Abstract
For many years, the active management of the Jurang Sate Hulu Irrigation Area has provided significant benefits to cropping patterns. However, the impacts of climate change on water availability and temperature variations present critical challenges to crop productivity. Therefore, an analysis of the effects of climate change is essential. The methods employed in the analysis of climate change include correlation and regression methods. This study uses nine variables of global climate change. The correlation method is applied to determine the extent of the influence of global climate variables, represented by Global Circulation Model (GCM) data, on rainfall and climate in the Jurang Sate Hulu Irrigation Area. The regression method is used to validate the prediction model for rainfall from 2024 to 2100. In the cropping pattern analysis, the Penman-Monteith method is used to calculate evapotranspiration, while the F.J. Mock method is used to calculate flow discharge. Based on the analysis, the global climate variables that most significantly influence rainfall in the Jurang Sate Hulu Irrigation Area are air temperature, wind speed, eastward wind, and surface temperature, with maximum correlation values of 0.551, 0.540, 0.589, and 0.625, respectively. In contrast, local climate variables have less influence, as they yield correlation values below 0.500. The regression analysis showed an average validation result for the selected model using two goodness-of-fit parameters: Root Mean Square Error (RMSE) of 124.371 and Nash-Sutcliffe Efficiency (NSE) of 0.403. The highest irrigation water requirement occurs during the third planting period, from 2051 to 2075, at 0.465 m³/s. The planned cropping pattern is paddy-paddy-second crops, with planting areas of 3,807 hectares for the period from 2024 to 2050, 3,595 hectares for the period from 2051 to 2075, and 3,383 hectares for the period from 2076 to 2100, with a total planting intensity of 300% during each period.
Published Version
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