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Using tree ring data as a proxy for transpiration to reduce predictive uncertainty of a model simulating groundwater-surface water-vegetation interactions

机译:使用年轮数据作为蒸腾作用的代理,以减少模拟地下水-地表水-植被相互作用的模型的预测不确定性

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The interactions between surface water, the vadose zone, groundwater, and vegetation are governed by complex feedback mechanisms. Numerical models simulating these interactions are essential in quantifying these processes. However, the notorious lack of field observations results in highly uncertain parameterizations. We suggest a new type of observation data to be included in the calibration data set for hydrological models simulating interactions with vegetation: Tree rings as a proxy for transpiration. We use the lower Tarim River as an example site for our approach. In order to forestall the loss of riparian ecosystems from reduced flow over a 300 km reach of the lower Tarim River, the Chinese government initiated periodical, ecological water releases. The water exchange processes in this region were simulated for a cross-section on the lower reaches of the Tarim River using a numerical model (Hydro-GeoSphere) calibrated against observations of water tables, as well as transpiration estimated from tree ring growth. A predictive uncertainty analysis quantifying the worth of different components of the observation dataset in reducing the uncertainty of model predictions was carried out. The flow of information from elements of the calibration dataset to the different parameters employed by the model was also evaluated. The flow of information and the uncertainty analysis demonstrate that tree ring records can significantly improve confidence in modeling ecosystem dynamics, even if these transpiration estimates are uncertain. To use the full potential of the historical information encapsulated in the Tarim River tree rings, however, the relationship between tree ring growth, and transpiration rates has to be studied further. (C) 2014 Elsevier B.V. All rights reserved.
机译:地表水,渗流带,地下水和植被之间的相互作用受复杂的反馈机制控制。模拟这些相互作用的数值模型对于量化这些过程至关重要。但是,众所周知,缺乏现场观测会导致高度不确定的参数设置。我们建议将一种新型的观测数据包括在模拟与植被相互作用的水文模型的校准数据集中:以树木年轮作为蒸腾作用的代名词。我们以塔里木河下游为例。为了防止塔里木河下游300公里处的流量减少,河岸生态系统遭受损失,中国政府发起了定期的生态水释放。使用数值模型(Hydro-GeoSphere)对水位的观测值进行校正,并根据树环的生长估算出的蒸腾作用,从而对该塔里木河下游断面的水交换过程进行了模拟。进行了预测不确定性分析,量化了观察数据集不同组成部分的价值,以减少模型预测的不确定性。还评估了从校准数据集元素到模型采用的不同参数的信息流。信息流和不确定性分析表明,即使这些蒸腾估算值不确定,树年轮记录也可以显着提高对生态系统动力学建模的信心。为了充分利用塔里木河树木年轮中封装的历史信息的潜力,必须进一步研究树木年轮生长与蒸腾速率之间的关系。 (C)2014 Elsevier B.V.保留所有权利。

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