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Daerah Tangkapan waduk Jatiluhur berada diantara 107011'36” - 107032'36" BT and 6029'50" - 6040'45" LS di Jawa Barat, Indonesia. Area dengan luas 380 km2 merupakan 8% dari seluruh total area Hulu Sungai Citarum seluas 4500 km2. Fungsi dari daerah ini untuk memenuhi kebutuhan air untuk pertanian di Karawang dan Bekasi dan memenuhi kebutuhan air di Jakarta. Tujuan dari penelitian ini untuk meneliti dampak dari perubahan ik (Climate Changes) terhadap hasil hidrologi di daerah tangkapan. Perubahan iklim ditentukan oleh beberapa scenario perubahan iklim yang disiapkan sebagai input dalam SWAT hidrologi model. Simulasi dilakukan sesudah model dikalibrasi untuk mendapatkan parameter model yang sesuai dengan model hidrologi. Setelah itu model divalidasi untuk mengetahui bahwa model menggambarkan keadaan lapangan. hasil penelitian menunjukkan bahwa nilai-nilai limpasan dan hasil air yang bervariasi berdasarkan perubahan iklim. Oleh karena itu, perlu adanya untuk mempertimbangkan faktor-faktor perubahan iklim untuk mempelajari proses hidrologi di Daerah Tangkapan Air.Kata Kunci: SWAT, hidrologi, skenario perubahan iklim dan area tangkapan=Jatiluhur Reservoir Catchment Area is located between 107011'36” - 107032'36" BT and 6029'50" - 6040'45" LS in West Java, Indonesia. The catchment area embraces 380 km2, which is 8% of the total coverage area in the upstream of Citarum River with the total area of 4500 km2. The functions of this catchment are essential for meeting the needs of water for agriculture in Karawang and Bekasi area, and drinking water needs for Jakarta area. The purpose of this study was to investigate the impact of climate change on hydrology yield in the catchment. Changes in climate are discovered by several different climate changes scenarios, prepared as input for hydrological model SWAT. Simulation scenarios conducted after the model is calibrated in order to obtain model parameters that are sensitive to the hydrological response. Afterwards models are validated to find out that the model has described the state of the field. The result showed that the values of runoff and water yield are varies based on climate change. Therefore, there is a need to consider the factors of climate change in order to study hydrological process of a watershed.Keywords: SWAT, hydrology, climate changes scenarios and catchment areas.

Design: At the heart of time series forecasting, if nonlinear and nonstationary data are analyzed using traditional time series, the results will be biased. At the same time, if just using machine learning without any consideration given to input from traditional time series, not much information can be obtained from the results because the machine learning model is a black box. Purpose: In order to better study time series forecasting, we extend the combination of traditional time series and machine learning and propose a hybrid cascade neural network considering a metaheuristic optimization genetic algorithm in space–time forecasting. Finding: To further show the utility of the cascade neural network genetic algorithm, we use various scenarios for training and testing while also extending simulations by considering the activation functions SoftMax, radbas, logsig, and tribas on space–time forecasting of pollution data. During the simulation, we perform numerical metric evaluations using the root-mean-square error (RMSE), mean absolute error (MAE), and symmetric mean absolute percentage error (sMAPE) to demonstrate that our models provide high accuracy and speed up time-lapse computing.