©2003 institute of water research, all rights reserved water quality modeling for ecological...

©2003 Institute of Water Research, all rights reserved

Water Quality Modelingfor Ecological Services under

Cropping and Grazing Systems

Da OuyangJon Bartholic

Institute of Water ResearchMichigan State University

©2003 Institute of Water Research, all rights reserved

Water Quality Modeling

Surface Water Quality- Soil Erosion- Sediment Delivery- Nutrient Loading (P, N)

Groundwater Quality- Pesticide / Nutrient Leaching

©2003 Institute of Water Research, all rights reserved

Water Quality Modeling

Surface Water Quality Modeling- RUSLE- SEDMOD- AGNPS / SWAT- MARI & Nutrient Loading Coefficients

Groundwater Quality Modeling- WIN-PST (Pesticide Screening Tool)

©2003 Institute of Water Research, all rights reserved

RUSLE

Revised Universal Soil Loss Equation

©2003 Institute of Water Research, all rights reserved

RUSLE

A = R K LS C P

A = Soil loss in tons per acre per yearR = Rainfall-runoff erosivity factorK = Soil erodibility factorS = Slop steepness factorL = Slope length factorC = Cover-management factorP = Support practice factor

©2003 Institute of Water Research, all rights reserved

SEDMOD

Spatially Explicit Sediment Delivery Model

©2003 Institute of Water Research, all rights reserved

Spatially Explicit Sediment Delivery Model (SEDMOD)

SDR = 39 A –1/8 + DP

Where SDR = sediment delivery ratio

A = watershed area in square km

DP = difference between the composite delivery

potential and its mean value

©2003 Institute of Water Research, all rights reserved

SEDMOD

Delivery Potential composite layer in GRID

DP = (SG)r(SG)w + (SS)r(SS)w + (SR)r(SR)w +

(SP)r(SP)w + (ST)r(ST)w + (OF)r(OF)w

Where SG = slope gradient

SS = slope shape

SR = surface roughness

SP = stream proximity

ST = soil texture

OF = overland flow index

r = parameter rating (1-100)

w = weighting factor (0-1)

©2003 Institute of Water Research, all rights reserved

Sediment Yield

SY = A * SDR

Where SY = Sediment Yield A = Gross Soil Loss SDR = Sediment Delivery Ratio

©2003 Institute of Water Research, all rights reserved

WIN-PST

Window-Based Pesticide Screening Tool

©2003 Institute of Water Research, all rights reserved

WIN-PST(Window-Based Pesticide Screening Tool)

Assess relative likelihood of pesticide loss from - field boundaries via runoff - below the root zone via percolation

Overall risk ratings are based on a matrix of- Pesticide (toxicity, application method and rate)- Soil (Soil texture, hydrologic group, slope, water table)

©2003 Institute of Water Research, all rights reserved

MARI

Manure Application Risk Index

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MARI(Manure Application Risk Index)

Identify areas where winter-time spreading of manure may cause potential risk for runoff losses of N or P

12 Field parameters: Soils; Slope; Soil Test P;

Concentration Water Flow; Residue/Cover;

Surface Water Setback; Vegetative Buffer Width;

Manure P / N Application Rate; Manure Application Method;

Others.

©2003 Institute of Water Research, all rights reserved

Data

• DEM (Digital Elevation Model, 30-meter)• SSURGO Soil Data (Soil Survey Geographic Database)• Landuse / Land cover data• Crop Residue Management Data (CTIC)• Other - EPA BASINS

Data and Tools for Water Quality Modeling

Previous Studies

Stony Creek Study

Corn-Corn Corn-Soybean Soybean-Wheat

Erosion 182,000 154,000 67,000

Sediment 61,000 52,000 28,000

Phosphorus 129 112 59

Estimated soil loss, sediment and phosphorus inStony Creek Watershed (tons / year)

y = 2.1343x

R2 = 0.9943

0

5

10

15

20

25

30

0 5 10 15

Suspended Solids (ton)

To

tal P

ho

sp

ho

rus (

kg

)

Measured Phosphorus and Suspended SolidsIn Sycamore Creek Watershed, MI

Findings from other study (Randall et al. 1997)

NO3 – losses from row crops (corn, soybean) were 30-50 times greater than losses from perennial crops such as Alfalfa

Atrazine Leaching Risk Mapping

Great Lakes Basin

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Estimated Potential Sediment LoadingContributed from Cropland (tons/yr.)

Questions & Discussion

(C = Cover-management factor)