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Optimization of irrigation water use to increase the benefit of agricultural products

Soentoro E.A.a, Perwira E.a, Suryadi Y.a, Winskayatib

a Water Resources Engineering Research Group, FCEE, Institut Teknologi Bandung, Bandung, Indonesia
b Citarum River Basin Authority, Ministry of Public Works and Housing, Indonesia

[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© The Authors, published by EDP Sciences, 2018.Shortage of irrigation water supply in dry season prevents many farmers from growing their crops, and the annual benefit from agricultural products will decrease as much as the area of irrigation fields which have lack of water. The objective of this study is to determine the maximum benefit from agricultural products based on water availability, by determining the appropriate cropping pattern and maximum planting areas through linear programming. The case-study location is at Leuwi Kuya Irrigation Region. Planting schedule is selected based on minimum water shortage from simulation of 6 alternative planting schedules. Then, the best pattern of cropping (planting method and the total area) is determined using linear programming. Optimization is carried out in 3 scenarios with various planting methods (conventional and SRI), minimum irrigation water demand (class-area system), and schedule for beginning of the 3-growing seasons annually. Result of this study is the optimal area of the irrigated region that can be planted based on the water availability. The maximum benefit is 89 billion rupiahs, using SRI planting method and distribution of three groups of irrigation fields in water supply schedule.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Cropping patterns,Irrigation water supply,Irrigation water use,Irrigation waters,Planting areas,Planting methods,Water availability,Water shortages[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Irrigation,Linear programming,Optimization,Planting area[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1051/matecconf/201815901026[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]