Hydroeconomic analysis framework for agricultural water ... · 7 8 9 Corn 0.5 0.0 0.5 1.0 Change in land (x100) 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Tomato 0 6 7 0. water management. water

Hydroeconomic analysis framework for agricultural watermanagement

Marco P. Maneta, PhD

Geosciences DepartmentThe University of Montana, Missoula

[email protected]

October 4, 2013

Integrated hydroeconomic analysisObjectives

How do droughts impact crop mix and water use?

How does agricultural change impact water availability and otherwater uses?

How do farmers respond to water policy?

What water policy maximizes the social and economic benefits ofirrigated agriculture while mitigating the negative impacts on otherwater users

M. Maneta (UM) Hydroeconomic analysis October 2013 2 / 17

Integrated hydroeconomic model

Optimization variables:- Crop mix and acreage- Hired and family labor used- Water applied- Amounts of seeds used- Amount of fertilizer used- Amount of pesticides used- Capital- Energy/electricity used

Productionfunction

Climate Flows

Production costs

Social constraints:- Available labor

Physical constraints:- Available land

Policy constraints:- Water allocation rules- Environmental flow mandates- Nitrogen export limits - Subsidies on production- Subsidies on acreage- Minimum wages

External price of inputs:- Price of fertilizers

- Price of seeds- Price of hired labor

- Price of energy- Price of water

Market price of crops

Environmental Social Farmer revenues

Trade-off curves showing the best(Pareto-optimal) policies

Risk aversion costs

PrecipitationGW availableSW available

Crop mixEvapotranspirationGWdemandSW demand

Optimization objectives

Agroeconomic model

Hydroclimatic model

Gross revenue


Economic model of agricultural production

maxX

net =∑j

pjqj(Xi ,j ,Paramsi ,j)−∑i

ciXi ,j−1

2ψjX

2land ,j

maxX

net =∑j

pj qj(Xi ,j ,Paramsi ,j) −∑i

ciXi ,j −1

2ψjX

2land ,j

qj (Xi ,j ,Paramsi ,j) = τj

(∑i

βi ,j Xi ,jρ

) νρ

Xi ,j =

Alfalfa Corn · · · cropj

land...

water...

.... . .

...inputi · · · xi ,j



maxX

net =∑j


ciXi ,j−1

2ψjX

2land ,j

maxX

net =∑j


ciXi ,j −1

2ψjX

2land ,j


(∑i

βi ,j Xi ,jρ

) νρ

Xi ,j =


land...

water...

.... . .




maxX

net =∑j


ciXi ,j−1

2ψjX

2land ,j

maxX

net =∑j


ciXi ,j −1

2ψjX

2land ,j


(∑i

βi ,jXρi ,j

) νρ


(∑i

βi ,j Xi ,jρ

) νρ

Xi ,j =


land...

water...

.... . .




maxX

net =∑j


ciXi ,j−1

2ψjX

2land ,j

maxX

net =∑j


ciXi ,j −1

2ψjX

2land ,j


(∑i

βi ,j Xi ,jρ

) νρ

Xi ,j =


land...

water...

.... . .




maxX

net =∑j


ciXi ,j−1

2ψjX

2land ,j

maxX

net =∑j


ciXi ,j −1

2ψjX

2land ,j


(∑i

βi ,j Xi ,jρ

) νρ

Xi ,j =


land...

water...

.... . .




maxX

net =∑j


ciXi ,j −1

2ψjX

2land ,j


(∑i

βi ,j Xi ,jρ

) νρ

Xi ,j =


land...

water...

.... . .



Hydrologic engine: HEC-HMSSimulation of water availability

Water distribution and availability is simulated using HEC-HMS


Remote Sensing of agricultural activityLandsat, MODIS

Information on crop acreage, yield and evapotranspiration


Recursive hydroeconomic model calibrationSatellite data assimilation stage

Information gets incorporated in the model as it becomes available.The model improves with time as more information is assimilated into themodel

Data Assimilation FrameworkEnsemble Kalman Filter

Agroeconomic model

Agronomic model parameterget sequentially updatedwith the latest observations

Satellite Data:- Crop Acreage- Yield- Evapotranspiration

Hydrologic Data:- Water available- Streamflows- Water quality- Diversion points- Well fields

Additional Data:- Labor data- Irrigation technology- Crop Calendar


Ensemble Kalman Filter...or how quantity can be a substitute of quality








Test runFarm in Yolo county, CA

Demonstration for a farm in California

610 ac commercial farm

All crops under irrigation

Farmer is not water constrained

Four crops (Alfalfa, wheat, corn, and tomato)

Three inputs (land, water, labor)

Xi ,j =

Alfalfa Wheat Corn Toms

land...

water...

labor. . .

...


ResultsData assimilation stage and parameter identification

0.0

0.1

0.2

0.3

0.4

0.5

0.6

β

Alfalfa

Bland Bwater Blabor

Wheat Corn

0.0

0.1

0.2

0.3

0.4

0.5

0.6

β

Tomato

0.66

0.68

0.70

0.72

0.74

σ

0.66

0.68

0.70

0.72

0.74

σ

0 5 10 15 20Assimilation cycles

10

15

20

25

30

τ




10

15

20

25

30

τ


ResultsReproduction of baseline observations

120 140 160 180 200 220 240Land (ac.)

0.000

0.005

0.010

0.015

0.020

0.025

0.030

0.035

Pro

babili

ty

Alfalfa

140 150 160 170 180 190 200 210 220Land (ac.)

0.00

0.01

0.02

0.03

0.04

0.05Wheat

70 80 90 100 110 120 130 140Land (ac.)

0.00

0.01

0.02

0.03

0.04

0.05

0.06Corn

50 100 150 200 250 300Land (ac.)

0.000

0.005

0.010

0.015

0.020Tomato

200 400 600 800 1000 1200 1400Water (cf/ac)

0.0000

0.0005

0.0010

0.0015

0.0020

0.0025

0.0030

0.0035

Pro

babili

ty

250 300 350 400 450 500 550 600 650 700Water (cf/ac)

0.000

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

200 250 300 350 400 450 500 550 600 650Water (cf/ac)

0.000

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0 200 400 600 800 1000 1200Water (cf/ac)

0.0000

0.0005

0.0010

0.0015

0.0020

0.0025

0.0030

0.0035

0.0040

0.0045

500 1000 1500 2000 2500 3000 3500 4000Labor(hrs)

0.0000

0.0002

0.0004

0.0006

0.0008

0.0010

0.0012

Pro

babili

ty

300 400 500 600 700 800 900 1000Labor(hrs)

0.000

0.001

0.002

0.003

0.004

0.005

0.006

0.007

200 300 400 500 600 700 800 900 1000Labor(hrs)

0.000

0.001

0.002

0.003

0.004

0.005

0 5000 10000 15000 20000 25000Labor(hrs)

0.00000

0.00005

0.00010

0.00015

0.00020


ResultsReproduction of baseline observations

120 140 160 180 200 220 240Land (ac.)

0.000

0.005

0.010

0.015

0.020

0.025

0.030

0.035

Pro

babili

ty

Alfalfa

140 150 160 170 180 190 200 210 220Land (ac.)

0.00

0.01

0.02

0.03

0.04

0.05Wheat

70 80 90 100 110 120 130 140Land (ac.)

0.00

0.01

0.02

0.03

0.04

0.05

0.06Corn

50 100 150 200 250 300Land (ac.)

0.000

0.005

0.010

0.015

0.020Tomato

200 400 600 800 1000 1200 1400Water (cf/ac)

0.0000

0.0005

0.0010

0.0015

0.0020

0.0025

0.0030

0.0035

Pro

babili

ty

250 300 350 400 450 500 550 600 650 700Water (cf/ac)

0.000

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

200 250 300 350 400 450 500 550 600 650Water (cf/ac)

0.000

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0 200 400 600 800 1000 1200Water (cf/ac)

0.0000

0.0005

0.0010

0.0015

0.0020

0.0025

0.0030

0.0035

0.0040

0.0045

500 1000 1500 2000 2500 3000 3500 4000Labor(hrs)

0.0000

0.0002

0.0004

0.0006

0.0008

0.0010

0.0012

Pro

babili

ty

300 400 500 600 700 800 900 1000Labor(hrs)

0.000

0.001

0.002

0.003

0.004

0.005

0.006

0.007

200 300 400 500 600 700 800 900 1000Labor(hrs)

0.000

0.001

0.002

0.003

0.004

0.005

0 5000 10000 15000 20000 25000Labor(hrs)

0.00000

0.00005

0.00010

0.00015

0.00020


ResultsSimulation of scenarios

Test drive: New water allocation rules that results in:- Scenario 1: 30% reduction in water available- Scenario 2: 50% reduction in water available


ResultsImpact of a reduced access to water

0.5 0.4 0.3 0.2 0.1 0.0 0.1 0.2Change in land (x100)

0

1

2

3

4

5

6

7

8

9

Pro

babili

ty

Alfalfa

0.3 0.2 0.1 0.0 0.1Change in land (x100)

0

2

4

6

8

10

12Wheat

0.5 0.4 0.3 0.2 0.1 0.0 0.1 0.2Change in land (x100)

0

1

2

3

4

5

6

7

8

9Corn

0.5 0.0 0.5 1.0Change in land (x100)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5Tomato

0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 0.1Change in water (x100)

0

1

2

3

4

5

6

7

Pro

babili

ty

0.5 0.4 0.3 0.2 0.1 0.0 0.1 0.2 0.3 0.4Change in water (x100)

0

1

2

3

4

5

6

0.8 0.6 0.4 0.2 0.0 0.2 0.4 0.6Change in water (x100)

0

1

2

3

4

5

1.0 0.5 0.0 0.5 1.0 1.5Change in water (x100)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

0.8 0.6 0.4 0.2 0.0 0.2 0.4 0.6 0.8Change in labor (x100))

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Pro

babili

ty

0.4 0.2 0.0 0.2 0.4Change in labor (x100))

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0.6 0.4 0.2 0.0 0.2 0.4 0.6 0.8Change in labor (x100))

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

1.0 0.5 0.0 0.5 1.0 1.5 2.0Change in labor (x100))

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

30% Restriction

50% Restriction

Realocation of resources under water restrictions (relative change respect to baseline)


ResultsSummary of impacts

Baseline 30% reduction 50% reduction

Water available 2300 1610 1150Water used 2060 1610 1150Shadow value $0.0 $9.00 $25.3% loss net rev -2.76 -11.3% change hiring -11.7 -28.9


Conclusions

Hydroeconomic models can be a valuable tool to inform policy andwater management

Coupled with remote sensing in a data assimilation framework permitsoperationalization

Hydroeconomic models may help develop water markets

Assimilation of frequent RS data permits the detection of gradualchanges in farming practices

Impact of water shortage on rural economies is not proportional toshortage amounts


Conclusions







Conclusions







Conclusions







Conclusions







THANK YOU


Hydroeconomic analysis framework for agricultural water ... · 7 8 9 Corn 0.5 0.0 0.5 1.0 Change in land (x100) 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Tomato 0 6 7 0. water management. water

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