Assessment of deforestation and land cover change impacts on flood peak discharge in Maduru oya basin, Sri Lanka

Abstract

Population growth raises demand and competition for water resources and food stocks while it changes the landuse types by anthropogenic activities to adopt applicable measures for supplying water for domestic, agricultural, and industrial purposes. These changes alter the hydrological response of the river basins and can impose the communities to severe environmental risks like floods and landslides. Therefore, understanding of landuse change is crucial to study river basins’ behavior and take mitigatory measures. The study presented here quantifies and analyzes the historical deforestation and landuse/landcover (LULC) change impacts on flood peak discharge of the Maduru Oya river basin, Sri Lanka using Hydrologic Engineering Centre-Hydrologic Modeling System (HEC-HMS) and remote sensing techniques. The Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), and Operational Land Imager-thermal Infrared Sensor (OLI-TIRS) images are acquired in 1976, 1994, 2009, 2021 and classified using maximum likelihood algorithm of supervised classification. The analysis of LULC change revealed that LU change was faster and in high magnitude from 1976 to 1994 compared to the remaining period to 2021. The LULC change quantification by analyzing each scenario revealed a 24.9% deforestation while a 2.2%, 9.8%, 8.4%, and 4.5% increase in homestead/garden, paddy, scrubland, and water body between 1976 to 1994, respectively. The deforestation further continued to a rate of 4.1% and a 2.0% decrease in water bodies was also found in 2009 while homestead/garden, paddy, and scrubland continued to increase by 3.5%, 1.4%, and 1.5% compared to 1994 landuse scenario, respectively. In contrast, the 2021 landuse scenario indicated a 7.6% decrease in scrubland while 3.6%, 0.5%, 1.5%, and 1.8% increase in forests, homestead/garden, paddy, and water bodies. The classified images were subjected to accuracy assessment. The overall accuracy of 82%, 84%, 88%, and 91% are found for 1976, 1994, 2009, and 2021 LU scenarios while having kappa coefficients of 0.78, 0.80, 0.85, and 0.89 for respective years. The Normalized Difference Vegetation Index (NDVI) assessment of scenarios corresponds to the landuse classified images. An event-based HEC-HMS model is used to simulate the flood events in the Welikanda catchment of the Maduru Oya river basin. The model is calibrated and validated using the 1976 landuse and then the subsequent landuses are applied to study LU change impact on flood peak discharge. For model performance evaluation, the Nash-Sutcliffe, RMSE Observations Standard Deviation Ratio (RSR) Percent Bias (PBIAS), and the Coefficient of determination (R 2 ) were exploited. The average NSE, RSR, PBIAS, and R 2 values of 0.92, 0.25, 17.60, and 0.94 achieved in calibration and 0.73, 0.50, -3.03, and 0.78 are found in the validation which all can be rated very good performance except for PBIAS as satisfactory in calibration and NSE as good in the validation. The land cover change resulted in an increase (22.3%) in flood peak from 842 m 3 /s in 1976 to 1,030 m 3 /s in 2021. As a result of the landcover changes, the volume is also increased (42.3%) from 178.16 MCM in 1976 to 253.52 MCM in 2021. This study provides useful information for land and water managers, forests conservation units, and hydrologist to understand the LULC change impacts on floods and paves the way for broad LU and hydrological studies in Sri Lanka which are rarely conducted. The same approach can be applied in different parts of Sri Lanka which are exposed to severe LU changes.