Hydrology and Earth System Sciences
There is an increasing demand for assessment of water provisioning ecosystem services. While simple mod- els with low data and expertise requirements are attractive, their use as decision-aid tools should be supported by un- certainty characterization. We assessed the performance of the InVEST annual water yield model, a popular tool for ecosystem service assessment based on the Budyko hydro- logical framework. Our study involved the comparison of 10 subcatchments ranging in size and land-use configuration, in the Cape Fear basin, North Carolina. We analyzed the model sensitivity to climate variables and input parameters, and the structural error associated with the use of the Budyko frame- work, a lumped (catchment-scale) model theory, in a spa- tially explicit way. Comparison of model predictions with ob- servations and with the lumped model predictions confirmed that the InVEST model is able to represent differences in land uses and therefore in the spatial distribution of water provi- sioning services. Our results emphasize the effect of climate input errors, especially annual precipitation, and errors in the ecohydrological parameter Z, which are both comparable to the model structure uncertainties. Our case study supports the use of the model for predicting land-use change effect on water provisioning, although its use for identifying areas of high water yield will be influenced by precipitation errors. While some results are context-specific, our study provides general insights and methods to help identify the regions and decision contexts where the model predictions may be used with confidence.
Licensed to Smith College and distributed CC-BY under the Smith College Faculty Open Access Policy.
Hamel, Perrine and Guswa, Andrew John, "Uncertainty Analysis of a Spatially Explicit Annual Water-Balance Model: Case Study of the Cape Fear Basin, North Carolina" (2015). Engineering: Faculty Publications, Smith College, Northampton, MA.