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Empirical validation of the InVEST water yield ecosystem service model at a national scale

机译:国家级InVEST水分生态系统服务模式的经验验证

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摘要

A variety of tools have emerged with the goal of mapping the current delivery of ecosystem services and quantifying the impact of environmental changes. An important and often overlooked question is how accurate the outputs of these models are in relation to empirical observations. In this paper we validate a hydrological ecosystem service model (InVEST Water Yield Model) using widely available data. We modelled annual water yield in 22 UK catchments with widely varying land cover, population and geology, and compared model outputs with gauged river flow data from the UK National River Flow Archive. Values for input parameters were selected from existing literature to reflect conditions in the UK and were subjected to sensitivity analyses. We also compared model performance between precipitation and potential evapotranspiration data sourced from global- and UK-scale datasets. We then tested the transferability of the results within the UK by additional validation in a further 20 catchments.udWhilst the model performed only moderately with global-scale data (linear regression of modelled total water yield against empirical data; slope = 0.763, intercept = 54.45, R2 = 0.963) with wide variation in performance between catchments, the model performed much better when using UK-scale input data, with closer fit to the observed data (slope = 1.07, intercept = 3.07, R2 = 0.990). With UK data the majority of catchments showed less than 10% difference between measured and modelled water yield but there was a minor but consistent overestimate per hectare (86 m3/ha/year). Additional validation on a further 20 UK catchments was similarly robust, indicating that these results are transferable within the UK. These results suggest that relatively simple models can give accurate measures of ecosystem services. However, the choice of input data is critical and there is a need for further validation in other parts of the worldud
机译:已经出现了各种工具,其目的是绘制当前生态系统服务的提供情况并量化环境变化的影响。一个重要且经常被忽略的问题是,这些模型的输出相对于经验观察的准确性如何。在本文中,我们使用广泛可用的数据验证了水文生态系统服务模型(InVEST水产量模型)。我们对22个具有不同土地覆盖,人口和地质状况的英国集水区的年水产量进行了建模,并将模型输出与英国国家河流流量档案馆的测量河流流量数据进行了比较。从现有文献中选择输入参数的值以反映英国的情况,并进行敏感性分析。我们还比较了来自全球和英国规模数据集的降水量和潜在蒸散数据之间的模型性能。然后,我们通过在另外20个集水区进行额外的验证,测试了结果在英国范围内的可传递性。 ud虽然模型仅对全球规模的数据进行了适度的执行(模拟总水产量与经验数据的线性回归;斜率= 0.763,截距= 54.45,R2 = 0.963),流域之间的性能差异很大,使用UK规模的输入数据时,模型的性能要好得多,与观测数据的拟合度更高(坡度= 1.07,截距= 3.07,R2 = 0.990)。根据英国的数据,大多数集水区的测得的水量与模拟的水量之间的差异不足10%,但每公顷的面积却有一个很小但一致的高估(86立方米/公顷/年)。类似地,对另外20个英国流域的附加验证也很可靠,表明这些结果可在英国范围内转移。这些结果表明,相对简单的模型可以给出生态系统服务的准确度量。但是,输入数据的选择至关重要,并且需要在世界其他地方进行进一步的验证 ud

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