PERAMALAN CURAH HUJAN EKSTRIM DI PROVINSI BANTEN DENGAN MODEL EKSTRIM SPASIAL

A. Djuraidah, Cici Suheni, Banan Nabila
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引用次数: 6

Abstract

Extreme rainfall can cause negative impacts such as floods, landslides, and crop failures. Extreme rainfall modeling using spatial extreme models can provide location information of the event. Spatial extreme models combine the extreme value theory, the max-stable process, and the geostatistical correlation function of F-madogram. The estimation of the return value on the spatial extreme models is performed using the copula approach. This research used monthly rainfall data from January 1998 until December 2014 at 19 rain stations in Banten Province. The results showed that there was a high spatial dependence on extreme rainfall data in Banten Province. The forecast in range 1.5 years showed the best result compared to other ranges (1 year, 3 years, and 5 years) with MAPE 20%. The pattern of extreme rainfall forecasting was similar to its actual value with a correlation of 0.7 to 0.8. The predicted location that has the highest extreme rainfall was the Pandeglang Regency. Extreme rainfall forecasting at 19 rain stations in Banten Province using spatial extreme models produced a good forecasting.
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应用EXTRIM空间模型处理班滕省EXTRIM监测
极端降雨会造成洪水、山体滑坡和作物歉收等负面影响。使用空间极值模型的极端降雨建模可以提供事件的位置信息。空间极值模型结合了极值理论、最大稳定过程和F-madogram的地质统计相关函数。使用copula方法对空间极值模型的返回值进行估计。这项研究使用了万丹省19个雨量站1998年1月至2014年12月的月度降雨量数据。结果表明,万丹省的极端降雨数据具有高度的空间依赖性。与其他范围(1年、3年和5年)相比,1.5年范围内的预测显示出最好的结果,MAPE为20%。极端降雨量预测模式与其实际值相似,相关性为0.7至0.8。预测的极端降雨量最高的地区是潘德朗县。万丹省19个雨量站采用空间极值模型进行的极端降雨预报效果良好。
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