跨流域引水与水库供水联合调度及变化条件对其影响研究
|
摘要
跨流域调水工程能够有效缓解水资源时空分布的不均匀性及社会需水的不平衡性,逐渐成为解决资源性缺水地区水资源需求的一种重要措施。为提高引水效率和效益,势必需要确定合理有效的跨流域引水与水库供水联合调度规则,指导水库运行。此外,调水工程建成后将是一个长期的运行过程,近年来不断加剧的气候变化及人类活动,未来仍将对区域水资源状况以及受水水库的调度运行产生影响。基于历史径流系列得到的调度规则,能否适应未来的变化条件,亟需进行研究。本文以此为切入点,以碧流河水库为研究对象,系统研究气候变化及人类活动对跨流域引水与水库供水联合调度的影响。主要研究内容及成果如下：
(1)基于历史长时期降雨、径流数据,开展特征值变化及趋势性检验分析。在此基础上,定性辨识气候变化和人类活动对径流的影响,识别研究区跨流域调水实际问题。为全文针对气候变化及人类活动对跨流域引水与水库供水联合调度影响开展探索性研究奠定基础。
(2)基于增加引水调度线的思想,设计跨流域引水与水库供水联合调度规则,并针对受水水库原设计中考虑生态需水不全面的问题,构建以均衡城市供水及生态供水为目标的多目标优化模型。基于历史长系列径流数据,采用带精英策略的遗传算法(NSGA-Ⅱ)进行模型求解,优化得到考虑“好”及“中”两种生态流量的城市及生态供水相互博弈的Pareto前沿解集,本文称之为历史方案。通过调度图特点及水库运行过程分析,验证历史方案的合理性；与不引水时优化调度结果对比,结果表明,研究区亟需通过引水来缓解供需水矛盾,本文设计并优化得到的跨流域引水与水库供水联合调度规则,实现了调水的有效性,在引水量约为2.5亿m3时,增加城市供水量约2.9亿m3,对于保障地区经济可持续发展具有重大意义。
(3)基于SWAT分布式水文模型的本地化构建,针对未来气候变化及人类活动影响展开分析。一方面,选取第五次国际耦合模式比较计划(CMIP5)试验中3种气候模型(ACCESS1.0、BCC-CSM1.1(m)及CMCC-CM)输出的气候数据；基于改进Morphing方法对未来气候情景数据进行降尺度修正,并分析未来降雨及气温变化。另一方面,在人类活动影响因子中,针对未来人类取用水信息难以预测的问题,提出基于相邻年降雨量水平的人类取用水模糊推理模型。在对历史时期人类取用水进行推理结果验证时发现,考虑人类取用水影响的径流系列与实测系列的拟合程度、模拟评价指标,均比SWAT模拟输出径流系列有较大改进。推理模型得到的模糊规则参数,揭示了历史人类取用水与降雨径流之间的关系规律,在未来短期内未规划大量增加人口的情况下,可作为推测未来取用水影响量的重要依据。
(4)以不同未来气候情景数据驱动SWAT模型,并在模型中直接考虑水利工程的影响,进行未来径流模拟预测；在该径流模拟系列及未来降雨系列的基础上,基于人类取用水推理模型预测未来取用水影响量,进一步改进SWAT模拟结果,获取变化条件下径流状况。结果表明,相对于历史长系列多年平均径流量,ACCESS1.0、 BCC-CSM1.1(m)及CMCC-CM模型情景下,未来径流量将分别变化+20.55%、-9.59%和-29.13%。基于统计学分析方法,进一步掌握未来各情景下降雨径流分布及趋势等变化特点,结论为研究变化条件对受水水库联合调度的影响奠定基础。
(5)针对未来径流量大幅减少的供水偏不安全情景(CMCC-CM模型情景),首先考察历史方案在该情景径流系列下的运行表现,包括各用水户供水量及保证率的满足情况；在运行指标变差的情况下,进行联合调度规则的重优化。结果表明,该情景下,在考虑“中”生态流量时,需要进行联合调度规则的重优化,才能基本满足各用水户供水保证率；而在考虑“好”生态流量时,需要将城市供水量目标降为4.57亿m3(较原城市供水量目标减少0.51亿m3),才能基本满足保证率要求。
(6)进一步针对未来气候情景不确定性对联合调度的影响展开分析。借助于所选取的三种未来气候情景,同时假定三个气候变化情景(未来多年平均径流量较历史长系列分别变化-9.91%、-15.08%及-21.35%),以识别未来调度规则进行调整的临界条件。通过对比分析历史方案在各情景径流系列下的运行表现,最终对未来联合调度提出运行建议：当径流减少量在15%以下时,继续沿用历史方案仍可基本满足各用水户的保证率要求；而当径流量减少15%以上时,建议仅考虑“中”生态流量,或适当降低考虑“好”生态流量时的城市供水量目标,才能满足各用水户的供水保证率要求。
Water transfer projects have been promoted as a real option to relieve regional water supply pressures caused by the non-uniform temporal and spatial distributions of water resources. It's necessary to design and optimize a set of water diversion-supply rules in order to improve the water diversion efficiency and effectiveness. Besides, it will be a long term operation after the project constructed. The changing climate condition and human activities may have impact on future reservoir operation. The future climate and human activities forecast and the impact of them attracts researchers'attentions. It is critically important to understand the performance of the historical optimal water diversion rules in changing future conditions, which might affect the water resources available in the receiving regions. Regarding this as the entry-point, this paper aims to develop an assessment framework to study the impacts of climate change and human activities on optimal water diversion strategies of a receiving reservoir in the water diversion project. The proposed framework is demonstrated using the water transfer project in the water deficit Biliu River reservoir basin, China. The main research content and results of this paper are summarized as follows:
(1) Analyze the historical precipitation and runoff variation, including the characteristic and change trend. On the basis of the variation analysis results, identify the impact of climate change and human activities qualitatively, as well as the actual water diversion problems in the study area. The analysis and problem identification laid the foundation for the following exploratory researches, i.e. optimize a Pareto front of inter-basin water diversion and reservoir water supply joint operation rules, as well as the impacts of future climate changes and human activities on reservoir future operation.
(2) Developing inter-basin water diversion and reservoir water supply joint operation rules of the receiving reservoir based on the thought of adding water diversion rules. The optimal water diversion problem is defined as a multi-objective problem with two conflicting objectives:minimizing the public and ecological water supply shortages. The popular non-dominated sorting genetic algorithm II (NSGA-II) is used to solve the optimization problem with two ecological water supply cases, i.e. the "good" and'"medium" cases. The derived Pareto-optimal solutions based on historical runoff series, hereinafter referred to as the historical optimal rules for short. The historical optimal rules are demonstrated reasonable according to the characteristic of joint operation rules, as well as the reservoir operation processes. Compared to the optimal results of no water diversion conditions, the designed and optimized operation rules are demonstrated can increase290X106m3water supply to the public water user when divert250×106m3water, and satisfy the guarantee rate of all the users. It implies that the optimal joint operation rules play a significant role to safeguard regional economic.
(3) Based on the distributed hydrologic model SWAT, the hydrologic response of future climate change and human activities are analyzed. On the one hand, three climate models (ACCESS1.0, BCC-CSM1.1(m) and CMCC-CM) of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) respectively run for a high Representative Concentration Pathway (RCP8.5) are selected. And a modified Morphing method is used to downscale the precipitation and temperature data. On the other hand, aim to solve the challenge of human water consumption forecast, which is one of the three main human activities, this paper put forward the Fuzzy Inference Model of human water consumption based on the precipitation levels of adjacent years. The efficiency of the fuzzy interface model is demonstrated based on the historical human water consumption data. The fitting degree and simulation evaluation indexes of the runoff simulation results modified by considering human water consumption are much better than the SWAT simulation results. The parameters of fuzzy rules, derived by the Fuzzy Inference Model, reveal the historical rules of the relationship between the human water consumption and the precipitation levels of adjacent years.Because there's no population growth plan in the study area, the inference model and the derived historical parameters of fuzzy rules can be an important basis for forecasting the future human water consumption.
(4) Drive SWAT model with several future climate scenarios, directly considering Yushi reservoir in the model, in order to generate future runoff conditions.In addition, modify the SWAT simulation results based on the Fuzzy Inference Model of human water consumption. Results show that, under future climate models ACCESS1.0, BCC-CSM1.1(m) and CMCC-CM, the future runoff increase20.55%, decrease9.59%and decrease29.13%respectively, compared to the historical runoff series. Statistical approaches are used to analyze the changes of the characteristic values, distribution and change trend of future precipitation and runoff series. The results of future runoff changes are the base of the analysis of the change conditions impact on reservoir joint operation rules.
(5) The future runoff sharp decreased scenario (CMCC-CM model), probably can't guarantee water supply to all the water users. According to the mentioned scenario, the performances of the historical optimal rules are re-evaluated under the "good" and "median" ecological water supply cases, using the predicted future runoff by comparing several operation indicators such as the average annual amount of water supply, the guarantee rate of water users, etc. In addition, the joint operation rules are re-optimized under future runoff when the main operation indicators appear worse. Results show that, under the mentioned scenario, when consider "median" ecological water supply, re-optimizing the joint operation rules can guarantee water supply; while consider "good" ecological water supply, reducing the public water supply target to457×106m3(51×106m3less than the original public water supply target), is inevitable in order to guarantee water supply for all the three users.
(6) Uncertainties of future climate scenarios impacts on joint operation are further analyzed. Besides the selected three CMIP5climate models, assumption of climate variables variation scenarios are also used to evaluated their impacts on the joint operation. The three assumptions of climate scenarios results in future runoff decrease9.91%,15.08%and21.35%respectively. The critical conditions of adjusting the historical optimal rules are identified based on the mentioned scenarios. According to the comparison of their performances using the historical optimal rules, suggestions are made finally:when the amount decrease of future runoff is less than15%, the historical optimal rules still can be used and the guarantee rate of water users can be basicly satisfied; while the amount decrease of future runoff is larger than15%,"median" ecological water supply case is suggested to be considered, or properly reducing the public water supply target of "good" ecological water supply case is inevitable, in order to guarantee water supply.
(1)基于历史长时期降雨、径流数据,开展特征值变化及趋势性检验分析。在此基础上,定性辨识气候变化和人类活动对径流的影响,识别研究区跨流域调水实际问题。为全文针对气候变化及人类活动对跨流域引水与水库供水联合调度影响开展探索性研究奠定基础。
(2)基于增加引水调度线的思想,设计跨流域引水与水库供水联合调度规则,并针对受水水库原设计中考虑生态需水不全面的问题,构建以均衡城市供水及生态供水为目标的多目标优化模型。基于历史长系列径流数据,采用带精英策略的遗传算法(NSGA-Ⅱ)进行模型求解,优化得到考虑“好”及“中”两种生态流量的城市及生态供水相互博弈的Pareto前沿解集,本文称之为历史方案。通过调度图特点及水库运行过程分析,验证历史方案的合理性；与不引水时优化调度结果对比,结果表明,研究区亟需通过引水来缓解供需水矛盾,本文设计并优化得到的跨流域引水与水库供水联合调度规则,实现了调水的有效性,在引水量约为2.5亿m3时,增加城市供水量约2.9亿m3,对于保障地区经济可持续发展具有重大意义。
(3)基于SWAT分布式水文模型的本地化构建,针对未来气候变化及人类活动影响展开分析。一方面,选取第五次国际耦合模式比较计划(CMIP5)试验中3种气候模型(ACCESS1.0、BCC-CSM1.1(m)及CMCC-CM)输出的气候数据；基于改进Morphing方法对未来气候情景数据进行降尺度修正,并分析未来降雨及气温变化。另一方面,在人类活动影响因子中,针对未来人类取用水信息难以预测的问题,提出基于相邻年降雨量水平的人类取用水模糊推理模型。在对历史时期人类取用水进行推理结果验证时发现,考虑人类取用水影响的径流系列与实测系列的拟合程度、模拟评价指标,均比SWAT模拟输出径流系列有较大改进。推理模型得到的模糊规则参数,揭示了历史人类取用水与降雨径流之间的关系规律,在未来短期内未规划大量增加人口的情况下,可作为推测未来取用水影响量的重要依据。
(4)以不同未来气候情景数据驱动SWAT模型,并在模型中直接考虑水利工程的影响,进行未来径流模拟预测；在该径流模拟系列及未来降雨系列的基础上,基于人类取用水推理模型预测未来取用水影响量,进一步改进SWAT模拟结果,获取变化条件下径流状况。结果表明,相对于历史长系列多年平均径流量,ACCESS1.0、 BCC-CSM1.1(m)及CMCC-CM模型情景下,未来径流量将分别变化+20.55%、-9.59%和-29.13%。基于统计学分析方法,进一步掌握未来各情景下降雨径流分布及趋势等变化特点,结论为研究变化条件对受水水库联合调度的影响奠定基础。
(5)针对未来径流量大幅减少的供水偏不安全情景(CMCC-CM模型情景),首先考察历史方案在该情景径流系列下的运行表现,包括各用水户供水量及保证率的满足情况；在运行指标变差的情况下,进行联合调度规则的重优化。结果表明,该情景下,在考虑“中”生态流量时,需要进行联合调度规则的重优化,才能基本满足各用水户供水保证率；而在考虑“好”生态流量时,需要将城市供水量目标降为4.57亿m3(较原城市供水量目标减少0.51亿m3),才能基本满足保证率要求。
(6)进一步针对未来气候情景不确定性对联合调度的影响展开分析。借助于所选取的三种未来气候情景,同时假定三个气候变化情景(未来多年平均径流量较历史长系列分别变化-9.91%、-15.08%及-21.35%),以识别未来调度规则进行调整的临界条件。通过对比分析历史方案在各情景径流系列下的运行表现,最终对未来联合调度提出运行建议：当径流减少量在15%以下时,继续沿用历史方案仍可基本满足各用水户的保证率要求；而当径流量减少15%以上时,建议仅考虑“中”生态流量,或适当降低考虑“好”生态流量时的城市供水量目标,才能满足各用水户的供水保证率要求。
Water transfer projects have been promoted as a real option to relieve regional water supply pressures caused by the non-uniform temporal and spatial distributions of water resources. It's necessary to design and optimize a set of water diversion-supply rules in order to improve the water diversion efficiency and effectiveness. Besides, it will be a long term operation after the project constructed. The changing climate condition and human activities may have impact on future reservoir operation. The future climate and human activities forecast and the impact of them attracts researchers'attentions. It is critically important to understand the performance of the historical optimal water diversion rules in changing future conditions, which might affect the water resources available in the receiving regions. Regarding this as the entry-point, this paper aims to develop an assessment framework to study the impacts of climate change and human activities on optimal water diversion strategies of a receiving reservoir in the water diversion project. The proposed framework is demonstrated using the water transfer project in the water deficit Biliu River reservoir basin, China. The main research content and results of this paper are summarized as follows:
(1) Analyze the historical precipitation and runoff variation, including the characteristic and change trend. On the basis of the variation analysis results, identify the impact of climate change and human activities qualitatively, as well as the actual water diversion problems in the study area. The analysis and problem identification laid the foundation for the following exploratory researches, i.e. optimize a Pareto front of inter-basin water diversion and reservoir water supply joint operation rules, as well as the impacts of future climate changes and human activities on reservoir future operation.
(2) Developing inter-basin water diversion and reservoir water supply joint operation rules of the receiving reservoir based on the thought of adding water diversion rules. The optimal water diversion problem is defined as a multi-objective problem with two conflicting objectives:minimizing the public and ecological water supply shortages. The popular non-dominated sorting genetic algorithm II (NSGA-II) is used to solve the optimization problem with two ecological water supply cases, i.e. the "good" and'"medium" cases. The derived Pareto-optimal solutions based on historical runoff series, hereinafter referred to as the historical optimal rules for short. The historical optimal rules are demonstrated reasonable according to the characteristic of joint operation rules, as well as the reservoir operation processes. Compared to the optimal results of no water diversion conditions, the designed and optimized operation rules are demonstrated can increase290X106m3water supply to the public water user when divert250×106m3water, and satisfy the guarantee rate of all the users. It implies that the optimal joint operation rules play a significant role to safeguard regional economic.
(3) Based on the distributed hydrologic model SWAT, the hydrologic response of future climate change and human activities are analyzed. On the one hand, three climate models (ACCESS1.0, BCC-CSM1.1(m) and CMCC-CM) of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) respectively run for a high Representative Concentration Pathway (RCP8.5) are selected. And a modified Morphing method is used to downscale the precipitation and temperature data. On the other hand, aim to solve the challenge of human water consumption forecast, which is one of the three main human activities, this paper put forward the Fuzzy Inference Model of human water consumption based on the precipitation levels of adjacent years. The efficiency of the fuzzy interface model is demonstrated based on the historical human water consumption data. The fitting degree and simulation evaluation indexes of the runoff simulation results modified by considering human water consumption are much better than the SWAT simulation results. The parameters of fuzzy rules, derived by the Fuzzy Inference Model, reveal the historical rules of the relationship between the human water consumption and the precipitation levels of adjacent years.Because there's no population growth plan in the study area, the inference model and the derived historical parameters of fuzzy rules can be an important basis for forecasting the future human water consumption.
(4) Drive SWAT model with several future climate scenarios, directly considering Yushi reservoir in the model, in order to generate future runoff conditions.In addition, modify the SWAT simulation results based on the Fuzzy Inference Model of human water consumption. Results show that, under future climate models ACCESS1.0, BCC-CSM1.1(m) and CMCC-CM, the future runoff increase20.55%, decrease9.59%and decrease29.13%respectively, compared to the historical runoff series. Statistical approaches are used to analyze the changes of the characteristic values, distribution and change trend of future precipitation and runoff series. The results of future runoff changes are the base of the analysis of the change conditions impact on reservoir joint operation rules.
(5) The future runoff sharp decreased scenario (CMCC-CM model), probably can't guarantee water supply to all the water users. According to the mentioned scenario, the performances of the historical optimal rules are re-evaluated under the "good" and "median" ecological water supply cases, using the predicted future runoff by comparing several operation indicators such as the average annual amount of water supply, the guarantee rate of water users, etc. In addition, the joint operation rules are re-optimized under future runoff when the main operation indicators appear worse. Results show that, under the mentioned scenario, when consider "median" ecological water supply, re-optimizing the joint operation rules can guarantee water supply; while consider "good" ecological water supply, reducing the public water supply target to457×106m3(51×106m3less than the original public water supply target), is inevitable in order to guarantee water supply for all the three users.
(6) Uncertainties of future climate scenarios impacts on joint operation are further analyzed. Besides the selected three CMIP5climate models, assumption of climate variables variation scenarios are also used to evaluated their impacts on the joint operation. The three assumptions of climate scenarios results in future runoff decrease9.91%,15.08%and21.35%respectively. The critical conditions of adjusting the historical optimal rules are identified based on the mentioned scenarios. According to the comparison of their performances using the historical optimal rules, suggestions are made finally:when the amount decrease of future runoff is less than15%, the historical optimal rules still can be used and the guarantee rate of water users can be basicly satisfied; while the amount decrease of future runoff is larger than15%,"median" ecological water supply case is suggested to be considered, or properly reducing the public water supply target of "good" ecological water supply case is inevitable, in order to guarantee water supply.
引文
[1]邵东国.跨流域调水工程规划调度决策理论与应用[M].武汉：武汉大学出版社,2001.
[2]彭勇.中长期水文预报与水库群优化调度方法及其系统集成研究[D].大连：大连理工大学,2007.
[3]IPCC. Climate Change 2007:Synthesis Report [M], Geneva, Switzerland,2007.
[4]《气候变化国家评估报告》编写委员会.气候变化国家评估报告[M].北京：科学出版社,2007.
[5]贾仰文,王浩,彭辉.水文学及水资源学科发展动态[J].中国水利水电科学研究院学报,2009.7(2)：241-248.
[6]Muller, M. Interbasin water sharing:a South African perspective [C]. In:International Hydrological Program-V. UNESCO. Paris:Proceedings of the International Workshop,1999:61-70.
[7]Azevedo, L.G.T., L.L.R. Porto, A.V. Mello, J.G. Pereira, D.L.P. Arrobas, L.C. Noronha, et al. Transferencia de agua entre bacias hidrograficas [M]. Serie Agua Brasil. Vol.7. Brasilia 2005.
[8]Ma, J., A.Y. Hoekstra, H. Wang, A.K. Chapagain, D.X. Wang. Virtual versus real water transfers within China [J]. Philosophical Transactions of the Royal Society,2006(361):835-842.
[9]Chang, J.X., J. Jiang. Water Dispatch of the South-to-North Water Transfer Project in Shaanxi Province [J]. JOURNAL OF NATURAL RESOURCES,2011.26(1):110-118.
[10]Dyrnes, G.V., A. Vatn. Who owns the water? A study of a water conflict in the Valley of Ixtlahuaca, Mexico [J]. Water Policy,2005.7(3):295-312.
[11]郑连第.中国历史上的跨流域调水工程[J].南水北调与水利科技,2003.1(1)：5-8.
[12]关志诚.跨流域调水工程的关键技术与建设实践[J].水利水电技术,2009(08)：89-94.
[13]李运辉,陈献耘,沈艳忱.巴基斯坦西水东调工程[J].水利发展研究,2003.3(1)：56-58.
[14]沈佩君,邵东国,郭元裕.国内外跨流调水工程建设的现状与前景[J].武汉水利电力大学学报,1995.28(5)：463-469.
[15]杨立信.澳大利亚雪山工程上游段建筑物的布置特点[J].水利发展研究,2002.2(7)：46-48.
[16]Weiner, D., B.Z. Arie. A stochastic dynamic programing model for the operation of the Mediterranean-Dead Sea Project [J]. Water Resources Research,1982.18(4):729-734.
[17]Li, S. X. Research on Operation Decision-Making and Management Pattern in Inter-Basin Water Teansfer System [D]. Dalian:Dalian University of Technology,2009.
[18]Jain, S.K., N.S.R.K. Reddy, U.C. Chaube. Analysis of a large inter-basin water transfer system in India [J]. Hydrological Sciences Journal,2005.50(1):125-137.
[19]Gupta, J., P.v.d. Zaag. Interbasin water transfers and integrated water resources anagement:Where engineering, science and politics interlock [J]. Physics and Chemistry of the Earth,2008(33):28-40.
[20]Sadegh, M., N. Mahjouri, R. Kerachian. Optimal Inter-Basin Water Allocation Using Crisp and Fuzzy Shapley Games [J]. Water Resources Management,2010(24):2291-2310.
[21]阮本清,王浩.西线调水区水资源分析及可调水量商榷[J].清华大学学报(自然科学版),2000.40(S1)：101-106.
[22]耿万东.丹江口水库可调出水量研究[D].郑州：郑州大学,2007.
[23]张玫,张玮.南水北调西线工程可调水量分析中几个主要问题的探讨[J].水文,2002.22(4)： 32-36.
[24]尹宏伟,李勇,郑垂勇.跨流域调水工程受水区水资源优化配置的模型[J].统计与决策,2007(23)：38-41.
[25]王浩,秦大庸,王建华,罗琳,裴源生.黄淮海流域水资源合理配置[M].北京：科学出版社,2003.
[26]赵勇,解建仓,马斌.基于系统仿真理论的南水北调东线水量调度[J].水利学报,2002.31(11)：38-43.
[27]王劲峰,刘昌明,于静洁,陈红焱.区际调水时空优化配置理论模型探讨[J].水利学报,2001.30(4)：7-15.
[28]游进军,王忠静,甘泓,张建中.两阶段补偿式跨流域调水配置算法及应用[J].水利学报,2008.39(7)：870-876.
[29]黄薇,陈进.跨流域调水水权分配与水市场运行机制初步探讨[J].长江科学院院报,2006.23(1)：50-52.
[30]李萍,徐明.关于调水工程水权问题的研究[J].水利经济,2002.20(2)：28-31.
[31]刘斌,朱尔明.试论南水北调工程与水权制度[J].中国水利,2002(1)：47-48.
[32]刘洪先.水权理论与南水北调工程水权分配[J].人民黄河,2002.24(3)：15-17.
[33]游进军,王忠静,甘泓,蒋云钟.国内跨流域调水配置方法研究现状与展望[J].南水北调与水利科技,2008.6(3)：1-4+8.
[34]郑通汉,任宪韶.水利工程供水两部制水价制度研究[M].北京：中国水利水电出版社,2006.
[35]张军,王华,董温荣,张永平.南水北调供水两部制水价模式探讨[J].水利经济,2006.24(3)：34-35.
[36]王国利,彭勇,何.斌,梁国华.GFS降雨预报在大伙房水库实时跨流域调水决策的应用研究[J].水资源与水工程学报,2010.21(2)：1-4.
[37]卢华友,沈佩君,邵东国,魏山忠,文丹,吴泽宇,et a1.跨流域调水工程实时优化调度模型研究[J].武汉水利电力大学学报,1997.30(5)：11-15.
[38]梁国华,王国利,王本德,董霞.大伙房跨流域引水工程预报调度方式研究[J].水力发电学报,2009.28(3)：32-36+46.
[39]习树峰,彭勇,梁国华,王本德,等.基于决策树方法的水库跨流域引水调度规则研究[J].大连理工大学学报,2012,52(1)：74-78.
[40]汪明娜,汪达.调水工程对环境利弊影响综合分析[J].水资源保护,2002(4)：10-14.
[41]Hirji, R. Inter-basin water transfers -emerging trends [R]. The World Bank, Washington, DC,1998.
[42]李善同,许新宜.南水北调与中国发展[M].北京：经济科学出版社,2004.
[43]郭潇,方国华,张哲恺.跨流域调水生态环境影响评价指标体系研究[J].水利学报,2008.39(9)：1125-1130.
[44]Petitjean, M.O.G., B.R. Davies. Ecological impacts of inter-basin water transfers:some case studies, research requirements and assessment procedures in Southern Africa [J]. South African Journal of Science,1988.84(10):819-828.
[45]Matete, M., R. Hassan. An ecological economics framework for assessing environmental flows:the case of inter-basin water transfers in Lesotho [J]. Global and Planetary Change,2005.47(2/4): 193-200.
[46]Li, Y., P. He, W. Xiao, B. Liu. The Research of Water Environment Cumulative Impacts of Delivery Canal on East Route of South-to-North Water Transfer Project [J]. Procedia Engineering,2012.28: 287-291.
[47]窦明,左其亭,胡彩虹.南水北调工程的生态环境影响评价研究[J].郑州大学学报(工学版),2005.26(2)：63-66.
[48]刘进琪.大通河跨流域调水对生态环境的影响[J].甘肃科学学报,2006.18(1)：49-52.
[49]史淑娟,李怀恩,林启才,党志良.跨流域调水生态补偿量分担方法研究[J].水利学报,2009.40(3)：268-273.
[50]习树峰.跨流域调水预报优化调度方法及应用研究[D].大连：大连理工大学,2011.
[51]郭生练,陈炯宏,刘攀,李雨.水库群联合优化调度研究进展与展望[J].水科学进展,2010.21(4)：496-503.
[52]胡铁松,万永华,冯尚友.水库群优化调度函数的人工神经网络方法研究[J].水科学进展,1995.6(1)：53-60.
[53]Srinivas, N. and Deb K. Multiobjective function Optimization using nondominated sorting genetic algorithms [J]. Evolutionary Computation,1995.2(3):221-248.
[54]Deb, K., Agrawal S., Pratpa A., e. al. A fast elitist nondominated sorting genetic algorithms for multi-objective optimization:NSG-II [C]. In:Proc of the Parallel Problem Solving from Nature VI Conf. Paris,2000:849-858.
[55]Suen, J.P., J.W. Eheart. Reservoir management to balance ecosystem and human needs: Incorporating the paradigm of the ecological flow regime [J]. Water Resource Research,2006. 42(W03417).
[56]张志刚,马光文.基于NSGA-Ⅱ算法的多目标水火电站群优化调度模型研究[J].水力发电学报,2010.29(1)：213-218.
[57]贠汝安,董增川,王好芳.基于NSGA2的水库多目标优化[J].山东大学学报(工学版),2010.40(6)：124-128.
[58]陈守煜.可变集一可变模糊集的发展及其在水资源系统中的应用[J].数学的实践与认识,2012(1)：92-101.
[59]Zadeh L A. Fuzzy sets [J]. Information and control,1965,8 (3):338-353.
[60]陈守煜.水资源系统可变集评价原理与方法[J].水利学报,2013,4(2)：134-142.
[61]Barnett, T.P., J.C. Adam, D.P. Lettenmaier. Potential impacts of a warming climate on water availability in snow-dominated regions [J]. Nature,2005(438):303-309.
[62]Frederick, K.D., P.H. Gleick. Water and global climate change:Potential impacts on U.S. water resources [R], Arlington, Virginia,1999.48.
[63]IPCC. Climate Chnage and Impact 1990 [M]. Cambridge:Cambridge Univesity Perss,1990.
[64]IPCC. Climate Chnage 1995. Impact, Adaptation, and Mitigation [M]. Cambridge:Cambridge Univesity Perss,1995.
[65]IPCC. Climate Chnage 2001.Impacts, adaptation, vulnerability [M]. Cambridge:Cambridge Univesity Perss,2001.
[66]英爱文,姜广斌.辽河流域水资源对气候变化的响应[J].水科学进展,增刊,1996.7：68-72.
[67]贾仰文,高辉,牛存稳,等.气候变化对黄河源区径流过程的影响[J].水利学报,2008.39(1)：52-58.
[68]Gleick, P.H. The development and testing of a water balance model for climate impact assessment: modeling the Sacramento basin [J]. Water Resources Research,1987.23(7):1049-1061.
[69]Christensen, N.S., A.W. Wood, N. Voisin, etal. The effects of climate change on the hydrology and water resources of the Colorado River basin [J]. Climatic Change,2004.62(1-3):337-363.
[70]袁飞,谢正辉,任立良,黄琼.气候变化对海河流域水文特性的影响[J].水利学报,2005.36(3)：274-279.
[71]Gleick, P.H. Climate change, hydrology, and water resources [J]. Reviews of geophysics,1989. 27(3):329-344.
[72]Xu, C.Y. Climate change and hydrologic models:A review of existing gaps and recent research developments [J]. Water Resources Management,1999.13(5):369-382.
[73]张建云,王国庆等.气候变化对水文水资源影响研究[M].2007,北京：科学出版社.
[74]Lettenmaier, D.P., T.Y. Gan. Hydrologic sensitivity of the Sacramento-San Jaoquin river basin, California, to global warming [J]. Water Resources Research,1990(26):69-86.
[75]Chiew, F.H.S., J. Vaze, N.R. Viney, J.M. Perraud, J. Teng, P.W. Jordan, et al. Estimation of runoff and the impact of climate change and development on runoff across the Murray-Darling Basin [C]. In:Proceedings of the Water Down Under 2008. Adelaide, Australia,2008:1957-1968.
[76]Prudhomme, C., D. Jakob, C. Svensson. Uncertainty and climate change impact on the flood regime of small UK catchments [J]. J Hydrol,2003(277):1-23.
[77]Wilby, R.L., I. Harris. A framework for assessing uncertainties in climate change impacts:low-flow scenarios for the River Thames, UK [J]. Water Resour Res,2006(42/W02419).
[78]Horton, P., B. Schaefli, A. Mezghani, B. Hingray, A. Musy. Assessment of climate change impacts on alpine discharge regimes with climate model uncertainty [J]. Hydrol Process,2006.20(10): 2091-2109.
[79]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：中国水利水电科学出版社,2005.
[80]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.
[81]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.
[82]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[A].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.
[83]Conway D.Understanding the Hydrological Impacts of Land-cover and Land-use Change[C].IHDP Update,2001,(1):5-6.
[84]陈军锋,陈秀万. SWAT模型的水量平衡及其在梭磨河流域的应用[J].北京大学学报,2004,40(2)：265-270.
[85]Crokea B F W,W S Merrittc.A J Jakemana.A dynamic model for predicting hydrologic response to land cover changes in gauged and ungauged catchments[J] Journal of Hydrology,2004, (291): 115-131.]
[86]Leavesley G H, S L arkstrom, P J Restrepo, et al. A modular approach to addressing model design, scale,and parameter estimation issues in distributed hydrological modeling [J].Hydrological Processes,2002, (16):173-187.
[87]李丽娟,姜德娟,李九一,粱丽乔,张丽.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(3)：211-224.
[88]初京刚.基于多源信息的分布式水文模拟及优化算法应用研究[D].大连：大连理工大学,2012.
[89]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.
[90]Li K Y, Coe M T, Ramankutty N, et al. Modeling the hydrological impact of land-use change in West Africa [J]. Journal of Hydrology,2007,337:258-268.
[91]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)：14-18.
[92]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.
[93]曹明亮.基于多源信息分析人类活动对径流及洪水预报的影响[D].大连：大连理工大学,2011.
[94]Marshall, E., and T. O. Randhir (2008), Spatial modeling of land cover change and watershed response using Markovian cellular automata and simulation, Water Resources Research,44, W04423, doi:10.1029/2006WR005514.
[95]Thanapakpawin, P., J. Richey, D. Thomas, S. Rodda, B. Campbell, and M. Logsdon (2006), Effects of landuse change on the hydrologic regime of the Mae Chaem river basin, NW Thailand, Journal of Hydrology,334,215-230, doi:10.1016/j.jhydrol.2006.10.012.
[96]Gtintner, A., M. S. Krol, J. C. De Araujo, and A. Bronstert (2004), Simple water balance modelling of surface reservoir systems in a large data-scarce semiarid region, Hydrological Sciences Journal, 49,901-918.
[97]Winchell, M., Srinivasan, R., DiLuzio, M., Arnold, J.,2008. ArcSWAT 2.1 interface for SWAT2005, user's guide.
[98]Cong ZhenTao; Yang DaWen; Gao Bing; Yang HanBo; Hu HePing.2009. Hydrological trend analysis in the Yellow River basin using a distributed hydrological model. Water Resources Research, VOL.45, W00A13.
[99]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)：158-162.
[100]张建敏,黄朝迎,吴金栋.气候变化对三峡水库运行风险的影响[J].地理学报,2000,55supplement,26-33.
[101]颜亦琪.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.
[102]Li, L.H., H. Xu, X. Chen, S.P. Simonovic. Streamflow forecast and reservoir operation performance assessment under climate change [J]. Water Resour Manage,2009(24):83-104.
[103]Slobodan P. Simonovic and Lanhai Li. Methodology for Assessment of Climate Change Impacts on Large-Scale Flood Protection System [J]. Journal of Water Resources Planning and Management, 2003,129:361-371.
[104]O'Hara, J.K. and Georgakakos, K.P.,2008. Quantifying the urban water supply impacts of climate change [J]. Water Resources Management,22(10):1477-97.
[105]Lopez, A., F. Fung, M. New, G. Watts, A. Weston, R.L. Wilby. From climate model ensembles to climate change impacts and adaptation:a case study of water resource management in the southwest of England [J]. Water Resour Res,2009(45/W08419).
[106]Raje, D., P.P. Mujumdar. Reservoir performance under uncertainty in hydrologic impacts of climate change [J]. Advances in Water Resources,2010(33):312-326.
[107]大连市水务局,大连理工大学,等.气候变化和人类活动对大连市水资源的影响研究[R].大连：大连理工大学,2010.
[108]李志栋,朱庆.数字高程模型[M].武汉：武汉测绘大学出版社,2000.
[109]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.
[110]王果.土壤学[M].北京：高等教育出版社,2009.
[111]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].中国科学院南京土壤研究所,南京,2003.
[112]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,2003.31(3)：104-106.
[113]张甘霖,龚子同,骆国宝,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.
[114]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(7)：82-86.
[115]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.
[116]张甘霖,史学正,龚子同,等.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.
[117]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].In：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,2004：792-801.
[118]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.
[119]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：增刊,2006：74-76.
[120]商瑶玲,王东华,吉建培,等.国家1：25万地形数据库的建立与应用[J].测绘通报,2001(10)：29-31.
[121]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,2009(9)：44-47.
[122]Birsana, M.V., P. Molnar, P. Burlando, M. Pfaundler. Streamflow trends in Switzerland [J]. Journal of Hydrology,2005(314):312-329.
[123]Chen, H., S.L. Guo, C.Y. Xu, V.P. Singh. Historical temporal trends of hydro-climatic variablesand runoff response to climate variability and their relevance in water resource management in the Hanjiang basin [J]. Journal of Hydrology,2007(344):171-184.
[124]曹明亮,张弛,周惠成,李慧赞.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)：87-89.
[125]Margaret A. Matter, Luis A. Garcia, Darrell G. Fontane, Brian Bledsoe. Characterizing hydroclimatic variability in tributaries of the Upper Colorado River Basin—WY1911-2001. Journal of Hydrology,2010,380:260-276.
[126]丁晶,邓育仁.随机水文学[M].成都：成都科技大学出版社,1988.260-276.
[127]蔡其华.充分考虑河流生态系统保护因素完善水库调度方式[J].中国水利,2006,(2)：19-22.
[128]张丽丽.南水北调中线生态补水调度技术研究[D].南京：河海大学,2010.
[129]殷峻暹,张丽丽,蒋云钟等.多维生态调控理论与实践——以长江流域为例[M].北京：中国水利水电出版社,2011.
[130]Shiau, J. T. and Wu, F. C. (2006). Compromise programming methodology for determining instream flow under multiobjective water allocation criteria. Journal of the American Water Resources Association,42(5),1179-1191.
[131]Tilmant, A., Beevers, L., and Muyunda, B. (2010). Restoring a flow regime through the coordinated operation of a multireservoir system:The case of the Zambezi River basin. Water Resource Research, VOL.46, W07533. doi:10.1029/2009WR008897.
[132]Yin, X. A., Yang, Z. F., Yang, W., Zhao, Y. W. and Chen, H. (2010). Optimized reservoir operation to balance human and riverine ecosystem needs:model development, and a case study for the Tanghe reservoir, Tang river basin, China. Hydrol. Process,24,461-471. doi:10.1002/hyp.7498.
[133]Yin, X. A. and Yang, Z. F. (2011). Development of a coupled reservoir operation and water diversion model:Balancing human and environmental flow requirements. Ecological Modelling,222, 224-231. doi:10.1016/j.ecolmodel.2010.06.025.
[134]Lund, J. R., and Reed, R. U.,1995 Drought water rationing and transferable rations. J. Water Resour. Plann. Manage.,121(6),429-437
[135]Tu, M. Y., M., Hsu, N. S., Tsai, F. T. C., and Yeh, W. W. G.,2008. Optimization of Hedging Rules for Reservoir Operations. Journal of Water Resources Planning and Management,134 (1):3-13.
[136]Tennant, D. L. Instream flow regimes for fish, wildlife, recreation and related environmental resources [J]. Fisheries,1976.1(4):6-10.
[137]谢涛,陈火旺.多目标优化与决策问题的演化算法[J].中国工程科学,2002,4(2)：59-68.
[138]王小平,曹立明.遗传算法一理论、应用与软件实现[M].西安：西安交通大学出版社,2002.
[139]刘莎.跨流域引水后受水水库优化调度图研究[D].大连：大连理工大学,2013.
[140]徐志侠,董增川,周健康,苏飞.生态需水计算的蒙大拿法及共应用[J].水利水电技术,2003,34(1)：15-17.
[141]Zhang, C., Christine A. Shoemaker, et al.2012. Impact of human activities on stream flow in the Biliu River basin, China. Hydrological Processes,27(17):2509-2523. doi:10.1002/hyp.9389.
[142]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,2010,29(7)：827-832.
[143]祝雪萍,仕玉治,张丹.SWAT模型在东北典型流域的应用研究.中国水利学会水资源专业委员会2009学术年会论文集,2009：176-182.
[144]Neitseh S L, Amold J G, Kiniry J R, et al. Soil and Water Assessment Tool:Theoretical Documentation, version2005 (available at http://www.brc.tamus.edu/swat/.
[145]Neitsch S L, Arnold J G, Kiniry J R, et al. Soil and water assessment tool input/output file documentation, version 2005. http://swatmodel.tamu.edu/media/1291/swat 2005io.pdf.
[146]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.
[147]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.
[148]Morris, M.D. Factorial sampling plans for preliminary computational experiments [J]. Technometrics, 1991.33(2):161-174.
[149]郝芳华,程红光,杨胜天.非点源污染模型一理论方法与应用[M].北京：中国环境科学出版社,2006.
[150]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.
[151]郭彦,董文杰,任福民,赵宗慈,黄建斌CMIP5模式对中国年平均气温模拟及其与CMIP3模式的比较[J].气候变化研究进展,2013,9(3)：181-186.
[152]姜燕敏,吴昊旻.20个CMIP5模式对中亚地区年平均气温模拟能力评估[J].气候变化研究进展,2013,9(2)：110-116.
[153]New M G, Hulme M, Jones P D. Representing twentieth-century spacetime climate variability. Part I: development of a 1961-1990 mean monthly terrestrial climatology [J]. Journal of Climate,1999,12: 829-856.
[154]辛晓歌,吴统文,张洁BCC气候系统模式开展的CMIP5试验介绍[J].气候变化研究进展,2012,8(5)：378-382.
[155]姜燕敏,吴昊旻.20个CMIP5模式对中亚地区年平均气温模拟能力评估[J].气候变化研究进展,2013,9(2)：110-116.
[156]陈敏鹏,林而达.代表性浓度路径情景下的全球温室气体减排和对中国的挑战[J].气候变化研究进展,2010,6(6)：436-442.
[157]Belcher, SE, JN Hacker and DS Powell. Constructing design weather data for future climates [J]. Building Services Engineering Research and Technology,2005,26(1):49-61.
[158]Milzow, C., V. Burg, and W. Kinzelbach (2010), Estimating future ecoregion distributions within the Okavango Delta Wetlands based on hydrological simulations and future climate and development scenarios, Journal of Hydrology,381,89-100, doi:10.1016/j.jhydrol.2009.11.028.
[159]Takagi, T., and M. Sufeno (1985), Fuzzy identification of systems and its application to modeling and control, IEEE Transactions on Systems, Man and Cybernetics,15 (1):116-132.
[160]张弛,周惠成,李伟.基于模糊推理和关联规则分析的河道洪水预报模型[J].大连理工大学学报,2008,48(2)：263-269.
[161]Jacquin, A. P., and A. Y. Shamseldin (2006), Development of rainfall-runoff models using Takagi-Sugeno fuzzy inference systems, Journal of Hydrology,329,154-173, doi:10.1016/j jhydrol.2006.02.009.
[2]彭勇.中长期水文预报与水库群优化调度方法及其系统集成研究[D].大连：大连理工大学,2007.
[3]IPCC. Climate Change 2007:Synthesis Report [M], Geneva, Switzerland,2007.
[4]《气候变化国家评估报告》编写委员会.气候变化国家评估报告[M].北京：科学出版社,2007.
[5]贾仰文,王浩,彭辉.水文学及水资源学科发展动态[J].中国水利水电科学研究院学报,2009.7(2)：241-248.
[6]Muller, M. Interbasin water sharing:a South African perspective [C]. In:International Hydrological Program-V. UNESCO. Paris:Proceedings of the International Workshop,1999:61-70.
[7]Azevedo, L.G.T., L.L.R. Porto, A.V. Mello, J.G. Pereira, D.L.P. Arrobas, L.C. Noronha, et al. Transferencia de agua entre bacias hidrograficas [M]. Serie Agua Brasil. Vol.7. Brasilia 2005.
[8]Ma, J., A.Y. Hoekstra, H. Wang, A.K. Chapagain, D.X. Wang. Virtual versus real water transfers within China [J]. Philosophical Transactions of the Royal Society,2006(361):835-842.
[9]Chang, J.X., J. Jiang. Water Dispatch of the South-to-North Water Transfer Project in Shaanxi Province [J]. JOURNAL OF NATURAL RESOURCES,2011.26(1):110-118.
[10]Dyrnes, G.V., A. Vatn. Who owns the water? A study of a water conflict in the Valley of Ixtlahuaca, Mexico [J]. Water Policy,2005.7(3):295-312.
[11]郑连第.中国历史上的跨流域调水工程[J].南水北调与水利科技,2003.1(1)：5-8.
[12]关志诚.跨流域调水工程的关键技术与建设实践[J].水利水电技术,2009(08)：89-94.
[13]李运辉,陈献耘,沈艳忱.巴基斯坦西水东调工程[J].水利发展研究,2003.3(1)：56-58.
[14]沈佩君,邵东国,郭元裕.国内外跨流调水工程建设的现状与前景[J].武汉水利电力大学学报,1995.28(5)：463-469.
[15]杨立信.澳大利亚雪山工程上游段建筑物的布置特点[J].水利发展研究,2002.2(7)：46-48.
[16]Weiner, D., B.Z. Arie. A stochastic dynamic programing model for the operation of the Mediterranean-Dead Sea Project [J]. Water Resources Research,1982.18(4):729-734.
[17]Li, S. X. Research on Operation Decision-Making and Management Pattern in Inter-Basin Water Teansfer System [D]. Dalian:Dalian University of Technology,2009.
[18]Jain, S.K., N.S.R.K. Reddy, U.C. Chaube. Analysis of a large inter-basin water transfer system in India [J]. Hydrological Sciences Journal,2005.50(1):125-137.
[19]Gupta, J., P.v.d. Zaag. Interbasin water transfers and integrated water resources anagement:Where engineering, science and politics interlock [J]. Physics and Chemistry of the Earth,2008(33):28-40.
[20]Sadegh, M., N. Mahjouri, R. Kerachian. Optimal Inter-Basin Water Allocation Using Crisp and Fuzzy Shapley Games [J]. Water Resources Management,2010(24):2291-2310.
[21]阮本清,王浩.西线调水区水资源分析及可调水量商榷[J].清华大学学报(自然科学版),2000.40(S1)：101-106.
[22]耿万东.丹江口水库可调出水量研究[D].郑州：郑州大学,2007.
[23]张玫,张玮.南水北调西线工程可调水量分析中几个主要问题的探讨[J].水文,2002.22(4)： 32-36.
[24]尹宏伟,李勇,郑垂勇.跨流域调水工程受水区水资源优化配置的模型[J].统计与决策,2007(23)：38-41.
[25]王浩,秦大庸,王建华,罗琳,裴源生.黄淮海流域水资源合理配置[M].北京：科学出版社,2003.
[26]赵勇,解建仓,马斌.基于系统仿真理论的南水北调东线水量调度[J].水利学报,2002.31(11)：38-43.
[27]王劲峰,刘昌明,于静洁,陈红焱.区际调水时空优化配置理论模型探讨[J].水利学报,2001.30(4)：7-15.
[28]游进军,王忠静,甘泓,张建中.两阶段补偿式跨流域调水配置算法及应用[J].水利学报,2008.39(7)：870-876.
[29]黄薇,陈进.跨流域调水水权分配与水市场运行机制初步探讨[J].长江科学院院报,2006.23(1)：50-52.
[30]李萍,徐明.关于调水工程水权问题的研究[J].水利经济,2002.20(2)：28-31.
[31]刘斌,朱尔明.试论南水北调工程与水权制度[J].中国水利,2002(1)：47-48.
[32]刘洪先.水权理论与南水北调工程水权分配[J].人民黄河,2002.24(3)：15-17.
[33]游进军,王忠静,甘泓,蒋云钟.国内跨流域调水配置方法研究现状与展望[J].南水北调与水利科技,2008.6(3)：1-4+8.
[34]郑通汉,任宪韶.水利工程供水两部制水价制度研究[M].北京：中国水利水电出版社,2006.
[35]张军,王华,董温荣,张永平.南水北调供水两部制水价模式探讨[J].水利经济,2006.24(3)：34-35.
[36]王国利,彭勇,何.斌,梁国华.GFS降雨预报在大伙房水库实时跨流域调水决策的应用研究[J].水资源与水工程学报,2010.21(2)：1-4.
[37]卢华友,沈佩君,邵东国,魏山忠,文丹,吴泽宇,et a1.跨流域调水工程实时优化调度模型研究[J].武汉水利电力大学学报,1997.30(5)：11-15.
[38]梁国华,王国利,王本德,董霞.大伙房跨流域引水工程预报调度方式研究[J].水力发电学报,2009.28(3)：32-36+46.
[39]习树峰,彭勇,梁国华,王本德,等.基于决策树方法的水库跨流域引水调度规则研究[J].大连理工大学学报,2012,52(1)：74-78.
[40]汪明娜,汪达.调水工程对环境利弊影响综合分析[J].水资源保护,2002(4)：10-14.
[41]Hirji, R. Inter-basin water transfers -emerging trends [R]. The World Bank, Washington, DC,1998.
[42]李善同,许新宜.南水北调与中国发展[M].北京：经济科学出版社,2004.
[43]郭潇,方国华,张哲恺.跨流域调水生态环境影响评价指标体系研究[J].水利学报,2008.39(9)：1125-1130.
[44]Petitjean, M.O.G., B.R. Davies. Ecological impacts of inter-basin water transfers:some case studies, research requirements and assessment procedures in Southern Africa [J]. South African Journal of Science,1988.84(10):819-828.
[45]Matete, M., R. Hassan. An ecological economics framework for assessing environmental flows:the case of inter-basin water transfers in Lesotho [J]. Global and Planetary Change,2005.47(2/4): 193-200.
[46]Li, Y., P. He, W. Xiao, B. Liu. The Research of Water Environment Cumulative Impacts of Delivery Canal on East Route of South-to-North Water Transfer Project [J]. Procedia Engineering,2012.28: 287-291.
[47]窦明,左其亭,胡彩虹.南水北调工程的生态环境影响评价研究[J].郑州大学学报(工学版),2005.26(2)：63-66.
[48]刘进琪.大通河跨流域调水对生态环境的影响[J].甘肃科学学报,2006.18(1)：49-52.
[49]史淑娟,李怀恩,林启才,党志良.跨流域调水生态补偿量分担方法研究[J].水利学报,2009.40(3)：268-273.
[50]习树峰.跨流域调水预报优化调度方法及应用研究[D].大连：大连理工大学,2011.
[51]郭生练,陈炯宏,刘攀,李雨.水库群联合优化调度研究进展与展望[J].水科学进展,2010.21(4)：496-503.
[52]胡铁松,万永华,冯尚友.水库群优化调度函数的人工神经网络方法研究[J].水科学进展,1995.6(1)：53-60.
[53]Srinivas, N. and Deb K. Multiobjective function Optimization using nondominated sorting genetic algorithms [J]. Evolutionary Computation,1995.2(3):221-248.
[54]Deb, K., Agrawal S., Pratpa A., e. al. A fast elitist nondominated sorting genetic algorithms for multi-objective optimization:NSG-II [C]. In:Proc of the Parallel Problem Solving from Nature VI Conf. Paris,2000:849-858.
[55]Suen, J.P., J.W. Eheart. Reservoir management to balance ecosystem and human needs: Incorporating the paradigm of the ecological flow regime [J]. Water Resource Research,2006. 42(W03417).
[56]张志刚,马光文.基于NSGA-Ⅱ算法的多目标水火电站群优化调度模型研究[J].水力发电学报,2010.29(1)：213-218.
[57]贠汝安,董增川,王好芳.基于NSGA2的水库多目标优化[J].山东大学学报(工学版),2010.40(6)：124-128.
[58]陈守煜.可变集一可变模糊集的发展及其在水资源系统中的应用[J].数学的实践与认识,2012(1)：92-101.
[59]Zadeh L A. Fuzzy sets [J]. Information and control,1965,8 (3):338-353.
[60]陈守煜.水资源系统可变集评价原理与方法[J].水利学报,2013,4(2)：134-142.
[61]Barnett, T.P., J.C. Adam, D.P. Lettenmaier. Potential impacts of a warming climate on water availability in snow-dominated regions [J]. Nature,2005(438):303-309.
[62]Frederick, K.D., P.H. Gleick. Water and global climate change:Potential impacts on U.S. water resources [R], Arlington, Virginia,1999.48.
[63]IPCC. Climate Chnage and Impact 1990 [M]. Cambridge:Cambridge Univesity Perss,1990.
[64]IPCC. Climate Chnage 1995. Impact, Adaptation, and Mitigation [M]. Cambridge:Cambridge Univesity Perss,1995.
[65]IPCC. Climate Chnage 2001.Impacts, adaptation, vulnerability [M]. Cambridge:Cambridge Univesity Perss,2001.
[66]英爱文,姜广斌.辽河流域水资源对气候变化的响应[J].水科学进展,增刊,1996.7：68-72.
[67]贾仰文,高辉,牛存稳,等.气候变化对黄河源区径流过程的影响[J].水利学报,2008.39(1)：52-58.
[68]Gleick, P.H. The development and testing of a water balance model for climate impact assessment: modeling the Sacramento basin [J]. Water Resources Research,1987.23(7):1049-1061.
[69]Christensen, N.S., A.W. Wood, N. Voisin, etal. The effects of climate change on the hydrology and water resources of the Colorado River basin [J]. Climatic Change,2004.62(1-3):337-363.
[70]袁飞,谢正辉,任立良,黄琼.气候变化对海河流域水文特性的影响[J].水利学报,2005.36(3)：274-279.
[71]Gleick, P.H. Climate change, hydrology, and water resources [J]. Reviews of geophysics,1989. 27(3):329-344.
[72]Xu, C.Y. Climate change and hydrologic models:A review of existing gaps and recent research developments [J]. Water Resources Management,1999.13(5):369-382.
[73]张建云,王国庆等.气候变化对水文水资源影响研究[M].2007,北京：科学出版社.
[74]Lettenmaier, D.P., T.Y. Gan. Hydrologic sensitivity of the Sacramento-San Jaoquin river basin, California, to global warming [J]. Water Resources Research,1990(26):69-86.
[75]Chiew, F.H.S., J. Vaze, N.R. Viney, J.M. Perraud, J. Teng, P.W. Jordan, et al. Estimation of runoff and the impact of climate change and development on runoff across the Murray-Darling Basin [C]. In:Proceedings of the Water Down Under 2008. Adelaide, Australia,2008:1957-1968.
[76]Prudhomme, C., D. Jakob, C. Svensson. Uncertainty and climate change impact on the flood regime of small UK catchments [J]. J Hydrol,2003(277):1-23.
[77]Wilby, R.L., I. Harris. A framework for assessing uncertainties in climate change impacts:low-flow scenarios for the River Thames, UK [J]. Water Resour Res,2006(42/W02419).
[78]Horton, P., B. Schaefli, A. Mezghani, B. Hingray, A. Musy. Assessment of climate change impacts on alpine discharge regimes with climate model uncertainty [J]. Hydrol Process,2006.20(10): 2091-2109.
[79]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：中国水利水电科学出版社,2005.
[80]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.
[81]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.
[82]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[A].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.
[83]Conway D.Understanding the Hydrological Impacts of Land-cover and Land-use Change[C].IHDP Update,2001,(1):5-6.
[84]陈军锋,陈秀万. SWAT模型的水量平衡及其在梭磨河流域的应用[J].北京大学学报,2004,40(2)：265-270.
[85]Crokea B F W,W S Merrittc.A J Jakemana.A dynamic model for predicting hydrologic response to land cover changes in gauged and ungauged catchments[J] Journal of Hydrology,2004, (291): 115-131.]
[86]Leavesley G H, S L arkstrom, P J Restrepo, et al. A modular approach to addressing model design, scale,and parameter estimation issues in distributed hydrological modeling [J].Hydrological Processes,2002, (16):173-187.
[87]李丽娟,姜德娟,李九一,粱丽乔,张丽.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(3)：211-224.
[88]初京刚.基于多源信息的分布式水文模拟及优化算法应用研究[D].大连：大连理工大学,2012.
[89]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.
[90]Li K Y, Coe M T, Ramankutty N, et al. Modeling the hydrological impact of land-use change in West Africa [J]. Journal of Hydrology,2007,337:258-268.
[91]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)：14-18.
[92]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.
[93]曹明亮.基于多源信息分析人类活动对径流及洪水预报的影响[D].大连：大连理工大学,2011.
[94]Marshall, E., and T. O. Randhir (2008), Spatial modeling of land cover change and watershed response using Markovian cellular automata and simulation, Water Resources Research,44, W04423, doi:10.1029/2006WR005514.
[95]Thanapakpawin, P., J. Richey, D. Thomas, S. Rodda, B. Campbell, and M. Logsdon (2006), Effects of landuse change on the hydrologic regime of the Mae Chaem river basin, NW Thailand, Journal of Hydrology,334,215-230, doi:10.1016/j.jhydrol.2006.10.012.
[96]Gtintner, A., M. S. Krol, J. C. De Araujo, and A. Bronstert (2004), Simple water balance modelling of surface reservoir systems in a large data-scarce semiarid region, Hydrological Sciences Journal, 49,901-918.
[97]Winchell, M., Srinivasan, R., DiLuzio, M., Arnold, J.,2008. ArcSWAT 2.1 interface for SWAT2005, user's guide.
[98]Cong ZhenTao; Yang DaWen; Gao Bing; Yang HanBo; Hu HePing.2009. Hydrological trend analysis in the Yellow River basin using a distributed hydrological model. Water Resources Research, VOL.45, W00A13.
[99]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)：158-162.
[100]张建敏,黄朝迎,吴金栋.气候变化对三峡水库运行风险的影响[J].地理学报,2000,55supplement,26-33.
[101]颜亦琪.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.
[102]Li, L.H., H. Xu, X. Chen, S.P. Simonovic. Streamflow forecast and reservoir operation performance assessment under climate change [J]. Water Resour Manage,2009(24):83-104.
[103]Slobodan P. Simonovic and Lanhai Li. Methodology for Assessment of Climate Change Impacts on Large-Scale Flood Protection System [J]. Journal of Water Resources Planning and Management, 2003,129:361-371.
[104]O'Hara, J.K. and Georgakakos, K.P.,2008. Quantifying the urban water supply impacts of climate change [J]. Water Resources Management,22(10):1477-97.
[105]Lopez, A., F. Fung, M. New, G. Watts, A. Weston, R.L. Wilby. From climate model ensembles to climate change impacts and adaptation:a case study of water resource management in the southwest of England [J]. Water Resour Res,2009(45/W08419).
[106]Raje, D., P.P. Mujumdar. Reservoir performance under uncertainty in hydrologic impacts of climate change [J]. Advances in Water Resources,2010(33):312-326.
[107]大连市水务局,大连理工大学,等.气候变化和人类活动对大连市水资源的影响研究[R].大连：大连理工大学,2010.
[108]李志栋,朱庆.数字高程模型[M].武汉：武汉测绘大学出版社,2000.
[109]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.
[110]王果.土壤学[M].北京：高等教育出版社,2009.
[111]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].中国科学院南京土壤研究所,南京,2003.
[112]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,2003.31(3)：104-106.
[113]张甘霖,龚子同,骆国宝,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.
[114]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(7)：82-86.
[115]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.
[116]张甘霖,史学正,龚子同,等.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.
[117]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].In：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,2004：792-801.
[118]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.
[119]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：增刊,2006：74-76.
[120]商瑶玲,王东华,吉建培,等.国家1：25万地形数据库的建立与应用[J].测绘通报,2001(10)：29-31.
[121]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,2009(9)：44-47.
[122]Birsana, M.V., P. Molnar, P. Burlando, M. Pfaundler. Streamflow trends in Switzerland [J]. Journal of Hydrology,2005(314):312-329.
[123]Chen, H., S.L. Guo, C.Y. Xu, V.P. Singh. Historical temporal trends of hydro-climatic variablesand runoff response to climate variability and their relevance in water resource management in the Hanjiang basin [J]. Journal of Hydrology,2007(344):171-184.
[124]曹明亮,张弛,周惠成,李慧赞.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)：87-89.
[125]Margaret A. Matter, Luis A. Garcia, Darrell G. Fontane, Brian Bledsoe. Characterizing hydroclimatic variability in tributaries of the Upper Colorado River Basin—WY1911-2001. Journal of Hydrology,2010,380:260-276.
[126]丁晶,邓育仁.随机水文学[M].成都：成都科技大学出版社,1988.260-276.
[127]蔡其华.充分考虑河流生态系统保护因素完善水库调度方式[J].中国水利,2006,(2)：19-22.
[128]张丽丽.南水北调中线生态补水调度技术研究[D].南京：河海大学,2010.
[129]殷峻暹,张丽丽,蒋云钟等.多维生态调控理论与实践——以长江流域为例[M].北京：中国水利水电出版社,2011.
[130]Shiau, J. T. and Wu, F. C. (2006). Compromise programming methodology for determining instream flow under multiobjective water allocation criteria. Journal of the American Water Resources Association,42(5),1179-1191.
[131]Tilmant, A., Beevers, L., and Muyunda, B. (2010). Restoring a flow regime through the coordinated operation of a multireservoir system:The case of the Zambezi River basin. Water Resource Research, VOL.46, W07533. doi:10.1029/2009WR008897.
[132]Yin, X. A., Yang, Z. F., Yang, W., Zhao, Y. W. and Chen, H. (2010). Optimized reservoir operation to balance human and riverine ecosystem needs:model development, and a case study for the Tanghe reservoir, Tang river basin, China. Hydrol. Process,24,461-471. doi:10.1002/hyp.7498.
[133]Yin, X. A. and Yang, Z. F. (2011). Development of a coupled reservoir operation and water diversion model:Balancing human and environmental flow requirements. Ecological Modelling,222, 224-231. doi:10.1016/j.ecolmodel.2010.06.025.
[134]Lund, J. R., and Reed, R. U.,1995 Drought water rationing and transferable rations. J. Water Resour. Plann. Manage.,121(6),429-437
[135]Tu, M. Y., M., Hsu, N. S., Tsai, F. T. C., and Yeh, W. W. G.,2008. Optimization of Hedging Rules for Reservoir Operations. Journal of Water Resources Planning and Management,134 (1):3-13.
[136]Tennant, D. L. Instream flow regimes for fish, wildlife, recreation and related environmental resources [J]. Fisheries,1976.1(4):6-10.
[137]谢涛,陈火旺.多目标优化与决策问题的演化算法[J].中国工程科学,2002,4(2)：59-68.
[138]王小平,曹立明.遗传算法一理论、应用与软件实现[M].西安：西安交通大学出版社,2002.
[139]刘莎.跨流域引水后受水水库优化调度图研究[D].大连：大连理工大学,2013.
[140]徐志侠,董增川,周健康,苏飞.生态需水计算的蒙大拿法及共应用[J].水利水电技术,2003,34(1)：15-17.
[141]Zhang, C., Christine A. Shoemaker, et al.2012. Impact of human activities on stream flow in the Biliu River basin, China. Hydrological Processes,27(17):2509-2523. doi:10.1002/hyp.9389.
[142]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,2010,29(7)：827-832.
[143]祝雪萍,仕玉治,张丹.SWAT模型在东北典型流域的应用研究.中国水利学会水资源专业委员会2009学术年会论文集,2009：176-182.
[144]Neitseh S L, Amold J G, Kiniry J R, et al. Soil and Water Assessment Tool:Theoretical Documentation, version2005 (available at http://www.brc.tamus.edu/swat/.
[145]Neitsch S L, Arnold J G, Kiniry J R, et al. Soil and water assessment tool input/output file documentation, version 2005. http://swatmodel.tamu.edu/media/1291/swat 2005io.pdf.
[146]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.
[147]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.
[148]Morris, M.D. Factorial sampling plans for preliminary computational experiments [J]. Technometrics, 1991.33(2):161-174.
[149]郝芳华,程红光,杨胜天.非点源污染模型一理论方法与应用[M].北京：中国环境科学出版社,2006.
[150]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.
[151]郭彦,董文杰,任福民,赵宗慈,黄建斌CMIP5模式对中国年平均气温模拟及其与CMIP3模式的比较[J].气候变化研究进展,2013,9(3)：181-186.
[152]姜燕敏,吴昊旻.20个CMIP5模式对中亚地区年平均气温模拟能力评估[J].气候变化研究进展,2013,9(2)：110-116.
[153]New M G, Hulme M, Jones P D. Representing twentieth-century spacetime climate variability. Part I: development of a 1961-1990 mean monthly terrestrial climatology [J]. Journal of Climate,1999,12: 829-856.
[154]辛晓歌,吴统文,张洁BCC气候系统模式开展的CMIP5试验介绍[J].气候变化研究进展,2012,8(5)：378-382.
[155]姜燕敏,吴昊旻.20个CMIP5模式对中亚地区年平均气温模拟能力评估[J].气候变化研究进展,2013,9(2)：110-116.
[156]陈敏鹏,林而达.代表性浓度路径情景下的全球温室气体减排和对中国的挑战[J].气候变化研究进展,2010,6(6)：436-442.
[157]Belcher, SE, JN Hacker and DS Powell. Constructing design weather data for future climates [J]. Building Services Engineering Research and Technology,2005,26(1):49-61.
[158]Milzow, C., V. Burg, and W. Kinzelbach (2010), Estimating future ecoregion distributions within the Okavango Delta Wetlands based on hydrological simulations and future climate and development scenarios, Journal of Hydrology,381,89-100, doi:10.1016/j.jhydrol.2009.11.028.
[159]Takagi, T., and M. Sufeno (1985), Fuzzy identification of systems and its application to modeling and control, IEEE Transactions on Systems, Man and Cybernetics,15 (1):116-132.
[160]张弛,周惠成,李伟.基于模糊推理和关联规则分析的河道洪水预报模型[J].大连理工大学学报,2008,48(2)：263-269.
[161]Jacquin, A. P., and A. Y. Shamseldin (2006), Development of rainfall-runoff models using Takagi-Sugeno fuzzy inference systems, Journal of Hydrology,329,154-173, doi:10.1016/j jhydrol.2006.02.009.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |