# A Comparison **of PRZM 3 and PRZM 5 Simulations**  Lauren Padilla 1 

### , Michael Winchell 1 

### , Russell Jones 2 

### , Scott Jackson 3 1. Stone Environmental, 2. Bayer CropScience,

3. BASF Corporation 

### 28 October 2014 1

# Overview Objective: To quantify differences in model results due to updates from PRZM 3 to PRZM 5. Approach:  

## Comparison of PRZM 3 and PRZM 5 runs for 59 standard scenarios  

## Varied Koc at 100, 10000, 1 million  

## Varied CAM 1 and CAM 2  

## All other input parameters held constant 2

# Background  

## PRZM 5 introduced in the Surface Water Concentration Calculator  

## PRZM 5 is an update of PRZM 3 to Fortran 2003  

## Mainly internal code changes  

### Modules easier to read and search  

### Variables easier to understand  

## Bug fixes, including to degradation, erosion, and application routines  

## Non - functioning and unused routines eliminated 3

# Input Parameters Assumed All Runs

4

**Pa ra**  **meter Va**  **lue Applica**  **tion Method**  CAM 1 or 2 **Applica tion**  **Ra te**  2 @ 1.25 kg /ha **Applica tion**  **In terval**  7 da ys **Fir st Applica**  **tion Da**  **te** 1 month after emergence **Foliar Half Lif e**  50 da ys **Soil Half Lif e**  50 da ys **Ko c**  100, 10,000 or 1 million

# Regression Comparison of Daily Loads - R 2

5  Generally very good agreement  Some scenarios where loadings do not occur on the same day

R2 = 0.995 R2 = 0.185

**Koc = 10000 Slide 5** 

**LP7** The formulas are the same, it's a difference of interpretation of what is considered the 'model' and what is 'observation'.

Calling it NSE is like saying PRZ3 are the observations and PRZM5 is the model. Calling it R2 is like saying, PRZM3 is the observed dependent variable and we are testing the model PRZM3_estimated = PRZM5 (the y=x line) against it. I think more people have heard of R2. Both concepts imply that we are looking at how well the time series match with a 1:1 relationship. Lauren Padilla, 10/22/2014

# Comparison of R 2 

# Values for Daily Load Time Series

6 **Koc CA** **M 1**  **CA M**  **2**7 **Koc** 

# Comparison of R 2 

# Values for Daily Load Time Series

**CA M**  **1 CA** **M 2** 

# Comparison of R 2 

# Values for Daily Load Time Series

8 **Koc CA** **M 1**  **CA M**  **2**

# Comparison of R 2 

# Values for Daily Load Time Series

9 **Koc CA** **M 1**  **CA M**  **2**

# Comparison of R 2 

# Values for Daily Load Time Series

10  Scenarios with lower R 2 values have irrigation applied.  Foliar applications at low Koc tend to have lower R 2

# Bulk Loading Time Series, MS Cotton Koc = 10000, CAM = 1

11 R2 = 0.99 Without irrigation

# Bulk Loading Time Series, ID Potato Koc = 10000, CAM = 1

12 R2 = 0.19 With irrigation

# Load Time Series, ID Potato, Koc = 10000, CAM = 1

13 • Shifted time - series primary reason for low R2 • No changes to scenario data • Irrigation applied on slightly dif ferent days

# Conclusions from R 2 

# Comparison  

## Generally good agreement between PRZM 3 and PRZM 5 in both timing and magnitude.  

## Some scenarios with irrigation have low R 2.  

## R 2 

## does not have a strong trend with Koc.  

## CAM 2 runs have slightly lower R 2 

## than CAM 1 in some cases and significantly lower R 2 

## in a few cases. 14

# Comparison of Bulk 30 - yr Cumulative Load

15 **Koc CA** **M = 2**

# Comparison of Soluble 30 - yr Cumulative Load

16 **CA M = 2** 
**Koc**

# Comparison of Sorbed 30 - yr Cumulative Load

17 **Koc CA** **M = 2**

# Comparison of 30 - yr Cumulative Eroded Sediment Losses and Runoff

18

# Conclusions from Cumulative Comparison  

## Cumulative runoff and erosion are very similar.  

## Bulk, soluble, and sorbed loadings are very similar.  

## Slightly greater variations in soluble loadings than sorbed loadings at low Koc.

19

# Comparison of 90 th 

# % - ile Annual Maximum Daily Loads

20 **Koc CA** **M 2**  **CA M**  **1**

# 90 th 

# % - ile Annual Maximum, Koc = 100

21 **CA M = 1** 

# 90 th 

# % - ile Annual Maximum, Koc = 100

22 **CA M = 1** 

# 90 th 

# % - ile Annual Maximum, Koc = 1 million

23 **CA M = 1** 

# 90 th 

# % - ile Annual Maximum, Koc = 1 million

24 **CA M = 1** 

# Annual Max Distributions, MS Cotton

25 **Koc CA** **M = 1**

# Annual Max Distributions, ID Potato

26 **Koc CA** **M = 1**

# Conclusions  

### Generally good agreement between PRZM 3 and PRZM 5 in both timing and magnitude for bulk daily time series and cumulative load totals.  

### CAM 2 time series slightly more sensitive than CAM 1 to model changes from PRZM 3 to 5.  

### Slight differences in timing do not result in major differences in annual maximums.  

### Soluble and sorbed loadings are similar in PRZM 3 and PRZM 5; models have similar partitioning.  

### Good agreement in distributions and 90 th 

### percentile annual maximum daily loads at all Kocs and CAMs. 27