13Borneo's diverse ecosystems, which are typical humid tropical conditions, are deteriorating 14 rapidly as the area is experiencing recurrent large-scale wildfires, affecting atmospheric 15 composition 1-4 and influencing regional climate processes 5,6 . Studies suggest that climate-16 driven drought regulates wildfires 2,7-9 , but these overlook subsurface processes leading to 17 hydrological drought, an important driver. Here, we show that models which include 18 hydrological processes better predict area burnt than those solely based on climate data. We been quantified yet. We show that including hydrology improves predictions of area burnt, 41 which so far typically are based on meteorology only. This is essential to predict future fire 42 extent particularly during strong during ENSO-driven droughts. groundwater dynamics is a key hydrological variable to understand the mechanism of the 46 drought-fire link (Fig. 1)
a b s t r a c tIn this paper, we discuss how an existing empirical drought index, i.e. the Keetch-Byram Drought Index (KBDI) that is commonly used for assessing forest fire danger, has been adjusted and modified for improved use in tropical wetland ecosystems. The improvement included: (i) adjustment of the drought factor to the local climate, and (ii) addition of the water table depth as a dynamic factor to control the drought index. We distinguished three different indices, the original Keetch-Byram Drought Index, the adjusted KBDI (KBDI adj ) that represents the original drought index, but including local climate information, and the modified KBDI (mKBDI) that considers both local climate information, and soil and hydrological characteristics. The mKBDI was developed and tested in a wetland forest of South Sumatra (Indonesia) from April 2009 to March 2011. During this period, hydrometeorological data were monitored and used to calculate the KBDI, KBDI adj , and mKBDI. First, mKBDI was calibrated using observed soil moisture that was converted to an observed drought index (DI obs ). The results indicate that performance of the mKBDI is encouraging based on the following: (i) its pattern followed the dynamics of DI obs , (ii) prediction of frequency of fire danger classes, and (iii) statistically criteria. The mKBDI clearly outperformed KBDI and KBDI adj . Furthermore, we found a critical water table depth when it reaches maximum fire danger (0.85 m for the wetland forest of South Sumatra) below which danger does not increase anymore. The mKBDI could be more widely applied, if pedotransfer functions are developed that link easily obtainable soil properties to the parameters of the water table factor. Our findings encourage land use planners, water managers and stakeholders (e.g. forest estate owners) to integrate local climate information, and soil and hydrological characteristics into the Keetch-Byram Drought Index to better predict fire danger, particularly in tropical wetland ecosystems.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.