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Evaluating the contribution of the climate change and human activities to runoff change under uncertainty

机译:评估气候变化和人类活动在不确定性下对径流变化的贡献

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Climate change and human activities are two important factors affecting surface runoff. In water resource planning and management, it is usually important to separate the contribution of the mentioned factors to the runoff change. In this paper, a new methodology is proposed to obtain the relative impact of human activities and climate change on streamflow under uncertainty. In this methodology, the breakpoint of the annual time series of the observed runoff is estimated and the time series is divided into two study periods; before and after the breakpoint, namely the "natural" and "impacted" periods. The Jazim monthly water balance model is used for monthly runoff simulation. To incorporate the effect of snow in simulating runoff, two Jazim-based monthly water balance models with Rao and Al Wagdany (1995) and McCabe and Markstrom (2007) snow modules are used. Then, the monthly water balance models are calibrated and verified for the natural and impacted periods. The main parameters of the water balance models are optimized using the Genetic Algorithms. The uncertainty of the parameters of the models is analyzed using differential evolution adaptive Metropolis (DREAM) algorithm, which is based on the Markov Chain Monte Carlo (MCMC) algorithm. This algorithm provides the posterior probability distribution functions (PDFs) of parameters of the runoff simulation models. Next, the PDFs of the contribution rate (CR) of the climate change and human activities to runoff are determined using the fixing changing method by taking into account the PDFs of the models' parameters. To show the applicability and efficiency of the proposed methodology, it is applied to the Zayandehrud sub-basin in Iran. Using the Standard Normal Homogeneity Test (SNHT), Pettitt and Buishand range tests, one breakpoint at 2006 is detected in runoff time series. Through the monthly rainfall-runoff simulations and the fixing-changing method, it is estimated that decrease in the runoff after the breakp
机译:气候变化和人类活动是影响表面径流的两个重要因素。在水资源规划和管理中,将提到的因素与径流变化分开的贡献通常很重要。本文提出了一种新方法,以获得人类活动和气候变化在不确定性下流出的相对影响。在这种方法中,估计了观察到的径流的年度时间序列的断点,并将时间序列分为两个研究时期;在断点之前和之后,即“自然”和“受影响”时期。 Jazim每月水平衡模型用于每月径流模拟。为了融入雪在模拟径流中的效果,使用了与RAO和Al Wagdany(1995)和McCabe和Markstrom(2007)雪模块的Jazim的每月水平模型。然后,为自然和受影响的时期校准并验证每月水平衡模型。使用遗传算法优化水平衡模型的主要参数。使用差分演进自适应Metropolis(Dream)算法分析模型参数的不确定性,该算法基于Markov链蒙特卡罗(MCMC)算法。该算法提供了径流模拟模型参数的后验概率分布功能(PDF)。接下来,使用定影改变方法通过考虑模型的参数的PDF来确定气候变化和人类活动的贡献率(Cr)的PDF。为了展示所提出的方法的适用性和效率,它适用于伊朗的Zayandehrud子盆地。使用标准正常均匀性测试(SNHT),Pettitt和Buishand范围测试,在径流时间序列中检测到2006年的一个断点。通过每月降雨 - 径流模拟和定影变化方法,估计断裂后径流减少

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