| Water is a basic natural resource and a strategic economic resource beneficial to people’s livelihood.However,water scarcity and pollution have seriously restricted the economic and social development of China.Therefore,the Chinese government has issued a series of policies to implement the strictest water resource management rules.Considering that agriculture accounts for the largest water consumption,scientifically and systematically quantifying and evaluating the current situation of agricultural water resource utilization of China are the keys to solving the bottleneck in water resources.Water footprint is a comprehensive analytical indicator for evaluating water consumption and pollution and can be used to describe the characteristics of water consumption and pollution related to agricultural activities.Most previous research conducted agricultural water footprint analysis at the inventory level and only focused on the direct process.Moreover,most works quantified water footprint and analyzed the virtual water flow from the perspectives of production and trade,respectively.Nevertheless,these studies were inadequate to comprehensively evaluate the water resources for agricultural activities and alleviate the current severe situation of water scarcity in China.Thus,quantitative analysis of direct and indirect water footprint environmental impacts should be conducted from multiple perspectives.In consideration of the spatial diversity of water footprint research,directly adopting foreign models would lead to deviations in water footprint results.However,agricultural water footprint quantitative model based on China’s regional situations is scarce.In addition,most previous studies focused on the agricultural water footprint evaluation of the current situation.The interaction mechanism and evolution trend of the internal factors of the"economic society-agricultural activities-resources-environment" composite system should be further explored.Thus,this study constructed a Chinese regional agricultural water footprint quantitative model.Grain was selected as an example for model application and water footprint calculation from the perspectives of production,trade,and consumption.The system dynamic method was integrated in this study to simulate the current level and future evolution trend of the water footprint of grain production and provide decision-making support for ensuring the green and sustainable development of grains.The detailed research progress is as follows:First,on the basis of China’s regional situation(e.g.,water resource endowment,geographic parameters,and population),this study built an agricultural water footprint quantitative model,which involved inventory construction,selection of impact categories,calculation of characterization factors,and normalization value calculations.The water footprint inventory involved the direct processes(e.g.,irrigation water and fertilizer runoff)and indirect processes(e.g.,fertilizer and diesel production)of agricultural activities.The model built in this study included six midpoint categories and three endpoint categories and linked the water footprint results and inventory via characterization factors.Moreover,Chinese regional water consumption and pollutant inventory was built and evaluated to provide a benchmark value for the combination and horizontal comparison of water footprint results in diverse categories.Second,this study applied the proposed model in grain production,quantified the water footprint of grain production,traced the key factors,and explored the spatiotemporal variations.The normalized water footprint result of China’s main grain(i.e.,wheat,maize,and rice)production in 2019 was 0.55.These environmental burdens were primarily derived from direct processes(i.e.,direct water consumption and emissions)and indirect processes(i.e.,fertilizer,diesel,and electricity production).The overall burdens presented an upward trend from 2010 to 2019,which was mainly driven by the agricultural economic effect.Evident spatial diversities of water footprint results for the unit grain and the overall grain were observed in this study.The water footprint result generated from the unit grain production was the highest in Xinjiang Province,while that generated from the overall grain production was the highest in Henan and Hunan provinces.In addition,the water footprint results of grain production showed significant global and local spatial aggregation characteristics,among which high-value provinces,such as Shandong,Henan,and Anhui provinces,were mainly clustered in major grain-producing regions.Third,this study applied the proposed model in grain trade.The flow pattern of China’s interprovincial grain trade during 2019-2020 was explored,and resulting embodied water footprint impacts were further evaluated.The normalized water footprint flow embodied in China’s interprovincial grain trade was 0.13.The embodied water footprint outflow was mainly from Anhui and Xinjiang provinces,while Shandong and Guangdong provinces were the main embodied water footprint importers.Maize trade contributed mostly to the embodied water footprint flow.China’s grain trade increased the normalized water footprint result by approximately 1.46×10-2 compared with the no-grain transfer scenario.The increase in environmental burdens was mainly attributed to the exportation of maize from Xinjiang Province to Guangdong and Shandong provinces,the exportation of maize from Henan Province to Guangdong Province,and the exportation of rice from Anhui Province to Zhejiang Province.Meanwhile,the exportation of maize from Jilin and Heilongjiang provinces to Shandong Province contributed mostly to environmental benefits.Fourth,this study applied the proposed model in grain consumption.The water footprint results,spatial distributions,and structural characteristics of grain consumption were explored.The normalized water footprint result of China’s grain consumption during 2019-2020 was 0.53.Spatial distribution results showed that the most serious environmental impact of grain consumption was located in Shandong Province.The water footprint results of grain consumption exhibited an evident spatial aggregation phenomenon.High values of water footprint results were mainly distributed in the eastern and southern provinces of China,whereas low values were mostly concentrated in the western regions.The regional water footprint structures of grain consumption were mostly dominated by internal water footprint,in which Jilin,Henan,and Inner Mongolia provinces had the highest degree of internalization.Economically developed regions(i.e.,Beijing and Shanghai)showed high degrees of externalization of water footprint driven by their regional advantages and demand pull.Lastly,to explore the evolution trend of agricultural water footprint,this study integrated the proposed model and system dynamics to construct a system dynamic model of "water footprint of grain production-grain security." This simulation model consisted of four subsystems,namely,socioeconomic,grain consumption,grain production,and water footprint analysis.Water footprint intensity and grain self-sufficiency rate were selected as indicators to evaluate the water footprint of grain production and grain security,respectively.Simulation results showed that the water footprint intensity would present a downward trend from 2020 to 2030,while the grain self-sufficiency rate would indicate a contrary tendency under the baseline scenario.The simulation result of the integrated scenario(i.e.,grain structure adjustment,agricultural input control,and dietary structure adjustment)demonstrated higher environmental benefits than that of a single policy.Specifically,it would reduce the water footprint intensity by 2.64%and increase the grain self-sufficiency rate by 4.02%in 2030.Overall,this study constructed China’s regional agricultural water footprint quantitative model and analyzed the water footprint of grain from the perspectives of production,trade,and consumption to verify the feasibility of the multiperspective application of the model.This model was also integrated with system dynamics to analyze the evolution trends and trade-off effects between multiple systems.This study could contribute to accurate decision-making for the source prevention and the entire life cycle control of water consumption and pollution of grain activities,as well as provide supports of theory,methodology,and path for the systematic and scientific formulation of multiperspective agricultural policies. |
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