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New Approaches to the Modelling of Lake Basin Morphometry

机译:湖盆形态学建模的新方法

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In lake modelling, a general and useful method of describing variations in area and volume with depth is of fundamental importance to describe processes and properties that change vertically within a given lake. In this work, two mathematical approaches to describe the shape of a lake basin are introduced and tested against empirical data. The two methods require only three easily available input parameters: maximum depth, surface area and volume. The first method is based on a traditional morphometric parameter, the volume development (V_d), and the second method on the new hypsographic development parameter (H_d). Both methods give area and volume at any depth of a lake and can furthermore be used to estimate lake bottom slopes. Comparisons with empirical area—depth and volume-depth distribution curves from 105 lakes that cover a wide range of lake morphometric characteristics have revealed that the two methods give very satisfactory results. The V_d-model yields r~2-values of 0.924 and 0.907 for area and volume description with lake depth, respectively. The corresponding r~2-values for the H_d-model are 0.988 and 0.996, respectively. Using the H_d-model, an approach has also been developed to test when and by how much it is necessary to correct the empirical volume of a lake given the number of measured strata and basin shape.
机译:在湖泊建模中,描述面积和体积随深度变化的通用且有用的方法对于描述在给定湖泊内垂直变化的过程和属性具有至关重要的意义。在这项工作中,介绍了两种描述湖盆形状的数学方法,并根据经验数据进行了测试。两种方法仅需要三个容易获得的输入参数:最大深度,表面积和体积。第一种方法基于传统形态计量学参数,即体积发展(V_d),第二种方法基于新的催眠术发展参数(H_d)。两种方法都给出了湖泊任何深度的面积和体积,并且还可用于估计湖泊底部的坡度。通过与经验区域的比较-来自105个湖泊的深度和体积-深度分布曲线,这些曲线涵盖了广泛的湖泊形态特征,发现这两种方法都给出了令人满意的结果。对于具有湖泊深度的面积和体积描述,V_d模型得出的r〜2-值分别为0.924和0.907。 H_d模型的相应r〜2值分别为0.988和0.996。使用H_d模型,还开发了一种方法来测试在给定被测地层数量和盆地形状的情况下,何时以及需要多少修正湖的经验体积。

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