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Joint Sino-German-Project: Impacts of Land Use and Management Practices on Water Resources under Climate Change in the Haihe River Basin, China

Joint Sino-German-Project: Impacts of Land Use and Management Practices on Water Resources under Climate Change in the Haihe River Basin, China
中德联合项目:中国海河流域气候变化下土地利用和管理实践对水资源的影响
批准号:
188417135
负责人:
Professor Dr. Hans-Georg Frede
金额:
$0.0万
依托单位:
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
2010
资助国家:
德国
项目状态:
已结题
起止时间:
2009-12-31 至 2014-12-31

项目摘要

项目成果

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中文摘要
翻译
了解气候变化和土地利用变化对水文-生物地球化学循环和水资源时空格局的影响对海河流域等高度发达流域具有重要意义。为了抵消这些对水循环和水资源的影响,在区域土地利用中实施最佳管理实践(BMPs)和政策方法至关重要。该联合提案的目标是:1)估计气候变化和土地利用变化(包括其不确定性)对海河流域水循环和水资源的影响;2)为决策者提供BMP和政策方法的建议。我们将收集现有的气象和水文数据,并检讨目前的土地使用管理做法和政策方针。将以高空间和时间分辨率收集额外的水质数据。我们将建立和校准一个集成的模型集成框架,该框架由6个不同复杂程度的水文模型(CMF、WetSpa、SWIM/SWAT、HBV-N-D、INCA和LASCAM)组成,能够预测水量和水质。观察到的水质和其他软数据将用于后验拒绝框架,以改进过程理解和模型结构。将估计所有模式的随机和结构不确定性,以提供预估全球变化影响的可靠范围。我们将开发和分析在当前和气候变化条件下土地利用变化情景和最佳管理实践及其对水-生物地球化学循环的影响。我们将采用综合方法,将所有模型应用于不同的变化情景,以预测和评估集水区水资源的潜在变化。最后,将根据情景评估和不确定性分析的结果,为该区域提出适当的土地利用管理做法和政策办法的建议。
英文摘要
Understanding the impacts of climate change and land use change on the spatio-temporal patterns of the hydro-biogeochemical cycle and water resources is of major importance in highly developed watersheds such as the Haihe River basin. Implementation of Best Management Practices (BMPs) and Policy Approaches in regional land use is essential in order to counteract these impacts on hydrological cycle and water resources. The goals of this joint proposal are 1) to provide estimates of the behaviour of the hydrological cycle and water resources due to climate change and land use change including their uncertainties, and 2) to provide recommendations on BMP and policy approaches in the Haihe River basin for policy makers. We will collect existing meteorological and hydrological data and review current land use management practices and policy approaches. Additional water quality data will be collected in high spatial and temporal resolution. We will setup and calibrate an integrated model ensemble framework that consists of 6 hydrological models of different complexity (CMF, WetSpa, SWIM/SWAT, HBV-N-D, INCA, and LASCAM) which are able to predict water quantity and quality. Observed water quality and other soft data will be used in an a posteriori rejectionist framework to improve process understanding and model structure. Stochastic and structural uncertainty of all models will be estimated to provide reliable ranges of projected global change impact. We will develop and analyze land use change scenarios and Best Management Practices and their impacts on the hydro-biogeochemical cycle under current and climate change conditions. In an integrated approach, we will apply all models to the different change scenarios in order to project and evaluate potential changes of water resources in the catchment area. Finally, recommendations of appropriate land use management practices and policy approaches for the region will be made based on the results of scenario assessments and uncertainty analysis.
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会议论文
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