Study On Risk Characteristics Of Regional Agricultural Water And Soil Resources System And Its Effect On Planting Structure

Agricultural water and soil resources are not only important resources for maintaining the stable development of the social economy but also the key factors in ensuring food production safety.With the rapid economic development and the continuous development of the population,the disturbance of agricultural land and water resources has been increasingly strengthened.The ecological and environmental problems caused by the agricultural water and soil resources system have been increasing,and the prospects are not optimistic.Jiansanjiang Administration is an important base of grain reserve and commodity grain production in China.Under the influence of high-intensity agricultural development,the negative impacts such as the drop of groundwater level,aggravation of agricultural non-point source pollution,and increased water and soil erosion have gradually emerged,and water and land resources pressure has been increasing.In this context,the assessment of regional water and soil environmental quality,establishment of regional water and soil resources system risk assessment index system,assessment of regional water and soil resource system risks,selection of key drivers of regional water and soil resource system risk evolution,optimization of agricultural planting structure,can provides some scientific basis for the research of regional agricultural water and soil resources risk and has important theoretical and practical significance for maintaining the sustainable use of water and soil resources and ensuring food security and ecological security.Taking the 15 farms in Jiansanjiang Administration as examples,The groundwater quality and soil quality are evaluated,the regional agricultural water and soil resource risk grades are measured,the key drivers of systemic risk are analyzed,and the local agricultural planting structure is optimized.The main research and content are as follows:(1)A comprehensive evaluation model for groundwater quality and soil quality based on a BP neural network optimized by the Krill shrimp group algorithm is established to assess the groundwater quality and soil quality of the Jiansanjiang Administration in 2016.According to the relevant data in 2016,the partial least-squares regression equations for groundwater quality index and soil quality index are established to extend the data,and then the evolution characteristics of the groundwater quality and soil quality of the Jiansanjiang Administration are analyzed.The results exhibit a good agreement of ground water quality in each farm and there is a certain spatial distribution pattern such as the water quality of grade I is mainly concentrated in the southwest position,grade II is in the north and south while the grade III is located in the mid-west and mid-east of the administration;Soil quality is generally good.The soil quality of each farm are in Grade III.Farms with Grade II soil quality are mainly distribute in the southwest and northeast,farms with Grade III soil quality are mainly concentrated in northwest and southeast locations;The groundwater quality of the Jiansanjiang Authority shows a downward trend from 1997 to 2016,but the groundwater quality in 2013~2016 showes signs of improvement.The soil quality of the Jiansanjiang Authority decreases from 1997 to 2016 year by year,but there is a slight increase in the soil quality index from 2013 to 2016,indicating an improvement of soil quality in the Jiansanjiang Administration.(2)The risk assessment models of agricultural water and soil resources based on AAFSA-PPE and the risk assessment model based on RAGA-PPE are established respectively for the 15 farms of Jiansanjiang Administration to assess the risk of water and soil resources in 2016.Through comparison and selection of the optimal evaluation model,the assessment of agricultural water and soil resource risks from 1997 to 2015 on 15 farms of Jiansanjiang Administration is carried out year by year,and the spatiotemporal variability of land and water resource risks of farms from 1997 to 2016 is analyzed.Finally,using the principal component analysis method to screen out the key drivers of agricultural water and soil resources risk of Jiansanjiang Administration.The results shows that the risk of water and soil resources of all farms established are above Grade III.The reliability and stability of the AAFSA-PPE model are better than that of the RAGA-PPE model,which is more suitable for regional water and land resource risk assessment.From 1997 to 2016,the risks of the agricultural water and soil resources system of the Jiansanjiang Administration are on the rise.In 1997,agricultural land and water resources with risk grade II farms mainly distribute in the northern and central authorities,and water and land resources risk grade III farms are mainly distributed in the southern part of the Authority,and the ratio between Class II farms and Class III farms is 3:2.By the end of 2016,there are only 3 farms with Grade III,and the ratio between Class II farms and Class III farms is 1:4.The key driving factors for risk assessment of the agricultural land and water resources system of the Jiansanjiang Administration are the amount of water per unit of arable land,land utilization rate,reclamation rate,utilization rate of agricultural land,unutilized land rate,pesticide application per unit area of cultivated land,and fertilizer per unit area of arable land.application amount,grain yield per unit area.(3)With the goal of changing the planting area of main grain crops in all farms of the Jiansanjiang Administration,the goal is to achieve the largest share of total output value,the largest total output of food crops,and the highest efficiency of water production,with arable land resources,irrigation water consumption,food demand,and cropping.Net production value,agricultural water and soil resource risk are constraints,and a plant structure optimization model based on multi-objective particle swarm optimization is constructed.The results show that after optimizing the planting structure,the three objectives of the total output,total net benefits,and irrigation water use of the three main food crops of the Jiansanjiang Administration in 2020,2030,and 2040 can all be improved to some extent.Multi-objective particle swarm agriculture The planting structure model is feasible;after adjustment,the proportion of rice planted by the Jiansanjiang Administration in 2020,2030 and 2040 has declined,and the proportion of corn and soybean has increased.In order to increase production,increase income,and save water for agriculture,the Jiansanjiang Administration should appropriately control the proportion of rice cultivation and stabilize the ratio of corn and soybean cultivation.