Evaluasi Kesesuaian Lahan dan Optimasi Penggunaan Lahan untuk Pengembangan Tanaman Kakao (Theobroma Cacao L.) (Studi Kasus di Kecamatan Batee dan Kecamatan Padang Tiji Kabupaten Pidie Propinsi Aceh)

Tujuan dari penelitian ini adalah untuk mengetahui kelas kesesuaian lahan tanaman kakao; mengetahui pengaruh karakteristik lahan untuk pengembangan kakao dan memperoleh tingkat kelayakan USAhatani; dan optimalisasi penggunaan lahan berdasarkan kelas kesesuaian lahan. Kelas kesesuaian lahan didapatkan dengan mencocokkan sifat fisik dan kimia dari lahan USAhatani serta mengoverlaikan peta-peta yang sesuai dengan persyaratan tumbuh tanaman kakao dengan ArcGIS. Selanjutnya dihitung tingkat kelayakan USAhatani kakao dan dilakukan optimasi menggunakan QM for Windows untuk mendapatkan lahan optimum dengan keuntungan maksimum. Kelas kesesuaian lahan yang didapatkan di Kecamatan Batee: kelas S1 (sangat sesuai) sebesar 35,42% (2.572,622 ha); S2 (sesuai) sebesar 20,31% (1.922,737 ha) dan N (tidak sesuai) sebesar 44,27% (3.572,008 ha); serta di Kecamatan Padang Tiji: kelas S1 (sangat sesuai) sebesar 2,72% (306,173 ha); S2 (sesuai) sebesar 92,50% (10.429,770 ha); dan N (tidak sesuai) sebesar 4,79% (539,606 ha). Hasil analisis program linier menunjukkan bahwa luas lahan yang optimal digunakan seluas 3.475,065 ha. Keuntungan maksimum yang dapat diperoleh dengan luas lahan 3.475,065 ha adalah Rp 29.756.057.638,21 dimulai pada tahun produksi ke-7. Luas lahan aktual saat ini di Kec. Batee seluas 4.495,359 ha dan di Kec. Padang Tiji seluas 10.735,943 ha yang merupakan sumberdaya yang dapat ditingkatkan. Hal ini berarti masih besarnya ketersediaan lahan yang dapat dimanfaatkan untuk pengembangan tanaman kakao

Modeling Hydrologic Response to Land Use and Climate Change in the Krueng Jreu Sub Watershed of Aceh Besar

Soil and Water Assessment Tool (SWAT) model was used to simulate impact of landuse and climate change on water resources in Krueng Jreu subwatershed located in Aceh Province – Indonesia. The subwatershed is a primary source of water to irrigated 233.52 km2 paddy field area through a surface irrigation system. The model performance was considerably good in predicting streamflow. The coefficients of determination varied between 0.58 and 0.72, while the Nash-Sutcliffe coefficients (ENS) ranged between 0.65-0.72 and the percentage bias were in the range of -0.36 to 2.30. Scenarios were applied to the best fit model to evaluate watershed responses to land use and climate changes. The model predicted increases in both runoff and water yield by 1% and 0.1% respectively as the result of increasing 15% settlement area. When all agricultural land within subwatershed converted to forest, water yield would increase by 1% during dry period and runoff contribution would decrease by 5%. Increases in surface flow by 23.6% and water yield by 15.1% were found under scenario of increasing 10% of daily precipitation. Increasing in evapotranspiration caused by an increase of 1.5⁰C in daily air temperature would decrease surface flow and water yield by 0.8% and 1.3%, respectively. Combination scenarios of changes in daily temperature and precipitation would increase evapotranspiration rate, annual water yield and runoff contribution

Pemodelan Daerah Tangkapan Air Waduk Keliling Dengan Model SWAT

This study aimed to model watershed area of Keliling Reservoir using SWAT model. The reservoir is located in Aceh Besar District, Province of Aceh. The model was setup using 90m x 90m digital elevation model, land use data extracted from remote sensing data and soil characteristic obtained from laboratory analysis on soil samples. Model was calibrated using observed daily reservoir volume and the model performance was analyzed using RMSE-observations standard deviation ratio (RSR), Nash-Sutcliffe efficiency (NSE) and percent bias (PBIAS). The model delineated the study area into 3,448 Ha having 13 subwatersheds and 76 land units (HRUs). The watershed is mostly covered by forest (53%) and grassland (31%). The analysis revealed the 10 most sensitive parameters i.e. GW_DELAY, CN2, REVAPMN, ALPHA_BF, SOL_AWC, GW_REVAP, GWQMN, CH_K2 and ESCO. Model performances were categorized into very good for monthly reservoir volume with ENS 0.95, RSR 0.23, and PBIAS 2.97. The model performance decreased when it used to analyze daily reservoir inflow with ENS 0.55, RSR 0.67, and PBIAS 3.46