditions, the precipitation presented a positive trend against the weakness of the Westerlies, which exerted the positive influence on TWSA.

Improved Understanding of Groundwater Storage Changes under the Influence of River Basin Governance in Northwestern China Using GRACE Data

Groundwater is crucial for economic development in arid and semiarid areas. The Shiyang River Basin (SRB) has the most prominent water use issues in northwestern China, and overexploited groundwater resources have led to continuous groundwater-level decline. The key governance planning project of the SRB was issued in 2007. This paper synthetically combines remote-sensing data from Gravity Recovery and Climate Experiment (GRACE) data and precipitation, actual evapotranspiration, land use, and in situ groundwater-level data to evaluate groundwater storage variations on a regional scale. Terrestrial water storage anomalies (TWSA) and groundwater storage anomalies (GWSA), in addition to their influencing factors in the SRB since the implementation of the key governance project, are analyzed in order to evaluate the effect of governance. The results show that GRACE-derived GWS variations are consistent with in situ observation data in the basin, with a correlation coefficient of 0.68. The GWS in the SRB had a slow downward trend from 2003 to 2016, and this increased by 0.38 billion m³/year after 2018. As the meteorological data did not change significantly, the changes in water storage are mainly caused by human activities, which are estimated by using the principle of water balance. The decline in GWS in the middle and lower reaches of the SRB has been curbed since 2009 and has gradually rebounded since 2014. GWS decreased by 2.2 mm EWH (equivalent water height) from 2011 to 2016, which was 91% lower than that from 2007 to 2010. The cropland area in the middle and lower reaches of the SRB also stopped increasing after 2011 and gradually decreased after 2014, while the area of natural vegetation gradually increased, indicating that the groundwater level and associated ecology significantly recovered after the implementation of the project.

Improving wheat grain yield via promotion of water and nitrogen utilization in arid areas

Crop yield is limited by water and nitrogen (N) availability. However, in Hexi Corridor of northwestern China, water scarcity and excessive fertilizer N in wheat (Triticum aestivum L.) production causes serious conflicts between water and N supply and crop demand. A field experiment was conducted from 2016 to 2018 to evaluate whether reducing of irrigation and fertilizer N will reduce grain yield of wheat. There were two irrigation quotas (192 and 240 mm) and three fertilizer N rates (135, 180, and 225 kg N ha⁻¹). The results showed that reducing irrigation to 192 mm and N rate to 180 kg N ha⁻¹ reduced water uptake, water uptake efficiency, and N uptake of spring wheat as compared to local practice (i.e., 240 mm irrigation and 225 kg N ha⁻¹ fertilizer). Whereas, it improved water and N utilization efficiency, and water and N productivity. Consequently, the irrigation and N rate reduced treatment achieved the same quantity of grain yield as local practice. The path analysis showed that interaction effect between irrigation and N fertilization may attributable to the improvement of grain yield with lower irrigation and N rate. The enhanced water and N utilization allows us to conclude that irrigation quota at 192 mm coupled with fertilizer N rate at 180 kg N ha⁻¹ can be used as an efficient practice for wheat production in arid irrigation areas.

Deterministic Analysis and Uncertainty Analysis of Ensemble Forecasting Model Based on Variational Mode Decomposition for Estimation of Monthly Groundwater Level

Precise multi-time scales prediction of groundwater level is essential for water resources planning and management. However, credible and reliable predicting results are hard to achieve even to extensively applied artificial intelligence (AI) models considering the uncontrollable error, indefinite inputs and unneglectable uncertainty during the modelling process. The AI model ensembled with the data pretreatment technique, the input selection method, or uncertainty analysis has been successfully used to tackle this issue, whereas studies about the comprehensive deterministic and uncertainty analysis of hybrid models in groundwater level forecast are rarely reported. In this study, a novel hybrid predictive model combining the variational mode decomposition (VMD) data pretreatment technique, Boruta input selection method, bootstrap based uncertainty analysis, and the extreme learning machine (ELM) model named VBELM was developed for 1-, 2- and 3-month ahead groundwater level prediction in a typical arid oasis area of northwestern China. The historical observed monthly groundwater level, precipitation and temperature data were used as inputs to train and test the model. Specifically, the VMD was used to decompose all the input-outputs into a set of intrinsic mode functions (IMFs), the Boruta method was applied to determine input variables, and the ELM was employed to forecast the value of each IMF. In order to ascertain the efficiency of the proposed VBELM model, the performance of the coupled model (VELM) hybridizing VMD with ELM algorithm and the single ELM model were estimated in comparison. The results indicate that the VBELM performed best, while the single ELM model performed the worst among the three models. Furthermore, the VBELM model presented lower uncertainty than the VELM model with more observed groundwater level values falling inside the confidence interval. In summary, the VBELM model demonstrated an excellent performance for both certainty and uncertainty analyses, and can serve as an effective tool for multi-scale groundwater level forecasting.

Estimation of the Qinghai-Tibetan Plateau runoff and its contribution to large Asian rivers

The Qinghai-Tibetan Plateau (QTP), named the Asian Water Towers, feeds more than 2.5 billion people in downstream regions. It is still unknown how much water outflows from this region owing to lack of observations. The main objective of this study is to clarify availability of water flowed out of this region and its contribution to large Asian rivers. The Global Land Data Assimilation System (GLDAS) products are evaluated with the help of observations of the QTP. In addition, a velocity-based routing method is embedded into the GLDAS model to route runoff products to the basin outlet in this study. The results show that the simulated dry season runoff in the GLDAS model is generally lower than the observed value, which is mainly because most hydrological models only consider the potential evapotranspiration (ET) when simulating ET, while ignoring the water constraint factor. Noah10_v2.0 has the highest precision at the QTP. For the monthly precipitation and runoff series, the relative error is within 5%, the correlation coefficient is greater than 0.90, and the Nash-Sutcliffe efficiencies are 0.95 and 0.76, respectively. Glacier melt runoff plays an important role in the QTP runoff, with a proportion of approximately 22%. It is relatively high in the Tarim River basin (83%), Syr Darya River and Amu Darya River basins (69%), and Indus River basin (60%). The contribution ratio also reaches 23% in the Yarlung Zangbo-Brahmaputra River and Ganges River basins, whereas it is the lowest in the Irrawaddy River basin (2%). According to the Noah10_v2.0 simulations, the mean annual runoff provided by the QTP exceeds 620 billion cubic metres, of which approximately 440 billion cubic metres flow out of the QTP and supply downstream regions of international rivers. The contribution ratio of the QTP runoff to the total runoff of its affected basins is approximately 16%.