In recent years, several empirical and mathematical methods have been developed to estimate runof, among which the SCS curve number (SCS-CN) method is one of the simplest and most widely used methods. The SCS-CN depends mainly on a CN parameter which corresponds to various soil, land cover, and land management conditions, selected from look-up tables. An application of GIS and RS techniques along with fled investigations made it possible to enhance the method from a lumped one to the level of semi-distributed models in which a specifc value can be assigned to each cell in raster maps. The up-to-date procedures require several datasets, feld measurements and overlying issues which limits the use of SCS-CN in data-scarce regions. In this research a new method has been developed which estimates the SCS-CN over the catchment with a minimum input dataset and acceptable accuracy and is based on the saturation-excess concept, which is used in the semi-distributed model: TOPMODEL. The proposed method depends on three parameters, including ndrain (soil porosity), z̄ (average distance to watershed water table surface) and m (which controls the efective depth of the saturated soil) and one input dataset, the so-called topographic index. Results showed that the maximum and minimum diferences between the basin-averaged CN based on the GIS and RS techniques and the proposed method for Kasilian and Jong watersheds are 12% and 0.3%, respectively. Also, the fndings indicated that, of the three parameters of proposed method, the m parameter plays a key role and that by increasing this parameter the basin-averaged CN tends to decrease and vice versa. Because of the dependence on a topographic index, the proposed method is strongly afected by DEM resolution and there are signifcant diferences between low and high-resolution DEMs. However, for a small scale watershed, similar to Kasilian, using DEMs with resolution lower than 100 m considerably decreases the above diferences. As an overall conclusion, the proposed method provides acceptable values of SCS-CN which is important for running rainfall-runof model in a data-limited or data-scarce regions. In addition, creating the gridded map for CN, which is required in most hydrological models, is one of the most important advantages of the proposed method.
2
Dostęp do pełnego tekstu na zewnętrznej witrynie WWW
River basins located in the Central Sudetes (SW Poland) demonstrate a high vulnerability to flooding. Four mountainous basins and the corresponding outlets have been chosen for modeling the streamflow dynamics using TOPMODEL, a physically based semi-distributed topohydrological model. The model has been calibrated using the Monte Carlo approach—with discharge, rainfall, and evapotranspiration data used to estimate the parameters. The overall performance of the model was judged by interpreting the efficiency measures. TOPMODEL was able to reproduce the main pattern of the hydrograph with acceptable accuracy for two of the investigated catchments. However, it failed to simulate the hydrological response in the remaining two catchments. The best performing data set obtained Nash-Sutcliffe efficiency of 0.78. This data set was chosen to conduct a detailed analysis aiming to estimate the optimal timespan of input data for which TOPMODEL performs best. The best fit was attained for the half-year time span. The model was validated and found to reveal good skills.
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.