Evaluation of SCS - unit hydrograph model to estimate peak flows in watersheds of Norte de Santander

In several studies it is necessary to determine the magnitude of extreme flows in a river. Having an adequate register of observed discharge it is possible to adjust a probability density function (fdp) that allows estimating events associated with a high return period (i.e. 100 years). In ungauged basins, such as the majority of basins in the world are, other methodologies are used, such as the Synthetic Unity Hydrograph proposed by the United State Soil Conservation Service (UH-SCS). The UH-SCS model was evaluated in watersheds of the Norte de Santander department (COL), in its capacity to estimate extreme flows, and to explore its possible regionalization. The evaluation is done by comparing estimates of Q100, using the Frequency Factors method and the UH-SCS model. Discharge and precipitation time series were obtained from the IDEAM network, selecting 19 basins based on their drainage area, climatological stations density and records length. Geomorphology was characterized using ArcMap™ on the ASTER-GDEM digital elevation model. Using information available on geology, soils, vegetation cover, and assuming a wet antecedent moisture condition (AMC-III), values of the median of relative Q100 error (ε-Q100) of + 507% and + 406% were obtained for the fdp Gumbel and Log-Pearson. Using dry antecedent moisture condition (AMC-I) ε-Q100 low to + 36% and + 17%. It was possible to minimize ε-Q100 by calibrating the Curve Number (CN) parameter. A satisfactory regionalization function for CN was not found. Applying SCS-HU under AMC-III condition, Q100 is greatly overestimated. It is possible to minimize the error by considering AMC-I and reduce CN, a counter-intuitive situation since extreme flows are associated with wet weather conditions (i.e. Año Niña). Improvements in the characterization of rainfall and soils in Norte de Santander should be investigated.

Effect of Watershed Subdivision and Antecedent Moisture Condition on HEC-HMS Model Performance in the Maha Oya Basin, Sri Lanka

In large scale watersheds, the accuracy level of medium and low flow simulation could decrease due to uncertainty of the watershed parameters. In hydrological modeling, sub division of watershed would help to better implement decision-making related to water resources management, which relies heavily on hydrologic simulations. However, an important concern will be raised over problems associated with lumped hydrologic models with watershed subdivision broadly applied in so called semi-distributed hydrological models since scale issues would significantly affect model performance, and thus, lead to dramatic variations in simulation results. It is important to achieve the appropriate level of sub divisions (discretization). Further at times, the resulting flood level can be much higher than expected, due to storm events. This is unprecedented and the reason may be due to saturated moisture level in the soil layer. Therefore, the Antecedent Moisture Condition (AMC) is an important parameter to be investigated to check the accuracy and possibility of further improvement of the model. In this paper, Hydrologic Modeling System (HEC-HMS) was used for continuous simulation to investigate the effect of watershed subdivision on the model performance. Further, the antecedent moisture condition (AMC) events were used to study the impacts of AMC on the model performance. Badalgama watershed is selected as study area in Maha Oya Basin in Sri Lanka. Spatial extents of Maha Oya Basin and Badalgama watershed are 1553 km² and 1272 km², respectively. Four rainfall stations and one river gauging station were selected in Badalgama watershed. Nash–Sutcliffe (NASH) coefficient and Mean Ratio of Absolute Error (MRAE) were selected as objective functions for modeling. The main focus was on MRAE, as the objective function, but Nash coefficient was also estimated and checked for comparison. In particular, results show that generally the accuracy of the model decreased from six to sixteen sub divisions, which shows that variation in the total number of sub watersheds had very little effect on runoff hydrographs and improvements generally disappear when the number of subdivisions reaches a relatively small number, approximately between six and sixteen sub-watersheds. The accuracy of the model with AMC-III increased by 12.04% when compared to AMC-II hence showing more reliable results as compared with AMC-II condition. In this research, recession method was used for base flow estimation, which led to mass balance error exceeding 20%. Therefore it is recommended that for improving the accuracy, linear reservoir method for base flow estimation should be used in order to conserve the water balance and AMC-III should be used for fully saturated soil instead of AMC-II.