Comparing two tools for ecosystem service assessments regarding water resources decisions

Abstract

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 W 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. KEYWORDS:ecosystem services, water yield, model comparison, SWAT, InVEST INTRODUCTIONHydrologic ecosystem services (HESs) are beginning to influence land management decisions through both regulations and investments targeted at protecting and improving water resources [Le Maitre et al., 2007;Gordon et al., 2010;Goldman-Benner et al., 2012]. HESs are the goods and services that ecosystems provide to people related to various uses of water, and include water availability for municipal, agricultural, and commercial use, the reduction of the magnitude and frequency of flow peaks to prevent floods, the reduction of sediment and nutrients in water, and the value of natural hydrologic systems for recreation [Brauman et al., 2007; Keeler et al., 2012;Brauman, 2015]. Land managers use HESs to support investments and meet regulatory requirements around water resources in both developing countries [Goldman, 2009] and developed countries [Lautenbach et al., 2010;Logsdon and Chaubey, 2013]. To support investments or meet regulations, scientists and managers assess HESs under expected future conditions based on some model of the landscape and ecosystem response; the landscapes are then managed to restore, retain, or optimize HESs and thus improve the status of the water resources. Scientists and managers assess HES provision in distinct decision contexts-combinations of investment and regulatory goals and institutional structures-which may decide both which models are applied and how model outputs are used to make decisions.

Improved Prediction of Stream Flow Based on Updating Land Cover Maps with Remotely Sensed Forest Change Detection

“…Preliminary runs of these models indicated that transpiration was much lower than expected. As pointed out by [45], this was due to a default operation practice in SWAT that kills and harvests the crops or forests every year. Such a forestry operation was not expected in our watersheds, and thus was removed, and the initial settings for tree growth for both types of simulations (five-year and annual) were modified accordingly.…”

Effect of National-Scale Afforestation on Forest Water Supply and Soil Loss in South Korea, 1971–2010

“…Nevertheless, forests with deep roots and low direct runoff provide the largest part of the water supply, and forest water yields can be used to determine the amount of total supply [27]. For the calculation of the water yield, various methods suggested by the previous studies included factors such as land use, forest species, age-class, precipitation, amount of evapotranspiration, porous ratio and depth of root [28,29].…”

Effect of Sediment Accumulation on Best Management Practice (BMP) Stormwater Runoff Volume Reduction Performance for Roadways

“…Since a lot of information is missing from reported sites to make this comparison effective, some studies used numerical simulations to evaluate the effect of each parameter on BMP system performance. Some of the numerical simulation studies include the Hydrological Simulation Program-Fortran (HSPF) [3,14], the Soil and Water Assessment Tool (SWAT) [15,16], the Long-Term Hydrologic Impact Assessment-Low Impact Development (L-THIA-LID) [17][18][19], and the Storm Water Management Model (SWMM) [20][21][22][23][24]. This paper seeks to explore BMP performance deterioration due to sediment accumulation using field and numerical simulations.…”