Comparing two tools for ecosystem service assessments regarding water resources decisions.

We present a comparison of two ecohydrologic models commonly used for planning land management to assess the production of hydrologic ecosystem services: the Soil and Water Assessment Tool (SWAT) and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) annual water yield model. We compare these two models at two distinct sites in the US: the Wildcat Creek Watershed in Indiana and the Upper Upatoi Creek Watershed in Georgia. The InVEST and SWAT models provide similar estimates of the spatial distribution of water yield in Wildcat Creek, but very different estimates of the spatial distribution of water yield in Upper Upatoi Creek. The InVEST model may do a poor job estimating the spatial distribution of water yield in the Upper Upatoi Creek Watershed because baseflow provides a significant portion of the site's total water yield, which means that storage dynamics which are not modeled by InVEST may be important. We also compare the ability of these two models, as well as one newly developed set of ecosystem service indices, to deliver useful guidance for land management decisions focused on providing hydrologic ecosystem services in three particular decision contexts: environmental flow ecosystem services, ecosystem services for potable water supply, and ecosystem services for rainfed irrigation. We present a simple framework for selecting models or indices to evaluate hydrologic ecosystem services as a way to formalize where models deliver useful guidance.

Returns on investment in watershed conservation: Application of a best practices analytical framework to the Rio Camboriú Water Producer program, Santa Catarina, Brazil.

Watershed management may have widespread potential to cost-effectively deliver hydrologic services. Mobilizing the needed investments requires credible assessments of how watershed conservation compares to conventional solutions on cost and effectiveness, utilizing an integrated analytical framework that links the bio-, litho-, hydro- and economic spheres and uses counterfactuals. We apply such a framework to a payment for watershed services (PWS) program in Camboriú, Santa Catarina State, Brazil. Using 1 m resolution satellite imagery, we assess recent land use and land cover (LULC) change and apply the Land Change Modeler tool to predict future LULC without the PWS program. We use current and predicted counterfactual LULC, site costs and a Soil and Water Assessment Tool model calibrated to the watershed to both target watershed interventions for sediment reduction and predict program impact on total suspended solids (TSS) concentrations at the municipal water intake-the principal program objective. Using local water treatment and PWS program costs, we estimate the return on investment (ROI; benefit/costs) of the program. Program ROI exceeds 1 for the municipal water utility in year 44, well within common drinking water infrastructure planning horizons. Because some program costs are borne by third parties, over that same period, for overall (social) program ROI to exceed 1 requires delivery of very modest flood and supply risk reduction and biodiversity co-benefits, making co-benefits crucial for social program justification. Transaction costs account for half of total program costs, a result of large investments in efficient targeting and program sustainability. Co-benefits justify increased cost sharing with other beneficiaries, which would increase ROI for the utility, demonstrating the sensitivity of the business case for watershed conservation to its broader social-economic case and the ability to forge institutional arrangements to internalize third-party benefits.

Sediment delivery modeling in practice: Comparing the effects of watershed characteristics and data resolution across hydroclimatic regions.

Geospatial models are commonly used to quantify sediment contributions at the watershed scale. However, the sensitivity of these models to variation in hydrological and geomorphological features, in particular to land use and topography data, remains uncertain. Here, we assessed the performance of one such model, the InVEST sediment delivery model, for six sites comprising a total of 28 watersheds varying in area (6-13,500km2), climate (tropical, subtropical, mediterranean), topography, and land use/land cover. For each site, we compared uncalibrated and calibrated model predictions with observations and alternative models. We then performed correlation analyses between model outputs and watershed characteristics, followed by sensitivity analyses on the digital elevation model (DEM) resolution. Model performance varied across sites (overall r2=0.47), but estimates of the magnitude of specific sediment export were as or more accurate than global models. We found significant correlations between metrics of sediment delivery and watershed characteristics, including erosivity, suggesting that empirical relationships may ultimately be developed for ungauged watersheds. Model sensitivity to DEM resolution varied across and within sites, but did not correlate with other observed watershed variables. These results were corroborated by sensitivity analyses performed on synthetic watersheds ranging in mean slope and DEM resolution. Our study provides modelers using InVEST or similar geospatial sediment models with practical insights into model behavior and structural uncertainty: first, comparison of model predictions across regions is possible when environmental conditions differ significantly; second, local knowledge on the sediment budget is needed for calibration; and third, model outputs often show significant sensitivity to DEM resolution.