Climate change impact on precipitation and streamflow in a humid tropical watershed

Abstract

The increasing rate of the global surface temperature in climate change will have a significant impact on local hydrological regimes and water resources. This situation leads to the assessment of the climate change impacts has become a priority. The objectives of this study are to determine the current and future climate change scenario using the downscaling methods and to assess the climate change impact on stream flow discharge. It describes the investigation on precipitation and temperature changes which influenced by the large-scale atmospheric variables for several selected rainfall stations in the Kerian watershed and one selected temperature station in the Ipoh watershed, Peninsular Malaysia. In this study, the Global Climate Models (GCMs) simulations from Hadley Centre 3rd generation with scenario A2 (HadCM3 A2) have been used, and downscaled into a fine resolution daily rainfall and temperature series appropriate for local scale hydrological impact studies. The proposed downscaling methods applied in this study are the Long Ashton Research Station Weather Generator (LARS-WG) and Statistical Down-Scaling Model (SDSM). The changes in stream flow discharge are assessed using Identication of Unit Hydrograph and Component Flows from Rainfall, Evaporation and Streamflow Data (IHACRES) and Artificial Neural Networks (ANN) methods. It describes the investigation on possible future stream flow changes for four selected flow gauging stations represent the Kerian watershed. The SDSM and LARS-WG similarly are able to simulate the mean daily rainfall satisfactory. However, the SDSM model is better than the LARS-WG model in downscaling of the daily maximum and minimum temperature. Both models give an increase trend on projection of future temperature for all months. The LARS-WG and SDSM models obviously are feasible and reliable methods for use as tools in quantifying effects of climate change condition on a local scale. The rainfall and temperature data downscaled with the SDSM and LARS-WG models obviously are not similar in the simulation of stream flow discharge using the ANN and IHACRES models. ANN yields a better performance than IHACRES. The study area is apparently will gain consistently increasing trend in the mean annual temperature of about 0.24-4.23oC, and facing varying rainfall depth for the next 100 years. While the data downscaled with SDSM resulted in an increase in mean daily flow of about 10-40% in the coming 100 years, the one downscaled with LARS-WG resulted in a decrease in mean daily flow of up to 40%. This is a clear indication of how the outcome of a hydrologic impact study can be affected by the selection of any one particular downscaling technique over the other. The implication that the flood or drought may frequently experienced in the future corresponding to climate scenario HadCM3 A2.