GIS Analysis of Soil Erosion and Chemical Concentration for White Rock Reservoir Watershed

1
GIS AnalysisofSoil Erosion and Chemical
Concentration for White Rock Reservoir Watershed

• GIS Master Project
• By
• Ovi Sipos
• Advisor Dr. Tom Brikowski
• UT Dallas
• November 2007

2
Introduction

• This study discuses the possibility of applying
  GIS to develop and analyze a spatial model of
  soil erosion and chemical concentration for the
  area of study.
• Several studies have been developed to estimate
  soil erosion and sediment transport at reduce
  scales, but just a few attempts have been made to
  provide direct mapping of spatial models.
• The importance of this study comes from the fact
  that a large scale model can be developed using
  the methodology investigated here.
• The purpose of this study is to determine the
  influence of agricultural and non-agricultural
  practices on the water quality correlated with
  soil erosion due to surface water.
• Several factors that influence soil erosion and
  sediment transportation are identified and
  analyzed such as runoff, land use, soil types and
  hydrological soil groups.

3
Objective

• The project objective can be divided in three
  objectives as following
• To establish a GIS model for the soil loss and
  sediment transportation due to water erosion
• To develop a GIS model for the chemical
  concentration in the study area in correlation
  with the land use practices
• To determine the relationship between the two
  models

4
Limitations

• Data availability and accuracy
• no spatial data for pesticide use
• pesticide data available just by zip code
• pesticide and precipitation data available on a
  monthly or annual average does not consider
  variations from year to year which is a negative
  factor

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Data sources

• Soil type data - Natural Resources Conservation
  Service http//www.ftw.nrcs.usda.gov/stat_dat
  a.html
• Land use / Land cover
• www.dfwinfo.com
• Pesticide data for Texas Texas Environmental
  Profile
• http//www.texasep.org
• Precipitation data Natural Resources
  Conservation Service
• http//www.ftw.nrcs.usda.gov/stat_data.html
• Digital Elevation Model USGS
• www.usgs.gov

6
Literature review

• The article by Van Meter, P.C., Land, L.F., and
  Brawn (1996) titled Water- quality trends using
  sediments cores from White Rock Lake, Dallas,
  Texas summarize the principal findings documents
  in a report on water quality for White Rock Creek
  Basin using dated sediment cores. The study used
  sediment cores to reconstruct water-quality
  conditions.
• City of Dallas - Drainage Design Manual provides
  criteria and design recommendations for storm
  drainage facilities in Dallas County. This manual
  is a valuable source of technical information
  that is specifically tailored for Dallas County
  and describes concepts and methods used in
  hydraulic design runoff, curve number method,
  rational method etc.
• The book Randall J. Charbeneau (2000) titled
  Groundwater Hydraulic and Pollutant Transport
  analyses the physical and chemical processes that
  control the transport and fate of hazardous
  substances in the subsurface environment. The
  book also provides important information about
  hydraulic and erosion cocepts.
• The article ArcGIS Hydro Data Model Structure and
  Definitions by David R. Maidment and Timothy L.
  Whiteaker (2000) provides and overview of the
  ArcGIS hydro data model that contains geospatial
  and temporal data describing the surface water
  flow system of the landscape.
• The article Modeling Agrichemical Transport in
  Midwest Rivers Using GIS by Pawel Mizgalewicz and
  David R. Maidment describes a method for
  regionalizing watershed and scaling water quality
  estimates.
• Several methods have been developed which involve
  the application of soil erosion equations and
  models and often require complex calculations. 
  Some examples include Journal of Paleolimnology
  (Bradbury, Van Meter 1996), Water Erosion
  Prediction Project (Cochrane and Flanagan, 2003),
  Sediment Delivery Distributed (SEDD) (Fernandez
  et al., 2003), Soil and Water Assessment Tool
  (Arnold et al., 1998 Tripathi et al., 2004),
  Hillslope Erosion Model (Wilson et al., 2001).

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Analysis

• The methodology followed in this paper is divided
  into the following steps
• Hydrological modeling of the area
• Modeling of soil loss as a result of water
  erosion
• Determination of rainfall and runoff relationship
• Modeling of chemical concentration for the area
  of study
• Soil Loss Chemical Concentration relationship

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1. Hydrological modeling of the area of study

• The purpose of this hydrological analysis is to
  determine the drainage areas and the discharge
  points specific for each area. The following
  steps describe this process.

Flow Direction
Flow Accumulation
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Hydrological modeling of the area of study-Cont
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Hydrological modeling of the area of study-Cont
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Hydrological modeling of the area of study-Cont
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Hydrological modeling of the area of study-Cont
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2. Modeling of soil loss as a result of water
erosion

• Revised Universal Soil Loss Equation (RUSLE)
• ARKLSCP
• Where
• A is the annual soil loss (t acre-1 yr-1)
• R is the rainfall erosion factor (MJ mm acre-1
  h-1 yr-1),
• K is the soil erodibility factor (t h MJ-1
  mm-1),
• L is the slope length (unitless),
• S is the slope gradient or steepness
  (unitless),
• C is the crop management factor (unitless) and
• P is the erosion control practice factor
  (unitless) (Wischmeier and
  
  
  
  
  Smith, 1978).

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Modeling of soil loss as a result of water
erosion-Cont

• ARKLSCP
• Support Practice Factor (P) describes the
  supporting effect of practices like contouring,
  cropping and terraces. Most of the time this
  variable is set to 1 in land management
  applications.

• Erosivity Factor (R) value for the study area was
  derived from precipitation records for Texas and
  is 291.

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Modeling of soil loss as a result of water
erosion-Cont

• ARKLSCP
• Soil Erodibility Factor (K) represents the
  susceptibility of soil to erosion and the rate of
  runoff. Table below presents the k values
  specific for certain soil types

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Modeling of soil loss as a result of water
erosion-Cont

• ARKLSCP
• Slope Length and Steepness Factor (LS) represents
  erodibility due to combination of slope length
  and steepness.
• LS (Flow Accum Cell Size/22.13)0.4 (sin
  slope/0.0896)1.3

Flow Accumulation
Slope
LS
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Modeling of soil loss as a result of water
erosion-Cont

• ARKLSCP
• Cover and Management Factor (C) represents the
  effect of soil cover and soil-disturbing
  activities on soil erosion. The values for C
  factor were input manually into the land use
  shape file based on land use and converted to
  grid.

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x
x
x
x
P-FACTOR
R-FACTOR
C-FACTOR
K-FACTOR
LS-FACTOR
APxRxCxKxLS
SOIL LOSS
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Soil Loss
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3. Determination of rainfall and runoff
relationship

• Determination of Rainfall / Runoff Relationship
  is required in order to assess the transport of
  chemical load throughout the study area. The
  volume of runoff for a grid cell is attributed to
  the quantity of precipitation over that
  particular cell. The procedure used to calculate
  this factor is SCS (Soil Conservation Services)
  Runoff Curve Number equation
• Where Q runoff
• S potential maximum retention
• P rainfall
• CN curve number

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Determination of rainfall and runoff
relationship-Cont
22
Determination of rainfall and runoff
relationship-Cont
23
Determination of rainfall and runoff
relationship-Cont
24
Determination of rainfall and runoff
relationship-Cont
25
Determination of rainfall and runoff
relationship-Cont
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4. Modeling of chemical concentration for the
area of study
Modeling the chemical concentration in the study
area is achieved by defining the mass of chemical
components transported per volume of runoff.
The chemical load estimation for the area is
calculating by taking the product of the expected
chemical concentration and the runoff depth
corresponding to that cell L (kg/year) K x Q
x CH x A Where Q is the runoff (mm/year or
mm/month) K is a constant equals to 10-6 A
drainage area CH chemical concentration
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Modeling of chemical concentration for the
area of study - Cont
The pesticide use data for Texas is available on
the Texas Environmental Profile website and it
can be ranked by state, county or zip code. The
zip code shape file was intersected with the
drainage area polygons shape file to determine
the chemical distribution for each individual
area. The chemical concentration was calculated
in units per square meter. Once the chemical
concentration was calculated a new field was
added to the attribute table for the Chemical
Load.
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Modeling of chemical concentration for the
area of study - Cont
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Modeling of chemical concentration for the
area of study - Cont
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Modeling of chemical concentration for the
area of study - Cont
DA_8
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5. SOIL LOSS-CHEMICAL CONCENTRATION RELATIONSHIP
SPATIAL AUTOCORRELATION FUNCTION Calculates the
cross correlation between the chemical load model
and the actual soil loss model in this
study. The correlation coefficient between the
two models is found to be 0.01 which reflects a
weak correlation between the two models.
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Conclusions
The chemical concentration and soil loss models
developed in this study have shown a possible
method of characterizing the process of
transportation of sediment and chemicals as they
actually contribute to the White Rock
watershed. The method uses data that is publicly
available and synthesizes the data in a
consistent and logical way across the area of
study. The procedure used for this method
utilizes standard ArcMap commands and
functions. The spatial correlation between
chemical concentration and soil loss due to water
erosion is weak therefore the erosion is not a
major factor in this model. The model gives
estimates for average monthly and annual flow as
well as spatial chemical concentration by zip
code. These data dont consider variation within
years and provide accurate pesticide
concentration for certain are which is a real
restriction.
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Conclusions-Cont.
The fact sheet The Water- quality trends using
sediments cores from White Rock Lake, Dallas,
Texas published under the USGS web site provides
important information about the sediment deposits
found in White Rock Lake and the correlation
between the urban land use and use of
insecticide. As you can see from these chats, the
use of DDT, which is a toxic compound of
insecticide, begun in 1939 and widespread use
continued until about 1972 when was prohibited.
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References

• City of Dallas, 2002 Drainage Design Manual
• David R. Maidment. 2003 ArcHydro GIS for Water
  Resources. Redlands California ESRI Press.
• David R. Maidment and Timothy L. Whiteaker
  (2000) ArcGIS Hydro Data Model Structure and
  Definitions
• U.S. Geological Survey (USGS)
• North Central Council of Governments (NCTCOG)
• U.S. Department of Agriculture (USDA)
• Environmental System Research Institute (ESRI)
• Texas Environmental Profile (www.texasep.org)
• Pawel Mizgalewicz and David R. Maidment (2000)
  Modeling Agrichemical Transport in Midwest Rivers
  Using GIS