Climate-smart decision support system for assessing water demand patterns under future climate change for Kerian rice irrigation scheme, Malaysia

The uncertainty of water availability for irrigation supply affects the sustainable rice production under the likely evolving climate change impacts. In recent decades, the growth of populations and drastically economic development in urban areas have resulted in a severe water shortage in many countries with 70% of total global water used for the agricultural sector. Climatic changes cause an increase in temperature, changes in rainfall patterns and other hydrogeological variables. These changes will have adverse effects on hydrological systems and water resources management, which are important sources for agriculture. Therefore, analyzing the impacts of climate change on water demand and management of water resources systems to assess agricultural production, especially for rice, has become an important issue. This study attempted to customize Climate-smart Decision Support System (Climate- smart DSS) for Kerian Rice Irrigation Scheme for irrigation water demand patterns and optimal reservoir operation policy for the best water management practices in the scheme under the impacts of future climate change. The development of mitigative measures is very crucial to reduce likely water shortages. IADA Kerian Irrigation Scheme, located in Perak, Malaysia was chosen as a study area to examine the future irrigation water demand patterns for rice scheme. The Bukit Merah Reservoir consisted of 480 km² of Kurau River Basin the dominant part of the reservoir, which is the main source for irrigation supply to meet the water demand of the scheme. In this study, future climate variables were generated using Climate-smart DSS, a user-friendly MATLAB interactive program. It was developed to generate future climate variables (rainfall, temperature, relative humidity, and wind speed), which were used as inputs for hydrologic and optimal reservoir operation models using MATLAB software. Statistical downscaling technique, the delta change method was used to downscale 10 GCMs under three RCPs (RCP4.5, RCP6.0, and RCP8.5) for two future periods (2021- 2050 and 2051-2080) at the study area. The Soil and Water Assessment Tool (SWAT) hydrologic model was used to evaluate the impact of climate change on future streamflow of Kurau River Basin and inflow patterns of the reservoir. The model was evaluated using 30 years of historical period streamflow records (1976-2006) to predict the future (2021-2080) hydrologic response of the Kurau River Basin. The discharge obtained from SWAT output was used as input in simulating irrigation release from Bukit Merah Reservoir for Kerian Irrigation Scheme. The projected streamflow generally indicate reduction during the off- season/first season (February to July) and main-season/second season (August to January) when compared to historical records, which could be due to high surface warming in future. Water demand patterns of the IADA Kerian Rice Irrigation Scheme were analyzed considering with evolving climate change conditions to cope with the resilience of Bukit Merah Reservoir. Reference evapotranspiration (ETo) was estimated using improved Climate-smart DSS from projections of temperature (maximum and minimum), relative humidity, wind speed, and solar radiation using Penman-Monteith equation. Multi-models average was used to adequate effectively express the patterns of predicted future ETo at the Kurau River Basin. The ETo is predicted to increase for each RCP scenario for the two periods (2021-2050 and 2051-2080) concerning with respect to the baseline period with the highest increase predicted under RCP8.5. The model outputs indicate the future is predicted to have a high demand for irrigation water, especially during the off-season compared to main-season concerning with respect to the baseline period. Finally, Linear Programming (LP) using LINGO software was applied, used to develop programming codes and compute the optimal future release patterns of irrigation supply from the reservoir. Simulation of optimum release shows that the off- season of rice planting will suffer shortage conditions under future climate for RCP4.5, RCP6.0, and RCP8.5 scenarios. It is revealed that the excess streamflow stored during the main-season will meet the shortage of irrigation supply in the off-season irrigation periods from February to July. The filling period of the Bukit Merah Reservoir was identified for July, November, December, and January. In future, the high streamflow during the main-season will compensate the peak water demand during the off-season irrigation demand. This study provides valuable information for water demand patterns and optimal water operation policy and will help irrigation managers and policymakers for their adaptation plans for responding to climate change.

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