Lash Model: a Hydrological Simulation Tool in Gis Framework
Year: 2014
Type: dissertation
Abstract: Conceptual rainfall-runoff models at the watershed scale are useful tools for assisting in water resources management, making it possible to estimate hydrologic variables, i.e. streamflow and sediment yield, and to predict hydrologic impacts due to land-use changes. However, most models have presented a high complexity in terms of data base requirements, as well as, many calibration parameters, thus resulting in serious difficulties to application on ´data poor´ watersheds. The development of the Lavras Simulation of Hydrology (LASH) in a GIS framework is described in this dissertation, detailing its main components, parameters, and capabilities. This model was proposed in order to overcome difficulties in simulating watersheds which lack of input data. LASH is a simple deterministic, semi-physically based, spatially distributed model using long-term data sets, and a few maps to predict streamflow at a watersheds´ outlet. The main hydrologic components simulated by the LASH on a daily basis are surface runoff, sub-surface flow, base flow, capillary rise, evapotranspiration, interception of precipitation by vegetation, and soil water availability. The first application of the LASH model was with a data base from the Jaguara Experimental Watershed (JEW, 32 km2), located in southeastern Brazil, to predict streamflow on a daily basis. The JEW´s database used in the LASH model was composed of weather and discharge data sets as well as a few maps. An automatic weather station located in the JEW provided values of climatic variables over time, i.e. temperature, relative humidity, wind speed, solar radiation, and precipitation, whereas, discharge data were obtained from an automatic gauge station set up at the JEW´s outlet. A satellite imagery was acquired to allow the classification of the land-use types in the watershed and, consequently, derivation of other input parameters as a function of each land-use. A Digital Elevation Model (DEM) enabled the model to detect differences in relief, while a soil map allowed us to account for the spatial distribution of values of maximum soil water availability. Firstly, a 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 Equation (GLUE)). The LASH model was calibrated over a 2-year period using the Shuffled Complex Evolution (SCE-UA) global search method to optimize model parameters found to be the most sensitive or not directly measurable. Subsequently, the parameters obtained through calibration were kept constant for validation step using a different period of time from that analyzed during calibration. A sensitivity analysis enabled us to identify the most sensitive parameters, which are associated with the base flow and surface runoff. 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. Six parameters were calibrated, namely Kb, KSS, KCR, λ, CS, and CSS. The Nash-Sutcliffe coefficient (CNS) values found were 0.820 and 0.764 during calibration and validation, respectively, whereas, log (CNS) values equal to 0.821 and 0.770 were obtained for the same periods. The simulated Q90% was 0.131 m3 s-1, while the observed Q90% value was 0.122 m3 s -1, thus, there was an overestimating of only 7%. The model resulted in CNS values of 0.807, 0.821 and 0.983 for minimum discharge, maximum discharge and mean discharge, respectively. The sensitivity analysis, range adjustment and uncertainty analysis were found to be important, since they allowed reducing both the number of runs during calibration step and uncertainty associated with parameter ranges. The Shuffled Complex Evolution (SCE-UA) optimization method was found to be an efficient algorithm for finding ´optimal´ parameter values. The SCE-UA presented a high efficiency (acceptable CNS values in most runs) and had a fast convergence. Based on the results obtained during calibration and validation phases, we concluded that the LASH model has a great potential for being applied in generating minimum and maximum discharge, as well as flow-duration curves. Therefore, the model can reliably be successfully applied to this medium-sized watershed or other similar sized watersheds having as goal to provide design values for various hydraulic structures as well as soil conservation. Furthermore, the application of the LASH model can allow engineers to design irrigation systems and for estimating ecological discharge over different periods of year, thus taking into account the sustainable development in similar tropical and subtropical watersheds.
Author: Samuel Beskow
Language: English
Subfield: Water Science and Technology
Field: Environmental Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W1825123909