基于引黄灌区土地变化的可持续性评价研究
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摘要
本研究以黑岗口、柳园口灌区为研究对象，以具有代表性的临近黄河四乡为研究区，以1988、2001、2011为时间节点分析研究区土地变化的时空分异规律；并运用化学分析、GIS技术和数理统计等分析方法，分析了引黄灌区内土壤重金属的含量、分布、类型、污染以及积累特征，探讨了土壤重金属污染因素，总结了引黄灌溉自流灌区内土地变化对土壤重金属污染的影响规律，对灌区未来土地利用变化、重金属含量和分布进行了模拟与预测。本研究探索了土地利用功能分类及其相互作用，进行了土地变化和土壤重金属污染的耦合分析，构建了引黄灌区独有的多功能土地变化分类指标体系与可持续性评价模型，论证了引黄灌区土地变化的可持续性。研究主要结论如下：
（1）20多年来研究区土地变化明显，农用地面积减少，城镇建设用地面积增加。本研究选取了研究区1988、2001和2011年三期遥感影像获取了土地利用变化信息，经过解译、计算和分析得出，研究区边缘区城镇化过程明显、人为影响显著。城镇建设用地通过占用农用地而扩展，非城镇建设用地间结构变化明显。农用地、滩涂、水域面积减少，城镇建设用地、工矿用地面积增加的态势。总量面积变化较大的土地利用类型有农用地、农村居民点；其次是城镇建设用地、水域和滩涂；工矿用地变化量相对较小。各土地类型间转入、转出频繁。城镇建设用地面积总量相对变化幅度较大，动态度最大，变化量和速度都是很大的，区域土地利用综合程度指数有一定增长，这表明23年间研究区内城市化过程明显，尤其是研究区南部靠近城市边缘区域，非农化程度很高，城镇建设用地的增长速度明显高于距其较远的地区。对比农用地和城镇建设用地的动态度可以发现，农用地流失快的地方基本上为建设用地增长快的地方，而农用地流失慢的地方建设用地增加速度也慢，二者空间上存在明显的相关性，体现了建设用地的扩展的主要是对农用地的占用。并运用马尔柯夫模型对研究区未来土地利用变化进行预测，结果发现研究区未来40年里，农用地面积将持续减少，滩涂面积也将小幅度减少；城镇建设用地的面积将持续增加，继续向研究区北部和西部扩展，水域和工矿用地有小幅度增加，总体趋势以建设用地的空间扩张、农用地的流失为特征。
（2）交通是造成研究区重金属污染的主要原因，Hg、Cd是整个研究区主要的重金属污染元素，存在较强的生态风险。土壤重金属污染程度反映出土地变化过程中所引起的区域土地质量变化，对研究区土壤重金属Cr、Cu、Ni、Pb、Zn、As和Hg进行分析与评价，得出Cr、Cu、Ni、Pb、Zn、As保持清洁，Hg、Cd是整个研究区主要的重金属污染元素，为评价土地变化的可持续性提供科学依据。在研究区内共采集土壤样品107个，经过化学实验分析和数理统计分析得出，研究区土壤重金属元素变异系数排序为：Hg> Cr> Cd>Cu>Ni>As>Pb>Zn。利用K-S进行土壤重金属含量正态分布检验，各元素均符合正态分布。发现Cd存在极大值和离群值，Cr、Cu、Ni、Pb、Zn存在离群值，As和Hg没有存在。在ArcGIS9.3平台上分析了研究区土壤重金属含量空间分布趋势，研究区西南区域和南部重金属含量较高。研究区域内8种重金属的理论变异函数拟合效果均较好，其中Cr、Zn、As符合球状模型，Ni、Cu、Cd、Pb、Hg符合高斯模型。研究区土壤重金属受人为活动与区域因素的共同影响，其中人为活动对Hg、Cd的空间分布结构的影响较为突出。通过内梅罗指数、地累积指数、污染负荷指数评价，得到Hg、Cd是整个研究区主要的重金属污染元素。单因子污染指数法得出了Hg和Cd有一定程度超过河南省潮土背景值；地累积指数法得出研究区土壤8种重金属均有一定程度的累积污染；污染负荷指数评价得出研究区土壤中重金属的污染状况整体上属于中等污染。而潜在生态风险评价得出研究区Cr、Ni、Cu、Zn、Pb、As均存在潜在生态风险，Hg和Cd存在强生态风险。同时GIS软件提供了强大的分析功能，能够对污染区域的面积进行精确统计。单因子污染指数、地累积指数和潜在生态危害指数污染评价结果显示出不尽相同的污染分布，单因子污染指数面积所显示的污染的区域明显要大于地累积指数和潜在生态危害指数的结果。在土壤重金属人为污染的评价结果基础上，进行了污染的影响因素分析。认为交通是造成污染的主要原因，水域作为污染传播的一个载体也是造成大面积连续污染的原因之一。
（3）运用情景预测模型，比照2011年土壤重金属含量平均值和污染面积分别预测了2021年研究区土壤中Cr、Ni、Cu、Zn、Cd、Pb、Hg、As等8种重金属含量、污染面积及分布趋势。结果表明研究区内各土壤重金属含量及污染面积在乐观、无突变和悲观三种情景下所预测的结果存在差别显著，不同情景背景下土壤重金属含量和分布有较大差异。其中在8种重金属在乐观情景下含量明显下降，土壤污染面积减少；而在无突变情景和悲观情景下8种重金属含量表现为不断增加，土壤污染面积也不断扩大，其中这两项在悲观情景下又明显比在无突变情景下要高。
（4）研究区1988、2001、2011年三个时期的可持续水平较高，在评价体系分级——不可持续、初步可持续、基本可持续和全面可持续，处于基本可持续与全面可持续水平。根据土地变化的可持续性评价模型，建立灌区土地变化的可持续性评价指标体系，选取能全面、系统的反映出评价对象的指标，运用层次分析法和加权综合分析法，在ArcGIS9.3环境下，通过图层叠加、栅格计算，运用综合评价模型进行图像空间运算，得出1988、2001、2011年三个时期的可持续等级发展水平，生成土地变化的可持续性综合指数分布图。从区域可持续水平等级结构来看，研究区可持续状况以基本可持续和全面可持续为主，基本可持续和全面可持续水平面积渐增长；不可持续面积逐步减少。从空间分布上看，三个时期的可持续水平等级分布趋势大致相同，由北向南逐级递减。全面可持续区域的主要分布在农用地、滩涂和水域，在研究区的北部地区；靠近城市的研究区南部三个时期的可持续发展水平比较低，这个区域主要分布在城镇建设用地范围内。从时间动态上看，研究区可持续水平趋向好的方向发展。
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.
（1）20多年来研究区土地变化明显，农用地面积减少，城镇建设用地面积增加。本研究选取了研究区1988、2001和2011年三期遥感影像获取了土地利用变化信息，经过解译、计算和分析得出，研究区边缘区城镇化过程明显、人为影响显著。城镇建设用地通过占用农用地而扩展，非城镇建设用地间结构变化明显。农用地、滩涂、水域面积减少，城镇建设用地、工矿用地面积增加的态势。总量面积变化较大的土地利用类型有农用地、农村居民点；其次是城镇建设用地、水域和滩涂；工矿用地变化量相对较小。各土地类型间转入、转出频繁。城镇建设用地面积总量相对变化幅度较大，动态度最大，变化量和速度都是很大的，区域土地利用综合程度指数有一定增长，这表明23年间研究区内城市化过程明显，尤其是研究区南部靠近城市边缘区域，非农化程度很高，城镇建设用地的增长速度明显高于距其较远的地区。对比农用地和城镇建设用地的动态度可以发现，农用地流失快的地方基本上为建设用地增长快的地方，而农用地流失慢的地方建设用地增加速度也慢，二者空间上存在明显的相关性，体现了建设用地的扩展的主要是对农用地的占用。并运用马尔柯夫模型对研究区未来土地利用变化进行预测，结果发现研究区未来40年里，农用地面积将持续减少，滩涂面积也将小幅度减少；城镇建设用地的面积将持续增加，继续向研究区北部和西部扩展，水域和工矿用地有小幅度增加，总体趋势以建设用地的空间扩张、农用地的流失为特征。
（2）交通是造成研究区重金属污染的主要原因，Hg、Cd是整个研究区主要的重金属污染元素，存在较强的生态风险。土壤重金属污染程度反映出土地变化过程中所引起的区域土地质量变化，对研究区土壤重金属Cr、Cu、Ni、Pb、Zn、As和Hg进行分析与评价，得出Cr、Cu、Ni、Pb、Zn、As保持清洁，Hg、Cd是整个研究区主要的重金属污染元素，为评价土地变化的可持续性提供科学依据。在研究区内共采集土壤样品107个，经过化学实验分析和数理统计分析得出，研究区土壤重金属元素变异系数排序为：Hg> Cr> Cd>Cu>Ni>As>Pb>Zn。利用K-S进行土壤重金属含量正态分布检验，各元素均符合正态分布。发现Cd存在极大值和离群值，Cr、Cu、Ni、Pb、Zn存在离群值，As和Hg没有存在。在ArcGIS9.3平台上分析了研究区土壤重金属含量空间分布趋势，研究区西南区域和南部重金属含量较高。研究区域内8种重金属的理论变异函数拟合效果均较好，其中Cr、Zn、As符合球状模型，Ni、Cu、Cd、Pb、Hg符合高斯模型。研究区土壤重金属受人为活动与区域因素的共同影响，其中人为活动对Hg、Cd的空间分布结构的影响较为突出。通过内梅罗指数、地累积指数、污染负荷指数评价，得到Hg、Cd是整个研究区主要的重金属污染元素。单因子污染指数法得出了Hg和Cd有一定程度超过河南省潮土背景值；地累积指数法得出研究区土壤8种重金属均有一定程度的累积污染；污染负荷指数评价得出研究区土壤中重金属的污染状况整体上属于中等污染。而潜在生态风险评价得出研究区Cr、Ni、Cu、Zn、Pb、As均存在潜在生态风险，Hg和Cd存在强生态风险。同时GIS软件提供了强大的分析功能，能够对污染区域的面积进行精确统计。单因子污染指数、地累积指数和潜在生态危害指数污染评价结果显示出不尽相同的污染分布，单因子污染指数面积所显示的污染的区域明显要大于地累积指数和潜在生态危害指数的结果。在土壤重金属人为污染的评价结果基础上，进行了污染的影响因素分析。认为交通是造成污染的主要原因，水域作为污染传播的一个载体也是造成大面积连续污染的原因之一。
（3）运用情景预测模型，比照2011年土壤重金属含量平均值和污染面积分别预测了2021年研究区土壤中Cr、Ni、Cu、Zn、Cd、Pb、Hg、As等8种重金属含量、污染面积及分布趋势。结果表明研究区内各土壤重金属含量及污染面积在乐观、无突变和悲观三种情景下所预测的结果存在差别显著，不同情景背景下土壤重金属含量和分布有较大差异。其中在8种重金属在乐观情景下含量明显下降，土壤污染面积减少；而在无突变情景和悲观情景下8种重金属含量表现为不断增加，土壤污染面积也不断扩大，其中这两项在悲观情景下又明显比在无突变情景下要高。
（4）研究区1988、2001、2011年三个时期的可持续水平较高，在评价体系分级——不可持续、初步可持续、基本可持续和全面可持续，处于基本可持续与全面可持续水平。根据土地变化的可持续性评价模型，建立灌区土地变化的可持续性评价指标体系，选取能全面、系统的反映出评价对象的指标，运用层次分析法和加权综合分析法，在ArcGIS9.3环境下，通过图层叠加、栅格计算，运用综合评价模型进行图像空间运算，得出1988、2001、2011年三个时期的可持续等级发展水平，生成土地变化的可持续性综合指数分布图。从区域可持续水平等级结构来看，研究区可持续状况以基本可持续和全面可持续为主，基本可持续和全面可持续水平面积渐增长；不可持续面积逐步减少。从空间分布上看，三个时期的可持续水平等级分布趋势大致相同，由北向南逐级递减。全面可持续区域的主要分布在农用地、滩涂和水域，在研究区的北部地区；靠近城市的研究区南部三个时期的可持续发展水平比较低，这个区域主要分布在城镇建设用地范围内。从时间动态上看，研究区可持续水平趋向好的方向发展。
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.
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