Water Quality Trading inthe Agricultural Community Dennis Frame Professor, UW – ExtensionDirector, UW – Discovery Farms
Purpose of This Presentation Discuss the reasons for, the challenges with and the possibilities of developing point/non-point trading programs Evaluate phosphorus losses from different farms and settings Discuss what point sources need/want
Water Quality Targets Total Phosphorus 0.1 mg/l for non-wadable rivers and estuary 0.075 mg/l for wadable streams
Water Quality Targets In this watershed you are evaluating sources of phosphorus and developing reduction targets Point sources Non-point sources Natural sources Background levels
Water Quality Targets The question is, can point sources afford to reduce phosphorus losses to achieve the new requirements? If not, how can they be achieved?
Water Quality Trading Can a process be developed where point sources can trade with non-point sources to achieve an overall reduction in phosphorus?
Water Quality Trading Can a process be developed where point sources can trade with non-point sources to achieve an overall reduction in phosphorus? Will changes in management show up in water quality? Annual variation Lack of precision in ag
Point Sources Easy to sample Easy to get flow rates Therefore, relatively easy to calculate nutrient loads
Nonpoint Sources Nonpoint source pollution, unlike pollution from industrial and sewage treatment plants, comes from many diffuse sources.
Nonpoint Sources NPS pollution is caused by rainfall or snowmelt moving over and through the ground. As the runoff moves, it picks up and carries away pollutants, finally depositing them into lakes, rivers, wetlands, coastal waters, and even our underground sources of drinking water.
Background A Dodge County Farmer: “I believe that all farmers are concerned about nutrients moving. We want to see real data--- not something manufactured by someone behind a desk in an office.”
Background I start with this quote because you cannot solve a problem until all the people involved in the challenge take ownership of the problem.
Background I start with this quote because you cannot solve a problem until all the people involved in the challenge take ownership of the problem. What I believe and “know”; What you believe and “know”; Is not as important as what the people and businesses living in the watershed think, believe and know!
Distribution of event-mean total P concentration 2003 - 08
KoepkeKoepkeFarms, Inc. KP3 (Surface) Annual P and Sediment Loss Surface phosphorus loss 7 280 was higher in corn years 6 240 (FY06, FY08) vs the DRP soybean year (FY07) Phosphorus yield (lbs/acre) Sediment yield (lbs/acre) 5 Particulate P 200 Sediment 4 160 Dissolved phosphorus 3 120 was the dominant form of P loss 2 80 1 40 Total P loss was not 0 0 strongly linked to FY2006 FY2007 FY2008 sediment C SB C The average total phosphorus loss for the surface basin was 3.1 pounds/acre/year
KoepkeKoepkeFarms, Inc. Speciation of Total Tile Phosphorus Loss Phosphorus Loss 1. The majority of P lost during the 23% monitoring period on this farm was Particulate P dissolved P. 77% Dissolved P Total Surface Phosphorus Loss 18% Particulate P 2. This farm’s no-till cropping system 82% Dissolved P greatly reduces sediment loss.
KoepkeKoepkeFarms, Inc. Conclusions Average total P loss for the surface basin (KP3) during the monitoring period was 3.1 pounds/acre/year; typically occurred at snowmelt and spring runoff (March, April) and during large runoff events through the year. The contributing area for tile drainage systems could not be determined; P yields could not be generated. Raw water sample concentrations and loads were used to identify trends in water quality data.
KoepkeKoepkeFarms, Inc. Conclusions Tile total P loss under alfalfa was lower than corn and soybeans. Increases in total P concentration and loads in tile lines were correlated to recent manure applications. The timing of manure applications likely had a role in the timing of P loss, especially in the dissolved form, on this farm.
Surface Phosphorus Loss by Basin 4.5 FY2004 frozen ground 4 FY2004 non-frozen ground 3.5 FY2005 frozen ground 3 FY2005 non-frozen ground Yield (lbs/acre) FY2006 frozen ground 2.5 FY2006 non-frozen ground 2 Site P2 removed FY2007 frozen ground Not sampled 1.5 FY2007 non-frozen ground 1 FY2008 frozen ground 0.5 FY2008 non-frozen ground 0 P1 P2 P3The average total phosphorus loss for all surface basins during the monitoring periodwas 1.8 pounds/acre/year.
Tile Phosphorus Loss Tile Phosphorus Loss by Basin 1.4 FY2005 frozen ground 1.2 FY2005 non-frozen ground 1.0 FY2006 frozen ground Yield (lbs/acres) 0.8 FY2006 non-frozen ground 0.6 FY2007 frozen ground 0.4 FY2007 non-frozen ground 0.2 FY2008 frozen ground 0.0 FY2008 non-frozen ground P4 P5Total phosphorus loss - tile basins = 0.9 pounds/acre/year• As water moves through the soil, it carries phosphorus with it through the preferentialflow paths and soil profile.
Surface vs. Tile Comparison 4-yr Basin Average: Total Phosphorus LossTile: 0.9 pounds/acre/year average Surface Tile 34% 66% Surface: 1.8 pounds/acre/year averageTile phosphorus loss was 34 percent of the combined total loss.Some phosphorus is lost via tile, but surface loss is the most dominant phosphoruspathway in these agricultural landscapes.
Collaboration Water quality cannot be improved without everyone being involved and being part of the solution. Every acre counts! Every source matters!!!
Challenges with Trading How do we estimate the current levels of loss (P-index, APEX, SWAT, etc.)? How do we accurately predict reductions? How do we account for variations based on weather, farming system and management?
Challenges with Trading The producers who are looking to get engaged with trading are probably the ones with the lowest levels of loss. Can they make changes that reduce losses to a level that is measurable in water quality? Farmers want to protect water quality – they need to be involved throughout the process.
Bragger Base Flow Samples Total P, WY02 - WY08TP Concentration, mg/L Dam Installed 0.40 North TP 0.35 0.30 South TP 0.25 0.20 0.15 0.10 0.05 0.00 Mar-02 Mar-08 Sep-02 Dec-04 Oct-03 Jul-06 Oct-08 Jan-01 Jan-06 Jun-05 Feb-07 Apr-03 May-04 Aug-01 Aug-07