PEMODELAN HUJAN DEBIT UNTUK ANALISIS KEKERINGAN PADA DAS TEMON

Abstract

Drought is a natural phenomenon highly affecting the availability of ground water reserve, required for either farminginterest or human need. In some areas, the water availability can be met and in certain period of time, it can be criticalbecause its amount is reduced substantially. Drought occurs not only because the decreased rainfall, but also becausethe decreased soil penetration/accommodation power as the result of the damaged penetration areas due to the inappropriateland use.This study employed a simulated neuron network Artificial Neural Network that was a mathematical model with linearfunction to generate flow rate. The drought analysis built on the drought threshold with probability of 0.5 called Qnormal(Q50). From the resulted flow rate, the deficit and drought duration, as well as the beginning of dry season every year,would be estimated.From the result of analysis it could be seen that nearly every year from 2007 to 2012 in certain month, the flow ratewas lower than the normal one (Q50), thereby there was a potential drought every year. The highest drought deficit was19.870m3 /s occurring in 2012, while, the longest drought duration occurred on the average for six months in 2007,2008, 2009, and 2012 from May to October. The beginning of dry season time was different each year and occurred inthe first month when the flow rate was lower than the normal one (Q50).