Mapping the Water-Economic Cascading Risks within a Multilayer Network of Supply Chains in China

Local water scarcity shocks can threaten supply chains by triggering cascading economic risks embedded in the flow of goods and services. However, the lack of cascading risk modeling techniques makes it challenging to determine how disruptions in one economic sector propagate to others through the supply chain. In this study, we construct a national multilayer cascading risk model using 2017 multiregional input-output data from China and simulate shock propagation. Our results show that the originating sector and geographic location of a shock are critical in determining the collapse's effects. The probability of a large avalanche (>1000 collapsed nodes) varies from 2 to 80% across provinces and from 1 to 96% across layers. Food production and processing, chemical smelting, and energy supply are critical layers that amplify the cascade effects of shocks. Grain regions like Henan and Hunan, manufacturing hubs such as Guangdong, and water and energy suppliers like Sichuan and Hubei face high cascading risks. Our scenario analyses show that reducing output dependence on nodes decreases the system's avalanche size by 20-40% while improving water production efficiency reduces it by 10-22%. These results highlight the importance of diversifying supply sources and optimizing water use efficiency to enhance network resilience.