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.

Evaluation of the applicability of climate forecast system reanalysis weather data for hydrologic simulation： A case study in the Bahe River Basin of the Qinling Mountains, China

In recent years, global reanalysis weather data has been widely used in hydrological modeling around the world, but the results of simulations vary greatly. To consider the applicability of Climate Forecast System Reanalysis（CFSR） data in the hydrologic simulation of watersheds, the Bahe River Basin was used as a case study. Two types of weather data（conventional weather data and CFSR weather data） were considered to establish a Soil and Water Assessment Tool（SWAT） model, which was used to simulate runoff from 2001 to 2012 in the basin at annual and monthly scales. The effect of both datasets on the simulation was assessed using regression analysis, Nash-Sutcliffe Efficiency（NSE）, and Percent Bias（PBIAS）. A CFSR weather data correction method was proposed. The main results were as follows.（1） The CFSR climate data was applicable for hydrologic simulation in the Bahe River Basin（R^2 of the simulated results above 0.50, NSE above 0.33, and ｜PBIAS｜ below 14.8. Although the quality of the CFSR weather data is not perfect, it achieved a satisfactory hydrological simulation after rainfall data correction.（2） The simulated streamflow using the CFSR data was higher than the observed streamflow, which was likely because the estimation of daily rainfall data by CFSR weather data resulted in more rainy days and stronger rainfall intensity than was actually observed. Therefore, the data simulated a higher base flow and flood peak discharge in terms of the water balance, except for some individual years.（3） The relation between the CFSR rainfall data（x） and the observed rainfall data（y） could berepresented by a power exponent equation： y=1.4789x0.8875（R2=0.98,P〈0.001）. There was a slight variation between the fitted equations for each station. The equation provides a theoretical basis for the correction of CFSR rainfall data.

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.

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.

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).

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.

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%）.

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.

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.

Evaluating the suitability of TRMM satellite rainfall data for hydrological simulation using a distributed hydrological model in the Weihe River catchment in China

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.

Mapping the urban natural ventilation potential by hydrological simulation

Urban wind environments are closely related to air pollution and outdoor human comfort.The urban natural ventilation potential(NVP)is an important factor in urban planning and design.However,for ventilation studies on urban scales,neither macroscale numerical simulations(i.e.,WRF,MM5,etc.)nor microscale computational fluid dynamics(CFD)simulations can conduct efficient analyses.Based on the similarity between water flows and airflows,an efficient approach is proposed in this paper to map the urban NVP.Through integrating the urban terrain model,urban form model,and prevailing wind pressure model,an airflow digital elevation model(AF-DEM),which represents the resistance to airflow and can be used for a hydrological simulation,is generated and applied to evaluate the urban airflow patterns under different terrain,urban form and ambient wind conditions.The objective was to develop a simulation platform that can efficiently predict the distribution of natural ventilation corridor and NVP.The stream network calculated through the simulation is regarded as potential ventilation corridors within the city,and an index calculated from the coverage rate of wind corridors(CRW)is proposed for evaluating the relative NVP.Taking Nanjing as a case study,8 AF-DEMs based on different wind directions and wind speed conditions are generated,and their corresponding ventilation corridor maps are constructed.The results are in good agreement with the empirical evidence,indicating that the hydrological model,though a rudimentary approximation of the actual airflows,was effective in revealing the natural ventilation corridor and characterize the relative NVP.Moreover,the implementation of this novel method is simple and convenient,and it has great application potential and value in urban design and management.

Water resources response and prediction under climate change in Tao'er River Basin,Northeast China

Climate change has significantly affected hydrological processes and increased the frequency and severity of water shortage,droughts and floods in northeast China.A study has been conducted to quantify the influence of climate change on the hydrologic process in the Tao’er River Basin(TRB),one of the most prominent regions in northeast China for water contradiction.The Soil and Water Assessment Tool(SWAT)model was calibrated and validated with observed land use and hydro-climatic data and then employed for runoff simulations at upper,middle and lower reaches of the river basin for different climate change scenarios.The results showed that a gradual increase in temperature and decrease in annual precipitation in the basin was projected for the period 2020-2050 for both representative concentration pathways(RCP)4.5 and 8.5 scenarios.The climate changes would cause a decrease in annual average runoff at basin outlet by 12 and 23 million m^(3) for RCP4.5 and 8.5,respectively.The future runoff in the upstream and midstream of the basin during 2020-2050 would be-10.8% and-12.1% lower than the observed runoff compared to the base period for RCP4.5,while those would be-5.3% and-10.7%lower for RCP8.5.The future runoff will decrease at three hydrology stations for the assumed future climate scenarios.The results can help us understand the future temperature and precipitation trends and the hydrological cycle process under different climate change scenarios,and provide the basis for the rational allocation and management of water resources under the influence of future climate change in the TRB.

Quantitative assessment on basin-scale hydrological services of wetlands

Despite recognizing the importance of hydrological function of wetlands, basin-scale wetlands services have rarely been investigated. The PHYSITEL/HYDROTEL modelling platform was used to quantitatively assess the impact of wetlands on quickflow and baseflow with paired simulation scenarios in Duobukuli River Basin, namely with wetlands and without wetlands.Simulation results showed that wetlands exert significant impact on basin hydrological processes by decreasing streamflow and altering streamflow regime(magnitude, frequency, duration and time of flow events). The intensity(significant or not) of wetlands influences on quickflow had daily, monthly and annual variation. Wetlands significantly attenuated quickflow during flood season while slightly support daily, monthly and annual baseflow. The average quickflow attenuation and baseflow support of wetlands were 5.89% and 0.83%, respectively. Although the intensity and effect(mitigation or augment) of wetlands on streamflow temporally varied at daily, monthly, seasonal and annual scales, wetland overall mitigated quickflow and augment baseflow in Duobukuli River Basin. Our results could provide insights for future decision-making for rehabilitation and conservation of wetlands as well as integrated basin water resources management.