@article{08775d8c862e47949834276e163a49eb,
title = "Gauging the severity of the 2012 Midwestern U.S. drought for agriculture",
abstract = "Different drought indices often provide different diagnoses of drought severity, making it difficult to determine the best way to evaluate these different drought monitoring results. Additionally, the ability of a newly proposed drought index, the Process-based Accumulated Drought Index (PADI) has not yet been tested in United States. In this study, we quantified the severity of 2012 drought which affected the agricultural output for much of the Midwestern US. We used several popular drought indices, including the Standardized Precipitation Index and Standardized Precipitation Evapotranspiration Index with multiple time scales, Palmer Drought Severity Index, Palmer Z-index, VegDRI, and PADI by comparing the spatial distribution, temporal evolution, and crop impacts produced by each of these indices with the United States Drought Monitor. Results suggested this drought incubated around June 2011 and ended in May 2013. While different drought indices depicted drought severity variously. SPI outperformed SPEI and has decent correlation with yield loss especially at a 6 months scale and in the middle growth season, while VegDRI and PADI demonstrated the highest correlation especially in late growth season, indicating they are complementary and should be used together. These results are valuable for comparing and understanding the different performances of drought indices in the Midwestern US.",
author = "Xiang Zhang and Chehan Wei and Renee Obringer and Deren Li and Nengcheng Chen and Dev Niyogi",
note = "Funding Information: Acknowledgments: Xiang was supported by the China Scholarship Council (CSC) under the State Scholarship Fund to pursue his study at Purdue University (No. 201506270080). DN acknowledges support from NSF CAREER AGS 0847472, USDA/NIFA grant on drought triggers and global trade 2011–67019–20042 and 2015–67023–23109, USDA NIFA Hatch project 1007699, and the financial support given by the Earth System Science Organization, Ministry of Earth Sciences, Government of India (Grant No./Project No. MM/SERP/CNRS/2013/INT-10/002) to conduct this research under Monsoon Mission. Nengcheng acknowledges support from Union Foundation of Ministry of Education of the People{\textquoteright}s Republic of China (6141A02022318), Creative Research Groups of Natural Science Foundation of Hubei Province of China (2016CFA003), and the Fundamental Research Funds for the Central Universities (2042017GF0057). The authors acknowledge the Multi-Resolution Land Characteristics Consortium (MRLC) for providing NLCD 2011 land cover data, the National Drought Mitigation Center for US Drought Monitor data, NLDAS for NLDAS_NOAH0125_M precipitation and soil moisture data, NOAA for AVHRR VHP data, USGS for VegDRI data, Dai Aiguo at University at Albany for sc_PDSI_pm data, Amir AghaKouchak in UC Irvine for the Standardized Drought Analysis Toolbox (SDAT) to calculate SPI, USDA NASS for corn growth and yield data, Global SPEI database for SPEI, West Wide Drought Tracker for Palmer Z-index. We thank three anonymous reviewers for their thoughtful comments and suggestions which led to substantial improvements in the manuscript. Publisher Copyright: {\textcopyright} 2017 by the authors.",
year = "2017",
month = aug,
day = "1",
doi = "10.3390/rs9080767",
language = "English (US)",
volume = "9",
journal = "Remote Sensing",
issn = "2072-4292",
publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",
number = "8",
}