Assessment of geostatistical methods for spatiotemporal analysis of drought patterns in East Texas, USA
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Drought is one of the most complex and least understood climate-related natural hazards. Active drought mitigation and contingency plan formulation often require a reliable drought distribution map. This study analyzed different spatial interpolation techniques to produce drought distribution map in East Texas, USA. Deterministic [inverse distance weighting (IDW) and spline], and geostatistical [ordinary kriging (Gaussian (KG) and spherical (KS))] interpolation techniques were employed as candidate methods for evaluation. Thirty-four years (1980–2013) of weather station data (N = 47) were used to calculate a 12-month Standardized Precipitation Evaporation Index (SPEI). The dataset was randomly divided into test data (70%, N = 33) and validation data (30%, N = 14). The resulting SPEI maps were cross-checked and validated through a validation dataset by calculating error matrices. The results indicate that KG tends to perform well in relatively drier conditions while IDW shows mixed results, performing well both in dry and wet conditions. The overall power of the four techniques to map 12-month drought conditions resulted in the order of IDW > KG > KS > spline.
KeywordsDrought Interpolation Inverse distance weighting Kriging SPEI Spline Validation
We would like to thank the NOAA Climate Data Online (CDO) program for providing data for this research. Sincere gratitude is also expressed to the Department of Physics and Geosciences, Texas A&M University-Kingsville, for providing access to the Geospatial Research Laboratory. Dr. W. Xi financially supported this work through his University Research Award, STEP-HG Faculty Research Award, and Research Startup Funds from Texas A&M University-Kingsville.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
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