Proposed Modification to Method for Determining Reasonable In-Season Demand for the Surface Water Coalition:

Use of the USDA Crop Data Layer

Presented to the SWC Methodology Technical Working Group by Matt Anders

February 11, 2015

Settlement Document Subject to I.R.E. 408

What is Cropping Pattern?

• Acreage of each crop type grown by SWC members.

• Used in the Methodology for calculating Reasonable In-Season Demand (RISD):

∑(% Crop x Irr. Acres x ET Crop) / Project Efficiency = RISD

Current Method

• Data Source: USDA National Agricultural Statistics Service (NASS).

• Download tabular crop acreages by county.

• Calculate crop type averages for 1990-2010 by county.

• Assign crop type percentages to each SWC member based on land area in each county.

Drawbacks

• NASS tabular data are adjusted to protect farmer privacy.

• Incomplete data since 2005.

• 1990-2010 average does not reflect current cropping patterns.

• Uncertain if county-wide cropping patterns represent SWC member cropping patterns.

Proposed Method: CDL

• Data Source: USDA National Agricultural Statistic Service (NASS)

http://nassgeodata.gmu.edu/CropScape

• Download digital Crop Data Layer (CDL)

• Calculate percentages by crop type for each SWC member.

Alternative Methods

• ET Idaho Delayed availability.

• METRIC Delayed availability and not annually produced .

Processing CDL

• Downloaded digital Crop Data Layer (CDL) for 2007-2013

• Data Speckling

Processing CDL

• Data Smoothing Options

• Filter

• 3 by 3 pixel filter.

• Each pixel in the dataset is assigned a value based on values of neighboring pixels.

• Zonal Statistics

• A polygon dataset determines zones.

• The majority value within each zone is assigned to all pixels in the zone.

• Based on testing decided to use Zonal Statistics.

Processing CDL

• Smoothed CDL with Zonal Statistics

• Overlaid IDWR Irrigated Lands dataset.

• Assigned the majority crop within each irrigated land polygon to all pixels that fall within the polygon.

Processing CDL

• Problems with Smoothing

• IDWR Irrigated Lands dataset not available for every year of CDL data. Used current or most recent Irrigated Lands dataset.

• Field assigned one crop even if it has multiple crops

SWC Member Irrigated Lands

• Dataset created by SWC Member

• Burley• Minidoka• TFCC

• Dataset created by IDWR based on water right permissible place of use (PPU)

• A&B• AFRD2• Milner• NSCC

Acres for Each SWC Member

• Processed in ArcGIS with a geoprocessing model

• CDL_Processing” script in the “CDL_Toolbox.tbx

• Step 1: Clip CDL with SWC Irrigated Lands Dataset

Acres for Each SWC Member

• Step 2: Group by Raster Value

• CDL Attribute Description: generic_cdl_attributes.dbf

RISD Group Name Raster Value Raster Value Description

Alfalfa 36 Alfalfa

Barley 21 Barley

Corn 1 Corn

Developed - Semi Irr 121122

Developed/Open SpaceDeveloped/Low Intensity

Dry Beans 42 Dry Beans

Oats 28 Oats

Pasture/Hay 3762176181

Other Hay/Non Alfalfa--- Historical value no longer usedGrass/Pasture--- Historical value no longer used

Peas 53 Peas

Potatoes 43 Potatoes

Spring Wheat 23 Spring Wheat

Sugarbeets 41 Sugarbeets

Winter Wheat 24 Winter Wheat

z_Non-Crop 6163111112131141142143152171190195

Fallow/Idle CroplandForestOpen WaterPerennial Ice/SnowBarrenDeciduous ForestEvergreen ForestMixed ForestShrubland--- Historical value no longer usedWoody WetlandsHerbaceous Wetlands

z_Developed - No Irr 123124

Developed/Med IntensityDeveloped/High Intensity

z_Other All other values

Acres for Each SWC Member

• Step 3: Calculate Acres by RISD Group (acres.xls)

• Step 4: Compute 3-Year Average (CDL_summary.xlsx)

• Discussion:

• Average data to reduce influence of a single year while still being representative of the current cropping pattern.

• 7 years of data did not indicate a clear relation between cropping pattern and water supply (CDL_summary_SWSI.xlsx), so decided to use a shorter average.

Comparison of Method ResultsNASS County Data: Average 1990-2010

  A&B AFRD2 BID Milner Minidoka NSCC TFCC

Alfalfa 20.2% 42.5% 40.4% 27.8% 36.9% 14.0% 29.5%

Barley 11.6% 3.3% 3.7% 12.0% 11.9% 20.1% 12.7%

Dry Beans 3.4% 4.4% 2.9% 9.2% 2.1% 3.6% 16.7%

Silage/Grain Corn 3.6% 5.7% 27.8% 14.9% 9.1% 2.0% 11.2%

Oats 0.2% 0.4% 0.4% 0.1% 0.8% 0.2% 0.2%

Potatoes 12.2% 11.9% 10.2% 10.5% 7.1% 13.7% 6.3%

Sugarbeets 12.6% 11.7% 4.0% 9.6% 12.0% 23.0% 6.7%

Spring Wheat 13.2% 5.2% 5.3% 8.3% 14.6% 15.0% 4.2%

Winter Wheat 23.0% 14.9% 5.2% 7.5% 5.5% 8.4% 12.5%

CDL Data: 3-Year Average

  A&B AFRD2 BID Milner Minidoka NSCC TFCC

Alfalfa 19.2% 26.6% 16.8% 20.9% 29.9% 22.4% 22.6%

Barley 31.1% 5.6% 4.3% 15.4% 13.2% 6.9% 10.9%

Corn 3.1% 28.1% 6.8% 11.2% 2.7% 31.3% 19.1%

Developed - Semi Irr 0.9% 2.6% 4.9% 0.4% 5.5% 2.5% 4.6%

Dry Beans 8.4% 2.5% 7.6% 13.0% 3.0% 3.6% 11.2%

Oats 0.1% 0.7% 0.1% 0.3% 0.2% 0.1% 1.0%

Pasture/Hay 2.6% 17.1% 5.3% 1.6% 9.0% 11.9% 15.0%

Peas 0.1% 0.0% 0.0% 0.4% 0.1% 0.1% 1.6%

Potatoes 8.7% 3.3% 10.7% 7.6% 11.9% 7.3% 2.8%

Spring Wheat 3.7% 3.7% 4.1% 3.7% 3.6% 1.8% 0.7%

Sugarbeets 18.7% 4.4% 20.6% 10.5% 12.0% 5.6% 3.0%

Winter Wheat 3.5% 5.5% 18.7% 15.0% 8.8% 6.5% 7.4%

Change: (NASS County Data: Average 1990-2010) - (CDL Data: 3-Year Average)

  A&B AFRD2 BID Milner Minidoka NSCC TFCC

Alfalfa -1.0% -15.9% -23.6% -6.9% -7.0% 8.4% -6.9%

Barley 19.5% 2.3% 0.6% 3.4% 1.3% -13.2% -1.9%

Corn -0.5% 22.4% -21.0% -3.7% -6.4% 29.3% 8.0%

Developed - Semi Irr --- --- --- --- --- --- ---

Dry Beans 5.0% -1.9% 4.7% 3.7% 0.9% 0.0% -5.5%

Oats -0.1% 0.3% -0.3% 0.2% -0.5% -0.1% 0.8%

Pasture/Hay --- --- --- --- --- --- ---

Peas --- --- --- --- --- --- ---

Potatoes -3.6% -8.6% 0.5% -2.9% 4.9% -6.4% -3.5%

Spring Wheat -9.4% -1.4% -1.2% -4.6% -11.0% -13.1% -3.5%

Sugarbeets 6.1% -7.3% 16.6% 0.9% 0.0% -17.5% -3.7%

Winter Wheat -19.6% -9.4% 13.5% 7.6% 3.4% -1.9% -5.0%

Information on Website

http://idwr.idaho.gov/News/WaterCalls/Surface%20Coalition%20Call/

• CDL folder

• Input CDL Datasets

CDL_swc_2007_30m_zs.tif (re-sampled from 56 m pixels to 30 m)CDL_swc_2008_30m_zs.tif (re-sampled from 56 m pixels to 30 m)CDL_swc_2009_30m_zs.tif (re-sampled from 56 m pixels to 30 m)CDL_swc_2010_zs.tifCDL_swc_2011_zs.tifCDL_swc_2012_zs.tifCDL_swc_2013_zs.tif

• Processing Output

• Output by company and year from the geoprocessing script.

• GIS Folder

• Geoprocessing Script: CDL_Toolbox.tbx• ArcMap Project: CDL-SWC-TWG.mxd• CDL Attribute Key: generic_cdl_attributes.dbf• Geoprocessing Script Grouping Calculation: CDL_Toolbox.tbx

Information on Website

http://idwr.idaho.gov/News/WaterCalls/Surface%20Coalition%20Call/

• Irrigated Acres folder

• Shapefiles of the irrigated acres used for each SWC member

• Burley BID_POU_2013.shp• Minidoka minidoka acres 3-13.shp• TFCC TFCC_2013.shp• A&B AB_SW_clip_IDWR_Irr2010.shp• AFRD2 AFRD2_snake_clip_IDWR_Irr2010.shp• Milner milner_clip_IDWR_Irr2010.shp• NSCC northside_clip_IDWR_Irr2010.shp

• Loose files

• CDL Method Comparison Results (Slide 12): CDL_Comparison_Method_Results.docx• This PowerPoint: CDL_Cropping_Pattern.pptx

Questions?

(208) 287-4932matthew.anders@idwr.idaho.gov