Early Warning of Lake Level Fluctuations using Global Precipitation Measurement Data: A Case Study Nong Han Lake

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ประวิทย์ อ่วงอารีย์
ชัยณรงค์ เพียรภายลุน
ทรงพล ประโยชน์มี


This research investigated the possibility of using Global Precipitation Measurement Data (GPM) for early warning of Nong Han level fluctuations. The simple correlations between the input variables (such as the current lake level, the outflow rate, the evaporation rate, the daily precipitation, and the GPM data) and a target variable (the early-warning index of Nong Han lake level-fluctuations) were examined. Moreover, the early-warning model of level fluctuations hazard was developed, using GMDH-type neural networks. The results indicated that the correlations between of Nong Han level fluctuations with the current lake level and the outflow rate are high; and, the interrelationship between evaporation rate, the daily precipitation, and the GPM data is medium-low. The model evaluation, which uses blind data show the high ability of model with 90.5 % accuracy. The GPM data, thus, represents a helpful tool for early warning of lake level fluctuations.


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