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.

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.

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.

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.

Improvement of LCM model and determination of model parameters at watershed scale for flood events in Hongde Basin of China

Considering the fact that the original two-parameter LCM model can only be used to investigate rainfall losses during the runoff period because the initial abstraction is not included, the LCM model was redefined as a three-parameter model, including the initial abstraction coefficient l, the initial abstraction Ia, and the rainfall loss coefficient R. The improved LCM model is superior to the original two-parameter model, which only includes r and R, where r is the initial rainfall loss index and can be calculated with l using the Soil Conservation Service curve number （SCS-CN） method, with r = 1/（1 ＋ λ）. The trial method was used to determine the parameter values of the improved LCM model at the watershed scale for 15 flood events in the Hongde Basin in China. The results show that larger r values are associated with smaller R values, and the parameter R ranges widely from 0.5 to 2.0. In order to improve the practicability of the LCM model, r = 0.833 with λ = 0.2 is reasonable for simplifying calculation. When the LCM model is applied to arid and semi-arid regions, rainfall without yielding runoff should be deducted from the total rainfall for more accurate estimation of rainfall-runoff.

Hydrological modelling in the anthroposphere: predicting local runoff in a heavily modified high-alpine catchment

Hydrological models within inflow forecasting systems for high-alpine hydropower reservoirs can provide valuable information as part of a decision support system for the improvement of hydropower production or flood retention. The information, especially concerning runoff, is however rarely available for the calibration of the hydrological models used. Therefore, a method is presented to derive local runoff from secondary information for the calibration of the model parameters of the rainfallrunoff model COSERO. Changes in water levels in reservoirs, reservoir outflows, discharge measurements at water intakes and in transport lines are thereby used to derive the local, "natural" flow for a given sub-catchment. The proposed method is applied within a research study for the ?BB Infrastructure Railsystem division in the Stubache catchment in the central Austrian Alps. Here, the ?BB operates the hydropower scheme "Kraftwerksgruppe Stubachtal", which consists of 7 reservoirs and 4 hydropower stations. The hydrological model has been set up considering this human influences and the high natural heterogeneity in topography and land cover, including glaciers. Overall, the hydrological model performs mostly well for the catchment with highest NSE values of 0.78 for the calibration and0.79 for the validation period, also considering the use of homogeneous parameter fields and the uncertainty of the derived local discharge values. The derived runoff data proved to be useful information for the model calibration. Further analysis, examining the water balance and its components as well as snow cover, showed satisfactory simulation results. In conclusion, a unique runoff dataset for a small scale high-alpine catchment has been created to establish a hydrological flow prediction model which in a further step can be used for improved and sustainable hydropower management.

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.

Streamflow Decomposition Based Integrated ANN Model

The prediction of riverflows requires the understanding of rainfall-runoff process which is highly nonlinear, dynamic and complex in nature. In this research streamflow decomposition based integrated ANN (SD-ANN) model is developed to improve the efficacy rather than using a single ANN model for the flow hydrograph. The streamflows are decomposed into two states namely 1) the rise state and 2) the fall state. The rainfall-runoff data obtained from the Kolar River basin is used to test the efficacy of the proposed model when compared to feed-forward ANN model (FF-ANN). The results obtained in this study indicate that the proposed SD-ANN model outperforms the single ANN model in terms of both the statistical indices and the prediction of high flows.

Verification of the MIKE11-NAM Model for Simulating Streamflow

Modeling watershed hydrological processes are important for water resources planning, development, and management. In this study, the MIKE 11-NAM (Nedbor-Afstromings Model model) was evaluated for simulation of streamflow from the Bina basin located in the Madhya Pradesh State of India. The model was calibrated and validated on a daily basis using five years (1994-1998) observed hydrological data. In addition, a model sensitivity analysis was performed on nine MIKE 11-NAM parameters to identify sensitive model parameters. Statistical and graphical approaches were used to assess the performance of the model in simulating the streamflow of the basin. Results show that during daily model calibration, the model performed very well with a coefficient of determination (R2) and the percentage of water balance error (WBL) values 0.87% and -8.63%, respectively. In addition, the model performed good during the validation period with R2 and WBL values of 0.68% and -6.72%, respectively. Model sensitivity analysis results showed that Overland flow runoff coefficient (CQOF), Time constant for routing overland flow (CK1,2) and Maximum water content in root zone storage (Lmax) were found as the most influential and sensitive model parameters for simulating streamflow. Overall, the model’s performance was satisfactory based on R2 and EI metrics.

Calibration and Validation of the GR2M Hydrologic Model in the Kouilou-Niari Basin in Southwestern Congo-Brazzaville

The hydrologic simulation of a catchment area, described as the transformation of rainfall into runoff, generally uses hydrologic model. This work opts for the global conceptual hydrologic model GR2M, a monthly time step model, to study the Kouilou-Niari basin, the second most important ones of the Republic of Congo. This includes two parameters to model the hydrologic behavior of a catchment area. The choice of the conceptual model GR2M is justified by the reduced number of parameters and the monthly time scale. The objective of this study is to determine the characteristic parameters of the GR2M model, by a calibrating and a validating procedure. The use of these parameters enables to follow the evolution of the water resources from the climatic variables. It has been first carried out a characterization of some physical, geological and climatic factors governing the flow, by dealing with the main climatic variables which constitute the inputs of the hydrologic model. Then, a hydrologic rainfall-runoff modeling allows to calibrate and validate the model at monthly time scale. Taking into account the number of parameters involved in hydrologic processes and the complexity of the cathment area, this model gives acceptable results throughout the Kouilou-Niari basin. The values of the Nash-Sutcliffe criterion and those of the correlation coefficient obtained are greater than 80% in validation, which explains the performance and robustness of the GR2M model on this basin.

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.

雷达雨量计资料用于径流模拟(英)

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.

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.

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.

基于SCS-CN model模型的北京市功能区产流风险分析（英文）

Urbanization significantly increases the risk of urban flooding. Therefore, quantitative study of urban rainfall-runoff processes can provide a scientific basis for urban planning and management. In this paper, the built-up region within the Fifth Ring Road of Beijing was selected as the study area. The details of land cover and urban function zones(UFZs) were identified using GIS and RS methods. On this basis, the SCS-CN model was adopted to analyze the rainfall-runoff risk characteristics of the study area. The results showed that:(1) UFZs within different levels of runoff risk varied under different rainfall conditions. The area ratio of the UFZs with high runoff risk increased from 18.90%(for rainfall return period of 1 a) to 54.74%(for period of 100 a). Specifically, urban commercial areas tended to have the highest runoff risk, while urban greening spaces had the lowest.(2) The spatial characteristics of the runoff risks showed an obvious circular distribution. Spatial cluster areas with high runoff risk were mainly concentrated in the center of the study area, while those with low runoff risk were mainly distributed between the fourth and fifth ring roads. The results indicated that the spatial clustering characteristic of urban runoff risk and runoff heterogeneity among different UFZs should be fully considered during urban rainwater management.

Monthly and seasonal streamflow forecasting of large dryland catchments in Brazil

Streamflow forecasting in drylands is challenging.Data are scarce,catchments are highly humanmodified and streamflow exhibits strong nonlinear responses to rainfall.The goal of this study was to evaluate the monthly and seasonal streamflow forecasting in two large catchments in the Jaguaribe River Basin in the Brazilian semi-arid area.We adopted four different lead times:one month ahead for monthly scale and two,three and four months ahead for seasonal scale.The gaps of the historic streamflow series were filled up by using rainfall-runoff modelling.Then,time series model techniques were applied,i.e.,the locally constant,the locally averaged,the k-nearest-neighbours algorithm(k-NN)and the autoregressive(AR)model.The criterion of reliability of the validation results is that the forecast is more skillful than streamflow climatology.Our approach outperformed the streamflow climatology for all monthly streamflows.On average,the former was 25%better than the latter.The seasonal streamflow forecasting(SSF)was also reliable(on average,20%better than the climatology),failing slightly only for the high flow season of one catchment(6%worse than the climatology).Considering an uncertainty envelope(probabilistic forecasting),which was considerably narrower than the data standard deviation,the streamflow forecasting performance increased by about 50%at both scales.The forecast errors were mainly driven by the streamflow intra-seasonality at monthly scale,while they were by the forecast lead time at seasonal scale.The best-fit and worst-fit time series model were the k-NN approach and the AR model,respectively.The rainfall-runoff modelling outputs played an important role in improving streamflow forecasting for one streamgauge that showed 35%of data gaps.The developed data-driven approach is mathematical and computationally very simple,demands few resources to accomplish its operational implementation and is applicable to other dryland watersheds.Our findings may be part of drought forecasting systems and potentially help allocating water months in advance.Moreover,the developed strategy can serve as a baseline for more complex streamflow forecast systems.

Runoff and Infiltration responses of revegetated slopes to clipping management on the northern Loess Plateau

Large-scale vegetation restoration can reduce local watershed water yield,limit vegetation establishment and subsequent growth,and influence regional ecosystem functions.Clipping management by reducing aboveground parts of grassland was gradually recommended and adopted in Grain-for-Green project management to offset these additional issues.Thus,scientific evaluation of the effectiveness of clipping management on infiltration and runoff processes is necessary for maintaining the stability of the surface water system and the sustainability of vegetation restoration in semi-arid regions.A field simulated rainfall experiment was conducted with four managed clipping grasslands(mainly bunge needlegrass and Stipa grandis),including no clipping,light clipping,heavy clipping,and complete clipping under three slope gradients(10,20,and 30°)and three rainfall intensities(60,90,and 120 mm/h)to explore the mechanism of runoff and infiltration responses to clipping using structural equation modeling and variation partitioning based on an SCS-CN model.The results showed the runoff coefficient of the light clipping,heavy clipping,and complete clipping plots were 1.33,2.22,and 4.22 times that of the no clipping plot.The light clipping,heavy clipping,and complete clipping plots decreased the infiltration coefficients by 0%,5%,and 26%relative to the no clipping plot.Rainfall intensity dominated runoff and infiltration amounts,and clipping intensity's total effect was stronger than slope gradient.Clipping intensity and slope gradient were more influential on runoff with increasing rainfall intensity.The mutual inhibition effect was between clipping intensity and slope gradient on runoff.In order to maintain the sustainability of restoration,a 25-50%vegetation coverage after clipping maximizes the benefits of increasing runoff and maintaining enough soil water supply that prevents possible soil drought.We propose that future vegetation restoration policies should evaluate the appropriate clipping intensity;meanwhile,local physiographic and climate conditions should be considered.These findings may offer guidance for the development of measures for runoff regulation and ecosystem functions of the watershed during vegetation restoration on the northern Loess Plateau.

A physically-based integrated numerical model for flow,upland erosion,and contaminant transport in surface-subsurface systems

This paper presents a physically-based integrated hydrologic model that can simulate the rain-fall-induced 2D surface water flow, 3D variably saturated subsurface flow, upland soil erosion and transport, and contaminant transport in the surface-subsurface system of a watershed. The model couples surface and subsurface flows based on the assumption of continuity conditions of pressure head and exchange flux at the ground, considering infiltration and evapotranspiration. The upland rill/interrill soil erosion and transport are simulated using a non-equilibrium transport model. Contaminant transport in the integrated surface and subsurface domains is simulated using advection-diffusion equations with mass changes due to sediment sorption and desorption and exchanges between two domains due to infiltration, diffusion, and bed change. The model requires no special treatments at the interface of upland areas and streams and is suitable for wetland areas and agricultural watersheds with shallow streams.

Impacts of water conservancy and soil conservation measures on annual runoff in the Chaohe River Basin during 1961-2005

Taking the Chaohe River Basin above the Miyun Reservoir in North China as a study area, the characteristics and variation trends of annual runoff and annual precipitation during 1961-2005 were analyzed applying Mann-Kendall test method on the basis of the hydrologic data of the major hydrological station （Xiahui Station） located at the outlet of the drainage basin and the meteorological data of 17 rainfall stations. Human activities including water conservancy projects construction and water diversion as well as implementation of soil and water conservation from 1961 to 2005 were carefully studied using time series contrasting method. The referenced period （1961-1980） that influenced slightly by human activities and the compared period （1981-2005） that influenced significantly by water conservancy and soil conservation measures were identified according to the runoff variation process analysis and abrupt change points detection during 1961-2005 applying double accumulative curve method, mean shift t-test method and Mann-Kendall mutation test technique. Based on the establishment of a rainfall-runoff empirical statistical model, impacts and the runoff-reducing effects of water conservancy and soil conservation measures on runoff reduction were evaluated quantitatively. The major results could be summarized as follows： （1） The annual precipitation in the drainage basin tends to decrease while the runoff has declined markedly since the 1960s, the average annual runoff from 1991 to 2000 was only 90.9% in proportion to that from 1961 to 1970. （2） The annual runoff variations in the drainage basin are significantly related to human activities. （3） During 1981-1990, 1991-2000, 2001-2005 and 1981-2005, the average annual runoff reduction amounts were 1.15×10^8, 0.28×10^8, 1.10×10^8 and 0.79×10^8 m^3 respectively and the average annual runoff-reducing effects were 31.99%, 7.13%, 40.71% and 23.79% accordingly. Runoff-reducing effects by water conservancy and soil conservation measures are more prominent in the low water period.