Elucidating Dominant Factors Affecting Land Surface Hydrological Simulations of the Community Land Model over China

In order to compare the impacts of the choice of land surface model(LSM)parameterization schemes,meteorological forcing,and land surface parameters on land surface hydrological simulations,and explore to what extent the quality can be improved,a series of experiments with different LSMs,forcing datasets,and parameter datasets concerning soil texture and land cover were conducted.Six simulations are run for the Chinese mainland on 0.1°×0.1°grids from 1979 to 2008,and the simulated monthly soil moisture(SM),evapotranspiration(ET),and snow depth(SD)are then compared and assessed against observations.The results show that the meteorological forcing is the most important factor governing output.Beyond that,SM seems to be also very sensitive to soil texture information;SD is also very sensitive to snow parameterization scheme in the LSM.The Community Land Model version 4.5(CLM4.5),driven by newly developed observation-based regional meteorological forcing and land surface parameters(referred to as CMFD_CLM4.5_NEW),significantly improved the simulations in most cases over the Chinese mainland and its eight basins.It increased the correlation coefficient values from 0.46 to 0.54 for the SM modeling and from 0.54 to 0.67 for the SD simulations,and it decreased the root-mean-square error(RMSE)from 0.093 to 0.085 for the SM simulation and reduced the normalized RMSE from 1.277 to 0.201 for the SD simulations.This study indicates that the offline LSM simulation using a refined LSM driven by newly developed observation-based regional meteorological forcing and land surface parameters can better model reginal land surface hydrological processes.

Mixed D-vine copula-based conditional quantile model for stochastic monthly streamflow simulation

Copula functions have been widely used in stochastic simulation and prediction of streamflow.However,existing models are usually limited to single two-dimensional or three-dimensional copulas with the same bivariate block for all months.To address this limitation,this study developed a mixed D-vine copula-based conditional quantile model that can capture temporal correlations.This model can generate streamflow by selecting different historical streamflow variables as the conditions for different months and by exploiting the conditional quantile functions of streamflows in different months with mixed D-vine copulas.The up-to-down sequential method,which couples the maximum weight approach with the Akaike information criteria and the maximum likelihood approach,was used to determine the structures of multivariate Dvine copulas.The developed model was used in a case study to synthesize the monthly streamflow at the Tangnaihai hydrological station,the inflow control station of the Longyangxia Reservoir in the Yellow River Basin.The results showed that the developed model outperformed the commonly used bivariate copula model in terms of the performance in simulating the seasonality and interannual variability of streamflow.This model provides useful information for water-related natural hazard risk assessment and integrated water resources management and utilization.

Hydrological Simulation Using TRMM and CHIRPS Precipitation Estimates in the Lower Lancang-Mekong River Basin

Satellite-based products with high spatial and temporal resolution provide useful precipitation information for data-sparse or ungauged large-scale watersheds. In the Lower Lancang-Mekong River Basin, rainfall stations are sparse and unevenly distributed, and the transboundary characteristic makes the collection of precipitation data more difficult, which has restricted hydrological processes simulation. In this study, daily precipitation data from four datasets(gauge observations, inverse distance weighted(IDW) data, Tropical Rainfall Measuring Mission(TRMM) estimates, and Climate Hazards Group InfraRed Precipitation with Stations(CHIRPS) estimates), were applied to drive the Soil and Water Assessment Tool(SWAT) model, and then their capability for hydrological simulation in the Lower Lancang-Mekong River Basin were examined. TRMM and CHIRPS data showed good performances on precipitation estimation in the Lower Lancang-Mekong River Basin, with the better performance for TRMM product. The Nash-Sutcliffe efficiency(NSE) values of gauge, IDW, TRMM, and CHIRPS simulations during the calibration period were 0.87, 0.86, 0.95, and 0.93 for monthly flow, respectively, and those for daily flow were 0.75, 0.77, 0.86, and 0.84, respectively. TRMM and CHIRPS data were superior to rain gauge and IDW data for driving the hydrological model, and TRMM data produced the best simulation performance. Satellite-based precipitation estimates could be suitable data sources when simulating hydrological processes for large data-poor or ungauged watersheds, especially in international river basins for which precipitation observations are difficult to collect. CHIRPS data provide long precipitation time series from 1981 to near present and thus could be used as an alternative precipitation input for hydrological simulation, especially for the period without TRMM data. For satellite-based precipitation products, the differences in the occurrence frequencies and amounts of precipitation with different intensities would affect simulation results of water balance components, which should be comprehensively considered in water resources estimation and planning.

Hydrological simulation approaches for BMPs and LID practices in highly urbanized area and development of hydrological performance indicator system

Urbanization causes hydrological change and increases stormwater runoff volumes, leading to flooding, erosion, and the degradation of instream ecosystem health. Best management practices （BMPs）, like detention ponds and infiltration trenches, have been widely used to control flood runoff events for the past decade. However, low impact development （LID） options have been proposed as an alternative approach to better mimic the natural flow regime by using decentralized designs to control stormwater runoff at the source, rather than at a centralized location in the watershed. For highly urbanized areas, LID stormwater management practices such as bioretention cells and porous pavements can be used to retrofit existing infrastructure and reduce runoff volumes and peak flows. This paper describes a modeling approach to incorporate these LID practices and the two BMPs of detention ponds and infiltration trenches in an existing hydrological model to estimate the impacts of BMPs and LID practices on the surface runoff. The modeling approach has been used in a parking lot located in Lenexa, Kansas, USA, to predict hydrological performance of BMPs and LID practices. A performance indicator system including the flow duration curve, peak flow frequency exceedance curve, and runoff coefficient have been developed in an attempt to represent impacts of BMPs and LID practices on the entire spectrum of the runoff regime. Results demonstrate that use of these BMPs and LID practices leads to significant stormwater control for small rainfall events and less control for flood events.

Application of a Coupled Land Surface-Hydrological Model to Flood Simulation in the Huaihe River Basin of China

A hydrological simulation in the Huaihe River Basin(HRB) was investigated using two different models: a coupled land surface hydrological model(CLHMS), and a large-scale hydrological model(LSX-HMS). The NCEP-NCAR reanalysis dataset and observed precipitation data were used as meteorological inputs. The simulation results from both models were compared in terms of flood processes forecasting during high flow periods in the summers of 2003 and 2007, and partial high flow periods in 2000. The comparison results showed that the simulated streamflow by CLHMS model agreed well with the observations with Nash-Sutcliffe coefficients larger than 0.76, in both periods of 2000 at Lutaizi and Bengbu stations in the HRB, while the skill of the LSX-HMS model was relatively poor. The simulation results for the high flow periods in 2003 and 2007 suggested that the CLHMS model can simulate both the peak time and intensity of the hydrological processes, while the LSX-HMS model provides a delayed flood peak. These results demonstrated the importance of considering the coupling between the land surface and hydrological module in achieving better predictions for hydrological processes, and CLHMS was proven to be a promising model for future applications in flood simulation and forecasting.

Landslide forecasting based on hydrological process simulation for a dump slope in an open mining pit

There are concerns about the safety issues of dump slope in the open-cast mining pit because of the risk of catastrophic destruction caused by slope failures that are related to several factors, such as atmospheric conditions(especially precipitation), vegetation and some others. The aim of this study is to investigate the hydrological regime in a dump slope and the influence of the saturation degree on the stability of dump slopes with consideration of precipitation and vegetation using the program of PCSiWaPro~?. Based on the hydrological simulation conducted through PCSiWaPro~?, the calculation of the Factor of Safety(Fs) in the dump slope using Geo-slope Software was improved with further consideration of soil-water weight in the unsaturated dump slope and the influence of water content on the variation of soil property parameters(e.g. cohesion).

Adaptability of machine learning methods and hydrological models to discharge simulations in datasparse glaciated watersheds

The accurate simulation and prediction of runoff in alpine glaciated watersheds is of increasing importance for the comprehensive management and utilization of water resources.In this study,long shortterm memory(LSTM),a state-of-the-art artificial neural network algorithm,is applied to simulate the daily discharge of two data-sparse glaciated watersheds in the Tianshan Mountains in Central Asia.Two other classic machine learning methods,namely extreme gradient boosting(XGBoost)and support vector regression(SVR),along with a distributed hydrological model(Soil and Water Assessment Tool(SWAT)and an extended SWAT model(SWAT_Glacier)are also employed for comparison.This paper aims to provide an efficient and reliable method for simulating discharge in glaciated alpine regions that have insufficient observed meteorological data.The two typical basins in this study are the main tributaries(the Kumaric and Toxkan rivers)of the Aksu River in the south Tianshan Mountains,which are dominated by snow and glacier meltwater and precipitation.Our comparative analysis indicates that simulations from the LSTM shows the best agreement with the observations.The performance metrics Nash-Sutcliffe efficiency coefficient(NS)and correlation coefficient(R^(2))of LSTM are higher than 0.90 in both the training and testing periods in the Kumaric River Basin,and NS and R^(2) are also higher than 0.70 in the Toxkan River Basin.Compared to classic machine learning algorithms,LSTM shows significant advantages over most evaluating indices.XGBoost also has high NS value in the training period,but is prone to overfitting the discharge.Compared with the widely used hydrological models,LSTM has advantages in predicting accuracy,despite having fewer data inputs.Moreover,LSTM only requires meteorological data rather than physical characteristics of underlying data.As an extension of SWAT,the SWAT_Glacier model shows good adaptability in discharge simulation,outperforming the original SWAT model,but at the cost of increasing the complexity of the model.Compared with the oftentimes complex semi-distributed physical hydrological models,the LSTM method not only eliminates the tedious calibration process of hydrological parameters,but also significantly reduces the calculation time and costs.Overall,LSTM shows immense promise in dealing with scarce meteorological data in glaciated catchments.

Hydrological Model to Simulate Daily Flow in a Basin with the Help of a GIS

Hydrological modeling is an essential tool to evaluate water resources in hydrological basins. The time invested in it depends on the structure of the hydrological model chosen, the amount and quality of information required and the efforts invested in calibration. CEQUEAU is a distributed hydrological model developed at the INRS-ETE, Quebec, Canada. The basin is divided into cells and the rainfall-runoff process is simulated cell by cell until the outlet. Recent advances in geomatics make it possible to develop modules integrated in geographic information systems (GIS) to facilitate the processing of information required by hydrological models. The objective of the present investigation is to implement the CEQUEAU model in Idrisi GIS for the hydrological modeling of basins, thereby reducing information processing time and improving limitations in the original version, such as the number of discretization cells and methods to calculate evapotranspiration. This document presents the results from the implementation of the CEQUEAU model, including evapotranspiration, water levels (in reservoirs, soil and aquifers) and hydrographs. These results show that these new changes provide more hydrology options to the user and with better results.

Simulation and analysis of river runoff in typical cold regions

It is generally agreed that global warming is taking place, which has caused runoff generation processes and apparently total runoff amount changes in cold regions of Northwestern China. It is absolutely necessary to quantify and analyze earth surface hydrolog- ical processes by numerical models for formulating scientific sustainable development of water resources. Hydrological models became established tools for studying the hydrological cycle, but did not consider frozen soil or glacier hydrology. Thus, they should be improved to satisfy the simulation of hydrological processes in cold regions. In this paper, an energy balance glacier melt model was successfully coupled to the VIC model with frozen soil scheme, thus improving the models performance in a cold catchment area. We performed the improved VIC model to simulate the hydrological processes in the Aksu River Basin, and the simulated results are in good agreement with observed data. Based on modeling hydrological data, the runoff components and their response to climate change were analyzed. The results show： （1） Glacial meltwater recharge accounts fbr 29.2% of runoff for the Toxkan River, and 58.7% for the Kunma Like River. （2） The annual total runoffoftwo branches of the Aksu River show in- creasing trends, increased by about 43.1%, 25.75 X 106 m3 per year for the Toxkan River and by 13.1%, 14.09 ~ l06 m3 per year for the Kunma Like River during the latter 38 years. （3） The annual total runoff of the Toxkan River increased simply due to the increase of non-glacial runoff, while the increase of annual total runoff of the Kunma Like River was the result of increasing gla- cial （42%） and non-glacial runoff （58%）.

Discharge Simulation in a Data-Scarce Basin Using Reanalysis and Global Precipitation Data: A Case Study of the White Volta Basin

Basins in many parts of the world are ungauged or poorly gauged, and in some cases existing measurement networks are declining. The purpose of this study was to examine the utility of reanalysis and global precipitation datasets in the river discharge simulation for a data-scarce basin. The White Volta basin of Ghana which is one of international rivers was selected as a study basin. NCEP1, NCEP2, ERA-Interim, and GPCP datasets were compared with corresponding observed precipitation data. Annual variations were not reproduced in NCEP1, NCEP2, and ERA-Interim. However, GPCP data, which is based on satellite and observed data, had good seasonal accuracy and reproduced annual variations well. Moreover, five datasets were used as input data to a hydrologic model with HYMOD, which is a water balance model, and with WTM, which is a river model;thereafter, the hydrologic model was calibrated for each datum set by a global optimization method, and river discharge were simulated. The results were evaluated by the root mean square error, relative error, and water balance error. As a result, the combination of GPCP precipitation and ERA-Interim evaporation data was the best in terms of most evaluations. The relative errors in the calibration and validation periods were 43.1% and 46.6%, respectively. Moreover, the results for the GPCP precipitation and ERA-Interim evaporation were better than those for the combination of observed precipitation and ERA-Interim evaporation. In conclusion, GPCP precipitation data and ERA-Interim evaporation data are very useful in a data-scarce basin water balance analysis.

Application of hydrological models in a snowmelt region of Aksu River Basin

This study simulated and predicted the runoff of the Aksu River Basin, a typical river basin supplied by snowmelt in an arid mountain region, with a limited data set and few hydrological and meteorological stations. Two hydrological models, the snowmelt-runoff model （SRM） and the Danish NedbФr-AfstrФmnings rainfall-runoff model （NAM）, were used to simulate daily discharge processes in the Aksu River Basin. This study used the snow-covered area from MODIS remote sensing data as the SRM input. With the help of ArcGIS software, this study successfully derived the digital drainage network and elevation zones of the basin from digital elevation data. The simulation results showed that the SRM based on MODIS data was more accurate than NAM. This demonstrates that the application of remote sensing data to hydrological snowmelt models is a feasible and effective approach to runoff simulation and prediction in arid unguaged basins where snowmelt is a major runoff factor.

Hydrological assessment of TRMM rainfall data over Yangtze River Basin

High-quality rainfall information is critical for accurate simulation of runoff and water cycle processes on the land surface. In situ monitoring of rainfall has a very limited utility at the regional and global scale because of the high temporal and spatial variability of rainfall. As a step toward overcoming this problem, microwave remote sensing observations can be used to retrieve the temporal and spatial rainfall coverage because of their global availability and frequency of measurement. This paper addresses the question of whether remote sensing rainfall estimates over a catchment can be used for water balance computations in the distributed hydrological model. The TRMM 3B42V6 rainfall product was introduced into the hydrological cycle simulation of the Yangtze River Basin in South China. A tool was developed to interpolate the rain gauge observations at the same temporal and spatial resolution as the TRMM data and then evaluate the precision of TRMM 3B42V6 data from 1998 to 2006. It shows that the TRMM 3B42V6 rainfall product was reliable and had good precision in application to the Yangtze River Basin. The TRMM 3B42V6 data slightly overestimated rainfall during the wet season and underestimated rainfall during the dry season in the Yangtze River Basin. Results suggest that the TRMM 3B42V6 rainfall product can be used as an alternative data source for large-scale distributed hydrological models.

Hydrological Response to Climate and Land Use Changes in the Dry–Warm Valley of the Upper Yangtze River

The hydrological process in the dry–warm valley of the mountainous area of southwest China has unique characteristics and has attracted scientific attention worldwide.Given that this is an area with fragile ecosystems and intensive water resource conflicts in the upper reaches of the Yangtze River,a systematic identification of its hydrological responses to climate and land use variations needs to be performed.In this study,MIKE SHE was employed and calibrated for the Anning River Basin in the dry–warm valley.Subsequently,a deep learning neural network model of the long short-term memory(LSTM)and a traditional multi-model ensemble mean(MMEM)method were used for an ensemble of 31 global climate models(GCMs)for climate projection.The cellular automata–Markov model was implemented to project the spatial pattern of land use considering climatic,social,and economic conditions.Four sets of climate projections and three sets of land use projections were generated and fed into the MIKE SHE to project hydrologic responses from 2021 to 2050.For the calibration and first validation periods of the daily simulation,the coefficients of determination(R)were 0.85 and 0.87 and the Nash–Sutcliffe efficiency values were 0.72 and 0.73,respectively.The advanced LSTM performed better than the traditional MMEM method for daily temperature and monthly precipitation.The average monthly temperature projection under representative concentration pathway 8.5(RCP8.5)was expected to be slightly higher than that under RCP4.5;this is contrary to the average monthly precipitation from June to October.The variations in streamflow and actual evapotranspiration(ET)were both more sensitive to climate change than to land use change.There was no significant relationship between the variations in streamflow and the ET in the study area.This work could provide general variation conditions and a range of hydrologic responses to complex and changing environments,thereby assisting with stochastic uncertainty and optimizing water resource management in critical regions.

Prediction of Debris Flow Runoff Process Based on Hydrological Model： a Case Study at Shenxi Gully,Regarding a Long-Term Impact by Wenchuan Earthquake

Debris flow runoff process is one of key parameters for the design of emergency measures and control engineering. The Shenxi gully in Dujiangyan region,located in the meizoseismal areas of Wenchuan earthquake,was selected as the study area. Based on the research of hazard inducing environment,a soil conservation service( SCS) hydrological model was used to simulate the process of water flow,and then the debris flow runoff process was calculated using the empirical formula combining the results from the SCS hydrological model. Taking the debris flow event occurred on July 9th,2013 as an example,the peak discharges of water flow and debris flow were calculated as 162. 12 and 689. 22 m3/s,with error of 6. 03% compared to the measured values. The debris flow confluence process lasted 1. 8h, which was similar with the actual result. The proposed methodology can be applied to predict the debris flow runoff process in quake-hit areas of the Wenchuan earthquake and is of great importance for debris flow mitigation.

Simulation of Water Resources in Buerhatong River Basin

1∶250 000 contour was used to generate 0. 0012°（ 4. 32 s） of grid DEM of the basin,to simulate flow line of slope surface and gradient line,automatically draw valley line,and count catchment area at slope surface point. We organized data at the sections with 100 m of interval to simulate water system,establish coding system of river network,and build associated point with slope surface system. ＂ Hillside hydrology＂ theory simulated subsurface flow between surface water and groundwater,and used catchment water at slope surface point,gradient,valley line and depletion curve to study soil moisture distribution in the basin.

Comparison of Parallel Genetic Algorithm and Particle Swarm Optimization for Parameter Calibration in Hydrological Simulation

Parameter calibration is an important part of hydrological simulation and affects the final simulation results.In this paper,we introduce heuristic optimization algorithms,genetic algorithm(GA)to cope with the complexity of the parameter calibration problem,and use particle swarm optimization algorithm(PsO)as a comparison.For large-scale hydrological simulations,we use a multilevel parallel parameter calibration framework to make full use of processor resources,and accelerate the process of solving high-dimensional parameter calibration.Further,we test and apply the experiments on domestic supercomputers.The results of parameter calibration with GA and PSO can basically reach the ideal value of 0.65 and above,with PSO achieving a speedup of 58.52 on TianHe-2 supercomputer.The experimental results indicate that using a parallel implementation on multicore CPUs makes high-dimensional parameter calibration in large-scale hydrological simulation possible.Moreover,our comparison of the two algorithms shows that the GA obtains better calibration results,and the PSO has a more pronounced acceleration effect.

基于陆气耦合模式的降雨径流模拟研究进展

基于陆气耦合模式的降雨径流模拟是变化环境下水文循环过程研究的重要内容之一。围绕陆气耦合降雨径流模拟,分析基于陆气耦合模式的降雨径流模拟框架,对比基础输入资料、天气模式和陆面水文模型各方面的优缺点,回顾基于该框架的发展历程,从集合预报、数据驱动、陆面水文模型与天气模式3个方面介绍了陆气耦合降雨径流模拟技术的发展,提出多尺度转换、双向耦合、不确定性问题及误差修正4个热点关键技术问题,并对未来研究进行展望,以期为推进基于陆气耦合模式的降雨径流模拟研究提供参考。

面向防洪“四预”的数字孪生流域水利专业模型研发与实践应用--以数字孪生飞云江流域为例

数字孪生流域是推动智慧水利建设的核心和关键,而水利专业模型是数字孪生流域建设的重要算法支撑。从实际业务支撑角度研发面向防洪“四预”的数字孪生流域水利专业模型,包括水文、水动力、水工程调度、风暴潮等模型,并以浙江省温州市的数字孪生飞云江流域为载体进行实践应用。结果显示,在应对台风“杜苏芮”“卡努”“鸿雁”过程中,各类模型运行情况良好,水文、水动力及风暴潮模型预报值与实测值拟合程度较高,误差满足规范许可要求,水工程调度模型可实现模型预期调度效果。研发的水利专业模型和应用案例可为其他流域数字孪生建设提供参考。