Classification of Runoff in Headwater Catchments: A Physical Problem?
Classification of Runoff in Headwater Catchments: A Physical Problem?
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DOI：
10.1111/j.1749-8198.2007.00075.x
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发表时间：
2008-01-01
影响因子：
3.1
通讯作者：
Lange, Holger
中科院分区：
文献类型：
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作者：
Hauhs, Michael;Lange, Holger
地球上的生命依赖于水，地球上哪里有自来水，哪里就有生命。然而，现有的水文学建模方法几乎完全忽略了水流的生物学方面。我们认为，在流域径流模型中忽略生物行为和相互作用过于严格，计算理论可以用来形式化行为和相互作用，并对生物对径流的影响进行建模。为了证明这一点，从径流数据中记录的流域行为的一般分类开始，我们将使用符号动力学来量化时间序列中的随机性和复杂性。这种方法表明，来自不同流域的径流记录显示出共同的行为。这一行为可以符合一条单参数曲线，分为三个区域。以这种方式，可以表示和分类不能通过算法生成的交互行为的类型。这表明，基于物理的流域模型并不能恰当地代表所有类型的相互作用行为，生物相互作用的特征存在于径流数据中。
Life on earth depends on water and where running water occurs on earth, there is life. Nevertheless, existing modelling approaches in hydrology almost completely neglect the biological aspects of water flow. We claim that ignoring biological behaviour and interaction in catchment runoff modelling is too restrictive, and that computational theories can be used to formalise behaviour and interaction and model the biological impact on runoff. To demonstrate this, starting with a general classification of catchment behaviour, as documented in runoff data, we will use symbolic dynamics to quantify randomness and complexity in the time series. This approach shows that runoff records from very different catchments show common behaviour. This behaviour can be fitted to a one-parametric curve, stratified into three regions. In this manner, it becomes possible to represent and classify types of interactive behaviour that cannot be generated algorithmically. This suggests that physically based catchment models do not properly represent all types of interactive behaviour, and that signatures of biological interaction are present in runoff data.