INUNDATION MAPPING OF THE KADALUNDI RIVER BASIN USING HEC SOFTWARES

Abstract

Hydrological simulations using computer modelling has recently advanced significantly. Computerized models have become an essential tool for understanding changes in river flow due to human intervention and encroachments on river flows and designing water management approaches which are ecologically sustainable. The Malappuram district has been taken up as the study area since it experiences an average rainfall of 2900mm as compared to the national average of 1200mm. The region has experienced flooding in the years 2007, 2009 and 2018. The HEC-HMS software was used to simulate rainfall-runoff processes for the Kadalundi river flowing through the Malappuram district. The objective behind hydrologic simulation was to develop a model which is representative of the natural hydrological process of the river basin. Results in the form of hydrographs (discharge vs. time curve) has been obtained from hydrological modeling. The results obtained were validated using various statistical parameters such as NSE, RMSE and PBIAS. The value of NSE changed from 0.69 during the calibration phase of model to 0.52 during validation which is within the acceptable range. The value of PBIAS improved from -21.75 during calibration to -16.78 during the validation phase. The correlation coefficient remained nearly constant with a value of about 0.74 during the modeling. Based on these statistical parameters, the model could be used to predict discharge in the river basin from future precipitation events. The results also explain the sensitivity of the various process viz. transform, loss and baseflow methods, which are used in hydrologic simulations. Hydrographs obtained from hydrologic simulation in HEC-HMS are further used in HEC-RAS to prepare inundation maps for the year 2007. The result has been compared with inundation map due to actual discharge for the same year and a raster comparison has been done using the spatial analyst tool in Arc GIS which yields nearly 72% accuracy