Spatial Aquatic Model:

Pilot Project Update

March 24, 2014

Presentation to the EMPM

Meridith Fry, Dirk Young, and 

Nelson Thurman
Outline

• Overview of SAM

– Why SAM?

– Improving our current modeling approach

• Overview of the Model

– Model structure and components

– Solution technique

• Performance and validation

• Next steps
Overview of SAM
SAM: Spatial [and Temporal] Aquatic Model

Intended to answer the risk management questions: 

• Do exposures exceed toxicity levels of concern?

• If so, where do these exposures occur and how 

often/ how long do they occur?

4

Spatially Explicit Assessment

Stressor 

distribution

Receptor 

range

Area exceeding level of concern

Pesticide

Where

When

How often

Animals

Plants

Humans
5

Why SAM?

Pass

Fail

When screening assessments exceed toxicity 

thresholds, we need a way to more effectively 

identify areas of potential concern
Overarching goals of SAM

• Improve on what we currently do, advancing the 

science by keeping up with what’s available

• Keep things as simple as possible without losing 

vital information in oversimplification

• Focus on the drivers

– Add complexity where it has an impact

– Where it doesn’t make much difference, keep it simple

• Be useful and understandable for both the 

modeler and the end users

• Provide confidence and reliability in our 

assessments
Overview of the Model
SAM Structure
Spatial data inputs: constructing 

scenarios

9

Soils - SSURGO Land Cover - CDL

Overlap soils with land cover to 

create basic scenarios

(NRCS) (USDA)
Additional spatial inputs

Meteorology 10 Crop Growth/Management

NCAR/NCEP Reanalysis Gridded Data

1948 – 2013 (daily)

↓

NOAA CPC: 0.25◦

x0.25◦ Daily US 

Precip

Scenarios
Constructing Watershed Recipes

11

List of unique scenarios 

and total area in a given 

basin NHD Plus (version 2) 

Mean flow data for 

each basin

Watershed

Recipes
SAM Structure
Pre-processed components

• Scenario Generator

– Calculates daily hydrologic values (irrigation, runoff, 

evaporation, vertical transport) and plant growth 

stages for each mapping unit-crop combination 

(MUKEY-CROP)

– Output: Daily runoff, daily soil moisture, plant growth 

stages for each MUKEY-CROP

• Super PRZM Hydro

– Sums daily runoff weighted by area of all MUKEY- CROP combinations in each watershed

– Output: Total daily runoff from each watershed over 

simulated time period
SAM Structure
Chemical/site-specific components

• Pesticide Transport and Water Body 

Concentration Calculator

– Links chemical transport and watershed hydrology 

to estimate pesticide concentrations in specific 

receiving water bodies

– Chemical and application details are read from 

graphical user interface (GUI)

– Output: Daily pesticide concentrations in receiving 

water body, daily flow, frequency of exceeding 

toxicity threshold, spatial maps
Transport from application site 

based on PRZM

• As in PRZM, the Calculator simulates leaching, 

sorption, degradation, and transport via runoff in 

top 2 cm soil compartment

• At each successive daily time step, the transport 

equation is solved analytically

*Currently, transport equation does not 

include loss of pesticide mass sorbed to 

Mass leached eroded soil

Mass stored Mass transported 

via runoff

Mass applied

Mass degraded

2 cm
Mass transported via runoff concept 

from PRZM2 to PRZM3 to SAM
Receiving water body volume and 

flow

• Receiving water body volume is first calculated:

• Mixing cell concept applied to all water bodies, given 

that volume of mixing cell is << mean flow rate

• Monthly mean base flows calculated using NHDPlus v2 

seasonalized annual average flow and long-term average 

daily watershed runoff

• Total daily flow in water body = Base flow + Daily Runoff

Flowing water body 

(streams, rivers)

Non-flowing water body 

(drinking water reservoir, pond)

Water body 

volume

Cross-sectional area (flow/velocity)

x Representative length (40 m)

Hollister (2011) method used to 

estimate lake morphometry
Solution technique for transport 

equation

Tridiagonal 2 diagonal Single Equation
Receiving water body concentration

• Using estimated volume (Vwb) and total flow (Qt), 

effective rate constant (k) for first-order washout from 

water body is calculated:

• Initial water body concentration, Co,wb:

• Water body concentration (Cwb) at indefinite time later:

Daily mean conc:

* Future work may handle reservoirs differently, as longer residence times 

permit mass to degrade or partition. For pilot study of atrazine, reservoir 

and flowing water body concentrations calculated identically.

wb

t

V

Q k(t) =

kt

wb o wb C t C t e− ( ) = ( ) ,

wb

runoff remaining

o wb V

M t M t

C t

( ) ( 1) ( ) ,

+ − =

( ) (1 ) ,

,

o wb k

avg wb e

k

C

C t − = −
Performance and Validation
Monitoring comparisons show SAM 

outputs are reasonable

• Confidence in results:

– Consistency in magnitude and seasonality between 

simulated flows & USGS stream gage measured flows

– Consistency in magnitude between simulated atrazine

concentrations & AMP/AEEMP measured concentrations

• Main finding -

SAM performs very well for a non-calibrated 

model. While results do not match monitoring 

data perfectly, they are reasonable and 

representative.
Consistency in magnitude of flows:

SAM daily total flow vs. USGS stream gage 

3353200

*Additional comparisons provided in Appendix A of Model Documentation
Consistency in seasonality of flows:

SAM monthly avg base & runoff flows vs. 

USGS stream gage 3353200

*Additional comparisons provided in Appendix B of Model Documentation

J F M A M J J A S O N D
Consistency in daily concentrations:

SAM daily atrazine concentrations vs. AMP 

monitoring data

*Additional comparisons provided in Appendix C of Model Documentation

Jan-03 Jan-04 Jan-05 Jan-06 Jan-07
*Additional comparisons provided in Appendix D of Model Documentation

Consistency in magnitude of averaged 

concentrations:

SAM single-day, 14-d avg, 30-d avg max 

concs vs. AMP monitoring (with bias factors)

1-d 14-d 30-d

 2003

1-d 14-d 30-d

 2004

1-d 14-d 30-d

 2005

1-d 14-d 30-d

 2006
Next Steps
Next Steps

• Complete Pilot Region Case Study: In compilation

• Generate heat maps, temporal maps to illustrate SAM capabilities

• Provide Pilot Study documentation: Developing avenue for comments

• Build out national spatial datasets (data 

development, input processing) 

• Flesh out erosion, spray drift, irrigation, 

other components

• Evaluate with other pesticide 

monitoring

• Expand to other regions in U.S.

• Build computer infrastructure: remote 

server, cloud computing

• EFED assessors, OPP management, risk 

managers, HED, industry, other EPA and 

federal agencies

• Follow-up discussions on model outputs 

and applications

• Beta testing

• “Virtual” workshop on SAM (industry, 

fed agencies, academia)

• Scientific Advisory Panel

• Incorporate feedback

• Finalize model ramp-up process

• Full scale modeling

• Roll-out plan TBD

• Consistent with science, policy

• Continuing evaluation period

Prepare Presentations for Target Audiences

Ramp Up National Model

Build Out SAM Model Implementation

Feedback on SAM

1

3 4

2a 2b
Thank you!

Questions?

Contact:

Nelson Thurman (Project Lead)

Office of Pesticide Programs, US EPA

thurman.nelson@epa.gov