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Research On Measure Analysis And Forecasting Of Water Footprint Of Navel Orange In Gannan Based On GIS

Posted on:2019-08-18Degree:MasterType:Thesis
Country:ChinaCandidate:J H CaiFull Text:PDF
GTID:2370330566470003Subject:Cartography and Geographic Information System
Abstract/Summary:PDF Full Text Request
Faced with the current situation of global water shortages,how to further reduce the high consumption of crops in water resources in agricultural production activities,increase the efficiency of agricultural water use,and rationally allocate water resources have become a new challenge for humanity.In view of this,this paper starts from the perspective of water footprint,the agricultural and meteorological data of navel orange planting in Gannan region from 2001 to 2016 were selected,the water footprint model of agricultural products was used to calculate the total water footprint,blue water,green water,grey water and ten thousand yuan GDP water footprint of navel oranges of 18 administrative units in Gannan region,and the main factors affecting the water footprint of navel orange were further studied,it was analyzed quantitatively from the scale of time and space.Finally,the GM(1,1),ARIMA,ELM combined model was used to predict the water footprint of the navel orange in Gannan region for 2017-2020 years.The main conclusions are as follows:(1)On the whole,the green,the grey and the total water footprint of the navel orange in Gannan region showed a similar decline in the past 2001-2016 years.Due to the influence of precipitation in different years,the blue water footprint fluctuates greatly,and its value was 0 in a year of high water.In 2016,the navel orange yield in Longnan County has been increasing,the biggest drop in green water was 93.22%;the amount of chemical fertilizer applied in Nankang area decreased significantly during the process of navel orange planting,the biggest drop in the grey water footprint of fertilizer was 93.81%,this shows that its water pollution is gradually decreasing,the ecological benefits were being further enhanced;Similarly,the largest decrease in the pesticide grey footprint in Nankang was 88.87%,it indicates that Nankang district takes the path of ecological agriculture in the process of navel orange planting,the pesticide application reduce significantly,it makes the footprint of pesticide grey water decrease continuously,the water environment of Nankang is further improved.(2)The spatial difference of planting Water footprint of navel Orange in Gannan was obvious.The high water footprint of navel orange in 2016 was mainly concentrated in Zhanggong and Shangyou counties,its low value areas were mainly Xunwu County and Longnan County.In 2016,the navel orange green water footprint high value areas were mainly concentrated in Zhanggong district and Shangyou county,the low value areas were distributed in Longnan and Xunwu counties;the high value areas of the chemical fertilizer grey water footprint were mainly concentrated in Dingnan County,the low value areas distributed in Chongyi and Xunwu County;the high value region of pesticide grey water footprint was distributed in Ganxian and Yudu counties,the low value areas were distributed in Longnan County,Xunwu County,Ruijin City and Nankang District;because 2016 was a year of high water,the navel orange blue water was zero.(3)From 2001 to 2016,the GDP water footprint of navel orange in Gannan was decreased,it indicates that the utilization rate of water resources of navel orange planting in south Jiangxi was increasing.In 2016,Xunwu county's ten thousand yuan GDP water footprint was the smallest,it indicates that the water resources utilization efficiency of navel orange planting in Xunwu County was the highest;Compared with 2001,In 2016,the largest decline in the water footprint of the ten thousand yuan GDP in Longnan County was 98.11%,it show that the efficiency of water resource utilization of navel orange planting in Longnan County was the highest,its agricultural economy had the greatest potential.From a spatial point of view,in 2016,the high value areas of the ten thousand yuan GDP water footprint were mainly distributed in Dingnan County,Zhanggong District and Shangyou County,the low-value areas were distributed in Ningdu County and Xunwu County,it shows that the utilization efficiency of the water resources of navel orange in Ningdu and Xunwu counties was the highest.(4)The main factors affecting the water footprint of navel orange in Gannan and the ranking of its correlation degree were as follows: Population factor > water resource factor > agricultural production factor > economic factor > people's life factor.The main factors affecting the water footprint of navel orange were the rural population index in population factor,the total water resource index and precipitation index in water resource factor,and the effective irrigation area index in agricultural production factor,the results show that the water footprint of navel orange in Gannan was most closely related to the number of people engaged in agricultural production,the total amount of water resources and the irrigation and water conservancy facilities,it can be concluded that the planting industry of navel orange in Gannan was characterized by low level of mechanization,low degree of large-scale planting,uneven spatial distribution of water resources and weak irrigation and water conservancy facilities,it has an obstacle to the further expansion of the planting area of navel orange.(5)According to the prediction results of the GM(1,1),ARIMA,ELM combinatorial model,it can be seen that only Xingguo County and Huichang County had an increasing water footprint of navel orange during 2017-2020,they were unsustainable development;the water footprint of the navel orange in the rest of the 16 districts and counties showed a decline.Using Water footprint data of navel Orange in Gannan from 2001 to 2016.Based on the water footprint data of navel orange from 2001 to 2016 in Gannan,the integrated model of GM(1,1),ARIMA,ELM has high prediction accuracy;the ELM algorithm has stronger learning ability and faster training speed,which was more suitable for predicting the time series of water footprint of small samples than the traditional soft computing method.
Keywords/Search Tags:water footprint of Gannan navel orange, GIS spatial analysis, water efficiency, GM(1,1) model, ARIMA model, ELM model, hybrid prediction model
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