Application of APEX and CEEOTSWAPP for Forestry

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Application of APEX and CEEOT-SWAPP for Forestry

• Ali Saleh ________________________________________
  ________________________

This study was funded by National Council for Air
and Stream Improvement NCASI
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Introduction

• There is an increase in nutrients and sediment
  losses from forested watersheds due to
  silvicultural practices
• Silviculture becoming a part of TMDL (total
  Maximum Daily Load) issue
• Field and watershed experiments to assess these
  losses are mostly tedious, time consuming, and
  expensive
• There is a need for an assessment tool (model),
  to evaluate these losses

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APEX model

• APEX (Agricultural Policy/Environmental eXtender)
  is a daily time-step model that originally was
  designed to simulate the edge-of-field runoff
  volume, nutrient concentration, and leach loading
  from agricultural land.
• This model has been used intensively for
  evaluation of point and non-point source pollution

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Components of the APEX Model
Weather Hydrology Erosion (wind and
water) Nutrients (N and P) Pesticides Crop
growth Tillage Management Routing Reservoirs Groun
dwater Grazing Manure management
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Objectives

• To modify the APEX model to simulate the effect
  of silvicultural practices on stream flow and
  loading of sediments and nutrients
• Test the modified APEX using data from various
  region of U.S.

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APEX modifications
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Modifications of APEX for Forestry
Rainfall
Evaporation (LE)
Canopy storage function of
max interception per event above ground
plant material (leaf area index)
Rainfall interception
Fall through
Evaporation
Litter storage function of
weight of litter
Runoff
ET
Quick Return Flow
Soil Storage
Lateral Flow to downstream sub area
Percolation to groundwater
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More modifications for forestry

• Soluble P upward movement by evaporation
• Nutrient enrichment ratio parameters
• Partial burning of above ground plant material

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Alto Watersheds
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Alto watersheds

• Measured flow, sediment, and nutrients (NO3-N,
  PO4-P, Organic-N and Particulate-P,total-N, and
  total-P) from
• Nine small watersheds (2.7 ha)
• 1980 Pretreatment
• 1981-85 Post-treatment
• 1999-01 Pretreatment
• 2002-03 Post-treatment
• Three large watersheds (70-135 ha)
• 1999-01 Pretreatment
• 2002-03 Post-treatment
• The treatments for nine small (included three
  replicates) and three large watersheds
• Intense (SHR)
• Conventional (CHP)
• Control (CON)

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SHR Treatment Operations
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Sheering
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Windrowing
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Burning
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CHP Treatment Operations
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Roller Chopping
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After Burning
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Table 2. Major soils in Alto watersheds
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Predicted (a) and measured (b) storm runoff for
different treatments
a
b
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Predicted (a) and measured (b) sediment loss for
different treatments
a
b
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Predicted (a) and measured (b) total-P for
different treatments
a
b
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Predicted and measured total-N for different
treatments
a
b
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Simulation results (average annual runoff and
sediment loss) for no roads and for roads within
given density and slope ranges
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Forestry Management Scenarios

• Filter strip effect (streamside management zones,
  SMZ)
• 10-m width on each side of stream
• various filtering efficiency
• Forest roads
• 6.1-m width
• density (1 to 3 km km-2)
• various slopes (1 to 15)

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Conclusions (Alto Watershed)

• Similar to what observed, simulated flow,
  sediment, and nutrients losses significantly
  increased on clear-cut watersheds as compared to
  control watersheds
• APEX reasonably simulated herbicides losses from
  treated watersheds
• Apex simulation of nine and three large
  watersheds showed that the APEX capability to
  simulate the forestry conditions at different
  scales
• In general the modified APEX performance was
  encouraging considering
• Forestry losses are small in magnitude
• Some difficulties in measured data

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Dry Creek Watershed

• Georgia

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Decatur County, Southwest Georgia Lower Flint
River Watershed
Decatur County, Southwest Georgia
Lower Flint River Watershed
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Dry Creek Watershed
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• Watershed Scale Treatments
• Treatment/Harvesting (Watersheds B
  C)
• Reference/Undisturbed (Watersheds A D)
• SMZ Treatments
• Partial Harvest SMZ
• Undisturbed SMZ

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Gibbs Farm Basin

• Georgia

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Objective 1

• To Evaluate and compare APEX predictions of SMZ
  reductions in stream water sediment and nutrient
  levels from mixed landuse watersheds in the
  Georgia Coastal Plain with those generated from
  the Riparian Ecosystem Management Model (REMM)

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Objective 1. Selected site for testing APEX for
SMZsData is available from Fox Den Field
located at the University of Georgia Gibbs
watershed near Tifton, Georgia
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Managed three-zone buffer system
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Objective 2

• utilize CEEOT-SWAPP to evaluate forested SMZ
  influences on water quality within a mixed
  landuse watershed

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Objective II Simulation of Gibbs Farm basin
using CEEOT-SWAPP programThe data is obtained
from Gibbs farm watershed, for over seven years
(October 1996 through November 2004)The Gibbs
farm basin is typical of the region with 23
fields identified within the 123 ha (304 ac)
basin with an average field size of 3 ha (7.4 ac)
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CEEOT

• Comprehensive Economic and Environmental
  Optimization Tool

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Farm-level Economic Model

• A whole-farm annual model that simulates the
  economic impacts of a wide range of scenarios on
  privately owned agricultural operations
• Model is calibrated with extensive data on farm
  practices, budgets and other watershed
  information
• Includes a number of simulation and optimization
  routines.
• A whole-farm annual model to simulate economic
  impacts of scenarios on farms
• Includes a number of simulation and optimization
  routines

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Watershed Scale Model (SWAT)

• SWAT is a daily-time step model
• SWAT was developed to predict the effect of
  different management scenarios on water quality,
  sediment yields, and pollutant loading in rural
  watersheds
• SWAT allows data input via Geographical
  Information System (GIS)

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Field-scale Model (APEX)
APEX was designed to simulate the edge-of-field
runoff volume, nutrients and loadings of sediment
and nutrients from crop and animal producing lands
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SWAT Strengths

• Comprehensive Hydrologic Balance?
  Physically-Based Inputs? Plant Growth
  Rotations, Crop Yields? Nutrient Cycling in
  Soil? Land Management - BMP Tillage,
  Irrigation, Fertilizer, Pesticides, Grazing,
  Rotations, Subsurface Drainage,
• Urban-Lawn Chemicals, Street Sweeping
• Generates the required data bases using AVSWAT
  from
• existing databases
• Stream routing function
• Input from other models and point sources, etc.

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SWAT Current Limitations

• Lack of concentrated animal feeding operations
  and related manure application routines
• Lacks of spatially explicit hydrologic response
  units
• Lacks multiple cropping system
• Empirical approach to simulate filter strips
• Improved simulation of riparian zones and other
  conservation practices

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APEX Strengths and Limitations

• Strengths
• Animal production
• Multi-crop system
• CO2 simulation
• Detailed filter strips simulation
• Strong forestry component
• Weaknesses
• Lack of GIS interface
• Lack of secondary routing component

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APEX-SWAT Linkage
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Simulated Landuse by APEX
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Input daily APEX edge-of-field
flows, and sediment and nutrient
loadings, at SWAT subbasin outlet
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CEEOT-SWAPP

• Automated CEEOT-SWAPP
• http//tiaer.tarleton.edu/transfer/CEEOT-SWAPP/

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Sample of CEEOT-SWAPP output
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What is next ?

• Complete the testing of modified APEX for
• Dry Creek watershed in Georgia
• Gibbs Farm Basin

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Thank You

• Questions