Evaluation of Overland Flow Paths Generated from Multiresolution DEMs J.M. Shawn Hutchinson 1, Stacy L. Hutchinson 2, and I.J. Kim 2 1 Department of Geography and 2 Department of Biological and Agricultural Engineering Kansas State University Manhattan, Kansas

AAG DenverDepartment of Geography, Kansas State University2 The Problem: NPS Pollution Largest contributors to surface water impairment are nonpoint source (NPS) pollutants – sediment, nutrients, pathogens, other chemicals Percent of Impaired Waters (1998) HUC 8 Scale “40% of streams in US are considered contaminated..”

AAG DenverDepartment of Geography, Kansas State University3 One Solution: VBS Vegetated buffer systems (VBS) – common and sustainable BMP for mitigating NPS pollutant transport

AAG DenverDepartment of Geography, Kansas State University4 VBS Illustrated Zone 1Zone 3Zone 2 Grass – control runoff, sediment Shrubs – nutrient removal Trees – bank stabilization Design standards from USDA Farm Service Agency and Natural Resource Conservation Service Source: NRCS Photo Gallery

AAG DenverDepartment of Geography, Kansas State University5 Assumptions… W L Uniform Sheet Flow A = W x L Concentrated Flow A = W x L x β β = A – Ineffective Area Hydrologic and Vegetation Conditions

AAG DenverDepartment of Geography, Kansas State University6 Overall Objectives To determine optimal DEM spatial resolution to model soil erosion processes To evaluate the efficiency of different VBS designs

False-Color Composite Landsat TM 5; June 7, 1997 N

AAG DenverDepartment of Geography, Kansas State University8 DEMs and Hydrology Zhang and Montgomery (1994) 10 m resolution is recommended Kuo et al. (1999) Hillslope curvature an important factor Runoff volume is affected most by DEM resolution during dry seasons Moglen et al., (2001) Coarser resolution DEMs tend to overestimate peak stream discharge

AAG DenverDepartment of Geography, Kansas State University9 DEM Creation GPS data collected on-site at 3m intervals using DGPS unit Raster DEMs created from interpolated point datasets of varying density: 30m, 10m, 3m ArcHydro tools Flow paths - D8 method

10 m3 m 30 m USGS 30 m

AAG DenverDepartment of Geography, Kansas State University11 Hmmmm…. Best resolution DEM for representing flow processes and ability to capture/assess small (sub-pixel) BMPs Traditional “flow accumulation” flow paths not sufficient Compounding assumptions – effective VBS relies on sheet overland flow Observed channelized flow (rill erosion) – need to identify where channelized flow begins

AAG DenverDepartment of Geography, Kansas State University12 Time of Concentration Time of concentration t watershed = t overland flow + t channel flow + t detainments t ov = equilibrium time when rainfall intensity equals runoff discharge rate Differences in the observed and computed t ov results from the transition from sheet to concentrated flow Sheet: [t ov measured ] ≈ [t ov-computed ] Concentrated: [t ov measured ] >> [t ov-computed ]

AAG DenverDepartment of Geography, Kansas State University13 Kinematic Wave Equation Federal Aviation Administration (1970) t ov = [1.8(1.1-C)L 0.50 ]/S C: rational method runoff coefficient Morgali and Linsley (1965); Rogan and Duru (1970) t ov = [0.93(nL) 0.6 ]/[i 0.4 S 0.5 ] Primary Variables: n = Manning’s coefficientL = slope length S = slopei = rainfall intensity

AAG DenverDepartment of Geography, Kansas State University14 When Sheet Flow? Ignoring impervious surfaces … Izzard (1946): iL (in/hr x ft) < 500 Not fully verified (Rogan and Duru 1972) SCS TR-55 (1986): Slope length < 300 ft Lacks justification (McCuen and Spiess 1995)

AAG DenverDepartment of Geography, Kansas State University15 Kinematic Wave Criteria McCuen and Spiess (1995) t ov = [0.93(nL) 0.6 ] / [i 0.4 (S 0.5 ) 0.6 ] Assessed measured and computed t ov from 59 field sites and lab experiments

AAG DenverDepartment of Geography, Kansas State University16 So What? Where calculated values of nLS -0.5 on a hillslope (or plot) is less than 100, sheet flow is the dominant flow type. Apply this measure to guide VBS placement within a watershed Good: Independent of i (rainfall intensity) Problem: Spatial estimates of Manning’s n

AAG DenverDepartment of Geography, Kansas State University20 Parting Shot… Flow paths from cell accumulation routines don’t address energy required for initiating rill erosion Identifying nLS -0.5 threshold will help place VBS where they can be most effective, and where model assumptions are valid – sheet flow dominated slopes Extend nLS -0.5 method to identify gully erosion sites…

AAG DenverDepartment of Geography, Kansas State University21 Acknowledgements Strategic Environmental Research and Development Program “Assessing the Impact of Maneuver Training on NPS Pollution and Water Quality” Project #CP-1339 Geographic Information Systems Spatial Analysis Laboratory, Kansas State University

AAG DenverDepartment of Geography, Kansas State University22 Applying the nLS -0.5 Criteria

AAG DenverDepartment of Geography, Kansas State University23 Operational Requirements Hydrologic Condition Maintaining uniform sheet flow through buffer Overland flow often becomes concentrated (Dillaha et al. 1986; Fabis et al. 1993; Dosskey et al. 2002) Vegetative Condition Maintaining healthy dense vegetation growth Vegetation condition varies within and between years

AAG DenverDepartment of Geography, Kansas State University24 Models assume sheet flow Best resolution DEM for representing flow processes and ability to capture small BMPs Traditional “flow accumulation” flow paths not a sufficient for Assuming VBS effective in removal – but it’s assumption is overland flow Observed channelized flow – need to understand where channelization initiates and not violate model assumptions Rill erosion (up to 200 mm deep) is onset of channelization = biggest cause of sediment transport (enough water with enough energy to move dirt)