Zexi Shen, Qiang Zhang, Vijay P. Singh, Peng Sun, Changqing Song, Huiqian Yu,
[Zexi Shen, Qiang Zhang, Changqing Song, Huiqian Yu]. Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing 100875, China.
[Zexi Shen, Qiang Zhang, Changqing Song, Huiqian Yu]. Faculty of Geographical Science, Academy of Disaster Reduction and Emergency Management, Beijing Normal University, Beijing 100875, China.
[Zexi Shen, Qiang Zhang, Changqing Song, Huiqian Yu]. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China.
[Vijay P. Singh]. Department of Biological and Agricultural Engineering and Zachry Department of Civil Engineering, Texas A&M University, College Station, Texas, USA.
[Peng Sun]. College of Territory Resources and Tourism, Anhui Normal University, Anhui 241000, China
Abstract: Agricultural drought is related to meteorological and hydrologic conditions and the resilience vegetation to water deficit that have negative impacts on agricultural production. In this study, an integrated drought condition index (IDCI) was developed by integrating precipitation, potential evapotranspiration, temperature, soil moisture, and vegetation conditions. The performance of IDCI in agricultural drought monitoring was evaluated by comparing with standing drought indices, such as sc-PDSI (self-calibrated Palmer Drought Severity Index), SMCI (Soil Moisture Condition Index), and SCYI (Scaled Crop Yields Index). Then, IDCI was used to characterize the spatiotemporal pattern of agricultural drought across Inner Mongolia, China. Results indicated that: (1) IDCI performed as well in drought monitoring as did sc-PDSI and SCYI. However, IDCI performed better than did SPEI3 (standardized precipitation evapotranspiration index at a time scale of 3 months), SMCI (Soil Moisture Condition Index) and VCI (Vegetation Condition Index) with respect to reliable and stable drought monitoring, detection of soil moisture and reflection of agricultural loss; (2) during the growing season (May-September), the frequency of droughts with higher than moderate drought intensity tended to be diminishing from May to August, and was amplifying again from August to September; (3) during 2000 to 2014, the drought severity was subject to regular variability with consecutive droughts during transitions between drought conditions; (4) compared to SMCI, VCI and SPEI3, IDCI is highly related to SCYI for maize with correlation coefficient of up to 0.788; the correlation coefficients between IDCI and SCYI for soybean and potato are larger than 0.5, while the SCYI for wheat is related to droughts with severe and even higher severity based on IDCI. The idea behind the development of IDCI can be referenced for drought monitoring in other regions of the globe.
Published in Journal of Hydrology, 2019, 571, 793-804.
