Study On Response Mechanism Of Agricultural Water Footprint To Climate Change And Evaluation

Climate change brings great challenges to China's food production and agricultural water security.Agricultural water footprint can be recognized as an comprehensive indicator of evaluating the use of water resources by agriculture,which reflects water volumes,water sources,and water required to eliminate agriculture water pollution.Hence,research on the mechanism of agricultural water footprint response to climate change and evaluation is of great significance to intensively understand how climate change influences the agricultural water cycles.Also,it is helpful for basin governers managing regional agriculltural water resources.The green,blue,and grey water footprint of winter wheat and summer maize in the haihe river basin and its spatial and temporal variation characteristics were assessed over 1956-2015.The direct and indirect effects of agricultural inputs and meteorological factors on water footprint of winter wheat are analyzed based on path analysis.the sensitivity of water footprint to its influencing factors was analyzed based on Sobol method.The DSSAT model was used to simulate the crops growth using the meteorological data,soil data and agricultural management data as inputs.This study estimated the future climate scenarios driven by the HadGEM2-ES mode under three typical concentration paths,named RCP2.6,RCP4.5,and RCP8.5.The DSSAT model were performed coupled with the three climate change scenarios,and the length of crop period,water consumption,yield and water footprint for winter wheat and summer maize were analyzed.The main conclusions of this study are as follows:?1?The green,blue,and grey water footprint of winter wheat and summer maize in the Haihe Hiver Basin were assessed using Pennman foumula and soil water balance method.The total water footprint of winter wheat and summer maize in Haihe River Basin was 20.1 billion m³/a?52%green,29%blue and 19%gray?and 15.1 billion m³/a?73%green,3%blue and 24%gray?,respectively.The water footprint for unit winter wheat and summer maize production was 1580m³/t and 1275m³/t.The total water footprint of winter wheat and summer maize showed an increasing trend due to the change of planting acreage.The water footprint of winter wheat and summer maize showed a significant decreasing trend due to the increasing crop yield and could be fitted by exponential function.Tianjin has the largest water footprint,mainly due to its lower crop yield and large application of nitrogen fertilizer.?2?The the direct and indirect effects of agricultural inputs and meteorological factors on water footprint for winter wheat were studied based on path analysis.The total power of agricultural machinery and the amount of converted fertilizer application,have the largest direct negative effect on the water footprint of winter wheat,with a direct path coefficient of-0.482 and-0.129 for temporal difference,-0.465 and-0.84 for spatial difference,respectively.Meteorological factors influence water footprint of winter wheat mainly by input factors of agricultural production.Among the meteorological factors,wind speed was the largest factor influencing the water footprint of winter wheat,with a direct path coefficient of 0.347 and 0.407 for temporal and spatial difference,respectively.Wind speed and air temperature has positive direct influence while the relative humidity and precipitation do negative.?3?the global sensitivity of water footprint of wheat to main influencing factors was studied by Sobol method.The results show that sensitivity of ET₀ to meteorological factors show significant seasonal changes.The temperature difference is the most sensitive factor in spring,autumn,and winter,with the first-order sensitivity coefficient of 0.56,0.61,and 0.45,respectively.The altitude is most sensitive in summer,with the first-order sensitivity coefficient of 0.29.The sensitivity of sunshine hours and altitude first increased and then decreased during the year.The temperature difference has the largest first-order and total sensitivity coefficient,which are 0.49 and 0.60,respectively.?4?The soil,meteorological data,and agricultural management data are collected for the DSSAT model.Long-term observed data for crop growth and yield were used to calibrate and verify the model and the Root-Mean-Error,Coefficiency of Residual Mass,and Index of Agreement were used to judge the simulation result.The model performed well and the the variety parameters were obtained which can used for long-term simulation of growth process.?5?Driven by the HadGEM2-ES model,the data of future climate change scenario under three typical concenreation paths?RCP2.6,RCP4.5,and RCP8.5?are generated and coupled with the DSSAT model to simulate the growth,yield and water footprint.The results show that air temperature and solar radiation in the haihe river basin all showed a significant upward trend in the scenarios of RCP2.6,RCP4.5,and RCP8.5.But in these scenarios the trends of precipitation,relative humidity and wind speed are inconsistent.By 2050,under the scenarios of RCP2.6,RCP4.5,and RCP8.5,the growth period of winter wheat will be shortened by 3d/10a,4d/10a and 3d/10a,respectively.The yield will be increased by 26%,16%and 13%,respectively,and the water footprint will be reduced by 10%,11%,and 13%,respectively.For summer maize,the growth period was shortened by 3d/10a,1d/10a,and 6d/10a,respectively,and the yield was reduced by 22%,31%,and58%,respectively,while the water footprint was increased by 41%,60%,and 151%,respectively.High emission would have a serious adverse effect on the growth and water use efficiency of summer maize.The research results provide reference for water resources managers to formulate relevant policies,cope with global climate change,and alleviate the contradiction of agricultural water shortage.In the future research,it is necessary to combine the crop growth model with field experiment observation of soil moisture conditions and crop growth parameters during the growth process of crops,so as to improve the accuracy of water footprint accounting and model simulation.