OPEN AGENT BASED RUNOFF AND EROSION SIMULATION (OARES): A GENERIC CROSS PLATFORM TOOL FOR SPATIO-TEMPORAL WATERSHED MONITORING USING CLIMATE FORECAST SYSTEM REANALYSIS WEATHER DATA
The aim of this study is to explore the applicability of Agent Based Modelling (ABM) for the simulation of rainfall runoff and soil erosion used in a watershed monitoring activity. The study utilizes Landsat 8 imagery for Land Use Land Cover (LULC) map generation, ASTER DEM for obtaining elevation information and Climate Forecast System Reanalysis (CFSR) 36 year weather data of Asan watershed, Uttarakhand, India. In the proposed model, four major agents (raindrops, soil, elevation and water amount) have been defined for estimating the soil erosion in the region. Moreover, the direct runoff has been simulated using the Soil Conservation Service (SCS) method. The analysis of the entire time series using this approach shows that there have been substantial changes in the rainfall runoff pattern primarily due to the varying environmental conditions of the study area since the late 1980s. Furthermore, a rough estimate of the soil erosion and deposition in the area have been computed which is aligned with the theory of sediment transport and deposition. In order to automate the entire model workflow, an open source cross platform tool has been developed using Python, R and NetLogo libraries. The Open Agent Based Runoff and Erosion Simulation (OARES) tool incorporates a generic interface for analysing large spatio-temporal datasets in watershed studies. The overall analysis concludes that the results obtained using ABM are comparable to that of the conventional hydrological models, and henceforth, ABM could be utilized as a future potential hydrological modelling paradigm.