Wildfire Potential Mapping over the State of Mississippi: A Land Surface Modeling Approach

Cooke, William H.; Mostovoy, G.; Anantharaj, Valentine; Jolly, W. Matt

doi:10.2747/1548-1603.49.4.492

Cited by 18 publications

(8 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…1 Thus, accurately estimating rainfall in space and time is a fundamental task, for example, to detect drought-prone areas for agricultural purposes, 2 mapping the wildfire potential, 3 and for water balance studies. 4 However, to generate a reliable estimate of rainfall, it is necessary for the study area to have a dense monitoring network, with rain gauges distributed regularly throughout the area and with consistent records made.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the Tropical Rainfall Measuring Mission 3B43 product over an inland area in Brazil and the effects of satellite boost on rainfall estimates

Curtarelli

Rennó

Alcântara

2014

J. Appl. Remote Sens

View full text Add to dashboard Cite

Abstract. The main objective of this study was to evaluate the monthly mean areal rainfall estimated using the Tropical Rainfall Measuring Mission (TRMM) 3B43 version 7 product over an inland area in Central Brazil. Furthermore, we investigated the effect of TRMM orbit boost (in August 2001) over the 3B43 estimates. The TRMM 3B43 estimates were compared to reference rainfall data, collected at 67 rain gauge stations irregularly distributed in the study area. The results showed a good agreement between the TRMM 3B43 areal monthly mean rainfall estimations and reference data (r > 0.97). The error analysis showed that the TRMM 3B43 product tends to overestimate the areal monthly mean rainfall at approximately 1.24%. The root-mean-square error (RMSE) for the entire period was 19.66 mm month −1 (15.75%). A Monte Carlo simulation and Wilcoxon statistical test showed that the RMSE increased significantly (p-value <0.01) after the boost, rising from 15.20 to 23.06 mm month −1 . However, the increase in the RMSE does not preclude the use of the TRMM 3B43 product for estimating the monthly mean areal rainfall over the Upper Paraná watershed. The impacts of boost on TRMM 3B43 estimates were observed only for rainfall rates higher than 250 mm month −1 .

show abstract

Section: Introductionmentioning

confidence: 99%

Evaluation of the Tropical Rainfall Measuring Mission 3B43 product over an inland area in Brazil and the effects of satellite boost on rainfall estimates

Curtarelli

Rennó

Alcântara

2014

J. Appl. Remote Sens

View full text Add to dashboard Cite

show abstract

“…It can be used to examine other environmental variables, such as evapotranspiration, based on empirical or physically-based methods [1][2][3][4][5], and used as an input to many hydrological and crop models that require spatially and temporally continuous temperature information. Climate and land surface models also need observed temperature data to set boundary conditions for future simulations [6]. Maximum and minimum air temperature data may be obtained from the Global Historical Climatology Network (GHCN) with over 75,000 stations located in 180 countries [7].…”

Section: Introductionmentioning

confidence: 99%

Estimating High Spatial Resolution Air Temperature for Regions with Limited in situ Data Using MODIS Products

Rhee

2014

Remote Sensing

View full text Add to dashboard Cite

Abstract:The use of land surface temperature and vertical temperature profile data from Moderate Resolution Imaging Spectroradiometer (MODIS), to estimate high spatial resolution daily and monthly maximum and minimum 2 m above ground level (AGL) air temperatures for regions with limited in situ data was investigated. A diurnal air temperature change model was proposed to consider the differences between the MODIS overpass times and the times of daily maximum and minimum temperatures, resulting in the improvements of the estimation in terms of error values, especially for minimum air temperature. Both land surface temperature and vertical temperature profile data produced relatively high coefficient of determination values and small Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) values for air temperature estimation. The correction of the estimates using two gridded datasets, National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis and Climate Research Unit (CRU), was performed and the errors were reduced, especially for maximum air temperature. The correction of daily and monthly air temperature estimates using the NCEP/NCAR reanalysis data, however, still produced relatively large error values compared to existing studies, while the correction of monthly air temperature estimates using the CRU data significantly reduced the errors; the MAE values for estimating monthly maximum air temperature range between 1.73 °C and 1.86 °C. Uncorrected land surface temperature generally performed better for estimating monthly minimum air temperature and the MAE values range from 1.18 °C to 1.89 °C. The suggested OPEN ACCESSRemote Sens. 2014, 6 7361 methodology on a monthly time scale may be applied in many data sparse areas to be used for regional environmental and agricultural studies that require high spatial resolution air temperature data.

show abstract

“…Pook and Gill, 1993;Pellizzaro et al, 2007). Soil moisture deficit is therefore a good proxy for the fuel moisture content and hence to assess fire danger potential (Cooke et al, 2012). One of the drought indices specifically developed to assess fire danger is the Keetch-Byram Drought Index (Keetch and Byram, 1968).…”

Section: Introductionmentioning

confidence: 99%

Modification of a fire drought index for tropical wetland ecosystems by including water table depth

Taufik

Setiawan

Lanen

2015

Agricultural and Forest Meteorology

View full text Add to dashboard Cite

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.

show abstract

Wildfire Potential Mapping over the State of Mississippi: A Land Surface Modeling Approach

Cited by 18 publications

References 26 publications

Evaluation of the Tropical Rainfall Measuring Mission 3B43 product over an inland area in Brazil and the effects of satellite boost on rainfall estimates

Evaluation of the Tropical Rainfall Measuring Mission 3B43 product over an inland area in Brazil and the effects of satellite boost on rainfall estimates

Estimating High Spatial Resolution Air Temperature for Regions with Limited in situ Data Using MODIS Products

Modification of a fire drought index for tropical wetland ecosystems by including water table depth

Contact Info

Product

Resources

About