Comparing SWAT and InVEST models for water yield and nutrient export: When is a simple model good enough for decision support?
Abstract
Tools that link land use and management changes with effects on water quantity and quality are in high demand. These tools are used to inform a variety of decisions from regulatory action to informing investments in conservation. However, not all managers or researchers have the time, expertise, or data availability to run complex hydrologic models. This raises the question: When are simple models good enough for decision support? We evaluated two hydrologic models commonly used to predict how land use and land management decisions affect water yield and nutrient export. We compare the continuous time model SWAT (Soil and Water Assessment Tool) that operates on a daily time step with the annual water yield and nutrient retention models in InVEST (Integrated Valuation of Environmental Services and Tradeoffs). We ran each model on two watersheds in Minnesota dominated by row crop agriculture. We calibrated each model to observed data for a baseline land use scenario and then compared predicted water yield and the export of nitrogen and phosphorus from four alternative conservation scenarios. We found good agreement between InVEST and SWAT for scenarios where lands were taken out of corn and soybean production and converted to perennial cover. The two models differed in their modeled nutrient export from scenarios that employed riparian buffers along all waterways. In these scenarios, InVEST predicted much higher reductions in nutrient loading than SWAT. Our analysis highlights key differences between the models in both their structure and assumptions, and provides insights into the value of additional model complexity across a range of decision contexts.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2013
- Bibcode:
- 2013AGUFM.H21F1135K
- Keywords:
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- 1847 HYDROLOGY Modeling;
- 1879 HYDROLOGY Watershed;
- 0402 BIOGEOSCIENCES Agricultural systems;
- 0496 BIOGEOSCIENCES Water quality