United States Department of Natural Resources Conservation Service Depressional Water Storage Conservation Effects Assessment Project (CEAP) CEAP- Science Note Volume on the Delmarva Peninsula March 2019 Potential to Improve Storm Flow Mitigation

Summary of Findings Background elevation model (DEM) estimated that 17,000 depressional features • This assessment validated the Wetlands provide an important exist on the Delmarva Peninsula, use of airborne LiDAR for accurate by modulating most of these being current or former measurement of depressional wet- storm flows and reducing the Delmarva bays (Fenstermacher et al. land elevation and morphology in a frequency of stream flood stage 2014). This estimate was an order low-relief landscape. and subsequent flooding of urban, of magnitude higher than reported • A majority (58 %) of the identi- suburban, and rural landscapes. in previous studies (Stolt and fied depressions on the Delmarva Watersheds with drained wetlands Rabenhorst 1987). Peninsula are classified as prior have reduced water storage capacity converted cropland. and less modulated (i.e., spiky) The extensive drainage of Delmarva • Another 18 % of total identified stream flows, making them more bays, primarily via ditches, to depressions are in mixed land use (i.e., subject to flooding (Miller and support agricultural activities has cropland and forestland), many of which Nudds 1996). undoubtedly had marked effects are likely drained. on water storage capacity and • Total estimated storage volume The majority of wetland loss hydrologic flow regulation services. associated with identified depressions within the United States has However, the status of depressional was 35,900 ha-m, including 16,900 occurred through drainage. wetland water storage and the ha-m on cropland, 12,400 ha-m on Organized ditch drainage on the potential for increased storage with forestland, and 6,600 ha-m on mixed Delmarva Peninsula dates to wetland restoration on the Delmarva forest and cropland. the 17th century with formation Peninsula are unknown, as is the • Mid-Atlantic Region restored wet- of the first recognized public extent of water storage volume loss land study sites had substantially less drainage association in North due to the conversion of natural storage volume than average depres- America (Bell and Favero 2000). wetlands to croplands. sions located on forestland and crop- Although depressional wetlands land, indicating that there is potential are prominent in the Delmarva This Mid-Atlantic Region (MIAR) to enhance performance of wetland landscape, they were once even CEAP-Wetland study provides restorations for improved storage more common. Many have been an estimate of surface water volume on Delmarva landscapes. drained to allow for agricultural storage volume once associated • In general, the agricultural landscape cultivation, primarily corn and with depressional wetlands on the of the Delmarva Peninsula has a very soybean production, in support Delmarva Peninsula, assesses the high capacity for increased surface of a substantive poultry industry proportion of storage volume loss water storage volume and could benefit (McCarty et al. 2008). Between the in this landscape due to drainage from implementation of wetland resto- 1780s and the 1980s, the states that for agricultural production, and ration and drainage control structures. compose the Delmarva Peninsula compares this loss with the gain • When landowners restore wetlands, lost significant amounts of wetland of storage volume associated the potential gains are large, especially area (Delaware 54%, Maryland with implementation of wetland where prior converted croplands are 73%, Virginia 42%; Dahl 1990). restoration practices on cropland. marginal for crop production. Con- trolled drainage structures, on ditches Depressional features, similar Assessment Approach and tile drains, can be used to increase to Carolina bays, are regionally seasonal water storage capacity within known as Delmarva bays and Study Area and Sites prior converted croplands that are cur- occur primarily near the border The research area encompassed rently productive cropland. Remaining between Maryland and Delaware the entire Delmarva Peninsula, forested natural wetlands store sub- in the northern and central portions with validation of extrapolation stantial surface water volume, support- of the Delmarva Peninsula (Tiner methodology occurring in New ing regulation of natural hazards (e.g., 2003; Fenstermacher et al. 2014). A Castle and Kent counties in Del- flooding) and hydrologic flow services detailed geomorphometric analysis aware, and Dorchester, Talbot, within agricultural landscapes. using a LiDAR-derived digital Caroline, and Queen Anne’s coun- ties in Maryland. For validation, Comparing Volume Estimates: lar Networks (TINs) were created for representative subsets were selected Ground-based Surveys vs. Air- individual wetlands using the total sta- from the known Delmarva Penin- craft-based LiDAR tion or LiDAR data points (Figure 1). sula depressions, including natural A set of 20 depressions representing and restored wetlands, as well as natural and restored wetlands and prior Volume calculations were performed prior converted croplands. Natural converted croplands were selected for in ArcMap using the hydrology wetlands were selected from the comparison of storage volume esti- function within the Spatial Ana- Delmarva bays on forestland. Re- mates based on ground-based surveys lyst extension. The spill point—the stored wetlands included cropland and airborne LiDAR. The ground- elevation at which water exits the areas that had been hydrologically based surveys took place during the depression—was selected using the restored to depressional wetlands summer and fall of 2012 (dry season), spill point function in 3D Analyst through USDA conservation pro- ensuring the greatest access to all and confirmed using multiple years grams. Prior converted cropland sections of the wetland using construc- of aerial imagery and DEMs. This sites included in the survey were lo- tion-grade robotic total station survey elevation point was then used in the cated on active croplands containing equipment. Elevation readings were Volume and Surface Area tool in roughly circular depressional areas taken in 0.3-m increments in areas ArcMap. Volume calculations from with morphologies approximating of rapid change, such as ditches and LiDAR-derived DEMs and total those established for Delmarva bays berms, and 5-m increments in areas of station surveys were compared. (Fenstermacher et al. 2014). minimal relief. Pairing Restored Wetlands with Outline of Storage Volume Scaling Total station data points were correct- Representative Natural Wetlands and Approach ed and processed with Trimble GPS Prior Converted Croplands This study used the following Pathfinder and imported into ArcMap Eleven wetland groups were formed multistep calibration and validation (ESRI, Redlands, CA). LiDAR data to assess the effectiveness of wetland process for scaling storage volume were collected from the Maryland restoration for the reestablishment of estimates across land cover Department of Natural Resources, the surface water storage volume. Each within the Delmarva Peninsula: 1) state of Delaware, or the Agricultural group contained one natural wetland, Validate the use of LiDAR-derived Research Service (ARS). All LiDAR one restored wetland, and one prior DEMs to estimate storage volume data had a vertical accuracy of ≤ 18 converted cropland resulting in 33 rep- using a field-based approach cm RMSE and were designed to meet resentative sites across the wetland al- at 20 depressional wetlands; 2) or exceed Federal Geographic Data teration gradient, most of which were Calibrate and validate a generalized Committee National Standards for also used to assess LiDAR reliability. formula to estimate depression Spatial Data Accuracy for data at a The natural wetland and prior convert- volume based on surface area, scale of 1:2,400. Estimated horizontal ed cropland pairs were selected to be relief, and a constant optimized positional accuracy of point returns within a 5 km buffer of each restored for Delmarva bays using a set of exceeds 50 cm. Triangulated Irregu- wetland. This approach minimized 58 representative depressional wetlands; 3) Test the utilization of median depression area against measured area for assigning land cover to wetlands within the set of 58 wetlands using high resolution imagery for validation; 4) Characterize distributions of measured relief and radius for a random subset (1,372) of the regional Delmarva bay population and further test use of median radius for land cover assignment using coarse resolution (30 m) National Land Cover Dataset (NLCD); 5) Use the distributions measured in the subset to randomly assign relief and radius to the full Delmarva bay population (about 14,500) and calculate storage volume using the calibrated general formula; 6) Assign land cover to the full population using the intersection of a median radius polygon with the land cover map. Figure 1. Example of a TIN created from ground-based survey data.

2 the influence of observed geographic (P), which varies from values of less bays. Fenstermacher et al. (2014) gradients in depression morphology than one to values greater than one further characterized the morphology (Fenstermacher et al. 2014). Wetland for convex and concave depressions, of 1,494 depressions selected through morphologic characteristics (i.e., area, respectively. The average value stratified random selection (roughly relief, and volume) typical for the of P for Delmarva bays—29 prior 10 % of the measured population) region were derived from the 33 rep- converted croplands and 29 natural by determining surface area, major/ resentative sites using the LiDAR-de- bays (total of 58)—were characterized minor axis, and orientation by man- rived DEMs and volume calculation by measurement of storage volume, ual construction of morphometric protocols described above. surface area, and relief using LiDAR- polygons (Figure 2). The relief of derived DEMs and ArcMap. Analysis these depressions was determined by Derivation of Equation for Calculat- of restored wetlands was not included measuring the elevation of three ran- ing Regional Storage Volume because they did not fit the model dom points in the depression relative Hayashi and van der Kamp (2000) based on natural processes. The sites to rim locations. In the present study, developed a generalized formula for selected were within the interval a portion of this population subsam- deriving the volume of depressional between the 1st and 3rd quartile of the ple (n=1,372) was used to estimate wetlands, which was used to calcu- median size of depressional wetlands storage volume for the full population late storage volume in vernal pools in the region (based on Fenstermacher set based on the Hayashi and van der (Brooks and Hayashi 2002). Ver- et al. 2014). The distribution of P was Kamp (2000) equation. nal pools exhibit many of the same found to be normal, and the average characteristics as Delmarva bays. The P along with measurements of area To account for skewness, each de- formula relates storage volume to and relief were used to estimate pression was randomly assigned a surface area and relief by inclusion of storage volume across the Delmarva surface area bin based on the distri- a dimensionless constant P. Peninsula (see next section). butions of depression radii for their respective land cover classes. The The Hayashi and van der Kamp (2000) Regional Estimation of Storage mixed class locations were random- formula, in which A = Area, V = Volume ly assigned to bins in the combined Volume, h = depth (relief), and P = a Using LiDAR coverage of the Del- (all) distribution. The depressions constant, is: marva, Fenstermacher et al. (2014) were then randomly assigned to relief identified and hand digitized the point histogram bins based on distributions V = (A * h)/(1 + 2/P) locations of nearly 15,000 Delmarva of depression relief for their respec- bays and then extrapolated findings tive land cover classes. This use of Calibration of the formula for a given to areas without LiDAR coverage for double randomization was found to area requires calculation of a constant a total population estimate of 17,000 have validity because analysis of

Figure 2. Example of a LiDAR-derived DEM (left) depicting a depressional forested wetland and the associated hand-delineated poly- gon created to represent the depression surface area over-laid on an aerial photograph (right).

3 the approximately 1,500 delineated 1 m) aerial photography. In the case volume estimates (i.e., 79 m3 to polygons demonstrated that surface of the approximately 1,400-wetland 26,700 m3). Overall there was good area and relief were not correlated subset, NLCD was used to assign land agreement between volume esti- (r = 0.08). With completed attribute cover based on both measured radii mates derived from ground- and Li- assignment for surface area and relief, of the morphometric polygons and DAR-based methodologies (Figure volume was then calculated using the median radii of the subset population. 3); on average, LiDAR-derived vol- Brooks-Hayashi formula using a P ume estimates were within 3 % of equal to 1.91, as determined using the Assessment Findings those based on ground surveys. The 58 calibration sites. largest discrepancies occurred with Comparing Volume Estimates: two of the restored wetlands, per- Land Cover Assignment Ground-based Surveys vs. Air- haps due to the inability of ground Land cover data were retrieved from craft-based LiDAR surveys to capture the irregular the 30 m resolution 2006 Multi- Traditionally ground-based surveys shape (i.e., large islands and micro- Resolution Land Characteristics have been used to obtain accurate topography) of some restorations. NLCD (Homer et al. 2015). estimates of depressional storage Intersection of wetland polygons with volume, but the advent of air- Evaluating Ability to Estimate Stor- the NLCD land cover map was used to craft-based LiDAR systems holds age Volume Based on Surface Area classify land use for each depression promise for expanded coverage. and Relief and determine whether the depression Variable wetland characteristics, A population of depressions with sim- is farmed. The threshold criteria such as vegetation cover, can ob- ilar geomorphic characteristics (i.e., used to designate a single land cover struct bare earth determinations Delmarva bays; Fenstermacher et al. classification was 80 % of depression required for accurate LiDAR DEM 2014) raises the likelihood of being surface area. When less than 80 % of development, thus biasing Li- able to predict storage volume based the depression area was occupied by DAR-based estimates of storage on surface area and relief alone. This one land cover class, the depression volume. We explored this potential ability was enhanced by use of the was classified as having a mixed land limitation by comparing estimates generalized Hayashi and van der cover. In the case of the 58-wetland of storage volume derived using Kamp (2000) volume formula. The subset, land cover assignment based ground- and LiDAR-based methods. population of 58 depressional wet- on NLCD was compared to that The depressions used in the analy- lands used to determine the range of obtained using high resolution (about sis varied widely in ground-based P for Delmarva depressional wetlands displayed a wide range of relief, volume, and surface area. All three of these parameters had skewed dis- tributions, with natural wetlands displaying greater skewness (Figure 4). By contrast, values of P were normally distrib- uted for the total (natural + prior converted cropland) population with a mean value of 1.91, and there was no statistically signif- icant difference in P between natural wetlands and prior converted crop- lands. Moreover, within the study area, P was found to be independent of a considerable Figure 3. Comparison of volume estimates using ground surveys and airborne LiDAR digital elevation models range in volume, at prior converted cropland [PCC], natural [NAT], and restored [RST] sites. relief, and surface

4 area. An average P of around 2 indi- cates a substantial concave morphol- ogy, which agrees with the findings of Fenstermacher et al. (2014) for Delmarva depressions. A more ex- tensive assessment of morphometric attributes was conducted using 1,372 natural depressional wetlands and prior converted croplands that were probably former depressional wet- lands whose perimeters had previ- ously been hand delineated (Fenster- macher et al. 2014). Analyses of this population also found that both radius and relief were not normally distrib- uted (Figure 5).

Regional Storage Volume Estimates Results demonstrate that NLCD, with its coarser spatial resolution, predicted prior converted croplands with 97 % accuracy and natural wet- lands with 87 % accuracy when us- ing actual digitized wetland bound- aries. Accuracy was only slightly reduced (average 90 %) when me- dian depressional radius (53 m) was used in conjunction with NLCD to determine land cover. Land cover was assigned to the previously delin- eated depressions using the NLCD based both on measured radii from the Fenstermacher et al. (2014) de- lineations and median radii (53 m), as well as the 80 % criteria (Table 1). Based on this approach, roughly 80 Figure 4. Range in morphometric properties for 29 prior converted croplands (PCC) and % of depressions fell within a single 29 natural wetlands (NAT) used for calibration. Graph representations: boxes = 25th and land type, including 53 % within the 75th percentiles; whiskers = 10th and 90th percentiles; dots = outliers; solid line = medi- agricultural class and 27 % within an; dashed line = mean. the natural forestland class. These findings verified the suitability of Table 1. Comparison of land cover classifications using hand-delineated polygons to using median radius and threshold those based on median radius and 80 % area threshold for single land type classification. values for scaling storage volume Original polygons Median radius measurements per land cover type to Site type the Delmarva Peninsula. Single land Single land type Mixed type Mixed Fenstermacher et al. (2014) detect- All sites 1,095 257 1,117 238 ed about 14,500 depressions on Cropland 732 118 729 107 cropland and forestland that were Forestland 363 139 388 131 consistent with classification as a Delmarva bay. For those point loca- tions, land cover was assigned using approximately 1,400-depression Total storage volume of the the NLCD and median radius. The subset. For the 14,500 population, a 14,500 depressions on cropland depressions were then classified as majority (58 %) of the depressions and forestland was determined to either forestland, cropland, or mixed were found to be located on crop- be 35,900 ha-m. Estimated water using the median radius and 80 % in- land, whereas 23 % were estimated storage volume for depressions on clusion rules. This assessment found to be on forestland and 18% on cropland sites totaled 16,900 ha-m, that 81 % of the 14,500 depressions mixed land cover (Figure 6). These compared to 12,400 ha-m for natural fell within a single land cover class, results are again comparable to those sites and 6,600 ha-m for sites with which is in close agreement with obtained with the use of the 1400-de- mixed classification. A substantial the 80 % finding pertaining to the pression subset. portion of the mixed class

5 depressions is also likely drained This Delmarva Peninsula study cov- regional estimates would become for crop production adding to the ered an area of about 1.55 million more comparable on a depression loss of storage volume. The median ha. In comparison, Gleason et al. per-area basis. storage capacities of depressions (2007) assessed storage volume in were 13,000, 17,100, and 15,300 m3 the Prairie Pothole Region (PPR) Storage Volume in Wetland for cropland, forestland, and mixed over an area of 445,000 ha and es- Restorations land cover, respectively. The natural timated a total depressional storage In the paired wetland assessment, depressions tended to have greater capacity of approximately 56,500 the morphometric properties of 11 surface area (Figure 4), which ha-m. The higher storage capacity restored wetlands were compared likely accounted for their greater per unit of land area in the PPR is to those of geographically similar storage capacity. Nevertheless, likely accounted for by a couple of natural wetlands and prior convert- because of the larger number of factors. One factor is that landscape ed croplands. Data showed that the depressions found on cropland, the relief on the Delmarva is less than range of restored wetland properties cropland land cover classification that on the PPR, and another is that tended to be less than those ob- has the greatest potential for storage Delmarva bays are concentrated in served for natural wetlands and prior volume if the land were not drained the upper portion of the Peninsula, converted croplands (Figure 7). This for agricultural purposes. These with the southern portion having a trend was particularly strong for area results reveal the great potential for low density of depressions (Figure and volume. Median storage volume storage volume gain with wetland 6). If analysis was limited to the of restored wetlands (1,480 m3) was restoration programs. high-density region of the Peninsula, between 53 and 60 % of that for pri- or converted croplands and natural wetlands, respectively (Figure 7). The measured storage volume for restored wetlands was also con- siderably smaller than the median volumes estimated for wetlands in the 58-site calibration set (natural = 5,450 m3, prior converted cropland = 8,260 m3) and almost a factor of 10 smaller than the population esti- mates of volume for depressions on cropland and forestland covering the Delmarva.These findings, in con- junction with the substantially lower number of restored wetlands on the Delmarva Peninsula relative to prior converted croplands and natural wetlands, indicate that current res- torations likely have limited impact on storage volume within the region, but that the potential surface water storage volume gain from restoration is great.

Conclusions

A recent survey of the Delmarva Peninsula discovered nearly 15,000 circular or semi-circular depressions with features consistent with the morphology of Delmarva bays (Fen- stermacher et al. 2014). The MIAR study component described herein found that most of these depres- sions (58 %) are located on actively farmed cropland, representing a loss of 16,900 ha-m of potential storage Figure 5. Distributions for relief and radius of about 1,400 natural wetlands and prior volume to agricultural production. converted croplands. Histograms were created using 26 bins for depression radius and Furthermore, an additional 18 % 11 bins for depression relief. Values on both X axes are in meters. identified depressions were found in

6 areas of mixed cropland–forestland cover, representing a likely loss of potential storage volume of 6,600 ha-m. This combined estimated loss of 23,500 ha-m of potential surface water storage volume has likely had a substantial, negative impact on hydrologic flows, increasing the like- lihood and duration of stream-over- bank events and resultant floods.

Wetland restoration can help modulate hydrologic flows in adjacent streams, in contrast to prior converted croplands, which enable larger flash storm flows directly after precipitation events (McDonough et al. 2015). Restored wetlands exhibited surface water flows intermediate to those of natural wetlands and prior converted croplands. Wetland area was found to be significantly correlated with the periodicity of surface water flows. Even when depressional wetlands are not directly connected to streams via surface water flow, their size and arrangement has been found to be critical for supporting flow in adjacent streams (McLaughlin et al. 2014). Although wetland restoration has been found to have a positive effect on the regulation of hydrologic flows and natural hazard vulnerability, the extremely large volume of surface water storage that has been lost at a landscape scale relative to the modest gains in water storage made possible by restoration highlights the value of Figure 6. Distribution of depressions with cropland, forestland, and mixed land cover increased, sustained restoration. In classifications. general, the agricultural landscape of the Delmarva Peninsula has a very high capacity for increased surface water storage volume. This study provides important perspective on the degree to which implementation of wetland restoration and drainage control structures can take advantage of potential storage volume capacity on croplands.

Figure 7. Range in storage volume for the paired sets of restored (RST), prior converted cropland (PCC), and natural (NAT) sites. Graph representations: boxes = 25th and 75th percentiles; whiskers = 10th and 90th percentiles; dots = outliers; solid line = median; dashed line = mean.

7 References nearby streams along a gradient of in the Mississippi River Valley. agricultural alteration. Wetlands Conservation Biology 10:847-853. Bell, W.H. and P. Favero. 2000. Moving 35:41-53. Stolt M.H. and M.C. Rabenhorst. 1987. water. A report to the Chesapeake McLaughlin, D., D. Kaplan, and M. Carolina Bays on the eastern shore of Bay Cabinet by the Public Drainage Cohen. 2014. A significant nexus: Maryland: I. characterization and Task Force. Contribution No. 2000- Geographically isolated wetlands classification.Soil Science Society of 1. Center for the Environment and influence landscape hydrology.Water America Journal 51:394–398 Society, Washington College. http:// Resources Research 50:7153-7166. Tiner, R.W. 2003. Geographically www.dnr.state.md.us/Bay/tribstrat/ Miller, M.W. and T.D. Nudds. 1996. isolated wetlands of the United public_drainage_report.pdf. Prairie landscape change and flooding States. Wetlands 23:494-516. Brooks, R. and M. Hayashi. 2002. Depth-area-volume and hydroperiod relationships of ephemeral (vernal) Conservation Effects Assessment Project: Translating forest pools in southern New England. Wetlands 22:247-255. Science into Practice Dahl, T.E., U.S. Fish and Wildlife Service, National Wetlands Inventory The Conservation Effects Assessment Project (CEAP) is a multiagency effort to build the science base for conservation. Project findings will help to guide USDA Group. 1990. Wetlands losses in conservation policy and program development and help farmers and ranchers make the United States, 1780’s to 1980’s. informed conservation choices. U.S. Dept. of the Interior, Fish and Wildlife Service, Washington, D.C. One of CEAP’s objectives is to quantify the environmental benefits of conservation Fenstermacher, D.E., M.C. Rabenhorst, practices for reporting at the national and regional levels. Because wetlands are M.W. Lang, G.W. McCarty, and affected by conservation actions taken on a variety of landscapes, the Wetlands B.A. Needleman. 2014. Distribution, National Component complements the national assessments for cropland, wildlife, morphometry and land use of and grazing lands. The wetlands national assessment works through numerous Delmarva Bays. Wetlands 34:1219- partnerships to support relevant assessments and focuses on regional scientific 1228. priorities. This project was conducted through collaboration among researchers with Gleason, R.A., B.A. Tangen, M.K. University of Maryland/College Park (UMD) and USDA, Agricultural Research Laubhan, K.E. Kermes, and N.H. Service (ARS), Beltsville. Primary investigators on this project were Megan Lang Euliss, Jr. 2007. Estimating water (UMD), Gregory McCarty (ARS), and Shelly Devereaux (UMD). This Science Note storage capacity of existing and was written by Drs. Megan Lang and Greg McCarty. potentially restorable wetland Any use of trade, firm, or product names is for descriptive purposes only and does depressions in a subbasin of the Red not imply endorsement by USDA. River of the North: U.S. Geological Survey Open-File Report 2007-1159, For more information, visit 36 pp. http://www.nrcs.usda.gov/wps/portal/nrcs/main/national/technical/nra/ceap, or con- tact Michael Carlo, Acting CEAP-Wetlands Component Leader, at michael.carlo@ Hayashi, M. and G. van der Kamp. wdc.usda.gov. 2000. Simple equations to represent the volume-area-depth relations of shallow wetlands in small In accordance with Federal civil rights law and USDA civil rights regulations and topographic depressions. Journal of policies, the USDA, its Agencies, offices, and employees, and institutions partic- Hydrology 237:74-851. ipating in or administering USDA programs are prohibited from discriminating Homer, C.G., J.A. Dewitz, L. based on race, color, national origin, religion, sex, gender identity (including gender Yang, S. Jin, P. Danielson, G. expression), sexual orientation, disability, age, marital status, family/parental status, Xian, J. Coulston, N.D. Herold, income derived from a public assistance program, political beliefs, or reprisal or J.D. Wickham, and K. Megown. retaliation for prior civil rights activity, in any program or activity conducted or 2015. Completion of the 2011 funded by USDA (not all bases apply to all programs). Remedies and complaint National Land Cover Database filing deadlines vary by program or incident. for the conterminous United States­—Representing a decade of Persons with disabilities who require alternative means of communication land cover change information. for program information (e.g., Braille, large print, audiotape, American Sign Photogrammetric Engineering and Language, etc.) should contact the responsible Agency or USDA’s TARGET Remote Sensing 81:345-354. Center at (202) 720-2600 (voice and TTY) or contact USDA through the Federal McCarty, G., L. McConnell, C. Relay Service at (800) 877-8339. Additionally, program information may be made Hapeman, A. Sadeghi, C. Graff, W. available in languages other than English. Hively, M. Lang, T. Fisher, T. Jordan, To file a program discrimination complaint, complete the USDA Program C. Rice, E. Codling, D. Whitall, E. Discrimination Complaint Form, AD-3027, found online at How to File a Lynn, D. Keppler, and M. Fogel. Program Discrimination Complaint and at any USDA office or write a letter 2008. Water quality and conservation addressed to USDA and provide in the letter all of the information requested practice effects in the Choptank River in the form. To request a copy of the complaint form, call (866) 632-9992. watershed. Journal of Soil and Water Submit your completed form or letter to USDA by: (1) mail: U.S. Department of Conservation 64:461-474. Agriculture, Office of the Assistant Secretary for Civil Rights, 1400 Independence McDonough, O., M. Lang, J. Hosen, Avenue, SW, Washington, D.C. 20250-9410; (2) fax: (202) 690-7442; or (3) and M. Palmer. 2015. Surface email: [email protected]. hydrologic connectivity between USDA is an equal opportunity provider, employer, and lender. Delmarva Bay wetlands and

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