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Quantitative Evaluation and Obstacle Factor Diagnosis of Agricultural Drought Disaster Risk Using Connection Number
Yi Cui1,2, Juliang Jin1,2, Xia Bai1,2
1School of Civil Engineering, Hefei University of Technology, Hefei 230009, China.
Entropy (Basel, Switzerland)
|July 27, 2022
Summary
This study introduces a new model for agricultural drought risk assessment using entropy concepts. The model found middle-risk status for drought in Suzhou, with risk decreasing since 2010, but exposure and resistance remain challenges.
Area of Science:
- Water Resources Management
- Environmental Science
- Risk Analysis
Background:
- Uncertainty analysis in complex water resource systems is crucial.
- Agricultural drought disaster risk requires effective quantitative evaluation and diagnosis.
Purpose of the Study:
- To propose a quantitative evaluation and obstacle factor diagnosis model for agricultural drought disaster risk.
- To apply entropy concepts and connection numbers for improved uncertainty analysis.
Main Methods:
- Utilized connection number and information entropy for model development.
- Applied the model to analyze agricultural drought disaster risk in Suzhou City from 2007-2017.
Main Results:
- Agricultural drought disaster risks in Suzhou were consistently in the middle-risk category.
- A decreasing trend in risk was observed from 2010 onwards.
- Information entropy analysis indicated that the difference degree item 'bI' provided more evaluative information than 'b'.
Conclusions:
- The proposed model is effective for regional drought disaster risk management.
- Reducing drought exposure and enhancing resistance capacity are key to lowering risk.
- Controlling agricultural population percentage, population density, and effective irrigation area are crucial for risk mitigation.
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