# Spatial Aquatic Model (SAM): **Update on the Regional Pilot Project** 

Presentation to the Environmental Modeling Public Meeting (EMPM)

3/19/13

Nelson Thurman, US EPA, OPP, EFED

# Spatial Aquatic Model Pilot Project Team

• Nelson Thurman

– project manager

• Dirk Young

– aquatic model development lead

• Shelly Thawley

– GIS, spatial development lead

• Jim Carleton

– hydrology, modeling, GIS expertise

• Ron Parker

– PRZM, hydrology expertise

• Kurt Pluntke

– database, modeling expertise

• Paul Mastradone

– modeling, risk management

• Phil Villanueva

– management lead

• Gabe Rothman

– climate/weather

• Chris Koper

– modeling (QA evaluations)3 

# What Do We Need to Know About **Pesticide Exposure in Water?**

How much? (magnitude)

How long? (duration) How often? (frequency) Where? (spatial) 

# Do the levels of exposure exceed the levels of concern? ...is actually several questions:

# Goal: Become More “Spatially Explicit”

No longer assumes a uniform distribution of the pesticide (stressor)

4 Spatially Explicit Assessment

Stressor distribution Receptor range Area exceeding level of concern



## Considers the overlap between the stressor and the receptors (humans, animals, plants) Pesticide

Where When How often Animals Plants Humans5 

# What We Needed to Move Forward

Nationally available spatial data. Quick, efficient modeling. Sufficient computing power, storage.

# Spatial Data for Aquatic Modeling

6 b) Soils

d) Weather a) Hydrology e) Crop Growth, Management c) Land Use/ Land Cover

# Adapting Our Current Aquatic Exposure **Modeling Approach**

Field or watershed with pesticide

applications

Runoff Drift

Erosion

7 Water body (pond or reservoir) (PRZM)

(EXAMS) Pesticide Fate and Transport Pesticide

Loading

Soil, Site , Crop, Hydrology

Weather (rainfall, temp., Irrigation)

# Incorporating Spatial Heterogeneity into **the Watershed Modeling Unit**

(b) Soil map

– land cover patterns 8 (a) Single, uniform watershed

# Redesigning PRZM for Spatial Modeling

9 Pesticide Fate and Transport Pesticide

Loading

Soil, Site , Crop, Hydrology

Weather (rainfall, temp., Irrigation) 

### Pesticide Fate & Transport

Routines

Hydrology / Scenario Generator Water Body Model

# Model Development and Data Quality

Review model routines Scientifically sound
Documented Verified Functioning as expected



## Sensitivity analyses Compare any code changes against current models 

## Evaluate results Compare with robust monitoring data Reasonable, protective

# General Flow of the Spatial Model **Process**

11 Tabular storage, calculations, manipulations
l argely occur outside of the spatial environment 

### Spatial data extracted, fed into models

Results are linked back to mappable

areas Heavy lifting Catchment/

field with pesticide applications

Receiving water body Runoff Drift

Erosion Pesticide Fate and Transport Pesticide Loading

Soil, Site , Crop, Hydrology

Weather (rainfall, temp., Irrigation)Spatial Scenario

Inputs

Non

Spatial Scenario

Inputs Hydrology/ Scenario Generator Scenario Files Hydrology Sediment Crop Specific Scenarios

Pesticide Fate/ Transport Model Watershed/ Water body Coverages Hydrology, Sediment Flux

Pesticide Fate/Tox Properties Pesticide

Flux by Model Unit

Watershed

Pesticide Flux

Water Body Model Watershed Calculator

Summary Outputs: LOC Exceedances

Pesticide EECs Link Data to Water Bodies Watershed Recipe

Files

User Input Interface

Use, Application Inputs

Calculate Endpoints 

# More **Complex Version** 

# Example Outputs

Areas exceeding toxicity thresh

holds

Exposure overlap with species of

concern Tables summarizing LOC

comparisons for eco, MOE comparisons for human health

Frequency, duration of

occurrences
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# Building SAM in a Phased Approach

Pilot 1: Proof of Concept Model Pilot 2: Model Development at a Regional Level

Pilot 3: Model Expanded to the US

# Progress and Plans

• Final stages of data development, compilation

• Model components evaluated

• Testing how the model components work together will begin soon

• Demonstration model

• Evaluation of computing, storage needs

• Expand model to national coverage

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