With the impacts of climate change and human activities, agricultural drought disaster losses have increased remarkably. Drought disaster risk assessment is a prerequisite for formulating disaster reduction strategies and ensuring food security. However, drought disaster risk is a complex system, and quantitative assessment methods reflecting the risk formation mechanism are still rarely reported. This study presented a chain transmission system structure of drought disaster risk, which meant that drought disaster loss risk R was derived from drought hazard H by the transformation of drought disaster vulnerability V. Based on this point, firstly, a drought hazard curve between drought intensity and drought frequency was established using remote sensing data and the copula function. Then, a crop loss calculation approach under various drought events and drought resistance capacity scenarios was achieved by two-season field experiments and the AquaCrop model. Finally, a loss risk curve cluster of “drought frequency–drought resistance capacity–yield loss rate” was proposed by the composition of the above two quantitative relationships. The results of the case study for summer maize in Bengbu City indicated that the average yield loss rate under 19 droughts occurring during the growth period of maize from 1982 to 2017 was 24.51%. High risk happened in 1988, 1992, 1994, 2001, and 2004, with the largest loss rate in 2001, up to 65.58%. Overall, droughts with a return period less than two years occurred frequently during the growth period of summer maize in Bengbu, though the loss risk was still controllable. In conclusion, the results suggest that the loss risk curve provides a new effective method of drought disaster risk quantitative assessment from a physical mechanism perspective, which lays a scientific foundation for decision-making in risk management.

An agricultural drought assessment is the basis for formulating agricultural drought mitigation strategies. Traditional agricultural drought assessment methods reflect agricultural drought degree by using the soil water deficit, e.g., Soil Moisture Anomaly Percentage Index (SMAPI). However, due to varying water demands for different crops, a given soil water deficit results in varying crop water deficits and agricultural droughts. This variation often leads to a misinterpretation of agricultural drought classification when one only considers the soil water deficit. To consider the influence of crop growth, this study proposes an agricultural drought assessment method by coupling hydrological and crop models (variable infiltration capacity-environmental policy integrated climate, VIC-EPIC). Agricultural drought in Jiangsu Province, China was evaluated using the VIC-EPIC model and crop water anomaly percentage index (CWAPI). The validation results based on the actual drought records showed that the correlation coefficients (0.79 and 0.82, respectively) of the statistical values and CWAPI simulated values of light and moderate drought area rates were greater than those for SMAPI (0.72 and 0.81, respectively), indicating that the simulation results of the VIC-EPIC model in Jiangsu Province were highly reasonable. The temporal and spatial variation characteristics of the drought grade in typical large-scale drought events in Jiangsu Province were also analyzed.

Hydrological variable frequency analysis is a fundamental task for water resource management and water conservancy project design. Given the deficiencies of higher distribution features for the upper tail section of hydrological variable frequency curves and the corresponding safer resulting design of water conservancy projects utilizing the empirical frequency formula and Pearson type III function-based curve fitting method, the normal cloud transform algorithm-based model for hydrological variable frequency analysis was proposed through estimation of the sample empirical frequency by the normal cloud transform algorithm, and determining the cumulative probability distribution curve by overlapping calculation of multiple conceptual cloud distribution patterns, which is also the primary innovation of the paper. Its application result in northern Anhui province, China indicated that the varying trend of the cumulative probability distribution curve of annual precipitation derived from the proposed approach was basically consistent with the result obtained through the traditional empirical frequency formula. Furthermore, the upper tail section of the annual precipitation frequency curve derived from the cloud transform algorithm varied below the calculation result utilizing the traditional empirical frequency formula, which indicated that the annual precipitation frequency calculation result utilizing the cloud transform algorithm was more optimal compared to the results obtained by the traditional empirical frequency formula. Therefore, the proposed cloud transform algorithm-based model was reliable and effective for hydrological variable frequency analysis, which can be further applied in the related research field of hydrological process analysis.

The coordinated development of water resources, social economy, and ecological environment (WSE) in the irrigation district is fundamental to sustainable management and food security. In this study, a model is established to address the lack of effective methods for quantitative assessment and diagnosis of WSE coordinated development due to the complex and uncertain WSE structure. Therefore, an assessment model of WSE development is proposed by utilizing the structural analysis of WSE and connection number theory. This study adopts a mechanical model to assess the status of WSE coordination and diagnose the uncoordinated reasons, and a coordinated development assessment model is constructed using a risk matrix. Applying this method in five counties of the Dagong irrigation district of the Yellow River indicates average values of 0.403 (low development), 0.377 (medium slowness), 0.497 (low development), 0.572 (medium development), and 0.589 (medium development) for the WSE development degree in Neihuang, Xunxian, Huaxian, Changyuan, and Fengqiu, respectively, during 2010–2017, with average values of 0.677 (medium incoordination), 0.781 (low coordination), 0.611 (high incoordination), 0.797 (low coordination), and 0.842 (medium coordination) for the WSE coordination degree. Coordinated development status in the area deteriorates gradually from south to north, and although the overall situation has been improved, the differences among the five counties remain significant, with Neihuang and Huaxian being the most severe incoordination. Enhancing the advance of economy and environment, matching and promoting the support capacity of water resources condition, and maintaining a balance of these three sub-systems are the crucial points of coordinated development of the WSE structure in the Dagong irrigation district. This study provides targeted policy reference for water resources planning and effectively promotes the application of structural water resources science.