Choptank River Conservation Effects Assessment Project

Home , Chester River, Choptank people, Choptank River, Tuckahoe Creek

NRCS Special Emphasis Watershed Research Findings and Recommendations 2004—2008

Conservation Effects Assessment Project

USDA - Agricultural Research Service Choptank River Watershed Project Final Report

Contact Information:

Project PIs NRCS Special Emphasis Watershed Gregory W. McCarty As part of the USDA-Natural Resources Conser- The Choptank River Watershed project has now USDA-ARS Beltsville, Maryland vation Service (NRCS) Special Emphasis Water- been converted to a USDA-ARS Benchmark [email protected] shed Program, the Choptank River Watershed Watershed for long-term study. This document 301-504-7401 project was initiated in 2004 and was continued serves as the final report to NRCS for the spe- Laura L. McConnell through 2008. cial emphasis watershed project. USDA-ARS Beltsville, Maryland [email protected] 301-504-6298 Watershed Description Project Co-PIs Thomas R. Fisher The Choptank River is a major tributary of University of Maryland the Chesapeake Bay and is located on the Del- Center for Environmental marva Peninsula. The 1756 square km (675 Science, Horn Point Laboratory square mi) Choptank River Watershed is 58% Cambridge, Maryland agricultural (cropland and extensive poultry pro- [email protected] duction), 33% forested, and only 9% urban. Cathleen J. Hapeman Portions of the Choptank River have been identi- USDA-ARS Beltsville, Maryland fied as “impaired waters” under Section 303(d) Cathleen. [email protected] of the Federal Clean Water Act due to high levels

W. Dean Hively of nutrients and sediments. USDA-ARS Beltsville, Maryland The Choptank River Watershed Project pro- [email protected] vides several unique aspects to the national Thomas E. Jordan Smithsonian Environmental Research CEAP effort. The river itself is tidal for much of Center its length and includes an ecologically delicate Edgewater, Maryland estuarine ecosystem. The soils in the region are [email protected] poorly drained and the topography is especially Megan W. Lang USDA-ARS flat; therefore, farmers have historically utilized Beltsville, Maryland a network of drainage ditches to facilitate the [email protected] movement of water into streams. Urban influ- Clifford P. Rice Choptank River Watershed ences are growing rapidly. USDA-ARS Beltsville, Maryland [email protected]

Ali M. Sadeghi Project Goals USDA-ARS Beltsville, Maryland • Improve estimates of nutrient reduction [email protected] Table of Contents efficiency values for the widely accepted David Whitall NOAA-NOS-NCCOS agricultural Best Management Practices (BMPs) Executive Summary 2 within the Choptank. Silver Spring, Maryland Background 3 [email protected]

Collaborators • Develop innovative remote sensing tools for Watershed Characteristics & Mustafa Altinikar estimate cover crop biomass/nutrient uptake Water Quality Sampling 4 University of Mississippi and to examine wetland hydroperiod and University, Mississippi Linking Land Use with Nutrient [email protected] connectivity on a watershed scale. & Pesticide Loads 5 Marilyn Fogel • Examine land use and hydrology effects on Carnegie Institution of Washington Forested Wetland Function Revealed 6 Washington, DC pesticide and nutrient loads to streams. [email protected] Improving Cover Crop Programs 8 • Utilize watershed water quality models to exam- Kenneth Staver Controlled Drainage for Nutrient Reduction 10 Wye Research and Education Center ine conservation practice implementation sce- Queenstown, Maryland narios to achieve water quality improvements. Modeling the Future of the Choptank 12 [email protected] Outreach to the Agricultural Community 14 John Rhoderick • Foster positive relationships with farmers, stake- Maryland Department of Agriculture holders, and customers to preserve the natural References 15 Annapolis, Maryland [email protected] resources of the Chesapeake Bay Watershed.

Executive Summary Page 2 `

Project Outcomes

Recommendations Linking Land use with Improving Cover Crops. Modeling the Future of to Achieve Nutrient and Pesticide Remote sensing technologies the Choptank. One sub- Water Quality Concentrations. Nutrient were combined with agronomic watershed of the Choptank, the practice data to determine bio- Improvement concentrations were negatively German Branch, was used to mass and nutrient uptake by Goals correlated with percent forest test two different watershed - winter cover crops. Critical fac- water quality models: An- content. NO3 concentrations tors governing uptake were varied little over time which is nAGNPs and SWAT. The Ger- planting date, crop species, and consistent with the more steady man Branch covers nearly planting method. A threshold delivery groundwater flow. 12,000 acres and is primarily Increase implementa- cover crop biomass of about 1 Phosphorus, however, was deliv- dominated by corn and soybean tion of early planted ton per acre was observed to ered primarily via overland flow. production receiving poultry winter cover crops of control root zone nitrate. Re- Both atrazine and metolachlor manure and fertilizer applica- barley and rye. sults of this work have been showed spikes in concentration tions. This approach significantly used to improve the ef- during early spring when those increases nutrient uptake fectiveness of the Mary- herbicides are typically applied. when compared with late land Cover Crop Program, Pesticide concentrations did not planted cover crops. The and improved nutrient follow the same land use corre- recommended target efficiency values have lations as nutrients indicating cover crop biomass for been developed with the that pesticide transport is more control of root zone Chesapeake Program complicated. Delivery can occur nitrate is about 1 ton per Office Nutrient subcom- via leaching, overland flow, and acre. mittee for use in the atmospheric delivery to riparian Chesapeake Bay water corridors via drift, volatilization, quality model. and/or deposition. Strategically place

controlled drainage structures to reduce Forested Wetland Controlled Drainage for Among the nutrients, nitrate nutrient flows into Function Revealed. Nutrient Reduction. losses are of particular concern, ditches. These struc- A combination of RADAR and Drainage ditches are extensively much of which escapes through tures enhance the process LiDAR remotely sensed data was used in the Choptank and pro- leaching from the crop land via of denitrification in soils. used to develop fine resolution vide a rapid pathway for nutri- subsurface flow from this domi- Storm events, however, maps of forested wetlands within ents to move into streams. nantly flat landscapes that per- can still result in nutrient the Choptank Watershed and to Studies have shown that an sist throughout the watershed. flushing into waterways. monitor their hydrology (i.e., average of 6% of nitrate applied In one assessment, the SWAT Further optimization of inundation and soil moisture). to agricultural fields can be model was used for analyses of this practice is required. This work provides a powerful transported in drainage water to alternative management prac- new approach to examine wet- receiving surface waters. Water tice and/or cropping system

land connectivity and to monitor control structures installed at scenarios. Evaluation of cover Protect existing wetland function on a landscape the drainage outlet were evalu- crop effects on nitrogen reduc- wetlands within the scale. These tools also can be ated as a potential conservation tion from the watershed was Choptank watershed used to assess ecological ser- practice. Proper management of the primary objective of this utilizing newly- vices provided by wetlands. For these structures not only re- model evaluation. Simulation developed tools. example, information gained on duces water flow, but also nutri- results demonstrated that cover These tools can show the biogeochemical status and ents, mainly N, due to enhanced crops could potentially reduce connectivity with adjacent landscape connection of wet- denitrification. Drainage control large amounts of nitrate in agricultural areas and lands provides an important structures are often managed to streams. Specifically, 5 to 30% monitor wetland function. indication of the role of wetlands increase water levels to just of nitrate could be reduced in Targeted expansion of in retention or removal of agri- below the root zone during the streams if cover crops are im- existing wetland areas cultural nutrients or pesticides growing season and to near the plemented on up to 50% of the and restoration of historic from agricultural production bottom of the drainage ditch conventional croplands in the wetlands could be used as areas. Furthermore, these tools during planting and harvesting. watershed. Furthermore, the an effective management can be used to monitor the ef- Proper management of these model simulations showed that strategy to reduce nutri- fectiveness of broad scale wet- structures can potentially reduce nitrogen loss reductions could ent and pesticide loads land hydrologic restoration. nitrate losses in drainage water also be more effective if cover prior to entering streams. from 15% to 30%. These re- crop implementation followed a sults have led to the addition of targeted watershed manage- controlled drainage to the Mary- ment approach. land cost share program.

Background Page 3 Land use, Conservation Programs, and Conservation Concerns

Land Use. The Choptank vation practices implemented by lar Maryland watersheds (MD- fertilizer phosphorus applica- River is located in the Delmarva farmers during federal fiscal DNR 2002). Water quality is the tion (Sprague et al. 2000). Peninsula in the Mid-Atlantic year 2006, with technical and/or greatest conservation concern in Nutrient Management Region of the United States. financial assistance provided by the watershed as it centers on Plans. In 1998, the Maryland The Choptank basin has an area NRCS, FSA, Maryland Depart- health of aquatic ecosystems of legislature enacted the Water of 794 sq. mi. At present, ap- ment of Agriculture (MDA), the the Choptank River. Nutrient, Quality Improvement Act proximately 60% of land area in Soil Conservation Districts, and sediment, and bacterial contami- which mandated improved the watershed is dedicated to other partner agencies, is shown nation are considered the most nutrient management by pro- crop production of corn, soy- in table 1. critical water quality problems, ducers. Since 2001, Maryland bean, wheat, and barley. State Programs. Maryland but pesticides and other inputs farmers and agricultural op- Small to medium animal feed- Department of Agriculture (MDA) of organic contaminants are also erators have been required to ing operations are also located also implements cost-share pro- a concern (Chesapeake Execu- develop and to implement in the watershed. Poultry programs to promote agricultural tive Council 2000). nutrient management plans. duction is the most prevalent conservation. Programs such as Nutrient Load Estimates. All farmers grossing $2,500 a animal production industry. the Maryland Agricultural Water The U.S. EPA Chesapeake Bay year or more or livestock pro- Chicken litter from poultry Quality Cost-Share (MACS) Pro- Program model houses is routinely recycled as a gram which supports implemen- (Phase 4.3) esti- fertilizer on the corn and soy- tation of 30 different agricultural mated that in bean production fields. BMPs including the Cover Crop 2000 agricultural Federal Programs. Several Program, Manure Transport Pro- sources contrib- federal and state conservation gram, and Nutrient Management uted 73% of the programs are available to farm- Cost-Share Program provide nitrogen (N) and ers in the Choptank River Water- additional financial assistance to 62% of the phos- shed. The Maryland Natural farmers within the watershed phorus (P) load to Resources Conservation Service (table 2). the Choptank (NRCS) provides technical and Ecosystem Concerns. Major River, whereas financial assistance for NRCS conservation concerns of the agricultural load- programs throughout Maryland Choptank River watershed are ing estimates in and in the Choptank River wa- water, soil, and air quality as 1985 were 82% of N and 72% of ducers with 3629 kg (8,000 lb) tershed counties. In addition to well as loss of wildlife habitat. P (MD-DNR 2005a). Urban or more of live animal weight these programs, NRCS provides The historical loss of wetlands in sources were predicted to ac- are now required to use a technical assistance for other the Upper Choptank River sub- count for 10 and 15% of annual nutrient management plan U.S. Department of Agriculture watershed is estimated to be loading for nitrogen and phos- that addresses both nitrogen programs, such as the Conser- 19,200 ha (47,400 acres) which phorus, respectively. During the and phosphorus inputs. In vation Reserve Program (CRP) represents approximately 11 % period 1985 to 2000, improved 2006, 94% of Maryland farm- and Conservation Reserve En- of the total watershed area nutrient management plans had land was covered under a hancement Program (CREP), (Maryland Department of Natu- greater impact on fertilizer appli- nutrient management plan which are administered by the ral Resources (MD-DNR) 2002). cation of phosphorus than nitro- (MDA 2007a). Maryland Farm Service Agency This loss of wetlands is large gen with a 24% decrease in (FSA). A list of selected conser- when compared with other simi-

Table 1. Selected Best Management Practices Reported that were implemented during fiscal year 2006 in Caroline, Dorchester, Queen Anne’s, and Talbot Counties, Maryland*

Crop Residue Riparian Streambank Cover Crop Residue Field Filter Nutrient Tree/Shrub Wetland Management Forest & Shoreline County Crop Management Border Strip Management Establishment Restoration Seasonal Buffer Protection (ha) (ha) (mi) (ha) (ha) (ha) (ha) (ha) (ha) (mi) Caroline 83 1538 73 6592 6 1579 0 34 10 66 Dorchester 2563 45 7232 5056 79 223 4 0 0 23 Queen Anne’s 1006 1061 29 1203 113 1446 8 358 4 10 Talbot 3771 1936 7 2271 8 2241 1 0 31 28 Total 7422 4580 7341 15122 207 5489 14 392 45 127 Table 2. Summary of Maryland Department of Agriculture conservation grants program for fiscal year 2006 in Caroline, Dorchester, Queen Anne’s, and Talbot Counties, Maryland**

MACS Program Cover Crop Program Nutrient Management Cost-Share County Projects Payment Applications Area (ha) Payment Applications Area (ha) Payment Caroline 28 $510,376 51 1,819 $226,079 32 5,400 $38,345 Dorchester 20 $262,608 57 5,908 $564,264 22 7,047 $34,374 Queen Anne's 36 $207,992 64 4,644 $391,803 6 1,340 $6,825 Talbot 18 $123,011 52 5,668 $540,888 16 2,710 $21,157 Total 102 $1,103,987 224 18,039 $1,723,034 76 16,497 $100,701 * NRCS, 2006 Performance Results System Report on conservation practices (http://ias.sc.egov.usda.gov/prsreport2006/). ** MDA, the Maryland Agricultural Water Quality Cost-Share (MACS) 2006 Annual Report (http://www.mda.state.md.us/pdf/macsar06.pdf)

Watershed Characteristics & Water Quality Sampling Page 4

Hydrologic and Morphological Characteristics

Summary of Soil types. The Tuckahoe Creek and Upper Choptank River Activities: sub-basins (figure 1) are located • 15 study sub-watersheds on Mid-Atlantic Coastal Plain selected for intensive soils with parent materials de- fined by the superposition of study—each with upper-delta-plain sands and differences in land use gravel on marine-inner-shelf and conservation sands. Local soil types under practice implementation cropland production include the • Stream height measured Othello series (fine-silty, mixed, every 30 minutes at active, mesic typic endoaquults) which are poorly-drained with outflow of each sub- moderately low-permeability, watershed and the Mattapex series (fine- • Rating curves developed silty, mixed, active, mesic aquic for each sub-watershed hapludults) which are moder- to estimate discharge ately well-drained with moderate rates or moderately-low permeability. Subwatershed gauging. • Nutrient and pesticide Sampling stations were estab- concentrations measured lished at the outlets of 15 upland monthly at the sub- sub-watersheds drained by 3rd watershed outflows and 4th order streams (figure under baseflow 1). Each stream was gauged conditions using a Solinst Levelogger Model 3001 F15/M5 with stage data • Land use data and recorded on a 30-min recording geospatial data layers interval. Stage-discharge rating Figure 1. Locations of study subwatersheds and sampling stations. developed for each curves were developed over a Hydrogeomorphic regions are designated. Monitoring stations subwatershed including wide range of baseflow and maintained by other state and federal agencies are also indicated. CREP implementation. event flow conditions. On sampling days, stream flow was • Nutrient and pesticide calculated based on average concentrations measured daily stage data and converted at downstream locations to flow with the appropriate Table 3. Area, hydric soil, and land use and soil for the 15 study subwatersheds in the Choptank River in the river less rating curve. Together, the 15 subwatersheds drain 322 km2 of % frequently. Sub- Area % % % % % hydric upland making up 16% of the basin* (km2) Agriculture† Developed† Forest† CREP‡ Feedlot soils Choptank River basin. 1 14 26 64.3 2.0 32.1 0.7 0.9 Water quality measure- 2 26 15 75.1 4.0 18.4 1.1 1.3 ments. In the current project, 3 25 33 69.6 1.8 23.1 5.2 0.4 stream water in the 15 sub- 4 17 34 63.3 0.0 28.3 8.1 0.3 watersheds has been analyzed 5 15 24 78.0 3.6 16.2 0.6 1.6 monthly for nutrients (NO3- and 3- 6 10 17 83.8 4.4 10.3 0.2 1.3 PO4 ) since 2003 and for cur- rently-used pesticides since 7 51 45 67.8 0.2 26.8 4.2 0.9 2005. 8 23 64 62.3 0.8 32.2 4.6 0.0 9 40 64 54.1 0.4 40.8 4.2 0.5 Recent Publication 10 16 58 61.5 2.3 35.1 0.4 0.7 McCarty et al. 2008. Water 11 12 60 54.3 8.4 32.3 3.7 1.2 quality and conservation prac- 12 12 32 74.3 0.3 21.6 3.5 0.3 tice effects in the Choptank 13 25 51 59.6 2.1 30.7 7.4 0.2 River watershed. Journal of 14 8.5 34 62.9 5.3 28.2 2.2 1.4 Stream gauging activities Soil and Water Conservation. using an acoustic doppler 15 23 19 76.8 5.1 15.6 0.8 1.7 current profiler 63(6):461-474. * Sub-basin numbers correspond to the subwatersheds shown in Figure 1. http:// hdl.handle.net/10113/22915 † Land use as of 1990, determined from Landsat images ‡ Conservation Reserve Enhancement Program (CREP)

Linking Land Use with Nutrient and Pesticide Loads Page 5

Nutrients and Pesticides Follow Different Paths

Land Use. Land use within supported by the high positive 0.8 2 the subwatersheds varies con- correlation between areal ex- R = 0.01 2 0.09 R = 0.32

siderably (Table 3), providing tent of hydric soil and forests g/L) 0.6 (P< 0.03) 2 μ opportunities to discern the (R = 0.72). 0.06 influence of land use on the Temporal Data. The tempo- 0.4

pollutant transport. Agriculture ral variance in the average nu- 0.2 0.03

and forest are the two land use trient and herbicide baseflow ( Metolacholr

classifications that account for concentrations for the 15 moni- 0.0 Phosphorus (mg P/L) 0.00 10 more than 90% of the land area tored streams during an annual 2 0.8 R = 0.01 2 within all the sub-watersheds. cycle is shown in Figure 2. Both 8 R = 0.73 (P< 0.001)

The percent agricultural lands atrazine and metolachlor g/L)

μ 0.6 ranged from approximately 50 showed spikes in concentration 6 to 80% while forested lands during early spring when those 0.4 4

ranged from 10 to 40%. Many herbicides are typically applied. ( Atrazine 0.2 2 Nitrate (mg N/L) of the areas within the sub- Mean concentrations for 0.0 0 watersheds that have remained atrazine [3.15 µg/L (ppb)] and 10 20 30 40 10 20 30 40 forested are also wetlands as metolachlor [1.56 µg/L (ppb)] % Forest % Forest

Figure 3. Relationship between percent forest land use in the 15 8 subwatersheds and the annual average agrochemical content in stream water. 6 g/L) μ 4 during the spring were 21 and No apparent relationship exists 11 times greater, respectively, between percent forested lands 2

Atrazine ( Atrazine than mean concentrations dur- for atrazine or metolachlor 0 ing all other sampling periods. which may reflect complex de- 5 Temporal data for average livery mechanisms for pesti- nutrient concentrations did not cides. Further investigation is 4

g/L) show similar spikes, although needed. μ 3 3- PO4 showed a slight spring- 2 time minimum in median and mean values. Mean or median 1 - NO3 concentrations for the Metolachlor ( 0 subwatersheds displayed little 0.3 temporal variance. Agrochemical Sources. 0.2 The lack of temporal variability - in NO3 concentrations is con- 0.1 sistent with a more steady delivery of via groundwater flow. This contrasts with the pre-

Phosphorus (mg P/L) 0.0 dominantly overland flow deliv- However, nutrient concentra- 12 ery for phosphorus. Pesticide tions were negatively correlated 10 transport from the fields to the with percent forest content. 8 streams is more complicated as This indicates the strong influ- 6 delivery can occur via leaching, ence of land use on nutrient 4 overland flow, and atmospheric loading. It is noteworthy that delivery to riparian corridors via current levels of CREP imple- Nitrate (mg N/L)Nitrate (mg 2 drift and/or volatilization/re- mentation in these subwater- 0 deposition. sheds have no detectable influ- Examining Land Use Con- ence on nutrient concentration. 5-Jul 6-Apr 5-Dec 24-Jul 27-Jul 31-Oct 25-Apr 29-Jun 16-Feb 29-Aug 26-Sep nections. Figure 3 shows the This could indicate that thresh- 30-May 30-May Date relationship between percent old levels have not been ob- forest content in the subwater- tained for implementation of Figure 2. The distributions in stream water concentration of herbicide sheds and the average annual buffers or that the buffers were and nutrient for the 15 monitored subwatersheds during an annual cycle concentrations of nutrients and not functional. (June 2005 to July-2006). The dashed and solid lines indicate mean and median values, respectively. herbicides in the stream water.

Forested Wetland Function Revealed Page 6

Using Radar to Monitor Forested Wetland Hydrology

Delmarva Bays in the Choptank watershed. These land distribution and the bio- peake Bay Watershed where Choptank. Wetland restoration unique landscape features pro- geochemical processes (e.g., over half of all wetlands are is an important component in vide much of the amphibian denitrification) that strongly forested. water quality improvement habitat for the region and har- influence the provision of wet- Forested wetlands are one of strategies in the Choptank River bor a number of endangered land water quality services. the most difficult types of wet- and for the Chesapeake Bay. amphibian and plant species Monitoring forested wetland lands to map using optical Large sections of the Choptank within the Choptank River wa- hydroperiod at a broad scale is imagery, such as aerial photo- River watershed have extensive tershed region. difficult using ground-based and graphs and Landsat. Ground- ditch networks so that many his- Monitoring Hydroperiod in traditional optical remote sens- based approaches are resource toric wetlands are now drained. Forested Wetlands. Wetland ing methods. The ability to lo- prohibitive over the large areas Geographically isolated wetlands hydroperiod (temporal fluctua- cate forested wetlands accu- often necessary for watershed called Delmarva Potholes or Bays tions in soil moisture and wet- rately is vital to the manage- management. In addition, exist- are abundant in parts of the land inundation) controls wet- ment of wetlands in the Chesa- ing wetland maps, such as the US Fish and Wildlife Service National Wetland Inventory, are difficult to update and represent conditions at one point in time. Better methods are needed to map and to characterize the hydrology of these ecosystems so that their pollutant mitigation potential can be assessed more RADAR Satellite accurately. Using Synthetic Aperture Radar. Satellite-based radar sensors have the capability to monitor changes in the status of the key hydrologic characteristics of wetlands throughout the year and with greater frequency than optical sensors, in part due to the ability of radars to collect images regardless of cloud cover or time of day (Figure 4). More importantly, the use of readily acquired multi-temporal radar data provides access to seasonal dynamics of wetland hydrology that static wetland maps cannot. Not being re- stricted by clouds is also important when collecting data during rainy periods when wetlands are often easier to discriminate. The Kilometers sensitivity of radar energy to water and its ability to pene- Figure 4. Map of trate forest canopies make ra- Choptank River Wa- dar sensors ideal for the detec- tershed developed tion of hydrologic patterns in using synthetic aper- forested wetlands. ture radar data. Higher intensity of Recent Publication red color indicates Lang, et al. 2008. Assessment wetter areas. Tem- of C-band synthetic aperture poral differences in radar data for mapping Coastal forest hydrology can Plain Forested Wetlands in the be detected through Mid-Atlantic Region. Remote frequent monitoring. Sensing of Environment. 112:4120-4135. Winter Early Spring Late Spring

Forested Wetland Function Revealed Page 7

Using LiDAR to Map Inundation Exploiting the Synergy of Information and Wetland Connectivity Gained from Active Sensors

Locating Delmarva Bays. Variations in elevation are Seeing through the Can- The bottom image is the relatively small on the Eastern Shore of Maryland. Subtle opy. Both RADAR and LiDAR digital elevation maps of the differences in topography can result in the formation of are similar in that they are same area in black and white wetlands. The LiDAR-derived digital elevation map shown in active (energy emitting) sens- developed from LiDAR. The Figure 5 illustrates the prevalence of Delmarva Bays and ing technologies based on the DEM is overlaid with the radar wetland flats in Caroline County. detection of reflected energy, maps shown in red. The DEMs Connectivity between Wetlands. Our research has however information gained can be used to estimate how demonstrated that the intensity of LiDAR signals can also from each sensor is unique and much surface water leaves be used to reveal synergistic for wetland charac- the agricultural fields. significant sur- terization. Both sensors have These maps can also be face flow path- the ability to see through the used to determine where this ways between forest canopy which makes water goes. Pathway A leads Delmarva Bays, them ideal for revealing under straight to a ditch and into the which have gen- canopy surface hydrology. Choptank. Pathway B leads to erally been con- The Choptank River Water- a forested wetland where sidered to be shed studies have provided nutrients, sediments, and isolated wet- opportunities to identify the pesticides may be removed lands, and inter- strengths of each sensor for prior to entering the Choptank mittent streams forested wetland characteriza- River. (Figure 6). tion. For example, RADAR can The ability of these wet- provide detailed temporal infor- lands to reduce certain pollut- Figure 5. LiDAR digital elevation map. Darker mation on wetland hydroperiod ants can be estimated utilizing areas are lower and may be wetlands or path- over a broad expanse such as the radar images. This infor- ways for water movement. Circular darkened the Choptank Watershed. Li- mation can be used then to areas are Delmarva Bays. DAR can provide very detailed best conserve wetland func- surface elevation maps and tion and to implement other point-in-time inundation maps best management practices A B which are extremely useful for properly. fine scale mapping of wetlands. The combined high resolution temporal and spatial datasets from these sensors can greatly improve understanding Ditch of ecological services Forest that wetlands provide and will likely have C D bearing on the management and conservation of wetland ecosystems in agricultural landscapes. Building Better Wetland Maps. An example of the synergistic advantage of these two tools is provided in Figure 7. The top image shows a farm with agricultural fields and a small for- Figure 6. Comparison of LiDAR intensity (A) and traditional ested area in the right aerial photography (B) of the same forested wetland areas. hand bottom corner. Figure 7. Aerial photo of farm com- Wetland maps created using these two types of data are shown pared with LiDAR and RADAR maps This area has been in C and D. Inundated areas are better delineated by LiDAR and flow paths drained through the and surface flow pathways between wetlands are much clearer. use of ditches.

Improving Cover Crop Programs Page 8

Winter Cover Crop Programs

Triticale Canola Conventional Cover without fall fertilizer applica- nization, soil phosphorus Ryegrass Spring Oats 1% Rape Crop Cost-Sharing. Farm- tion) and legume-grass cover management, erosion preven- 3% 0% 2% ers who enroll in the Mary- crop mixes for use on certified tion (Kaspar et al. 2001), Rye land conventional cover crop organic farms. This combina- farm profitability (Watkins et 9% cost-share program are com- tion of cover crop cost-share al. 2002), pest control (Staver Barley pensated at a variable rate programs receives consider- and Brinsfield 1998), and 18% that pays more for early-and able annual funding. It is ex- yield of following crops (Hively standard-planting dates (Sept pected to make a significant and Cox 2001; Kabir and Ko- 15 - Oct 15) than for late- contribution to the reduction of ide, 2002; Snapp et al. 2005). planting dates (up to Nov 5) non-point source agricultural These positive environmental Wheat (Figure 8). Nutrient applica- nutrient pollution to the effects, however, can be lim- 67% tion is prohibited prior to Chesapeake Bay. ited if the cover crops are not March 1st of the following Cover Crop Benefits. Rye established in a manner that year, and the cover cover crops have been shown promotes the growth of abun- Figure 8. crop may not be to decrease leaching of soil N dant biomass prior to the 2007/2008 Oct 15 to harvested for sale. by up to 80% by reducing winter season. Maryland Nov 5 Commodity available soil nitrate concen- Cover Crop 16% Cover Crops. Ad- trations during winter months Program Acres ditional cost-share (Staver and Brinsfield 1998; by species programs support Shipley et al. 1991; Strock et (above) and Oct. 1 to 15 Before Oct. 1 the implementation al. 2004). Cover crops have by planting 25% 59% date (right) of commodity cover also been shown to have bene- crops (grain crops ficial effects on soil aggregate grown for market stability and mycorrhizal colo-

Satellites Provide a Watershed View of Cover Crop Performance

Estimating Cover Crop red) / (NIR + red)]. The NDVI, Effectiveness. Current esti- which correlates closely to plant mates of cover crop effective- leaf area index (Weigland et al. ness and nutrient uptake effi- 1992), has been used success- ciency rely heavily upon small- fully to measure the biomass, plot (e.g., Shipley et al. 1991) yield, N status, chlorophyll con- and catchment-scale experi- tent, and photosynthetic capacity mental data (Staver and Brins- of wheat crops (Bendetti and field 1998) extrapolated to Rossini 1993; Hansen and Schjo- match implementation acre- erring 2003; Reyniers and Vrindts ages. In practice, however, 2006; Weigland et al. 1992). landscape-scale variability in Combining Techniques. The physical, environmental, and current study derived estimates farm management parameters of cover crop N uptake efficien- makes estimation of the actual cies at the landscape scale by magnitude of cover crop N up- using a combination of satellite take complex. remote sensing imagery, on-farm Normalized Difference sampling, and acquisition of agro- Vegetation Index. Remotely- nomic data from cost-share pro- sensed data have long been gram implementation records used to estimate vegetation (Figure 9). This innovative meth- abundance in the landscape (Lu odology allowed the direct 2006; Pinter et al. 2003). A evaluation of agronomic factors commonly used measure (species choice, planting date, (Tucker 1979), the Normalized and planting method) affecting Difference Vegetation Index cover crop productivity. It also (NDVI), is calculated as a ratio allows accurate cost-benefit Figure 9. SPOT satellite image of the Tuckahoe Creek Branch, Choptank River. Red areas indicate vegetation. Cover crop of red and near-infrared (NIR) analysis of cover crop programs fields are shown in yellow. Biomass and soil sampling locations reflectance: [NDVI = (NIR – (Figure 10). are shown in orange.

Improving Cover Crop Programs Page 9 Nitrogen Uptake by Cover Crops Governed by Species and Planting

16 Overall Findings Future Goals Planted Sept. 7 to Oct. 15 14 Planted After Oct. 15 • The combination of satellite • Develop an operational 12 remote sensing with conserva- monitoring tool allowing tion practice implementation watershed managers to 10 data allows the evaluation of effectively manage winter (pounds/acre) cover crop performance on a cover crops, including the 8 landscape scale and the identi- ability to target implemen- fication of most successful tation to achieve environ- uptake

6 management strategies. mental endpoints. 4 • Early planted rye and barley • Expand the use of remote Nitrogen 2 cover crops produce a greater sensing and GIS technolo- biomass and therefore take up gies to monitor erosion 0 significantly more nitrogen than control in the upland Pied- Rye Barley Wheat early planted wheat cover mont landscape.

$10.00 crops. Pre‐Oct. 15 Post‐Oct. 15 $9.36 $8.99 • Begin scale-up of technol- $9.00 • An emphasis on early planted ogy transfer by working $8.00 rye and barley will increase the with Soil Conservation $7.02 efficiency of cover crop cost- Districts to develop opera-

abatement $7.00

N share programs by reducing tional GIS tools for cover

$6.00 of crop monitoring and man- the cost of nitrogen removal. $5.00 agement. • The recommended target cover pound $4.00 $3.46 crop biomass for control of root $3.07 per

$3.00 zone nitrate is about 1 ton per acre. $2.00

Dollars $1.00 Upcoming Publication $‐ Rye Barley Wheat Hively, W.D. et al. 2009. Using satellite remote sensing to estimate winter cover crop nutrient uptake efficiency. Figure 10. Nitrogen uptake by cover crops and cost of N abate- Journal of Soil and Water Conservation. (in press) ment relative to planting date

Leveraging Resources: Two Targeted Watersheds Grants Awarded

Scientists working on the Innovative BMP Implementation Implementing and Evaluat- crops, assess yield reduc- Choptank River CEAP project Strategies to Improve Water ing Small Grain Commodity tions and economic cost/ cooperated with Maryland Quality within the Choptank River Cover Crops for Water Qual- benefit associated with Department of Agriculture Watershed with a Targeted Effort ity Protection and Bio- eliminating fall fertilization staff received two grants in the Tuckahoe Sub-Basin Energy Production: Chester on small grains. from the National Fish and Grant Period: 3/2006 to 9/2009 River Watershed Wildlife Foundation’s Tar- Funding: $ 982,000 Grant Period: 4/2008 to 9/2010 geted Watersheds Program. Objectives: Funding: $ 375,400 Funding was supplied by the • Increase cover crop implementa- Objectives: U.S. EPA and the Chesa- tion on the Tuckahoe Creek Brach • Evaluate the environmental peake Bay Trust. by 6000 acres. and economic benefits asso- • Develop improved nutrient reduc- ciated with barley and wheat tion efficiencies for conventional commodity cover crops cover crop, commodity cover crop grown within the Choptank and drainage control structures. River and Chester River Wa- tersheds. • Develop a flexible, user-friendly planning tool that may be used by • Utilize remote sensing and on conservation program managers to -farm research to quantify optimize BMP implementation nutrient uptake by winter small grain commodity cover

Controlled Drainage for Nutrient Reduction

Page 10

Assessing the Effectiveness of Controlled Drainage Structures

Controlled Drainage Struc- controlled drainage structures in tures. Because of the exten- the watershed but very limited sive ditch drainage network in data exists to support their Water flux Phosphorus 9 the watershed, the potential effectiveness on the Delmarva 15 Nitrogen 0.15 exists for substantial reduction Peninsula. Results from field of nitrogen export from agricul- experiments conducted in North tural fields using flow control Carolina indicated that up to a 10 0.10 6 structures installed in these 60% reduction in nitrogen ex- ditches. By restricting ditch port is possible (Osmond et al. 5 0.05 3 water flow, these structures can 2002). Delaware has proposed N flux (g/10 minutes) (g/10 N flux

promote the formation of anoxic using a 45% efficiency factor fluxP (g/10 minutes) Water flux (L/10 minutes) (L/10 flux Water conditions in the elevated and the Chesapeake Bay Pro- 0 0.00 0 groundwater and the ditch wa- gram has accepted a recom- ter behind the structure which mendation of 33% reduction to is necessary for denitrification. be used in their Bay Water 0.0 0.5 1.0 1.5 2.0 2.5 Pilot Programs. MDA has a Quality model (Palace et al. Fraction of Day pilot program to introduce the 1998; Osmond et al. 2002). Figure 12. Flux of water and nutrients through a drainage control structure during a storm event. Water flux in the controlled drainage Conference Proceeding structure was monitored by use of a V-notch weir (90o) with water height monitored using a bubbler flow meter. Water samples were Sadeghi et al. Watershed Model Evaluation of Agricultural Ditch collected hourly during the event by auto-sampler. Drainage Control Structures for Improved Water Quality, 21st Century Watershed Technology: Improving Water Quality and Environment Conference Proceedings, 29 March - 3 April 2008, Results. Several control storm flow increased, the Concepcion, Chile 701P0208cd. drainage structures were in- nitrate concentration and stalled in the Choptank River flux increased markedly watershed in 2006 and 2007. (Figure 12). Increases in Nutrient concentrations were phosphorus concentration measured under base flow and and flux lagged slightly be- storm flow conditions. The data hind those of nitrate and suggest that the increased deni- may indicate slower overland trification occurs under no or flow delivery due to prefer- base flow conditions with little or ential flow mechanisms no nitrate in ditch water. flushing groundwater nitrate. However, significant flushing This event represented ex- of groundwater nitrate through port of 0.53 kg N and 0.007 these structures takes place kg P from an estimated with storm flow events. As drainage area of 2.6 ha.

Figure 11. Controlled drainage structure and ditch equipped with flow monitoring and sampling equipment (above). Top view of controlled drainage structure. Boards can be added and removed to adjust water levels (right).

Controlled Drainage for Nutrient Reduction

Page 11

Examining Denitrification Using Nitrogen Isotope Signatures

Denitrification Assess- dissolved N2 resulting from de- 10 ment in Conservation Tech- nitrification (Bohlke, 2002; A R2 = 0.74 nologies. Assessing the role of Mookherji et al. 2003) which 8 (P<0.001) denitrification in the fate of was then correlated with the agricultural nitrogen at land- isotopic signatures in the nitrate 6 scape and watershed scales has pool. These combined meas- been nearly an intractable prob- urements for groundwater can lem. Such assessments, how- also provide calibration for the 4 ever, are needed to measure isotopic signatures for nitrate N/L) Nitrate (mg more accurately the effective- found in ditches and streams 2 ness of BMPs, such as riparian which integrates denitrification buffers, wetlands, and con- measurements to the scale of 0 trolled drainage management, drainage. 50 60 70 80 90 to mitigate nutrient pollution. Results. Landscape-scale % Agricultural land The isotopic composition of assessments of denitrification 12 nitrogen and oxygen in nitrate based on isotopic data have R2 = 0.32 can signal nutrient source and/ proven useful for assessing B 10 (P<0.088) or extent of biogeochemical effects of land use on nitrogen processing of the nitrate pool by export. Analysis of stream wa- denitrifiers within ecosystems ter from 13 sub-watersheds in 8 O 18

(Mayer et al. 2002). Denitrifica- the Choptank River watershed δ tion will cause enrichment of showed a strong linear relation- 6 15N and 18O in nitrate with an ship between nitrate concentra- accompanying decrease in ni- tion and the percentage of land 4 trate concentrations. The area under crop production amount of denitrification can be (Figure 13A). 2 calculated from the changes in The residuals between meas- -2 -1 0 1 2 isotope abundances according ured nitrate concentrations and Residual nitrate (mg N/L) to known Rayleigh fractionation estimated concentrations taken relationships (Lindsey et al. from the regression line in plot Figure 13. A. Nitrate concentration in stream water versus 2003). Figure 13A were roughly corre- percentage of agricultural land in the sub-watersheds. The displayed line is fit by linear regression. B. The 18O abun- Isotopic signals. Separa- lated with enrichment of the dance in nitrate in stream water vs. the residual nitrate. tion of the different isotopic heavy oxygen isotope (δ18O) Residual nitrate is the observed nitrate minus the nitrate signals may be challenging, but (Figure 13B). These findings predicted by a linear regression of nitrate concentration vs. in cases where sources such as suggest that denitrification can the percentage of agricultural land in the watershed. commercial fertilizers are well account for the observed re- characterized, the biogeochemi- siduals in nitrate concentration cal signal can be differentiated. and that the isotopic approach For groundwater samples, dis- has merit for landscape scale solved gas analysis (N2 and Ar) assessment of denitrification. was used to detect the excess

Leveraging Resources: Water Quality Grant Awarded to Partners

During this project, Co-PIs Tho- The project focused on detailed mas Fisher, Thomas Jordan studies of denitrification within along with collaborator Kenneth the same 15 subwatersheds Staver received funding using a combination of dis-

($493,000) from AFRI (formerly solved gas measurements (N2,

CSREES) for the project enti- O2 and Ar) and the isotopic tled, “Effects of agricultural composition of nitrate in conservation practices on ni- groundwater and stream water. trate losses from croplands of This project expanded upon but Groundwater sampling for dissolved gases and nitrate the Choptank River basin”. did not duplicate the work described above.

Modeling the Future of the Choptank

Page 12 AnnAGNPs Model Calibration of German Branch

About AnnAGNPS. Ann- sessing future scenarios. There- AGNPS is a model designed to fore, to calibrate AnnAGNPS for evaluate risk and cost/benefit the German Branch, farm man- analyses at the watershed agement schedules were de- scale. The model was developed rived from NASS data and sup- to specifically simulate long- plemented with information term sediment and nutrient gathered from County Extension transport from ungauged agri- Offices. Management schedules cultural watersheds. It runs on for the AnnAGNPS cells reflect a continuous, daily time step, as closely as possible manage- and can be used to estimate ment practices that were imple- surface runoff quantities and mented within 1991-1995. associated pollutant loadings for Evaluation of the 1994 DOQQs watersheds of various scales, (digital orthophoto quarter- from small to very large. quadrangle) was also used to The basic modeling compo- pinpoint spatial information nents are hydrology, sediment, such as the location of poultry nutrient, and pesticide trans- houses. port. The pollutants are routed Crop Rotation and Man- from their origin within the land agement Schedules. Two area and are either deposited typical crop rotation and man- within a stream channel or agement schedules were identi- transported out of the water- fied. Neither rotation included a shed. This approach provides a cover crop because there were watershed model capable of no programs promoting their simulating most of the manage- use in place during that time ment practices that are applied period. All small grains were on farms. AnnAGNPS, like most assumed to be grown as com- other watershed models, uses modity and were fertilized in the SCS curve number tech- the fall and again in spring. The nique to generate daily runoff first rotation accounts for the and RUSLE 1.05 technology 70% of the cropland being un- (Renard et al, 1997) to gener- der conservation tillage man- ate daily estimates of sheet and agement, and the second rota- rill erosion from fields (Geter tion accounts for the 30% of Figure 14. Detailed landuse overlaid with AnnAGNPS cells and Theurer, 1998). the watershed in conventional (black boundaries) for the German Branch subwatershed Land Use Inputs for Mod- tillage management. eling the German Branch. Nutrient Content in Poultry Riparian Buffers. Natural Calibration and Valida- Initial modeling was focused on Litter. Poultry litter was as- riparian buffers have been simu- tion. Within the 1991-1995 the German Branch subwater- sumed to be applied to all lated in AnnAGNPS by increasing time period, AnnAGNPS was shed (Figure 14) which has a cropped fields because inter- the time of concentration (Tc) calibrated using the first 3 long-term record of water qual- views with extension agents and adjusting the RUSLE sub-P years of climate and water ity data. All AnnAGNPS inputs suggested about 95% of Ger- factor in cells that contain ripar- quality data. The last two reflect those occurring during man Branch farmers used some ian areas. Identification of these years (1994 and 1995) were the simulation period (1991- poultry litter on their farms. The areas was performed through used for validation. The Nash- 1995). Model calibration and nutrient content of the litter visual inspection of the overlay Sutcliffe coefficient of effi- subsequent validation were was estimated from literature of the landuse map, 1994 ciency (NS) was used to performed using 1990-1995 provided by the MD Extension DOQQ’s and AnnAGNPS Topaz evaluate model performance. water quality data records pro- Service. Both inorganic and generated cells. The adjustment In recent literature, Nash- vided by Primrose et al. (1997). organic N and P ratios were of those parameters was used Sutcliffe values have been Determining exact manage- needed for the poultry manure as a point of calibration. For used to successfully evaluate ment practices for farms is diffi- and is a sensitive parameter to cells containing buffers, the Tc AnnAGNPS performance for cult because of the inherent N and P outputs of the model was initiated at a 25% increase watersheds in Canada (Leon privacy of farm owners. This (Leon et al, 2004). for the cells containing buffers et al., 2004) and New South information, however, is critical (over a no-buffer scenario) and Wales Australia (Baginska et for accurately applying the the RUSLE sub-P factor was al., 2003). model in developing and as- adjusted to 0.78.

Modeling the Future of the Choptank

Page 13

Predicting Cover Crop Effects in the German Branch

Results. In the German 140 Branch, AnnAGNPS calibration and validation of monthly flow Observed resulted in final NS values of 120 Predicted 0.61 and 0.71 respectively. These values indicate that the 40% cover model performed well at esti- 75% cover mating monthly flows. The final 100 curve numbers after calibration were as follows: corn-no-till-73, corn-conventional-till-76, wheat 80 -72, soybean-72, and fallow-83. Although monthly total N loads were calibrated to a low 60 NS value of 0.51, trends were Total(ton) N fairly well simulated. While this calibration level is only slightly 40 above an acceptable 0.5 value, further adjustments to the input parameters did not improve the 20 calibration. In many cases, AnnAGNPS underpredicted observed N 0 loads, particularly during the summer months. This may be 1991 1992 1993 1994 1995 attributable to the patchy spatial distribution of summer storms. Year Given the quick response time Figure 15. Total N exported from the German Branch subwatershed—observed, model prediction using of the German Branch stream, it actual land use data, and simulation with land use changed to 40% and 75% cover crop is not unreasonable to assume that an isolated thunderstorm producing significant rain within near or within the watershed Cover Crops Effects. The With 40% of the land area the subwatershed might not be boundary was not found. A effect of cover crops on nutrient in cover crops, the Ann- recorded by the off-site climate second source of error in the loads was evaluated by ran- AGNPS cells containing cover station, but could result in run- model predictions is undoubt- domly assigning cover crop crops were not well con- off. edly the result of uncertainty practices to agricultural land use nected spatially; therefore, AnnAGNPS does allow for in the spatial and temporal cells until 40% and 75% acre- the mitigation effect on runoff multiple climate stations, how- variability of management age was achieved. This cover would be expected to be lim- ever, another reliable station practices. crop simulation assumes 1) that ited. When the acreage of winter grain crops are not fertil- farmland in cover crops in- ized and 2) that cover crops creases to 75%, more of the replace both winter conventional AnnAGNPS cells with cover grain crops and winter fallows. crop are connected, multiply- In this scenario, 40% cover ing the mitigation effects on cropping resulted in little yearly runoff. reduction in total N, however Conclusion. Simulation of increasing the percentage of two different cover crop lev- cover crop to 75% yielded a els in the watershed revealed dramatic decrease in total N that a high level of cover crop at the outlet (Figure 15). The implementation is needed response in N runoff to percent (more than 40%) before any cover crop does not appear to significant effect on N loads be linear. The reason for this is in the German Branch can be not well understood, but may be observed. related to the placement of cover crops within the watershed during the simulation.

Gathering spatial data for modeling efforts

Outreach to the Agriculture Community

Page 14

Customer Workshops and Outreach Activities

A number of different types of outreach activities have been car- ried out as part of this project to keep our customers informed.

CUSTOMER WORKSHOPS tour demonstration of different sampling techniques was given October 19, 2006— A 1-day for attendees. workshop was held in Ruths- burg, Maryland within the March 25, 2008— Another 1- Choptank River Watershed. day workshop was attended by Attendance was around 60 approximately 100 people in- people including producers, cluding congressional staffers, county extension personnel, scientists from several states, Maryland Department of Agri- and representatives of all the culture, other government groups listed above. This agencies such as US EPA, US workshop included field dem- Forest Service, USGS, and onstrations and a panel discus- other ARS and university sci- sion to identify agricultural Additional Outreach Activities • Maryland Chesapeake Bay entists. Presentations were research efforts are critical to included: Restoration Fair—2007 provided on the various as- the restoration of Chesapeake pects of the project, and a field Bay tributaries. • Queen Anne’s County Agronomy • Maryland Pesticide Net- Day—2006-2007 work—2007-2008

• Caroline County Public Drainage • Maryland Soil Conservation Association Annual Meeting — Districts Tour of Choptank 2006-2008 Watershed sponsored by Maryland Department of • Choptank River Tributary Strate- Agriculture —2008 gies Team Meeting—2006 • Chesapeake Bay Commis- • USEPA Targeted Watersheds sion Cover Crop Enhance- Workshops 2006-2008 ment Workshop—2008 • Queen Anne’s County Maryland • CRC Ecosystem Based Man- Extension—2007 agement Workshop—2009 • Caroline County Maryland Exten- • March 2009 – Association of sion Office—2007 State Wetland Managers: • Ditch Drainage Tour of Eastern State/Tribal/Federal Coordi- nation Meeting Presenta- Shore - 2007 tion—2009

SCIENTIFIC CONFERENCES • American Society of Agronomy National Meetings: 2005—2008 • American Chemical Society National Meetings: 2006— • International Geoscience and 2008 including Symposium Remote Sensing Symposium: on Water Quality in Chesa- 2008 peake Bay 2008 • Society of Wetland Scientists • Soil and Water Conservation Presentations: 2008 Society National Meetings: 2005—2008

References

Page 15

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Acknowledgement

• This work was funded in part by the USDA-NRCS Special Emphasis Watersheds Program of the Conservation Effects Assessment Project. Additional NRCS funding was also received from the USDA-NRCS Wetlands CEAP Program.

• This work was also funded by USDA-ARS as part of the Natural Resources and Sustainable Agricultural Systems National Programs.

• Additional funding was also received from NOAA-NOS as part of a parallel project “Impacts of concentrated animal feeding operation (CAFO) related stressors on a costal environment”.

• Additional funding sources from USDA-AFRI and NFWF (USEPA) are described within the report text.

Photography Credits

• USDA-ARS and partners • IAN Image Library (www.ian.umces.edu/imagelibrary/)

Disclaimer

• Use of trade names does not imply an endorsement of the products named or criticism of similar ones not names.