1 

### Charge Questions for SAP Discussion The specific charge questions on the Spatial Aquatic Model (SAM) for this SAP are organized by section.

Section 1: SAM Conceptual model
Q1

. The conceptual watershed model for SAM accounts for spatial and temporal variability in soil, land cover, weather, and crop/management inputs and integrates outputs at watershed pour points by area

- weighting.

a. Please discuss the strengths and limitations of the conceptual watershed model for representing spatial and temporal variability in pesticide concentrations in water. b. Please comment on how clearly this conceptual approach is explained. What additional documentation, description, and/or characteriza tion is necessary to ensure clarity and transparency ?

Section 2: SAM Model Components and Approach
Q2

. Please comment on the model organization and improvements to model code

.

a. SAM is organized into three components (scenario generator, hydrology, and calculator) to reduce redundant calculations, increase model efficiency, and make use of pre

processing for creating standalone scenarios and hydrology (Section 2.1)

. USEPA OPP found this to be the best approach for handling the large quantity of the spati al and temporal inputs, while preserving the user’s ability to run unique simulations every time. Please comment on the separation of independent processes (e.g., hydrology, pesticide transport) to maximize computational efficiency and minimize user run

- ti me . b. USEPA OPP has improved the PRZM model code to eliminate inefficiencies and excessive calculations

. For e xample, simplifying the soil surface into a single layer, as described in Section 2.1.1, increased computational time by 10

- fold with negligible ch ange in results

. Please comment on this general approach to improve the model’s speed and efficiency without sacrificing accuracy and provide any additional recommendations for improving model efficiency

. Q3

. Section 2.3 and 2.4 describe initial model evaluation steps for SAM to evaluate model uncertainty, sensitivity, and performance in comparison to measured (monitoring) data. Additional model evaluations occur in Sections 4. 3 and 5. 4

.

a. What additional sensitivity analyses would the SAP recommen d for model evaluation ? b. Current model evaluation compared SAM estimates to available atrazine monitoring data collected at daily to weekly intervals. Given the importance of robust, frequently

sampled monitoring data for evaluation, w hat additional monitoring or other types of data are currently available to test and evaluat e how well SAM meets EPA objectives2 of transparent processes and clear, consistent, and reasonable products for risk assessments and risk characterization?

Section 3: Input Data
Q 4

. T o substantially lessen the number of scenarios and improve computational speed of the model, USEPA OPP evaluated the option of grouping soil map units into classes based on factors that have the greatest impact on pesticide loss due to runoff and ero sion (USDA water quality index, described in Section 3.3). A comparison of runoff volume, pesticide mass, and pesticide concentration outputs showed little difference between the two approaches. Please comment on any implications for using soil grouping cl asses for watershed

- scale modeling.
Q 5

. In order to generate the soil

- land cover

- weather station s cenarios needed for modeling, USEPA OPP took spatial data at different scales and re

- gridded them to the same scale for aggregation (Section 3.2). Based on comparative testing of the model (Sections 2. 4 , 4. 3 , and 5. 4 ), this appears to be a feasible approach. Please comment on the implications for aggregating spatial inputs across varying scales.

Section 4 : Accounting for Time

- of

- Travel Effects
Q 6

. As described in Section s 4 .1 and 4 .2 , USEPA OPP has evaluated an approach for representing concentrations at the pour points of drainage networks that involves

a ggregating upstream drainage areas into integer

- day stream travel

- time zone s , and the use of mathe matical convolution to represent in

- stream dispersive spreading of both influent runoff volume s and pesticide mass es

. Please comment on the u se of this approach, and on any modifications or alternative approaches that US EPA OPP might consider for accomplishing the same ends

. Q 7

. USEPA OPP has not yet investigated possible adaptations of the approach referred to in Q uestion 6 to simulate reactive and/or sorbing chemicals. Please comment on the potential for modifying this approach to simulat e such chemicals.

a. Given the risk assessment purpose of SAM, please comment on the applicability of the described approach in dual

- compartment (aqueous and benthos) system s for representing chemical decay and sorption during transport in surface waters across a range of spatial scales. b. Please recommend any watershed

- scale monitoring datasets that may be suitable for use in evaluati ng estimated concentrations of pesticides that sorb non - negligibly to sediment , and any possible sources of data for representing the benthic sediment layer in surface waters throughout the country.3 Section 5 : Defining the Likely Pesticide Application Window based on Crops and Weather
Q 8

. Pesticide applications often depend on planting dates, crop growth, and harvest da tes, which vary with weather. To improve upon the initial approach of stratifying planting and harvesting dates within states by using a Plant Hardiness Zone map (Section 3.1.4), USEPA OPP tested the potential for using empirical data (USDA weekly crop pro gress reports) and, where such data are incomplete, crop growth models (Sections 5.2 and 5.3).

a. Please comment on the use of crop planting dates and growth stages to provide reference points for pesticide application windows. How applicable is this approac h for predict ing the application window for all types of conventional pesticides (e.g., herbicides, growth regulators, fungicides, insecticides, etc.). For pesticide or pest types for which this approach may not work, what alternative methods are available ? b. As noted in Section 5.2, empirical crop progress data are not available for all crops, all areas, or all years. Please recommend any additional data sources that could provide useful information on spatial and temporal (year

- to

- year) variability in crop planting, growth, and harvesting dates for use in modeling.

c. Where empirical data are missing, USEPA OPP explored the possibility of using crop growth/phenology models such as growing degree days (GDD) to fill in missing data. Please comment on the number of crops with available GDD models and availability of alternative models/data for other crops or crop groupings. Q 9

. The test version of SAM provides the user with options for defining the extent of the pesticide application window and the distribution of pesticide applications across that window (e.g., uniform distribution, triangular distribution). Crop progress report s or, in their absence, crop growth models, offer an option for defining the application window and shape of the distribution (Section 5.1). Please comment on the use of empirical data or models to define the distribution of pesticide applications within a n application window.