NERC Centre for Ecology and Hydrology, Maclean Building, Wallingford, Oxfordshire OX10 8BB, UK.
NERC Centre for Ecology and Hydrology, Maclean Building, Wallingford, Oxfordshire OX10 8BB, UK.
Sci Total Environ. 2016 Nov 1;569-570:1418-1426. doi: 10.1016/j.scitotenv.2016.06.227. Epub 2016 Jul 7.
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. Whilst 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, R(2)=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, R(2)=0.990). With UK data the majority of catchments showed <10% difference between measured and modelled water yield but there was a minor but consistent overestimate per hectare (86m(3)/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 world.
出现了各种工具,旨在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。一个重要但经常被忽视的问题是,这些模型的输出与经验观测相比有多准确。在本文中,我们使用广泛可用的数据验证了一个水文生态系统服务模型(InVEST 水产量模型)。我们在 22 个具有广泛不同的土地覆盖、人口和地质的英国流域中模拟了年水产量,并将模型输出与来自英国国家河流水文档案的测量河流水流量数据进行了比较。输入参数的值从现有文献中选择,以反映英国的情况,并进行了敏感性分析。我们还比较了源自全球和英国尺度数据集的降水和潜在蒸散数据对模型性能的影响。然后,我们在另外 20 个流域中进行了进一步验证,以检验结果在英国境内的可转移性。虽然模型在使用全球尺度数据时仅表现中等(模型总水产量与经验数据的线性回归;斜率=0.763,截距=54.45,R(2)=0.963),且流域之间的性能差异很大,但在使用英国尺度输入数据时,模型的表现要好得多,与观测数据的拟合更紧密(斜率=1.07,截距=3.07,R(2)=0.990)。在英国数据中,大多数流域的实测水产量与模型模拟水产量之间的差异小于 10%,但每公顷的估计值略高(86m(3)/ha/year)。在另外 20 个英国流域上进行的额外验证同样稳健,表明这些结果在英国境内具有可转移性。这些结果表明,相对简单的模型可以提供生态系统服务的准确衡量。然而,输入数据的选择至关重要,需要在世界其他地区进一步验证。