Modeling of groundwater level fluctuation in the tropical peatland area of Riau, Indonesia

Abstract

The groundwater level (GWL) is a key parameter for assessing the level of fire risk in the peatland so that if the predicted fluctuations of GWL in the next few days or weeks can be predicted; the risk of peat fire can also be estimated. The purpose of this study is to develop a hydrological model using regression analysis that can be used to predict GWL in the peatland. The data used for modeling were historically recorded of rainfall and GWL fluctuations from SESAME equipment in Dompas village, Riau, Indonesia. Regression analysis was carried out using four data length scenarios, such as one-month, two-months, three-months, and six-months to find out which time period could represent hydrological conditions in the field. The results showed that the regression analysis using three-months and six-months data represented the best results of the GWL prediction with a correlation coefficient of 0.95. However, the prediction using one-month and two-months data represented reasonable prediction results with a correlation coefficient of 0.86 and 0.89 respectively. Judging from observed and predicted GWL that was always in the lower position than 0.4 m depth, this area was always in the high risk of peat fire throughout the year.