Sustainability Evaluation Of Land Change Based On The Yellow River Irrigation Areas

The Heigangkou and Liuyuankou irrigation areas are the focus of this research. Fourrepresentative villages have been selected as the study areas which are near the Yellow River.The changes in the land during the years of1988,2001and2011. Chemical Analysis, GISTechnology and Mathematical Statisticasare used to find out what effect by land change in thegravity-irrigated areas of Yellow River has on heavy metal pollution in the soil, and in turmsof the content of heavy metal in the soil in the irrigation areas, as well as distributuion, types,pollution and the characteristics of accumulation. The factors of heavy metal pollution in thesoil are analyzed, and the functional clusters of land utilization in the irrigation areas are alsorefined. The study has an importand significance for simulating and forecasting the change ofland utilization, as well as th content and distribution of heavy metal in the irrigation areas inthe future. The purpose of the study is to explore the classifications of landuse as well as howland-use change affects soil pollution, coupled with analysis of the land change and heavymetal in the soil. This study will establish a particular Multifunctional System of land-useclassification and a model of sustainability assessment, and analyze the sustainability of landchange in the Yellow River irrigation areas. The main conclusions obtained from the researchare as follows:(1) The study areas had an obvious land use change. The study obtained information onland-use change by using three sets of remote-sensing images from the years of1988,2001and2011. After interpreting, calculating and analyzing, the results show that there was anobvious urbanization process and human impact on the edge of the study areas. The expansionof urban construction land through the occupation of cultivated land, and the structural changeof non-urban construction land are obvious from the year1988to2011. The decrease ofagricultural land, tidal flats and water areas, and the increase of urban construction land,industrial and mining sites represent the change of land use type in the study area from theyear1988to2011. The land use type with the largest change of total amount is agriculturalland and rural residential land; the second is urban construction land, tidal flats and waterareas; the variation of industrial and mining land is relatively small. There were frequenttransforms among the various land types from the year1988to2011. The absolute value ofthe total land area variation has increased, the change range is relatively larger than before,and the biggest is dynamic degree, as well as amount and speed. The index of regional land-use shows a certain degree of growth, which indicates that the process of urbanization inthe study area is clear during23years, especially in the south of study area, which is near theurban fringe area, which has a high degree of non-agricultural land. The growth rate ofconstruction land is markedly higher than that of the far regions. Compared to the degree ofchange and the rate of dynamic degree of cultivated land and construction land, it can befound that agricultural land was lost quickly, while construction land increased quickly. Thereis a significant correlation between these two areas; what once embodied agricultural land hasbecome the chief source of recently increased construction land. Farmland reduction hasbecome a reality that cannot be ignored. More land changed from agricultural land, more thanany land shifted to agricultural use. To a certain extent, it shows that the speed of thetransformation of the to non-agriculture land is very significant. In all types of land in thestudy areas, tidal flats and water areas are remarkable; from an overall perspective, these twoareas are reduced, and their trend of development is concurrent. This study uses the MarkovModel to predict the future of land use change in the study area. The result indicates that inthe next40years, the farmland area decreased will continue to decrease remarkably, and tidalflats will also have small reductions. Urban construction land will continue to expand to thenorth and west of the study areas, and water and industrial land will increase slightly. Theoverall trend is characterized by the expansion of construction space and the loss ofagricultural land.(2) The extent of heavy metal pollution reflects the change of regional land qualitycaused in the process of change. By statistical analysis of soil heavy metal content in thestudy areas, the coefficients of variation of soil heavy metal elements in the study areas aresorted as follows: Hg> Cr> Cd>Cu>Ni>As>Pb>Zn. Using the K-S to test the normaldistribution of content of heavy metals in the soil, the elements accord with normaldistribution. The test that found Cd had the maximum amount and was the outlier, Cr, Cu, Ni,Pb and Zn were also outliers, and Hg did not exist. By analyzing the spatial distribution of thesoil heavy metal content with the ArcGIS9.3platform, the most polluted areas are in thesouthwest and south. All8heavy metals examined in the study areas fit the variation functionof Fitting Effect Theory; Cr, Zn and As accord with the spherical model, while Ni, Cu, Cd, Pband Hg accord with the Gauss model. The heavy metals in the soil in the research areas wereaffected both by human activities and regional factors, with human activities having moreinfluence on the spatial distribution structure of Hg and Cd. According to the Nemero Index,Geoaccumulation Index and Pollution Load Index, Hg and Cd were the main elements of heavy metal pollution in the study areas. The single factor pollution index method showedthat Hg and Cd exceed the standard acceptable amount to some degree in Henan province. All8studied heavy metals demonstrated a certain degree of cumulative pollution by thegeo-accumulation index. Overall, the pollution situation was at the medium level as evaluatedby the Pollution Load Index. And the assessment of the Potential Ecological Risk exhibitedthat there were ecological risks from Hg、Pb、As、Cd; Hg and Cd were especially serious.Meanwhile, GIS software provides an analysis function to accurately calculate the size of thecontamination zone. This study evaluated the pollution level using Factor Pollution Index,Geoaccumulation Index and Potential Ecological Risk Index; the results showed a differentpollution distribution from any of these indexes. The polluted area according to the FactorPollution Index is significantly greater than the other two. Based on the evaluation results ofthe heavy metal pollution in the soil, this study analyzed the impact factors of the pollution.Land traffic is considered to be the main cause of pollution. Polluted water continuouslyspead the pollution to the land on a wild area, which is the secondary cause.(3) Using the scene of heavy metal predicting model, this study forecasts the content,pollution areas and distribution trend by8heavy metals in the soil in the year of2021; theyare Cr、Ni、Cu、Zn、Cd、Pb、Hg、As. The study also takes the average content and pollutionarea of heavy metals in the soil in the year of2011as a reference. The results show that underthree scenarios (one positive, one neutral and one negative), the prediction for the content ofheavy metal in the soil and pollution areas have significant differences. Different situationsand backgrounds have striking differences. In the positive scenario, the content of all8heavymetals significantly decreased, and the area of soil pollution decreased; while the contentgradually increased in the neutral and negative scenarios, the area of soil pollution alsoincreased. In these two cases, the negative scenario is more obvious than the neutral scenario.(4) According to the sustainable evaluation model of land change, my study establishesthe index system of sustainable evaluation in the irrigation areas. This study uses the analysismethods: AHP and weighted comprehensive, and selects indicators which can fully reflect theobject of evaluation. In ArcGIS9.3, through the layer stack, grid computing, andcomprehensive evaluation model for image space operation, my study concludes that thesustainable development level in three periods of1988,2001,2011, produces the distributionmaps of comprehensive index of sustainable development in irrigated area. From the point ofview of regional sustainable level structure, and the sustainable situation of the study areas,the size of the sustainable area is increasing and the size of the non-sustainable areas is gradually decreasing. From the spatial distribution, the trend of sustainable levels in threeperiods is roughly the same, decreased from north to the south. Overall, the sustainable areasare mainly distributed in the north of the study areas, such as agricultural land, tidal flats andwater areas. The level of sustainable development near the southern city is mainly distributedin the area within the scope of urban construction land, which is relatively low at the threestages. Over time, sustainability improved in the study areas.