Development of Rainfall threshold model for the watershed/sub-watershed landscape at data scarce situation – a case study of mid-hill region, Nepal.

Abstract

<p>Landslides are common in the mid-hill region of Nepal where the terrain slopes are steep and consist of fragile geo-morphology. In Nepal, the casual and triggering factors of the landslides are respectively the underlying geology, intense rainfall and unplanned construction of rural roads is highly recognized, which is however less known and limited in study. Establishment of rainfall threshold for landslides at the watershed landscape is data driven, which is scared in the context of Nepal. The only available long term daily rainfall and sparsely available historical landslides date has been used to develop the rainfall threshold model for the two watersheds in central and western mid-hill regions respectively the Sindhukhola and Sotkhola in Bagmati and Karnali Provinces of Nepal. The watersheds are located in two distinct hydro-climatic regions in terms of rainfall amount and intensity. Historical daily (monsoonal) rainfall data of over four decades (1970-2016) were analyzed available from the Department of Hydrology and Meteorology (DHM)/Government of Nepal and five days’ antecedent rain was calculated. With the limitedly available temporal landslides data, correlation was examined among the 5-days antecedent rain (mm/5days) and daily rainfall (mm/day) portrayed the rainfall threshold (RT) model (Sindhukhola=180-1.07R<sub>T5adt</sub> and Sotkhola = 110-0.83*R<sub>T5adt</sub>). Utilizing the five days’ antecedent rain fitted into the model, results the threshold rainfall. Deducting the five days’ antecedent rains to the RT described the threshold exceedance (R) for the landslides. The model can be plotted in simple spreadsheet (landslides date in Y-axis and threshold exceedance R in X-axis) to visualize the changes in the threshold exceedance over time, whenever the threshold exceedance progressively and rapidly increased and crossed the threshold line and reached to the positive (> 0) zone, the plots allows for the landslides warning notice. In case of the threshold exceedance is further increased there is likely to have landslides in the watersheds. The model was validated with the 35 dated landslides recorded in monsoon 2015 in Sotkhola watershed. The result indicated that the model preserves 72% coefficient of determination (R<sup>2</sup>) where there were landslides in the watershed during 2015 monsoon. Due to the simplicity and at the data scarce situation, the model was found to be useful to forecast the landslides during the monsoon season in the region. The model; however, can be improved for better performance whenever the higher resolution time-series landslides data and automated weather stations are available in the watersheds. Linking this model to the proper landslide susceptibility map, and the real time rainfall data through mobile communication techniques, landslide early warning system can be established.</p><p><strong>KEYWORDS: </strong>landslide, rainfall threshold, data-scare, antecedent rainfall</p><p><strong>