Rainfall-Runoff Modeling and Hydrological Responses to the Projected Climate Change for Upper Baro Basin, Ethiopia

This paper presents the results of Rainfall-Runoff modeling and simulation of hydrological responses under changing climate using HEC-HMS model. The basin spatial data was processed by HEC-GeoHMS and imported to HEC-HMS. The calibration and validation of the HEC-HMS model was done using the observed hydrometeorological data (1989-2018) and HEC-GeoHMS output data. The goodness-of-fit of the model was measured using three performance indices: Nash and Sutcliffe coefficient (NSE) = 0.8, Coefficient of Determination (R2) = 0.8, and Percent Difference (D) = 0.03, with values showing very good performance of the model. Finally, the optimized HEC-HMS model has been applied to simulate the hydrological responses of Upper Baro Basin to the projected climate change for mid-term (2040s) and long-term (2090s) A1B emission scenarios. The simulation results have shown a mean annual percent decrease of 3.6 and an increase of 8.1 for Baro River flow in the 2040s and 2090s scenarios, respectively, compared to the baseline period (2000s). A pronounced flow variation is rather observed on a seasonal basis, reaching a reduction of 50% in spring and an increase of 50% in autumn for both mid-term and long-term scenarios with respect to the base period. Generally, the rainfall-runoff model is developed to solve, in a complementary way, the two main problems in water resources management: the lack of gauged sites and future hydrological response to climate change data of the basin and the region in general. The study results imply that seasonal and time variation in the hydrologic cycle would most likely cause hydrologic extremes. And hence, the developed model and output data are of paramount importance for adaptive strategies and sustainable water resources development in the basin.

Hydrological daily rainfall-runoff simulation with BTOPMC model and comparison with Xin'anjiang model

A grid-based distributed hydrological model, the Block-wise use of TOPMODEL （BTOPMC）, which was developed from the original TOPMODEL, was used for hydrological daily rainfall-runoff simulation. In the BTOPMC model, the runoff is explicitly calculated on a cell-by-cell basis, and the Muskingum-Cunge flow concentration method is used. In order to test the model＇s applicability, the BTOPMC model and the Xin＇anjiang model were applied to the simulation of a humid watershed and a semi-humid to semi-arid watershed in China. The model parameters were optimized with the Shuffle Complex Evolution （SCE-UA） method. Results show that both models can effectively simulate the daily hydrograph in humid watersheds, but that the BTOPMC model performs poorly in semi-humid to semi-arid watersheds. The excess-infiltration mechanism should be incorporated into the BTOPMC model to broaden the model＇s applicability.

Rainfall-runoff simulation and flood forecasting for Huaihe Basin

The main purpose of this study was to forecast the inflow to Hongze Lake using the Xin＇anjiang rainfall-runoff model. The upper area of Hongze Lake in the Huaihe Basin was divided into 23 sub-basins, including the surface of Hongze Lake. The influence of reservoirs and gates on flood forecasting was considered in a practical and simple way. With a one-day time step, the linear and non-linear Muskingum method was used for channel flood routing, and the least-square regression model was used for real-time correction in flood forecasting. Representative historical data were collected for the model calibration. The hydrological model parameters for each sub-basin were calibrated individually, so the parameters of the Xin＇anjiang model were different for different sub-basins. This flood forecasting system was used in the real-time simulation of the large flood in 2005 and the results are satisfactory when compared with measured data from the flood.

Application of Hydrological Model to Simulate Rainfall-Runoff into An Khe Reservoir in the Ba River Basin, Vietnam

The BR （Ba River） basin is one of 9 main river basins in Vietnam. In the past 20 years, natural hazards such as flood andinundation have been complex and increased dramatically in both frequency and intensity in the BR basin. Recently, there have beenapproximately 198 large and small operating reservoirs which lead to increase natural hazards in the river basin. An Khe reservoir,one of big reservoirs in the upstream of the Ba river, impacts significantly on flooding in the downstream. This paper useshydrological model to simulate the flows as a basic for the safety operation of An Khe reservoir in order to prevent the downstreamfloods. The results indicate the Nash-Sutcliffe coefficient higher than 0.8 is stable and reliable parameter.

Particle Swarm Optimization for Identifying Rainfall-Runoff Relationships

Rainfall-runoff processes can be considered a single input-output system where the observed rainfall and runoff are inputs and outputs, respectively. Conventional models of these processes cannot simultaneously identify unknown structures of the system and estimate unknown parameters. This study applied a combinational optimization and Particle Swarm Optimization (PSO) for simultaneous identification of system structure and parameters of the rainfall-runoff relationship. Subsystems in proposed model are modeled using combinations of classic models. Classic models are used to transform the system structure identification problem into a combinational optimization and can be selected from those typically used in the hydrological field. A PSO is then applied to select the optimized subsystem model with the best data fit. The parameters are estimated simultaneously. The proposed model is tested in a case study of daily rainfall-runoff for the upstream Kee-Lung River. Comparison of the proposed method with simple linear model (SLM) shows that, in both calibration and validation, the PSO simulates the time of peak arrival more accurately compared to the SLM. Analytical results also confirm that the PSO accurately identifies the system structure and parameters of the rainfall-runoff relationship, which are a useful reference for water resource planning and application.

Artificial Neural Networks for Event Based Rainfall-Runoff Modeling

The Artificial Neural Network (ANN) approach has been successfully used in many hydrological studies especially the rainfall-runoff modeling using continuous data. The present study examines its applicability to model the event-based rainfall-runoff process. A case study has been done for Ajay river basin to develop event-based rainfall-runoff model for the basin to simulate the hourly runoff at Sarath gauging site. The results demonstrate that ANN models are able to provide a good representation of an event-based rainfall-runoff process. The two important parameters, when predicting a flood hydrograph, are the magnitude of the peak discharge and the time to peak discharge. The developed ANN models have been able to predict this information with great accuracy. This shows that ANNs can be very efficient in modeling an event-based rainfall-runoff process for determining the peak discharge and time to the peak discharge very accurately. This is important in water resources design and management applications, where peak discharge and time to peak discharge are important input

The hydrothermal changes of permafrost active layer and their impact on summer rainfall-runoff processes in an alpine meadow watershed,northwest China

The freezing-thawing variation of permafrost active layer increases the complexity of rainfall-runoff processes in alpine river basins,Northwest China.And alpine meadow is the prominent ecosystem in these basins.This study selected a small alpine meadow watershed in the upper reaches of the Shule River Basin,China.We investigated alpine rainfall-runoff processes,as well as impacts of summer thaw depth of active layer,soil temperature and moisture variation on streamflow based on in-situ observations from July 2015 to December 2020.Some hydrologic parameters or indices were calculated using statistical methods,and impacts of permafrost change on river runoff were assessed using the variable infiltration capacity model(VIC).In the alpine meadow,surface soil(0–10 cm depth)of the active layer starts to freeze in mid-October each year,and begins to thaw in early April.Also,the deeper soil(70–80 cm depth)of the active layer starts to freeze in late October,and begins to thaw in late June.Moisture content in shallow soils fluctuates regularly,whereas deeper soils are more stable,and their response to rainstorms is negligible.During active layer thawing,the moisture content increases with soil depth.In the alpine meadow,vertical infiltration only occurred in soils up to 40 cm deep,and lateral flow occurred in0–20 and 60–80 cm deep soils at current rainfall intensity.Summer runoff ratios were 0.06–0.31,and runoff floods show lags of 9.5–23.0 h following the rainfall event in the study area.The freeze–thaw process also significantly impacts runoff regression coefficients,which were 0.0088–0.0654 per hour.Recession coefficient decrease negatively correlates with active layer thawing depth in summer and autumn.Alpine river basin permafrost can effectively increase peak discharge and reduce low flow.These findings are highly significant for rainfall–runoff conversion research in alpine areas of inland rivers.

Rainfall-Runoff Simulation in Part of Lower Niger Basin

Water resources assessment in poorly gauged and ungauged basins demand supportive rainfall-runoff estimation, while resolving practical water resource management and planning issues. In this study, the research method employed involves rainfall-runoff modeling and simulation with proper efficiency criteria evaluation using the MODMENS modeling platform, a numerical rainfall-runoff semi-distributed GR2M conceptual lumped model. The rainfall-runoff simulation was carried-out in three selected sub-basins of Lower River Niger Basin based on observable discharge dataset. Related error estimation was carried-out to estimate the runoff simulation uncertainty while model optimization approach entails use of Rosenbrock-Simplex method and model reliability evaluation entails the use of Nash and Sutcliffe efficiency criteria methods. Result shows a satisfactory model performance at Baro and Makurdi gauging stations （savannah ecological zone） while under-estimation characterizes simulated flow at Onitsha gauging station（Forest ecological region）. Seasonally, the model best fit the dry season flow but underestimate during the high flow periods （rainy seasons and wetter years）.

Evaluating the Performance of HEC-HMS and SWAT Hydrological Models in Simulating the Rainfall-Runoff Process for Data Scarce Region of Ethiopian Rift Valley Lake Basin

A number of physically-based and distributed watershed models have been developed to model the hydrology of the watershed. For a specific watershed, selecting the most suitable hydrological model is necessary to obtain good simulated results. In this study, two hydrologic models, Soil and Water Assessment Tool (SWAT) and Hydrological Engineering Centre-The Hydrologic Modeling System (HEC-HMS), were applied to predict streamflow in Katar River basin, Ethiopia. The performances of these two models were compared in order to select the right model for the study basin. Both models were calibrated and validated with stream flow data of 11 years (1990-2000) and 7 years (2001-2007) respectively. Nash-Sutcliffe Error (NSE) and Coefficient of Determination (R2) were used to evaluate efficiency of the models. The results of calibration and validation indicated that, for river basin Katar, both models could simulate fairly well the streamflow. SWAT gave the model performance with the R2 > 0.78 and NSE > 0.67;and the HEC-HMS model provided the model performance with the R2 > 0.87 and NSE > 0.73. Hence, the simulated streamflow given by the HEC-HMS model is more satisfactory than that provided by the SWAT model.

Using SWAT Model and Field Data to Determine Potential of NASA-POWER Data for Modelling Rainfall-Runoff in Incalaue River Basin

Incalaue is a tributary of Lugenda River in NSR (Niassa Special Reserve) in North-Eastern Mozambique. NSR is a data-poor remote area and there is a need for rainfall-runoff data to inform decisions on water resources management, and scientific methods are needed for this wide expanse of land. This study assessed the potential of a combination of NASA-POWER (National Aeronautics and Space Administration and Prediction of Worldwide Energy Resources) remotely sensed rainfall data and FAO (Food and Agriculture Organization of the United Nations) soil and land use/cover data for modelling rainfall-runoff in Incalaue river basin. DEM (Digital Elevation Model) of 1:250,000 scale and a grid resolution of 30 m × 30 m downloaded from USGS (the United States Geological Survey) website;clipped river basin FAO digital soil and land use/cover maps;and field-collected data were used. SWAT (Soil and Water Assessment Tool) model was used to assess rainfall -runoff data generated using the NASA-POWER dataset and gauged rainfall and river flow data collected during fieldwork. FAO soil and land use/cover datasets which are globally available and widely used in the region were used for comparison with soil data collected during fieldwork. Field collected data showed that soil in the area is predominantly sandy loam and only sand content and bulk density were uniformly distributed across the soil samples. SWAT model showed a good rainfall-runoff relationship using NASA-POWER data for the area (R2 = 0.7749) for the studied period (2019-2021). There was an equally strong rainfall-runoff relationship for gauged data (R2 = 0.8131). There were uniform trends for the rainfall, temperature, and relative humidity in NASA-POWER meteorological data. Timing of peaks and lows in rainfall and river flow observed in the field and modelled were confirmed by residents as the trend in the area. This approach was used because there was no historical rainfall and river flow data since the river basin is ungauged for hydrologic data. The study showed that NASA-POWER data has the potential for use for modelling the rainfall-runoff in the basin. The difference in rainfall-runoff relationship with field-collected data could be because of landscape characteristics or topsoil layer not catered for in the FAO soil data.

Assessment of soil erosion in the Irga watershed on the eastern edge of the Chota Nagpur Plateau,India

Human activities to improve the quality of life have accelerated the natural rate of soil erosion.In turn,these natural disasters have taken a great impact on humans.Human activities,particularly the conversion of vegetated land into agricultural land and built-up area,stand out as primary contributors to soil erosion.The present study investigated the risk of soil erosion in the Irga watershed located on the eastern fringe of the Chota Nagpur Plateau in Jharkhand,India,which is dominated by sandy loam and sandy clay loam soil with low soil organic carbon(SOC)content.The study used the Revised Universal Soil Loss Equation(RUSLE)and Geographical Information System(GIS)technique to determine the rate of soil erosion.The five parameters(rainfall-runoff erosivity(R)factor,soil erodibility(K)factor,slope length and steepness(LS)factor,cover-management(C)factor,and support practice(P)factor)of the RUSLE were applied to present a more accurate distribution characteristic of soil erosion in the Irga watershed.The result shows that the R factor is positively correlated with rainfall and follows the same distribution pattern as the rainfall.The K factor values in the northern part of the study area are relatively low,while they are relatively high in the southern part.The mean value of the LS factor is 2.74,which is low due to the flat terrain of the Irga watershed.There is a negative linear correlation between Normalized Difference Vegetation Index(NDVI)and the C factor,and the high values of the C factor are observed in places with low NDVI.The mean value of the P factor is 0.210,with a range from 0.000 to 1.000.After calculating all parameters,we obtained the average soil erosion rate of 1.43 t/(hm^(2)•a),with the highest rate reaching as high as 32.71 t/(hm^(2)•a).Therefore,the study area faces a low risk of soil erosion.However,preventative measures are essential to avoid future damage to productive and constructive activities caused by soil erosion.This study also identifies the spatial distribution of soil erosion rate,which will help policy-makers to implement targeted soil erosion control measures.

Indoor imitation experimental study on driving factors of rainfall-runoff process

The driving actions of rainfall-runoff process can be attributed to two aspects. The first is the influence of precipitation process, and the second is that of the ground pad. The re- search results of 179 indoor experiments conducted to imitate rainfall-runoff process indicate that both precipitation duration and intensity play important roles in affecting confluence lag time, which is obviously inconsistent with the traditional hypotheses. The nonlinear relationship is of great significance to the confluence curve especially when the precipitation duration is less than the total confluence time or the precipitation intensity is small. Therefore it can be concluded that the unit hydrograph (UH) can be applied to rainfall-runoff process imitation in the humid areas in the south China region. However, the UH application should be strictly modified in accordance with precipitation conditions in the arid and semiarid region of north China where the precipitation duration is short and the intensity is unstable. It will be hard to get ideal imitation results if the UH is applied blindly without considering specific conditions in the north China region. This also explains the unsatisfactory imitation results caused by using various hydrological models in the north China region. When the precipitation duration is short, and the watershed has not reached total watershed concentration, the characteristics of confluence change greatly, which reflects the actual situation in the north China region. Therefore necessary nonlinear corrections should be made when UH is applied. If the duration is longer than the total confluence time and the balance between pondage and discharge is stricken, the imitation research results will be applicable to both rainfall-runoff relation with longer duration in the south China region and the basic theoreti- cal research on runoff generation and concentration. On conditions of adequate rainfall, peak discharge is in linear relationship with intensity, but has nothing to do with the ground pad. There is a negative linear relationship between intensity and time to peak . The amount of pondage capacity in a catchment is in linear relationship with intensity and peak discharge, with obvious influence by the ground pad status and interception, and it has nothing to do with the position of interceptions.

Integrated rainfall-runoff process with shallow water model by mass varied smoothed particle hydrodynamics:Infiltration effect implementation

Rainfall-runoff modeling is essential for addressing a wide range of issues in urban drainage system design and operation in both scientific research and engineering practice.Recently,it has become increasingly attractive to use the smoothed particle hydrodynamics(SPH)method to model rainfall-runoff because of its inherent features such as mesh-free and automatic adaptiveness for wet-dry interfaces.However,one of its inadequacies is the lack of an infiltration effect within rainfall-runoff modeling.Hence,we propose a new methodology that innovatively integrates the infiltration effect into the shallow water equation(SWE)system with the SPH method(SPH-SWE)to represent a more complete rainfall-runoff process.In the proposed method,the mass-varied SPH-SWE(MVSPH-SWE)method is enhanced by integrating the infiltration model.A naked area treatment(NAT)method is subsequently proposed to improve the modeling efficiency and accuracy.The obtained numerical results are validated using experimental data from the literature.The results demonstrate that the proposed method is accurate and reliable.The achievements and findings of this study are expected to improve and extend the use of existing hydrological process models.

Comparison of the performance of a hydrologic model and a deep learning technique for rainfall-runoff analysis

Rainfall-runoff analysis is the most important and basic analysis in water resources management and planning.Conventional rainfall-runoff analysis methods generally have used hydrologic models.Rainfall-runoff analysis should consider complex interactions in the water cycle process,including precipitation and evapotranspiration.In this study,rainfall-runoff analysis was performed using a deep learning technique that can capture the relationship between a hydrological model used in the existing methodology and the data itself.The study was conducted in the Yeongsan River basin,which forms a large-scale agricultural area even after industrialization,as the study area.As the hydrology model,SWAT(Soil and Water Assessment Tool)was used,and for the deep learning method,a Long Short-Term Memory(LSTM)network was used among RNNs(Recurrent Neural Networks)mainly used in time series analysis.As a result of the analysis,the correlation coefficient and NSE(Nash-Sutcliffe Efficiency),which are performance indicators of the hydrological model,showed higher performance in the LSTM network.In general,the LSTM network performs better with a longer calibration period.In other words,it is worth considering that a data-based model such as an LSTM network will be more useful than a hydrological model that requires a variety of topographical and meteorological data in a watershed with sufficient historical hydrological data.

The effects of rainfall regimes and rainfall characteristics on peak discharge in a small debris flow-prone catchment

Peak discharge plays an important role in triggering channelized debris flows.The rainfall regimes and rainfall characteristics have been demonstrated to have important influences on peak discharge.In order to explore the relationship between rainfall regimes and peak discharge,a measuring system was placed at the outlet of a small,debris flow-prone catchment.The facility consisted of an approximately rectangular stilling basin,ending with a sharp-crested weir.Six runoff events were recorded which provided a unique opportunity for characterizing the hydrological response of the debris flow-prone catchment.Then,a rainfall–runoff model was tested against the flow discharge measurements to have a deep understanding of hydrological response.Based on the calibrated rainfall-runoff model,twelve different artificially set rainfall patterns were regarded as the input parameters to investigate the effect of rainfall regimes on peak discharge.The results show that the rainfall patterns have a significant effect on peak discharge.The rainfall regimes which have higher peak rainfall intensity and peak rainfall point occur at the later part of rainfall process are easy to generate larger peak discharge in the condition of the same cumulative rainfall and duration.Then,in order to explore the relationship between rainfall characteristics and peak discharge under different cumulative precipitation and different duration,167 measured rainfall events were also collected.On the basis of rainfall depth,rainfall duration,and maximum hourly intensity,all the rainfall events were classified into four categories by using K-mean clustering.Rainfall regime 1 was composed of rainfall events with a moderate mean P(precipitation),a moderate D(duration),and a moderate I60(maximum hourly intensity).Rainfall regime 2 was the group of rainfall events with a high mean P,long D.Rainfall regime 3,however,had a low P and a long D.The characteristic of Rainfall regime 4 was high I60 and short duration with large P.The results show that the rainfall regime 2 and 4 are easier to generate peak discharge as the rainfall intensity plays an important role in generating peak discharge.The results in this study have implications for improving peak discharge prediction accuracy in debris flow gully.

Analysis of Runoff in Ungauged Mountain Watersheds in Sichuan,China using Kinematic-wave-based GIUH Model

Floods are one of the most common natural hazards occurring all around the world.However,the knowledge of the origins of a food and its possible magnitude in a given region remains unclear yet.This lack of understanding is particularly acute in mountainous regions with large degrees in Sichuan Province,China,where runoff is seldom measured.The nature of streamflow in a region is related to the time and spatial distribution of rainfall quantity and watershed geomorphology.The geomorphologic characteristics are the channel network and surrounding landscape which transform the rainfall input into an output hydrograph at the outlet of the watershed.With the given geomorphologic properties of the watershed,theoretically the hydrological response function can be determined hydraulically without using any recorded data of past rainfall or runoff events.In this study,a kinematic-wave-based geomorphologic instantaneous unit hydrograph (KW-GIUH) model was adopted and verified to estimate runoff in ungauged areas.Two mountain watersheds,the Yingjing River watershed and Tianquan River watershed in Sichuan were selected as study sites.The geomorphologic factors of the two watersheds were obtained by using a digital elevation model (DEM) based on the topographic database obtained from the Shuttle Radar Topography Mission of US's NASA.The tests of the model on the two watersheds were performed both at gauged and ungauged sites.Comparison between the simulated and observed hydrographs for a number of rainstorms at the gauged sites indicated the potential of the KW-GIUH model as a useful tool for runoff analysis in these regions.Moreover,to simulate possible concentrated rainstorms that could result in serious flooding in these areas,synthetic rainfall hyetographs were adopted as input to the KW-GIUH model to obtain the flow hydrographs at two ungauged sites for different return period conditions.Hydroeconomic analysis can be performed in the future to select the optimum design return period for determining the flood control work.

Water Quality Model Establishment for Middle and Lower Reaches of Hanshui River,China

With the development of industry and agriculture,nitrogen,phosphorus and other nutrients in the Hanshui River greatly increase and eutrophication has become an important threat to the water quality of the Hanshui River,especially in the middle and lower reaches.The primary objective of this study was to establish the water quality model for the middle and lower reaches of the Hanshui River based on the model of MIKE 11.The main pollutants migration and transformation process could be simulated using the water quality model.The rainfall-runoff model,hy-drodynamic model and water quality model were established using MIKE 11.The pollutants,such as chemical oxygen demand(COD),biochemical oxygen demand(BOD),ammonia nitrogen,nitrate nitrogen,phosphorus,dissolved oxy-gen(DO),were simulated and predicted using the above three models.A set of methods computing non-point source pollution load of the Hanshui River Basin was proposed in this study.The simulated and observed values of COD,BOD5,ammonia,nitrate,DO,and total phosphorus were compared after the parameter calibration of the water quality model.The simulated and observed results match better,thus the model can be used to predict water quality in the fu-ture for the Hanshui River.The pollution trend could be predicted using the water quality model according pollution load generation.It is helpful for government to take effective measures to prevent the water bloom and protect water quality in the river.

Runoff Simulation Using Radar and Rain Gauge Data

The conceptual rainfall-runoff model TOPMODEL is used to simulate runoffs of the Meishan and Nianyushan catchments during the summers of 1998 and 1999 in the GAME/HUBEX (GEWEX Asia Monsoon Experiment /HUAIHE River Basin Experiment) project. The rainfall distributions are estimated by weather radar and rain gauge networks according to different methods. Observed and simulated runoffs are compared and analyzed for both catchments. Results show that (1) the runoff of the catchment is best simulated by radar data combined with rain gauge network data from inside the catchment, and (2) the rainfall estimated by radar adjusted by a few rain gauges outside the catchment can be used to simulate runoff equally as well as using the dense rain gauge network alone.

GIS-Based Spatial Mapping of Flash Flood Hazard in Makkah City, Saudi Arabia

Flash floods occur periodically in Makkah city, Saudi Arabia, due to several factors including its rugged to-pography and geological structures. Hence, precise assessment of floods becomes a more vital demand in development planning. A GIS-based methodology has been developed for quantifying and spatially mapping the flood characteristics. The core of this new approach is integrating several topographic, metrological, geological, and land use datasets in a GIS environment that utilizes the Curve Number (CN) method of flood modelling for ungauged arid catchments. Additionally, the computations of flood quantities, such as depth and volume of runoff, are performed in the attribute tables of GIS layers, in order to assemble all results in the same environment. The accomplished results show that the runoff depth in Makkah, using a 50-years re-turn period, range from 128.1 mm to 193.9 mm while the peak discharge vary from 1063 m3/s to 4489 m3/s. The total flood volume is expected to reach 172.97 million m3 over Makkah metropolitan area. The advan-tages of the developed methodology include precision, cost-effective, digital outputs, and its ability to be re-run in other conditions.

Sediment transport following water transfer from Yangtze River to Taihu Basin

To meet the increasing ：need of fresh water and to improve the water quality of Taihu Lake, water transfer from the Yangtze River was initiated in 2002. This study was performed to investigate the sediment distribution along the river course following water transfer. A rainfall-runoff model was first built to calculate the runoff of the Taihu Basin in 2003. Then, the flow patterns of river networks were simulated using a one-dimensional river network hydrodynamic model. Based on the boundary conditions of the flow in tributaries of the Wangyu River and the water level in Taihu Lake, a one-dimensional hydrodynamic and sediment transport numerical model of the Wangyu River was built to analyze the influences of the inflow rate of the water transfer and the suspended sediment concentration （SSC） of inflow on the sediment transport. The results show that the water transfer inflow rate and SSC of inflow have significant effects on the sediment distribution. The higher the inflow rate or SSC of inflow is, the higher the SSC value is at certain cross-sections along the ：river course of water transfer. Higher inflow rate and SSC of inflow contribute to higher sediment deposition per kilometer and sediment thickness. It is also concluded that a sharp decrease of the inflow velocity at the entrance of the Wangyu River on the river course of water transfer induces intense sedimentation at the cross-section near the Changshu hydro-junction. With an increasing distance from the Changshu hydro-junction, the sediment deposition and sedimentation thickness decrease gradually along the river course.