Development, sensitivity and uncertainty analysis of LASH model

Abstract

Many hydrologic models have been developed to help manage natural resources all over the world. Nevertheless, most models have presented a high complexity regarding data base requirements, as well as, many calibration parameters. This has brought serious difficulties for applying them in watersheds where there is scarcity of data. The development of the Lavras Simulation of Hydrology (LASH) in a GIS framework is described in this study, 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 Uncertainty Estimation -GLUE) with a data base from a Brazilian Tropical Experimental Watershed (32 km 2 ), 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 watershed outlet. We were able to identify the most sensitive parameters which are associated with the base flow and surface runoff components, using a reference watershed. 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 less required iterations. GLUE was found to be an efficient method to analyze uncertainties related to the prediction of mean daily streamflow in the watershed.

Modelagem Hidrológica Determinística Chuva-Vazão Em Bacias Hidrográficas: Uma Abordagem Introdutória

“…No entanto, uma vez que as funções empíricas associadas aos componentes físicos são frequentemente usadas em modelos conceituais, alguns hidrólogos preferem classificar os modelos como semi-conceituais ou fisicamente baseados. O primeiro inclui as características dos processsos, mas os parâmetros das equações tem um nível razoável de empirismo; o segundo emprega equações diferenciais para representar os processos, sendo seus parâmetros mais representativos da realidade física (BESKOW, 2009).…”

Agricultural watershed modeling: a review for hydrology and soil erosion processes

“…However, when the researchers first discussed the model structure, they drew the conclusion that the great challenge would be the necessity of developing a model compatible with the reality of developing countries in terms of both hydrological processes and lack of data base availability. The first applications of LASH to Brazilian watersheds were reported in the studies of Mello et al (2008), who employed the model in a semi-distributed and lumped approach, and of Beskow et al (2011) who applied LASH in its grid-cell spatially distributed approach.…”

“…• Kss (mm day -1 ): hydraulic conductivity of the subsurface soil layer, varying from 0 to 182.4 (Rawls et al, 1993) From the work of Beskow et al (2011) and Beskow, Mello and Norton (2011), the LASH model now works within a GIS environment, making it a distributed model by cells. Each step described before is run over a cell whose size will be defined by the users, as presented in the following figure (Figure 2), elaborated by Beskow et al (2011).…”

“…Each step described before is run over a cell whose size will be defined by the users, as presented in the following figure (Figure 2), elaborated by Beskow et al (2011).…”

“…Having this spatial reference for the LASH model application, Beskow et al (2011) and Beskow, Mello and Norton (2011) developed a mathematical procedure for its calibration:…”