Assessment of Extreme Precipitation for Developing Agricultural Adaptation Strategy in the Selo Watershed Area

Sugeng Nugroho, Rudi Febriamansyah, N. Nurhamidah, Dodo Gunawan
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Abstract

The ongoing climate change resulting from the effects of global warming is manifested through increased variability and a rise in extreme precipitation events. Given this situation, it becomes imperative for farmers to adapt to these changes to ensure the long-term sustainability of their businesses. Therefore, this research aimed to assess extreme precipitation for planning adaptation strategies for agricultural water resources in the Selo watershed, Tanah Datar Regency, West Sumatra Province, Indonesia. Climate Hazards Group Infrared Precipitation and Stations (CHIRPS) data were used to accomplish this, spanning 1981 to 2020. A set of indices recommended by ETCCDI, including PRCPTOT, CDD, CWD, R95p, R99p, SDII, R10mm, R20mm, R30mm, and R40mm were employed to assess extreme precipitation. Climate Data Operator (CDO) and GrADS were conducted for downscale and plotting data. Furthermore, the Mann-Kendall test was conducted to determine the significance of change trends in the indices. R-Climdex was used to determine the extreme event based on the data used. The results showed that all indices indicated wet conditions during the period 1981-2020. The topographic characteristics of the watershed served as a basis for selecting suitable adaptation strategies within the agricultural water resources sector. One potential approach involves integrating conservation-based adaptation practices with comprehensive watershed management techniques. Factors such as the area’s sensitivity to changes in the total intensity or frequency of precipitation, combined with the local environmental conditions, can be considered in determining the optimal adaptation approach.
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塞洛流域制定农业适应战略的极端降水评估
由全球变暖影响造成的持续气候变化表现为变率增加和极端降水事件增加。鉴于这种情况,农民必须适应这些变化,以确保其业务的长期可持续性。因此,本研究旨在评估印度尼西亚西苏门答腊省Tanah Datar Regency Selo流域的极端降水,以规划农业水资源适应策略。气候灾害组织红外降水和台站(CHIRPS)的数据用于完成这项工作,时间跨度为1981年至2020年。采用中国气象中心推荐的PRCPTOT、CDD、CWD、R95p、R99p、SDII、R10mm、R20mm、R30mm、R40mm等指标对极端降水进行评价。气候数据操作(CDO)和梯度(gradient)对小尺度和标绘数据进行了处理。通过Mann-Kendall检验确定各指标变化趋势的显著性。使用R-Climdex根据所使用的数据确定极端事件。结果表明:1981—2020年,各指标均表现出湿润状态。流域的地形特征是在农业水资源部门选择适当的适应战略的基础。一种可能的办法是将基于保护的适应实践与综合流域管理技术结合起来。在确定最佳适应方法时,可以考虑该地区对降水总强度或频率变化的敏感性以及当地环境条件等因素。
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来源期刊
International Journal on Advanced Science, Engineering and Information Technology
International Journal on Advanced Science, Engineering and Information Technology Agricultural and Biological Sciences-Agricultural and Biological Sciences (all)
CiteScore
1.40
自引率
0.00%
发文量
272
期刊介绍: International Journal on Advanced Science, Engineering and Information Technology (IJASEIT) is an international peer-reviewed journal dedicated to interchange for the results of high quality research in all aspect of science, engineering and information technology. The journal publishes state-of-art papers in fundamental theory, experiments and simulation, as well as applications, with a systematic proposed method, sufficient review on previous works, expanded discussion and concise conclusion. As our commitment to the advancement of science and technology, the IJASEIT follows the open access policy that allows the published articles freely available online without any subscription. The journal scopes include (but not limited to) the followings: -Science: Bioscience & Biotechnology. Chemistry & Food Technology, Environmental, Health Science, Mathematics & Statistics, Applied Physics -Engineering: Architecture, Chemical & Process, Civil & structural, Electrical, Electronic & Systems, Geological & Mining Engineering, Mechanical & Materials -Information Science & Technology: Artificial Intelligence, Computer Science, E-Learning & Multimedia, Information System, Internet & Mobile Computing
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