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Global human‐induced warming has intensified water circulation in the atmospheric environment and altered the streamflow generation regime. The VIC hydrological model approach for impact assessment of climate change and human activities mainly focuses on variations in streamflow, but ignores other critical flooding characteristics induced by extreme streamflow, especially bivariate flooding characteristics. In this work, the copula functions are employed to structure the flooding risk under the shared socioeconomic pathway (SSP) across the Yellow River basin (YRB). This is based on the multi‐model ensemble (MME) and Delta downscaling outputs (Delta‐MME) of the CMIP6 global climate models (GCMs), as well as the flooding characteristics simulated by VIC hydrological model. Compared to the reference period (1995–2014), Delta‐MME reveals a significant warming and humidifying trend under three SSPs over the YRB. Despite uncertainties originating from climate variables and hydrological model, multiple findings underscore the substantial influence of climate change on the flooding generation regime in YRB. This includes: (a) an increase in the streamflow under all SSPs; (b) a larger flooding peak (Q) and volume (W) under SSP585, with Q and W at the Huayuankou hydrologic station (HYK) increasing by 52.7% and 44.8%, respectively; (c) an advancement in the bivariate flooding risk, particularly in SSP585 where flooding co‐occurrence return period at HYK may be more than 50 times earlier. This study underscores that the urgent need to enhance social resilience to climate change in the YRB. Plain Language Summary: The YRB, as the second‐longest river in China, is confronted with the threat of catastrophic flooding hazards. The CMIP6, representing the latest climate prediction products, was developed by Earth System Grid Federation. This research aims to propose a novel perspective for predicting future flooding risks along the YRB under all SSPs. The findings of this research could hold great potential for informing mitigation and adaptation policies regarding flooding hazards in the YRB. Key Points: The VIC hydrologic model is employed to simulate flooding magnitude to climate change over the Yellow River basinFlooding magnitude over the Yellow River basin become more fluctuating under three SSPsFuture return period levels for flooding peak and volume have reduced significantly from the historical period, with the co‐occurrence return period being more prominent than the joint return period [ABSTRACT FROM AUTHOR]

Hydrological modeling is essential for runoff simulations in line with climate studies, especially in remote areas with data scarcity. Advancements in climatic precipitation datasets have improved the accuracy of hydrological modeling. This research aims to evaluate the APHRODITE, PERSIANN-CDR, and ERA5-Land climatic precipitation datasets for the Hablehroud watershed in Iran. The datasets were compared with interpolated ground station precipitation data using the inverse distance weighted (IDW) method. The variable infiltration capacity (VIC) model was utilized to simulate runoff from 1992 to 1996. The results revealed that the APHRODITE and PERSIANN-CDR datasets demonstrated the highest and lowest accuracy, respectively. The sensitivity of the model was analyzed using each precipitation dataset, and model calibration was performed using the Kling–Gupta efficiency (KGE). The evaluation of daily runoff simulation based on observed precipitation indicated a KGE value of 0.78 and 0.76 during the calibration and validation periods, respectively. The KGE values at the daily time scale were 0.64 and 0.77 for PERSIANN-CDR data, 0.62 and 0.75 for APHRODITE precipitation data, 0.50 and 0.66 for ERA5-Land precipitation data during the calibration and validation periods, respectively. These results indicate that despite varying sensitivity, climatic precipitation datasets present satisfactory performance, particularly in poorly gauged basins with infrequent historical datasets. [ABSTRACT FROM AUTHOR]

Abstract Global human‐induced warming has intensified water circulation in the atmospheric environment and altered the streamflow generation regime. The VIC hydrological model approach for impact assessment of climate change and human activities mainly focuses on variations in streamflow, but ignores other critical flooding characteristics induced by extreme streamflow, especially bivariate flooding characteristics. In this work, the copula functions are employed to structure the flooding risk under the shared socioeconomic pathway (SSP) across the Yellow River basin (YRB). This is based on the multi‐model ensemble (MME) and Delta downscaling outputs (Delta‐MME) of the CMIP6 global climate models (GCMs), as well as the flooding characteristics simulated by VIC hydrological model. Compared to the reference period (1995–2014), Delta‐MME reveals a significant warming and humidifying trend under three SSPs over the YRB. Despite uncertainties originating from climate variables and hydrological model, multiple findings underscore the substantial influence of climate change on the flooding generation regime in YRB. This includes: (a) an increase in the streamflow under all SSPs; (b) a larger flooding peak (Q) and volume (W) under SSP585, with Q and W at the Huayuankou hydrologic station (HYK) increasing by 52.7% and 44.8%, respectively; (c) an advancement in the bivariate flooding risk, particularly in SSP585 where flooding co‐occurrence return period at HYK may be more than 50 times earlier. This study underscores that the urgent need to enhance social resilience to climate change in the YRB.

Hydrological modeling is essential for runoff simulations in line with climate studies, especially in remote areas with data scarcity. Advancements in climatic precipitation datasets have improved the accuracy of hydrological modeling. This research aims to evaluate the APHRODITE, PERSIANN-CDR, and ERA5-Land climatic precipitation datasets for the Hablehroud watershed in Iran. The datasets were compared with interpolated ground station precipitation data using the inverse distance weighted (IDW) method. The variable infiltration capacity (VIC) model was utilized to simulate runoff from 1992 to 1996. The results revealed that the APHRODITE and PERSIANN-CDR datasets demonstrated the highest and lowest accuracy, respectively. The sensitivity of the model was analyzed using each precipitation dataset, and model calibration was performed using the Kling–Gupta efficiency (KGE). The evaluation of daily runoff simulation based on observed precipitation indicated a KGE value of 0.78 and 0.76 during the calibration and validation periods, respectively. The KGE values at the daily time scale were 0.64 and 0.77 for PERSIANN-CDR data, 0.62 and 0.75 for APHRODITE precipitation data, 0.50 and 0.66 for ERA5-Land precipitation data during the calibration and validation periods, respectively. These results indicate that despite varying sensitivity, climatic precipitation datasets present satisfactory performance, particularly in poorly gauged basins with infrequent historical datasets.

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In order to improve the simulation accuracy of snowmelt runoff in the alpine areas and better guide the sustainable development and utilization of water resources in the glacial snowmelt areas, and the Ili river basin as a typical research area. the meteorological simulation results of the Weather Research and Forecasting (WRF) model with high resolution simulation accuracy were used to drive the distributed Variable Infiltration Capacity (VIC) hydrological model, and the data assimilation technology was used to improve the accuracy of meteorological simulation in the WRF model. The WRF-VIC atmospheric-hydrological coupling model based on the data assimilation correction is constructed to carry out snowmelt runoff simulation research in alpine mountains. The results show that the WRF-VIC atmospheric-hydrological coupling model has better simulation results in non-flood season runoff, and the total simulation error value of the whole flood season was -81.85mm; and the data assimilation improves the runoff simulation effect of the WRF-VIC atmospheric-hydrological coupling model in the flood season, and the error is reduced from -81.85 mm to -68.86 mm. [ABSTRACT FROM AUTHOR]

Better representations of groundwater processes need to be incorporated into large-scale hydrological models to improve simulations of regional- to global-scale hydrology and climate, as well as understanding of feedbacks between the human and natural systems. We incorporated a 2D groundwater flow model into the variable infiltration capacity (VIC) hydrological model code to address its lack of a lateral groundwater flow component. The water table was coupled with the variably saturated VIC soil column allowing bi-directional exchange of water between the aquifer and the soil. We then investigated how variations in aquifer properties and grid resolution affect modelled evapotranspiration (ET), runoff and groundwater recharge. We simulated nine idealised, homogenous aquifers with different combinations of transmissivity, storage coefficient, and three grid resolutions. The magnitude of cell ET, runoff, and recharge significantly depends on water table depth. In turn, the distribution of water table depths varied significantly as grid resolution increased from 1° to 0.05° for the medium and high transmissivity systems, resulting in changes of model-average fluxes of up to 12.3% of mean rainfall. For the low transmissivity aquifer, increasing the grid resolution has a minimal effect as lateral groundwater flow is low, and the VIC grid cells behave as vertical columns. The inclusion of the 2D groundwater model in VIC will enable the future representation of irrigation from groundwater pumping, and the feedbacks between groundwater use and the hydrological cycle.

Existing gauging networks are sparse and not readily available in real-time over the transboundary Lancang−Mekong River (LMR) basin, making it difficult to accurately identify drought. In this study, we aimed to build an operational real-time Lancang−Mekong drought monitor (LMDM), through combining satellite real-time data and the Variable Infiltration Capacity (VIC) hydrological model at a 0.25° spatial resolution. Toward this, three VIC runs were conducted: (1) a 60-year (1951−2010) historical simulation driven by Princeton’s global meteorological forcing (PGF) for yielding ‘normal’ conditions (PGF-VIC), wherein the VIC was calibrated with 20-year observed streamflow at six hydrological stations; (2) a short-period (2011−2014) simulation to bridge the gap between the historical and the real-time modeling; (3) the real-time (2015−present) simulation driven by bias-corrected satellite data, wherein the real-time soil moisture (SM) estimate was expressed as percentile (relative to the ‘normal’) for drought monitoring. Results show that VIC can successfully reproduce the observed hydrographs, with the Nash−Sutcliffe efficiency exceeding 0.70 and the relative bias mostly within 15%. Assessment on the performance of LMDM shows that the real-time SM estimates bear good spatial similarity to the reference, with the correlation coefficient beyond 0.80 across >70% of the domain. In terms of drought monitoring, the LMDM can reasonably reproduce the two recorded droughts, implying extreme droughts covering the Lower LMR during 2004/05 and widespread severe 2009/10 drought across the upper domain. The percentage drought area implied by the LMDM and the reference is close, corresponding to 66% and 60%, 43% and 40%, and 44% and 36% for each typical drought month. Since January 2015, the LMDM was running in an operational mode, from which the 2016 unprecedented drought was successfully identified in Mekong Delta. This study highlights the LMDM’s capability for reliable real-time drought monitoring, which can serve as a valuable drought early warning prototype for other data-poor regions.

Due to the high elevation, complex terrain, severe weather, and inaccessibility, direct meteorological observations do not exist over large portions of the Tibetan Plateau, especially the western part of it. Satellite rainfall estimates have been very important sources for precipitation information, particularly in rain gauge-sparse regions. In this study, Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) products 3B42, RTV5V6, and RTV7 were evaluated for their applicability to the upper Yellow and Yangtze River basins on the Tibetan Plateau. Moreover, the capability of the TMPA products to simulate streamflow was also investigated using the Variable Infiltration Capacity (VIC) semi-distributed hydrological model. Results show that 3B42 performs better than RTV5V6 and RTV7, based on verification of the China Meteorological Administration (CMA) observational precipitation data. RTV5V6 can roughly capture the spatial precipitation pattern but overestimation exists throughout the entire study region. The anticipated improvements of RTV7 relative to RTV5V6 have not been realized in this study. Our results suggest that RTV7 significantly overestimates the precipitation over the two river basins, though it can capture the seasonal cycle features of precipitation. 3B42 shows the best performance in streamflow simulation of the abovementioned satellite products. Although involved in gauge adjustment at a monthly scale, 3B42 is capable of daily streamflow simulation. RTV5V6 and RTV7 have no capability to simulate streamflow in the upper Yellow and Yangtze River basins.

Summary In this study, we evaluate four widely used global high-resolution satellite precipitation products against gauge observations over the Tibetan Plateau (TP). We also investigate the capability of the satellite products in streamflow simulations using the VIC hydrological model. Results show that the 3B42 and CMORPH perform better than the 3B42RT and PERSIANN at both plateau and basin scales. The 3B42RT and PERSIANN considerably overestimate the gauge precipitation estimates almost over the entire plateau, and the PERSIANN fail to capture the spatial and temporal pattern of the gauge precipitation estimates. For different satellite estimates, the error sources are systematically different for various seasons. For the 3B42, the miss bias is the main problem. The CMORPH exhibits obvious negative hit bias and miss bias in the rainy season and false-rain bias in the non-rainy season. The total bias in the 3B42RT and PERSIANN mainly attribute to positive hit bias in the rainy season and false-rain bias in the non-rainy season. The 3B42RT and PERSIANN show little capability for streamflow simulations over the TP, while the CMORPH exhibits an encouraging potential for hydrological applications in this regions in spite of the general underestimates. The 3B42 shows comparable performance to the CMA (China Meteorological Administration) data in both monthly and daily streamflow simulations mostly due to the monthly gauge adjustment involved in it. [ABSTRACT FROM AUTHOR]

Better representations of groundwater processes need to be incorporated into large-scale hydrological models to improve simulations of regional- to global-scale hydrology and climate, as well as understanding of feedbacks between the human and natural systems. We incorporated a 2D groundwater flow model into the variable infiltration capacity (VIC) hydrological model code to address its lack of a lateral groundwater flow component. The water table was coupled with the variably saturated VIC soil column allowing bi-directional exchange of water between the aquifer and the soil. We then investigated how variations in aquifer properties and grid resolution affect modelled evapotranspiration (ET), runoff and groundwater recharge. We simulated nine idealised, homogenous aquifers with different combinations of transmissivity, storage coefficient, and three grid resolutions. The magnitude of cell ET, runoff, and recharge significantly depends on water table depth. In turn, the distribution of water table depths varied significantly as grid resolution increased from 1° to 0.05° for the medium and high transmissivity systems, resulting in changes of model-average fluxes of up to 12.3% of mean rainfall. For the low transmissivity aquifer, increasing the grid resolution has a minimal effect as lateral groundwater flow is low, and the VIC grid cells behave as vertical columns. The inclusion of the 2D groundwater model in VIC will enable the future representation of irrigation from groundwater pumping, and the feedbacks between groundwater use and the hydrological cycle. [ABSTRACT FROM AUTHOR]

• The future hydropower generation of 62 reservoirs under climate change was predicted • The macro-scale distributed hydrological model was combined with the optimal operation model considers the specific operation process of large-scale reservoirs. • Hydropower generation is sensitive to climate change, especially under high emission scenario. Climate change, which impacts the spatial and temporal distribution of water resources, has a significant influence on the future hydropower generation. Studying the future evolution pattern of hydropower generation under climate change is of great significance for the medium- and long-term hydropower prediction. The objective of this paper is to predict the future hydropower generation of large-scale reservoir groups under climate change. The innovation of this paper is that the macro-scale distributed hydrological model combined with the optimal operation model of large-scale reservoirs was proposed for hydropower generation prediction. The established model considers the specific operation processes of large-scale reservoir groups, including 62 reservoirs in the case study. First, the Statistical Downscaling Model (SDSM) was built, and the evolution trend of future rainfall and temperature was predicted. Second, the macro-scale distributed Variable Infiltration Capacity (VIC) model was built to predict the future runoff. Finally, the optimal operation generation model of large-scale reservoir groups was established to predict the trends of hydropower generation under climate change. Results demonstrate that under RCP2.6 scenario, there is no significant increase or decrease trend of hydropower generation in the future. But under RCP4.5 and RCP8.5 scenarios, the hydropower generation shows a growing trend, and the increase trend under RCP8.5 scenario is more obvious than that under RCP4.5 scenario. Thus, the development of hydropower generation is sensitive to climate change. This study can provide a reference for the long-term prediction of hydropower generation capacity in the upper Yangtze River Basin. [ABSTRACT FROM AUTHOR]

Existing gauging networks are sparse and not readily available in real-time over the transboundary Lancang–Mekong River (LMR) basin, making it difficult to accurately identify drought. In this study, we aimed to build an operational real-time Lancang–Mekong drought monitor (LMDM), through combining satellite real-time data and the Variable Infiltration Capacity (VIC) hydrological model at a 0.25° spatial resolution. Toward this, three VIC runs were conducted: (1) a 60-year (1951–2010) historical simulation driven by Princeton's global meteorological forcing (PGF) for yielding 'normal' conditions (PGF-VIC), wherein the VIC was calibrated with 20-year observed streamflow at six hydrological stations; (2) a short-period (2011–2014) simulation to bridge the gap between the historical and the real-time modeling; (3) the real-time (2015–present) simulation driven by bias-corrected satellite data, wherein the real-time soil moisture (SM) estimate was expressed as percentile (relative to the 'normal') for drought monitoring. Results show that VIC can successfully reproduce the observed hydrographs, with the Nash–Sutcliffe efficiency exceeding 0.70 and the relative bias mostly within 15%. Assessment on the performance of LMDM shows that the real-time SM estimates bear good spatial similarity to the reference, with the correlation coefficient beyond 0.80 across >70% of the domain. In terms of drought monitoring, the LMDM can reasonably reproduce the two recorded droughts, implying extreme droughts covering the Lower LMR during 2004/05 and widespread severe 2009/10 drought across the upper domain. The percentage drought area implied by the LMDM and the reference is close, corresponding to 66% and 60%, 43% and 40%, and 44% and 36% for each typical drought month. Since January 2015, the LMDM was running in an operational mode, from which the 2016 unprecedented drought was successfully identified in Mekong Delta. This study highlights the LMDM's capability for reliable real-time drought monitoring, which can serve as a valuable drought early warning prototype for other data-poor regions. [ABSTRACT FROM AUTHOR]