基于多源信息分析人类活动对径流及洪水预报的影响
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摘要
水资源问题是21世纪全球资源环境的首要问题,直接关系着人类的生存和社会的发展。我国人均水资源量不足、水资源时空分布不均的两大特点,决定了供水安全与防洪安全是我国经济社会发展的重大任务和重要保证。近几十年来,随着人口增长和社会经济的发展,人类活动使水资源的赋存形式发生了深刻变化,使河川径流减少,极端洪水灾害事件增加,供水和防洪问题更加突出。这些变化给我国水资源研究领域带来了许多新问题,如人类活动影响下的径流演变规律与水资源供需平衡问题,及人类活动影响下的洪水预报与洪灾防治问题等。本文以此为切入点,以辽宁省碧流河水库流域为对象,研究气候变化与人类活动对以城市供水为主大型水库来水量的影响；以吉林省丰满水库流域为对象,研究中小水利工程对洪水预报的影响。主要研究内容与成果如下：
(1)根据人类活动对径流及洪水的影响特点,将人类活动影响因子分为三类：是影响流域的产汇流条件,主要包括土地利用变化、水保工程、河道整治等影响；二是人类直接取用水,主要包括跨流域调水及灌区等引水工程、地下水开采等；三是影响流域河道的汇流过程,主要包括水库塘坝等蓄水工程的影响。针对上述人类活动影响因子,分析了人类活动对碧流河水库流域和丰满水库流域的径流及洪水的影响特点。
(2)采用Kendall秩次相关法、Spearman秩次相关法及线性回归检验法分析两个流域的水文气象要素变化趋势,定性分析引起流域径流变化的原因。在此基础上,根据碧流河水库流域降水、气温的变化,采用总量控制、随机分配的方法对降水序列进行还原计算,该方法通过降水序列的变化趋势计算历年需还原的降水总量,再以代表站丰、平、枯3个典型年各月平均降水天数为条件,将还原降水随机分配到每个月内；采用总量控制、比例放大的方法还原气温序列,该方法通过还原前、后的气温计算还原系数,以此系数对原系列进行放大计算还原气温序列。还原后的降水、气温序列剔除了趋势性特点,仅具有周期性特点。
(3)利用碧流河流域的DEM、土壤、土地利用及气象水文等数据建立了碧流河水库流域的SWAT模型。采用以水量平衡为控制条件的多站点多变量的SWAT模型率定方法,在总量控制与年内分配相结合的优化准则下,利用各分站控制流域的属性,从上游到下游逐级确定模型参数,使碧流河水库流域的SWAT模型能反映流域水循环过程。
(4)传统GLUE方法采用纳西效率系数Ens作为单一似然判据,常会产生较大的水量模拟误差,影响模型参数的不确定性分析结果。为此本文提出了由纳西效率系数Ens、相对误差Re及相关系数R2三个指标组成多准则似然判据的改进GLUE方法,并采用多目标模糊优选模型确定多准则GLUE方法的后验似然函数值,进而建立评价SWAT模型参数的不确定性分析方法。经验证,对于90%置信区间,改进的GLUE方法获得的区间宽度比传统GLUE方法更窄,SWAT模型的不确定性更小。通过随机扰动分析了降水数据不确定性对模拟结果的影响,发现降水数据的不确定性较小,与参数不确定性分析结论一致。
(5)结合气象要素还原计算及SWAT模型情景模拟,提出了气候变化及人类活动对径流影响的定量成因分析法。该方法首先根据GDP及人口变化,确定人类活动影响变点,通过变点前后径流序列及由SWAT模型模拟出的对应还原气象要素序列的还原径流序列,计算出气候变化与人类活动对径流变化的贡献率。在碧流河水库流域的应用表明,对于1981～2005年,气候(降水、气温)变化和人类活动对碧流河水库来水量变化的影响比例分别为39%与61%.针对碧流河水库流域1980s情景及2000s情景的SWAT模型,采用情景模拟法,模拟出不同时段对应不同土地利用及上游是否修建中小水库共3种情景的径流量。对比分析各情景模拟结果,发现碧流河水库来水量减少的主要原因是直接取用水及中小水库的拦蓄,土地利用变化对来水量的影响较小。
(6)将Landsat TM/ETM+遥感数据与传统气象水文数据结合,提出基于遥感数据的小水库拦洪计算方法。该方法根据遥感数据提取的水面信息与有资料小水库的实测库容信息,以子流域为基本计算单元,建立不同坡度的各类子流域的小水库塘坝面积库容关系；以包含洪水时段的两景遥感数据为基础,通过分析两景遥感数据的水面面积及对应时段内降水、蒸发的变化,计算出小水库塘坝的逐日水面面积变化,并将其转化为库容的变化,从而计算出小水库塘坝的拦洪量,此拦洪量可用于校正原洪水预报方案。在丰满Ⅱ区流域的应用表明,全流域水利工程对20060826洪水的拦洪量为4389.6万m3,校正后的洪量相对误差由校正前的31.8%降低到10.1%.
(7)提出了考虑单景遥感数据的小水库塘坝蓄泄规律分析方法,并将其应用于丰满Ⅱ区流域的7场洪水。该方法首先利用遥感数据获得小水库塘坝的初始蓄水状态,再选用小水库塘坝初始蓄水状态、洪水所处汛期阶段及降水量3个因子,分析不同因子下的小水库塘坝拦洪规律,分析结果可用于洪水实时预报校正。
最后对全文做了总结,并对有待于进一步研究的问题进行了展望。
Water resources problem, which has a close relationship to human survival and society development, is the most important issue of resource and environment of the world in the 21st century. The safety of water supply and flood control is the graveness task and important guarantee, which is decided by the basic characteristics of the water resources problem in our country:deficiency of water resources quantity per capita and unbalanced spatial-temporal distributing. In the last few decades, along with the population explosion and development of economy and society, the profound variation of water resources mechanism can be found because of human activities. Decreasing the stream flow, increasing the flood frequency, the problem of water supply and flood control will be more stand out. Many new problem of water resources were brought by these variations, such as, runoff change and the balance between water supply and water demand, flood forecast and control under the human-natural driving model. According to these problems, this paper choose Biliu river reservoir basin as study case, analyze the impact of climate change and human activities on large-size reservoir's runoff which assignment is provide water to cities; choose Fengman river reservoir basin as study case, analyze the impact of middle- and small-size reservoirs on flood forecasting. The study content and result are as follows:
(1) Impact factors of human activities are divided into three classes according to the impact of human activities on runoff and flood. The first class of factor is the impact on condition of runoff yield and concentration, such as land use change, runoff yield and concentration, river regulation, and so on. The second class is directly water use, which are mainly contain water diversion project(such as inter-basin water transfer and irrigation district), groundwater exploitation, and so on; The third class is the impact on runoff process, such as the impact of sluice projects like reservoirs and ponds. Analyze the impact characteristic of human activities on Biliu river reservoir basin and Fengman river reservoir basin, aiming at the three classes of factors above.
(2) Qualitative analyze the factors of runoff change, by analyzing the variation trend of hydrometeorological data in study area used Kendall rank correlation method, Spearman rank correlation method and linear regression test. On this basis, according to the variation of precipitation and temperature, the method of total amount control and random distribution is used to calculate the reduced precipitation series. This method, first calculate the total amount of reduced precipitation by its variation trend, and then calculate the average precipitation days of each month of representative station in three typical years(wet, normal and dry), finally, random distribute the reduced precipitation to each month according to the calculated precipitation days of each month. The method of total amount control and proportional amplifying is used to calculate the reduced temperature series. This reduced temperature series can be calculated by original temperature series multiplied by reduction coefficient, which is calculated by comparison the temperature variation between before and after reduction. Only periodicity characteristic can be found in the reduced precipitation and temperature series, the trend characteristic is eliminated.
(3) The SWAT model of Biliu river reservoir basin is established used DEM, soil, land use and hydrometeorological data. In this study, the author adopted a multi-site and multi-variable approach based on the water balance control to calibration of SWAT model. Under the optimization criterion of total amount control and annual distribution, according to the attribute of each hydrologic station, calibrate the parameter from upstream to downstream successively. The calibrated SWAT model can reflect the water cycle process in Biliu river reservoir basin.
(4) The GLUE method use Nash-Sutcliffe coefficient (Ens) as single likelihood criterion, which may lead large simulation error, and then affect the uncertainty analyze. In this study, the author adopted a multi likelihood criterion, which contain three criterions (Nash-Sutcliffe coefficient (Ens), relative error (Re) and determination coefficient (R2)), to improve the GLUE method. And the posterior likelihood function of the improved GLUE method is calculated by multi-objective fuzzy optimization model. Then, the uncertainty analyze method of SWAT model is established. The application shows that, for 90% confidence interval, the width of an interval for improved GLUE method is more narrow than unimproved method, which indicate the smaller uncertainty of SWAT model. The uncertainty of precipitation is found relative less by the method of precipitation randomization change, which got the same conclusion of parameter uncertainty analyze.
(5) The method of genesis analysis is adopted to calculate the impact of climate change and human activities on runoff, through the hydrometeorological data reduction method and SWAT model scenario simulation. Firstly, the author find the change-point of human activities by analyze the GDP and population change. The contribution rate of climate change and human activities are calculated by analyze the runoff series pre-and post the change-point and the reduction runoff series simulated by SWAT model. Applying this method to Biliu river reservoir basin, the result shows that, for 1981-2005, the impact of climate (precipitation and temperature) change and human activities on runoff are take the percentage of 39% and 61% respectively. Aiming at scenario 1980s and scenario 2000s of SWAT model in Biliu river reservoir basin, scenario simulation method is used to simulate the runoff of different scenarios which contains different land use and weather consider mid-and small-size reservoirs. It is easy to found that, the main reason of human activities induced runoff decrease is directly water use and detention of the reservoir in up-stream, the impact of land use change is relative less.
(6) Combining remote sensing data (Landsat TM/ETM+) and traditional hydrometeorological data, a method for determining the flood detention quantity of ponds and small reservoirs based on remote sensing data was proposed. This method choose sub-watershed as basic calculation unit, and according to the water surface area extracted by remote sensing data and the measured volume of small reservoirs which has measured data, capacity-area relationship of ponds and small reservoirs is established in different category of sub-watershed divided by average slope. Based on the two scenes remote sensing data that contains the flood period, the water surface area change is calculated by analyze the water surface area of two scenes remote sensing data and the variation of precipitation and potential evaporation in corresponding time period. The flood detention quantities can be calculate by convert the water surface variation to volume variation, through the capacity-area relationship. This value can be used to adjust the primary flood forecasting model. The application in Fengman subarea II basin shows that, the flood detention quantity of the entire basin is 4389.6×104m3. Using this value to adjust the primary flood forecasting model, the relative error decreased from 31.8% to 10.1%.
(7) The analyze method of detention and discharge mechanism for ponds and small reservoirs based on single scene remote sensing data is proposed, and applied in 7 floods of Fengman subareaⅡbasin. This method, Firstly, the initial volume of ponds and small reservoirs are calculated in the use of remote sensing data, and then choose the initial volume, phase of flood season and precipitation as three factors, analyze the flood detention mechanism in the different condition. The result can be used for real-time flood forecasting adjustment.
Finally, a summary is given and some problems to be further studied are discussed.
(1)根据人类活动对径流及洪水的影响特点,将人类活动影响因子分为三类：是影响流域的产汇流条件,主要包括土地利用变化、水保工程、河道整治等影响；二是人类直接取用水,主要包括跨流域调水及灌区等引水工程、地下水开采等；三是影响流域河道的汇流过程,主要包括水库塘坝等蓄水工程的影响。针对上述人类活动影响因子,分析了人类活动对碧流河水库流域和丰满水库流域的径流及洪水的影响特点。
(2)采用Kendall秩次相关法、Spearman秩次相关法及线性回归检验法分析两个流域的水文气象要素变化趋势,定性分析引起流域径流变化的原因。在此基础上,根据碧流河水库流域降水、气温的变化,采用总量控制、随机分配的方法对降水序列进行还原计算,该方法通过降水序列的变化趋势计算历年需还原的降水总量,再以代表站丰、平、枯3个典型年各月平均降水天数为条件,将还原降水随机分配到每个月内；采用总量控制、比例放大的方法还原气温序列,该方法通过还原前、后的气温计算还原系数,以此系数对原系列进行放大计算还原气温序列。还原后的降水、气温序列剔除了趋势性特点,仅具有周期性特点。
(3)利用碧流河流域的DEM、土壤、土地利用及气象水文等数据建立了碧流河水库流域的SWAT模型。采用以水量平衡为控制条件的多站点多变量的SWAT模型率定方法,在总量控制与年内分配相结合的优化准则下,利用各分站控制流域的属性,从上游到下游逐级确定模型参数,使碧流河水库流域的SWAT模型能反映流域水循环过程。
(4)传统GLUE方法采用纳西效率系数Ens作为单一似然判据,常会产生较大的水量模拟误差,影响模型参数的不确定性分析结果。为此本文提出了由纳西效率系数Ens、相对误差Re及相关系数R2三个指标组成多准则似然判据的改进GLUE方法,并采用多目标模糊优选模型确定多准则GLUE方法的后验似然函数值,进而建立评价SWAT模型参数的不确定性分析方法。经验证,对于90%置信区间,改进的GLUE方法获得的区间宽度比传统GLUE方法更窄,SWAT模型的不确定性更小。通过随机扰动分析了降水数据不确定性对模拟结果的影响,发现降水数据的不确定性较小,与参数不确定性分析结论一致。
(5)结合气象要素还原计算及SWAT模型情景模拟,提出了气候变化及人类活动对径流影响的定量成因分析法。该方法首先根据GDP及人口变化,确定人类活动影响变点,通过变点前后径流序列及由SWAT模型模拟出的对应还原气象要素序列的还原径流序列,计算出气候变化与人类活动对径流变化的贡献率。在碧流河水库流域的应用表明,对于1981～2005年,气候(降水、气温)变化和人类活动对碧流河水库来水量变化的影响比例分别为39%与61%.针对碧流河水库流域1980s情景及2000s情景的SWAT模型,采用情景模拟法,模拟出不同时段对应不同土地利用及上游是否修建中小水库共3种情景的径流量。对比分析各情景模拟结果,发现碧流河水库来水量减少的主要原因是直接取用水及中小水库的拦蓄,土地利用变化对来水量的影响较小。
(6)将Landsat TM/ETM+遥感数据与传统气象水文数据结合,提出基于遥感数据的小水库拦洪计算方法。该方法根据遥感数据提取的水面信息与有资料小水库的实测库容信息,以子流域为基本计算单元,建立不同坡度的各类子流域的小水库塘坝面积库容关系；以包含洪水时段的两景遥感数据为基础,通过分析两景遥感数据的水面面积及对应时段内降水、蒸发的变化,计算出小水库塘坝的逐日水面面积变化,并将其转化为库容的变化,从而计算出小水库塘坝的拦洪量,此拦洪量可用于校正原洪水预报方案。在丰满Ⅱ区流域的应用表明,全流域水利工程对20060826洪水的拦洪量为4389.6万m3,校正后的洪量相对误差由校正前的31.8%降低到10.1%.
(7)提出了考虑单景遥感数据的小水库塘坝蓄泄规律分析方法,并将其应用于丰满Ⅱ区流域的7场洪水。该方法首先利用遥感数据获得小水库塘坝的初始蓄水状态,再选用小水库塘坝初始蓄水状态、洪水所处汛期阶段及降水量3个因子,分析不同因子下的小水库塘坝拦洪规律,分析结果可用于洪水实时预报校正。
最后对全文做了总结,并对有待于进一步研究的问题进行了展望。
Water resources problem, which has a close relationship to human survival and society development, is the most important issue of resource and environment of the world in the 21st century. The safety of water supply and flood control is the graveness task and important guarantee, which is decided by the basic characteristics of the water resources problem in our country:deficiency of water resources quantity per capita and unbalanced spatial-temporal distributing. In the last few decades, along with the population explosion and development of economy and society, the profound variation of water resources mechanism can be found because of human activities. Decreasing the stream flow, increasing the flood frequency, the problem of water supply and flood control will be more stand out. Many new problem of water resources were brought by these variations, such as, runoff change and the balance between water supply and water demand, flood forecast and control under the human-natural driving model. According to these problems, this paper choose Biliu river reservoir basin as study case, analyze the impact of climate change and human activities on large-size reservoir's runoff which assignment is provide water to cities; choose Fengman river reservoir basin as study case, analyze the impact of middle- and small-size reservoirs on flood forecasting. The study content and result are as follows:
(1) Impact factors of human activities are divided into three classes according to the impact of human activities on runoff and flood. The first class of factor is the impact on condition of runoff yield and concentration, such as land use change, runoff yield and concentration, river regulation, and so on. The second class is directly water use, which are mainly contain water diversion project(such as inter-basin water transfer and irrigation district), groundwater exploitation, and so on; The third class is the impact on runoff process, such as the impact of sluice projects like reservoirs and ponds. Analyze the impact characteristic of human activities on Biliu river reservoir basin and Fengman river reservoir basin, aiming at the three classes of factors above.
(2) Qualitative analyze the factors of runoff change, by analyzing the variation trend of hydrometeorological data in study area used Kendall rank correlation method, Spearman rank correlation method and linear regression test. On this basis, according to the variation of precipitation and temperature, the method of total amount control and random distribution is used to calculate the reduced precipitation series. This method, first calculate the total amount of reduced precipitation by its variation trend, and then calculate the average precipitation days of each month of representative station in three typical years(wet, normal and dry), finally, random distribute the reduced precipitation to each month according to the calculated precipitation days of each month. The method of total amount control and proportional amplifying is used to calculate the reduced temperature series. This reduced temperature series can be calculated by original temperature series multiplied by reduction coefficient, which is calculated by comparison the temperature variation between before and after reduction. Only periodicity characteristic can be found in the reduced precipitation and temperature series, the trend characteristic is eliminated.
(3) The SWAT model of Biliu river reservoir basin is established used DEM, soil, land use and hydrometeorological data. In this study, the author adopted a multi-site and multi-variable approach based on the water balance control to calibration of SWAT model. Under the optimization criterion of total amount control and annual distribution, according to the attribute of each hydrologic station, calibrate the parameter from upstream to downstream successively. The calibrated SWAT model can reflect the water cycle process in Biliu river reservoir basin.
(4) The GLUE method use Nash-Sutcliffe coefficient (Ens) as single likelihood criterion, which may lead large simulation error, and then affect the uncertainty analyze. In this study, the author adopted a multi likelihood criterion, which contain three criterions (Nash-Sutcliffe coefficient (Ens), relative error (Re) and determination coefficient (R2)), to improve the GLUE method. And the posterior likelihood function of the improved GLUE method is calculated by multi-objective fuzzy optimization model. Then, the uncertainty analyze method of SWAT model is established. The application shows that, for 90% confidence interval, the width of an interval for improved GLUE method is more narrow than unimproved method, which indicate the smaller uncertainty of SWAT model. The uncertainty of precipitation is found relative less by the method of precipitation randomization change, which got the same conclusion of parameter uncertainty analyze.
(5) The method of genesis analysis is adopted to calculate the impact of climate change and human activities on runoff, through the hydrometeorological data reduction method and SWAT model scenario simulation. Firstly, the author find the change-point of human activities by analyze the GDP and population change. The contribution rate of climate change and human activities are calculated by analyze the runoff series pre-and post the change-point and the reduction runoff series simulated by SWAT model. Applying this method to Biliu river reservoir basin, the result shows that, for 1981-2005, the impact of climate (precipitation and temperature) change and human activities on runoff are take the percentage of 39% and 61% respectively. Aiming at scenario 1980s and scenario 2000s of SWAT model in Biliu river reservoir basin, scenario simulation method is used to simulate the runoff of different scenarios which contains different land use and weather consider mid-and small-size reservoirs. It is easy to found that, the main reason of human activities induced runoff decrease is directly water use and detention of the reservoir in up-stream, the impact of land use change is relative less.
(6) Combining remote sensing data (Landsat TM/ETM+) and traditional hydrometeorological data, a method for determining the flood detention quantity of ponds and small reservoirs based on remote sensing data was proposed. This method choose sub-watershed as basic calculation unit, and according to the water surface area extracted by remote sensing data and the measured volume of small reservoirs which has measured data, capacity-area relationship of ponds and small reservoirs is established in different category of sub-watershed divided by average slope. Based on the two scenes remote sensing data that contains the flood period, the water surface area change is calculated by analyze the water surface area of two scenes remote sensing data and the variation of precipitation and potential evaporation in corresponding time period. The flood detention quantities can be calculate by convert the water surface variation to volume variation, through the capacity-area relationship. This value can be used to adjust the primary flood forecasting model. The application in Fengman subarea II basin shows that, the flood detention quantity of the entire basin is 4389.6×104m3. Using this value to adjust the primary flood forecasting model, the relative error decreased from 31.8% to 10.1%.
(7) The analyze method of detention and discharge mechanism for ponds and small reservoirs based on single scene remote sensing data is proposed, and applied in 7 floods of Fengman subareaⅡbasin. This method, Firstly, the initial volume of ponds and small reservoirs are calculated in the use of remote sensing data, and then choose the initial volume, phase of flood season and precipitation as three factors, analyze the flood detention mechanism in the different condition. The result can be used for real-time flood forecasting adjustment.
Finally, a summary is given and some problems to be further studied are discussed.
引文
[1]刘昌明,陈志恺.中国水资源现状评价和供需发展趋势分析[M].北京：中国水利水电出版社.2011.
[2]王浩,贾仰文,王建华,等.人类活动影响下的黄河流域水资源演化规律初探[J].自然资源学报,2005,20(2)：157-162.
[3]任立良,张炜,李春红,等.中国北方地区人类活动对地表水资源的影响研究[J].河海大学学报,2001,29(4)：13-18.
[4]刘沛林.长江流域历史洪水的周期地理学研究[J].地球科学进展,2000,15(5)：503-508.
[5]王浩,雷晓辉,秦大庸,等.基于人类活动的流域产流模型构建[J].资源科学,2003,25(6)：14-18.
[6]李向阳.水文模型参数优选及不确定性分析方法研究[D].大连：大连理工大学,2005.
[7]张学真,刘燕.灞河出山径流序列变化的小波分析[J].水资源保护,2006,22(3)：11-15.
[8]李艳,陈晓宏,王兆礼.北江流域径流量分布规律及其变异性分析[J].水资源与水工程学报,2006,17(4)：14-17.
[9]栾兆擎,胡金明,邓伟.人类活动对挠力河流域径流情势的影响[J].资源科学,2007,29(2)：46-51.
[10]李林,王振宇,秦宁生,等.长江上游径流量变化及其与影响因子关系分析[J].自然资源学报,2004,19(6)：694-700.
[11]曹建廷,秦大河,罗勇,等.长江源区1956-2000年径流量变化分析[J].水科学进展,2007,18(1)：29-33.
[12]黄强,蒋晓辉,刘俊萍,等.二元模式下黄河年径流变化规律研究[J].自然科学进展,2002,12(8)：874-877.
[13]王玉明,张学成,王玲,等.黄河流域20世纪90年代天然径流量变化分析[J].人民黄河,2002,24(3)：9-11.
[14]贺国庆,李湘姣,刘国纬,等.人类活动对广东省水循环的影响分析[J].水文,2008,28(1)：70-72.
[15]许炯心,孙季.嘉陵江流域年径流量的变化及其原因[J].山地学报,2007,25(2)：153-159.
[16]高龙华.径流演变的人类驱动力模型[J].水利学报,2006,37(9)：1129-1133.
[17]许继军,杨大文,刘志雨.基于分布式水文模型的长江上游水资源时空变异性分析[J].水文,2007,27(3)：10-15.
[18]夏军.灰色系统水文学——理论、方法及应用[M].武汉：华中理工大学出版社.2000.
[19]欧春平.流域水资源系统不确定性分析及其建模研究——以海河流域为例[D].北京：中国科学院地理科学与资源研究所.2007.
[20]张继国,刘新仁.降水时空分布不均匀性的信息熵分析——(Ⅰ)基本概念与数据分析[J].水科学进展,2000,11(2)：133-137.
[21]张继国,刘新仁.降水时空分布不均匀性的信息熵分析——(Ⅱ)模型评价与应用[J].水科学进展,2000,11(2)：133-137.
[22]佟春生,黄强,刘涵.基于复杂性理论的径流时间序列动力学特征分析[J].系统工程理论与实践,2004,9：102-107.
[23]Lindensehmidt K.E., Fleischbein K., Baborowski. Structural uncertainty in a river water quality modeling system [J]. Ecological Modelling,2007,204(3-4):289-300.
[24]Beven K., Binley A. Future of distributed models:Model calibration and uncertainty prediction [J]. Hydrological Processes,1992,6(3):279-298.
[25]李胜,梁忠民.GLUE方法分析新安江模型参数不确定性的应用研究[J].东北水利水电,2006,24(259)：31-33.
[26]舒畅,刘苏峡,莫兴国,等.新安江模型参数的不确定性分析[J].地理研究,2008,27(2)：343-352.
[27]黄国如,解河海.基于GLUE方法的流域水文模型的不确定性分析[J].华南理工大学学报(自然科学版),2007,35(3)：137-149.
[28]Misgana K. Muleta, John W. Nicklow. Sensitivity and uncertainty analysis coupled with automatic calibration for a distributed watershed model [J]. Journal of Hydrology.2005,306:127-145.
[29]徐宗学,李占玲.黑河源区径流模拟与模型不确定性分析[G]//中国水利学会水资源专业委员会2009学术年会论文集.大连：大连理工大学出版社,2009：148-155.
[30]Blasone R S, Vrugt J A. Generalized likelihood uncertainty estimation (GLUE) using adaptive Markov Chain Monte Carlo sampling [J]. Advances in Water Resources,2008,31:630-648.
[31]卫晓婧,熊立华.改进的GLUE方法在水文模型不确定性研究中的应用[J].水利水电快报,2008,29(6)：23-25.
[32]刘艳丽.径流预报模型不确定性研究及水库防洪风险分析[D].大连：大连理工大学,2008.
[33]刘艳丽,梁国华,周惠成.水文模型不确定性分析的多准则似然判据GLUE方法[J].四川大学学报(工程科学版),2009,41(4)：89-96.
[34]林凯荣,陈晓宏,江涛.基于Copula_Glue的水文模型参数的不确定性[J].中山大学学报(自然科学版),2009,48(3)：109-115.
[35]邓义祥,郑丙辉,苏一兵,等.似然度函数对GLUE方法的影响[J].环境科学研究,2008,21(2)：44-48.
[36]Bryan A. Tolson, Christine A. Shoemaker. Efficient prediction uncertainty approximation in the calibration of environmental simulation models [J]. Water Resources Reseaech,2008,44(1-19): 69-85.
[37]唐丽霞.黄土高原清水河流域土地利用／气候变异对径流泥沙的影响[D].北京：北京林业大学,2009.
[38]Thiemann M, Trosset M, Gupta H, et al. Bayesian recursive parameter estimation for hydrologic models[J]. Water Resources Research,2001,37:2521-2535.
[39]金树权.水库水源地水质模拟预测与不确定性分析[D].杭州：浙江大学,2008.
[40]Kuezera G, Parent E. Monte Carlo assessment of parameter uncertainty in conceptual catchment models:the Metropolis algorithm [J]. Journal of Hydrology,1998,211(1-4):69-85.
[41]Bryan A.Tolson, Christine A. Shoemaker. Dynamically dimensioned search algorithm for computationally efficient watershed model calibration [J]. Water Resources Research,2007,43: 1-16.
[42]熊立华,卫晓婧,万民.水文模型两种不确定性研究方法的比较[J].武汉大学学报(工学版),2009,42(2)：137-142.
[43]Jing Yang, Peter Reichert, K.C. Abbaspour, et al. Comparing uncertainty analysis techniques for a SWAT application to the Chaohe Basin in China[J]. Journal of Hydrology,2008,358:1-22.
[44]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.
[45]中野秀章(李云森译).森林水文学[M].北京：中国林业出版社,1983.
[46]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.
[47]黄明斌,康绍忠,李玉山.黄土高原沟壑区森林和草地小流域水文行为的比较研究[J].自然资源学报,1999,14(3)：226-231.
[48]穆兴民,王文龙,徐学选.黄土高原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.
[49]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.
[50]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.
[51]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.
[52]张蕾娜,李秀彬,王兆锋,等.一种可用于表征土地利用变化水文效应的水文模型探讨——SWAT模型在云州水库流域的应用研究[J].水文,2004,24(3)：4-8.
[53]谢媛媛.黄土高原典型流域土地利用/森林植被变化的水文生态响应研究[D].北京：北京林业大学.2006.
[54]池宸星,郝振纯,王玲,等.黄土区人类活动影响下的产汇流模拟研究[J].地理科学进展,2005,24(3)：101-108.
[55]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,2003,58(1)：53-62.
[56]高俊峰,闻余华.太湖流域土地利用变化对流域产水量的影响[J].地理学报,2002,57(2)：194-200.
[57]Bouraoui F, G Vachaud, T Chen. Prediction of the effect of climatic changes and land use management on water resources [J]. Physics and Chemistry of the Earth,1998,23(4):379-384.
[58]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 (Part B:Hydrology, Oceans & Atmosphere), 2001, (26):577-582.
[59]Wegehenkel Martin. Estimating of the impact of land use changes using the conceptual hydrological model THESEUS—a case study [J]. Physics and Chemistry of the Earth,2002, (27):631-640.
[60]刘登伟,封志明,延军平.秦岭南北地区人口增长对水资源影响的比较研究[J].干旱区资源与环境,2005,19(7)：147-151.
[61]栾兆擎,邓伟.三江平原人类活动的水文效应[J].水土保持通报,2003,23(5)：11-14.
[62]许炯心.人类活动对黄河河川径流的影响[J].水科学进展,2007,18(5)：648-655.
[63]周红,秦嘉轮,卫江益.人类活动对塔里木河年径流影响量的估算[J].干旱区地理,2002,25(1)：70-74.
[64]刘红玉,李兆富.三江平原典型湿地流域水文情势变化过程及其影响因素分析[J].自然资源学报,2005,20(4)：493-501.
[65]高迎春,姚治君,刘宝勤,等.密云水库入库径流变化趋势及动因分析[J].地理科学进展,2002,21(6)：546-553.
[66]贾仰文,王浩.“黄河流域水资源演变规律与二元演化模型”研究成果简介[J].水利水电技术,2006,37(2)：45-52.
[67]王浩,王成明,王建华,等.二元年径流演化模式及其在无定河流域的应用[J].中国科学(E辑),2004,34：42-48.
[68]贾仰文,王浩,严登华.黑河流域水循环系统的分布式模拟(Ⅰ)—模型开发与验证[J].水利学报,2006,37(5)：534-542.
[69]程晓陶,吴玉成,王艳艳,等.洪水管理新理念与防洪安全保障体系的研究[M].北京：中国水利水电出版社,2004.
[70]Pinter N, Ickes BS, Wlosinski JH, et al. Trends in flood stages:Contrasting results from the Mississippi and Rhine River systems [J]. Journal of Hydrology,2006,331:554-566.
[71]Brath A, Montanari A, Moretti G. Assessing the effect on flood frequency of land use change via hydrological simulation [J]. Journal of Hydrology,2006,324:141-153.
[72]许有鹏,于瑞宏,马宗伟.长江中下游洪水灾害成因及洪水特征模拟分析[J].长江流域资源与环境,2005,14(5)：638-643.
[73]张帜,刘明.冰湖溃坝洪水对满拉水库影响分析及BREACH模型的应用[J].水道港口,1994,2：10-15.
[74]宝力高,包玉海.小流域雨洪估算的多元回归模型[J].内蒙古科技与经济1999,6：42-43.
[75]许珂艳.黄河下游洪峰水位预报多元回归方法研究[D].南京：河海大学,2006.
[76]郭生练,王金星,彭辉,等.考虑人类活动影响的丰满水库洪水预报方案[J].水电能源科学,2000,18(02)：14-17.
[77]尹雄锐,张翔,夏军,等.考虑土地覆被的神经网络径流模拟研究[J].水电能源科学,2004,22(2)：13-15.
[78]沈清德,全鸿烈.水库上游水利工程对中小型水库洪水预报的影响[J].东北水利水电,2002,21(3)：43-44.
[79]程春田,王本德.考虑人类活动影响的流域水文模型参数的确定[J].大连理工大学学报,1995,35(3)：400-404.
[80]杨涛,张鹰,陈界仁,等.基于数字平台的黄河多沙粗沙区分布式水文模型研究—以黄河岔巴沟流域为例[J].水利学报,2005,36(4)：456-459.
[81]吴险峰,刘昌明,郝芳华,等.黄河小花区间暴雨径流过程分布式模拟[J].水科学进展,2004,15(4)：511-516.
[82]黄粤,陈曦,钱静,等.塔里木河干流生态闸洪水漫溢过程分布式水文模拟——以灿木里克生态闸为例[J].自然资源学报,2007,22(1)：37-43.
[83]董小涛,李致家.HEC模型在洪水预报中的运用[J].东北水利水电,2004,22(11)：43-44.
[84]Todini Eciarapica L. The TOPKAPI Model[C]//Singh VP. eta Mathematical models of large watershed Hydrology. Littleton Colorado:Water Resourses Pub lacations,2001.
[85]李兰,朱芮芮,钟名军.基于GIS的LL-Ⅱ分布式降水径流模型的应用[J].水电能源科学,2004,22(1)： 8-11.
[86]于澎涛,徐德应,王彦辉.应用官司河分布式水文模型模拟流域降雨-径流过程[J].林业科学,2003,39(1)：1-9.
[87]梁钟元,贾仰文,李开杰,等.分布式水文模型在洪水预报中的应用研究综述[J].人民黄河,2007,29(2)：29-32.
[88]魏锋,曾飞.黄河小花间分布式模型洪水预报系统集成研究[J].人民长江,2010,41(24)：25-31.
[89]许继军.分布式水文模型在长江流域的应用研究[D].北京：清华大学,2007.
[90]颜亦奇.受人类活动影响的水库设计洪水调度研究[D].南京：河海大学,2004.
[91]大连市河道管理处.大连市河流特征值手册[M].2005.
[92]张树文,张养贞,李颖,等.东北地区土地利用/覆被时空特征分析[M].北京：科学出版社,2006：42-45.
[93]李伟.人类活动对洪水预报影响分析及防洪调度研究[D].大连：大连理工大学,2009.
[94]李志栋,朱庆.数字高程模型[M].武汉：武汉测绘大学出版社,2000.
[95]孔凡哲.基于数字化平台的分布式流域水文模型和流域汇流研究[D].南京：河海大学,2003.
[96]Moore I D, O'Loughlin E M, Burch G J. A contour-based topographic model for hydrological and ecological applications [J]. Earth Surface Processes and Landforms,1988,13:305-620.
[97]解河海Topmodel的应用及参数不确定性研究[D].南京：河海大学,2006.
[98]叶爱中,夏军,王纲胜,等.基于数字高程模型的河网提取及子流域生成[J].水利学报,2006,36(5)：531-537.
[99]吴信才.地理信息系统原理与方法[M].北京：电子工业出版社,2002.
[100]梅安新,秦其明.遥感导论[M].北京：高等教育出版社,2001.
[101]戴昌达,雷莉萍.TM图像的光谱信息特征与最佳波段组合[J].环境遥感,1989,4(4)：282-292.
[102]Liu J G. Evaluation of Landsat-7 ETM+ panchromatic band for image fusion with multispectral bands [J]. Natural Resources Research,2000,9(4):269-276.
[103]刘纪远,张增祥,庄大方,等.20世纪90年代中国土地利用变化时空特征及其成因分析[J].地理研究,2003,22(1)：1-12.
[104]刘纪远,庄大方,张增祥,等.中国土地利用时空数据平台建设及其支持下的相关研究[J].地球信息科学,2002,3：3-8.
[105]田光进,庄大方,刘明亮.近10年中国耕地资源时空变化特征[J].地理科学进展,2003,18(1)：30-36.
[106]全斌.土地利用与土地覆被变化学导论[M].北京：中国环境科学出版社,2010.
[107]王果.土壤学[M].北京：高等教育出版社,2009.
[108]史学正,于东升,潘贤章,等.国家科技攻关计划土壤数据库专题研究分析报告[R].南京：中国科学院南京土壤研究所,2003.
[109]史学正,于东升.“数字土壤”——21世纪土壤学面临的机遇与挑战[J].土壤通报,2000,31(3)：104-106.
[110]张甘霖,龚子同,骆国保,等.国家土壤信息系统的结构、内容与应用[J].地理科学,2001,21(5)：401-406.
[111]张定祥,史学正,于东升,等.中国1：100万土壤数据库建设的基础[J].地理学报,2002,57(7s)：82-86.
[112]张定祥,潘贤章,史学正,等.中国1：100万土壤数据库建设中的几个问题[J].土壤通报,2003,34(2)：81-84.
[113]张甘霖,史学正,龚子同.中国土壤地理学发展的回顾与展望[J].土壤学报,2008,45(5)：792-801.
[114]史学正,于东升,潘贤章,等.中国1：100万土壤数据库及其应用[C].中国土壤学会第十次全国会员代表大会暨第五届海峡两岸土壤肥料学术交流研讨会论文集(面向农业与环境的土壤科学综述篇),北京：科学出版社,2004.
[115]商瑶玲,王东华,吉建培,等.国家1：50000地形数据库的数据设计与建库[J].测绘科学,2006,s1：74-76.
[116]商瑶玲,王东华,吉建培,等.全国1：25万地形数据库的建立与应用[J].测绘通报,2001,10：29-31.
[117]杨洪泉,李孝明,李成名.1：25万地形图数据挖掘初探[J].测绘通报,2002,9：44-47.
[118]曹明亮,张弛,周惠成,等.丰满上游流域人类活动影响下的降雨径流变化趋势分析[J].水文,2008,28(5)：86-89.
[119]丁晶,邓育仁.随机水文学[M].成都：成都科技大学出版社,1988.
[120]屠其璞,王俊得,丁裕国,等.气象应用概率统计学[M].北京：气象出版社,1984：222-229.
[121]施能.气象科研与预报中的多元统计分析方法[M].北京：气象出版社,2002(第二版).
[122]仕玉治.气候变化及人类活动对流域水资源的影响及实例研究[D].大连：大连理工大学,2011.
[123]贾仰文,王浩,倪广恒,等.分布式流域水文模型原理与实践[M].北京：中国水利水电出版社,2005.
[124]Neitsch S L, Arnold J G, Kiniry J R, et al. Soil and Water Assessment Tool:Theoretical Documentation, version 2005 (available at http://www.brc.tamus.edu/swat/).
[125]王中根,刘昌明,黄友波.SWAT模型的原理、结构及应用研究[J].地理科学进展,2003,22(1)：79-86.
[126]郭兵.太阳总辐射与日照时数相关关系的区域模型分析[D].西安：西安建筑科技大学,2006.
[127]辽宁省土壤肥料总站.辽宁土种志[M].沈阳：辽宁大学出版社,2009.
[128]魏怀斌,张占庞,杨金鹏.SWAT模型土壤数据库建立方法[J].水利水电技术,2007,38(6)：15-18.
[129]M D Morris. Factorial sampling plans for preliminary computational experiments [J]. Technometrics, 1991,33(2):161-174.
[130]M D MeKay, R J Beckmlan, W J Conover. A comparison of three methods for selecting values of input variables in the analysis of output from a computer code [J]. Technometrics,1979,21(2): 239-245.
[131]K Christiaens, J Feyen. Use of sensitivity and uncertainty measures in distributed hydrological modeling with an application to the MIKE SHE model [J].Water Resources Research,2002,38(9): 10-18.
[132]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)：256-261.
[133]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]J G Arnold, R S Muttiah, R Srinivasan, et al. Regional estimation of base flow and groundwater recharge in the upper Mississippi basin [J]. Journal of Hydrology,2000,227(1):21-40.
[135]J Benaman, CA Shoemaker, DA Haith. Calibration and validation of soil and water assessment tool on an agricultural watershed in upstate New York [J]. Journal of hydrologic engineering,2005,10(5): 363-374.
[136]Robert S. Ahl, Scott W. Woods, Hans R. Zuuring. Hydrologic calibration and validation of SWAT in a snow-dominated rocky mountain watershed, Montana, USA [J]. Journal of the American water resources association,2008,44(6):1411-1430.
[137]L Galvan, M Olias, RF de Villaran, et al. Application of the SWAT model to an AMD-affected river (Meca River, SW Spain). Estimation of transported pollutant load [J]. Journal of Hydrology,2009, 377 (3-4):445-454.
[138]J Schuol, KC Abbaspour, R Srinivasan, et al. Estimation of freshwater availability in the West African sub-continent using the SWAT hydrologic model [J]. Journal of Hydrology,2008,352 (1-2): 30-49.
[139]KS. Wu, CA. Johnston. Hydrologic response to climatic variability in a Great Lakes Watershed:A case study with the SWAT model [J]. Journal of Hydrology,2007,337 (1-2):187-199.
[140]V. Sridhar, A. Nayak. Implications of climate-driven variability and trends for the hydrologic assessment of the Reynolds Creek Experimental Watershed, Idaho [J]. Journal of Hydrology,2010, 385(1-4):183-202.
[141]KC Abbaspour, J Yang, I Maximov, et al. Modelling hydrology and water quality in the pre-ailpine/alpine Thur watershed using SWAT[J]. Journal of Hydrology,2007,333 (2-4):413-430.
[142]张东,张万昌,朱利,等.SWAT分布式流域水文物理模型的改进及应用研究[J].地理科学,2005,25(4)：434-440.
[143]王林,张明旭,陈兴伟.基于SWAT模型的晋江西溪流域径流模拟[J].亚热带资源与环境学报,2007,2(1)：28-33.
[144]刘吉峰,霍世青,李世杰,等.SWAT模型在青海湖布哈河流域径流变化成因分析中的应用[J].河海大学学报(自然科学版),2007,35(2)：159-163.
[145]Wenzhi Cao, William B. Bowden, Tim Dayie, et al. Multi-variable and multi-site calibration and validation of SWAT in a large mountainous catchment with high spatial variability [J]. Hydrologocal processes,2006,20(5):1057-1073.
[146]K L White, I Chaubey. Sensitivity analysis, calibration, and validations for a multisite and multivariable SWAT model [J]. Journal of the American water resources association,2005,41(5): 1077-1089.
[147]解河海,郝振.基于TOPMODEL的东江流域水文模拟[J].水科学研究,2008,2(1)：56-62.
[148]Chaplot V. Impact of DEM mesh size and soil map scale on SWAT runoff, sediment, and N03-N loads predictions [J]. Journal of Hydrology,2005,312:207-222.
[149]任希岩,张雪松,郝芳华,等.DEM分辨率对产流产沙模拟影响研究[J].水土保持研究,2004,11(1)：1-4.
[150]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(3),22-25.
[151]Hornberger G M, Spear R C. An approach to the preliminary analysis of environmental systems [J]. Journal of Environmental management,1981,12:7-18.
[152]Beven K, Freer J. Equifinality, data assimilation, and uncertainty estimation in mechanistic modeling of complex environmental systems using the GLUE methodology [J]. Journal of Hydrology,2001, 249:11-29.
[153]陈守煜.可变模糊集理论与模型及其应用[M].大连：大连理工大学出版社,2009.
[154]Xiong L H, O'Connor K M. An empirical method to improve the prediction limits of the GLUE methodology in rainfall-runoff modeling [J]. Journal of Hydrology,2008,349:115-124.
[155]卫晓婧,熊立华,万民,等.融合马尔科夫链-蒙特卡洛算法的改进通用似然不确定性估计方法在流域水文模型中的应用[J].水利学报,2008,40(4)：464-473.
[156]刘冀.径流分类组合预报方法及其研究应用[D].大连：大连理工大学,2008.
[157]辽宁省人民政府地方志办公室.辽宁年鉴[M].沈阳：辽宁年鉴编辑部.
[158]《辽宁经济统计年鉴》编辑委员会.辽宁经济统计年鉴[M].沈阳：辽宁人民出版社.
[159]中国城市经济社会年鉴理事会.中国城市经济社会年鉴[M].北京：中国城市经济社会出版社.
[160]大连市统计局.大连统计年鉴[M].北京：中国统计出版社.
[161]Anthes R A, Hsie E Y, Kuo Y H. Description of the penn state/NCAR mesoscale model version4 (MM4). Tech. Note NCAR/TN-281+STR,1987,66.
[162]Giorgi F, Bates G T. The climatological skill of a regional model complex terrain[J]. Mon.Wea.Rev., 1989,117:2325-2347.
[163]Dickinson R E, Kennedy P J, Giorgi F, et al. A regional climate model for the western United States[J]. Clim.Change,1989,15:383-422.
[164]Giorgi F, Marinucci M R, Bates G T. Development of a second-generation regional climate model (RegCM2). Part Ⅰ:Boundary-layer and radiative transfer processes [J], Mon.Wea.Rev.,1993a,121: 2794-2813.
[165]Giorgi F, Marinucci M R, Bates G T. Development of a second-generation regional climate model (RegCM2). Part Ⅱ:Convective processes and assimilation of lateral boundary conditions [J]. Mon.Wea.Rev.,1993b,121:2814-2832.
[166]Pal J S, Giorgi F, Bi X Q, et al. The ICTP RegCM3 and RegCNET. Regional climate modeling for the developing world [J]. Bull. Am. Meteorol. Soc.,2007,88(9):1395-1409.
[167]宋瑞艳.一个高分辨率区域气候模式(RegCM3)对中国未来极端降水事件变化的预估[D].北京：中国气象科学研究院,2008.
[168]周建玮,王咏青.区域气候模式RegCM3应用研究综述[J].气象科学,2007,27(6)：702-708.
[169]张可欣,孙成武RegCM3对山东夏季气候高分辨率模拟[J].气象科学,2009,29(4)：490-497.
[170]Nellie E, X Q Bi, F Giorgi.2006. RegCM Version 3.1 Users Guide. NCAR Tech Note,6-11.
[171]刘纪远,刘明亮,庄大方,等.中国近期土地利用变化的空间格局分析[J].中国科学(D辑),2002,32(12)：1031-1040.
[172]Lotta Andersson, Julie Wilk, Martin C. Todd, et al. Impact of climate change and development scenarios on flow patterns in the Okavango River [J]. Journal of Hydrology,2006,331:43-57.
[173]Bergstrom, S., Carlsson, B., Gardelin, M., et al. Rummukainen, M., Climate change impacts on runoff in Sweden-assessments by global climate models, dynamical downscaling and hydrological modeling [J]. Climate Res.2001,16 (2):101-112.
[174]秦大河.中国气候与环境演变：气候与环境变化的影响与适应、减缓对策(上下卷)[M].北京：科学出版社,2005.
[175]张利平,陈小凤,赵志鹏,等.气候变化对水文水资源影响的研究进展[J].地理科学进展,2008,27(3)：60-67.
[176]Jia Y W, Wang H, Zhou Z H, et al. Development of the WEP-L distributed hydrological model and dynamic assessment of water resources in the Yellow River basin [J]. Journal of Hydrology,2006, 331:606-629.
[177]Ren L L, Wang M R, Li C H, et al. Impacts of human activity on river runoff in the northern area of China[J]. Journal of Hydrology,2002,261:204-217.
[178]Xu J J, Yang D W, Yi Y H, et al. Spatial and temporal variation of runoff in the Yangtze River basin during the past 40 years [J]. Quaternary International,2008,186:32-42.
[179]Barlage M J, P L Richards, et al. Impacts of climate change and land use change on runoff from a Great Lakes watershed [J]. Journal of Great Lakes Research,2002,28(4):568-582.
[180]Seguis L, Cappelaere B, et al. Simulated impacts of climate change and land-clearing on runoff from a small Sahelian catchment [J].Hydrological Processes,2004,18(17):3401-3413.
[181]Monteith J L. Evaporation and environment [J]. Symposia of the Society for Experimental Biology, 1965,19:205-234.
[182]Liebe J, van de Giesen N, Andreini M. Estimation of small reservoir storage capacities in a semi-arid environment [J]. Physics and Chemistry of the Earth,2005,30(6):448-454.
[183]丁智雄.DEM与遥感相结合的水库水位面积曲线测定方法研究[J].水利水电技术,2010,41(1)：83-86.
[184]Du Y Y, Zhou C H. Automatically extracting remote sensing information for water bodies[J]. Journal of Remote Sensing,1988,2(4):264-269.
[185]曹波.基于遥感图像和DEM测定水库动库容的方法研究[D].武汉：华中科技大学,2006.
[186]吴赛.基于EOS/MODIS的水体提取模型及其在洪灾监测中的应用[D].武汉：华中科技大学,2005.
[187]李永生,武鹏飞.基于MODIS数据的艾比湖湖面变化研究[J].水资源与水工程学报,2008,19(5)：110-112.
[188]Mcfeeters S K. The use of the Normalized Difference Water Index(NDWI) in the delineation of open water features [J]. International Journal of Remote Sensing,1996,17(7):1425-1432.
[189]Gao B C. NDWI-A normalized difference water index for remote sensing of vegetation liquid water from space [J], Remote Sensing of Environment,1995,58:257-266.
[190]Ouma Y, Tateishi R. A water index for rapid mapping of shoreline changes of five East African Rift Valley lakes:An empirical analysis using Landsat TM and ETM+ data[J], International Journal of Remote Sensing,2006,27(15):3153-3181.
[191]Sawunyama T, Senzanje A, Mhizha A. Estimation of small reservoir storage capacities in Limpopo River Basin using geographical information systems (GIS) and remotely sensed surface areas Case of Mzingwane catchment [J]. Physics and Chemistry of the Earth,2006,31(15):935-943.
[192]水利部松辽水利委员会.东北地区实用洪水预报方案(上册)[M].2003.
[2]王浩,贾仰文,王建华,等.人类活动影响下的黄河流域水资源演化规律初探[J].自然资源学报,2005,20(2)：157-162.
[3]任立良,张炜,李春红,等.中国北方地区人类活动对地表水资源的影响研究[J].河海大学学报,2001,29(4)：13-18.
[4]刘沛林.长江流域历史洪水的周期地理学研究[J].地球科学进展,2000,15(5)：503-508.
[5]王浩,雷晓辉,秦大庸,等.基于人类活动的流域产流模型构建[J].资源科学,2003,25(6)：14-18.
[6]李向阳.水文模型参数优选及不确定性分析方法研究[D].大连：大连理工大学,2005.
[7]张学真,刘燕.灞河出山径流序列变化的小波分析[J].水资源保护,2006,22(3)：11-15.
[8]李艳,陈晓宏,王兆礼.北江流域径流量分布规律及其变异性分析[J].水资源与水工程学报,2006,17(4)：14-17.
[9]栾兆擎,胡金明,邓伟.人类活动对挠力河流域径流情势的影响[J].资源科学,2007,29(2)：46-51.
[10]李林,王振宇,秦宁生,等.长江上游径流量变化及其与影响因子关系分析[J].自然资源学报,2004,19(6)：694-700.
[11]曹建廷,秦大河,罗勇,等.长江源区1956-2000年径流量变化分析[J].水科学进展,2007,18(1)：29-33.
[12]黄强,蒋晓辉,刘俊萍,等.二元模式下黄河年径流变化规律研究[J].自然科学进展,2002,12(8)：874-877.
[13]王玉明,张学成,王玲,等.黄河流域20世纪90年代天然径流量变化分析[J].人民黄河,2002,24(3)：9-11.
[14]贺国庆,李湘姣,刘国纬,等.人类活动对广东省水循环的影响分析[J].水文,2008,28(1)：70-72.
[15]许炯心,孙季.嘉陵江流域年径流量的变化及其原因[J].山地学报,2007,25(2)：153-159.
[16]高龙华.径流演变的人类驱动力模型[J].水利学报,2006,37(9)：1129-1133.
[17]许继军,杨大文,刘志雨.基于分布式水文模型的长江上游水资源时空变异性分析[J].水文,2007,27(3)：10-15.
[18]夏军.灰色系统水文学——理论、方法及应用[M].武汉：华中理工大学出版社.2000.
[19]欧春平.流域水资源系统不确定性分析及其建模研究——以海河流域为例[D].北京：中国科学院地理科学与资源研究所.2007.
[20]张继国,刘新仁.降水时空分布不均匀性的信息熵分析——(Ⅰ)基本概念与数据分析[J].水科学进展,2000,11(2)：133-137.
[21]张继国,刘新仁.降水时空分布不均匀性的信息熵分析——(Ⅱ)模型评价与应用[J].水科学进展,2000,11(2)：133-137.
[22]佟春生,黄强,刘涵.基于复杂性理论的径流时间序列动力学特征分析[J].系统工程理论与实践,2004,9：102-107.
[23]Lindensehmidt K.E., Fleischbein K., Baborowski. Structural uncertainty in a river water quality modeling system [J]. Ecological Modelling,2007,204(3-4):289-300.
[24]Beven K., Binley A. Future of distributed models:Model calibration and uncertainty prediction [J]. Hydrological Processes,1992,6(3):279-298.
[25]李胜,梁忠民.GLUE方法分析新安江模型参数不确定性的应用研究[J].东北水利水电,2006,24(259)：31-33.
[26]舒畅,刘苏峡,莫兴国,等.新安江模型参数的不确定性分析[J].地理研究,2008,27(2)：343-352.
[27]黄国如,解河海.基于GLUE方法的流域水文模型的不确定性分析[J].华南理工大学学报(自然科学版),2007,35(3)：137-149.
[28]Misgana K. Muleta, John W. Nicklow. Sensitivity and uncertainty analysis coupled with automatic calibration for a distributed watershed model [J]. Journal of Hydrology.2005,306:127-145.
[29]徐宗学,李占玲.黑河源区径流模拟与模型不确定性分析[G]//中国水利学会水资源专业委员会2009学术年会论文集.大连：大连理工大学出版社,2009：148-155.
[30]Blasone R S, Vrugt J A. Generalized likelihood uncertainty estimation (GLUE) using adaptive Markov Chain Monte Carlo sampling [J]. Advances in Water Resources,2008,31:630-648.
[31]卫晓婧,熊立华.改进的GLUE方法在水文模型不确定性研究中的应用[J].水利水电快报,2008,29(6)：23-25.
[32]刘艳丽.径流预报模型不确定性研究及水库防洪风险分析[D].大连：大连理工大学,2008.
[33]刘艳丽,梁国华,周惠成.水文模型不确定性分析的多准则似然判据GLUE方法[J].四川大学学报(工程科学版),2009,41(4)：89-96.
[34]林凯荣,陈晓宏,江涛.基于Copula_Glue的水文模型参数的不确定性[J].中山大学学报(自然科学版),2009,48(3)：109-115.
[35]邓义祥,郑丙辉,苏一兵,等.似然度函数对GLUE方法的影响[J].环境科学研究,2008,21(2)：44-48.
[36]Bryan A. Tolson, Christine A. Shoemaker. Efficient prediction uncertainty approximation in the calibration of environmental simulation models [J]. Water Resources Reseaech,2008,44(1-19): 69-85.
[37]唐丽霞.黄土高原清水河流域土地利用／气候变异对径流泥沙的影响[D].北京：北京林业大学,2009.
[38]Thiemann M, Trosset M, Gupta H, et al. Bayesian recursive parameter estimation for hydrologic models[J]. Water Resources Research,2001,37:2521-2535.
[39]金树权.水库水源地水质模拟预测与不确定性分析[D].杭州：浙江大学,2008.
[40]Kuezera G, Parent E. Monte Carlo assessment of parameter uncertainty in conceptual catchment models:the Metropolis algorithm [J]. Journal of Hydrology,1998,211(1-4):69-85.
[41]Bryan A.Tolson, Christine A. Shoemaker. Dynamically dimensioned search algorithm for computationally efficient watershed model calibration [J]. Water Resources Research,2007,43: 1-16.
[42]熊立华,卫晓婧,万民.水文模型两种不确定性研究方法的比较[J].武汉大学学报(工学版),2009,42(2)：137-142.
[43]Jing Yang, Peter Reichert, K.C. Abbaspour, et al. Comparing uncertainty analysis techniques for a SWAT application to the Chaohe Basin in China[J]. Journal of Hydrology,2008,358:1-22.
[44]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.
[45]中野秀章(李云森译).森林水文学[M].北京：中国林业出版社,1983.
[46]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.
[47]黄明斌,康绍忠,李玉山.黄土高原沟壑区森林和草地小流域水文行为的比较研究[J].自然资源学报,1999,14(3)：226-231.
[48]穆兴民,王文龙,徐学选.黄土高原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.
[49]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.
[50]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.
[51]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.
[52]张蕾娜,李秀彬,王兆锋,等.一种可用于表征土地利用变化水文效应的水文模型探讨——SWAT模型在云州水库流域的应用研究[J].水文,2004,24(3)：4-8.
[53]谢媛媛.黄土高原典型流域土地利用/森林植被变化的水文生态响应研究[D].北京：北京林业大学.2006.
[54]池宸星,郝振纯,王玲,等.黄土区人类活动影响下的产汇流模拟研究[J].地理科学进展,2005,24(3)：101-108.
[55]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,2003,58(1)：53-62.
[56]高俊峰,闻余华.太湖流域土地利用变化对流域产水量的影响[J].地理学报,2002,57(2)：194-200.
[57]Bouraoui F, G Vachaud, T Chen. Prediction of the effect of climatic changes and land use management on water resources [J]. Physics and Chemistry of the Earth,1998,23(4):379-384.
[58]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 (Part B:Hydrology, Oceans & Atmosphere), 2001, (26):577-582.
[59]Wegehenkel Martin. Estimating of the impact of land use changes using the conceptual hydrological model THESEUS—a case study [J]. Physics and Chemistry of the Earth,2002, (27):631-640.
[60]刘登伟,封志明,延军平.秦岭南北地区人口增长对水资源影响的比较研究[J].干旱区资源与环境,2005,19(7)：147-151.
[61]栾兆擎,邓伟.三江平原人类活动的水文效应[J].水土保持通报,2003,23(5)：11-14.
[62]许炯心.人类活动对黄河河川径流的影响[J].水科学进展,2007,18(5)：648-655.
[63]周红,秦嘉轮,卫江益.人类活动对塔里木河年径流影响量的估算[J].干旱区地理,2002,25(1)：70-74.
[64]刘红玉,李兆富.三江平原典型湿地流域水文情势变化过程及其影响因素分析[J].自然资源学报,2005,20(4)：493-501.
[65]高迎春,姚治君,刘宝勤,等.密云水库入库径流变化趋势及动因分析[J].地理科学进展,2002,21(6)：546-553.
[66]贾仰文,王浩.“黄河流域水资源演变规律与二元演化模型”研究成果简介[J].水利水电技术,2006,37(2)：45-52.
[67]王浩,王成明,王建华,等.二元年径流演化模式及其在无定河流域的应用[J].中国科学(E辑),2004,34：42-48.
[68]贾仰文,王浩,严登华.黑河流域水循环系统的分布式模拟(Ⅰ)—模型开发与验证[J].水利学报,2006,37(5)：534-542.
[69]程晓陶,吴玉成,王艳艳,等.洪水管理新理念与防洪安全保障体系的研究[M].北京：中国水利水电出版社,2004.
[70]Pinter N, Ickes BS, Wlosinski JH, et al. Trends in flood stages:Contrasting results from the Mississippi and Rhine River systems [J]. Journal of Hydrology,2006,331:554-566.
[71]Brath A, Montanari A, Moretti G. Assessing the effect on flood frequency of land use change via hydrological simulation [J]. Journal of Hydrology,2006,324:141-153.
[72]许有鹏,于瑞宏,马宗伟.长江中下游洪水灾害成因及洪水特征模拟分析[J].长江流域资源与环境,2005,14(5)：638-643.
[73]张帜,刘明.冰湖溃坝洪水对满拉水库影响分析及BREACH模型的应用[J].水道港口,1994,2：10-15.
[74]宝力高,包玉海.小流域雨洪估算的多元回归模型[J].内蒙古科技与经济1999,6：42-43.
[75]许珂艳.黄河下游洪峰水位预报多元回归方法研究[D].南京：河海大学,2006.
[76]郭生练,王金星,彭辉,等.考虑人类活动影响的丰满水库洪水预报方案[J].水电能源科学,2000,18(02)：14-17.
[77]尹雄锐,张翔,夏军,等.考虑土地覆被的神经网络径流模拟研究[J].水电能源科学,2004,22(2)：13-15.
[78]沈清德,全鸿烈.水库上游水利工程对中小型水库洪水预报的影响[J].东北水利水电,2002,21(3)：43-44.
[79]程春田,王本德.考虑人类活动影响的流域水文模型参数的确定[J].大连理工大学学报,1995,35(3)：400-404.
[80]杨涛,张鹰,陈界仁,等.基于数字平台的黄河多沙粗沙区分布式水文模型研究—以黄河岔巴沟流域为例[J].水利学报,2005,36(4)：456-459.
[81]吴险峰,刘昌明,郝芳华,等.黄河小花区间暴雨径流过程分布式模拟[J].水科学进展,2004,15(4)：511-516.
[82]黄粤,陈曦,钱静,等.塔里木河干流生态闸洪水漫溢过程分布式水文模拟——以灿木里克生态闸为例[J].自然资源学报,2007,22(1)：37-43.
[83]董小涛,李致家.HEC模型在洪水预报中的运用[J].东北水利水电,2004,22(11)：43-44.
[84]Todini Eciarapica L. The TOPKAPI Model[C]//Singh VP. eta Mathematical models of large watershed Hydrology. Littleton Colorado:Water Resourses Pub lacations,2001.
[85]李兰,朱芮芮,钟名军.基于GIS的LL-Ⅱ分布式降水径流模型的应用[J].水电能源科学,2004,22(1)： 8-11.
[86]于澎涛,徐德应,王彦辉.应用官司河分布式水文模型模拟流域降雨-径流过程[J].林业科学,2003,39(1)：1-9.
[87]梁钟元,贾仰文,李开杰,等.分布式水文模型在洪水预报中的应用研究综述[J].人民黄河,2007,29(2)：29-32.
[88]魏锋,曾飞.黄河小花间分布式模型洪水预报系统集成研究[J].人民长江,2010,41(24)：25-31.
[89]许继军.分布式水文模型在长江流域的应用研究[D].北京：清华大学,2007.
[90]颜亦奇.受人类活动影响的水库设计洪水调度研究[D].南京：河海大学,2004.
[91]大连市河道管理处.大连市河流特征值手册[M].2005.
[92]张树文,张养贞,李颖,等.东北地区土地利用/覆被时空特征分析[M].北京：科学出版社,2006：42-45.
[93]李伟.人类活动对洪水预报影响分析及防洪调度研究[D].大连：大连理工大学,2009.
[94]李志栋,朱庆.数字高程模型[M].武汉：武汉测绘大学出版社,2000.
[95]孔凡哲.基于数字化平台的分布式流域水文模型和流域汇流研究[D].南京：河海大学,2003.
[96]Moore I D, O'Loughlin E M, Burch G J. A contour-based topographic model for hydrological and ecological applications [J]. Earth Surface Processes and Landforms,1988,13:305-620.
[97]解河海Topmodel的应用及参数不确定性研究[D].南京：河海大学,2006.
[98]叶爱中,夏军,王纲胜,等.基于数字高程模型的河网提取及子流域生成[J].水利学报,2006,36(5)：531-537.
[99]吴信才.地理信息系统原理与方法[M].北京：电子工业出版社,2002.
[100]梅安新,秦其明.遥感导论[M].北京：高等教育出版社,2001.
[101]戴昌达,雷莉萍.TM图像的光谱信息特征与最佳波段组合[J].环境遥感,1989,4(4)：282-292.
[102]Liu J G. Evaluation of Landsat-7 ETM+ panchromatic band for image fusion with multispectral bands [J]. Natural Resources Research,2000,9(4):269-276.
[103]刘纪远,张增祥,庄大方,等.20世纪90年代中国土地利用变化时空特征及其成因分析[J].地理研究,2003,22(1)：1-12.
[104]刘纪远,庄大方,张增祥,等.中国土地利用时空数据平台建设及其支持下的相关研究[J].地球信息科学,2002,3：3-8.
[105]田光进,庄大方,刘明亮.近10年中国耕地资源时空变化特征[J].地理科学进展,2003,18(1)：30-36.
[106]全斌.土地利用与土地覆被变化学导论[M].北京：中国环境科学出版社,2010.
[107]王果.土壤学[M].北京：高等教育出版社,2009.
[108]史学正,于东升,潘贤章,等.国家科技攻关计划土壤数据库专题研究分析报告[R].南京：中国科学院南京土壤研究所,2003.
[109]史学正,于东升.“数字土壤”——21世纪土壤学面临的机遇与挑战[J].土壤通报,2000,31(3)：104-106.
[110]张甘霖,龚子同,骆国保,等.国家土壤信息系统的结构、内容与应用[J].地理科学,2001,21(5)：401-406.
[111]张定祥,史学正,于东升,等.中国1：100万土壤数据库建设的基础[J].地理学报,2002,57(7s)：82-86.
[112]张定祥,潘贤章,史学正,等.中国1：100万土壤数据库建设中的几个问题[J].土壤通报,2003,34(2)：81-84.
[113]张甘霖,史学正,龚子同.中国土壤地理学发展的回顾与展望[J].土壤学报,2008,45(5)：792-801.
[114]史学正,于东升,潘贤章,等.中国1：100万土壤数据库及其应用[C].中国土壤学会第十次全国会员代表大会暨第五届海峡两岸土壤肥料学术交流研讨会论文集(面向农业与环境的土壤科学综述篇),北京：科学出版社,2004.
[115]商瑶玲,王东华,吉建培,等.国家1：50000地形数据库的数据设计与建库[J].测绘科学,2006,s1：74-76.
[116]商瑶玲,王东华,吉建培,等.全国1：25万地形数据库的建立与应用[J].测绘通报,2001,10：29-31.
[117]杨洪泉,李孝明,李成名.1：25万地形图数据挖掘初探[J].测绘通报,2002,9：44-47.
[118]曹明亮,张弛,周惠成,等.丰满上游流域人类活动影响下的降雨径流变化趋势分析[J].水文,2008,28(5)：86-89.
[119]丁晶,邓育仁.随机水文学[M].成都：成都科技大学出版社,1988.
[120]屠其璞,王俊得,丁裕国,等.气象应用概率统计学[M].北京：气象出版社,1984：222-229.
[121]施能.气象科研与预报中的多元统计分析方法[M].北京：气象出版社,2002(第二版).
[122]仕玉治.气候变化及人类活动对流域水资源的影响及实例研究[D].大连：大连理工大学,2011.
[123]贾仰文,王浩,倪广恒,等.分布式流域水文模型原理与实践[M].北京：中国水利水电出版社,2005.
[124]Neitsch S L, Arnold J G, Kiniry J R, et al. Soil and Water Assessment Tool:Theoretical Documentation, version 2005 (available at http://www.brc.tamus.edu/swat/).
[125]王中根,刘昌明,黄友波.SWAT模型的原理、结构及应用研究[J].地理科学进展,2003,22(1)：79-86.
[126]郭兵.太阳总辐射与日照时数相关关系的区域模型分析[D].西安：西安建筑科技大学,2006.
[127]辽宁省土壤肥料总站.辽宁土种志[M].沈阳：辽宁大学出版社,2009.
[128]魏怀斌,张占庞,杨金鹏.SWAT模型土壤数据库建立方法[J].水利水电技术,2007,38(6)：15-18.
[129]M D Morris. Factorial sampling plans for preliminary computational experiments [J]. Technometrics, 1991,33(2):161-174.
[130]M D MeKay, R J Beckmlan, W J Conover. A comparison of three methods for selecting values of input variables in the analysis of output from a computer code [J]. Technometrics,1979,21(2): 239-245.
[131]K Christiaens, J Feyen. Use of sensitivity and uncertainty measures in distributed hydrological modeling with an application to the MIKE SHE model [J].Water Resources Research,2002,38(9): 10-18.
[132]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)：256-261.
[133]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]J G Arnold, R S Muttiah, R Srinivasan, et al. Regional estimation of base flow and groundwater recharge in the upper Mississippi basin [J]. Journal of Hydrology,2000,227(1):21-40.
[135]J Benaman, CA Shoemaker, DA Haith. Calibration and validation of soil and water assessment tool on an agricultural watershed in upstate New York [J]. Journal of hydrologic engineering,2005,10(5): 363-374.
[136]Robert S. Ahl, Scott W. Woods, Hans R. Zuuring. Hydrologic calibration and validation of SWAT in a snow-dominated rocky mountain watershed, Montana, USA [J]. Journal of the American water resources association,2008,44(6):1411-1430.
[137]L Galvan, M Olias, RF de Villaran, et al. Application of the SWAT model to an AMD-affected river (Meca River, SW Spain). Estimation of transported pollutant load [J]. Journal of Hydrology,2009, 377 (3-4):445-454.
[138]J Schuol, KC Abbaspour, R Srinivasan, et al. Estimation of freshwater availability in the West African sub-continent using the SWAT hydrologic model [J]. Journal of Hydrology,2008,352 (1-2): 30-49.
[139]KS. Wu, CA. Johnston. Hydrologic response to climatic variability in a Great Lakes Watershed:A case study with the SWAT model [J]. Journal of Hydrology,2007,337 (1-2):187-199.
[140]V. Sridhar, A. Nayak. Implications of climate-driven variability and trends for the hydrologic assessment of the Reynolds Creek Experimental Watershed, Idaho [J]. Journal of Hydrology,2010, 385(1-4):183-202.
[141]KC Abbaspour, J Yang, I Maximov, et al. Modelling hydrology and water quality in the pre-ailpine/alpine Thur watershed using SWAT[J]. Journal of Hydrology,2007,333 (2-4):413-430.
[142]张东,张万昌,朱利,等.SWAT分布式流域水文物理模型的改进及应用研究[J].地理科学,2005,25(4)：434-440.
[143]王林,张明旭,陈兴伟.基于SWAT模型的晋江西溪流域径流模拟[J].亚热带资源与环境学报,2007,2(1)：28-33.
[144]刘吉峰,霍世青,李世杰,等.SWAT模型在青海湖布哈河流域径流变化成因分析中的应用[J].河海大学学报(自然科学版),2007,35(2)：159-163.
[145]Wenzhi Cao, William B. Bowden, Tim Dayie, et al. Multi-variable and multi-site calibration and validation of SWAT in a large mountainous catchment with high spatial variability [J]. Hydrologocal processes,2006,20(5):1057-1073.
[146]K L White, I Chaubey. Sensitivity analysis, calibration, and validations for a multisite and multivariable SWAT model [J]. Journal of the American water resources association,2005,41(5): 1077-1089.
[147]解河海,郝振.基于TOPMODEL的东江流域水文模拟[J].水科学研究,2008,2(1)：56-62.
[148]Chaplot V. Impact of DEM mesh size and soil map scale on SWAT runoff, sediment, and N03-N loads predictions [J]. Journal of Hydrology,2005,312:207-222.
[149]任希岩,张雪松,郝芳华,等.DEM分辨率对产流产沙模拟影响研究[J].水土保持研究,2004,11(1)：1-4.
[150]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(3),22-25.
[151]Hornberger G M, Spear R C. An approach to the preliminary analysis of environmental systems [J]. Journal of Environmental management,1981,12:7-18.
[152]Beven K, Freer J. Equifinality, data assimilation, and uncertainty estimation in mechanistic modeling of complex environmental systems using the GLUE methodology [J]. Journal of Hydrology,2001, 249:11-29.
[153]陈守煜.可变模糊集理论与模型及其应用[M].大连：大连理工大学出版社,2009.
[154]Xiong L H, O'Connor K M. An empirical method to improve the prediction limits of the GLUE methodology in rainfall-runoff modeling [J]. Journal of Hydrology,2008,349:115-124.
[155]卫晓婧,熊立华,万民,等.融合马尔科夫链-蒙特卡洛算法的改进通用似然不确定性估计方法在流域水文模型中的应用[J].水利学报,2008,40(4)：464-473.
[156]刘冀.径流分类组合预报方法及其研究应用[D].大连：大连理工大学,2008.
[157]辽宁省人民政府地方志办公室.辽宁年鉴[M].沈阳：辽宁年鉴编辑部.
[158]《辽宁经济统计年鉴》编辑委员会.辽宁经济统计年鉴[M].沈阳：辽宁人民出版社.
[159]中国城市经济社会年鉴理事会.中国城市经济社会年鉴[M].北京：中国城市经济社会出版社.
[160]大连市统计局.大连统计年鉴[M].北京：中国统计出版社.
[161]Anthes R A, Hsie E Y, Kuo Y H. Description of the penn state/NCAR mesoscale model version4 (MM4). Tech. Note NCAR/TN-281+STR,1987,66.
[162]Giorgi F, Bates G T. The climatological skill of a regional model complex terrain[J]. Mon.Wea.Rev., 1989,117:2325-2347.
[163]Dickinson R E, Kennedy P J, Giorgi F, et al. A regional climate model for the western United States[J]. Clim.Change,1989,15:383-422.
[164]Giorgi F, Marinucci M R, Bates G T. Development of a second-generation regional climate model (RegCM2). Part Ⅰ:Boundary-layer and radiative transfer processes [J], Mon.Wea.Rev.,1993a,121: 2794-2813.
[165]Giorgi F, Marinucci M R, Bates G T. Development of a second-generation regional climate model (RegCM2). Part Ⅱ:Convective processes and assimilation of lateral boundary conditions [J]. Mon.Wea.Rev.,1993b,121:2814-2832.
[166]Pal J S, Giorgi F, Bi X Q, et al. The ICTP RegCM3 and RegCNET. Regional climate modeling for the developing world [J]. Bull. Am. Meteorol. Soc.,2007,88(9):1395-1409.
[167]宋瑞艳.一个高分辨率区域气候模式(RegCM3)对中国未来极端降水事件变化的预估[D].北京：中国气象科学研究院,2008.
[168]周建玮,王咏青.区域气候模式RegCM3应用研究综述[J].气象科学,2007,27(6)：702-708.
[169]张可欣,孙成武RegCM3对山东夏季气候高分辨率模拟[J].气象科学,2009,29(4)：490-497.
[170]Nellie E, X Q Bi, F Giorgi.2006. RegCM Version 3.1 Users Guide. NCAR Tech Note,6-11.
[171]刘纪远,刘明亮,庄大方,等.中国近期土地利用变化的空间格局分析[J].中国科学(D辑),2002,32(12)：1031-1040.
[172]Lotta Andersson, Julie Wilk, Martin C. Todd, et al. Impact of climate change and development scenarios on flow patterns in the Okavango River [J]. Journal of Hydrology,2006,331:43-57.
[173]Bergstrom, S., Carlsson, B., Gardelin, M., et al. Rummukainen, M., Climate change impacts on runoff in Sweden-assessments by global climate models, dynamical downscaling and hydrological modeling [J]. Climate Res.2001,16 (2):101-112.
[174]秦大河.中国气候与环境演变：气候与环境变化的影响与适应、减缓对策(上下卷)[M].北京：科学出版社,2005.
[175]张利平,陈小凤,赵志鹏,等.气候变化对水文水资源影响的研究进展[J].地理科学进展,2008,27(3)：60-67.
[176]Jia Y W, Wang H, Zhou Z H, et al. Development of the WEP-L distributed hydrological model and dynamic assessment of water resources in the Yellow River basin [J]. Journal of Hydrology,2006, 331:606-629.
[177]Ren L L, Wang M R, Li C H, et al. Impacts of human activity on river runoff in the northern area of China[J]. Journal of Hydrology,2002,261:204-217.
[178]Xu J J, Yang D W, Yi Y H, et al. Spatial and temporal variation of runoff in the Yangtze River basin during the past 40 years [J]. Quaternary International,2008,186:32-42.
[179]Barlage M J, P L Richards, et al. Impacts of climate change and land use change on runoff from a Great Lakes watershed [J]. Journal of Great Lakes Research,2002,28(4):568-582.
[180]Seguis L, Cappelaere B, et al. Simulated impacts of climate change and land-clearing on runoff from a small Sahelian catchment [J].Hydrological Processes,2004,18(17):3401-3413.
[181]Monteith J L. Evaporation and environment [J]. Symposia of the Society for Experimental Biology, 1965,19:205-234.
[182]Liebe J, van de Giesen N, Andreini M. Estimation of small reservoir storage capacities in a semi-arid environment [J]. Physics and Chemistry of the Earth,2005,30(6):448-454.
[183]丁智雄.DEM与遥感相结合的水库水位面积曲线测定方法研究[J].水利水电技术,2010,41(1)：83-86.
[184]Du Y Y, Zhou C H. Automatically extracting remote sensing information for water bodies[J]. Journal of Remote Sensing,1988,2(4):264-269.
[185]曹波.基于遥感图像和DEM测定水库动库容的方法研究[D].武汉：华中科技大学,2006.
[186]吴赛.基于EOS/MODIS的水体提取模型及其在洪灾监测中的应用[D].武汉：华中科技大学,2005.
[187]李永生,武鹏飞.基于MODIS数据的艾比湖湖面变化研究[J].水资源与水工程学报,2008,19(5)：110-112.
[188]Mcfeeters S K. The use of the Normalized Difference Water Index(NDWI) in the delineation of open water features [J]. International Journal of Remote Sensing,1996,17(7):1425-1432.
[189]Gao B C. NDWI-A normalized difference water index for remote sensing of vegetation liquid water from space [J], Remote Sensing of Environment,1995,58:257-266.
[190]Ouma Y, Tateishi R. A water index for rapid mapping of shoreline changes of five East African Rift Valley lakes:An empirical analysis using Landsat TM and ETM+ data[J], International Journal of Remote Sensing,2006,27(15):3153-3181.
[191]Sawunyama T, Senzanje A, Mhizha A. Estimation of small reservoir storage capacities in Limpopo River Basin using geographical information systems (GIS) and remotely sensed surface areas Case of Mzingwane catchment [J]. Physics and Chemistry of the Earth,2006,31(15):935-943.
[192]水利部松辽水利委员会.东北地区实用洪水预报方案(上册)[M].2003.