invest 2.2.1 nutrient retention model

27
Invest 2.2.1 Nutrient Retention model Yonas Ghile

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Invest 2.2.1 Nutrient Retention model. Yonas Ghile. Why Nutrient Retention model?. ~ 14,000 people die daily G lobal water treatment cost ~$24.6 billion/year Dead fish zone in the Gulf of M exico ~5, 000 mil 2 Non-Point Source is major cause . Biophysical Inputs. Soils - PowerPoint PPT Presentation

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Page 1: Invest 2.2.1 Nutrient Retention model

Invest 2.2.1Nutrient Retention model

Yonas Ghile

Page 2: Invest 2.2.1 Nutrient Retention model

Why Nutrient Retention model?

~ 14,000 people die daily

Global water treatment cost

~$24.6 billion/year Dead fish zone in the Gulf of

Mexico ~5, 000 mil2

Non-Point Source is major cause

Page 3: Invest 2.2.1 Nutrient Retention model

Biophysical Inputs

Land Use/Land CoverNutrient loading, Retention capacity, root depth, crop coefficient

TopographyDigital elevation model, slope threshold

ClimatePrecp, PET

SoilsSoil depth, PAWC

Watershed AreasMain and sub for point of interest and water quality analysis

Page 4: Invest 2.2.1 Nutrient Retention model

Biophysical Inputs...

Page 5: Invest 2.2.1 Nutrient Retention model

1. Estimate Water yield 3. Estimate Pollutant Load value

4. Estimate nutrient retained

5. Estimate pollutant reached the stream

𝐴𝐿𝑉 π‘₯=𝐿𝑉 π‘₯βˆ— 𝐴π‘₯

𝑅𝑒𝑑π‘₯=𝐴𝐿𝑉 π‘₯βˆ—π‘…π‘₯

wheat

Cornforest

2. Calculate flow direction

Page 6: Invest 2.2.1 Nutrient Retention model

Valuation

Time

Load

ing

Critical Loading

6. Estimate Avoided treatment costs

Page 7: Invest 2.2.1 Nutrient Retention model

Some Questions

Where are the pollutant sources?

Where are the pollutant retention areas?

How much is retained?

What is the Value of this retention?

Page 8: Invest 2.2.1 Nutrient Retention model

Informs Policy Makers to Protect areas that retain most

Design management practices that lead to maximum retention

Create payment programs to get most return on investment

Identify services that conflict with water purification

How much retention will we gain or lose under future

management or conservation plans?

Page 9: Invest 2.2.1 Nutrient Retention model

Strengths

Uses readily available and minimum data

Simple, applicable and spatially explicit

Link the biophysical functions to economic values

Values each parcel on the landscape

Page 10: Invest 2.2.1 Nutrient Retention model

Limitations All bio-physio-chemical processes are lumped in one number

export coefficient

Annual basis, misses seasonality

No instream processes and point sources

Less relevant to areas dominated by infiltration excess

Assess one pollutant per run

No saturation in uptake

Page 11: Invest 2.2.1 Nutrient Retention model

Model Calibration and Testing

Sensitivity Analysis to identify most sensitive parameters

Model Calibration using long term average actual data

Find crop coefficient and root depth within acceptable ranges

Model parameter (Zhang constant)

Find export coefficients and vegetation efficiencies within

acceptable ranges

Validate Model by conducting comparisons with observed data or

other model output

Page 12: Invest 2.2.1 Nutrient Retention model

y = 0.81xRΒ² = 0.94p < 0.01

0

100

200

300

400

500

600

0 100 200 300 400 500 600 700

Sim

ulat

ed to

tal p

hosp

horu

s (t)

Observed total phosphorus (t)

Phosphorus loads (kg/yr)

Hainan Island, China

Page 13: Invest 2.2.1 Nutrient Retention model

Hainan Island, China

y = 1.11xRΒ² = 0.92p < 0.01

0

1000

2000

3000

4000

5000

6000

7000

0 1000 2000 3000 4000 5000 6000

Sim

ulat

ed to

tal n

itrog

en (t

)

Observed total nitrogen (t)

Nitrogen Loads (kg/yr)

Page 14: Invest 2.2.1 Nutrient Retention model

Hands-on SessionRun the water yield model

Page 15: Invest 2.2.1 Nutrient Retention model

Hands-on SessionRun the nutrient retention model

Page 16: Invest 2.2.1 Nutrient Retention model

Hands-on SessionRun the valuation model

Page 17: Invest 2.2.1 Nutrient Retention model

Hainan Island, China

Actual (2008)

IEM RNF

No Expansion

IncreaseNo changeDecline

Page 18: Invest 2.2.1 Nutrient Retention model

Baoxing, China

Retained TN Retained TP

High

Low

High

Low

Page 19: Invest 2.2.1 Nutrient Retention model

Scenarios for Mine Expansionin Columbia

Current Mines

Permits Granted

Permits Pending

All possible permits

Page 20: Invest 2.2.1 Nutrient Retention model

Columbia

Permits Granted Permits Pending All possible Permits

Change in Nitrogen Export (kg/ha/yr)

Page 21: Invest 2.2.1 Nutrient Retention model

Columbia

High Impact Zones should avoided

Permits Granted Permits Pending All possible Permits

Page 22: Invest 2.2.1 Nutrient Retention model

Coming up soon

Improve vegetation retention rates

Include Point source pollutant

Include bacterial contamination

Improve pollutant load adjustment

Tier 2 nutrient retention model

Page 23: Invest 2.2.1 Nutrient Retention model

Hands-on Session

Any idea how you would use the Nutrient Retention Model in your work?

Page 24: Invest 2.2.1 Nutrient Retention model

How Does it Work?

β€’ Pollutant Load Value:

β€’ Hydrologic Sensitivity Score:

β€’ Adjusted Loading Value:

𝐿𝑉 π‘₯=𝐸π‘₯βˆ—π΄π‘₯

= =log

*

Page 25: Invest 2.2.1 Nutrient Retention model

How Does it Work?...

𝑃𝑉𝑆𝑅π‘₯=βˆ‘π‘‘=0

π‘‡βˆ’1 π‘‡π‘œπ‘‘ π‘Ÿπ‘’π‘‘π‘Žπ‘–π‘›π‘₯βˆ—π‘€πΆ(1+π‘Ÿ )𝑑

forestStream

Pollutant input

Ywheat

Cornforest

Page 26: Invest 2.2.1 Nutrient Retention model

How Does it Work?...Removal of polluntats by vegetation and soil along the flowpaths is calculated as follows

Page 27: Invest 2.2.1 Nutrient Retention model

Valuation

Time

Load

ing

Critical Loading

)_1(**)(_CNLLoadAnnretainedpCostValuewp xx