the effects of climate change on groundwater extraction...

The effects of climate change on groundwater extraction for agriculture and

land-use change

Ernst Bertone Oehninger,C.-Y. Cynthia Lin Lawell, James N. Sanchirico, and Michael R. Springborn

University of California at Davis

August 2016

Motivation

- Population Growth: 9 billion by 2050

- Changes in food consumption habits

- Yields affected by climate change

- Pressure on water resources

- Deforestation- GHG Emissions

- Biodiversity loss

- Agricultural biodiversity

Effects of climate change on groundwater extraction for agriculture and land-use change

• Worldwide, 60% of groundwaterwithdrawn is used in agriculture • In some countries, this can be as high as

90%

• Decline in water table levels

• Climate change has the potential to impact groundwater availability in several ways• Indirectly, by changing agricultural land-

use and agricultural practices• Directly, by changing water availability

Previous Literature • Effects of climate change on farmland values and/or agricultural profits

• Schlenker, Hanemann and Fisher (2006); Deschênes and Greenstone (2007); Fisher et al. (2012); Deschênes and Greenstone (2012); Moore and Lobell (2014); Fezzi and Bateman (2015); Costinot, Donaldson and Smith (2016)

• Effects of climate change on crop yields and/or acreage• Schlenker and Roberts (2009); Ortiz-Bobea (2012); Roberts, Schlenker and Eyer (2013); Ortiz-Bobea (2013); Lee

and Sumner (2015); Miao, Khanna and Huang (2016); Burke and Emerick (2016)

• Effects of climate change on food markets• Lybbert, Smith and Sumner (2014)

• Effects of climate change on irrigation decisions• Olen, Wu, and Langpap (2016)

• Econometric models of the effects of climate change • Hsiang (2016)

• Groundwater use• Dermyer (2011); Pfeiffer and Lin (2012); Mieno and Brozovic (2013); Pfeiffer and Lin (2014a); Pfeiffer and Lin

(2014b); Lin and Pfeiffer (2015); Lin Lawell (2015); Lin Lawell (2016)

• Water demand and/or supply• Schoengold, Sunding and Moreno (2006); Mukherjee and Schwabe (2015)

Hypothesis

Climate variables

Crop selection and acreage

Technology adoption

Water use

Land-use & ag. biodiversity

High Plains Aquifer in Kansas

• 99% of water extracted is used for crop production

• Remaining 1% used for livestock, domestic, and industrial purposes

• Economy of region is based on irrigated agriculture

• The main crops grown in western Kansas, roughly in order of decreasing water intensiveness, are alfalfa, corn, soybeans, sorghum, and wheat

• Corn production accounts for more than 50 percent of all irrigated land

Data Sources

• The High Plains Aquifer (SD, NE, WY, CO, KS, OK, NM, TX)

• 20,000 groundwater-irrigated fields in western Kansas from 1996 to 2012 302k obs.

• Water rights, water use and crop choice from the Water Information Management and Analysis System (WIMAS-Kansas Geological Survey)

Data Sources

• Wells’ characteristics were obtained from the Water Well Completion Records (WWC5) Database (also from KGS).

• Weather data was obtained from the High Plains Regional Climate Center (HPRCC)

• Soil moisture was obtained from NASA’s NLDAS-2 (ArcGIS)

• Crop prices from the USDA – ERS Feed Grains Database and quandl.com.

• Energy prices are from the Energy Information Administration (EIA).

Soil moisture 0-10cm 1996

Soil moisture 0-10cm 2012

Climate Specifications1. Annual average temperature (&sq), annual precipitation (&sq), and annual average humidity.

2. Annual maximum temperature (&sq), annual precipitation (&sq), and annual average humidity.

3. Monthly average temperature (&sq), monthly precipitation (&sq), and monthly average humidity.

4. Monthly fraction of days with maximum temperature > 30C (&sq), monthly precipitation (&sq), and monthly humidity.

5. Average temperature over the last 3 years (&sq), total precipitation over the last 3 years (&sq) , and annual averagehumidity.

6. Average temperature over the last 3 years (&sq), total precipitation over the last 3 years (&sq), annual average humidity, annual average temperature (&sq), and annual precipitation (&sq).

7. Annual fraction of days with maximum temperature > 30C (&sq), summer fraction of days with maximum temperature> 30C (&sq), annual precipitation (&sq), and annual average humidity.

8. Average monthly temperature over last 3 years (&sq), average monthly precipitation over last 3 years (& sq), averagemonthly humidity over last 3 years

9. Average fraction of days with maximum temperature >30C for each month over last 3 years (&sq), average monthlyprecipitation over last 3 years (& sq), average monthly humidity over last 3 years

10. Average temperature over last 3 years (&sq), total precipitation over last 3 years (&sq), average temperature over the first 4 months of the year (before crop decision) (&sq), average precipitation over the first 4 months of the year (& sq), average humidity over the first 4 months of the year

Non-linear effects: squared variables, fraction of days with maximum temperature > 30C

Climate SpecificationsVariable 1 2 3 4 5 6 7 8 9 10

Annual

Average Temperature P P

Total Precipitation P P P P

Average Humidity P P P P P P

Maximum Temperature P

Fraction of Days with Max Temp >30C P

Fraction of Days with Max Temp >30C (Summer Only) P

Average Temperature (Early year) P

Total Precipitation (Early year) P

Average Humidity (Early year) P

Monthly

Average Temperature P

Total Precipitation P P

Average Humidity P P

Fraction of Days with Max Temp >30C P

3-Year Average

Average Temperature P P P

Total Precipitation P P P

Monthly Temperature P

Monthly Precipitation P P

Monthly Humidity P P

Monthly Fraction of Days with Max Temp >30C P

Econometric models• Reduced form models

• Extensive margin: crop acreage nict for each farmer i each time period tTobit regression:

nict = g(Tit, pct, xit, et, zit-1), c = alfalfa, corn, sorghum, soybeans, wheat

where• nict is the number of acres planted to each crop c• Tit are climate-related variables • pct are crop price futures • xit is a vector of plot-level variables including:

• irrigation technology, evapotranspiration, recharge, slope, soil quality, quantity of water authorized for extraction, field size, depth to groundwater, saturated thickness

• et are energy prices• zit-1 is a vector of lagged dummy variables indicating which crops were planted in the previous

season

We are interested in the coefficients in the climate variables Tit

Econometric models

• Reduced form models• Intensive margin: water demand wit for each farmer i each time period t,

conditional on crop choice

OLS regression:

wit = h(Tit, nict*, xit, et)

• We include number of acres planted to each crop and the number of acres planted to each crop squared

Econometric models

• Reduced form models• Total marginal effect of the climate variables Tit = sum of the effects along the

intensive and extensive margins

Econometric models


intensive and extensive margins• The intensive margin is from the water demand equation

Econometric models


intensive and extensive margins• The intensive margin is from the water demand equation

• The extensive margin is from cropland allocation models

Results: Intensive Margin

• Climate Variables 1


Variable Intensive MarginsMonocrop Multicrop

Annual average temperature 3.241444 4.199428Annual precipitation -2.4853*** -1.63714***Annual average humidity 0.329*** 0.151**

Variable Intensive Margins

Monocrop Multicrop

Average temperature over the past 3 years 9.180875 12.48282Total precipitation over the past 3 years -0.54564*** -0.15177Annual average humidity -0.203*** -0.225***

Margins are measured in acre-feet per unit of climate variable





Annual Fraction of days with max_temp > 30C 19.724 20.438

Summer Fraction of days with max_temp > 30C 104.635*** 121.48***Annual precipitation -1.473*** -0.659***Annual average humidity 0.222*** 0.048

Margins are measured in acre-feet per unit of climate variable


Average temperature over the last 3 years (F) 12.992 18.428

Total precipitation over the last 3 years (in) -0.509** -0.151

Annual average humidity -0.063 -0.04Early year Temperature -1.182 -2.512

Early year Precipitation -17.944*** -16.729***Early year Humidity 0.236*** -0.067*


• The intensive margins are generally negative for precipitation (i.e., more precipitation leads to a decrease in water use) and positive for the summer fraction of days with temperature higher than 30oC (higher temperatures lead to an increase in water use)

• Monthly intensive margins for the fraction of days with temperature higher than 30oC are generally negative at the beginning of the year (January to May) and positive after that.

• We obtained mixed results for other temperature and humidity variables.

Results: Extensive MarginClimate specification 1, Multicrop

dw/dn_c dn_c/dT dw/dn_c*dn_c/dT

Annual average temperature

Alfalfa 0.514273931 0.03016188 0.015511469Corn 0.421594199 0.65806368 0.27743583

Sorghum -0.05035381 8.54903318 -0.430476385Soybeans 0.338239195 9.47663894 3.205370729

Wheat -0.07188507 -0.14436902 0.010377978Total 3.07821962

Annual precipitation

Alfalfa 0.514273931 -0.803142478 -0.41303524Corn 0.421594199 0.753435314 0.317643957

Sorghum -0.05035381 -0.869857924 0.04380066Soybeans 0.338239195 2.50195835 0.846260379**

Wheat -0.07188507 -1.42242068 0.102250815*

Total 0.896920571

Annual humidity

Alfalfa 0.514273931 2.142 1.101574761***Corn 0.421594199 0.643 0.27108507***Sorghum -0.05035381 1.86 -0.093658085**Soybeans 0.338239195 -1.217 -0.411637101***Wheat -0.07188507 -0.353 0.025375431*

Total 0.892740076***

Results: Extensive MarginClimate specification 5, Multicrop

dw/dn_c dn_c/dT dw/dn_c*dn_c/dT

Average temperature over the past 3 years

Alfalfa 0.516411 -3.30973 -1.70918Corn 0.416339 1.922243 0.800305***

Sorghum -0.06994 18.57525 -1.29912Soybeans 0.324826 16.97849 5.515056***

Wheat -0.0703 -0.56177 0.03949Total 3.34654

Total precipitation over the past 3 years

Alfalfa 0.516411 0.135886 0.070173***Corn 0.416339 0.509685 0.212202***

Sorghum -0.06994 -0.57962 0.040538***Soybeans 0.324826 0.666692 0.216559***

Wheat -0.0703 -0.20876 0.014675***

Total 0.55415***

Annual humidity

Alfalfa 0.516411 2.431 1.255396***Corn 0.416339 0.125 0.052042***Sorghum -0.06994 1.938 -0.13554***Soybeans 0.324826 -1.673 -0.54343***Wheat -0.0703 0.118 -0.00829***

Total 0.62017***

Results: Extensive Margin

• Long-term temperature (3-year average) generally has positive extensive margins for corn and soybeans.

• Precipitation effects tend to be positive for soybeans.

• Long-term precipitation (3-year average) generally has positive extensive margins.

• We obtained mixed results for humidity.

Results for total marginal effect – Climate Specifications 1 and 5

Variable Total Marginal EffectMonocrop Multicrop

Annual average temperature 15.204 7.278Annual precipitation -0.558 -0.74

Annual humidity 3.526*** 1.044***



Variable Total Marginal Effect

Monocrop Multicrop

Average temperature over the past 3 years 30.301 15.829Total precipitation over the past 3 years 0.814 0.402Annual humidity 2.14*** 0.395**

Results for total marginal effect – Climate Specification 7 and 10• Climate Variables 7


Variable Total Marginal EffectMonocrop Multicrop

Annual fraction of days with maximum temperature > 30C 13.07 68.064

Summer fraction of days with maximum temperature > 30C 193.312 141.476

Annual precipitation 1.541 0.733

Annual humidity 2.847*** 0.768***

Variable Total Marginal effectMonocrop Multicrop

Average temperature over the last 3 years (F) 35.081 23.766Total precipitation over the last 3 years (in) 0.863 0.402Annual average humidity 1.219* 0.259Early year Temperature -3.865 -5.023

Early year Precipitation -0.632 -6.918Early year Humidity 0.442 -0.427***

Results: Total Marginal Effect

• The long-term (3-year average) fraction of days with maximum temperatures over 30 degrees C generally has a negative total effect in April and September and a positive effect in October and November.

• We found mixed results for precipitation and humidity.

Effects of climate change on irrigation technology adoption• We analyze the effects of climate change on:

• Center pivot sprinkler adoption

• Center pivot sprinkler with dropped nozzles adoption

Irrigation technology

• New, more efficient irrigation technology: “dropped nozzles”

• attach to center-pivot irrigators and reduce the amount of water lost to evaporation and drift

Dropped nozzles

Dropped nozzles hang right above the crop, reducing water lost to evaporation and drift.

Source: USDA Natural Resources Conservation Service

Dropped-nozzle center pivot system

Center-pivot irrigation with water-saving dropped nozzles on wheat growing in Yuma County, Colorado, 1987.

Source: USDA National Resources Conservation Service

Results: Center pivot sprinkler adoption

• Climate Variables 1 – Marginal effects


Variable Multicrop MonocropAnnual average temperature (F) -0.00854 -0.0526

Annual average temperature squared (F^2) 0.000168 0.000598Annual precipitation (in) 0.0248*** 0.0308***Annual precipitation squared (in^2) -0.000779*** -0.000984***

Annual average humidity (%) -0.00524*** -0.00580***

Variable Multicrop Monocrop

Average temperature over the last 3 years (F) -0.172*** -0.179*

Average temperature over the last 3 years squared (F^2) 0.00161*** 0.00168**

Total precipitation over the last 3 years (in) 0.00369*** 0.00605***

Total precipitation over the last 3 years squared (in^2) -3.09e-05*** -4.87e-05***


Results: Center pivot sprinkler with dropped nozzles adoption• Climate Variables 1 – Marginal effects


Variable Multicrop MonocropAnnual average temperature (F) -0.117*** -0.146***

Annual average temperature squared (F^2) 0.00111*** 0.00138***Annual precipitation (in) 0.000723 -0.000527Annual precipitation squared (in^2) 1.82e-05 5.26e-05


Variable Multicrop Monocrop

Average temperature over the last 3 years (F) -0.121* -0.0705

Average temperature over the last 3 years squared (F^2) 0.00116* 0.000714

Total precipitation over the last 3 years (in) 0.00891*** 0.00920***

Total precipitation over the last 3 years squared (in^2) -6.76e-05*** -6.83e-05***


Effects of climate change on irrigation technology adoption• Results:

• Irrigation technology adoption decisions are affected by climate variables

Effects of climate change on irrigation technology adoption• Results:

• Irrigation technology adoption decisions are affected by climate variables

• Ongoing work:• We will incorporate technology adoption decisions in calculating total

marginal effect of climate change

Changes in Biodiversity and Agricultural Biodiversity levels caused by land-use changes

Effects of climate change on groundwater extraction for agriculture in Kansas:

• Could changes in water use, irrigation systems or crop choice affect local biodiversity?

• Can such changes affect the availability of environmental water?

• Do farmers diversify their crop acreage during years of higher temperatures or lower precipitation levels?

Results: Crop Diversification



Variable Multicrop

Annual average temperature (F) 0.185***

Annual average temperature squared (F^2) -0.00173***Annual precipitation (in) -0.0110***Annual precipitation squared (in^2) 0.000177***

Annual average humidity (%) -0.00504***

Variable Multicrop

Average temperature over the last 3 years (F) 0.272***

Average temperature over the last 3 years squared (F^2) -0.00254***

Total precipitation over the last 3 years (in) -0.0113***

Total precipitation over the last 3 years squared (in^2) 8.09e-05***



• Climate Variables 7 – Marginal effectsVariable MulticropAnnual Fraction of days with max_temp > 30C 4.997***

Annual Fraction of days with max_temp > 30C Squared -9.056***

Summer Fraction of days with max_temp > 30C -1.562***

Summer Fraction of days with max_temp > 30C Squared 0.895***

Annual precipitation (in) -0.0111***

Annual precipitation squared (in^2) 0.000177***




Variable Multicrop

Average temperature over the last 3 years (F) 0.319***

Average temperature over the last 3 years squared (F^2) -0.00302***

Total precipitation over the last 3 years (in) -0.0106***

Total precipitation over the last 3 years squared (in^2) 7.62e-05***


Early year Temperature 0.0406**

Early year Temperature Squared -0.000389*

Early year Precipitation -0.134***

Early year Precipitation Squared 0.0408***

Early year Humidity 0.00119***


• Groundwater in Kansas: Farmers tend to diversify crop acreage in warmer/dryer years • Positive coefficients for annual average temperatures

• Negative coefficients for annual precipitation and humidity

• Positive coefficients for early year temperature

• Negative coefficients for early year precipitation


• Groundwater in Kansas: Farmers tend to diversify crop acreage in warmer/dryer years • Positive coefficients for annual average temperatures

• Negative coefficients for annual precipitation and humidity

• Positive coefficients for early year temperature

• Negative coefficients for early year precipitation

• Ongoing work:• We will incorporate crop diversification decisions in calculating total marginal

effect of climate change

Conclusion

• Changes in climate variables influence crop choice, crop acreage, technology adoption, and water demand

• Such changes in behavior can also affect the diversity of crops planted

Thank you!

the effects of climate change on groundwater extraction...

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