Erosion models: quality of spatial predictions
Erosion models: quality of spatial predictions
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DOI：
10.1002/hyp.1168
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发表时间：
2003-04-15
影响因子：
3.2
通讯作者：
Hessel, R
中科院分区：
文献类型：
--
作者：
Jetten, V;Govers, G;Hessel, R
概述了空间分布的径流和侵蚀模型的预测质量。摘要介绍了全球变化和陆地生态系统焦点3方案组织的模型比较研讨会的结果，以及研究人员个人取得的其他结果。结果与文献中普遍持有的观点一致，分布式模型的预测质量是中等良好的总流量在出口处，而不是很好的净土壤流失。只有在进行广泛校准的情况下才是如此：未校准的结果通常很糟糕。更简单的集总模型似乎表现得与更复杂的分布式模型一样好，尽管后者产生更详细的空间分布结果，可以帮助研究人员。所有这些结果都是出口的基础上：模型进行了测试，集中排放和土壤流失或水文和沉积。令人惊讶的是，很少有测试已经做了模拟和模拟的侵蚀模式的比较，虽然这可能是一样重要的意义上的设计抗侵蚀措施和确定源和汇区。两项研究中，侵蚀模型LISEM（林布尔格土壤侵蚀模型）的空间性能进行了分析。看来：（i）模型对分辨率非常敏感（ii）空间模式预测不是很好;（iii）当结果被重新采样到较低分辨率时，性能变得更好，以及（iv）当模型中的某些过程（在这种情况下是沟壑切口）被限制在所谓的“关键区域”，从具有简单规则的数字高程模型中选择。与校准和验证空间分布的土壤侵蚀模型相关的困难，在很大程度上，由于土壤侵蚀现象在空间和时间上的变异性很大，而且预测这些过程的模型中所用的输入参数值具有不确定性。因此，这些问题无法通过构建更完整、更复杂的模型来解决。然而，这种情况可能会得到改善，使用更多的空间信息模型校准和验证，而不是输出数据，并通过使用“最佳”模型，只描述在给定的景观中运行的主导过程。版权所有（C）2003约翰威利父子有限公司。
An overview is given on the predictive quality of spatially distributed runoff and erosion models. A summary is given of the results of model comparison workshops organized by the Global Change and Terrestrial Ecosystems Focus 3 programme, as well as other results obtained by individual researchers. The results concur with the generally held viewpoint in the literature that the predictive quality of distributed models is moderately good for total discharge at the outlet, and not very good for net soil loss. This is only true if extensive calibration is done: uncalibrated results are generally bad. The more simple lumped models seem to perform equally well as the more complex distributed models, although the latter produce more detailed spatially distributed results that can aid the researcher. All these results are outlet based: models are tested on lumped discharge and soil loss or on hydrographs and sedigraphs. Surprisingly few tests have been done on the comparison of simulated and modelled erosion patterns, although this may arguably be just as important in the sense of designing anti-erosion measures and determining source and sink areas. Two studies are shown in which the spatial performance of the erosion model LISEM (Limburg soil erosion model) is analysed. It seems that: (i) the model is very sensitive to the resolution (grid cell size); (ii) the spatial pattern prediction is not very good; (iii) the performance becomes better when the results are resampled to a lower resolution and (iv) the results are improved when certain processes in the model (in this case gully incision) are restricted to so called 'critical areas', selected from the digital elevation model with simple rules.The difficulties associated with calibrating and validating spatially distributed soil erosion models are, to a large extent, due to the large spatial and temporal variability of soil erosion phenomena and the uncertainty associated with the input parameter values used in models to predict these processes. They will, therefore, not be solved by constructing even more complete, and therefore more complex, models. However, the situation may be improved by using more spatial information for model calibration and validation rather than output data only and by using 'optimal' models, describing only the dominant processes operating in a given landscape. Copyright (C) 2003 John Wiley Sons, Ltd.