Watershed Management Assessment Through Modeling: SALT and CEAP Dr. Claire Baffaut Water Quality Short Course Boone County Extension Office April 12, 2007

Watershed Assessment Inventory potential sources of pollution Determine pollution pathways Link the characteristics of the watershed with the water quality in its streams, lakes, and groundwater. Predict water quality when land use or land management change in the watershed.

Water Quality Data Why don’t we just use measured data? Data are limited in frequency and duration. Pollutant concentrations are first and foremost dependent on weather. Measured concentrations or flow can be the result of several factors.

Example: Atrazine in Goodwater Creek

Possible Reasons Percent Crop Area in No-Till and Conservation Tillage Percent Area Protected by Waterways Estimated average corn planting dates from 1992 to 2004.

Modeling can help find what is responsible for measured flows or concentrations.

What is a Model? A mathematical equation is a model –The USLE equation (for soil loss estimation) Computer simulation model for watershed assessment: –A combination of equations that represent the different processes in the watershed. –These equations link the topography, the soil characteristics, the management, and the weather to flow and water quality.

Field Level: EPIC Environmental Policy Integrated Climate model

Watershed Level: APEX or SWAT Ponds and reservoirs Streams and waterways Subsurface and groundwater flow

What can we do with modeling? Watershed scale Farm scale Field scale

Stream and river issues How dirty is it ? Where do water and pollutants come from ? How much water is there ? What is affecting flow and pollutant concentrations ?

Farm issues What is the best way to distribute the manure between different fields to minimize environmental impacts? How can we maximize profits while minimizing environmental impacts?

Field problems How much soil is lost from the field? How long will it take to loose productivity? How much phosphorus is leaving the field? How much carbon can the soil sequester? How much nutrient is lost to percolation?

What if scenarios What happens if… –a toxic substance leeks out of an industrial site. –the number of CAFO’s in an area increases. –agricultural land becomes residential or industrial. –better management practices are implemented.

Data requirements USER INPUT Topographic data (GIS) Weather data (National Weather Service) Soil and Land use data (GIS) Management data (??) DATABASES Weather database Fertilizer database Tillage database Crop database

Management Data Census data. – Some data on total fertilizer amounts, or crops being grown. Usually on a county basis. – Little information on tillage practices, timing of operations, rotations implemented … Panel consensus. –Form of interview where the panel members have to agree that a practice is representative.

Garbage in  Garbage out MODEL Garbage

In Color, still MODEL Garbage

Even if animated, it is still MODEL Garbage in Garbage out

Model Calibration To be accepted, a model needs to be calibrated Calibration: Adjusting the parameters of the model to have good agreement between model predictions and measured data over a period of time. Validation: Verifying that the model results and the measured data match over a different period of time.

Examples of answers provided by models

6 Selected AgNPS-SALT Projects Long Branch Upper and Lower Maries River Jenkins Basin Flat Creek Miami Creek

BMPs Fully Simulated With SWAT Erosion control through tillage and terraces Erosion control through grade stabilization structures (ponds) Woodland protection (livestock exclusion) Grassland establishment / improvement Pasture management Poultry litter export

Predicted Change in Stream Loads after Implementation of the Project WatershedSediment Total Nitrogen Total Phosphorus Miami Creek-8 %-11 %-29 % Long Branch-2 %-8 %-11 % Flat Creek-17 %-7 %-14 % Maries River-22 %-20 %-19 % Jenkins Basin-11 %-8 %-17 %

Conclusion: Why Model? Link watershed characteristics, watershed management, and water quality. That allows to: –Understand the link. –Focus the action where it is most useful. Predict the consequences of “what if” scenarios without having to try them. BUT because garbage in causes garbage out, there is a need to understand the model and calibration process: –Development of specific databases for Missouri. –Training.