Author
BESKOW, SAMUEL - Universidade Federal De Lavras | |
MELLO, CARLOS - Universidade Federal De Lavras | |
Norton, Lloyd | |
DA SILVA, ANTONIO - Universidade Federal De Lavras |
Submitted to: Catena
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 3/25/2011 Publication Date: 3/25/2011 Citation: Beskow, S., Mello, C.R., Norton, L.D., Da Silva, A.M. 2011. Performance of a distributed semi-conceptual hydrological model under tropical watershed conditions. Catena. 86:160-171. Interpretive Summary: Predicting water delivery from watersheds is needed for many practical reasons. The only way to predict the effects of changing land use or climate change scenarios on flow out of a watershed is to use simulation models. Most existing models are complex and require large amounts of input data to make an estimate of watershed flow or sediment delivery. In many cases sufficient data to drive these models does not exist especially in areas in developing countries. This paper reports on a new simple watershed hydrology model that was developed to easily estimate the water flow leaving a watershed with minimal data. It also reports on which input parameters are sensitive for the predictions and where potential for errors in the predictions may occur. It was tested for a medium sized watershed in the Brazilian tropical area which minimal data was available and predictions of water flow compared to actual flow. The model was found to be very simple to use and accurately predicted watershed flow. The impact of the development and validation of this model is that it can reliably be applied to other watersheds with limited data to evaluate the effects on future land-use or climatic changes on stream flow to drinking water supplies, hydro-electric facilities, irrigation systems and streams. Technical Abstract: Many hydrologic models have been developed to help manage natural resources all over the world. Nevertheless, most models have presented a high complexity in terms of data base requirements, as well as, many calibration parameters. This has resulted in serious difficulties to application in catchments which have a scarcity of data. The development of the Rio Grande Hydrologic Simulation Tool in a GIS framework (LASH) is described in this paper which focuses on its main components, parameters, and capabilities. Coupled with LASH, sensitivity analysis, parameter range reduction, and uncertainty analysis were performed prior to the calibration effort by using specific techniques (Morris method, Monte Carlo simulation and a Generalized Likelihood Uncertainity Equation (GLUE)) with a data base from a Brazilian Tropical Experimental Catchment (32 km2), in order to predict streamflow on a daily basis. LASH is a simple deterministic and spatially distributed model using long-term data sets, and a few maps to predict streamflow at a catchment's outlet. Based on the results found we were able to identify the most sensitive parameters using a reference catchment which are associated with the base flow and surface runoff components. Using a conservative threshold, two parameters had their range of values reduced, thus resulting in outputs closer to measured values and facilitating automatic calibration of the model with fewer iterations need to be run. GLUE was found to be an efficient method to analyze uncertainties related to the prediction of mean daily streamflow in the catchment. |