It is an important standard to judge the flood disaster in the basin whether the rainfall at the flood-inducing interface is reached.In this paper,the Xin'anjiang model,Topmodel model and SCS model were selected t...It is an important standard to judge the flood disaster in the basin whether the rainfall at the flood-inducing interface is reached.In this paper,the Xin'anjiang model,Topmodel model and SCS model were selected to calculate and compare the rainfall at the flood-inducing interface in the Zhanghe Reservoir basin in Hubei Province.The results showed that average relative error and average absolute error of Xin'anjiang model were-3.36%and-21.46×10^(5)m^(3),which were the minimum,followed by Topmodel model with 5.72%and 26.22×10^(5)m^(3),SCS model with 11.33%and 58.13×10^(5)m^(3).The minimum absolute error of the three hydrological models in calculating the rainfall at the critical interface was 3.26 mm,while the maximum was 49.24 mm.When the initial water level exceeded 120 m,the difference among the three models in calculating the rainfall at the critical interface became more and more obvious.When the reservoir water level was lower than 120 m,it mainly referred to the calculation results of Xin'anjiang model.When the reservoir water level was higher than 120 m,it mainly referred to the calculation results of Topmodel model.The research conclusion can provide reference for small and medium-sized basins selecting hydrological model to calculate the rainfall at the flood-inducing interface.展开更多
November 21-22,2011,Johannesburg,South Africa The fourth annual workshop of the International Geoscience Programme Project 565“Developing the Global Geodetic Observing System into a Monitoring System for the Global W...November 21-22,2011,Johannesburg,South Africa The fourth annual workshop of the International Geoscience Programme Project 565“Developing the Global Geodetic Observing System into a Monitoring System for the Global Water Cycle,”which was jointly organized by IGCP 565,the Group on Earth Observations(GEO)and the Global Geodetic Observing System(GGOS),was held on November 21-22,2011 at the Witwatersrand University,Johannesburg,South Africa.展开更多
Actual evapotranspiration is a key process of hydrological cycle and a sole term that links land surface water balance and land surface energy balance.Evapotranspiration plays a key role in simulating hydrological eff...Actual evapotranspiration is a key process of hydrological cycle and a sole term that links land surface water balance and land surface energy balance.Evapotranspiration plays a key role in simulating hydrological effect of climate change,and a review of evapotranspiration estimation methods in hydrological models is of vital importance.This paper firstly summarizes the evapotranspiration estimation methods applied in hydrological models and then classifies them into the integrated converting methods and the classification gathering methods by their mechanism.Integrated converting methods are usually used in hydrological models and two differences exist among them:one is in the potential evaporation estimation methods,while the other in the function for defining relationship between potential evapora tion and actual evapotranspiration.Due to the higher information requirements of the Pen-man-Monteith method and the existing data uncertainty,simplified empirical methods for calculating potential and actual evapotranspiration are widely used in hydrological models.Different evapotranspiration calculation methods are used depending on the complexity of the hydrological model,and importance and difficulty in the selection of the most suitable evapotranspiration methods is discussed.Finally,this paper points out the prospective de velopment trends of the evapotranspiration estimating methods in hydrological modeling.展开更多
Accurate estimation of evapotranspiration(ET),especially at the regional scale,is an extensively investigated topic in the field of water science. The ability to obtain a continuous time series of highly precise ET va...Accurate estimation of evapotranspiration(ET),especially at the regional scale,is an extensively investigated topic in the field of water science. The ability to obtain a continuous time series of highly precise ET values is necessary for improving our knowledge of fundamental hydrological processes and for addressing various problems regarding the use of water. This objective can be achieved by means of ET data assimilation based on hydrological modeling. In this paper,a comprehensive review of ET data assimilation based on hydrological modeling is provided. The difficulties and bottlenecks of using ET,being a non-state variable,to construct data assimilation relationships are elaborated upon,with a discussion and analysis of the feasibility of assimilating ET into various hydrological models. Based on this,a new easy-to-operate ET assimilation scheme that includes a water circulation physical mechanism is proposed. The scheme was developed with an improved data assimilation system that uses a distributed time-variant gain model(DTVGM),and the ET-soil humidity nonlinear time response relationship of this model. Moreover,the ET mechanism in the DTVGM was improved to perfect the ET data assimilation system. The new scheme may provide the best spatial and temporal characteristics for hydrological states,and may be referenced for accurate estimation of regional evapotranspiration.展开更多
This study simulated and predicted the runoff of the Aksu River Basin, a typical river basin supplied by snowmelt in an arid mountain region, with a limited data set and few hydrological and meteorological stations. T...This study simulated and predicted the runoff of the Aksu River Basin, a typical river basin supplied by snowmelt in an arid mountain region, with a limited data set and few hydrological and meteorological stations. Two hydrological models, the snowmelt-runoff model （SRM） and the Danish NedbФr-AfstrФmnings rainfall-runoff model （NAM）, were used to simulate daily discharge processes in the Aksu River Basin. This study used the snow-covered area from MODIS remote sensing data as the SRM input. With the help of ArcGIS software, this study successfully derived the digital drainage network and elevation zones of the basin from digital elevation data. The simulation results showed that the SRM based on MODIS data was more accurate than NAM. This demonstrates that the application of remote sensing data to hydrological snowmelt models is a feasible and effective approach to runoff simulation and prediction in arid unguaged basins where snowmelt is a major runoff factor.展开更多
Hydrological models are crucial for characterizing large-scale water quantity variations and correcting GNSS reference station vertical displacements.We evaluated the robustness of multiple models,such as the Global L...Hydrological models are crucial for characterizing large-scale water quantity variations and correcting GNSS reference station vertical displacements.We evaluated the robustness of multiple models,such as the Global Land Data Assimilation System (GLDAS),the Famine Early Warning System Network Land Data Assimilation System (FLDAS),the National Centers for Environmental Prediction (NCEP),and the WaterGAP Global Hydrology Model (WGHM).Inter-model and outer comparisons with Global Positioning System (GPS) coordinate time series,satellite gravity field Mascon solutions,and Global Precipitation Climatology Centre (GPCC) guide our assessment.Results confirm WGHM's 26% greater effectiveness in correcting nonlinear variations in GPS height time series compared to NCEP.In the Amazon River Basin,a 5-month lag between FLDAS,GLDAS,and satellite gravity results is observed.In eastern Asia and Australia,NCEP's Terrestrial Water Storage Changes (TWSC)-derived surface displacements correlate differently with precipitation compared to other models.Three combined hydrological models (H-VCE,H-EWM,and H-CVM) utilizing Variance Component Estimation (VCE),Entropy Weight Method (EWM),and Coefficient of Variation Method (CVM) are formulated.Correcting nonlinear variations with combined models enhances global GPS height scatter by 15%-17%.Correlation with precipitation increases by 25%-30%,and with satellite gravity,rises from 0.2 to 0.8 at maximum.The combined model eliminates time lag in the Amazon Basin TWSC analysis,exhibiting a four times higher signal-to-noise ratio than single models.H-VCE demonstrates the highest accuracy.In summary,the combined hydrological model minimizes discrepancies among individual models,significantly improving accuracy for monitoring large-scale TWSC.展开更多
Hydrological modeling,leveraging mathematical formulations to represent the hydrological cycle,is a pivotal tool in representing the spatiotemporal dynamics and distribution patterns inherent in hydrology.These models...Hydrological modeling,leveraging mathematical formulations to represent the hydrological cycle,is a pivotal tool in representing the spatiotemporal dynamics and distribution patterns inherent in hydrology.These models serve a dual purpose:they validate theoretical robustness and applicability via observational data and project future trends,thereby bridging the understanding and prediction of natural processes.In rapid advancements in computational methodologies and the continuous evolution of observational and experimental techniques,the development of numerical hydrological models based on physicallybased surface-subsurface process coupling have accelerated.Anchored in micro-scale conservation principles and physical equations,these models employ numerical techniques to integrate surface and subsurface hydrodynamics,thus replicating the macro-scale hydrological responses of watersheds.Numerical hydrological models have emerged as a leading and predominant trend in hydrological modeling due to their explicit representation of physical processes,heightened by their spatiotemporal resolution and reliance on interdisciplinary integration.This article focuses on the theoretical foundation of surface-subsurface numerical hydrological models.It includes a comparative and analytical discussion of leading numerical hydrological models,encompassing model architecture,numerical solution strategies,spatial representation,and coupling algorithms.Additionally,this paper contrasts these models with traditional hydrological models,thereby delineating the relative merits,drawbacks,and future directions of numerical hydrological modeling.展开更多
Vegetation information is seldom considered in lumped conceptual rainfall-runoff models.This paper uses two modified rainfall-runoff models,the Xinanjiang-ET and SIMHYD-ET models in which vegetation leaf area index is...Vegetation information is seldom considered in lumped conceptual rainfall-runoff models.This paper uses two modified rainfall-runoff models,the Xinanjiang-ET and SIMHYD-ET models in which vegetation leaf area index is incorporated,to investigate impacts of vegetation change and climate variability on streamflow in a Southern Australian catchment,the Crawford River experimental catchment,where Tasmanian blue gum plantations were introduced gradually from 1998 till 2005.The Xinanjiang-ET and SIMHYD-ET models incorporate remotely-sensed leaf area index(LAI) data obtained from the Advanced Very High Resolution Radiometer(AVHRR) on board NOAA polar orbiting satellites.Compared to the original versions,the Xinanjiang-ET and SIMHYD-ET models show marginal improvements in runoff simulations in the pre-plantation period(1882-1997).The calibrated Xinanjaing-ET and SIMHYD-ET models are then used to simulate plantation impact on streamflow in the post-plantation period.The total change in streamflow between the pre-plantation and post-plantation periods is 32.4 mm/a.The modelling results from the two models show that plantation reduces streamflow by 20.5 mm/a,and climate variability reduces streamflow by 11.9 mm/a.These results suggest that increase in plantations can reduce streamflow substantially,even more than climate variability.展开更多
The aim of this paper is to present graphically the behaviour of a simulation model to the varying parameters and to establish the suitability of this representation as a valid tool for the analysis of the same parame...The aim of this paper is to present graphically the behaviour of a simulation model to the varying parameters and to establish the suitability of this representation as a valid tool for the analysis of the same parameters. In this paper, we define parameter combinatorial diagram as the joint graphical representation of all box plots related to the adjustment between real and simulated data, by setting and/or changing the parameters of the simulation model. To do this, we start with a box plot representing the values of an objective adjustment function, achieving these results when varying all the parameters of the simulation model, Then we draw the box plot when setting all the parameters of the model, for example, using the median or average. Later, we get all the box plots when carrying out simulations combining fixed or variable values of the model parameters. Finally, all box plots obtained are represented neatly in a single graph. It is intended that the new parameter combinatorial diagram is used to examine and analyze simulation models useful in practice. This paper presents combinatorial diagrams of different examples of application as in the case of hydrologic models of one, two, three, and five parameters.展开更多
Forest hydrology,the study of water dynamics within forested catchments,is crucial for understanding the intricate relationship between forest cover and water balances across different scales,from ecosystems to landsc...Forest hydrology,the study of water dynamics within forested catchments,is crucial for understanding the intricate relationship between forest cover and water balances across different scales,from ecosystems to landscapes,or from catchment watersheds.The intensified global changes in climate,land use and cover,and pollution that occurred over the past century have brought about adverse impacts on forests and their services in water regulation,signifying the importance of forest hydrological research as a re-emerging topic of scientific interest.This article reviews the literature on recent advances in forest hydrological research,intending to identify leading countries,institutions,and researchers actively engaged in this field,as well as highlighting research hotspots for future exploration.Through a systematic analysis using VOSviewer,drawing from 17,006 articles retrieved from the Web of Science Core Collection spanning 2000–2022,we employed scientometric methods to assess research productivity,identify emerging topics,and analyze academic development.The findings reveal a consistent growth in forest hydrological research over the past two decades,with the United States,Charles T.Driscoll,and the Chinese Academy of Sciences emerging as the most productive country,author,and institution,respectively.The Journal of Hydrology emerges as the most co-cited journal.Analysis of keyword co-occurrence and co-cited references highlights key research areas,including climate change,management strategies,runoff-erosion dynamics,vegetation cover changes,paired catchment experiments,water quality,aquatic biodiversity,forest fire dynamics and hydrological modeling.Based on these findings,our study advocates for an integrated approach to future research,emphasizing the collection of data from diverse sources,utilization of varied methodologies,and collaboration across disciplines and institutions.This holistic strategy is essential for developing sustainable approaches to forested watershed planning and management.Ultimately,our study provides valuable insights for researchers,practitioners,and policymakers,guiding future research directions towards forest hydrological research and applications.展开更多
Anthropogenically induced land use/land cover(LULC)transformations and accelerating climatic variabilities have emerged as pivotal forces reshaping the hydrological equilibrium of fluvial systems,particularly in ecolo...Anthropogenically induced land use/land cover(LULC)transformations and accelerating climatic variabilities have emerged as pivotal forces reshaping the hydrological equilibrium of fluvial systems,particularly in ecologically sensitive basins.This study systematically interrogates the compounded ramifications of LULC dynamics and projected climate change on the hydrological response of the Upper Jemma Watershed an integral sub-catchment of the Upper Blue Nile River system.Employing the advanced QSWAT+hydrological modeling framework within a GIS interface,the analysis integrates bias‐corrected climatic projections under RCP 4.5 and RCP 8.5 scenarios alongside multi-temporal remote sensing‐derived land cover datasets.The findings unveil an unequivocal intensification of surface runoff and streamflow due to expansive agricultural encroachment,juxtaposed with a discernible decline in evapotranspiration and soil water retention.Climatic perturbations,notably temperature elevation and precipitation attenuation,further exacerbate these trends,with pronounced seasonality in hydrological fluxes.Importantly,synergistic interactions between land cover transformation and climatic anomalies manifest in nonlinear hydrological alterations,amplifying peak flows and diminishing baseflows.This underscores the riverine system's heightened vulnerability and the necessity for integrated watershed management strategies that account for multifactorial hydrological stressors.The study provides a robust empirical and modeling basis to inform adaptive water governance within transboundary river basins susceptible to environmental transitions.展开更多
The simulation of hydrological consequences of climate change has received increasing attention from the hydrology and land-surface modelling communities. There have been many studies of climate-change effects on hydr...The simulation of hydrological consequences of climate change has received increasing attention from the hydrology and land-surface modelling communities. There have been many studies of climate-change effects on hydrology and water resources which usually consist of three steps： （1） use of general circulation models （GCMs） to provide future global climate scenarios under the effect of increasing greenhouse gases, （2） use of downscaling techniques （both nested regional climate models, RCMs, and statistical methods） for ＂downscaling＂ the GCM output to the scales compatible with hydrological models, and （3） use of hydrologic models to simulate the effects of climate change on hydrological regimes at various scales. Great progress has been achieved in all three steps during the past few years, however, large uncertainties still exist in every stage of such study. This paper first reviews the present achievements in this field and then discusses the challenges for future studies of the hydrological impacts of climate change.展开更多
The integration of Artificial Intelligence(AI)and Machine Learning(ML)into groundwater exploration and water resources management has emerged as a transformative approach to addressing global water challenges.This rev...The integration of Artificial Intelligence(AI)and Machine Learning(ML)into groundwater exploration and water resources management has emerged as a transformative approach to addressing global water challenges.This review explores key AI and ML concepts,methodologies,and their applications in hydrology,focusing on groundwater potential mapping,water quality prediction,and groundwater level forecasting.It discusses various data acquisition techniques,including remote sensing,geospatial analysis,and geophysical surveys,alongside preprocessing methods that are essential for enhancing model accuracy.The study highlights AI-driven solutions in water distribution,allocation optimization,and realtime resource management.Despite their advantages,the application of AI and ML in water sciences faces several challenges,including data scarcity,model reliability,and the integration of these tools with traditional water management systems.Ethical and regulatory concerns also demand careful consideration.The paper also outlines future research directions,emphasizing the need for improved data collection,interpretable models,real-time monitoring capabilities,and interdisciplinary collaboration.By leveraging AI and ML advancements,the water sector can enhance decision-making,optimize resource distribution,and support the development of sustainable water management strategies.展开更多
Accurate prediction of flood events is important for flood control and risk management.Machine learning techniques contributed greatly to advances in flood predictions,and existing studies mainly focused on predicting...Accurate prediction of flood events is important for flood control and risk management.Machine learning techniques contributed greatly to advances in flood predictions,and existing studies mainly focused on predicting flood resource variables using single or hybrid machine learning techniques.However,class-based flood predictions have rarely been investigated,which can aid in quickly diagnosing comprehensive flood characteristics and proposing targeted management strategies.This study proposed a prediction approach of flood regime metrics and event classes coupling machine learning algorithms with clustering-deduced membership degrees.Five algorithms were adopted for this exploration.Results showed that the class membership degrees accurately determined event classes with class hit rates up to 100%,compared with the four classes clustered from nine regime metrics.The nonlinear algorithms(Multiple Linear Regression,Random Forest,and least squares-Support Vector Machine)outperformed the linear techniques(Multiple Linear Regression and Stepwise Regression)in predicting flood regime metrics.The proposed approach well predicted flood event classes with average class hit rates of 66.0%-85.4%and 47.2%-76.0%in calibration and validation periods,respectively,particularly for the slow and late flood events.The predictive capability of the proposed prediction approach for flood regime metrics and classes was considerably stronger than that of hydrological modeling approach.展开更多
Flood events occurrences and frequencies in the world are of immense worry for the stability of the economy and life safety. Africa continent is the third continent the most negatively affected by the flood events aft...Flood events occurrences and frequencies in the world are of immense worry for the stability of the economy and life safety. Africa continent is the third continent the most negatively affected by the flood events after Asia and Europe. Eastern Africa is the most hit in Africa. However, Africa continent is at the early stage in term of flood forecasting models development and implementation. Very few hydrological models for flood forecasting are available and implemented in Africa for the flood mitigation. And for the majority of the cases, they need to be improved because of the time evolution. Flash flood in Bamako (Mali) has been putting both human life and the economy in jeopardy. Studying this phenomenon, as to propose applicable solutions for its alleviation in Bamako is a great concern. Therefore, it is of upmost importance to know the existing scientific works related to this situation in Mali and elsewhere. The main aim was to point out the various solutions implemented by various local and international institutions, in order to fight against the flood events. Two types of methods are used for the flood events adaptation: the structural and non-structural methods. The structural methods are essentially based on the implementation of the structures like the dams, dykes, levees, etc. The problem of these methods is that they may reduce the volume of water that will inundate the area but are not efficient for the prediction of the coming floods and cannot alert the population with any lead time in advance. The non-structural methods are the one allowing to perform the prediction with acceptable lead time. They used the hydrological rainfall-runoff models and are the widely methods used for the flood adaptation. This review is more accentuated on the various types non-structural methods and their application in African countries in general and West African countries in particular with their strengths and weaknesses. Hydrologiska Byråns Vattenbalansavdelning (HBV), Hydrologic Engineer Center Hydrologic Model System (HEC-HMS) and Soil and Water Assessment Tool (SWAT) are the hydrological models that are the most widely used in West Africa for the purpose of flood forecasting. The easily way of calibration and the weak number of input data make these models appropriate for the West Africa region where the data are scarce and often with bad quality. These models when implemented and applied, can predict the coming floods, allow the population to adapt and mitigate the flood events and reduce considerably the impacts of floods especially in terms of loss of life.展开更多
The study is focused on hydrological response of a catchment to rainfall in extremely humid monsoonal climate region at the Meghalaya Plateau(India)near Cherrapunji.This area has been rarely investigated due to the la...The study is focused on hydrological response of a catchment to rainfall in extremely humid monsoonal climate region at the Meghalaya Plateau(India)near Cherrapunji.This area has been rarely investigated due to the lack of the detailed hydro-meteorological data.Hourly rainfall data were collected between 1999 and 2009 and hydrological data obtained for the Maw-Ki-Syiem experimental catchment(0.22 km^(2))was used to calibrate hydrological models(SCS-CN and GIUH)and to model river runoff during rainy periods in 2005.Hydrographs revealed rapid responses of the catchment to heavy rainfall.The rising limb and recession limb were very steep and coincided with hourly course of rainfall.展开更多
The regional hydrological system is extremely complex because it is affected not only by physical factors but also by human dimensions.And the hydrological models play a very important role in simulating the complex s...The regional hydrological system is extremely complex because it is affected not only by physical factors but also by human dimensions.And the hydrological models play a very important role in simulating the complex system.However,there have not been effective methods for the model reliability and uncertainty analysis due to its complexity and difficulty.The uncertainties in hydrological modeling come from four important aspects：uncertainties in input data and parameters,uncertainties in model structure,uncertainties in analysis method and the initial and boundary conditions.This paper systematically reviewed the recent advances in the study of the uncertainty analysis approaches in the large-scale complex hydrological model on the basis of uncertainty sources.Also,the shortcomings and insufficiencies in the uncertainty analysis for complex hydrological models are pointed out.And then a new uncertainty quantification platform PSUADE and its uncertainty quantification methods were introduced,which will be a powerful tool and platform for uncertainty analysis of large-scale complex hydrological models.Finally,some future perspectives on uncertainty quantification are put forward.展开更多
The objective of this study is to quantitatively evaluate Tropical Rainfall Measuring Mission （TRMM） data with rain gauge data and further to use this TRMM data to drive a Dis- tributed Time-Variant Gain Model （DT...The objective of this study is to quantitatively evaluate Tropical Rainfall Measuring Mission （TRMM） data with rain gauge data and further to use this TRMM data to drive a Dis- tributed Time-Variant Gain Model （DTVGM） to perform hydrological simulations in the semi-humid Weihe River catchment in China. Before the simulations, a comparison with a 10-year （2001-2010） daily rain gauge data set reveals that, at daily time step, TRMM rainfall data are better at capturing rain occurrence and mean values than rainfall extremes. On a monthly time scale, good linear relationships between TRMM and rain gauge rainfall data are found, with determination coefficients R2 varying between 0.78 and 0.89 for the individual stations. Subsequent simulation results of seven years （2001-2007） of data on daily hydro- logical processes confirm that the DTVGM when calibrated by rain gauge data performs better than when calibrated by TRMM data, but the performance of the simulation driven by TRMM data is better than that driven by gauge data on a monthly time scale. The results thus suggest that TRMM rainfall data are more suitable for monthly streamfiow simulation in the study area, and that, when the effects of recalibration and the results for water balance components are also taken into account, the TRMM 3B42-V7 product has the potential to perform well in similar basins.展开更多
Considering a detailed hydrologic model in the land surface scheme helps to improve the simulation of regional hydro-climatology. A hydrologic model, which includes spatial heterogeneities in precipitation and infiltr...Considering a detailed hydrologic model in the land surface scheme helps to improve the simulation of regional hydro-climatology. A hydrologic model, which includes spatial heterogeneities in precipitation and infiltration, is constructed and incorporated into the land surface scheme BATS. Via the coupled-model (i.e., a regional climate model) simulations, the following major conclusions are obtained: the simulation of surface hydrology is sensitive to the inclusion of heterogeneities in precipitation and infiltration; the runoff ratio is increased after considering the infiltration heterogeneity, a result which is more consistent with the observations of surface moisture balance over humid areas; the introduction of the parameterization of infiltration heterogeneity can have a greater influence on the regional hydro-climatology than the precipitation heterogeneity; and the consideration of the impermeable fraction for the region reveals some features that are closer to the trend of aridification over northern China.展开更多
The Nu-Salween River(NSR),the longest free-flow river in Southeast Asia,plays an irreplaceable role in social development and ecological protection.The lower NSR region is particularly valuable as it is inhabited by a...The Nu-Salween River(NSR),the longest free-flow river in Southeast Asia,plays an irreplaceable role in social development and ecological protection.The lower NSR region is particularly valuable as it is inhabited by approximately 6.7 million people.The basin has limited hydraulic conservancy infrastructure and insufficient ability to cope with climate change risks.Studying the hydrological characteristics and changes in the basin provides the scientific basis for rational protection and development of the basin.However,owing to the limitation of observation data,previous studies have focused on the local area and neglected the study of the lower reaches,which is not enough to reflect the spatial characteristics of the entire basin.In this study,the ECMWF 5th generation reanalysis data(ERA5)and Multi-Source Weighted-Ensemble Precipitation(MSWEP)were applied to develop a geomorphology-based hydrological model(GBHM)for reconstructing hydrological datasets(i.e.GBHM-ERA5 and GBHM-MSWEP).The reconstructed datasets covering the complete basin were verified against the gauge observation and compared with other commonly used streamflow products,including Global Flood Awareness System v2.1,GloFAS-Reanalysis dataset v3.0,and linear optimal runoff aggregate(LORA).The comparison results revealed that GBHM-ERA5 is significantly better than the other four datasets and provides a good reproduction of the hydrological characteristics and trends of the NSR.Detailed analysis of GBHM-ERA5 revealed that:(1)A multi-year mean surface runoff represented 39%of precipitation over the basin during 1980–2018,which had low surface runoff in the upstream,while areas around the Three Parallel Rivers Area and the estuary had abundant surface runoff.(2)The surface runoff and discharge coefficient of variations in spring were larger than those in other seasons,and the inter-annual variation in the downstream was smaller than that in the upstream and midstream regions.(3)More than 70%of the basin areas showed a decreasing trend in the surface runoff,except for parts of Nagqu,south of Shan State in Myanmar,and Thailand,where surface runoff has an increasing trend.(4)The downstream discharge has dropped significantly at a rate of approximately 680 million cubic metresper year,and the decline rate is greater than that of upstream and midstream,especially in summer.This study provides a data basis for subsequent studies in the NSR basin and further elucidates the impact of climate change on the basin,which is beneficial to river planning and promotes international cooperation on the water-and eco-security of the basin.展开更多
基金Supported by Open Project Fund of China Meteorological Administration Basin Heavy Rainfall Key Laboratory(2023BHR-Y26)Innovation Project Fund of Wuhan Metropolitan Area Meteorological Joint Science and Technology(WHCSQY202305)+1 种基金Innovation and Development Special Project of China Meteorological Administration(CXFZ2022J019)Project of Huanggang Meteorological Bureau's Scientific Research(2022Y02).
文摘It is an important standard to judge the flood disaster in the basin whether the rainfall at the flood-inducing interface is reached.In this paper,the Xin'anjiang model,Topmodel model and SCS model were selected to calculate and compare the rainfall at the flood-inducing interface in the Zhanghe Reservoir basin in Hubei Province.The results showed that average relative error and average absolute error of Xin'anjiang model were-3.36%and-21.46×10^(5)m^(3),which were the minimum,followed by Topmodel model with 5.72%and 26.22×10^(5)m^(3),SCS model with 11.33%and 58.13×10^(5)m^(3).The minimum absolute error of the three hydrological models in calculating the rainfall at the critical interface was 3.26 mm,while the maximum was 49.24 mm.When the initial water level exceeded 120 m,the difference among the three models in calculating the rainfall at the critical interface became more and more obvious.When the reservoir water level was lower than 120 m,it mainly referred to the calculation results of Xin'anjiang model.When the reservoir water level was higher than 120 m,it mainly referred to the calculation results of Topmodel model.The research conclusion can provide reference for small and medium-sized basins selecting hydrological model to calculate the rainfall at the flood-inducing interface.
文摘November 21-22,2011,Johannesburg,South Africa The fourth annual workshop of the International Geoscience Programme Project 565“Developing the Global Geodetic Observing System into a Monitoring System for the Global Water Cycle,”which was jointly organized by IGCP 565,the Group on Earth Observations(GEO)and the Global Geodetic Observing System(GGOS),was held on November 21-22,2011 at the Witwatersrand University,Johannesburg,South Africa.
基金CAS-CSIRO Cooperative Research Program,No.CJHZ1223National Basic Research Program of China,No.2010CB428406
文摘Actual evapotranspiration is a key process of hydrological cycle and a sole term that links land surface water balance and land surface energy balance.Evapotranspiration plays a key role in simulating hydrological effect of climate change,and a review of evapotranspiration estimation methods in hydrological models is of vital importance.This paper firstly summarizes the evapotranspiration estimation methods applied in hydrological models and then classifies them into the integrated converting methods and the classification gathering methods by their mechanism.Integrated converting methods are usually used in hydrological models and two differences exist among them:one is in the potential evaporation estimation methods,while the other in the function for defining relationship between potential evapora tion and actual evapotranspiration.Due to the higher information requirements of the Pen-man-Monteith method and the existing data uncertainty,simplified empirical methods for calculating potential and actual evapotranspiration are widely used in hydrological models.Different evapotranspiration calculation methods are used depending on the complexity of the hydrological model,and importance and difficulty in the selection of the most suitable evapotranspiration methods is discussed.Finally,this paper points out the prospective de velopment trends of the evapotranspiration estimating methods in hydrological modeling.
基金National Key Basic Research Program of China(973 Program),No.2015CB452701National Natural Science Foundation of China,No.41271003+1 种基金No.41371043No.41401042
文摘Accurate estimation of evapotranspiration(ET),especially at the regional scale,is an extensively investigated topic in the field of water science. The ability to obtain a continuous time series of highly precise ET values is necessary for improving our knowledge of fundamental hydrological processes and for addressing various problems regarding the use of water. This objective can be achieved by means of ET data assimilation based on hydrological modeling. In this paper,a comprehensive review of ET data assimilation based on hydrological modeling is provided. The difficulties and bottlenecks of using ET,being a non-state variable,to construct data assimilation relationships are elaborated upon,with a discussion and analysis of the feasibility of assimilating ET into various hydrological models. Based on this,a new easy-to-operate ET assimilation scheme that includes a water circulation physical mechanism is proposed. The scheme was developed with an improved data assimilation system that uses a distributed time-variant gain model(DTVGM),and the ET-soil humidity nonlinear time response relationship of this model. Moreover,the ET mechanism in the DTVGM was improved to perfect the ET data assimilation system. The new scheme may provide the best spatial and temporal characteristics for hydrological states,and may be referenced for accurate estimation of regional evapotranspiration.
基金supported by the National Basic Research Program of China(Grant No.2006CB400502)the World Bank Cooperative Project(Grant No.THSD-07)the 111 Program of the Ministry of Education and the State Administration of Foreign Expert Affairs,China(Grant No.B08048)
文摘This study simulated and predicted the runoff of the Aksu River Basin, a typical river basin supplied by snowmelt in an arid mountain region, with a limited data set and few hydrological and meteorological stations. Two hydrological models, the snowmelt-runoff model （SRM） and the Danish NedbФr-AfstrФmnings rainfall-runoff model （NAM）, were used to simulate daily discharge processes in the Aksu River Basin. This study used the snow-covered area from MODIS remote sensing data as the SRM input. With the help of ArcGIS software, this study successfully derived the digital drainage network and elevation zones of the basin from digital elevation data. The simulation results showed that the SRM based on MODIS data was more accurate than NAM. This demonstrates that the application of remote sensing data to hydrological snowmelt models is a feasible and effective approach to runoff simulation and prediction in arid unguaged basins where snowmelt is a major runoff factor.
基金funded by the National Natural Science Foundation of China (42174030)Major Science and Technology Program for Hubei Province (Grant No.2022AAA002)+2 种基金Special fund of Hubei Luojia Loboratory (220100020)the National Natural Science Foundation of China under Grant 42304031the China Postdoctoral Science Foundation 2022M722441。
文摘Hydrological models are crucial for characterizing large-scale water quantity variations and correcting GNSS reference station vertical displacements.We evaluated the robustness of multiple models,such as the Global Land Data Assimilation System (GLDAS),the Famine Early Warning System Network Land Data Assimilation System (FLDAS),the National Centers for Environmental Prediction (NCEP),and the WaterGAP Global Hydrology Model (WGHM).Inter-model and outer comparisons with Global Positioning System (GPS) coordinate time series,satellite gravity field Mascon solutions,and Global Precipitation Climatology Centre (GPCC) guide our assessment.Results confirm WGHM's 26% greater effectiveness in correcting nonlinear variations in GPS height time series compared to NCEP.In the Amazon River Basin,a 5-month lag between FLDAS,GLDAS,and satellite gravity results is observed.In eastern Asia and Australia,NCEP's Terrestrial Water Storage Changes (TWSC)-derived surface displacements correlate differently with precipitation compared to other models.Three combined hydrological models (H-VCE,H-EWM,and H-CVM) utilizing Variance Component Estimation (VCE),Entropy Weight Method (EWM),and Coefficient of Variation Method (CVM) are formulated.Correcting nonlinear variations with combined models enhances global GPS height scatter by 15%-17%.Correlation with precipitation increases by 25%-30%,and with satellite gravity,rises from 0.2 to 0.8 at maximum.The combined model eliminates time lag in the Amazon Basin TWSC analysis,exhibiting a four times higher signal-to-noise ratio than single models.H-VCE demonstrates the highest accuracy.In summary,the combined hydrological model minimizes discrepancies among individual models,significantly improving accuracy for monitoring large-scale TWSC.
基金supported by the National Natural Science Foundation of China(Grant Nos.41930759,42325502)the West Light Foundation of the Chinese Academy of Sciences(Grant No.xbzg-zdsys-202215)+2 种基金the Chinese Academy Sciences Talents Program,National Cryosphere Desert Data Centerthe Qinghai Key Laboratory of Disaster Prevention(Grant No.QFZ-2021-Z02)2023 First Batch of Science and Technology Plan Projects of Lanzhou City(Grant No.2023-1-49)。
文摘Hydrological modeling,leveraging mathematical formulations to represent the hydrological cycle,is a pivotal tool in representing the spatiotemporal dynamics and distribution patterns inherent in hydrology.These models serve a dual purpose:they validate theoretical robustness and applicability via observational data and project future trends,thereby bridging the understanding and prediction of natural processes.In rapid advancements in computational methodologies and the continuous evolution of observational and experimental techniques,the development of numerical hydrological models based on physicallybased surface-subsurface process coupling have accelerated.Anchored in micro-scale conservation principles and physical equations,these models employ numerical techniques to integrate surface and subsurface hydrodynamics,thus replicating the macro-scale hydrological responses of watersheds.Numerical hydrological models have emerged as a leading and predominant trend in hydrological modeling due to their explicit representation of physical processes,heightened by their spatiotemporal resolution and reliance on interdisciplinary integration.This article focuses on the theoretical foundation of surface-subsurface numerical hydrological models.It includes a comparative and analytical discussion of leading numerical hydrological models,encompassing model architecture,numerical solution strategies,spatial representation,and coupling algorithms.Additionally,this paper contrasts these models with traditional hydrological models,thereby delineating the relative merits,drawbacks,and future directions of numerical hydrological modeling.
文摘Vegetation information is seldom considered in lumped conceptual rainfall-runoff models.This paper uses two modified rainfall-runoff models,the Xinanjiang-ET and SIMHYD-ET models in which vegetation leaf area index is incorporated,to investigate impacts of vegetation change and climate variability on streamflow in a Southern Australian catchment,the Crawford River experimental catchment,where Tasmanian blue gum plantations were introduced gradually from 1998 till 2005.The Xinanjiang-ET and SIMHYD-ET models incorporate remotely-sensed leaf area index(LAI) data obtained from the Advanced Very High Resolution Radiometer(AVHRR) on board NOAA polar orbiting satellites.Compared to the original versions,the Xinanjiang-ET and SIMHYD-ET models show marginal improvements in runoff simulations in the pre-plantation period(1882-1997).The calibrated Xinanjaing-ET and SIMHYD-ET models are then used to simulate plantation impact on streamflow in the post-plantation period.The total change in streamflow between the pre-plantation and post-plantation periods is 32.4 mm/a.The modelling results from the two models show that plantation reduces streamflow by 20.5 mm/a,and climate variability reduces streamflow by 11.9 mm/a.These results suggest that increase in plantations can reduce streamflow substantially,even more than climate variability.
文摘The aim of this paper is to present graphically the behaviour of a simulation model to the varying parameters and to establish the suitability of this representation as a valid tool for the analysis of the same parameters. In this paper, we define parameter combinatorial diagram as the joint graphical representation of all box plots related to the adjustment between real and simulated data, by setting and/or changing the parameters of the simulation model. To do this, we start with a box plot representing the values of an objective adjustment function, achieving these results when varying all the parameters of the simulation model, Then we draw the box plot when setting all the parameters of the model, for example, using the median or average. Later, we get all the box plots when carrying out simulations combining fixed or variable values of the model parameters. Finally, all box plots obtained are represented neatly in a single graph. It is intended that the new parameter combinatorial diagram is used to examine and analyze simulation models useful in practice. This paper presents combinatorial diagrams of different examples of application as in the case of hydrologic models of one, two, three, and five parameters.
基金supported by Yibin University,Sichuan,China and Hebei University,Baoding,China(Grant No.521100221033).
文摘Forest hydrology,the study of water dynamics within forested catchments,is crucial for understanding the intricate relationship between forest cover and water balances across different scales,from ecosystems to landscapes,or from catchment watersheds.The intensified global changes in climate,land use and cover,and pollution that occurred over the past century have brought about adverse impacts on forests and their services in water regulation,signifying the importance of forest hydrological research as a re-emerging topic of scientific interest.This article reviews the literature on recent advances in forest hydrological research,intending to identify leading countries,institutions,and researchers actively engaged in this field,as well as highlighting research hotspots for future exploration.Through a systematic analysis using VOSviewer,drawing from 17,006 articles retrieved from the Web of Science Core Collection spanning 2000–2022,we employed scientometric methods to assess research productivity,identify emerging topics,and analyze academic development.The findings reveal a consistent growth in forest hydrological research over the past two decades,with the United States,Charles T.Driscoll,and the Chinese Academy of Sciences emerging as the most productive country,author,and institution,respectively.The Journal of Hydrology emerges as the most co-cited journal.Analysis of keyword co-occurrence and co-cited references highlights key research areas,including climate change,management strategies,runoff-erosion dynamics,vegetation cover changes,paired catchment experiments,water quality,aquatic biodiversity,forest fire dynamics and hydrological modeling.Based on these findings,our study advocates for an integrated approach to future research,emphasizing the collection of data from diverse sources,utilization of varied methodologies,and collaboration across disciplines and institutions.This holistic strategy is essential for developing sustainable approaches to forested watershed planning and management.Ultimately,our study provides valuable insights for researchers,practitioners,and policymakers,guiding future research directions towards forest hydrological research and applications.
文摘Anthropogenically induced land use/land cover(LULC)transformations and accelerating climatic variabilities have emerged as pivotal forces reshaping the hydrological equilibrium of fluvial systems,particularly in ecologically sensitive basins.This study systematically interrogates the compounded ramifications of LULC dynamics and projected climate change on the hydrological response of the Upper Jemma Watershed an integral sub-catchment of the Upper Blue Nile River system.Employing the advanced QSWAT+hydrological modeling framework within a GIS interface,the analysis integrates bias‐corrected climatic projections under RCP 4.5 and RCP 8.5 scenarios alongside multi-temporal remote sensing‐derived land cover datasets.The findings unveil an unequivocal intensification of surface runoff and streamflow due to expansive agricultural encroachment,juxtaposed with a discernible decline in evapotranspiration and soil water retention.Climatic perturbations,notably temperature elevation and precipitation attenuation,further exacerbate these trends,with pronounced seasonality in hydrological fluxes.Importantly,synergistic interactions between land cover transformation and climatic anomalies manifest in nonlinear hydrological alterations,amplifying peak flows and diminishing baseflows.This underscores the riverine system's heightened vulnerability and the necessity for integrated watershed management strategies that account for multifactorial hydrological stressors.The study provides a robust empirical and modeling basis to inform adaptive water governance within transboundary river basins susceptible to environmental transitions.
文摘The simulation of hydrological consequences of climate change has received increasing attention from the hydrology and land-surface modelling communities. There have been many studies of climate-change effects on hydrology and water resources which usually consist of three steps： （1） use of general circulation models （GCMs） to provide future global climate scenarios under the effect of increasing greenhouse gases, （2） use of downscaling techniques （both nested regional climate models, RCMs, and statistical methods） for ＂downscaling＂ the GCM output to the scales compatible with hydrological models, and （3） use of hydrologic models to simulate the effects of climate change on hydrological regimes at various scales. Great progress has been achieved in all three steps during the past few years, however, large uncertainties still exist in every stage of such study. This paper first reviews the present achievements in this field and then discusses the challenges for future studies of the hydrological impacts of climate change.
文摘The integration of Artificial Intelligence(AI)and Machine Learning(ML)into groundwater exploration and water resources management has emerged as a transformative approach to addressing global water challenges.This review explores key AI and ML concepts,methodologies,and their applications in hydrology,focusing on groundwater potential mapping,water quality prediction,and groundwater level forecasting.It discusses various data acquisition techniques,including remote sensing,geospatial analysis,and geophysical surveys,alongside preprocessing methods that are essential for enhancing model accuracy.The study highlights AI-driven solutions in water distribution,allocation optimization,and realtime resource management.Despite their advantages,the application of AI and ML in water sciences faces several challenges,including data scarcity,model reliability,and the integration of these tools with traditional water management systems.Ethical and regulatory concerns also demand careful consideration.The paper also outlines future research directions,emphasizing the need for improved data collection,interpretable models,real-time monitoring capabilities,and interdisciplinary collaboration.By leveraging AI and ML advancements,the water sector can enhance decision-making,optimize resource distribution,and support the development of sustainable water management strategies.
基金National Key Research and Development Program of China,No.2023YFC3006704National Natural Science Foundation of China,No.42171047CAS-CSIRO Partnership Joint Project of 2024,No.177GJHZ2023097MI。
文摘Accurate prediction of flood events is important for flood control and risk management.Machine learning techniques contributed greatly to advances in flood predictions,and existing studies mainly focused on predicting flood resource variables using single or hybrid machine learning techniques.However,class-based flood predictions have rarely been investigated,which can aid in quickly diagnosing comprehensive flood characteristics and proposing targeted management strategies.This study proposed a prediction approach of flood regime metrics and event classes coupling machine learning algorithms with clustering-deduced membership degrees.Five algorithms were adopted for this exploration.Results showed that the class membership degrees accurately determined event classes with class hit rates up to 100%,compared with the four classes clustered from nine regime metrics.The nonlinear algorithms(Multiple Linear Regression,Random Forest,and least squares-Support Vector Machine)outperformed the linear techniques(Multiple Linear Regression and Stepwise Regression)in predicting flood regime metrics.The proposed approach well predicted flood event classes with average class hit rates of 66.0%-85.4%and 47.2%-76.0%in calibration and validation periods,respectively,particularly for the slow and late flood events.The predictive capability of the proposed prediction approach for flood regime metrics and classes was considerably stronger than that of hydrological modeling approach.
文摘Flood events occurrences and frequencies in the world are of immense worry for the stability of the economy and life safety. Africa continent is the third continent the most negatively affected by the flood events after Asia and Europe. Eastern Africa is the most hit in Africa. However, Africa continent is at the early stage in term of flood forecasting models development and implementation. Very few hydrological models for flood forecasting are available and implemented in Africa for the flood mitigation. And for the majority of the cases, they need to be improved because of the time evolution. Flash flood in Bamako (Mali) has been putting both human life and the economy in jeopardy. Studying this phenomenon, as to propose applicable solutions for its alleviation in Bamako is a great concern. Therefore, it is of upmost importance to know the existing scientific works related to this situation in Mali and elsewhere. The main aim was to point out the various solutions implemented by various local and international institutions, in order to fight against the flood events. Two types of methods are used for the flood events adaptation: the structural and non-structural methods. The structural methods are essentially based on the implementation of the structures like the dams, dykes, levees, etc. The problem of these methods is that they may reduce the volume of water that will inundate the area but are not efficient for the prediction of the coming floods and cannot alert the population with any lead time in advance. The non-structural methods are the one allowing to perform the prediction with acceptable lead time. They used the hydrological rainfall-runoff models and are the widely methods used for the flood adaptation. This review is more accentuated on the various types non-structural methods and their application in African countries in general and West African countries in particular with their strengths and weaknesses. Hydrologiska Byråns Vattenbalansavdelning (HBV), Hydrologic Engineer Center Hydrologic Model System (HEC-HMS) and Soil and Water Assessment Tool (SWAT) are the hydrological models that are the most widely used in West Africa for the purpose of flood forecasting. The easily way of calibration and the weak number of input data make these models appropriate for the West Africa region where the data are scarce and often with bad quality. These models when implemented and applied, can predict the coming floods, allow the population to adapt and mitigate the flood events and reduce considerably the impacts of floods especially in terms of loss of life.
文摘The study is focused on hydrological response of a catchment to rainfall in extremely humid monsoonal climate region at the Meghalaya Plateau(India)near Cherrapunji.This area has been rarely investigated due to the lack of the detailed hydro-meteorological data.Hourly rainfall data were collected between 1999 and 2009 and hydrological data obtained for the Maw-Ki-Syiem experimental catchment(0.22 km^(2))was used to calibrate hydrological models(SCS-CN and GIUH)and to model river runoff during rainy periods in 2005.Hydrographs revealed rapid responses of the catchment to heavy rainfall.The rising limb and recession limb were very steep and coincided with hourly course of rainfall.
基金National Key Basic Research Program of China,No.2010CB428403National Grand Science and Technology Special Project of Water Pollution Control and Improvement,No.2009ZX07210-006
文摘The regional hydrological system is extremely complex because it is affected not only by physical factors but also by human dimensions.And the hydrological models play a very important role in simulating the complex system.However,there have not been effective methods for the model reliability and uncertainty analysis due to its complexity and difficulty.The uncertainties in hydrological modeling come from four important aspects：uncertainties in input data and parameters,uncertainties in model structure,uncertainties in analysis method and the initial and boundary conditions.This paper systematically reviewed the recent advances in the study of the uncertainty analysis approaches in the large-scale complex hydrological model on the basis of uncertainty sources.Also,the shortcomings and insufficiencies in the uncertainty analysis for complex hydrological models are pointed out.And then a new uncertainty quantification platform PSUADE and its uncertainty quantification methods were introduced,which will be a powerful tool and platform for uncertainty analysis of large-scale complex hydrological models.Finally,some future perspectives on uncertainty quantification are put forward.
基金National Key Technology P&D Program,No.2012BAB02B00The Fundamental Research Funds for the Central Universities
文摘The objective of this study is to quantitatively evaluate Tropical Rainfall Measuring Mission （TRMM） data with rain gauge data and further to use this TRMM data to drive a Dis- tributed Time-Variant Gain Model （DTVGM） to perform hydrological simulations in the semi-humid Weihe River catchment in China. Before the simulations, a comparison with a 10-year （2001-2010） daily rain gauge data set reveals that, at daily time step, TRMM rainfall data are better at capturing rain occurrence and mean values than rainfall extremes. On a monthly time scale, good linear relationships between TRMM and rain gauge rainfall data are found, with determination coefficients R2 varying between 0.78 and 0.89 for the individual stations. Subsequent simulation results of seven years （2001-2007） of data on daily hydro- logical processes confirm that the DTVGM when calibrated by rain gauge data performs better than when calibrated by TRMM data, but the performance of the simulation driven by TRMM data is better than that driven by gauge data on a monthly time scale. The results thus suggest that TRMM rainfall data are more suitable for monthly streamfiow simulation in the study area, and that, when the effects of recalibration and the results for water balance components are also taken into account, the TRMM 3B42-V7 product has the potential to perform well in similar basins.
基金This work was jointly supported by the National Natural Science Foundation of China under Grant No. 40205012, and 40201048, the Chinese NKBRSF Project G1999043400 and the Foundation of the China Ministry of Education (Grant No. 20010284027). The computat
文摘Considering a detailed hydrologic model in the land surface scheme helps to improve the simulation of regional hydro-climatology. A hydrologic model, which includes spatial heterogeneities in precipitation and infiltration, is constructed and incorporated into the land surface scheme BATS. Via the coupled-model (i.e., a regional climate model) simulations, the following major conclusions are obtained: the simulation of surface hydrology is sensitive to the inclusion of heterogeneities in precipitation and infiltration; the runoff ratio is increased after considering the infiltration heterogeneity, a result which is more consistent with the observations of surface moisture balance over humid areas; the introduction of the parameterization of infiltration heterogeneity can have a greater influence on the regional hydro-climatology than the precipitation heterogeneity; and the consideration of the impermeable fraction for the region reveals some features that are closer to the trend of aridification over northern China.
基金This work is jointly supported by the National Key Research and Development Program of China(2016YFA0601603)the Second Tibetan Plateau Scientific Expedition and Research Program(2019QZKK0206)+1 种基金the National Natural Science Foundation of China(91747101&41801260)the Strategic Priority Research Program of Chinese Academy of Sciences(XDA20100103).
文摘The Nu-Salween River(NSR),the longest free-flow river in Southeast Asia,plays an irreplaceable role in social development and ecological protection.The lower NSR region is particularly valuable as it is inhabited by approximately 6.7 million people.The basin has limited hydraulic conservancy infrastructure and insufficient ability to cope with climate change risks.Studying the hydrological characteristics and changes in the basin provides the scientific basis for rational protection and development of the basin.However,owing to the limitation of observation data,previous studies have focused on the local area and neglected the study of the lower reaches,which is not enough to reflect the spatial characteristics of the entire basin.In this study,the ECMWF 5th generation reanalysis data(ERA5)and Multi-Source Weighted-Ensemble Precipitation(MSWEP)were applied to develop a geomorphology-based hydrological model(GBHM)for reconstructing hydrological datasets(i.e.GBHM-ERA5 and GBHM-MSWEP).The reconstructed datasets covering the complete basin were verified against the gauge observation and compared with other commonly used streamflow products,including Global Flood Awareness System v2.1,GloFAS-Reanalysis dataset v3.0,and linear optimal runoff aggregate(LORA).The comparison results revealed that GBHM-ERA5 is significantly better than the other four datasets and provides a good reproduction of the hydrological characteristics and trends of the NSR.Detailed analysis of GBHM-ERA5 revealed that:(1)A multi-year mean surface runoff represented 39%of precipitation over the basin during 1980–2018,which had low surface runoff in the upstream,while areas around the Three Parallel Rivers Area and the estuary had abundant surface runoff.(2)The surface runoff and discharge coefficient of variations in spring were larger than those in other seasons,and the inter-annual variation in the downstream was smaller than that in the upstream and midstream regions.(3)More than 70%of the basin areas showed a decreasing trend in the surface runoff,except for parts of Nagqu,south of Shan State in Myanmar,and Thailand,where surface runoff has an increasing trend.(4)The downstream discharge has dropped significantly at a rate of approximately 680 million cubic metresper year,and the decline rate is greater than that of upstream and midstream,especially in summer.This study provides a data basis for subsequent studies in the NSR basin and further elucidates the impact of climate change on the basin,which is beneficial to river planning and promotes international cooperation on the water-and eco-security of the basin.
