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Evaluation of Drought Vulnerability of Maize and Influencing Factors in Songliao Plain Based on the SE-DEA-Tobit Model. REMOTE SENSING 2022. [DOI: 10.3390/rs14153711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Rain-fed agriculture is easily affected by meteorological disasters, especially drought. As an important factor of risk formation, actively carrying out agricultural drought vulnerability assessments is conducive to improving food security and reducing economic losses. In this study, an SE-DEA model with regional exposure and drought risk as input factors and the maize yield reduction rate and drought-affected area as output factors is established. The aim is to evaluate and zone the drought vulnerability of the maize belt in the Songliao Plain. The results show the following: (1) From 2000 to 2019, the drought vulnerability of maize showed a fluctuating increasing trend. The vulnerability in Harbin and central Jilin Province is high, which is extremely unfavorable for maize production. (2) Comparing the historical disaster data with the drought vulnerability map generated using the SE-DEA model, it could be found that the results obtained using the SE-DEA model are reliable. (3) The Tobit model shows that the proportion of the effective irrigated area is more important to alleviate vulnerability. For drought vulnerability zoning using a cluster analysis, we suggest that regulated deficit irrigation should be actively developed in high-vulnerability areas to ensure maize yield while improving water efficiency. The results of this study can provide a basis for the development of drought mitigation and loss reduction strategies, and they provide new ideas for future research.
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Identification and Risk Characteristics of Agricultural Drought Disaster Events Based on the Copula Function in Northeast China. ATMOSPHERE 2022. [DOI: 10.3390/atmos13081234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
Accurate feature identification of drought disaster events is required for proper risk management in agriculture. This study improved the crop water deficit index (CWDI) by including the daily meteorological, crop development stage, soil moisture content, and yield data for 1981–2020 in northeastern China. Two drought characteristic variables (drought duration and intensity) were extracted using the theory of runs to produce the improved crop water deficit index (CWDIwp). Thresholds for the bivariate indicators were also determined for agricultural drought events of varying severity. A joint distribution model for drought variables was constructed based on five types of Archimedean copulas. The joint probability and the joint recurrence period for agricultural drought events were analyzed for drought events with varying intensities in northeast China. The results suggest that the CWDIwp can reliably identify the onset, duration, and intensity of drought events over the study area and can be used to monitor agricultural drought events. The conditional probability of drought intensity (duration) decreased as the drought duration (intensity) threshold increased, whereas the drought recurrence period increased as the threshold for drought duration and intensity rose. In the period (1981–2020), drought intensity in the three Northeastern provinces showed an increasing trend in the order Jilin Province > Liaoning Province > Heilongjiang Province. The spatial distribution of the joint probability and the joint recurrence period was obvious, and the joint probability showed a decreasing distribution trend from west to east. The distribution trend for the joint probability was opposite to that of the joint recurrence period. Furthermore, the areas with high drought probability values corresponded to the areas with low values for the recurrence period, indicating that the drought occurrence probability was higher, and the recurrence period value was lower in the drought-prone areas. The high-risk drought areas (60–87%) were in western Liaoning and western Jilin, with a recurrence period of 1–3 years, whereas the low-risk areas (<40%) were located in the mountainous areas of eastern Liaoning and eastern Jilin. The joint probability and joint recurrence period for agricultural drought events of varying severity were quite different, with the probability following the order light drought > moderate drought > severe drought > extreme drought. The order for the recurrence period was light drought < moderate drought < severe drought < extreme drought. The results provide technical support for disaster prevention and mitigation in drought risk management.
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Assessment of Maize Drought Risk in Midwestern Jilin Province: A Comparative Analysis of TOPSIS and VIKOR Models. REMOTE SENSING 2022. [DOI: 10.3390/rs14102399] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Drought is a major natural disaster that causes a reduction in rain-fed maize yield. Agricultural drought risk assessment is conducive to improving regional disaster management ability, thereby reducing food security risks and economic losses. Considering the complexity of risk assessment research, an increasing number of researchers are focusing on the multiple-criteria decision-making (MCDM) method. However, the applicability of the MCDM method to agro-meteorological disaster risk assessments is not clear. Therefore, this study comprehensively evaluated hazard, exposure, vulnerability, and emergency response and recovery capability using the TOPSIS and VIKOR models to generate a maize drought risk map in mid-western Jilin Province and ranked the drought risk of each county. The results showed that: (1) maize drought risk in the middle and west of Jilin province showed an increasing trend. Spatially, the risk diminished from west to east. The drought risks faced by Tongyu, Changchun, and Dehui were more severe; (2) the evaluation results of the two models were verified using the yield reduction rate. The VIKOR model was found to be more suitable for agrometeorological drought risk assessments; (3) according to the damage degree of drought disaster to maize, the cluster analysis method was used to divide the study area into three sub-regions: safe, moderate drought, and severe drought. Combined with the characteristics of different regions, suggestions on disaster prevention and mitigation are proposed. The results of this study can provide a basis for formulating strategies to alleviate drought, reduce losses, and ensure the sustainable development of agriculture.
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