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In the past decade, more than 300 people have died per year on average due to mountain torrents in China. Mountain torrents mostly occur in ungauged small and medium-sized catchments, so it is difficult to maintain high accuracy of flood prediction. In order to solve the problem of the low accuracy of flood simulation in the ungauged areas, this paper studies the influence of different methods on the parameter regionalization of distributed hydrological model parameters in hilly areas of Hunan Province. According to the terrain, landform, soil and land use characteristics of each catchment, we use Shortest Distance, Attribute Similarity, Support Vector Regression, Generative Adversarial Networks, Classification and Regression Tree and Random Forest methods to create parameter regionalization schemes. In total, 426 floods of 25 catchments are selected to calibrate the model parameters, and 136 floods of 8 catchments are used for verification. The results showed that the average values of the Nash–Sutcliffe coefficients of each scheme were 0.58, 0.64, 0.60, 0.66, 0.61 and 0.68, and the worst values were 0.27, 0.31, 0.25, 0.43, 0.35 and 0.59. The random forest model is the most stable solution and significantly outperforms other methods. Using the random forest model to regionalize parameters can improve the accuracy of flood simulation in ungauged areas, which is of great significance for flash flood forecasting and early warning. [ABSTRACT FROM AUTHOR]

The Qinling Mountains are located in a transition zone between (semi)-arid regions in north China and humid regions in south China. The water resource and water ecology of regional rivers are strongly affected by climate change and human activity. In this paper, the stochastic simulation of river water regulation was performed and an optimal water regulation scheme of rubber dam projects was developed by establishing a multi-objective stochastic constraint water regulation model of rubber dam projects based on the coupling of a distributed hydrological model and a water balance model. Results show that a 40% reduction of water occurred in the lower river channel due to the operation of water supply project in the upper reach and impoundment by rubber dam projects in the lower reaches. This water reduction was associated with decreased water environment selfpurification capacity and serious deterioration of water quality for smaller ecological basic flow and mean flow velocity. By establishing a multi-objective stochastic constraint programming model, the average velocity and the ecological basic flow at different adjusting heights of rubber dams are determined. The regulation scheme of rubber dam projects we propose in this paper may optimize the current river water management strategies and help to improve the river water quality environment in urban rivers. [ABSTRACT FROM AUTHOR]

• Provide an alternative approach to utilize the subsidence areas for flood storage. • A hydrologic model was redeveloped to evaluate the flood storage of the study area. • The simulation results in Huaihe River show that the approach is feasible. Floods are one of the most devastating natural disasters, especially in the midstream plain area of the Huaihe River Basin (HRB) in China, where it is densely populated. This region has suffered from serious backwater flood problems due to its topography and geomorphology. Additional storage space is critical for this region in order to control flood. The middle reach of the Huaihe River is a coal-rich region. The large subsidence areas caused by coal mining may help reduce the issue of insufficient flood storage space, and therefore evaluation of the flood storage capacity in the subsidence areas becomes necessary. A distributed coupled surface water - groundwater model, MODCYCLE, was redeveloped to simulate the interaction between the rivers, the water in the subsidence areas and groundwater. The model was used to simulate maximum flood storage capacity in the subsidence areas and the ability to reduce flood peaks. Two scenarios were created for land subsidence conditions in 2010 and 2030 where typical flood events in 2003 were used. It is revealed that for the 2010 scenario, there was flood overflow even with the maximum storage space used, whereas for the 2030 scenario, the subsidence areas could completely contain the flood water, and therefore eliminate the backwater flood problem. Compared with the 2010 subsidence scenario, the water levels in the depressions can also be significantly reduced in the 2030 subsidence scenario. Our results, from an integrated hydrological modeling's perspective, suggest that using the subsidence areas caused by coal mining for flood storage has the potential to alleviate the problem of backwater flood in the study area, and in the meantime provides an alternative management approach for handling the subsidence areas. [ABSTRACT FROM AUTHOR]

This study proposes and tests a new approach to detect and analyze changes in flood regime using a distributed hydrological model (EasyDHM), using the Second Songhua River basin, China, as a case study. Model calibration and parameter sensitivity were used to represent flood regimes in a 60-year series (1954-2013), with three different flood regime periods identified. The changes in flood regime were estimated by model parameters, flood result residuals and the overall process in the hydrological model in the three periods. The results show that human activities significantly impacted flood regimes, with significant flood regime change largely attributed to increases in water storage in multiple small reservoirs. Flood volume was reduced significantly between the periods in all three watersheds. The parameters also changed in variety between the periods. The study highlights the importance of incorporating data on small-reservoir constructions in flood control systems. [ABSTRACT FROM AUTHOR]

As the two largest rivers in China, the Yangtze and Yellow Rivers are of great importance for water cycle and hydrological processes over the country, which have been significantly affected by climate change. In this study, by assessing the suitability of multiple GCMs (General Circulation Models) recommended by IPCC (Intergovernmental Panel on Climate Change), SDSM (Statistical Downscaling Model) and ASD (Automated Statistical Downscaling) were used to generate future climate change scenarios, which were used to drive VIC (Variable Infiltration Capacity) and SWAT (Soil and Water Assessment Tool) models to quantify climate change impacts in the Yangtze River Delta region and upper reaches of the Yellow River basin, respectively. Results showed that suitability assessment method adopted in this study coupled with statistical downscaling could effectively reduce uncertainties of GCMs. Compared with the baseline period (1961-1990), projected annual runoff in future periods (2046-2065 and 2081-2100) would decreased by 9.5% and 3% in the Yangtze River Delta region. While annual runoff in the upper Yellow River basin during future two periods would decrease by 16.9% and 22.2%. The results are of great significance to future water resources management and sustainable development under climate change in major river basins of China. [ABSTRACT FROM AUTHOR]

In cold regions, the occurrence of frozen ground has a fundamental control over the character of the water cycle. To investigate the impact of changing ground temperature conditions on hydrological processes in the context of climate change, a distributed hydrological model with an explicit frozen ground module was applied to an alpine watershed in the upstream area of the Hei'he River in the Qilian Mountains, northwest China. After evaluating the base model, we considered scenarios of frost-free ground and climate change. Results showed that the base model with a frozen ground module successfully captured the water balance and thermal regimes in the basin. When the frozen ground module was turned off, the simulated groundwater recharge and base flow increased by a factor of two to three because surface runoff caused by exceeding infiltration capacities at high elevations, which occurred in the base model, was eliminated. Consequently, the river hydrograph became smoother and flatter, with summer flood peaks delayed and reduced in volume. The annual mean depth where subsurface runoff was generated, was about 2.4 m compared to 1.1 m in the base model. For a warming climate, a combination of increasing evapotranspiration and reducing permafrost area results in smoother and flatter hydrographs, and a reduction in total river discharge. Although our analysis using numerical models has its limitations, it still provides new quantitative understanding of the influences of frozen ground and climate change on hydrological processes in an alpine watershed. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

• A new hydrological-water quality model for humid and semi-humid catchments in China is presented. • Both horizontal and vertical heterogeneity are considered in the hydrological process and the water quality process modelling. • Model uncertainty and the sensitivity of model parameters are investigated. Non-point source (NPS) pollutants may cause water quality deterioration and eutrophication, posing a significant threat to aquatic systems. Understanding and modelling surface and sub-surface hydrological processes and nutrient cycles are therefore essential for water resources management and pollution control. This paper presents a new hydrological-water quality model for application in humid and semi-humid catchments in China, considering both hydrological processes, and nutrient transport and transformation. The model divides the soil into three layers, and each layer is implemented with individual computational procedures for soil wetness and nutrient process. Nutrient transport is driven by hydrological processes and follows the same pathways as water flow in the model: surface runoff, infiltration, and outflow from individual soil layers. River channels are described separately with routines to account for the turnover of nutrients. Model parameters are selected according to literature/open-sourced data or estimated from soil texture or land use types. The model is applied to simulate the hydrological processes and phosphorus transport in the Tongyang River Basin in China and the model performance is confirmed by comparing the predicted discharge and total phosphorus concentrations with measured data at the catchment outlets of Tonghe River and Yanghe River over 3 years. Uncertainty analysis has been further carried out using the GLUE method to demonstrate sensitivity of the simulation results to the selection of model parameters. After model calibration, the predicted results are found to compare well with field observations in terms of flow discharge and total phosphorus concentration. From sensitivity analysis, it is found that the recession coefficient of channel system (CS) and the pollutant recession coefficient of surface runoff (p KS) are the most influential hydrological and water quality parameters that control the arrival time and duration of flood peak and nutrient concentration peak, respectively. [ABSTRACT FROM AUTHOR]

• An assimilation scheme with error estimation on a distributed model is developed. • MAP provides effective error parameter estimation for EnKF of a distributed model. • Tests under different forcing show its potential to overcome poor rainfall forcing. • Tests in catchments with different features show mixed results. For flood simulation in small- and medium-sized catchments, discharge observations may be used to update model states of a distributed hydrological model to improve performance. The ensemble Kalman filter (EnKF) has been widely used for hydrological assimilation due to its relative simplicity and robustness. An advantage of the EnKF is that it is easy to include different sources of uncertainty, therefore the choice of error model is crucial for the application of the EnKF assimilation. This paper describes an EnKF assimilation scheme for estimating error models using the maximum a posteriori estimation method (MAP). We test this scheme in two small and medium-sized catchments in China with different characteristics, and in addition compared the performance differences under two kinds of rainfall forcing. We show that MAP is beneficial in specifying error models and providing reliable ensemble spread. The assimilation scheme can effectively ameliorate the degradation of distributed hydrological model performance due to uncalibrated model parameters and/or poor quality of input data. [ABSTRACT FROM AUTHOR]

Summary Flash flooding is one of the most common natural hazards in China, particularly in mountainous areas, and usually causes heavy damage and casualties. However, the forecasting of flash flooding in mountainous regions remains challenging because of the short response time and limited monitoring capacity. This paper aims to establish a strategy for flash flood warnings in mountainous ungauged catchments across humid, semi-humid and semi-arid regions of China. First, we implement a geomorphology-based hydrological model (GBHM) in four mountainous catchments with drainage areas that ranges from 493 to 1601 km 2 . The results show that the GBHM can simulate flash floods appropriately in these four study catchments. We propose a method to determine the rainfall threshold for flood warning by using frequency analysis and binary classification based on long-term GBHM simulations that are forced by historical rainfall data to create a practically easy and straightforward approach for flash flood forecasting in ungauged mountainous catchments with drainage areas from tens to hundreds of square kilometers. The results show that the rainfall threshold value decreases significantly with increasing antecedent soil moisture in humid regions, while this value decreases slightly with increasing soil moisture in semi-humid and semi-arid regions. We also find that accumulative rainfall over a certain time span (or rainfall over a long time span) is an appropriate threshold for flash flood warnings in humid regions because the runoff is dominated by excess saturation. However, the rainfall intensity (or rainfall over a short time span) is more suitable in semi-humid and semi-arid regions because excess infiltration dominates the runoff in these regions. We conduct a comprehensive evaluation of the rainfall threshold and find that the proposed method produces reasonably accurate flash flood warnings in the study catchments. An evaluation of the performance at uncalibrated interior points in the four gauged catchments provides results that are indicative of the expected performance at ungauged locations. We also find that insufficient historical data lengths (13 years with a 5-year flood return period in this study) may introduce uncertainty in the estimation of the flood/rainfall threshold because of the small number of flood events that are used in binary classification. A data sample that contains enough flood events (10 events suggested in the present study) that exceed the threshold value is necessary to obtain acceptable results from binary classification. [ABSTRACT FROM AUTHOR]

Drought assessment is important for developing measures to reduce agricultural vulnerability and thereby secure the livelihoods of those who depend on agriculture. This study uses four global ensemble weather prediction systems: the China Meteorological Administration (CMA), the European Centre for Medium-Range Weather Forecasts (ECMWF), the UK Met Office (UKMO), and the US National Centres for Environmental Prediction (NCEP) in the THORPEX (The Observing System Research and Predictability Experiment) Interactive Grand Global Ensemble (TIGGE) archive from 2006 to 2010. Based on results from the XXT (the first X denotes Xinanjiang, the second X denotes hybrid, and the T denotes TOPMODEL) distributed hydrological model, as well as soil moisture observations and digital elevation model (DEM) data, synthesized drought grades were established in the Huaihe River Basin of China. To filter out the impact of short-term fluctuations on observed soil moisture, a 30-day moving average was calculated. Use of the moving average significantly improves the correlation between observed soil moisture and simulated soil water deficit depth. Finally, a linear regression model describing the relationship between observed soil moisture and simulated soil water deficit depth was constructed. The deterministic regression coefficient was 0.5872, the correlation coefficient was 0.77, and the regression coefficient was − 154.23. The trends in drought grades calculated using soil moisture and soil water deficit depth were found to be the same, and the grades agreed to within one level. Our findings highlight the importance of synthesizing drought grading when assessing drought using different soil moisture indicators in order to obtain a more comprehensive forecast of drought conditions. [ABSTRACT FROM AUTHOR]

Climate variability and human activity are the two driving forces that alter the hydrological cycle and spatiotemporal distribution of water resources. Using the Taoer River Basin (TRB) as an example, this study analyzed the impacts of climate variability and human activities on streamflow discharge in various periods and the resulting hydrological alterations. First, historical streamflow data were divided into four periods (baseline period and altered periods 1, 2, and 3). Based on the proposed basic identification framework, four assessment methods (the hydrological sensitivity method, distributed hydrological model, linear regression model, and runoff restoring computation) are used and provided relatively consistent estimates of streamflow attribution. Climate variability is the driving factor for streamflow changes, and the relative contributions in altered periods 1, 2, and 3 are 81% (+ 50.34 mm), 68% (+ 13.37 mm), and 53% (-19.23 mm), respectively. In addition, climate variability and reservoir construction have different impacts on the hydrological regime at different periods, and reservoir regulation's effect on the hydrological regime depends on climatic conditions. Combined with this case study, we further discuss the necessity of breakpoint selection and period subdivision in the attribution of streamflow changes, and analyze the applicability of different methods with current ideas for improvement. This study not only has practical significance for water resource planning and adaptive policy formulation in the TRB but also provides a useful reference for similar studies., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

By using the Variable Infiltration Capacity model with Palmer Drought Severity Index (VIC-PDSI) model and Standardized Precipitation Index (SPI), spatiotemporal trends of climate variation during the main growing seasons for plants of Loess Plateau between 1971 and 2010 were detected and characterized. The VIC-PDSI model is established by combining the VIC model with PDSI. The simulation results and the grids system of VIC were applied to substitute for the two-layer bucket-type model to do the hydrological accounting, which could improve the physical mechanism of PDSI and expand its application range. Our results suggest that the climate of the study area has experienced a drying and warming trend during the past four decades. Apart from some individual years and regions, there was a perpetuation of water deficit over the Plateau both in spring and summer. The drought frequency increased from southeast to northwest in spring, while the drought frequency decreased from southeast to northwest in summer. The climate in the southern part of the Loess Plateau, accounting for 23.3% of the study region, showed a significant drying and warming trend in spring over the past four decades. The climate variability detected by VIC-PDSI model shows good agreement with that monitored by SPI. Since a large part of the study region frequently suffered from water shortage during the main growing seasons for plants, people living in such drought-prone areas should take measures to prevent the negative effects on agricultural production, reforestation, and regional food security caused by drought. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The generality of the Christiansen model is verified using potential evaporation data as reference for the unit model developed in stella. The spatial model in SME is calibrated with data from six hydrological and meteorological stations around the study area. The results show that the observed and simulated data have a good fit, in which the revised Nash-Sutcliffe efficiency (NSE), balance error ( B), and explained variance (EV) are 0.56, −0.2, and 0.55, respectively. The best fit is seen in autumn and winter; for spring, the actual values are generally higher than in simulated observations. The spatial model can simulate the majority of summer peaks, but some are not simulated well. Running the model under different spatial resolutions shows a certain degree of stability, with the revised NSE ranging from 0.29 to 0.50. As spatial resolution increases, the simulation NSE values behave non-linearly. With the other parameters unchanged the impact of human activities, which is represented by climate change scenarios on the hydrological process, is analyzed. Assuming constant temperature, precipitation has a greater influence on runoff than on evaporation; while when precipitation is constant, evaporation is influenced more by temperature. Although the model can validate the effect of climate change on runoff and evapotranspiration, it is not enough to describe the complex relationship between runoff, evaporation, temperature, and precipitation accurately, because the description of the water cycle process is simplified compared with a highly specialized hydrological model. The water and heat coupling process is not included in the soil freezing and thawing process; the source code of SME needs to be deeply understood to improve the algorithms of interpolation and conflux. More importantly, the current work does not consider the impact of human activities endogenously. The main purpose of this paper is to build a better basis for developing a meaningful integrated ecological economic model in the Heihe River Basin to solve its ecological and economic problems. [ABSTRACT FROM AUTHOR]

A shortage of water has limited the socio-economic development of the Heihe River Basin in northwestern China and has led to many ecological and economic problems. Only the development and application of integration tools can effectively represent the functionality of the watershed and aid in strategic decision making. In the framework of SME, modular and hierarchical model building can simplify the research work. According to the main ideas and key processes commonly used in distributed hydrological models, and combined with the spatial characteristics of the mountainous region of the Heihe River Basin, a unit hydrological model was developed using stella, which was an icon-based software package specifically designed for dynamic systems modeling, and an algorithm for spatial distribution in SME was introduced. This paper describes only the model structure and basic equations, whereas in the next paper, model calibration results using the data measured at meteorological stations, together with land use data and soil data, will be further introduced. [ABSTRACT FROM AUTHOR]

Abstract: In this study, we analyzed the drought variation trends in six subregions of the Loess Plateau over the past four decades. To do this, we used a new method wherein we combined the Variable Infiltration Capacity (VIC) Model for simulating watershed hydrological processes and Palmer Drought Severity Index (PDSI) for drought assessment and analysis. A new classified calibration procedure of climate characteristic coefficient, K j , was introduced in the study to improve the traditional PDSI computation method. The results suggest that the total area affected by drought in subregions 1–3 located in the middle reaches of the Yellow River mainly exhibited downward trends during 1971–2010. As these domains are the principal sediment sources of the Yellow River, the decreasing trends in drought area could benefit to vegetation recover in these regions, which are key sites of “Grain for Green” project, and help to control the severe soil and water losses. However, subregions 4–6 located in the upper reaches of the Yellow River primarily experienced upward trends in the total drought area. These subregions are the main grain producing areas of the study region, and the increase in drought area may cause damage to agricultural production and regional food security. The spatial distribution of drought frequency increased from southeast to northwest on the Loess Plateau. Most areas of the subregions 4–6 of the plateau exhibited an upward trend in drought frequency as indicated by a Mann–Kendall test, and the upward trend will show persistent behavior in the future, according to a Hurst exponent analysis. Generally speaking, the drought hazard in the upper reaches of the Yellow River tended to be increasingly severe, while drought hazard in the middle reaches has relieved to certain extent over the past four decades. [Copyright &y& Elsevier]

Summary: Spatial rainfall is a key input to distributed hydrological models, and its precisions heavily affect the accuracy of stream flow predictions from a hydrological model. Traditional interpolation techniques which obtain the spatial rainfall distribution from rain gauge data have some limitations caused by data scarcity and bad quality, especially in developing countries or remote locations. Satellite-based precipitation products are expected to offer an alternative to ground-based rainfall estimates in the present and the foreseeable future. For this purpose, the quality and usefulness of satellite-based precipitation products need to be evaluated. The present study compares the difference of Tropical Rainfall Measuring Mission (TRMM) rainfall with rain gauges data at different time scales and evaluates the usefulness of the TRMM rainfall for hydrological processes simulation and water balance analysis at the Xinjiang catchment, located in the lower reaches of the Yangtze River in China. The results show at daily time step TRMM rainfall data are better at determining rain occurrence and mean values than at determining the rainfall extremes, and larger difference exists for the maximal daily and maximal 5-day rainfalls. At monthly time scale, good linear relationships between TRMM rainfall and rain gauges rainfall data are received with the determination coefficients (R 2) varying between 0.81 and 0.89 for the individual stations and 0.88 for areal average rainfall data, respectively. But the slope of regression line ranges between 0.74 for Yingtan and 0.94 for Yushan, indicating that the TRMM satellite is inclined to underestimate the monthly rainfall in this area. The simulation of daily hydrological processes shows that the Water Flow Model for Lake Catchment (WATLAC) model using conventional rain gauge data produces an overall good fit, but the simulation results using TRMM rainfall data are discontented. The evaluation results imply that the TRMM rainfall data are unsuited for daily stream flow simulation in this study area with desired precisions. However, good performance can be received using TRMM rainfall data for monthly stream flow simulations. The comparison of the simulated annual water balance components shows that the different rainfall data sources can change the volume value and proportion of water balance components to some extent, but it generally meets the need of practical use. [Copyright &y& Elsevier]

Abstract: Restricted computing power has become one of the primary factors obstructing advancement in basin simulations for majority of hydrological models. Parallel computing is one of the most available approaches to solve this problem. Using binary-tree theory, we present in this study a common parallel computing framework based on the message passing interface (MPI) protocol for modeling hydrological processes of river basins. A practical and dynamic spatial domain decomposition method, based on the binary-tree structure of the drainage network, is proposed. This framework is computationally efficient, and is independent of the type of physical models chosen. The framework is tested in the Chabagou river basin of China, where two years of runoff processes of the entire basin were simulated. Results demonstrate that the system may provide efficient computing performance. However, primarily because of the constraint of the binary-tree structure for drainage network, this study finds that unlimited enhancement of computing efficiency is impossible to realize. [Copyright &y& Elsevier]

The hydrological processes are controlled by many factors such as topography, soil, climate and land management practices. These factors have been included in most hydrological models. This study develops a raster-based distributed hydrological model for catchment runoff simulation integrating flood polders regulation. The overland flow and channel flow are calculated by kinematic wave equations. A simple bucket method is used for outflow estimation of polders. The model was applied to Xitiaoxi catchment of Taihu Lake Basin. The accuracy of the model was satisfactory with Nash-Sutcliffe efficiencies of 0.82 during calibration period and 0.85 for validation at Hengtangcun station. The results at Fanjiacun station are slightly worse due to the tidal influence of Taihu Lake with high values of root mean square errors. A model sensitivity analysis has shown that the ratio of potential evapotranspiration to pan evaporation (K), the outflow coefficients of the freewater storage to groundwater (KG) and interflow (KSS) and the areal mean tension water capacity (WM) were the most sensitive parameters. The simulation results indicate that the polder systems could reduce the flood peaks. Additionally, it was confirmed that the proposed polders operation method improved the accuracy of discharge simulation slightly. [ABSTRACT FROM AUTHOR]

Summary: Miyun Reservoir is the main raw water source for Beijing’s domestic water supply. Flow discharge to Miyun Reservoir decreased drastically over a 50-year period, from 1956 to 2005, and had seriously affected Beijing’s water supply. Climate variability and human activity had been identified as the two main reasons for the decrease in flow. Here, climate variability refers to changes in precipitation and temperature. Impact of human activity includes direct withdrawal of water (referred to as “direct abstraction” in this paper) from the river (primary) or groundwater and indirect impact due to man-made changes in land use and vegetation in the upstream of the reservoir. According to the historical record, “direct abstraction” from the upstream of the reservoir has increased significantly since 1984. The study period was split into two sub-periods, from 1956 to 1983 and from 1984 to 2005. Based on the historical record, annual runoff in the upstream catchment of Miyun Reservoir (i.e., inflow into the reservoir) had decreased from 90.3mm to 41.8mm for the two sub-periods, a decrease of 48.5mm. Over the same period, average annual “direct abstraction” increased from 2.2mm to 13.4mm, an increase of 11.2mm. The latter accounted for 23% (11.2mm/48.5mm) of the decrease in inflow into the reservoir. This study utilised: (1) a distributed hydrological model (geomorphology-based hydrological model, or GBHM) and (2) a climate elasticity model to conduct a quantitative assessment of the impact of climate variability and the indirect impact of human activity on the inflow into the reservoir. Simulation results of GBHM and the climate elasticity model showed that climate impact was accountable for about 55% and 51% of the decrease in reservoir inflow, respectively. The indirect impact of human activity (mainly man-made land use and vegetation changes) accounted for 18% of the decrease in reservoir inflow. [Copyright &y& Elsevier]

An integrated modeling system has been developed for water resources management of the Tarim River Basin, China. The system coupled remote sensing (RS)/geography information system (GIS) technique with distributed hydrological model to simulate the rainfall runoff, snow melting, and evapotranspiration process of the hydrological cycle. A case study was carried out in the Kaidu watershed. RS/GIS technique was used for effectively accessing, processing, and managing spatial data, such as land use, vegetative cover, soil, topography, precipitation, and evapotranspiration. The model was calibrated and validated against observed discharge for two hydrological stations during the period 1998–2001, and it generally performed well for Nash-Sutcliffe coefficient, water balance coefficient, and correlation coefficient. The Nash-Sutcliffe coefficient was approximately over 0.7 and the water balance error was lower than ± 5%, indicating reasonable prediction accuracy. A comparison between the conventional and RS-based hydrological models was conducted. Although the two models exhibit similar performances on runoff and snow melt simulation, the RS-based hydrological model had better performance in the simulation of actual evapotranspiration. Modeling results provide useful decision support for water resources management. [ABSTRACT FROM AUTHOR]

The article discusses a study which examines a physical based distributed-parameter model combining surface runoff and ground water flow. A proposed watershed model for the simulations of extreme flood events and long-term periods that occurred in the Shihmen reservoir watershed in China from 1986 to 2001 was used to identify physics-based multiple processes occurring in watershed, including evaporation, infiltration, percolation, surface runoff and ground water flow. The study revealed that the proposed model exhibited a favorable potential for storm based simulations, recession period modelling, and long-term simulations.

Abstract: An integrated model is established to simulate both hydrological processes and accompanied pollutant transfer processes in the Yellow River Basin. The model couples distributed hydrological model WEP-L (Water and Energy transfer Processes in Large river basins) and a newly developed water quality module which includes simulation functions of soil erosion and sediment transport, and non-point and point sources transfer to rivers. To overcome the defects of traditional water quality assessment, two aspects of improvement are conducted. One is the improvement of the traditional characteristic channel length approach, i.e., the product of multiplying channel length by lateral section area is selected as a new assessment criterion to reflect the different contributions of small channels and big ones, thus making the assessment results more objective. The other is the suggestion of integrated assessment approach for both water at channel lateral sections and water generated in sub-basins. The assessment results in the Yellow River Basin illustrate: (1) the improved characteristic channel length approach shows rivers of water quality worse than Class III account for 75% whilst the traditional approach give a result of 45%, implying that the actual status of water quality is worse than the traditional understanding; (2) the quality of water generated in sub-basins is much better than the quality of water at channel lateral sections. The assessment results describe the status of water resources quantity and quality from different points of view and thus provide valuable information for the water resources development and management in the basin. [Copyright &y& Elsevier]

Summary: Dynamic assessment of water resources becomes desirable to reflect water resources variations in the basins under strong human impacts. A physically based distributed hydrological model, WEP-L, which couples simulations of natural hydrological processes and water use processes, is developed for the purpose. Concepts of special water resources (i.e., surface water resources and groundwater resources) and general water resources (i.e., the special water resources plus the precipitation directly utilized by ecosystem) are proposed, and an approach for dynamic assessment of water resources is suggested. Basin subdivision, classification of land covers, and deduction of water use spatial/temporal distributions in the Yellow River basin are carried out with the aid of remote sensing (RS) data and geographic information system (GIS) techniques. The basin is subdivided into 8485 sub-watersheds and 38,720 contour bands, and the WEP-L model is verified by comparing simulated and observed discharges at main gage stations. Lastly, continuous simulations of 45 years (1956–2000) in variable time steps (from 1h to 1 day) are performed for various land cover and water use conditions, and water resources assessment results under present condition of land cover and water use are compared with those under historical condition of land cover and water use. The study results reveal that: (1) the surface water resources reduced, but the groundwater resources non-overlapped with the surface water resources increased under the impact of human activities in the Yellow River basin; and (2) the special water resources reduced, but the general water resources increased accompanied with increase of the precipitation directly utilized by ecosystem in the basin. [Copyright &y& Elsevier]

The lumped hydrological model and empirical model have the problems of low accuracy and short forecasting period in real-time flood forecasting of small- and medium-sized rivers in a mountainous watershed. The sharing of underlying surface data such as high-resolution DEM, land use data, soil data, and the popularization and application of the Internet of Things, big data, cloud computing, and intelligent calculation methods makes distributed hydrological model an effective method for real-time runoff simulation and prediction. The topographic, kinematic, approximation, and integration (TOPKAPI) model is a distributed hydrological model whose physical mechanism developed gradually in the late 20th century. It has great advantages in real-time flood forecasting in small- and medium-sized watersheds. Based on the data required by the TOPKAPI model, in this study, 26 selected flood events were simulated from 2000 to 2013 at the outlet section of the upper reach of the Zhenjiang River in Guangdong Province, and the effect of application of the model in flood forecasting of small- and medium-sized rivers was evaluated. The results show that the pass rate (considering the peak discharge as the evaluation item) of 18 flood events in the calibration period was 66.67%, and that of 8 flood events in the validation period was 75%, while the mean Nash efficiency coefficient of the selected 26 flood events was 0.789. According to the simulation results, real-time flood forecasting should be closely combined with the dispatching of the small- and medium-sized reservoirs in the basin. The application of the TOPKAPI model can make a scientific and rapid analysis of the flood control situation in the whole basin and provide accurate information and maximum convenience for flood forecasting consultation and decision making. Additionally, it can improve the efficiency of disaster prevention and mitigation work in small- and medium-sized river basins, and has a major significance in enhancing the modernization level of flood forecasting. [ABSTRACT FROM AUTHOR]

• A probabilistic LSTM network is proposed to make uncertainty estimates in MIKE SHE. • Two common residual error models are defined as a benchmark comparison. • The probabilistic LSTM network has the best performance of probabilistic predictions. Errors in hydrological simulations have impacted their applications in flood prediction and water resources management. Properly characterizing the properties of errors such as heteroscedasticity and autocorrelation can provide improved hydrological predictions. Here, we present a probabilistic Long Short-Term Memory (LSTM) network for modeling hydrological residual errors. Three steps are undertaken to characterize uncertainty using the LSTM: (i) the network is trained with gradient optimization to obtain optimal predictions; (ii) the distribution of the errors for optimal predictions are estimated using a Bayesian Markov chain Monte Carlo (MCMC) algorithm; (iii) probabilistic predictions are made using the inferred error distribution and optimal predictions. We examine the model in the source of Yellow River, China over the period 1992–2015. A distributed hydrological model MIKE SHE is applied to simulate streamflows in the catchment. As benchmarks, we compare the results with a Bayesian linear regression model and a traditional probabilistic residual error model. Results show the probabilistic LSTM network reduces the heteroscedasticity and removes almost all autocorrelations in residual errors. Besides, compared with the other two methods, the proposed method produces more than 50% narrower uncertainty intervals with the best probability coverage. Our results highlight the potential ability of a deep learning approach integrated with a hydrological model to better characterize predictive uncertainty in hydrologic modeling. [ABSTRACT FROM AUTHOR]

A spatially distributed trace metal transport and transformation module was developed and implemented within the hydrological model TOPKAPI-ETH. The new module can be used to better understand, at high spatial and temporal resolution, the transport and reactions of trace metals as they move through a catchment from upland sources to downstream areas and water bodies. The newly developed module takes into consideration solid metal in multiple chemical phases with different reactivity and simulates their mutual transformation over time, which gives the possibility to analyze the fraction of different solid metal phases present in the river suspended sediment. The characteristics and potential of the model are demonstrated by simulating Zinc (Zn) and Cadmium (Cd) dynamics in a headwater catchment of the Xiang River in South China, which has been highly perturbed by mining activities. The developed module is shown to reasonably reproduce the observed dynamics of dissolved and total trace metals flux for 14 months at two monitoring stations. The distributed solute transport model was proved to be capable of explaining the reasons underlying the spatial variability of C-Q relationships that are driven by the combined effect of point and non-point pollution sources, as well as identifying the spatiotemporal hotspots of trace metal pollution. By means of synthetic numerical experiments, a limited impact of slow reactions on dissolved Cd transport from upland to river over short-temporal scales was demonstrated, while for longer scales, e.g. >5 years, this effect becomes more relevant, highlighting potential long-lasting sources of trace metal pollution and their impacts., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

The lack of ground-based observation data usually limits the analysis of extreme precipitation and streamflow, especially for the ungauged or data-limited regions. Satellite-based precipitation products (SPPs) with high temporal and spatial resolutions can provide potential data sources in the regions without adequate precipitation data, and it has received much attention of regional or global hydro-climatic analysis. This study aims to evaluate the accuracy of four widely used long time series SPPs (CHIRPS, TMPA, CMORPH and PERSIANN) in capturing extreme precipitation and streamflow events in a humid region of southern China. It is found that, for extreme precipitation detection, both CMORPH and TMPA can capture most heavy and extreme precipitation, CMORPH works better on the rainfall distribution characteristics, while TMPA shows the best performance in capturing the extreme precipitation events with relatively low RMSE, ME and BIAS, and high R values of extreme precipitation indices. For the streamflow simulation, the combinations of different inputs and different models present different model performances. TMPA provides the most accurate hydrological model simulation results, while simulated streamflow forced by CMORPH exhibits considerable underestimation of streamflow. However, the combination of CMORPH and VIC model obtains the best efficiency for detecting extreme streamflow, followed by the combination of TMPA and SWAT model, which indicates the selection of a suitable model and input data is essential to obtain reliable and accurate results for the detection of extreme streamflow. This study is expected to provide a valuable reference for the application and comparison of multiple SPPs and models at watershed scales. • The four long-term series SPPs are evaluated in the detection of extreme precipitation and streamflow events. • TMPA is the best in capturing precipitation extremes, while CMORPH is better in detecting streamflow extremes. • The combination of CMORPH and VIC model obtains the best efficiency for detecting streamflow extremes. • The choice of hydrological model will affect the accuracy assessment of SPPs for detecting streamflow extremes. [ABSTRACT FROM AUTHOR]

• Dimension-adaptive key grid strategy improves the simulation performance. • Spatial distributions of parameters can be identified by the proposed strategy. • Runoff and evaporation products helps to reduce the uncertainty of the parameters. Distributed hydrological models have been developed to describe temporal and spatial variations. However, it is difficult to calibrate the spatially heterogeneous parameters because of dimensional issues and spatial uncertainty. This study aims to propose a dimension-adaptive key grid (DAKG) calibration strategy to identify spatial parameters of distributed hydrological models. The method uses sensitivity analyses to find important model parameters, and significantly fewer grid points are then selected as representative grids to reduce the dimensionality of parameters. Apart from the observed outlet streamflow, grid actual evaporation, and grid runoff are used for the multi-objective calibration framework. The Xiangjiang basin, the Yuanjiang basin, and the source region of the Yellow River in China are used as case studies, where the Variable Infiltration Capacity (VIC) land surface models have been calibrated. The results indicate that: (1) The proposed DAKG calibration strategy improves performance in terms of accuracy and model complexity for hydrological simulation. (2) The spatial distributions of the shape parameter B and the thickness of the second soil layer Depth2 are easy to be identified, where the spatial distribution of Depth2 is the most positively correlated with that of elevation. (3) The fusion of the runoff and evaporation products helps to reduce the uncertainty of the distributed parameters. Overall, the DAKG calibration strategy is an effective technique for parameter identification in distributed hydrological models. [ABSTRACT FROM AUTHOR]

Based on the bibliometric and data visualization analysis software Citespace, this study carried out document statistics and information mining on the Web of Science database and characterized the distributed hydrological model knowledge system from 1986 to 2019. The results show a few things: (1) from 1986 to 2019, the United States and China accounted for 41% of the total amount of publications, and they were the main force in the field of distributed hydrological model research; (2) field research involves multiple disciplines, mainly covering water resources, geology, earth sciences, environmental sciences, ecology and engineering; (3) the frontier of field research has shifted from using distributed hydrological models in order to simulate runoff and nonpoint source environmental responses to the coupling of technologies and products that can obtain high-precision, high-resolution data with distributed hydrological models. (4) Affected by climate warming, the melting of glaciers has accelerated, and the spatial distribution of permafrost and water resources have changed, which has caused a non-negligible impact on the hydrological process. Therefore, the development of distributed hydrological models suitable for alpine regions and the response of hydrological processes to climate change have also become important research directions at present. [ABSTRACT FROM AUTHOR]

The impacts of human activity lead to uncertainty and ambiguity when ecological water requirements (EWRs) are calculated based entirely on the current hydrological conditions of urban rivers, and the requirements for meeting the rivers' function will also be uncertain. Human activity and river function goals are important factors affecting EWRs. This paper discusses the definition of urban river EWRs and the uncertainties in the results of the calculation, and proposes a calculation method for urban river EWRs that is independent of human activity. The Beiyun River Basin, China, was selected for a case study. The EWRs of the Beiyun River were calculated by combining a precipitation frequency curve with a distributed hydrological model. The rationality of the calculated results was verified using the Tennant method and an evaporation plus seepage calculation for the river. The results of the calculation for the urban river EWRs method proposed in this paper are unique, and the total amount is not affected by human activities. With respect to wet, normal, and dry precipitation frequencies, the minimum, suitable, and ideal EWRs of the Beiyun River are 1.48 × 108 m3, 2.79 × 108 m3, and 3.57 × 108 m3, respectively. The research conclusions are of great significance for the objective determination of the EWRs of urban rivers, and for promoting the appropriate planning and development of urban water. [ABSTRACT FROM AUTHOR]

Precipitation observation and prediction is difficult in many high elevation regions due to the complex terrain and the lack of in situ observations for comparison. The Nujiang River (upper and middle Salween River) basin in the Tibetan Plateau is no exception. Because of this shortcoming, we propose the use of gauge-observed discharge time series at the basin outlet (e.g., Jiayuqiao hydrological station) to evaluate the performance of four different precipitation products (e.g., satellite-based products and reanalysis datasets). A physically-based distributed cryosphere hydrological model with coupled snow and frozen soil physics was adopted to transfer the basin-wide gridded precipitation into the basin-outlet discharges. First, we corrected and evaluated the four precipitation products. A correlation relationship was established between each precipitation product and the available (limited) gauge rainfall within different elevation zones, and then used to correct the four precipitation products in the study basin. Secondly, a distributed cryosphere hydrological model was used to simulate the basin-outlet runoff driven by each corrected precipitation product. The results indicated that modern-era retrospective analysis for Research and Applications, version 2 (MERRA2) precipitation has better performance in the upper Nujiang River basin relative to the other precipitation products based on comparisons of observed and simulated runoff. [ABSTRACT FROM AUTHOR]

Hydrological modelling is a critical tool for preventing and mitigating severe flood disasters. This study aims to assess the applicability of a physically based distributed hydrological model, CASCade Two Dimensional SEDiment (CASC2D‐SED), for flood forecasting in four typical medium and small watersheds across three hydroclimatic zones (semi‐arid, semihumid, and humid) in China. CASC2D‐SED model has the best performance in Xianbeigou (semi‐arid), followed by Luanchuan (semihumid), and Shujia (humid), while has the relatively lowest performance in Chengcun (humid). It tends to underestimate a large portion of the discharges in the watersheds, indicating that the Green‐Ampt infiltration‐excess model, the only runoff generation scheme in CASC2D‐SED model, imposes restrictions on hydrological simulation without further accounting for subsurface and groundwater flows. This limitation is particularly obvious in the semihumid and humid regions. Our analysis suggests that combining infiltration‐excess and saturation‐excess runoff generation mechanisms and accounting for subsurface and groundwater flows in CASC2D‐SED will further enhance its capacity for flood forecasting and hydrological simulation for semihumid and humid hydroclimatic zones. [ABSTRACT FROM AUTHOR]

Slope ecological restoration and climate change are important factors affecting the hydrological processes of the Huangshui River Basin in Qinghai province, China. How to quantitatively identify the impact of slope ecological restoration on runoff and whether slope ecological restoration can mitigate the impact of future climate change on runoff are both very important. In this paper, the Huangshui River above the center of Minhe county was taken as the research area, and the Pinus tabulaeformis and shrubs were taken as the main forest land types of slope ecological restoration. First, based on the law of forest land variation, the construction scales of slope ecological restoration in different periods were identified. The influence of slope ecological restoration on runoff was then quantitatively evaluated by using a distributed hydrological model. Second, the future climate scenarios of five general circulation models (GCMs) under three representative concentration pathways (RCPs) (i.e., RCP2.6, RCP4.5, and RCP8.5) from 2021 to 2050 were selected and modified by model integration. Combined with the slope ecological restoration scenarios, the influence of slope ecological restoration on runoff under future climate scenarios was explored. The results showed that the effect of slope ecological restoration was significant. Compared with 1980, the area of slope ecological restoration increased by 24% in 2017. Under the present climate conditions (1960-2017), different periods of slope ecological restoration have an effect on the process of runoff in the wet season (June, July, August, and September) and dry season (January, February, March, and December), which eliminates the maximum, replenishes the minimum, and reduces the variability of runoff processes in the watershed. Under the future climate scenario (2021-50), slope ecological restoration will reduce runoff. On the other hand, climate change will increase runoff, and the combination of the two effects will have a certain offsetting effect. On the whole, comparing the influence of slope ecological restoration on the runoff process with that of climate change in different seasons, due to the main influence of slope ecological restoration, the runoff decreased by about 55% in the temperate season (April, May, October, and November), and increased by about 50% in the dry season or wet season due to the main influence of future climate scenarios.

Predictions in ungauged basins (PUB) has been always a focus of hydrological research. The problem presented by ungauged basins is how to reasonably estimate water resource availability. To solve the issues of data scale, this study combines field experiments and hydrological models to estimate freshwater availability in a typical ungauged sea island located in southeastern China. The free parameters in the hydrological model were derived from the point-scale rainfall-runoff experiments rather than calibration using river discharge observations. The rainfall-runoff experiments were performed on six sites covering 11 land cover types. Model validation at a sub-catchment showed that the combined method could successfully reproduce monthly streamflow, with a Nash–Sutcliffe Efficiency of 0.82, correlation coefficient of 0.85, and flow volume error of 6.5%. The simulation results indicate high heterogeneity and distinct seasonal dynamics in freshwater availability across the entire island. This pioneering PUB study for Chinese islands could provide reference for planning and management of freshwater in a water shortage area. [ABSTRACT FROM AUTHOR]