A distributed runoff model for inland mountainous river basin of Northwest China

In order to predict the futuristic runoff under global warming, and to approach to the effects of vegetation on the ecological environment of the inland river mountainous watershed of Northwest China, the authors use the routine hydrometric data to create a distributed monthly model with some conceptual parameters, coupled with GIS and RS tools and data. The model takes sub-basin as the minimal confluent unit, divides the main soils of the basin into 3 layers, and identifies the vegetation types as forest and pasture. The data used in the model are precipitation, air temperature, runoff, soil weight water content, soil depth, soil bulk density, soil porosity, land cover, etc. The model holds that if the water amount is greater than the water content capacity, there will be surface runoff. The actual evaporation is proportional to the product of the potential evaporation and soil volume water content. The studied basin is Heihe mainstream mountainous basin, with a drainage area of 10,009 km 2 . The data used in this simulation are from Jan. 1980 to Dec. 1995, and the first 10 years' data are used to simulate, while the last 5 years' data are used to calibrate. For the simulation process, the Nash-Sutcliffe Equation, Balance Error and Explained Variance is 0.8681, 5.4008 and 0.8718 respectively, while for the calibration process, 0.8799, -0.5974 and 0.8800 respectively. The model results show that the futuristic runoff of Heihe river basin will increase a little. The snowmelt, glacier meltwater and the evaportranspiration will increase. The air temperature increment will make the permanent snow and glacier area diminish, and the snowline will rise. The vegetation, especially the forest in Heihe mountainous watershed, could lead to the evapotranspiration decrease of the watershed, adjust the runoff process, and increase the soil water content.

Application of snowmelt runoff model(SRM) in mountainous watersheds:A review

The snowmelt runoff model （SRM） has been widely used in simulation and forecast of streamflow in snow-dominated mountainous basins around the world. This paper presents an overall review of worldwide applications of SRM in mountainous watersheds, particularly jn data-sparse watersheds of northwestern China. Issues related to proper selection of input climate variables and parameters, and determination of the snow cover area （SCA）using remote sensing data in snowmelt runoff modeling are discussed through extensive review of literature. Preliminary applications of SRM in northwestern China have shown that the model accuracies are relatively acceptable although most of the watersheds lack measured hydro-meteorological data. Future research could explore the feasibility of modeling snowmelt runoff in data-sparse mountainous watersheds in northwestern China by utilizing snow and glacier cover remote sensing data, geographic information system （GIS） tools, field measurements, and innovative ways of model parameterization.

Application of spatially varying storage capacity model for runoff parameterization in semi-arid catchment

This paper introduces the method of designation of water storage capacity for each grid cell within a catchment, which considers topography, vegetation and soil synthetically. For the purpose of hydrological process simulation in semi-arid regions, a spatially varying storage capacity （VSC） model was developed based on the spatial distribution of water storage capacity and the vertical hybrid runoff mechanism. To verify the applicability of the VSC model, both the VSC model and a hybrid runoff model were used to simulate daily runoff processes in the catchment upstream of the Dianzi hydrological station from 1973 to 1979. The results showed that the annual average Nash-Sutcliffe coefficient was 0.80 for the VSC model, and only 0.67 for the hybrid runoff model. The higher annual average Nash-Sutcliffe coefficient of the VSC model means that this hydrological model can better simulate daily runoff processes in semi-arid regions. Furthermore, as a distributed hydrological model, the VSC model can be applied in regional water resource management.

Hydrologic modeling of the Heihe watershed by DLBRM in Northwest China

Water shortage is a chronic problem in arid Northwest China.The rapid population growth and expanding urbanization as well as potential climate change impacts are likely to worsen the situation,threatening domestic,irrigation,and industrial supplies and even the survival of the ecosystems in Northwest China.This paper describes the preliminary work of adapting the Distributed Large Basin Runoff Model(DLBRM) to the Heihe watershed(the second largest inland river in arid Northwestern China,with a drainage area of 128,000 km2) for understanding distribution of glacial-snow melt,groundwater,surface runoff,and evapotranspi-ration,and for assessing hydrological impacts of climate change and glacial recession on water supply in the middle and lower reaches of the watershed.Preliminary simulation results show that the Qilian Mountain in the upper reach area produces most runoff in the Heihe watershed.The simulated daily river flows during the period of 1990-2000 indicate that the Heihe River dis-charges about 1×109 m3 of water from the middle reach(at Zhengyixia Station) to lower reach,with surface runoff and interflow contributing 51 and 49 percent respectively.The sandy lower soil zone in the middle reach has the highest evapotranspiration rate and also contributes nearly half of the river flow.Work underway focuses on the DLBRM model improvement and incorporation of the climate change and management scenarios to the hydrological simulations in the watershed.

Application of Snow Melt Runoff Model in a Mountainous Basin of Iran

Simulation and modeling the stream flow provide major data while it is a challenge in mountainous basins with regard to the important role of snowmelt runoff as well as the data scarcity in these places. The main purpose of this paper is to examine the capability of an integrated application of remote sensing data and Snowmelt Runoff Model (SRM) to simulate scheme of daily stream flow in the snow-dominated catchment, located in the North-East region of Iran. The main parameters of the model are Snow Cover Area (SCA), temperature and participation. Regarding to the lack of measured data, the input variable and parameters of the model are extracted or estimated based on accessible maps, satellite data and available meteorological and hydrological stations. The changes of snow-cover, as spatial-temporal data, which are the most effective variable in performance of SRM, are obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) eight-day composite snow cover images. The evaluation of the model application efficiency was tested by the coefficient of determination and the volume difference, which are 0.85% and -4.6% respectively. The result depicts the relative capability of SRM though it is evident that the more accurate the estimation of model parameters, the more efficient simulation results can be obtained.

Understanding the impact of mountain landscapes on water balance in the upper Heihe River watershed in northwestern China

Estimating the impact of mountain landscape on hydrology or water balance is essential for the sus- tainable development strategies of water resources. Specifically, understanding how the change of each landscape influences hydrological components will greatly improve the predictability of hydrological responses to mountain landscape changes and thus can help the government make sounder decisions. In the paper, we used the VIC （Variable Infiltration Capacity） model to conduct hydrological modeling in the upper Heihe River watershed, along with a frozen-soil module and a glacier melting module to improve the simulation. The improved model performed satisfactorily. We concluded that there are differences in the runoff generation of mountain landscape both in space and time. About 50% of the total runoff at the catchment outlet were generated in mid-mountain zone （2,900-4,000 m asl）, and water was mainly consumed in low mountain region （1,700-2,900 m asl） because of the higher requirements of trees and grasses. The runoff coefficient was 0.37 in the upper Heihe River watershed. Barren landscape produced the largest runoff yields （52.46% of the total runoff） in the upper Heihe River watershed, fol- lowed by grassland （34.15%）, shrub （9.02%）, glacier （3.57%）, and forest （0.49%）. In order to simulate the impact of landscape change on hydrological components, three landscape change scenarios were designed in the study. Scenario 1, 2 and 3 were to convert all shady slope landscapes at 2,000-3,300 m, 2,000-3,700 m, and 2,000-4,000 m asl respectively to forest lands, with forest coverage rate increased to 12.4%, 28.5% and 42.0%, respectively. The runoff at the catchment outlet correspondingly declined by 3.5%, 13.1% and 24.2% under the three scenarios. The forest landscape is very important in water conservation as it reduced the flood peak and increased the base flow. The mountains as ＂water towers＂ play important roles in water resources generation and the impact of mountain landscapes on hydrology is significant.

Determination of urban runoff coefficient using time series inverse modeling

Runoff coefficient is an important parameter for the decision support of urban stormwater management. However, factors like comprehensive land-use type, variable spatial elevation, dynamic rainfall and groundwater elevation, make the direct estimation of runoff coefficient difficult. This paper presented a novel method to estimate the urban runoff coefficient using the inverse method, where observed time-series catchment outfall flow volume was employed as input for the water balance model and runoff coefficients of different catchments were treated as unknown parameters. A developed constrained minimization objective function was combined to solve the model and minimized error between observed and modeled outfall flow is satisfactory for the presenting of a set of runoff coefficients. Estimated runoff coefficients for the urban catchments in Shanghai downtown area demonstrated that practice of low impact design could play an important role in reducing the urban runoff.

Estimation of Unit Flood Discharge for Various Land Use Types with a Focus on Urbanization

We proposed unit flood discharge model that defined as the discharge into end-order (smallest) drainage canals. The discharge acts an important role for estimating regional flooding by big rainfall events which leading roughly estimation of flood discharge associated with land use changes as urbanization. In some areas of Japan, increased urbanization with insufficient drainage canal capacity has led to increasingly frequent flooding and flood damage. The aim of this study was to investigate the effect of urbanization on unit flood discharge using a runoff model for the Tedori River alluvial fan area, Japan. The discharge was studied as collecting runoff from paddy fields, upland crop fields, and residential lots. A runoff model for various land use types in the study area was developed using actual and physical properties of the runoff sites, and parameters for paddy fields. The model was tested using 54 big events and inputted those. The maximum total runoff ratio among different land use types was observed for residential lots, and the ratio remained relatively constant across different flood events. The minimum total runoff ratio was observed for irrigated paddy fields. There was a positive relationship between the total runoff ratio and total precipitation for all land use types. Whereas, the relationship between the peak runoff ratio and peak precipitation was variable. The runoff analysis was carried out using 60-min and 10-min precipitation data. For agricultural land, data for both intervals produced similar results.

Simulation of snowmelt-runoff under climate change scenarios in a data-scarce mountain environment

Pakistan is an agriculture-based economy and major proportion of irrigation water for its cultivated lands is abstracted from the Upper Indus Basin(UIB).UIB water supplies are mostly contributed from the high-altitude snow and glacier fields situated in the Hindukush–Karakoram–Himalayan ranges.Any change in the flows of these river catchments due to climate variability may result in the form of catastrophic events like floods and droughts and hence will adversely affect the economy of Pakistan.This study aims to simulate snowmelt runoff in a mountainous sub-catchment(Shyok River basin)of the UIB under climate change scenarios.Snowmelt Runoff Model(SRM)coupled with remotely sensed snow cover product(MOD10A2)is used to simulate the snowmelt runoff under current and future climate scenarios in the study area.The results indicate that(a)SRM has efficiently simulated the flow in Shyok River with average Nash–Sutcliff coefficient value(R2)of 0.8(0.63–0.93)for all six years(2000–2006)of basin-wide and zone-wise simulations,(b)an increase of 10%(by 2050)and 20%(by 2075)in SCA will result in a flow rise of∼11%and∼20%,respectively,and(c)an increase of 1℃(by 2025),2℃(by 2050),3℃(by 2075)and 4℃(by 2100)in mean temperature will result in a flow rise of∼26%,∼54%,∼81%and∼118%,respectively.This study suggests that SRM equipped with remotely sensed snow cover data is an effective tool to estimate snowmelt runoff in high mountain data-scarce environments.

Evaluation of accuracy of linear regression models in predicting urban stormwater discharge characteristics

Stormwater runoff has been identified as a source of pollution for the environment, especially for receiving waters. In order to quantify and manage the impacts of stormwater runoff on the environment, predictive models and mathematical models have been developed. Predictive tools such as regression models have been widely used to predict stormwater discharge characteristics. Storm event characteristics, such as antecedent dry days （ADD）, have been related to response variables, such as pollutant loads and concentrations. However it has been a controversial issue among many studies to consider ADD as an important variable in predicting stormwater discharge characteristics. In this study, we examined the accuracy of general linear regression models in predicting discharge characteristics of roadway runoff. A total of 17 storm events were monitored in two highway segments, located in Gwangju, Korea. Data from the monitoring were used to calibrate United States Environmental Protection Agency＇s Storm Water Management Model （SWMM）. The calibrated SWMM was simulated for 55 storm events, and the results of total suspended solid （TSS） discharge loads and event mean concentrations （EMC） were extracted. From these data, linear regression models were developed. R2 and p-values of the regression of ADD for both TSS loads and EMCs were investigated. Results showed that pollutant loads were better predicted than pollutant EMC in the multiple regression models. Regression may not provide the true effect of site-specific characteristics, due to uncertainty in the data.