Agricultural Drought Risk Assessment Based on a Comprehensive Model Using Geospatial Techniques in Songnen Plain, China

Fengjie Gao, Si Zhang, Rui Yu, Yafang Zhao, Yuxin Chen and Ying Zhang ()
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Fengjie Gao: School of Public Administration and Law, Northeast Agricultural University, Harbin 150036, China
Si Zhang: School of Public Administration and Law, Northeast Agricultural University, Harbin 150036, China
Rui Yu: School of Public Administration and Law, Northeast Agricultural University, Harbin 150036, China
Yafang Zhao: School of Public Administration and Law, Northeast Agricultural University, Harbin 150036, China
Yuxin Chen: School of Public Administration and Law, Northeast Agricultural University, Harbin 150036, China
Ying Zhang: School of Resources and Environment, Northeast Agricultural University, Harbin 150036, China

Land, 2023, vol. 12, issue 6, 1-19

Abstract: Drought is a damaging and costly natural disaster that will become more serious in the context of global climate change in the future. Constructing a reliable drought risk assessment model and presenting its spatial pattern could be significant for agricultural production. However, agricultural drought risk mapping scientifically still needs more effort. Considering the whole process of drought occurrence, this study developed a comprehensive agricultural drought risk assessment model that involved all risk components (exposure, hazard, vulnerability and mitigation capacity) and their associated criteria using geospatial techniques and fuzzy logic. The comprehensive model was applied in Songnen Plain to justify its applicability. ROC and AUC techniques were applied to evaluate its efficiency, and the prediction rate was 88.6%. The similar spatial distribution of water resources further verified the model’s reliability. The southwestern Songnen Plain is a very-high-risk (14.44%) region, determined by a high vulnerability, very high hazardousness and very low mitigation capacity, and is the region that should be paid the most attention to; the central part is a cross-risk region of high risk (24.68%) and moderate risk (27.28%) with a serious disturbance of human agricultural activities; the northeastern part is a dry grain production base with a relatively optimal agricultural production condition of very low risk (22.12%) and low risk (11.48%). Different drought mitigation strategies should be adopted in different regions due to different drought causes. The findings suggest that the proposed model is highly effective in mapping comprehensive drought risk for formulating strong drought mitigation strategies and could be used in other drought-prone areas.

Keywords: comprehensive agriculture drought risk assessment; fuzzy logic; spatial technique; mitigation capacity; Songnen Plain (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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