When making conservation decisions within watersheds, it can be helpful to use decision support tools (DSTs). These software-based tools can assist in identifying opportunities for best management practices (BMPs) or estimating potential outcomes or costs from implementing BMPs.
There are dozens of DSTs available to aid in conservation planning or outcomes estimation. Some well-known DSTs include the Pollutant Load Estimation Tool (PLET), Spreadsheet Tool for Estimating Pollutant Loads (STEPL), Agricultural Conservation Planning Framework (ACPF), Nutrient Tracking Tool (NTT), Wisconsin Soil Nutrient Application Planner (SnapPlus), and Prioritize, Target, and Measure Application (PTMApp).
With so many options, it’s important to carefully evaluate each tool’s unique outcomes, requirements, and processes to determine the best fit for your project. Here are some important considerations to keep in mind when choosing a DST.
Determine your goal.
Identifying your goal is an important first step. Are you trying to estimate losses from the current landscape or a potential future landscape? Or are you looking to identify potential locations for BMPs?
Most tools can be divided into two categories: planning or estimation. Planning tools are BMP-focused tools that identify potential locations using landscape attributes (e.g., soils, topography, land use) and NRCS standards. Estimation tools are outcomes-focused tools that predict the current losses to the environment or the benefits or costs of adopting BMPs.
It is also important to consider the area to be modeled. Most estimation DSTs focus on cropland; however, nutrient and sediment losses can also occur in pastureland, forests, feedlots, and urban areas. To model loss from an entire watershed, you need a tool that considers all land uses.
Identify which outcomes to measure.
When using an estimation DST, another important consideration is the measured outcomes. Most estimation DSTs approximate nitrogen, phosphorus, and sediment loss from the landscape. Some DSTs will provide additional outcomes, such as economics, water storage, and carbon sequestration.
Be sure the outcomes are what you expect. Some tools only estimate total nutrient loads or nutrients in specific forms (e.g., nitrate). The specific outcomes estimated are often a product of the background processes of the tool.
Learn which tools are available for your region.
Some tools are nationally available, while others are tailored to specific geographic locations. Although many regional tools can be used in other states or countries, additional validation steps may be necessary by someone familiar with the local soils and hydrology (water flow).
In some cases, extra data pre-processing is required to prepare data for entry into the tool, particularly in areas outside of a tool’s intended range.
Using and validating a tool beyond its intended range can be a valuable way to support future expansion of that tool and promote data-sharing and collaboration.
Choose what analysis scale makes sense.
Most DSTs operate at the 12-digit hydrologic unit code (HUC-12) scale. However, DSTs can range from field to HUC-2 watershed scales.
Field-scale DSTs often require fine-resolution data specific to the field, such as soil test results, fertilizer rates, or tillage operations. These tools are ideal for working with individual farmers.
Analyses at the HUC-2 scale often use generalized data and require less data collection. These large-area analyses are often ideal for considering potential outcomes at the beginning of a project but are often too generalized to be very accurate or precise.
Consider the tool platform and your computing power.
Consider what platform the DST lives on and who will run the tool. Tools built in Microsoft Excel or online are often more user-friendly than GIS applications like Q-GIS and ArcGIS.
A few tools have a separate desktop application, which must be downloaded and installed on your computer. Some platforms require paid accounts, such as ArcGIS.
The analysis scale and platform often determine how much memory and processing speed are required to run a tool. Using the wrong computer can result in slow processing times or crashed programs, especially when using tools within a desktop application or a GIS program.
Align the effort required with your capacity.
Tools range in complexity, often due to the platform and required steps. Some DSTs can be run by students or interns, while others require extensive GIS knowledge and tool-specific training.
If you need training, you can often find videos on the tool’s website.
More complex tools will take longer to run, with some taking weeks to complete, not including training. Simple DSTs can be run in only a few hours, but results will often be more generalized.
All DST results should be validated by someone with local knowledge of the landscape and soils.
Determine your needs for spatial explicitness.
The platform, background processes, input data, and time required are all related to whether a DST is spatially explicit or implicit.
Spatially explicit tools consider the precise spatial location of a BMP. Hydrology through a field or landscape is often considered. Spatially explicit DSTs generally take longer to run and require more processing power.
When using spatially implicit tools, the effects of BMPs are estimated with little to no regard for spatial location. In these tools, soil properties are often considered, but not hydrology.
Use appropriate data.
No matter what tool you select, your analysis will only be as good as the data provided.
Some tools come with default data, which is helpful to run a quick analysis. However, it’s always recommended to supply your own data whenever possible. Default data is often generalized over large areas and out-of-date.
Below are some recommended data sources that are commonly used in DSTs.
| Name | Available Data |
| Web Soil Survey | Soils (visualization, direct download) |
| SSURGO Portal | Soils (tables) |
| Geospatial Data Gateway | Boundaries, course elevation*, climate, roads, etc. |
| State GIS Databases: Iowa | Indiana | Minnesota | Wisconsin | Boundaries, elevation*, roads, etc. |
| National Agricultural Statistics Service | Annual farm survey: counts, acres, yields, etc. |
| USDA Cropland CROS | Annual land cover |
| Agricultural Conservation Planning Framework Core Data | Watershed and field boundaries, land cover, soils, etc. |
| USGS StreamStats | Stream flow volume, course watershed delineation |
| Operational Tillage Information System (OpTIS) | Cover crop and conservation tillage adoption estimates |
Additional Resources
A Guide to Water Quality, Climate, Social, and Economic Outcomes Estimation Tools by American Farmland Trust
Water Quality Model, Tool, and Calculator Basics by Minnesota Board of Soil and Water Resources
Header photo credit: Sand County Foundation
