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Shandong Province, the main grain-producing area in China, has ranked first in China in terms of total agricultural output value for many years. However, droughts with high frequency and long duration have been hindering local agricultural production. This paper aims to assess the risk of drought disasters in Shandong Province. Firstly, based on the natural disaster system theory, an agricultural drought disaster risk assessment model is developed. This model is applied to assess the agricultural drought hazard, exposure, vulnerability, emergency response and recovery capability, and agricultural drought disaster risk from 2012 to 2020. Secondly, risk uncertainty is analyzed through the evolution of risk over the past years. Finally, the accuracy of the risk assessment is verified through agricultural drought-related losses. The results show that: (1) The risk assessment results are in good agreement with the actual drought losses. (2) From the spatial scale, the high-risk areas of agricultural drought disasters were mainly located in the western part of Shandong Province. High-hazard areas of drought were located in eastern Shandong Province, and areas with high agricultural exposure and vulnerability were concentrated in the western part of the province, and the emergency response and recovery capacity of Rizhao and Zaozhuang was low. (3) From the time scale, there was high uncertainty of agricultural drought disaster risk in Dongying, Qingdao, and Heze in 2012–2020, all of which had reached a high-risk level of agricultural drought disaster several times. The agricultural exposure in Dongying, the agricultural vulnerability in Heze, and the emergency response and recovery capacity in Heze and Linyi all showed an increasing trend. The interannual variation characteristics and spatial zoning of agricultural drought risk are explored, and it is instructive for risk decision-makers to better develop drought response measures and improve drought resilience. [ABSTRACT FROM AUTHOR]

Mastering the pattern of food loss caused by droughts and floods aids in planning the layout of agricultural production, determining the scale of drought and flood control projects, and reducing food loss. The Standardized Precipitation Evapotranspiration Index is calculated using monthly meteorological data from 1984 to 2020 in Shandong Province of China and is used to identify the province's drought and flood characteristics. Then, food losses due to droughts and floods are estimated separately from disaster loss data. Finally, the relationship between drought/flood-related factors and food losses is quantified using methods such as the Pearson correlation coefficient and linear regression. The results show that: 1) there is a trend of aridity in Shandong Province, and the drought characteristic variables are increasing yearly while flood duration and severity are decreasing. 2) The food losses caused by droughts in Shandong Province are more than those caused by floods, and the area where droughts and floods occur frequently is located in Linyi City. 3) The impact of precipitation on food loss due to drought/flood is significant, followed by potential evapotranspiration and temperature. 4) The relationship between drought and flood conditions and food losses can be precisely quantified. The accumulated drought duration of one month led to 1.939 × 104 t of grain loss, and an increase in cumulative flood duration of one month resulted in 1.134 × 104 t of grain loss. If the cumulative drought severity and average drought peak increased by one unit, food loss due to drought will increase by 1.562 × 104 t and 1.511 × 106 t, respectively. If the cumulative flood severity and average flood peak increase by one unit, food loss will increase by 8.470 × 103 t and 1.034 × 106 t, respectively. [ABSTRACT FROM AUTHOR]

[Display omitted] • Drought and flood risk assessment models for rainfed crops are proposed. • Drought and flood risk monitoring indicators for rainfed crops are established. • Drought and flood months associated with rainfed crop yields. • The probability of grain loss caused by different degrees of drought and flood. Rainfed agriculture ensures global food security. However, periodic droughts and floods endanger rainfed crop productivity. This work aims to identify drought and flood risks in rainfed agriculture using conditional probabilities and to reduce food losses caused by drought and floods. The standardized precipitation evapotranspiration index is produced from 1996 to 2020 using meteorological data from the three northeastern provinces and is used to establish four time-scale drought indicators. The Pearson correlation coefficient is then used to identify drought indicators related to rainfed crop production. The Copula-Bayesian conditional probabilities were used to calculate the probability of yield reduction of rainfed crops when drought indicators indicate varied drought and flood conditions. The results show that: (1) Droughts from May to July and floods from January to March had the most significant impact on rainfed crops in the three northeastern provinces. (2) The cities of Huludao, Changchun, Baishan, Baicheng, Yanbian, Hegang, and Jiamusi face a more significant danger of drought in rainfed crops. In contrast, Yichun and Suihua face a higher risk of flooding in rainfed crops. (3) When drought monitoring indicators decreased by one unit, rainfed crop output declined the most in Fuxin city; when the drought indicator increased by one unit, rainfed crop yield decreased the most in Liaoyuan city. The study's findings can provide quantitative direction for food security work in China's three northeastern regions. [ABSTRACT FROM AUTHOR]