地表覆盖遥感分类数据质量及变化对水文过程模拟和水资源评估影响研究
|
摘要
在全球环境变化问题中,地表覆盖变化是自然与人类活动综合影响最为显著的要素。地表覆盖变化对地表水文过程的影响研究是目前的研究热点。地表覆盖遥感分类数据的分辨率与分类类别一直是水文模型模拟精度的主要影响因素之一。RS与GIS的快速发展推动了水文学科的发展,在水文研究中发挥重要的作用,具有重大的科学意义。因此本论文从水文学当前的研究热点出发,对于地表覆盖遥感分类数据对水文过程模拟以及区域地表水资源评估进行了综合探讨性研究,提出一些新的研究思路和方法,具有重要的科学意义和实际应用价值。
本文以江苏省苏北片区为研究区,评价了地表覆盖遥感分类数据的分辨率对地表水资源评估的影响；以秦淮河流域为研究区,采用SWAT模型研究了地表覆盖遥感分类数据分类类别对流域径流模拟的影响作用；以太湖流域为研究区,利用河网水文模型研究地表覆盖遥感分类数据分辨率导致的水文过程模拟结果差异,评价了地表覆盖变化对区域水文过程的影响。主要研究成果如下：
(1)地表覆盖遥感分类数据变化特征
随着遥感影像分辨率降低,所获取的地表覆盖遥感分类数据的变化主要集中于水田和旱地的面积变化,主要表现是水田面积的大量增加伴随着旱地面积的减少,以及水田面积与水面、城镇用地面积不同程度的转化。随时间推移伴随的主要变化是城镇用地面积的增加,反映了城市化进程的影响。其主要表现是城镇面积大量增加伴随着水田面积的大量减少,旱林地面积增加而水面面积减少。城市化现象在有些研究区呈加快的趋势。
(2)地表覆盖遥感分类数据分辨率对地表水资源评估的影响
地表覆盖遥感分类数据分辨率对水资源估算有较大的影响,变化比例从0.7%-105.2%不等。特殊干旱年(P=95%),基于两种不同分辨率地表覆盖遥感分类数据下的水资源评估结果有显著差异,多个水利分区差异在50%以上；一般干旱年(P=75%)的变化率与平水年(P=50%)的变化率基本在20%以下。
将基于不同分辨率地表覆盖遥感分类数据模拟输出的地表水资源量的模拟结果与《江苏省水资源调查评价》的多年平均地表水资源量评估结果相比较,基于10m分辨率地表覆盖遥感分类数据模拟的地表水资源量与《江苏省水资源调查评价》的结果拟合度较高。其次,基于相同分辨率地表覆盖遥感分类数据,平水年情境下的模拟结果与《江苏省水资源调查评价》中对应保证率的多年平均结果差异最小,拟合度最高。一般干旱年其次,特殊干旱年拟合度较差。
相同水文情景下,模拟的地表水资源量随着地表覆盖遥感分类数据分辨率的降低呈减小的趋势；主要的产流变化是水田和城镇产流的增加伴随着旱地产流与水面产流的减少。其中,以水田产流的增加较显著,旱地产流减小较明显。降雨量的多少是影响产流量总量多少的主要影响因素,而分辨率变化导致下垫面统计变化是产流过程及产流变化量的主要影响因素。
(3)地表覆盖遥感分类数据分类类别对径流模拟的影响
随着遥感影像土地利用分类类别的增加,模拟的年均流量下降。根据多年日模拟结果,随着分类体系的变化,流域的出口断面流量全年2/3的日模拟结果变化较小,全年1/10的日模拟结果变化达5%以上,最大差额为31.6m3/s,达出口断面流量的12.64%。基于不同土地利用分类类别地表覆盖遥感分类数据模拟输出的流域月均流量结果显示,地表覆盖遥感分类数据的土地利用分类类别对水文模拟的影响比地表覆盖遥感分类数据分辨率的影响小。分辨率的变化对流域的月均流量模拟有较明显的影响作用。随着地表覆盖遥感分类数据分辨率降低,模拟的月均流量洪峰值升高。基于不同时期地表覆盖遥感分类数据的模拟结果显示,随时间的推移模拟的月均流量洪峰值升高。
基于不同土地利用分类类别的地表覆盖遥感分类数据模拟输出的结果之间的差异较明显。土地利用分类类别对区域径流的影响作用大小与土地利用类别对水循环影响作用大小成正相关关系。在将土地利用类别分为4类、5类、12类的对比性研究中发现,将土地利用类别分为4类的模拟结果与将土地利用类别分为5类的模拟结果之间的差距比将土地利用类别分为5类的模拟结果与将土地利用类别分为12类的模拟结果之间的差距大,相差一个量级。分析认为,4类分类体系与5类分类体系主要变化是4类分类体系将草地林地作为1类土地利用类别,5类分类体系将草地林地分为草地、林地2类土地利用类别,这样的分类差别对产汇流有一定的影响作用。而分为12类更细的分类类别主要的变化是树木种类细分,细分的土地利用类别间的产汇流机制差异较小,继而此类土地利用类别细分对水文模拟结果影响较小。因此,地表覆盖遥感分类数据在水文方面的应用中,若进一步细分类别从影响水文过程的产汇流结构特征出发考虑分类类别,适用性会更好。
(4)地表覆盖遥感分类数据分辨率对水文过程模拟结果的影响
地表覆盖遥感分类数据的分辨率对流域水位过程模拟结果有显著影响作用。基于不同分辨率地表覆盖遥感分类数据计算得到的产流结果差异较大。地表覆盖遥感分类数据分辨率差异越大,模拟输出的水位差值越大。分辨率引起的计算差异随着降雨量的增加而增加,存在累计叠加的效应。降雨和下垫面分辨率对产流计算结果均有显著影响作用。基于分辨率较高的地表覆盖遥感分类数据模拟输出的产流量比基于分辨率较低的地表覆盖遥感分类数据模拟输出的产流量高。基于相同分辨率地表覆盖遥感分类数据,随着时间推移和城市化进程引起的地表覆盖变化下模拟输出的研究区产流量呈增加趋势。
相同水文条件下,基于分辨率较高地表覆盖遥感分类数据模拟输出的流域水位也较高。基于不同分辨率地表覆盖遥感分类数据模拟输出的研究区水位计算结果对比研究发现,基于30m分辨率地表覆盖遥感分类数据模拟输出的水位与基于调查统计地表覆盖数据模拟出的水位之间的差异最大,其最大变化幅度为8.7%(丰水年常州站)；基于10m与300m分辨率地表覆盖遥感分类数据模拟输出的水位差异其次,其最大变化幅度为7.43%(丰水年常州站)；基于30m与300m分辨率地表覆盖遥感分类数据计算输出的水位最大变化幅度为5.94%(丰水年无锡站)。基于相同分辨率变化的地表覆盖遥感分类数据,丰水年情景下模拟输出的水位差距在三种水文情景计算结果中最大。因此,利用遥感数据进行相关研究时,为了更接近真实情况,计算结果应做相应的校正。
模拟结果显示,降雨量的多少是水位过程整体高低的主要影响因素。整体趋势上,丰水年(P=20%)情景下模拟的水位最高,平水年(P=50%)情景下模拟的水位其次,枯水年(P=90%)情景下模拟的水位最低。其中,丰水年的水位起伏最大,且大部分时间都比其他两个典型年的水位高,尤其是在汛期。平水年水位过程起伏较小,全年一半以上水位比枯水年的水位高。枯水年的水位少数时段比平水年水位高。由此可见,除了降雨量等水文条件外,其它因素对水位过程有一定的影响。丰水年地表覆盖遥感分类数据的水文响应比枯水年的水文响应更显著；其次,地表覆盖遥感分类数据的变化对水位过程有一定的影响,总体趋势是随着城市化进程地表覆盖的变化,水位整体呈升高的趋势。每个站点起伏变化有异,变化幅度在0.33%-6.45%之间。
本论文首次探讨基于共享途径可获取的地表覆盖遥感分类数据分辨率对地表水资源量评估以及地表水文过程模拟的影响作用,弥补了该研究区域的研究空白,对水文模拟及水资源评估中正确使用和选择地表覆盖遥感分类数据空间分辨率具有参考价值,为地表覆盖遥感分类数据更好地应用于水文研究就提出新的探索途径。进行不同土地利用分类类别的地表覆盖遥感分类数据变化对水文模拟影响研究,提出应用于水文的遥感影像土地利用分类标准的主要衡量指标,对合理选择地表覆盖数据分类精细程度具有指导意义。基于不同保证率水文情景和不同时期地表覆盖变化的水文过程模拟,分析降雨与地表覆盖变化对流域水文过程影响作用,为流域水文要素研究提出新的研究思路和研究方法,具有创新性与科学性。
Among all global environmental changes, Land Cover Change is the most significant one in the areas of combined effects of natural and human activities. The impact of Land Cover Change on surface hydrological processes is a hot research topic at present. The resolution and classification of land cover data have been one of the main factors of the hydrological model accuracy. The rapid development of RS and GIS, which has promoted the development of Hydrological Sciences and played an important role in the hydrological study, has a scientific significance. This paper puts forward some new ideas and methods based upon:the current research focus of hydrology, integrated exploratory study of the impact of Land Cover Change on the hydrological process simulation and the regional surface water resources assessment. Thus this paper has a strong academic exploration and scientific significance.
Taking the example of the Case Study of Northern Jiangsu Province, the paper studies the effect of the resolution of land cover data on regional surface water resources evaluation; Taking Qinhuai Watershed as an example, it researches the impact of the classification of land cover data on hydrological simulation process. In time scale, it studies the impact of different periods, different resolution land cover data on hydrological process simulation in Taihu Lake. The main conclusions are as follows:
(1)Variable characteristics of land cover data
With the decrease of remote sensing image resolution, the area changes of land cover are mainly shown in paddy field and dryland. When the paddy field area increases, the dryland area will decrease and the area of water surface and urban will change in different extent. The increasing of urban area shows the impact of urbanization. It is apparent that with the urban area increasing, the paddy area decreases remarkably and that with the Drought woodland increasing, the water surface area decreases. In addition, the speed of urbanization seems faster in some places.
(2)The impact of the resolution of surface coverage remote sensing classification data on the surface water resources assessment.
The resolution of Land cover data has a great impact on water resources estimates of water resources regionalization, with the change in the proportion ranging from0.7%to105.2%. Especially in dry years (P=95%).The results of the runoff in the two resolutions have a significant difference. The differences of the multiple water conservancy partitions are more than50%and the difference between normal water years (P=50%) and general drought years (P=75%) is less than20%.
Comparing the simulated results of the surface water resources amount of the land cover based on different resolution remote sensing image with the years average amount of surface water resources results in Jiangsu Province Water Resources Assessment, the simulated results based on10m resolution have higher degree of fitting. The results caused by different resolution of drought years and special drought years are coincident. Besides, based on the same resolution, the difference between stimulated results in normal years and yearly mean results is the smallest. The second is that of general dry years, the fitting of special dry year is the poorest.
Under the condition of the same assurance, with the surface coverage data remote sensing image resolution decreases, the simulated surface water resources seems to be smaller; The main production flow change is that the paddy field and urban runoff deceases with the decrease of dry land and surface runoff. Among them, the increase of runoff in paddy field and the decrease of dry land runoff are more significant. The rainfall influences production flow a lot. The statistical change of underlying surface based on resolution is the main factor of runoff generation. Rainfall and land cover data affect surface water resources amount significantly.
(3)The impact of the classification of surface coverage remote sensing data on hydrological simulation process.
Runoff simulation results in different classification system show that the feature classification system of remote sensing images affects hydrological modeling less than the resolution remote sensing image. The influence degree of the feature classification system is diverse in the different position of the sub-basin. The differences change most obviously in the10th sub-basin, while no significant differences in more than half of the sub-basin. According to day simulation results of many years, with the change of classification system, the flow change of the outlet section is small in two-thirds of year and is more than5%in one-tenth of year, especially the biggest difference to31.6m3/s, which are amount to12.64%of the outlet section flow.
Secondly, the influence degree of regional runoff caused by the feature classification system is positively correlated with hydrological cycle. From comparative study of feature classification divided into four categories, five categories, and twelve categories, difference of simulation results of the feature type divided into four categories is lager than that divided into five categories and twelve categories. In addition, the results are significant differences caused by different classification system with the changes in the classification. For the tenth sub-basins of the study area case, monthly average flow in the condition of feature type divided into twelve categories in most cases are larger than that divided into five categories, with the range of0.06%to0.34%in2008. In2005, monthly average flow in the condition of feature type divided into twelve categories compare with that divided into five categories, both have50%increase and decrease in a month, with the range of0.07to0.1%. And compared monthly flow in the condition of feature type divided into five categories compare with that divided into four categories, monthly average flow change ratio is from0.07%to0.1%, with the range of0.14%to1.41%.
(4) The effect of different resolution land cover data on the result of hydrological simulation
The changes of land cover data come from different resolution remote sensing images and have a significant effect on watershed level. It appeared a tendency of the higher water level with the higher classification resolution. The higher the remote sensing images resolution is, the greater difference of the simulative water level will be. If the differences of resolution increase with the rainfall, there will be a total superposition effect.
In the same hydrological and meteorological conditions, water level of the basin increases with the increase of the RS image resolution. The difference of30m resolution RS image results and statistical results is biggest. In the high flow year, the maximum difference is up to the8.7%of the normal water level, such as Changzhou station. The difference of water level caused by the land coverage data come from10m resolution remote sensing images and that of300m is less than it, up to7.43%of the normal such as Changzhou station in high flow year. Next is the difference of water level caused by the land coverage data come from30m resolution remote sensing images and that of300m, up to5.49%of the normal such as Wuxi station in high flow year. On condition of the same resolution change, the water level difference in high flow years is bigger than that in other normal years. Therefore, in order to be closer to the real situation, the simulation results should be adjusted when we do some related researches.
Land cover change and rainfall both have an effect on watershed hydrological process. The amount of rainfall is the main influence factor for the overall level of water level process. On the overall trend, the whole water level is the highest in high flow year (P=20%), higher in normal flow year (P=50%) and the lowest in dry years (P=90%). The water level fluctuation is the biggest in high flow year, and the water level is higher than the other two represent years, especially in the flood season. The water level fluctuation is much less in normal flow years, and the water level is lower than that in dry years. The water level in dry year is the lowest, while it is higher than the other two represent years in fewer periods. Thus, in addition to the effect of rainfall, other factors also have certain effect on water level process. In the condition of the high flow year, firstly, hydrological response is more significant than that in dry year. Secondly, the changes of land cover data have an effect on water process. It shows the trend that the water level increases with the change features of land cover data with the development of city. The fluctuations in each station are different, which is approximately from0.33%to6.45%.
This paper first discusses the impact of remote sensing image resolution of land cover data from share on surface water resources evaluation and surface hydrological process simulation, and then makes up gap in the fields of research, and suggests new ways for surface coverage data to be better used in hydrological research. It studies the impact of classification system of different land cover data change on hydrological simulation accuracy and gives some main indexes that will be applied in features classification standard of hydrologic remote sensing image. It is based on the hydrological situation with different assurance rate and hydrological process simulation of land cover change in different period. In addition, the paper respectively discusses the rainfall and surface coverage change on watershed hydrological process, putting forward new research idea and method for watershed hydrological elements. It is an exploratory study with high scientific meaning.
本文以江苏省苏北片区为研究区,评价了地表覆盖遥感分类数据的分辨率对地表水资源评估的影响；以秦淮河流域为研究区,采用SWAT模型研究了地表覆盖遥感分类数据分类类别对流域径流模拟的影响作用；以太湖流域为研究区,利用河网水文模型研究地表覆盖遥感分类数据分辨率导致的水文过程模拟结果差异,评价了地表覆盖变化对区域水文过程的影响。主要研究成果如下：
(1)地表覆盖遥感分类数据变化特征
随着遥感影像分辨率降低,所获取的地表覆盖遥感分类数据的变化主要集中于水田和旱地的面积变化,主要表现是水田面积的大量增加伴随着旱地面积的减少,以及水田面积与水面、城镇用地面积不同程度的转化。随时间推移伴随的主要变化是城镇用地面积的增加,反映了城市化进程的影响。其主要表现是城镇面积大量增加伴随着水田面积的大量减少,旱林地面积增加而水面面积减少。城市化现象在有些研究区呈加快的趋势。
(2)地表覆盖遥感分类数据分辨率对地表水资源评估的影响
地表覆盖遥感分类数据分辨率对水资源估算有较大的影响,变化比例从0.7%-105.2%不等。特殊干旱年(P=95%),基于两种不同分辨率地表覆盖遥感分类数据下的水资源评估结果有显著差异,多个水利分区差异在50%以上；一般干旱年(P=75%)的变化率与平水年(P=50%)的变化率基本在20%以下。
将基于不同分辨率地表覆盖遥感分类数据模拟输出的地表水资源量的模拟结果与《江苏省水资源调查评价》的多年平均地表水资源量评估结果相比较,基于10m分辨率地表覆盖遥感分类数据模拟的地表水资源量与《江苏省水资源调查评价》的结果拟合度较高。其次,基于相同分辨率地表覆盖遥感分类数据,平水年情境下的模拟结果与《江苏省水资源调查评价》中对应保证率的多年平均结果差异最小,拟合度最高。一般干旱年其次,特殊干旱年拟合度较差。
相同水文情景下,模拟的地表水资源量随着地表覆盖遥感分类数据分辨率的降低呈减小的趋势；主要的产流变化是水田和城镇产流的增加伴随着旱地产流与水面产流的减少。其中,以水田产流的增加较显著,旱地产流减小较明显。降雨量的多少是影响产流量总量多少的主要影响因素,而分辨率变化导致下垫面统计变化是产流过程及产流变化量的主要影响因素。
(3)地表覆盖遥感分类数据分类类别对径流模拟的影响
随着遥感影像土地利用分类类别的增加,模拟的年均流量下降。根据多年日模拟结果,随着分类体系的变化,流域的出口断面流量全年2/3的日模拟结果变化较小,全年1/10的日模拟结果变化达5%以上,最大差额为31.6m3/s,达出口断面流量的12.64%。基于不同土地利用分类类别地表覆盖遥感分类数据模拟输出的流域月均流量结果显示,地表覆盖遥感分类数据的土地利用分类类别对水文模拟的影响比地表覆盖遥感分类数据分辨率的影响小。分辨率的变化对流域的月均流量模拟有较明显的影响作用。随着地表覆盖遥感分类数据分辨率降低,模拟的月均流量洪峰值升高。基于不同时期地表覆盖遥感分类数据的模拟结果显示,随时间的推移模拟的月均流量洪峰值升高。
基于不同土地利用分类类别的地表覆盖遥感分类数据模拟输出的结果之间的差异较明显。土地利用分类类别对区域径流的影响作用大小与土地利用类别对水循环影响作用大小成正相关关系。在将土地利用类别分为4类、5类、12类的对比性研究中发现,将土地利用类别分为4类的模拟结果与将土地利用类别分为5类的模拟结果之间的差距比将土地利用类别分为5类的模拟结果与将土地利用类别分为12类的模拟结果之间的差距大,相差一个量级。分析认为,4类分类体系与5类分类体系主要变化是4类分类体系将草地林地作为1类土地利用类别,5类分类体系将草地林地分为草地、林地2类土地利用类别,这样的分类差别对产汇流有一定的影响作用。而分为12类更细的分类类别主要的变化是树木种类细分,细分的土地利用类别间的产汇流机制差异较小,继而此类土地利用类别细分对水文模拟结果影响较小。因此,地表覆盖遥感分类数据在水文方面的应用中,若进一步细分类别从影响水文过程的产汇流结构特征出发考虑分类类别,适用性会更好。
(4)地表覆盖遥感分类数据分辨率对水文过程模拟结果的影响
地表覆盖遥感分类数据的分辨率对流域水位过程模拟结果有显著影响作用。基于不同分辨率地表覆盖遥感分类数据计算得到的产流结果差异较大。地表覆盖遥感分类数据分辨率差异越大,模拟输出的水位差值越大。分辨率引起的计算差异随着降雨量的增加而增加,存在累计叠加的效应。降雨和下垫面分辨率对产流计算结果均有显著影响作用。基于分辨率较高的地表覆盖遥感分类数据模拟输出的产流量比基于分辨率较低的地表覆盖遥感分类数据模拟输出的产流量高。基于相同分辨率地表覆盖遥感分类数据,随着时间推移和城市化进程引起的地表覆盖变化下模拟输出的研究区产流量呈增加趋势。
相同水文条件下,基于分辨率较高地表覆盖遥感分类数据模拟输出的流域水位也较高。基于不同分辨率地表覆盖遥感分类数据模拟输出的研究区水位计算结果对比研究发现,基于30m分辨率地表覆盖遥感分类数据模拟输出的水位与基于调查统计地表覆盖数据模拟出的水位之间的差异最大,其最大变化幅度为8.7%(丰水年常州站)；基于10m与300m分辨率地表覆盖遥感分类数据模拟输出的水位差异其次,其最大变化幅度为7.43%(丰水年常州站)；基于30m与300m分辨率地表覆盖遥感分类数据计算输出的水位最大变化幅度为5.94%(丰水年无锡站)。基于相同分辨率变化的地表覆盖遥感分类数据,丰水年情景下模拟输出的水位差距在三种水文情景计算结果中最大。因此,利用遥感数据进行相关研究时,为了更接近真实情况,计算结果应做相应的校正。
模拟结果显示,降雨量的多少是水位过程整体高低的主要影响因素。整体趋势上,丰水年(P=20%)情景下模拟的水位最高,平水年(P=50%)情景下模拟的水位其次,枯水年(P=90%)情景下模拟的水位最低。其中,丰水年的水位起伏最大,且大部分时间都比其他两个典型年的水位高,尤其是在汛期。平水年水位过程起伏较小,全年一半以上水位比枯水年的水位高。枯水年的水位少数时段比平水年水位高。由此可见,除了降雨量等水文条件外,其它因素对水位过程有一定的影响。丰水年地表覆盖遥感分类数据的水文响应比枯水年的水文响应更显著；其次,地表覆盖遥感分类数据的变化对水位过程有一定的影响,总体趋势是随着城市化进程地表覆盖的变化,水位整体呈升高的趋势。每个站点起伏变化有异,变化幅度在0.33%-6.45%之间。
本论文首次探讨基于共享途径可获取的地表覆盖遥感分类数据分辨率对地表水资源量评估以及地表水文过程模拟的影响作用,弥补了该研究区域的研究空白,对水文模拟及水资源评估中正确使用和选择地表覆盖遥感分类数据空间分辨率具有参考价值,为地表覆盖遥感分类数据更好地应用于水文研究就提出新的探索途径。进行不同土地利用分类类别的地表覆盖遥感分类数据变化对水文模拟影响研究,提出应用于水文的遥感影像土地利用分类标准的主要衡量指标,对合理选择地表覆盖数据分类精细程度具有指导意义。基于不同保证率水文情景和不同时期地表覆盖变化的水文过程模拟,分析降雨与地表覆盖变化对流域水文过程影响作用,为流域水文要素研究提出新的研究思路和研究方法,具有创新性与科学性。
Among all global environmental changes, Land Cover Change is the most significant one in the areas of combined effects of natural and human activities. The impact of Land Cover Change on surface hydrological processes is a hot research topic at present. The resolution and classification of land cover data have been one of the main factors of the hydrological model accuracy. The rapid development of RS and GIS, which has promoted the development of Hydrological Sciences and played an important role in the hydrological study, has a scientific significance. This paper puts forward some new ideas and methods based upon:the current research focus of hydrology, integrated exploratory study of the impact of Land Cover Change on the hydrological process simulation and the regional surface water resources assessment. Thus this paper has a strong academic exploration and scientific significance.
Taking the example of the Case Study of Northern Jiangsu Province, the paper studies the effect of the resolution of land cover data on regional surface water resources evaluation; Taking Qinhuai Watershed as an example, it researches the impact of the classification of land cover data on hydrological simulation process. In time scale, it studies the impact of different periods, different resolution land cover data on hydrological process simulation in Taihu Lake. The main conclusions are as follows:
(1)Variable characteristics of land cover data
With the decrease of remote sensing image resolution, the area changes of land cover are mainly shown in paddy field and dryland. When the paddy field area increases, the dryland area will decrease and the area of water surface and urban will change in different extent. The increasing of urban area shows the impact of urbanization. It is apparent that with the urban area increasing, the paddy area decreases remarkably and that with the Drought woodland increasing, the water surface area decreases. In addition, the speed of urbanization seems faster in some places.
(2)The impact of the resolution of surface coverage remote sensing classification data on the surface water resources assessment.
The resolution of Land cover data has a great impact on water resources estimates of water resources regionalization, with the change in the proportion ranging from0.7%to105.2%. Especially in dry years (P=95%).The results of the runoff in the two resolutions have a significant difference. The differences of the multiple water conservancy partitions are more than50%and the difference between normal water years (P=50%) and general drought years (P=75%) is less than20%.
Comparing the simulated results of the surface water resources amount of the land cover based on different resolution remote sensing image with the years average amount of surface water resources results in Jiangsu Province Water Resources Assessment, the simulated results based on10m resolution have higher degree of fitting. The results caused by different resolution of drought years and special drought years are coincident. Besides, based on the same resolution, the difference between stimulated results in normal years and yearly mean results is the smallest. The second is that of general dry years, the fitting of special dry year is the poorest.
Under the condition of the same assurance, with the surface coverage data remote sensing image resolution decreases, the simulated surface water resources seems to be smaller; The main production flow change is that the paddy field and urban runoff deceases with the decrease of dry land and surface runoff. Among them, the increase of runoff in paddy field and the decrease of dry land runoff are more significant. The rainfall influences production flow a lot. The statistical change of underlying surface based on resolution is the main factor of runoff generation. Rainfall and land cover data affect surface water resources amount significantly.
(3)The impact of the classification of surface coverage remote sensing data on hydrological simulation process.
Runoff simulation results in different classification system show that the feature classification system of remote sensing images affects hydrological modeling less than the resolution remote sensing image. The influence degree of the feature classification system is diverse in the different position of the sub-basin. The differences change most obviously in the10th sub-basin, while no significant differences in more than half of the sub-basin. According to day simulation results of many years, with the change of classification system, the flow change of the outlet section is small in two-thirds of year and is more than5%in one-tenth of year, especially the biggest difference to31.6m3/s, which are amount to12.64%of the outlet section flow.
Secondly, the influence degree of regional runoff caused by the feature classification system is positively correlated with hydrological cycle. From comparative study of feature classification divided into four categories, five categories, and twelve categories, difference of simulation results of the feature type divided into four categories is lager than that divided into five categories and twelve categories. In addition, the results are significant differences caused by different classification system with the changes in the classification. For the tenth sub-basins of the study area case, monthly average flow in the condition of feature type divided into twelve categories in most cases are larger than that divided into five categories, with the range of0.06%to0.34%in2008. In2005, monthly average flow in the condition of feature type divided into twelve categories compare with that divided into five categories, both have50%increase and decrease in a month, with the range of0.07to0.1%. And compared monthly flow in the condition of feature type divided into five categories compare with that divided into four categories, monthly average flow change ratio is from0.07%to0.1%, with the range of0.14%to1.41%.
(4) The effect of different resolution land cover data on the result of hydrological simulation
The changes of land cover data come from different resolution remote sensing images and have a significant effect on watershed level. It appeared a tendency of the higher water level with the higher classification resolution. The higher the remote sensing images resolution is, the greater difference of the simulative water level will be. If the differences of resolution increase with the rainfall, there will be a total superposition effect.
In the same hydrological and meteorological conditions, water level of the basin increases with the increase of the RS image resolution. The difference of30m resolution RS image results and statistical results is biggest. In the high flow year, the maximum difference is up to the8.7%of the normal water level, such as Changzhou station. The difference of water level caused by the land coverage data come from10m resolution remote sensing images and that of300m is less than it, up to7.43%of the normal such as Changzhou station in high flow year. Next is the difference of water level caused by the land coverage data come from30m resolution remote sensing images and that of300m, up to5.49%of the normal such as Wuxi station in high flow year. On condition of the same resolution change, the water level difference in high flow years is bigger than that in other normal years. Therefore, in order to be closer to the real situation, the simulation results should be adjusted when we do some related researches.
Land cover change and rainfall both have an effect on watershed hydrological process. The amount of rainfall is the main influence factor for the overall level of water level process. On the overall trend, the whole water level is the highest in high flow year (P=20%), higher in normal flow year (P=50%) and the lowest in dry years (P=90%). The water level fluctuation is the biggest in high flow year, and the water level is higher than the other two represent years, especially in the flood season. The water level fluctuation is much less in normal flow years, and the water level is lower than that in dry years. The water level in dry year is the lowest, while it is higher than the other two represent years in fewer periods. Thus, in addition to the effect of rainfall, other factors also have certain effect on water level process. In the condition of the high flow year, firstly, hydrological response is more significant than that in dry year. Secondly, the changes of land cover data have an effect on water process. It shows the trend that the water level increases with the change features of land cover data with the development of city. The fluctuations in each station are different, which is approximately from0.33%to6.45%.
This paper first discusses the impact of remote sensing image resolution of land cover data from share on surface water resources evaluation and surface hydrological process simulation, and then makes up gap in the fields of research, and suggests new ways for surface coverage data to be better used in hydrological research. It studies the impact of classification system of different land cover data change on hydrological simulation accuracy and gives some main indexes that will be applied in features classification standard of hydrologic remote sensing image. It is based on the hydrological situation with different assurance rate and hydrological process simulation of land cover change in different period. In addition, the paper respectively discusses the rainfall and surface coverage change on watershed hydrological process, putting forward new research idea and method for watershed hydrological elements. It is an exploratory study with high scientific meaning.
引文
[1]夏军,谈戈.全球变化与水文学科新的进展与挑战[J].资源科学,2002,24(3)：1-7.
[2]夏军,左其亭.国际水文科学研究的新进展[J].地球科学进展,2006,21(3)：259-261.
[3]尉颖琪.从国际水文计划看水文研究变化趋势[J].科技资讯,2011,28(10a)：143.
[4]李丽娟,姜德娟,李九一等.土地利用/覆被变化的水文效应研究进展[J].自然资源学报,2007,22(2)：211-224.
[5]张磊,吴炳方.关于土地覆被遥感监测的几点思考[J].国土资源遥感,2011,(1)：15-20.
[6]Bartholome'e A S, Belward. GLC 2000:A new approach to global land cover mapping from earth observation data [J]. International Journal of Remote Sensing, 2005,26(9):1959-1977.
[7]李秀彬.土地覆被变化的水文水资源效应研究——社会需求与科学问题.中国地理学会自然地理专业委员会.土地覆被变化及其环境效应论文集[C]..北京：星球地图出版社,2002.1-6.
[8]白淑英,陈灵梅,王莉等.土地利用/覆被变化研究现状与展望[J].安徽农业科学.2010,38(30)：17003-17005.
[9]周广胜,王玉辉.土地利用/覆盖变化对气候的反馈作用[J].自然资源学报,1999,14(4)：318-322.
[10]DeFries R, Eshleman K N. Land-use change and hydrologic processes:A major focus for the future[J]. Hydrological Processes,2004,18(11):2183-2186.
[11]赵启学,郑艳波,周庆东.大伙房水库以上流域人类活动对水库径流的影响[J].东北水利水电.2008,26(12)：32-33.
[12]Lahmer W, Pfutzner B, Becker A. Assessment of land-use and climate change impacts on the mesoscale [J]. Physics and Chemistry of the Earth,2001,26:565-575.
[13]陈莹.长江三角洲地区中小流域城镇化的水文效应分析[D].南京大学,2009.
[14]刘贤赵.论水文尺度问题[J].干旱区地理,2004,27(1)：61-65.
[15]孙庆艳.华北土石山区典型流域森林植被水文生态过程响应研究[D].北京： 北京林业大学,2008.
[16]傅国斌,刘昌明.遥感技术在水文学中的应用与研究进展[J].水科学进展,2001,12(4)：547-559.
[17]李春晖,杨志峰.水资源评价进展与存在的几个问题[J].水土保持学报,2004,18(5)：189-192.
[18]Turner B L,Moss R H,Skole D L. Human dimensions of global environmental change programme [R].HDP Report No.5,1993.
[19]王晓云.流域土地利用变化对径流影响问题的研究[D].天津：天津大学建筑工程学院,2008.
[20]陈军锋,李秀彬.森林植被变化对流域水文影响的争论[J].自然资源学报,2001,16(5)：474-480.
[21]古丽巴哈·扎依提.乌鲁木齐市土地利用/覆被变化及其水文水资源效应研究[D].乌鲁木齐：新疆师范大学,2011.
[22]中野秀章(李云森译).森林水文学[M].北京：中国林业出版社,1983.
[23]穆兴民,王文龙,徐学选.黄土高塬沟壑区水土保持对小流域地表径流的影响[J].水利学报,1999,(2)：71-75.
[24]穆兴民,王飞,李靖,等.水土保持措施对河川径流影响的评价方法研究进展[J].水土保持通报,2004,24(3)：73-78.
[25]Bosch J M, Hewlett J D.A review of catchment experiments to determine the effect of vegetation changes on water yield and evapotranspiration[J].Journal of Hydrology,1982,(103):323-333.
[26]Bari M A, Smettem K R J, Sivapalan M.Understanding changes in annual runoff following land use changes:a systematic data-based approach[J].Hydrological Processes,2005, (19):2463-2479.
[27]Post D A. Identification of relationships between catchment-scale hydrologic response and landscape attributes [D]. PhD Dissertation. Australian National University,Australian,1996.
[28]Wang G X,Liu J Q,Kubota J,et al. Effects of land-use changes on hydrological processes in the middle Basin of the Heihe River, northwest China[J]. Hydrologic Processes,2007,21:1370-1382.
[29]梁国付.伊洛河流域景观动态及其径流效应研究[D].南京：河海大学,2010.
[30]徐艳会.基于SWIM模型分析土地利用变化对黄前流域产流的影响[D].泰安：山东农业大学,2011.
[31]高娃.土地利用变化对泾河水系东川流域径流的影响[D].呼和浩特：内蒙古农业大学,2010.
[32]张蕾娜,李秀彬.用水文特征参数变化表征人类活动的水文效应初探——以云州水库流域为例[J].资源科学,2004,26(2)：62-67.
[33]陈军锋.土地利用变化对流域水文的影响——以长江上游梭磨河流域为例[D].北京：中国科学院地理科学与资源研究所,2002.
[34]Conway D.Understanding the hydrological impacts of land-cover and land-use change[C].IHDP Update,2001,(1):5-6.
[35]Crawford N.H, Linsley R K.Digital simulation in hydrology:Stanford Watershed Model IV [R].Tech.Rep.No.39,Stanford Univ,Palo Alto,Calif.1966.
[36]王中根,刘昌明,吴险峰.基于DEM的分布式水文模型研究综述[J].自然资源学报,2003,18(2)：1-6.
[37]左其亭,王中根.现代水文学[M].郑州：黄河水利出版社,2002.
[38]刘革非.气候变化与土地利用变化对泾河流域径流和输沙的影响[D].北京：中国林业科学研究院,2011.
[39]Karvonen T, Koivusalo H, Jauhainen M, et al.A hydrological model for predicting runoff from different land use areas [J].Journal of Hydrology,1999, (217):253-265.
[40]Kite G W, Ellehoj E,Dalton A.GIS for large-scale watershed modeling in geographical information systems in hydrology [A]. VP Singh, Kluwer Academic Publishers,Dordrecht,Netherlands,1996.237-268.
[41]熊立华,郭生练,田向荣.基于DEM的分布式流域水文模型及应用[J].水科学进展,2004,15(4)：517-520.
[42]Onstad C A, Jamieson D GModelling the effects of land use modifications on runoff[J].Water Resources Research,1970,6(5):1287-1295.
[43]Parkin G, O'Donnell G,Ewen J,et al.Validation of catchment models for predicting land-use and climate change impacts-Case study for a Mediterranean catchment[J]. Journal of Hydrology,1996,(175):595-613.
[44]邓慧平,李秀彬,陈军锋,等.流域土地覆被变化水文效应的模拟——以长 江上游源头区梭磨河为例[J].地理学报,2003,25(1)：53-62.
[45]陈军锋,李秀彬.土地覆被变化的水文响应模拟研究[J].应用生态学报,2004,15(5)：833-836.
[45]王腊春,周寅康,许有鹏等.太湖流域洪涝灾害损失模拟及预测[J].自然灾害学报,2000,9(1)：33-39.
[46]Wu W,Hall Charles A S,Scatena F N. Modelling the impact of recent land-cover changes on the stream flows in northeastern Puerto Rico[J]. Hydrological Processes, 2007,21(21):2944-2956.
[47]Beighley R E, Melack J M, Dunne T. Impacts of climatic regimes and urbanization on streamflow in California coastal watersheds [J]. Journal of the American Water Resources Association,2003,39(6):1419-1433.
[48]李道峰.黄河河源区径流对气候和土地覆被变化的响应[D].北京：北京师范大学,2003.
[49]Klocking B,Haberlandt U. Impact of land use changes on water dynamics--a case study in temperate meso and macro scale river Basins [J]. Physics and Chemistry of the Earth,2002,27:619-629.
[50]Bhaduri B,Grove M,Lowry C. Assessing the long-term hydrologic impact of land use change:Cuppy McClure watershed,Indiana[J]. Journal of the American Water Resources Association.1997,89(11):94-106.
[51]Fohrer N,Haverkamp S,Eckhardt K,et al. Hydrologic response to land use changes on the catchment scale[J]. Physics and Chemistry of the Earth (B),2001,26: 577-582.
[52]Fohrer N,Haverkamp S, Frede H G. Assessment of the effects of land use patterns on hydrologic landscape functions:development of sustainable land use concepts for low mountain range areas [J]. Hydrological Processes,2005,19(3):659-672.
[53]Krysanova V,Hattermann F,Wechsung F. Development of the ecohydrological model SWIM for regional impact studies and vulnerability assessment [J]. Hydrological Processes,2005,19(3):763-783.
[54]曹丽娟,张冬峰,张勇,等.土地利用变化对长江流域气候及水文过程影响的敏感性研究[J].大气科学,2010,34(4)：726-736.
[55]郑璟,方伟华,史培军,等.快速城市化地区土地利用变化对流域水文过程影响的模拟研究：以深圳市布吉河流域为例[J].自然资源报,2009,24(9)：1561-1572.
[56]高超,翟建青,陶辉,等.巢湖流域土地利用/覆被变化的水文效应研究[J].自然资源学报,2009,24(10)：1794-1802.
[57]王艳君,吕宏军,施雅风等.城市化流域的土地利用变化对水文过程的影响——以秦淮河流域为例[J].自然资源学报,2009,24(1)：30-36
[58]李恒鹏,王旭强,杨桂山等.基于单元格网的STREAM分布式水文模型及其应用—以太湖上游西苕溪流域为例[J].长江流域资源与环境,2007,16(6)：715-720.
[59]田宇鸣,李新.土地利用/覆被变化(LUCC)环境效应研究综述[J].环境科学与管理,2006,31(05)：64-68.
[60]Turner I B L,Merwr N B, Slole D L, et al. IGBP ReportsNo.35.Land use and land cover change(LUCC):Science/research plan[R].1995.
[61]史德明.长江流域水土流失与洪涝灾害关系剖析[J].土壤侵蚀与水土保持学报.1999,5(1)：1-6.
[62]张丽琴.城市地区土地利用变化人类活动驱动因子研究—以武汉地区为例[D].武汉：中国地质大学,2005.
[63]傅伯杰,邱扬,王军等.黄土丘陵区小流域土地利用变化对水土流失的影响[J].地理学报.2007,57(6)：717-722.
[64]陈百明,刘新卫,杨红LUCC研究的最新进展评述[J].地理科学进展,2003,21(1)：22-29.
[65]Land use and land cover change science/research plan[R]. IGBP Report, 1996(35),HDP Report,1996,7:8.
[66]史培军,宫鹏,李晓兵等.土地利用土地覆盖变化研究的方法与实践[M].北京：科学出版社,2000.
[67]邵怀勇,仙巍,周万村等.三峡工程实施十年间库区土地利用/覆被时空变化研究——以开县为例[J].水土保持研究,2007,14(3)：243-245,248.
[68]高照良,穆兴民.黄土水蚀风蚀交错区土地利用/覆被时空变化研究——以陕西省神木县六道沟流域为例[J].水土保持学报,2004,18(05)：150-154.
[69]杨桄,卢珊,王宗明等.基于遥感和GIS的长岭县土地利用/覆被时空变化研究[J].吉林农业大学学报.2006.28(1)：63-67.
[70]邹滨,杨令宾,佟志军,李欣欣等.半干旱环境下的土地利用/覆被时空变 化研究——以吉林省通榆县为例[J].遥感技术与应用,2007,22(05)602-607.
[71]李秀彬.全球环境变化研究的核心领域——土地利用/土地覆盖被变化的国际研究动向[J].地理学报,1996,51(6)：553-558.
[72]倪绍祥.土地利用履被变化研究的几个问题[J].自然资源学报,2005,20(6)：933-937.
[73]李静,赵庚星,田素锋,等.论土地利用/土地覆盖变化驱动力研究[J].国土资源科技管理.2004,21(1)：22-25.
[74]McNeill J,Alves D,Arizpe L,etal. Toward a typology and regionalization of land-coverand land-use changeReportofworking groupB [C]//MeyerW B, Turner Ⅱ B L. Changes in land use and land cover:A GlobalPerspective. Cambridge Cambridge University Press,1994.
[75]Ehrlich P R, Daily C C. Population extiction and saving bio-diversity[J]. Ambio, 1993,22(2-3):64-68.
[76]张佳华,王长耀.人类活动影响下科尔沁沙地沙漠化动态的敏感性分析及灰色预测[J].应用生态学报,1999,10(2)：163-166.
[77]李静,赵庚星,范瑞彬.黄河三角洲土地利用及土地覆盖变化驱动力分析[J].西北农林科技大学学报(自然科学版).2003,31(3)：117-122.
[78]李百红,赵庚星,董超等.基于遥感和GIS的黄河三角洲盐化土地动态及其驱动力分析[J].自然资源学报.2011.
[79]杨桂山.长江三角洲近50年耕地数量变化的过程与驱动机制研究[J].自然资源学报,2001,16(2)：121-127.
[80]王艳君,姜彤,吕宏军.快速城市化地区的土地利用时空动态变化研究——以南京市为例[J].长江流域资源与环境.2005,14(2)：168-172.
[81]顾朝林.北京土地利用/覆盖变化机制研究[J].自然资源学报,1999,14(4)307-312.
[82]唐华俊,吴文斌,杨鹏,等.土地利用/土地覆被变化(LUCC)模型研究进展[J].地理学报,2009,64(4)：456-468.
[83]陈佑启.中国土地利用变化及其影响的空间建模分析[J].地理科学进展,2000,19(2)：116-127.
[84]蔡运龙.土地利用/土地覆被变化研究：寻求新的综合途径[J].地理研究, 2001,20(6)：645-652.
[85]杨梅,张广录,侯永平.区域土地利用变化驱动力研究进展与展望[J].地理与地理信息科学.2011,27(1)：95-100.
[86]Clarke K C, Hoppen S, Gaydos L. A self-modifying cellular automaton model of historieal urbanization in the SanFrancisco Bay area[J].Environment and Planning B:Planning and Design,1997,24:247-261.
[87]Whiter, Engeleng, Uljee. High-resolution integrated modeling of the spatial dynamics of urban and regional systems[J].ComPuters.Environment and Urban Systems,2000,24:383-400.
[88]Wuf, Webster C J.Simulating artificial cities in a GIS environment:Urban growth under alternative regulative regimes[J].International Journal of Geographical Information Seienee,2000,14(7):625-648.
[89]Li X, Yen A G O.Datamining of cellular automatas, transition rules[J]. International Journal of Geographical Information Seience,2004,18 (8):723-744.
[90]刘淑燕,余新晓,李庆云,等.基于CA-Markov模型的黄土丘陵区土地利用变化[J].农业工程学报,2010,26(11)：297-303.
[91]Vorosmarty C J,Green P, Salisbury J,et al. Global water resources:vulnerability from climate change and population growth[J]. Science,2000,289:284-288.
[92]石赞赞,董延军,李杰,等.东江流域土地覆被变化的水文响应模拟研究[J].人民长江,2009,(06)：27-30.
[93]Bronstert Axel,Daniel Niehoff,Gerd Burger.Effects of climate and land-use change on storm runoff generation:present knowledge and modelling capabilities [J]. Hydrological Processes,2002,(16):509-529.
[94]Huang H J,Cheng S J,Wen J C,et al. Effect of growing watershed imperviousness on hydrograph parameters and peak discharge[J]. Hydrological Processes,2008, 22(13):2075-2085.
[94]许有鹏,丁瑾佳,陈莹.长江三角洲地区城市化的水文效应研究[J].水利水运工程学报,2009,(4)：67-73.
[95]Chang H. Comparative streamflow characteristics in urbanizing Basins in the Portland Metropolitan Area,Oregon, USA[J]. Hydrological Processes,2007,21(2): 211-222.
[95]刘敏,许世远,侯立军,欧冬妮.长江三角洲土地利用/土地覆被动态变化及其环境效应[J].资源科学,2010,32(8)：1533-1537.
[96]李丽娟,姜德娟,杨俊伟等.陕西大理河流域土地利用/覆被变化的水文效应[J].地理研究.2010,29(7)：1232-1243.
[96]史培军,袁艺,陈晋.深圳市土地利用变化对流域径流的影响[J].生态学报,2001,21(7)：1041-1049.
[97]Gremillion P,Gonyeau A,Wanielista M. Application of alternative hydrograph separation models to detect changes in flow paths in a watershed undergoing urban development[J]. Hydrological Processes,2000,14(8):1485-1501.
[98]Xu Youpeng, Xu Jintao, Ding Jinjia et al., Impacts of urbanization on hydrology in the Yangtze River Delta, China[J].Water Science &Techonology-WST,2010,1221-1229.
[99]Chin A. Urban transformation of river landscapes in a global context [J]. Geomorphology,2006,79:460-487.
[100]凌敏华.基于GIS的水资源评价及系统开发[D].郑州：郑州大学,2006.
[101]Leopold L B. Hydrology for Urban Planning--A Guidebook on the Hydrologic Effects of Urban Land Use.U.S [J]. Geological Survey Circular, Washington D.C., 1968,554.
[102]Hammer T R. Stream channel enlargement due to urbanization [J]. Water Resources Research,1972,8:139-167.
[103]Hollis G E. The Effect of Urbanization on Floods of Different Recurrence Interval [J]. Water Resources Research,1975,11(3),431-435.
[104]Brun S E, Band L E. Simulating runoff behavior in an urbanizing watershed. Computers [J]. Environment and Urban Systems,2000,24:5-22.
[105]Camorani G, Castellarin A, Brath A. Effects of land-use changes on the hydrologic response of reclamation systems [J]. Physics and Chemistry of the Earth, 2005,30:561-574.
[106]郑璟,袁艺,冯文利等.土地利用变化对地表径流深度影响的模拟研究——以深圳地区为例[J].自然灾害学报,2005,14(6)：77-82.
[107]盛前丽.香溪河流域土地利用变化径流效应研究[D].北京：北京林业大学,2008.
[108]秦莉俐,陈云霞,许有鹏.城镇化对径流的长期影响研究[J].南京大学学报(自 然科学),2005,41(3)：279-285.
[109]徐光来,许有鹏,徐宏亮.城市化水文效应研究进展[J].自然资源学报,2010,25(12)：2171-2178.
[110]韩昌来,毛锐.太湖水系结构特点及其功能的变化[J].湖泊科学,1997,9(4)：300-306.
[111]袁雯,杨凯,唐敏,等.平原河网地区河流结构特征及其对调蓄能力的影响.地理研究,2005,24(5)：717-724.
[112]胡淑萍.北京山区典型流域防护林体系对位配置研究[D].北京：北京林业大学,2008.
[113]Calder I R.Land use impacts on water resources.Background Paper No.1.In Land-water Linkages in Rural Watersheds[R].Electronic Workshop, FAO:Rome,18 September-27 October,2000.
[114]石培礼,李文华.森林植被变化对水文过程和径流的影响效应[J].自然资源学报,2001,16(5)：481-487.
[115]周晓峰,赵惠勋,孙慧珍.正确评价森林水文效应[J].自然资源学报,2001,16(5)：420-426.
[116]谢晓云,邓亚东,梁虹.基于SCS模型的岩溶地区生态恢复的水文响应研究[J].水科学与工程技术.2011,(03)：43-45.
[117]何绍福,马剑,李春茂.“3S”技术发展综述[J].三明高等专科学校学,2001,18(3)：50-54.
[118]马莉,宋庆.“3S”集成技术研究现状的综述[J].资源环境与发展,2009,(2)：32-35.
[119]马剑.基于“3S”技术的森林草地动态变化研究.[D]昆明：云南师范大学,2001.
[120]侯建楠.基于3S技术的哈日图热格国家森林公园森林调查研究[D].乌鲁木齐：新疆师范大学,2008.
[121]何凯.“3S”集成技术在合成孔径雷达中的应用研究[D].武汉：武汉理工大学,2003.
[121]李德仁.论21世纪遥感与GIS的发展.武汉大学学报(信息科学版),2003,28(2)：127-131.
[122]李芝喜.林业遥感[M].吉林：东北林业大学出版社,1990.
[123]郝桂娟.大兴安岭东麓旱作丘陵区耕地质量演变与可持续利用[D].北京：中国农业科学院,2009.
[124]马瑞.RS和GIS技术支持下的黄土丘陵沟壑区退耕还林还草决策系统研究[D].兰州：甘肃农业大学,2006.
[125]田庆久,闵祥军.植被指数研究进展[J].地球科学进展,1998,13(4)：327-333.
[126]Bhan S K, Saha S K, Pade L M.Use of remote sensing and GIS technology in sustainable [J]. Agricultural Management and Development,1997, (4).
[127]陆守一,唐小明.地理信息系统使用教程[M].北京：中国林业出版社,1998.
[128]徐冠华,孙枢.迎接“数学地球”的挑战[J].遥感学报,1999,13(2)：86-88.
[129]Colby J D and Keating P L.Landcover classification using Landsat TM Imagery in the tropical highlands:the influence of anisotropic reflectance[J]. Remote Sensing, 1998, (8).
[130]Arnold J G, Williams J R, Srinivasan R, et al. Large area hydrologic modeling andassessment Part I:Model development [J]. Journal of the American Water ResourcesAssociation.1998,34 (1):73-89.
[131]Neitsch S L, Arnold J G, Kiry J R, et al. Soil and water assessment tool user's manual[M].Temple:Grassland,soil and Water Research Laboratory, Agricultural Research Service,2002.
[132]王晓燕.非点源污染及其管理[M].北京：海洋出版社,2003.
[133]肖军仓,周文斌,罗定贵,等.非点源污染模型SWAT用户应用指南[M].北京：地质出版社,2010.
[134]郝芳华,程红光,杨胜天.非点源污染模型：理论方法与应用[M].北京：中国环境科学出版社,2006.
[134]王振涛,王腊春SWAT模型土壤物理属性数据遥感反演建库研究[J].水利水电技术,2011,42(11)：88-91.
[135]Arnold J G, Allen P M. Estimating hydrologic budgets for three illinois watersheds [J] J Hydrol,1996,176 (1):57-77.
[135]王振涛.地表覆盖数据对水文模拟的影响[D].南京：南京大学,2012.
[136]Amatya D M, Jha M K, Williams T M, et al. SWAT-based Streamflow and Embayment Modeling of a Karst affected chapel branch watershed[R]. SC. Trans. Of the ASABE,2011.
[137]Cho J, Mostaghimi S, Kang MS. Development and application of a modeling approach for surface water and groundwater interaction[J]. Agr Water Manage,2010, 97(1):123-130.
[138]Larose M, Heathman G C, Norton D. et al. Impacts of conservation buffers and grasslands on total phosphorus loads using hydrological modeling and remote sensing techniques [J]. Catena,2011.
[139]Lee M S, Park G, Park M J, et al. Evaluation of non-point source pollution reduction by applying Best Management Practices using a SWAT model and QuickBird high resolution satellite imagery [J]. Journal of Environmental Sciences, 2010,22(6):826-833.
[140]Nie W, Yuan Y, Kepner W, et al. Assessing impacts of Landuse and Landcover changes on hydrology for the upper San Pedro watershed[J]. J Hydrol,2011.
[141]Lenhart T, Eckhardt K, Fohrer N, et al. Comparison of two different approaches of sensitivity analysis [J]. Physics and Chemistry of the Earth, Parts A/B/C,2002, 27(9):645-654.
[142]Chaubey I, Cotter A S, Costello T A, et al. Effect of DEM data resolution on SWAT output uncertainty[J]. Hydrol Process,2005,19(3):621-628.
[143]Jham G P W, Secchl S, Others. Effect of watershed subdivision on SWAT flow, sediment, and nutrient predictions [J]. J Am Water Resour As,2004,40(3):811-825.
[144]关作正,石岚,徐丽娜.黄河流域托万区间SWAT模型土壤属性数据库的建立[J].内蒙古水利,2009(4)：5-7.
[145]王建鹏,崔远来.水稻灌区水量转化模型及其模拟效率分析[J].农业工程学报,2011(1)：22-28.
[146]陈小凤.基于SWAT模型的白莲河流域径流模拟研究[J].水电能源科学,2009(1)：21-23.
[147]冯夏清,章光新,尹雄锐.基于SWAT模型的乌裕尔河流域气候变化的水文响应[J].地理科学进展,2010(7)：827-832.
[148]王艳君,吕宏军,姜彤.子流域划分和DEM分辨率对SWAT径流模拟的影响研究.[J]水文,2008,28(03)：22-25.
[149]罗巧,王克林,王勤学.基于SWAT模型的湘江流域土地利用变化情景的径流模拟研究[J].中国生态农业学报,2011(6)：1431-1436.
[150]陆地水文.中国地理与资源文摘[J].2010.
[151]毕华兴,中北理.遥感和地理信息系统与水文学整合研究进展[J],水土保持学报.2002,16(2)：45-49.
[152]杜文才,夏岑岭.水文水资源遥感研究中的若干问题[J].河海科技进展。1991,11(1)：31-39.
[153]彭定志.基于RS和GIS的水文模型以及洪灾监测评估系统的研究[D].武汉：武汉大学,2005.
[154]陈忠合,苗力欣,王云.遥感与GIS在水资源管理中的应用[J].河南水利与南水北调.2007,(2)：12-13.
[155]刘晓鹏,向丽,戴晓晖.地理信息系统在水文学中的应用现状与发展趋势[J].新疆水利,1999,(2)：8-17.
[156]李纪人.遥感与水问题[J],国土资源遥感.1999,41(3)：23-27.
[157]李纪人.遥感和GIS在干旱和半干旱地区水资源管理中的应用[J].水利水电科技进展,2002,22(5)：1-4.
[158]张炜,贺瑞敏,张静芳等.遥感技术在现代水文学中的应用[J],内蒙古水利,2006,(4)：6-7.
[159]Barrett. The Bristol Method of Satellite improved rainfall Monitoring [M]. In: Precipitation measurements from Space, Edited by DAttlas and Thiele,1981.
[160]何延波,杨琨.遥感和地理信息系统在水文模型中的应用[J].地质地球化学,1999,27(2)：99-103.
[161]刘凤莲,陈植华.流域水文模型发展展望[J].地质灾害与环境保护,2005,16(1)：71-71.
[162]杨海龙.三峡库区小流域森林植被理水调洪规律的研究[D].北京：北京林业大学,2004.
[163]李纪人.遥感和地理信息系统在分布式流域水文模型研制中的应用[J].水文,1997,(3)：8-12.
[164]Travaylia C.Reconniasance Groundwater Appraisalal Bohol Island. Philippiness [R].by Satellite Data Analysis, FAO,1987.
[165]Rango. Resolution in operational remote sensing of snow cover[R].In:IAHS, Pub.1985,145:371-382.
[166]Martinee. Snowmelt-Runoff Model for stream flow forcast [J].Nordic Hydrol., 1975,16(3).
[167]Griffith. Rainfall estimation from Geosynchranus Satellite Imagery-Visible and Infred Studied[J].Mon.Weath.Rev,1978,106:1153-1171.
[168]陈怀亮,毛留喜,冯定元.遥感监测土壤水分的理论、方法及进展[J].遥感技术与应用.1999,14(2)：55-65.
[169]杨胜天,刘昌明.黄河流域土壤水分遥感计算及水循环过程分析[J].中国科学E辑技术科学2004,34(增刊)1-12.
[170]张仁华,孙晓敏,刘纪远等.定量遥感反演作物蒸腾和土壤水分利用率的区域分异[J].中国科学,D辑,2001,31(1)：959-968.
[171]Zhang Renhua,Su Hongbo,Li Zhaoliang, etal. The Potential information in the temperature difference between shadow and sunlit of surfaces and a new way of retrieving the soil molsture[J]. Seienee in China(SeriesD),2001,44(2):112-123.
[172]张超,王会肖.土壤水分研究进展及简要评述[J].干旱地区农业研究,2003,21(4)：117-125.
[173]刘畅.栽针保阔林分土壤水分动态及影响因子分析[D].哈尔滨：东北林业大学,2007.
[174]刘明岗,万东辉,姬忠光.遥感在水资源管理中的应用[J].黑龙江水利科技,2008,36(3)：82-83.
[175]魏成阶,王世新.遥感技术在我国洪涝灾害监测评估中的作用[J].中国科学院院刊,1998,(6)：443-447.
[176]魏文秋,陈秀万·抗洪救灾遥感系统中河道防洪信息系统的实验研究[J]·水科学进展,1994,5(1)：71-77.
[177]李纪人.遥感在水利行业中的应用[J].卫星应用,2012(1)：61-64.
[178]张长江,刘衍.RS和GIS技术及其在水资源管理中的应用[J].山东水利,2003,(12)：21-22.
[179]姚鹤岭.GIS在水资源综合开发中的应用[J].人民黄河,2000,22(3)：19-21.
[180]杨柳俊,张宇亮.浅议应用遥感技术开展水资源评价[J].治淮,2011,(12)：10-11.
[181]李相明.遥感和地理信息系统在水资源管理中的应用[J].枣庄师专学报 2001,18(2).
[182]沈芳,匡定波.太湖流域典型中小湖群水资源利用及动态变化的遥感调查与分[J].遥感学报,2003,7(03)：221-226.
[183]王丽娟,景耀全.浅谈遥感监测水环境[J].环境技术2004,(06)：15-16.
[184]詹小国,文余源.3S技术在长江水利中的应用及展望[J].人民长江,2001,32(12)：27-29.
[185]D.R麦克佛森GIS在南非水资源管理中的应用[J].水利水电快报,1995,(2)：22-26.
[186]王疆霞,李云峰等.GIS技术及其在水文学和水资源管理方面的应用[J].西北地质,2003,36(144).
[187]James L D. NSF research in hydrological sciences [J]. Journal of Hy-drology, 1995,17(2):3-14.
[188]彭定志,熊立华,郭生练等.MODIS在水文水资源中的应用与展望[J].水科学进展,2004,15(05)：683-688.
[189]李常斌,冯兆东,马金珠,等.区域尺度分布式水文模拟的时空分辨率[J].干旱区研究,2008,25(02)：169-173.
[190]叶许春,张奇,刘健等.土壤数据空间分辨率对水文过程模拟的影响[J].地理科学进展,2009,28(04)：575-582.
[191]Di Luzio M., Arnold J.G., Srinivasan R. Effect of GIS data quality on small watershed stream flow and sediment simulations [J]. Hydrol Process,2005,19(3SI): 629-650.
[192]沈金祥,陈曦,杨辽等.额尔齐斯河-斋桑湖流域近20年来土地利用/土地覆被时空演变[J].干旱区地理.2010,(02)；189-195.
[193]孙秀邦,范伟,严平等.遥感影像土地覆被分类研究进展[J].中国农学通报.2007,23(09)：607-610.
[194]冯春,陈建平.土地利用/土地覆盖研究中遥感图像分类精度的提高方法[J].地理与地理信息科学.2003,19(03)：26-28.
[195]陈军,陈晋,宫鹏.全球地表覆盖遥感制图的发展动向,2010.
[196]苏北：http://www.hudong.co,2011-06-13
[197]李增福江苏省南水北调受水区水文模型研究[D].南京：南京大学,2011.
[198]张廷斌.西藏谢通门县铜金矿带遥感图像蚀变信息提取及多源数据融合在成矿预测中的应用[D].成都：成都理工大学,2006.
[199]雷四华.平原河网地区水流模型及其在水资源调度中的应用[D].南京：河海大学,2007.
[200]马倩.江苏省地表水资源评价与利用研究[J].中国农村水利水电.2007,(11)：74-76.
[201]蔡永明,张科利,李双才.不同粒径间土壤质地资料的转换问题研究[J].土壤学报.2003,40(4)：511-517.
[202]门明新.基于空间数据库的土壤侵蚀和碳氮储量研究[D].北京：中国农业大学,2005.
[203]Williams J R, Sharply A N. EPIC-Erosion Productivity Impact Calculator I. Model Documentation. US Department of Agriculture Technical Bulletin. N.1990.
[204]朱琰.太湖流域实时洪水预报调度系统研究[D].南京：河海大学,2003.
[205]周奕君.基于ArcEngine的洪水风险管理信息系统及三维分析研究[D].上海：同济大学,2008.
[206]付苗苗.苏州澄湖地区晚更新世沉积记录与环境变迁[D]上海：华东师范大学,2009.
[207]太湖流域_太湖流域简介.http://www.baikedq.c,2010-05-07.
[208]马振坤.太湖流域水量水质实时监测决策支持系统模型研究及应用[D].南京：河海大学,2007.
[209]张继宗.太湖水网地区不同类型农田氮磷流失特征[D].北京中国农业科学院,2006.
[210]王腊春,许有鹏等.太湖地区河网调蓄能力分析[J].《南京大学学报》(自然科学),1999,35(6)：712-718.
[211]王新军,穆荣,张忠生.浅谈第二次全国土地调查土地利用分类.测绘与空间地理信息.2011,34(04)：13-16.
[212]岳健,张雪梅.关于我国土地利用分类问题的讨论[J].干旱区地理.2003,26(01)：78-88.
[213]张静,郭玉芳.地理国情监测中地表覆盖分类体系研究[J].测绘标准化.2012,28(3)：8-10.
[214]周炳中,陈浮,包浩生等.长江三角洲土地利用分类研究[J].资源科学.2002,24(02)：88-92.
[215]林爱文,黄仁涛,佐藤洋平.对我国新的土地分类体系问题的探讨[J].国土资源科技管理.2002,19(3)：7-10.
[216]李树国,马仁会.对我国土地利用分类体系的探讨[J].中国土地科.2000,14(01)：39-40.
[217]许有鹏等.长江三角洲地区城市化对流域水系与水文过程的影响[M].北京：科学出版社,2012
[2]夏军,左其亭.国际水文科学研究的新进展[J].地球科学进展,2006,21(3)：259-261.
[3]尉颖琪.从国际水文计划看水文研究变化趋势[J].科技资讯,2011,28(10a)：143.
[4]李丽娟,姜德娟,李九一等.土地利用/覆被变化的水文效应研究进展[J].自然资源学报,2007,22(2)：211-224.
[5]张磊,吴炳方.关于土地覆被遥感监测的几点思考[J].国土资源遥感,2011,(1)：15-20.
[6]Bartholome'e A S, Belward. GLC 2000:A new approach to global land cover mapping from earth observation data [J]. International Journal of Remote Sensing, 2005,26(9):1959-1977.
[7]李秀彬.土地覆被变化的水文水资源效应研究——社会需求与科学问题.中国地理学会自然地理专业委员会.土地覆被变化及其环境效应论文集[C]..北京：星球地图出版社,2002.1-6.
[8]白淑英,陈灵梅,王莉等.土地利用/覆被变化研究现状与展望[J].安徽农业科学.2010,38(30)：17003-17005.
[9]周广胜,王玉辉.土地利用/覆盖变化对气候的反馈作用[J].自然资源学报,1999,14(4)：318-322.
[10]DeFries R, Eshleman K N. Land-use change and hydrologic processes:A major focus for the future[J]. Hydrological Processes,2004,18(11):2183-2186.
[11]赵启学,郑艳波,周庆东.大伙房水库以上流域人类活动对水库径流的影响[J].东北水利水电.2008,26(12)：32-33.
[12]Lahmer W, Pfutzner B, Becker A. Assessment of land-use and climate change impacts on the mesoscale [J]. Physics and Chemistry of the Earth,2001,26:565-575.
[13]陈莹.长江三角洲地区中小流域城镇化的水文效应分析[D].南京大学,2009.
[14]刘贤赵.论水文尺度问题[J].干旱区地理,2004,27(1)：61-65.
[15]孙庆艳.华北土石山区典型流域森林植被水文生态过程响应研究[D].北京： 北京林业大学,2008.
[16]傅国斌,刘昌明.遥感技术在水文学中的应用与研究进展[J].水科学进展,2001,12(4)：547-559.
[17]李春晖,杨志峰.水资源评价进展与存在的几个问题[J].水土保持学报,2004,18(5)：189-192.
[18]Turner B L,Moss R H,Skole D L. Human dimensions of global environmental change programme [R].HDP Report No.5,1993.
[19]王晓云.流域土地利用变化对径流影响问题的研究[D].天津：天津大学建筑工程学院,2008.
[20]陈军锋,李秀彬.森林植被变化对流域水文影响的争论[J].自然资源学报,2001,16(5)：474-480.
[21]古丽巴哈·扎依提.乌鲁木齐市土地利用/覆被变化及其水文水资源效应研究[D].乌鲁木齐：新疆师范大学,2011.
[22]中野秀章(李云森译).森林水文学[M].北京：中国林业出版社,1983.
[23]穆兴民,王文龙,徐学选.黄土高塬沟壑区水土保持对小流域地表径流的影响[J].水利学报,1999,(2)：71-75.
[24]穆兴民,王飞,李靖,等.水土保持措施对河川径流影响的评价方法研究进展[J].水土保持通报,2004,24(3)：73-78.
[25]Bosch J M, Hewlett J D.A review of catchment experiments to determine the effect of vegetation changes on water yield and evapotranspiration[J].Journal of Hydrology,1982,(103):323-333.
[26]Bari M A, Smettem K R J, Sivapalan M.Understanding changes in annual runoff following land use changes:a systematic data-based approach[J].Hydrological Processes,2005, (19):2463-2479.
[27]Post D A. Identification of relationships between catchment-scale hydrologic response and landscape attributes [D]. PhD Dissertation. Australian National University,Australian,1996.
[28]Wang G X,Liu J Q,Kubota J,et al. Effects of land-use changes on hydrological processes in the middle Basin of the Heihe River, northwest China[J]. Hydrologic Processes,2007,21:1370-1382.
[29]梁国付.伊洛河流域景观动态及其径流效应研究[D].南京：河海大学,2010.
[30]徐艳会.基于SWIM模型分析土地利用变化对黄前流域产流的影响[D].泰安：山东农业大学,2011.
[31]高娃.土地利用变化对泾河水系东川流域径流的影响[D].呼和浩特：内蒙古农业大学,2010.
[32]张蕾娜,李秀彬.用水文特征参数变化表征人类活动的水文效应初探——以云州水库流域为例[J].资源科学,2004,26(2)：62-67.
[33]陈军锋.土地利用变化对流域水文的影响——以长江上游梭磨河流域为例[D].北京：中国科学院地理科学与资源研究所,2002.
[34]Conway D.Understanding the hydrological impacts of land-cover and land-use change[C].IHDP Update,2001,(1):5-6.
[35]Crawford N.H, Linsley R K.Digital simulation in hydrology:Stanford Watershed Model IV [R].Tech.Rep.No.39,Stanford Univ,Palo Alto,Calif.1966.
[36]王中根,刘昌明,吴险峰.基于DEM的分布式水文模型研究综述[J].自然资源学报,2003,18(2)：1-6.
[37]左其亭,王中根.现代水文学[M].郑州：黄河水利出版社,2002.
[38]刘革非.气候变化与土地利用变化对泾河流域径流和输沙的影响[D].北京：中国林业科学研究院,2011.
[39]Karvonen T, Koivusalo H, Jauhainen M, et al.A hydrological model for predicting runoff from different land use areas [J].Journal of Hydrology,1999, (217):253-265.
[40]Kite G W, Ellehoj E,Dalton A.GIS for large-scale watershed modeling in geographical information systems in hydrology [A]. VP Singh, Kluwer Academic Publishers,Dordrecht,Netherlands,1996.237-268.
[41]熊立华,郭生练,田向荣.基于DEM的分布式流域水文模型及应用[J].水科学进展,2004,15(4)：517-520.
[42]Onstad C A, Jamieson D GModelling the effects of land use modifications on runoff[J].Water Resources Research,1970,6(5):1287-1295.
[43]Parkin G, O'Donnell G,Ewen J,et al.Validation of catchment models for predicting land-use and climate change impacts-Case study for a Mediterranean catchment[J]. Journal of Hydrology,1996,(175):595-613.
[44]邓慧平,李秀彬,陈军锋,等.流域土地覆被变化水文效应的模拟——以长 江上游源头区梭磨河为例[J].地理学报,2003,25(1)：53-62.
[45]陈军锋,李秀彬.土地覆被变化的水文响应模拟研究[J].应用生态学报,2004,15(5)：833-836.
[45]王腊春,周寅康,许有鹏等.太湖流域洪涝灾害损失模拟及预测[J].自然灾害学报,2000,9(1)：33-39.
[46]Wu W,Hall Charles A S,Scatena F N. Modelling the impact of recent land-cover changes on the stream flows in northeastern Puerto Rico[J]. Hydrological Processes, 2007,21(21):2944-2956.
[47]Beighley R E, Melack J M, Dunne T. Impacts of climatic regimes and urbanization on streamflow in California coastal watersheds [J]. Journal of the American Water Resources Association,2003,39(6):1419-1433.
[48]李道峰.黄河河源区径流对气候和土地覆被变化的响应[D].北京：北京师范大学,2003.
[49]Klocking B,Haberlandt U. Impact of land use changes on water dynamics--a case study in temperate meso and macro scale river Basins [J]. Physics and Chemistry of the Earth,2002,27:619-629.
[50]Bhaduri B,Grove M,Lowry C. Assessing the long-term hydrologic impact of land use change:Cuppy McClure watershed,Indiana[J]. Journal of the American Water Resources Association.1997,89(11):94-106.
[51]Fohrer N,Haverkamp S,Eckhardt K,et al. Hydrologic response to land use changes on the catchment scale[J]. Physics and Chemistry of the Earth (B),2001,26: 577-582.
[52]Fohrer N,Haverkamp S, Frede H G. Assessment of the effects of land use patterns on hydrologic landscape functions:development of sustainable land use concepts for low mountain range areas [J]. Hydrological Processes,2005,19(3):659-672.
[53]Krysanova V,Hattermann F,Wechsung F. Development of the ecohydrological model SWIM for regional impact studies and vulnerability assessment [J]. Hydrological Processes,2005,19(3):763-783.
[54]曹丽娟,张冬峰,张勇,等.土地利用变化对长江流域气候及水文过程影响的敏感性研究[J].大气科学,2010,34(4)：726-736.
[55]郑璟,方伟华,史培军,等.快速城市化地区土地利用变化对流域水文过程影响的模拟研究：以深圳市布吉河流域为例[J].自然资源报,2009,24(9)：1561-1572.
[56]高超,翟建青,陶辉,等.巢湖流域土地利用/覆被变化的水文效应研究[J].自然资源学报,2009,24(10)：1794-1802.
[57]王艳君,吕宏军,施雅风等.城市化流域的土地利用变化对水文过程的影响——以秦淮河流域为例[J].自然资源学报,2009,24(1)：30-36
[58]李恒鹏,王旭强,杨桂山等.基于单元格网的STREAM分布式水文模型及其应用—以太湖上游西苕溪流域为例[J].长江流域资源与环境,2007,16(6)：715-720.
[59]田宇鸣,李新.土地利用/覆被变化(LUCC)环境效应研究综述[J].环境科学与管理,2006,31(05)：64-68.
[60]Turner I B L,Merwr N B, Slole D L, et al. IGBP ReportsNo.35.Land use and land cover change(LUCC):Science/research plan[R].1995.
[61]史德明.长江流域水土流失与洪涝灾害关系剖析[J].土壤侵蚀与水土保持学报.1999,5(1)：1-6.
[62]张丽琴.城市地区土地利用变化人类活动驱动因子研究—以武汉地区为例[D].武汉：中国地质大学,2005.
[63]傅伯杰,邱扬,王军等.黄土丘陵区小流域土地利用变化对水土流失的影响[J].地理学报.2007,57(6)：717-722.
[64]陈百明,刘新卫,杨红LUCC研究的最新进展评述[J].地理科学进展,2003,21(1)：22-29.
[65]Land use and land cover change science/research plan[R]. IGBP Report, 1996(35),HDP Report,1996,7:8.
[66]史培军,宫鹏,李晓兵等.土地利用土地覆盖变化研究的方法与实践[M].北京：科学出版社,2000.
[67]邵怀勇,仙巍,周万村等.三峡工程实施十年间库区土地利用/覆被时空变化研究——以开县为例[J].水土保持研究,2007,14(3)：243-245,248.
[68]高照良,穆兴民.黄土水蚀风蚀交错区土地利用/覆被时空变化研究——以陕西省神木县六道沟流域为例[J].水土保持学报,2004,18(05)：150-154.
[69]杨桄,卢珊,王宗明等.基于遥感和GIS的长岭县土地利用/覆被时空变化研究[J].吉林农业大学学报.2006.28(1)：63-67.
[70]邹滨,杨令宾,佟志军,李欣欣等.半干旱环境下的土地利用/覆被时空变 化研究——以吉林省通榆县为例[J].遥感技术与应用,2007,22(05)602-607.
[71]李秀彬.全球环境变化研究的核心领域——土地利用/土地覆盖被变化的国际研究动向[J].地理学报,1996,51(6)：553-558.
[72]倪绍祥.土地利用履被变化研究的几个问题[J].自然资源学报,2005,20(6)：933-937.
[73]李静,赵庚星,田素锋,等.论土地利用/土地覆盖变化驱动力研究[J].国土资源科技管理.2004,21(1)：22-25.
[74]McNeill J,Alves D,Arizpe L,etal. Toward a typology and regionalization of land-coverand land-use changeReportofworking groupB [C]//MeyerW B, Turner Ⅱ B L. Changes in land use and land cover:A GlobalPerspective. Cambridge Cambridge University Press,1994.
[75]Ehrlich P R, Daily C C. Population extiction and saving bio-diversity[J]. Ambio, 1993,22(2-3):64-68.
[76]张佳华,王长耀.人类活动影响下科尔沁沙地沙漠化动态的敏感性分析及灰色预测[J].应用生态学报,1999,10(2)：163-166.
[77]李静,赵庚星,范瑞彬.黄河三角洲土地利用及土地覆盖变化驱动力分析[J].西北农林科技大学学报(自然科学版).2003,31(3)：117-122.
[78]李百红,赵庚星,董超等.基于遥感和GIS的黄河三角洲盐化土地动态及其驱动力分析[J].自然资源学报.2011.
[79]杨桂山.长江三角洲近50年耕地数量变化的过程与驱动机制研究[J].自然资源学报,2001,16(2)：121-127.
[80]王艳君,姜彤,吕宏军.快速城市化地区的土地利用时空动态变化研究——以南京市为例[J].长江流域资源与环境.2005,14(2)：168-172.
[81]顾朝林.北京土地利用/覆盖变化机制研究[J].自然资源学报,1999,14(4)307-312.
[82]唐华俊,吴文斌,杨鹏,等.土地利用/土地覆被变化(LUCC)模型研究进展[J].地理学报,2009,64(4)：456-468.
[83]陈佑启.中国土地利用变化及其影响的空间建模分析[J].地理科学进展,2000,19(2)：116-127.
[84]蔡运龙.土地利用/土地覆被变化研究：寻求新的综合途径[J].地理研究, 2001,20(6)：645-652.
[85]杨梅,张广录,侯永平.区域土地利用变化驱动力研究进展与展望[J].地理与地理信息科学.2011,27(1)：95-100.
[86]Clarke K C, Hoppen S, Gaydos L. A self-modifying cellular automaton model of historieal urbanization in the SanFrancisco Bay area[J].Environment and Planning B:Planning and Design,1997,24:247-261.
[87]Whiter, Engeleng, Uljee. High-resolution integrated modeling of the spatial dynamics of urban and regional systems[J].ComPuters.Environment and Urban Systems,2000,24:383-400.
[88]Wuf, Webster C J.Simulating artificial cities in a GIS environment:Urban growth under alternative regulative regimes[J].International Journal of Geographical Information Seienee,2000,14(7):625-648.
[89]Li X, Yen A G O.Datamining of cellular automatas, transition rules[J]. International Journal of Geographical Information Seience,2004,18 (8):723-744.
[90]刘淑燕,余新晓,李庆云,等.基于CA-Markov模型的黄土丘陵区土地利用变化[J].农业工程学报,2010,26(11)：297-303.
[91]Vorosmarty C J,Green P, Salisbury J,et al. Global water resources:vulnerability from climate change and population growth[J]. Science,2000,289:284-288.
[92]石赞赞,董延军,李杰,等.东江流域土地覆被变化的水文响应模拟研究[J].人民长江,2009,(06)：27-30.
[93]Bronstert Axel,Daniel Niehoff,Gerd Burger.Effects of climate and land-use change on storm runoff generation:present knowledge and modelling capabilities [J]. Hydrological Processes,2002,(16):509-529.
[94]Huang H J,Cheng S J,Wen J C,et al. Effect of growing watershed imperviousness on hydrograph parameters and peak discharge[J]. Hydrological Processes,2008, 22(13):2075-2085.
[94]许有鹏,丁瑾佳,陈莹.长江三角洲地区城市化的水文效应研究[J].水利水运工程学报,2009,(4)：67-73.
[95]Chang H. Comparative streamflow characteristics in urbanizing Basins in the Portland Metropolitan Area,Oregon, USA[J]. Hydrological Processes,2007,21(2): 211-222.
[95]刘敏,许世远,侯立军,欧冬妮.长江三角洲土地利用/土地覆被动态变化及其环境效应[J].资源科学,2010,32(8)：1533-1537.
[96]李丽娟,姜德娟,杨俊伟等.陕西大理河流域土地利用/覆被变化的水文效应[J].地理研究.2010,29(7)：1232-1243.
[96]史培军,袁艺,陈晋.深圳市土地利用变化对流域径流的影响[J].生态学报,2001,21(7)：1041-1049.
[97]Gremillion P,Gonyeau A,Wanielista M. Application of alternative hydrograph separation models to detect changes in flow paths in a watershed undergoing urban development[J]. Hydrological Processes,2000,14(8):1485-1501.
[98]Xu Youpeng, Xu Jintao, Ding Jinjia et al., Impacts of urbanization on hydrology in the Yangtze River Delta, China[J].Water Science &Techonology-WST,2010,1221-1229.
[99]Chin A. Urban transformation of river landscapes in a global context [J]. Geomorphology,2006,79:460-487.
[100]凌敏华.基于GIS的水资源评价及系统开发[D].郑州：郑州大学,2006.
[101]Leopold L B. Hydrology for Urban Planning--A Guidebook on the Hydrologic Effects of Urban Land Use.U.S [J]. Geological Survey Circular, Washington D.C., 1968,554.
[102]Hammer T R. Stream channel enlargement due to urbanization [J]. Water Resources Research,1972,8:139-167.
[103]Hollis G E. The Effect of Urbanization on Floods of Different Recurrence Interval [J]. Water Resources Research,1975,11(3),431-435.
[104]Brun S E, Band L E. Simulating runoff behavior in an urbanizing watershed. Computers [J]. Environment and Urban Systems,2000,24:5-22.
[105]Camorani G, Castellarin A, Brath A. Effects of land-use changes on the hydrologic response of reclamation systems [J]. Physics and Chemistry of the Earth, 2005,30:561-574.
[106]郑璟,袁艺,冯文利等.土地利用变化对地表径流深度影响的模拟研究——以深圳地区为例[J].自然灾害学报,2005,14(6)：77-82.
[107]盛前丽.香溪河流域土地利用变化径流效应研究[D].北京：北京林业大学,2008.
[108]秦莉俐,陈云霞,许有鹏.城镇化对径流的长期影响研究[J].南京大学学报(自 然科学),2005,41(3)：279-285.
[109]徐光来,许有鹏,徐宏亮.城市化水文效应研究进展[J].自然资源学报,2010,25(12)：2171-2178.
[110]韩昌来,毛锐.太湖水系结构特点及其功能的变化[J].湖泊科学,1997,9(4)：300-306.
[111]袁雯,杨凯,唐敏,等.平原河网地区河流结构特征及其对调蓄能力的影响.地理研究,2005,24(5)：717-724.
[112]胡淑萍.北京山区典型流域防护林体系对位配置研究[D].北京：北京林业大学,2008.
[113]Calder I R.Land use impacts on water resources.Background Paper No.1.In Land-water Linkages in Rural Watersheds[R].Electronic Workshop, FAO:Rome,18 September-27 October,2000.
[114]石培礼,李文华.森林植被变化对水文过程和径流的影响效应[J].自然资源学报,2001,16(5)：481-487.
[115]周晓峰,赵惠勋,孙慧珍.正确评价森林水文效应[J].自然资源学报,2001,16(5)：420-426.
[116]谢晓云,邓亚东,梁虹.基于SCS模型的岩溶地区生态恢复的水文响应研究[J].水科学与工程技术.2011,(03)：43-45.
[117]何绍福,马剑,李春茂.“3S”技术发展综述[J].三明高等专科学校学,2001,18(3)：50-54.
[118]马莉,宋庆.“3S”集成技术研究现状的综述[J].资源环境与发展,2009,(2)：32-35.
[119]马剑.基于“3S”技术的森林草地动态变化研究.[D]昆明：云南师范大学,2001.
[120]侯建楠.基于3S技术的哈日图热格国家森林公园森林调查研究[D].乌鲁木齐：新疆师范大学,2008.
[121]何凯.“3S”集成技术在合成孔径雷达中的应用研究[D].武汉：武汉理工大学,2003.
[121]李德仁.论21世纪遥感与GIS的发展.武汉大学学报(信息科学版),2003,28(2)：127-131.
[122]李芝喜.林业遥感[M].吉林：东北林业大学出版社,1990.
[123]郝桂娟.大兴安岭东麓旱作丘陵区耕地质量演变与可持续利用[D].北京：中国农业科学院,2009.
[124]马瑞.RS和GIS技术支持下的黄土丘陵沟壑区退耕还林还草决策系统研究[D].兰州：甘肃农业大学,2006.
[125]田庆久,闵祥军.植被指数研究进展[J].地球科学进展,1998,13(4)：327-333.
[126]Bhan S K, Saha S K, Pade L M.Use of remote sensing and GIS technology in sustainable [J]. Agricultural Management and Development,1997, (4).
[127]陆守一,唐小明.地理信息系统使用教程[M].北京：中国林业出版社,1998.
[128]徐冠华,孙枢.迎接“数学地球”的挑战[J].遥感学报,1999,13(2)：86-88.
[129]Colby J D and Keating P L.Landcover classification using Landsat TM Imagery in the tropical highlands:the influence of anisotropic reflectance[J]. Remote Sensing, 1998, (8).
[130]Arnold J G, Williams J R, Srinivasan R, et al. Large area hydrologic modeling andassessment Part I:Model development [J]. Journal of the American Water ResourcesAssociation.1998,34 (1):73-89.
[131]Neitsch S L, Arnold J G, Kiry J R, et al. Soil and water assessment tool user's manual[M].Temple:Grassland,soil and Water Research Laboratory, Agricultural Research Service,2002.
[132]王晓燕.非点源污染及其管理[M].北京：海洋出版社,2003.
[133]肖军仓,周文斌,罗定贵,等.非点源污染模型SWAT用户应用指南[M].北京：地质出版社,2010.
[134]郝芳华,程红光,杨胜天.非点源污染模型：理论方法与应用[M].北京：中国环境科学出版社,2006.
[134]王振涛,王腊春SWAT模型土壤物理属性数据遥感反演建库研究[J].水利水电技术,2011,42(11)：88-91.
[135]Arnold J G, Allen P M. Estimating hydrologic budgets for three illinois watersheds [J] J Hydrol,1996,176 (1):57-77.
[135]王振涛.地表覆盖数据对水文模拟的影响[D].南京：南京大学,2012.
[136]Amatya D M, Jha M K, Williams T M, et al. SWAT-based Streamflow and Embayment Modeling of a Karst affected chapel branch watershed[R]. SC. Trans. Of the ASABE,2011.
[137]Cho J, Mostaghimi S, Kang MS. Development and application of a modeling approach for surface water and groundwater interaction[J]. Agr Water Manage,2010, 97(1):123-130.
[138]Larose M, Heathman G C, Norton D. et al. Impacts of conservation buffers and grasslands on total phosphorus loads using hydrological modeling and remote sensing techniques [J]. Catena,2011.
[139]Lee M S, Park G, Park M J, et al. Evaluation of non-point source pollution reduction by applying Best Management Practices using a SWAT model and QuickBird high resolution satellite imagery [J]. Journal of Environmental Sciences, 2010,22(6):826-833.
[140]Nie W, Yuan Y, Kepner W, et al. Assessing impacts of Landuse and Landcover changes on hydrology for the upper San Pedro watershed[J]. J Hydrol,2011.
[141]Lenhart T, Eckhardt K, Fohrer N, et al. Comparison of two different approaches of sensitivity analysis [J]. Physics and Chemistry of the Earth, Parts A/B/C,2002, 27(9):645-654.
[142]Chaubey I, Cotter A S, Costello T A, et al. Effect of DEM data resolution on SWAT output uncertainty[J]. Hydrol Process,2005,19(3):621-628.
[143]Jham G P W, Secchl S, Others. Effect of watershed subdivision on SWAT flow, sediment, and nutrient predictions [J]. J Am Water Resour As,2004,40(3):811-825.
[144]关作正,石岚,徐丽娜.黄河流域托万区间SWAT模型土壤属性数据库的建立[J].内蒙古水利,2009(4)：5-7.
[145]王建鹏,崔远来.水稻灌区水量转化模型及其模拟效率分析[J].农业工程学报,2011(1)：22-28.
[146]陈小凤.基于SWAT模型的白莲河流域径流模拟研究[J].水电能源科学,2009(1)：21-23.
[147]冯夏清,章光新,尹雄锐.基于SWAT模型的乌裕尔河流域气候变化的水文响应[J].地理科学进展,2010(7)：827-832.
[148]王艳君,吕宏军,姜彤.子流域划分和DEM分辨率对SWAT径流模拟的影响研究.[J]水文,2008,28(03)：22-25.
[149]罗巧,王克林,王勤学.基于SWAT模型的湘江流域土地利用变化情景的径流模拟研究[J].中国生态农业学报,2011(6)：1431-1436.
[150]陆地水文.中国地理与资源文摘[J].2010.
[151]毕华兴,中北理.遥感和地理信息系统与水文学整合研究进展[J],水土保持学报.2002,16(2)：45-49.
[152]杜文才,夏岑岭.水文水资源遥感研究中的若干问题[J].河海科技进展。1991,11(1)：31-39.
[153]彭定志.基于RS和GIS的水文模型以及洪灾监测评估系统的研究[D].武汉：武汉大学,2005.
[154]陈忠合,苗力欣,王云.遥感与GIS在水资源管理中的应用[J].河南水利与南水北调.2007,(2)：12-13.
[155]刘晓鹏,向丽,戴晓晖.地理信息系统在水文学中的应用现状与发展趋势[J].新疆水利,1999,(2)：8-17.
[156]李纪人.遥感与水问题[J],国土资源遥感.1999,41(3)：23-27.
[157]李纪人.遥感和GIS在干旱和半干旱地区水资源管理中的应用[J].水利水电科技进展,2002,22(5)：1-4.
[158]张炜,贺瑞敏,张静芳等.遥感技术在现代水文学中的应用[J],内蒙古水利,2006,(4)：6-7.
[159]Barrett. The Bristol Method of Satellite improved rainfall Monitoring [M]. In: Precipitation measurements from Space, Edited by DAttlas and Thiele,1981.
[160]何延波,杨琨.遥感和地理信息系统在水文模型中的应用[J].地质地球化学,1999,27(2)：99-103.
[161]刘凤莲,陈植华.流域水文模型发展展望[J].地质灾害与环境保护,2005,16(1)：71-71.
[162]杨海龙.三峡库区小流域森林植被理水调洪规律的研究[D].北京：北京林业大学,2004.
[163]李纪人.遥感和地理信息系统在分布式流域水文模型研制中的应用[J].水文,1997,(3)：8-12.
[164]Travaylia C.Reconniasance Groundwater Appraisalal Bohol Island. Philippiness [R].by Satellite Data Analysis, FAO,1987.
[165]Rango. Resolution in operational remote sensing of snow cover[R].In:IAHS, Pub.1985,145:371-382.
[166]Martinee. Snowmelt-Runoff Model for stream flow forcast [J].Nordic Hydrol., 1975,16(3).
[167]Griffith. Rainfall estimation from Geosynchranus Satellite Imagery-Visible and Infred Studied[J].Mon.Weath.Rev,1978,106:1153-1171.
[168]陈怀亮,毛留喜,冯定元.遥感监测土壤水分的理论、方法及进展[J].遥感技术与应用.1999,14(2)：55-65.
[169]杨胜天,刘昌明.黄河流域土壤水分遥感计算及水循环过程分析[J].中国科学E辑技术科学2004,34(增刊)1-12.
[170]张仁华,孙晓敏,刘纪远等.定量遥感反演作物蒸腾和土壤水分利用率的区域分异[J].中国科学,D辑,2001,31(1)：959-968.
[171]Zhang Renhua,Su Hongbo,Li Zhaoliang, etal. The Potential information in the temperature difference between shadow and sunlit of surfaces and a new way of retrieving the soil molsture[J]. Seienee in China(SeriesD),2001,44(2):112-123.
[172]张超,王会肖.土壤水分研究进展及简要评述[J].干旱地区农业研究,2003,21(4)：117-125.
[173]刘畅.栽针保阔林分土壤水分动态及影响因子分析[D].哈尔滨：东北林业大学,2007.
[174]刘明岗,万东辉,姬忠光.遥感在水资源管理中的应用[J].黑龙江水利科技,2008,36(3)：82-83.
[175]魏成阶,王世新.遥感技术在我国洪涝灾害监测评估中的作用[J].中国科学院院刊,1998,(6)：443-447.
[176]魏文秋,陈秀万·抗洪救灾遥感系统中河道防洪信息系统的实验研究[J]·水科学进展,1994,5(1)：71-77.
[177]李纪人.遥感在水利行业中的应用[J].卫星应用,2012(1)：61-64.
[178]张长江,刘衍.RS和GIS技术及其在水资源管理中的应用[J].山东水利,2003,(12)：21-22.
[179]姚鹤岭.GIS在水资源综合开发中的应用[J].人民黄河,2000,22(3)：19-21.
[180]杨柳俊,张宇亮.浅议应用遥感技术开展水资源评价[J].治淮,2011,(12)：10-11.
[181]李相明.遥感和地理信息系统在水资源管理中的应用[J].枣庄师专学报 2001,18(2).
[182]沈芳,匡定波.太湖流域典型中小湖群水资源利用及动态变化的遥感调查与分[J].遥感学报,2003,7(03)：221-226.
[183]王丽娟,景耀全.浅谈遥感监测水环境[J].环境技术2004,(06)：15-16.
[184]詹小国,文余源.3S技术在长江水利中的应用及展望[J].人民长江,2001,32(12)：27-29.
[185]D.R麦克佛森GIS在南非水资源管理中的应用[J].水利水电快报,1995,(2)：22-26.
[186]王疆霞,李云峰等.GIS技术及其在水文学和水资源管理方面的应用[J].西北地质,2003,36(144).
[187]James L D. NSF research in hydrological sciences [J]. Journal of Hy-drology, 1995,17(2):3-14.
[188]彭定志,熊立华,郭生练等.MODIS在水文水资源中的应用与展望[J].水科学进展,2004,15(05)：683-688.
[189]李常斌,冯兆东,马金珠,等.区域尺度分布式水文模拟的时空分辨率[J].干旱区研究,2008,25(02)：169-173.
[190]叶许春,张奇,刘健等.土壤数据空间分辨率对水文过程模拟的影响[J].地理科学进展,2009,28(04)：575-582.
[191]Di Luzio M., Arnold J.G., Srinivasan R. Effect of GIS data quality on small watershed stream flow and sediment simulations [J]. Hydrol Process,2005,19(3SI): 629-650.
[192]沈金祥,陈曦,杨辽等.额尔齐斯河-斋桑湖流域近20年来土地利用/土地覆被时空演变[J].干旱区地理.2010,(02)；189-195.
[193]孙秀邦,范伟,严平等.遥感影像土地覆被分类研究进展[J].中国农学通报.2007,23(09)：607-610.
[194]冯春,陈建平.土地利用/土地覆盖研究中遥感图像分类精度的提高方法[J].地理与地理信息科学.2003,19(03)：26-28.
[195]陈军,陈晋,宫鹏.全球地表覆盖遥感制图的发展动向,2010.
[196]苏北：http://www.hudong.co,2011-06-13
[197]李增福江苏省南水北调受水区水文模型研究[D].南京：南京大学,2011.
[198]张廷斌.西藏谢通门县铜金矿带遥感图像蚀变信息提取及多源数据融合在成矿预测中的应用[D].成都：成都理工大学,2006.
[199]雷四华.平原河网地区水流模型及其在水资源调度中的应用[D].南京：河海大学,2007.
[200]马倩.江苏省地表水资源评价与利用研究[J].中国农村水利水电.2007,(11)：74-76.
[201]蔡永明,张科利,李双才.不同粒径间土壤质地资料的转换问题研究[J].土壤学报.2003,40(4)：511-517.
[202]门明新.基于空间数据库的土壤侵蚀和碳氮储量研究[D].北京：中国农业大学,2005.
[203]Williams J R, Sharply A N. EPIC-Erosion Productivity Impact Calculator I. Model Documentation. US Department of Agriculture Technical Bulletin. N.1990.
[204]朱琰.太湖流域实时洪水预报调度系统研究[D].南京：河海大学,2003.
[205]周奕君.基于ArcEngine的洪水风险管理信息系统及三维分析研究[D].上海：同济大学,2008.
[206]付苗苗.苏州澄湖地区晚更新世沉积记录与环境变迁[D]上海：华东师范大学,2009.
[207]太湖流域_太湖流域简介.http://www.baikedq.c,2010-05-07.
[208]马振坤.太湖流域水量水质实时监测决策支持系统模型研究及应用[D].南京：河海大学,2007.
[209]张继宗.太湖水网地区不同类型农田氮磷流失特征[D].北京中国农业科学院,2006.
[210]王腊春,许有鹏等.太湖地区河网调蓄能力分析[J].《南京大学学报》(自然科学),1999,35(6)：712-718.
[211]王新军,穆荣,张忠生.浅谈第二次全国土地调查土地利用分类.测绘与空间地理信息.2011,34(04)：13-16.
[212]岳健,张雪梅.关于我国土地利用分类问题的讨论[J].干旱区地理.2003,26(01)：78-88.
[213]张静,郭玉芳.地理国情监测中地表覆盖分类体系研究[J].测绘标准化.2012,28(3)：8-10.
[214]周炳中,陈浮,包浩生等.长江三角洲土地利用分类研究[J].资源科学.2002,24(02)：88-92.
[215]林爱文,黄仁涛,佐藤洋平.对我国新的土地分类体系问题的探讨[J].国土资源科技管理.2002,19(3)：7-10.
[216]李树国,马仁会.对我国土地利用分类体系的探讨[J].中国土地科.2000,14(01)：39-40.
[217]许有鹏等.长江三角洲地区城市化对流域水系与水文过程的影响[M].北京：科学出版社,2012