Livingston, Stanley J

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Long-Term Watershed Monitoring - Do's and Don'ts  S.J. Livingston1   The USDA-ARS National Soil Erosion Research Laboratory (NSERL) initiated a watershed monitoring network in northeastern Indiana in 2002.  The objectives of this network include monitoring nutrients, pesticides and soil loss from agricultural lands at the field to watershed scale, using a paired nested approach.  We are also evaluating topography, land-use, and conservation practices influences on losses from these watersheds.  New and innovative BMP’s are being evaluated at the field and watershed scale (Smith and Livingston, 2013).  The data is also being used for validation of new and existing modelling efforts.  This network has expanded from three ditch sites monitoring/sampling flow, to nine stream/ditch sites and six surface/subsurface edge-of-field monitoring locations monitoring flow, turbidity, and 14 weather/soil moisture installations mostly co-located at existing water quality monitoring stations (Table 1).  Each station is networked wirelessly and accessible via the internet in near real-time.  Transducer level and ultrasonic velocity sensors (AV sensors) are used in ditches and in field tile monitoring locations for calculation of discharge under all conditions.  Surface runoff is measured using topographic depression collector tile inlets (tile risers) as well as weirs (Figure 1) and flumes in locations with free fall to ditches utilizing instream transducer AV sensors along with bubbler and ultrasonic level sensors.  This work has allowed for the study and development of an NRCS-approved alternative drainage system, the blind inlet, which has been shown to reduce sediment loads by up to 85% (Smith and Livingston, 2013).  Cooperator interaction (Figure 2) is critical and an ongoing process, requiring face-to-face interaction and sharing of pertinent data.  This presentation will describe the lessons learned while developing a network such as this, which is now part of the Conservation Effects Assessment Project (CEAP) (Maresch et al., 2008), the Long-Term Agroecosystem Research (LTAR) network  (Walbridge and Shafer, 2011), and the Soil Moisture Active/Passive (SMAP) satellite calibration/validation project (NASA-JPL, 2016).    Figure 1. Edge of field monitoring.                    Figure 2. Field trips and demonstrations.                                                            1Stanley J. Livingston, Soil Scientist, USDA-Agricultural Research Service, National Soil Erosion Research Laboratory, West Lafayette, Indiana, USA. Corresponding author: S.J. Livingston, email: Stan.Livingston@ars.usda.gov. Table 1. Monitoring station descriptions.      References Maresch, W., M.R. Walbridge, and D. Kugler. 2008. Enhancing conservation on agricultural landscapes: A new direction for the Conservation Effects Assessment Project. JSWC 63(6): 198A-203A.  NASA-JPL. 2016. SMAP Soil Moisture Active Passive - Cal/Val Activities. NASA, Jet Propulsion Laboratory, California Institute of Technology. Available at: http://smap.jpl.nasa.gov/science/validation/. (Accessed 24 March 2016) Smith, D.R., and S.J. Livingston. 2013. Managing farmed closed depressional areas using blind inlets to minimize phosphorus and nitrogen losses. Soil Use & Mgmt. 29(s1): 94-102. Walbridge, M.R, and S.R. Shafer. 2011. A long-term agro-ecosystem research (LTAR) network for agriculture. Conference Program, Fourth Interagency Conference on Research in the Watersheds, 26–30 September 2011, Fairbanks, AK. pp. 44-45.  Site ID hectares Site type Major Soils Land Use/Cropping Site ID hectares Site type Major Soils Land Use/CroppingAXL 4303 watershedBlount silt loamPewamo silty clay, Glynwood loamRawson sandy loam, Rensselaer loamSebewa sandy loam78% Agriculture14% Grass/Pasture6% ForestBLG 1417 watershedBlount silt loamPewamo silty clayGlynwood loamSebewa sandy loamRensselaer loam83% Agriculture12% Grass/Pasture3% ForestALG 1934 watershedBlount silt loamPewamo silty clayGlynwood loamRawson sandy loamMorley silty clay loam77% Agriculture16% Grass/Pasture6% ForestBME2 123 watershedBlount silt loamPewamo silty clayMoreley silty clay loamGlenwood loam78% Agriculture22% forestAME 298 watershedRawson sandy loamPewamo silty clayMorley silty clay loamBlount silt loam79% Agriculture15% Grass/Pasture4% ForestBME2b 2.15 edge of fieldBlount silt loamGlenwood loamPewamo silty clay100% agricultureAS1 2.22edge of fieldPewamo silty clayGlynwood loamMorley silty clay loam100% Agriculture CLG 1380 watershedBlount silt loamPewamo silty clayGlynwood loamMorley silty clay loam 73% Agriculture17% Grass/Pasture5% ForestAS2 2.71edge of fieldGlynwood loamBlount silt loam100% Agriculture CME2 308 watershedBlount silt loamPewamo silty clayMorley silty clay-loamGlenwood loam60% Agriculture40% CRP/non Ag or low density ResidentialADE 4.88edge of fieldPewamo silty clayGlynwood loamMorley silty clay loamWallkill silt loam100% Agriculture CME2b 80 watershedBlount silt loamPewamo silty clayMorley silty clay-loamGlenwood loam93% Agriculture7% ForestADW 4edge of fieldPewamo silty clayGlynwood loamMorley silty clay loamWallkill silt loam100% Agriculture F34 19259 watershedBlount silt loamPewamo silty clayGlynwood loamRawson sandy loam Rensselaer loamSebewa sandy loam74% Agriculture14% Grass/Pasture8% Forest3% developedADWT 2edge of fieldPewamo silty clayGlenwood loam100% AgricultureD05, D10, D20, D14NA Weather/Soil only NA NA

Long-Term Watershed Monitoring - Do\u27s and Don\u27ts

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Long-Term Watershed Monitoring - Do\u27s and Don\u27ts

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