Based on improvement of a distributed hydrology-soil-vegetation model (DHSVM for short) and its application to North China,a nested regional climatic-hydrologic model system is developed by connecting DHSVM with RegCM...Based on improvement of a distributed hydrology-soil-vegetation model (DHSVM for short) and its application to North China,a nested regional climatic-hydrologic model system is developed by connecting DHSVM with RegCM2/China.The simulated climate scenarios,including control and 2×CO_2 outputs,are downscaled to 8 stations in Luanhe River and Sanggan River Basins to drive the hydrology model.According to simulation results,under double CO_2 scenarios,annual mean temperature and evapotranspiration will increase 2.8C and 29 mm,respectively; precipitation also increase but with different value for each basin,6 mm for Luanhe River Basin while 46 mm for Sanggan River Basin;runoff change for the two basins is different too,27 mm decrease for Luanhe River Basin while 26 mm increase for Sanggan River Basin.As a result,the runoff in future for Luanhe River Basin and Sanggan River Basin will be 74 mm and 71 mm, respectively,which is approximately a quarter of annual mean runoff(284 mm)of the whole country.Total streamflow for the two basins will decrease about 2.5×10~8m^3.All these indicate that the warm and dry trend will continue in the two river basins under double CO_2 scenarios.The nested model system,with both climatic and hydrologic prediction ability,could also be applied to other basins in China by parameter adjustment.展开更多
The advanced distributed hydrology-soil-vegetation model DHSVM,developed by Wigmosta et al.(1994)is introduced from US Pacific Northwest National Laboratory.To apply DHSVM in China for the first time some improvements...The advanced distributed hydrology-soil-vegetation model DHSVM,developed by Wigmosta et al.(1994)is introduced from US Pacific Northwest National Laboratory.To apply DHSVM in China for the first time some improvements have been made in terms of the basin characteristics: 1)to change evapotranspiration model,using the improved Penman-Monteith approach in place of the original one;2)to change the model structure,inserting datasets from 4 stations to grid cells for each river basin,instead of datasets from one or two stations;3)to develop new hydrology, vegetation and soil parameterization schemes for improving the simulated results,with focus on calculation and adjustment of 11 parameters,such as soil porosity (?),field capacity θ_(fc),leaf area index LAI,stochastic resistance γ_s,among the total 33 parameters.Then the improved DHSVM is driven by observed datasets for Luanhe River Basin and Sanggan River Basin,respectively.The simulated evapotranspiration(ET),runoff,snow water equivalent,water table,soil moisture and percolation are then gained as DHSVM outputs.The simulated ET shows that the highest peak appears in May or June instead of July or August.This is consistent with the real situations, owing to the improvement of ET model.The simulated runoff process and flood peak are quite consistent with the observed ones.The model efficiency values for Luanhe River and Sanggan River Basins are 0.89 and 0.82,respectively,which shows high simulating ability of the model system for both relatively humid and dry basins.展开更多
Climate change and human activities are primary drivers of runoff variations,significantly impacting the hydrological balance of river basins.In recent decades,the Yellow River Basin,China has experienced a marked dec...Climate change and human activities are primary drivers of runoff variations,significantly impacting the hydrological balance of river basins.In recent decades,the Yellow River Basin,China has experienced a marked decline in runoff,posing challenges to the sustainable development of regional water resources and ecosystem stability.To enhance the understanding of runoff dynamics in the basin,we selected the Dahei River Basin,a representative tributary in the upper reaches of the Yellow River Basin as the study area.A comprehensive analysis of runoff trends and contributing factors was conducted using the data on hydrology,meteorology,and water resource development and utilization.Abrupt change years of runoff series in the Dahei River Basin was identified by the Mann-Kendall and Pettitt tests:1999 at Dianshang,Qixiaying,and Meidai hydrological stations and 1995 at Sanliang hydrological station.Through hydrological simulations based on the Variable Infiltration Capacity(VIC)model,we quantified the factors driving runoff evolution in the Dahei River Basin,with climate change contributing 9.92%–22.91%and human activities contributing 77.09%–90.08%.The Budyko hypothesis method provided similar results,with climate change contributing 13.06%–20.89%and human activities contributing 79.11%–86.94%.Both methods indicated that human activities,particularly water consumption,were dominant factors in the runoff variations of the Dahei River Basin.The integration of hydrological modeling with attribution analysis offers valuable insights into runoff evolution,facilitating adaptive strategies to mitigate water scarcity in arid and semi-arid areas.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
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
Characterized by special morphologic,geographic,hydrologic,and societal behaviors,the water resources management of the Mediterranean catchment often shows a higher level of complexity including security issues of wat...Characterized by special morphologic,geographic,hydrologic,and societal behaviors,the water resources management of the Mediterranean catchment often shows a higher level of complexity including security issues of water supply,inundation risks,and environment management under the perspective of climate change.To have a comprehensive understanding of the Mediterranean water-cycle system,a deterministic distributed hydrologic modeling approach has been developed and presented in this study based on an application in the Var catchment(2800 km^(2))located at the French Mediterranean region.A 1D and 2D coupled model of MIKE SHE and MIKE 11 has been set up under a series of hypotheses to represent the whole hydrologic and hydrodynamic processes including rainfall-runoff,snow-melting,channel flow,overland flow,and the water exchange between land surface and unsaturated/saturated zones.The developed model was first calibrated with 4 years daily records from 2008 to 2011,then to be validated and further run within hourly time interval to produce detailed representation of the catchment water-cycle from 2012 to 2014.The deterministic distributed modeling approach presented in this study is able to represent its complicated water-cycle and used for supporting the decision‐making process of the water resources management of the catchment.展开更多
In this study we compared weekly GNSS position time series with modelled values of crustal deformations on the basis of Gravity Recovery and Climate Experiment （GRACE） data. The Global Navigation Satellite Systems ...In this study we compared weekly GNSS position time series with modelled values of crustal deformations on the basis of Gravity Recovery and Climate Experiment （GRACE） data. The Global Navigation Satellite Systems （GNSS） time series were taken from homogeneously reprocessed global network solutions within the International GNSS Service （IGS） Reprucessing 1 project and from regional solutions performed by Warsaw University of Technology （WUT） European Permanent Network （EPN） Local Analysis Center （LAC） within the EPN reprocessing project. Eight GNSS sites from the territory of Poland with observation timespans between 2.5 and 13 years were selected for this study. The Total Water Equivalent （TWE） estimation from GRACE data was used to compute deformations using the Green＇s function formalism. High frequency components were removed from GRACE data to avoid aliasing problems. Since GRACE observes mainly the mass transport in continental storage of water, we also compared GRACE deformations and the GNSS position time series, with the deformations computed on the basis of a hydrosphere model. We used the output of Water GAP Hydrology Model （WGHM） to compute deformations in the same manner as for the GRACE data. The WGHM gave slightly larger amplitudes than GNSS and GRACE. The atmospheric non-tidal loading effect was removed from GNSS position time series before comparing them with modelled deformations. The results confirmed that the major part of observed seasonal variations for GNSS vertical components can be attributed to the hy- drosphere loading. The results for these components agree very well both in the amplitude and phase. The decrease in standard deviation of the residual GNSS position time series for vertical components corrected for the hydrosphere loading reached maximally 36% and occurred for all but one stations for both global and regional solutions. For horizontal components the amplitudes are about three times smaller than for vertical components therefore the comparison is much more complicated and the conclusions are ambiguous.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
Surface runoff is mainly generated by two mechanisms, infiltration excess (Horton) runoff and saturation excess (Dunne) runoff; and the spatial variability of soil properties, antecedent soil moisture, topography, and...Surface runoff is mainly generated by two mechanisms, infiltration excess (Horton) runoff and saturation excess (Dunne) runoff; and the spatial variability of soil properties, antecedent soil moisture, topography, and rainfall will result in different surface runoff generation mechanisms. For a large area (e.g., a model grid size of a regional climate model or a general circulation model), these runoff generation mechanisms are commonly present at different portions of a grid cell simultaneously. Missing one of the two major runoff generation mechanisms and failing to consider spatial soil variability can result in significant under/over estimation of surface runoff which can directly introduce large errors in soil moisture states over each model grid cell. Therefore, proper modeling of surface runoff is essential to a reasonable representation of feedbacks in a land-atmosphere system. This paper presents a new surface runoff parameterization with the Philip infiltration formulation that dynamically represents both the Horton and Dunne runoff generation mechanisms within a model grid cell. The parameterization takes into account the effects of soil heterogeneity on Horton and Dunne runoff. The new parameterization is implemented into the current version of the hydrologically based Variable Infiltration Capacity (VIC) land surface model and tested over one watershed in Pennsylvania, USA and over the Shiguanhe Basin in the Huaihe Watershed in China. Results show that the new parameterization plays a very important role in partitioning the water budget between surface runoff and soil moisture in the atmosphere-land coupling system, and has potential applications on large hydrological simulations and land-atmospheric interactions. It is further found that the Horton runoff mechanism should be considered within the context of subgrid-scale spatial variability of soil properties and precipitation.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 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
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
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
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
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
Debris flow forecast is an important means of disaster mitigation. However, the accuracy of the statistics-based debris flow forecast is unsatisfied while the mechanism-based forecast is unavailable at the watershed s...Debris flow forecast is an important means of disaster mitigation. However, the accuracy of the statistics-based debris flow forecast is unsatisfied while the mechanism-based forecast is unavailable at the watershed scale because most of existing researches on the initiation mechanism of debris flow took a single slope as the main object. In order to solve this problem, this paper developed a model of debris flow forecast based on the water-soil coupling mechanism at the watershed scale. In this model, the runoff and the instable soil caused by the rainfall in a watershed is estimated by the distrib- uted hydrological model （GBHM） and an instable identification model of the unsaturated soil. Because the debris flow is a special fluid composed of soil and water and has a bigger density, the density esti- mated by the runoff and instable soil mass in a watershed under the action of a rainfall is employed as a key factor to identify the formation probability of debris flow in the forecast model. The Jiangjia Gulley, a typical debris flow valley with a several debris flow events each year, is selected as a case study watershed to test this forecast model of debris flow. According the observation data of Dongchuan Debris Flow Observation and Research Station, CAS located in Jiangjia Gulley, there were 4 debris flow events in 2006. The test results show that the accuracy of the model is satisfied.展开更多
This study presented a simulation-based two-stage interval-stochastic programming （STIP） model to support water resources management in the Kaidu-Konqi watershed in Northwest China. The modeling system coupled a dis...This study presented a simulation-based two-stage interval-stochastic programming （STIP） model to support water resources management in the Kaidu-Konqi watershed in Northwest China. The modeling system coupled a distributed hydrological model with an interval two-stage stochastic programing （ITSP）. The distributed hydrological model was used for establishing a rainfall-runoff forecast system, while random parameters were pro- vided by the statistical analysis of simulation outcomes water resources management planning in Kaidu-Konqi The developed STIP model was applied to a real case of watershed, where three scenarios with different water re- sources management policies were analyzed. The results indicated that water shortage mainly occurred in agri- culture, ecology and forestry sectors. In comparison, the water demand from municipality, industry and stock- breeding sectors can be satisfied due to their lower consumptions and higher economic values. Different policies for ecological water allocation can result in varied system benefits, and can help to identify desired water allocation plans with a maximum economic benefit and a minimum risk of system disruption under uncertainty.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
A grid and Green-Ampt based （Grid-GA）distributed hydrologic physical model was developed for flood simulation and forecasting in semi-humid and semi-arid basin. Based on topographical information of each grid cell e...A grid and Green-Ampt based （Grid-GA）distributed hydrologic physical model was developed for flood simulation and forecasting in semi-humid and semi-arid basin. Based on topographical information of each grid cell extracted fi＇om the digital elevation model （DEM） and Green-Ampt infiltration method, the Grid-GA model takes into consideration the redistribution of water content, and consists of vegetation and root interception, evapotranspiration, runoff generation via the excess infiltration mechanism, runoff concentration, and flow routing. The downslope redis- tribution of soil moisture is explicitly calculated on a grid basis, and water exchange among grids within runoff routing along the river drainage networks is taken into consideration. The proposed model and Xin＇anjiang model were ap- plied to the upper Lushi basin in the Luohe River, a tributary of the Yellow River, with an area of 4 716 km2 for flood simulation. Results show that both models perform well in flood simulation and can be used for flood forecasting in semi-humid and semi-arid region.展开更多
文摘Based on improvement of a distributed hydrology-soil-vegetation model (DHSVM for short) and its application to North China,a nested regional climatic-hydrologic model system is developed by connecting DHSVM with RegCM2/China.The simulated climate scenarios,including control and 2×CO_2 outputs,are downscaled to 8 stations in Luanhe River and Sanggan River Basins to drive the hydrology model.According to simulation results,under double CO_2 scenarios,annual mean temperature and evapotranspiration will increase 2.8C and 29 mm,respectively; precipitation also increase but with different value for each basin,6 mm for Luanhe River Basin while 46 mm for Sanggan River Basin;runoff change for the two basins is different too,27 mm decrease for Luanhe River Basin while 26 mm increase for Sanggan River Basin.As a result,the runoff in future for Luanhe River Basin and Sanggan River Basin will be 74 mm and 71 mm, respectively,which is approximately a quarter of annual mean runoff(284 mm)of the whole country.Total streamflow for the two basins will decrease about 2.5×10~8m^3.All these indicate that the warm and dry trend will continue in the two river basins under double CO_2 scenarios.The nested model system,with both climatic and hydrologic prediction ability,could also be applied to other basins in China by parameter adjustment.
文摘The advanced distributed hydrology-soil-vegetation model DHSVM,developed by Wigmosta et al.(1994)is introduced from US Pacific Northwest National Laboratory.To apply DHSVM in China for the first time some improvements have been made in terms of the basin characteristics: 1)to change evapotranspiration model,using the improved Penman-Monteith approach in place of the original one;2)to change the model structure,inserting datasets from 4 stations to grid cells for each river basin,instead of datasets from one or two stations;3)to develop new hydrology, vegetation and soil parameterization schemes for improving the simulated results,with focus on calculation and adjustment of 11 parameters,such as soil porosity (?),field capacity θ_(fc),leaf area index LAI,stochastic resistance γ_s,among the total 33 parameters.Then the improved DHSVM is driven by observed datasets for Luanhe River Basin and Sanggan River Basin,respectively.The simulated evapotranspiration(ET),runoff,snow water equivalent,water table,soil moisture and percolation are then gained as DHSVM outputs.The simulated ET shows that the highest peak appears in May or June instead of July or August.This is consistent with the real situations, owing to the improvement of ET model.The simulated runoff process and flood peak are quite consistent with the observed ones.The model efficiency values for Luanhe River and Sanggan River Basins are 0.89 and 0.82,respectively,which shows high simulating ability of the model system for both relatively humid and dry basins.
基金supported by the National Key Research and Development Program of China(2022YFC3204401)the National Natural Science Foundation of China(U23A2001,U2243234)+2 种基金the Major Science and Technology Projects of Inner Mongolia Autonomous Region(KCX2024013-1,2022EEDSKJXM005)the Inner Mongolia Autonomous Region Science and Technology Leading Talent Team(2022LJRC0007)the Inner Mongolia Agricultural University Basic Research Business Expenses Project(BR221012,BR221204).
文摘Climate change and human activities are primary drivers of runoff variations,significantly impacting the hydrological balance of river basins.In recent decades,the Yellow River Basin,China has experienced a marked decline in runoff,posing challenges to the sustainable development of regional water resources and ecosystem stability.To enhance the understanding of runoff dynamics in the basin,we selected the Dahei River Basin,a representative tributary in the upper reaches of the Yellow River Basin as the study area.A comprehensive analysis of runoff trends and contributing factors was conducted using the data on hydrology,meteorology,and water resource development and utilization.Abrupt change years of runoff series in the Dahei River Basin was identified by the Mann-Kendall and Pettitt tests:1999 at Dianshang,Qixiaying,and Meidai hydrological stations and 1995 at Sanliang hydrological station.Through hydrological simulations based on the Variable Infiltration Capacity(VIC)model,we quantified the factors driving runoff evolution in the Dahei River Basin,with climate change contributing 9.92%–22.91%and human activities contributing 77.09%–90.08%.The Budyko hypothesis method provided similar results,with climate change contributing 13.06%–20.89%and human activities contributing 79.11%–86.94%.Both methods indicated that human activities,particularly water consumption,were dominant factors in the runoff variations of the Dahei River Basin.The integration of hydrological modeling with attribution analysis offers valuable insights into runoff evolution,facilitating adaptive strategies to mitigate water scarcity in arid and semi-arid areas.
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.
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.
基金supported by the National Key R&D Program of China(No.2023YFC3006702)the Natural Science Foundation of Beijing Municipality(IS23117).
文摘Characterized by special morphologic,geographic,hydrologic,and societal behaviors,the water resources management of the Mediterranean catchment often shows a higher level of complexity including security issues of water supply,inundation risks,and environment management under the perspective of climate change.To have a comprehensive understanding of the Mediterranean water-cycle system,a deterministic distributed hydrologic modeling approach has been developed and presented in this study based on an application in the Var catchment(2800 km^(2))located at the French Mediterranean region.A 1D and 2D coupled model of MIKE SHE and MIKE 11 has been set up under a series of hypotheses to represent the whole hydrologic and hydrodynamic processes including rainfall-runoff,snow-melting,channel flow,overland flow,and the water exchange between land surface and unsaturated/saturated zones.The developed model was first calibrated with 4 years daily records from 2008 to 2011,then to be validated and further run within hourly time interval to produce detailed representation of the catchment water-cycle from 2012 to 2014.The deterministic distributed modeling approach presented in this study is able to represent its complicated water-cycle and used for supporting the decision‐making process of the water resources management of the catchment.
文摘In this study we compared weekly GNSS position time series with modelled values of crustal deformations on the basis of Gravity Recovery and Climate Experiment （GRACE） data. The Global Navigation Satellite Systems （GNSS） time series were taken from homogeneously reprocessed global network solutions within the International GNSS Service （IGS） Reprucessing 1 project and from regional solutions performed by Warsaw University of Technology （WUT） European Permanent Network （EPN） Local Analysis Center （LAC） within the EPN reprocessing project. Eight GNSS sites from the territory of Poland with observation timespans between 2.5 and 13 years were selected for this study. The Total Water Equivalent （TWE） estimation from GRACE data was used to compute deformations using the Green＇s function formalism. High frequency components were removed from GRACE data to avoid aliasing problems. Since GRACE observes mainly the mass transport in continental storage of water, we also compared GRACE deformations and the GNSS position time series, with the deformations computed on the basis of a hydrosphere model. We used the output of Water GAP Hydrology Model （WGHM） to compute deformations in the same manner as for the GRACE data. The WGHM gave slightly larger amplitudes than GNSS and GRACE. The atmospheric non-tidal loading effect was removed from GNSS position time series before comparing them with modelled deformations. The results confirmed that the major part of observed seasonal variations for GNSS vertical components can be attributed to the hy- drosphere loading. The results for these components agree very well both in the amplitude and phase. The decrease in standard deviation of the residual GNSS position time series for vertical components corrected for the hydrosphere loading reached maximally 36% and occurred for all but one stations for both global and regional solutions. For horizontal components the amplitudes are about three times smaller than for vertical components therefore the comparison is much more complicated and the conclusions are ambiguous.
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.
基金The research reported herein was jointly supported by the National Natural Science Foundation of China under Grant Nos. 40145020, 40275023, 49794030, the National Key Program for Developing Basic Sciences under Grant Nos. G1998040905 and 2001CB309404,
文摘Surface runoff is mainly generated by two mechanisms, infiltration excess (Horton) runoff and saturation excess (Dunne) runoff; and the spatial variability of soil properties, antecedent soil moisture, topography, and rainfall will result in different surface runoff generation mechanisms. For a large area (e.g., a model grid size of a regional climate model or a general circulation model), these runoff generation mechanisms are commonly present at different portions of a grid cell simultaneously. Missing one of the two major runoff generation mechanisms and failing to consider spatial soil variability can result in significant under/over estimation of surface runoff which can directly introduce large errors in soil moisture states over each model grid cell. Therefore, proper modeling of surface runoff is essential to a reasonable representation of feedbacks in a land-atmosphere system. This paper presents a new surface runoff parameterization with the Philip infiltration formulation that dynamically represents both the Horton and Dunne runoff generation mechanisms within a model grid cell. The parameterization takes into account the effects of soil heterogeneity on Horton and Dunne runoff. The new parameterization is implemented into the current version of the hydrologically based Variable Infiltration Capacity (VIC) land surface model and tested over one watershed in Pennsylvania, USA and over the Shiguanhe Basin in the Huaihe Watershed in China. Results show that the new parameterization plays a very important role in partitioning the water budget between surface runoff and soil moisture in the atmosphere-land coupling system, and has potential applications on large hydrological simulations and land-atmospheric interactions. It is further found that the Horton runoff mechanism should be considered within the context of subgrid-scale spatial variability of soil properties and precipitation.
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.
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.
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 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supported by the foundation of the Research Fund for Commonweal Trades (Meteorology) (No. GYHY201006039)
文摘Debris flow forecast is an important means of disaster mitigation. However, the accuracy of the statistics-based debris flow forecast is unsatisfied while the mechanism-based forecast is unavailable at the watershed scale because most of existing researches on the initiation mechanism of debris flow took a single slope as the main object. In order to solve this problem, this paper developed a model of debris flow forecast based on the water-soil coupling mechanism at the watershed scale. In this model, the runoff and the instable soil caused by the rainfall in a watershed is estimated by the distrib- uted hydrological model （GBHM） and an instable identification model of the unsaturated soil. Because the debris flow is a special fluid composed of soil and water and has a bigger density, the density esti- mated by the runoff and instable soil mass in a watershed under the action of a rainfall is employed as a key factor to identify the formation probability of debris flow in the forecast model. The Jiangjia Gulley, a typical debris flow valley with a several debris flow events each year, is selected as a case study watershed to test this forecast model of debris flow. According the observation data of Dongchuan Debris Flow Observation and Research Station, CAS located in Jiangjia Gulley, there were 4 debris flow events in 2006. The test results show that the accuracy of the model is satisfied.
基金supported by the National Basic Research Program of China(2010CB951002)the Dr.Western-funded Project of Chinese Academy of Science(XBBS201010 and XBBS201005)+1 种基金the National Natural Sciences Foundation of China (51190095)the Open Research Fund Program of State Key Laboratory of Hydro-science and Engineering(sklhse-2012-A03)
文摘This study presented a simulation-based two-stage interval-stochastic programming （STIP） model to support water resources management in the Kaidu-Konqi watershed in Northwest China. The modeling system coupled a distributed hydrological model with an interval two-stage stochastic programing （ITSP）. The distributed hydrological model was used for establishing a rainfall-runoff forecast system, while random parameters were pro- vided by the statistical analysis of simulation outcomes water resources management planning in Kaidu-Konqi The developed STIP model was applied to a real case of watershed, where three scenarios with different water re- sources management policies were analyzed. The results indicated that water shortage mainly occurred in agri- culture, ecology and forestry sectors. In comparison, the water demand from municipality, industry and stock- breeding sectors can be satisfied due to their lower consumptions and higher economic values. Different policies for ecological water allocation can result in varied system benefits, and can help to identify desired water allocation plans with a maximum economic benefit and a minimum risk of system disruption under uncertainty.
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.
基金Supported by National Natural Science Foundation of China (No.50479017)Program for Changjiang Scholars and Innovative Research Team in University (PCSIRT) (No. IRT0717)
文摘A grid and Green-Ampt based （Grid-GA）distributed hydrologic physical model was developed for flood simulation and forecasting in semi-humid and semi-arid basin. Based on topographical information of each grid cell extracted fi＇om the digital elevation model （DEM） and Green-Ampt infiltration method, the Grid-GA model takes into consideration the redistribution of water content, and consists of vegetation and root interception, evapotranspiration, runoff generation via the excess infiltration mechanism, runoff concentration, and flow routing. The downslope redis- tribution of soil moisture is explicitly calculated on a grid basis, and water exchange among grids within runoff routing along the river drainage networks is taken into consideration. The proposed model and Xin＇anjiang model were ap- plied to the upper Lushi basin in the Luohe River, a tributary of the Yellow River, with an area of 4 716 km2 for flood simulation. Results show that both models perform well in flood simulation and can be used for flood forecasting in semi-humid and semi-arid region.
