Extending rhem from hillslopes to watersheds
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This document discusses extending the Rangeland Hydrology and Erosion Model (RHEM) from hillslopes to watershed and large areas using the KINEROS2 and AGWA hydrology models. It provides an overview of KINEROS2 and AGWA capabilities for modeling hydrology, erosion, and sediment transport at various scales. It also discusses challenges in obtaining RHEM parameters over large areas and potential approaches using data from the National Resources Inventory, ecological site descriptions, remote sensing, and regression relationships. The document concludes with next steps around improving parameterization and integrating state and transition models and remote sensing data.
Extending rhem from hillslopes to watersheds
- 1. Extending RHEM from Hillslopes to Watersheds and Large Areas with AGWA/KINEROS2 David Goodrich, Haiyan Wei, Mariano Hernandez, Ken Spaeth, Mary Nichols, Shea Burns, Phil Guertin, Carl Unkrich Overview • KINEROS2 – background • AGWA Overview and Rangeland Modeling Tools • RHEM Parameters • From NRI • From remote sensing
- 2. • Hydrology, erosion, sediment transport • Event or continuous (< minute time steps) • Approximate watershed by cascade of overland flow elements (planar or curvilinear), channels, impoundments • Physically-based kinematic interactive routing – infiltration, overland flow, erosion, and sediment transport Kinematic Runoff and Erosion Model (KINEROS2) https://www.tucson.ars.ag.gov/kineros/
- 3. rainfall intensity (i) infiltration (f) Finite difference step length (dx) fi x Q t h -= + channel element Excess Runoff From an Overland Flow Model Element - KINEROS2 / RHEM Q q Zones of aggregation and degradation can be identified in detailed output
- 4. New Features and Capabilities • Incorporation of the Rangeland Hydrology and Erosion Model (RHEM) and a dynamic (non-steady state) version of the Water Erosion Prediction Project Model (DWEPP) into KINEROS2. – Detailed representation of hillslope elements (geometry, soil, vegetation) – DWEPP parameters are available for most cultivated agriculture – RHEM parameters coming with ESD and STM models – Seamless integration between hillslope erosion modeling and sediment transport in channels – Caution: 1-D channel erosion and transport is quite simple (bank collapse, armoring not treated) – Make a distinction between large area modeling (many hillslopes within a watershed) and large watershed modeling (sediment yield at outlet)
- 5. Southwest Watershed Research Center Tucson - Tombstone, AZ EXAMPLE: KINEROS2 / RHEM Simulations Compare sediment yields from different plant community parameterizations on a small watershed using K2 - RHEM Approach • Parameterize a small watershed for RHEM • Use RHEM parameterization equations with values from NRI data for 3 plant communities • Use observed data from storm events that produced sizeable sediment yields • Run RHEM and compare results from different plant community parameterizations
- 6. Southwest Watershed Research Center Tucson - Tombstone, AZ K2 - RHEM Watershed Simulation – 8/6/2006 Event 0 20 40 60 80 100 120 140 1600 10 20 30 40 50 60 70 0 10 20 30 40 50 60 Rainfall(mm/hr) Outflow(mm/hr) Time (min) Precip Natives Shrubs Lehmann 0 20 40 60 80 100 120 140 1600 2 4 6 8 10 12 0 10 20 30 40 50 60 Rainfall(mm/hr) Sedigraph(kg/s) Time (min) Precip Natives Shrubs Lehmann Lehmann vs Natives Shrubs vs Natives Runoff (mm / hr) Sediment (kg / s)
- 7. Watershed ID: 73 Area Slope Profile (Geometric) Width Slope Length Effective Hyd. Cond. Rock Volume (Infiltration) Soil Suction Porosity Max saturation Runoff friction factor (Hydraulic) Erosion friction factor Conc. Flow Erosion Coef. (Engelund- Critical Shear Stress Hansen Splash & Sheet Erosion Coef. Erosion) Particle Size Distribution Interception N Watershed - Large Area Application of KINEROS2 ・ Topography (USGS 10 m DEM) ・ Soils for texture class – (SSURGO) ・ For RHEM need % plant form types % Foliar cover % Basal plant cover % Rock cover % Litter cover % Cyptogram cover Parameters needed for each hillslope model element Pre – RHEM Formulation For K2 – RHEM Formulation need: Motivation for the development of AGWA – Automated Geospatial Watershed Assessment Tool
- 8. AGWA – Background - Basics • An automated GIS interface for watershed modeling (hydrology, erosion, WQ) designed for resource managers • Applicable to ungauged / gauged watersheds • Operates with nationally available data (DEM, Soils, Land Cover) • Simple, direct method for model parameterization • Investigate the impacts of land cover change - Identify sensitive, “at-risk” areas - Assess impacts of management (e.g. growth, fire, mulch) • Provide repeatable results for relative change assessments • Must have good rainfall-runoff observations for quantitative predictions • Three established watershed/hillslope models for multiple scales - KINEROS2 - SWAT - RHEM / DWEPP (hillslope runoff and erosion within KINEROS2) - 4000+ Reg. users; 10,500+ downloads, 170 countries; >250 citations
- 9. Watershed Characterization (model elements) + Land Cover Soils Rain (Observed or Design Storm) Results Run model and import results Intersect model elements with Watershed Delineation using Digital Elevation Model (DEM) Sediment yield (t/ha)Sediment discharge (kg/s) Water yield (mm)Channel Scour (mm) Transmission loss (mm)Peak flow (m3/s or mm/hr) Channel Disch. (m3/day)Sediment yield (kg) Percolation (mm)Runoff (mm or m3) ET (mm)Plane Infiltration (mm) Precipitation (mm)Channel Infiltration (m3/km) SWAT OutputsKINEROS Outputs AGWA Conceptual Design: Inputs and Outputs Output results that can be displayed in AGWA Hillslope
- 10. Visualization of Results Color-ramping of results for each element to show spatial variability Calculate and view differences between model runs Multiple simulation runs for a given watershed Channel simulation differences also displayed 8 Hydrograph/Sedigra ph for overland and channel elements
- 11. Data for AGWA Parameterization • Digital Elevation Model - Usually USGS 10m – 30m DEM will work fine in western terrains in large watersheds - LIDAR can be used • Soils - USDA STATSGO – nationally available; SSURGO where available - FAO soils globally • Land Use - Land Cover (NLCD, ReGAP, ESD) • Weather - If not using design storms - “good” rainfall data is essential in time/space (more later) • Management Information - Where and what - Information must be provided by user! (i.e. burn severity map) Topography Land Cover Soils
- 12. o Representative Slope Profile and Flow Length • Calculate a weighted length for each flow path • Lr is the representative flow length • Calculate a weight grid for every cell on the hillslope • Calculate a weighted slope for each cell - Si NRI Pt (Flanagan et al. 2011)
- 13. o Representative Slope Profile and Flow Length NRI Pt • AGWA/RHEM Calculates a weighted length and slope for each flow path using DEM (Flanagan et al. ‘11) 1374 1376 1378 1380 1382 1384 1386 1388 1390 1392 0 100 200 300 400 500 600 700 800 900 1000 Hillslope Profile (Element 61) AGWA/Flanagan (S=1.6%) Visual Slope Profile (S=1.5%) Uniform Slope (S=1.8%) L = 50m web RHEM Gen. Profile (S=1.7%) Ele. 61 At NRI point estimate uniform slope, L = 50 m (used in RCA) Most natural hillslope proflie have lower slopes at ridge and toe. Digitize 3 flow paths from ridge Using web RHEM to match general hillslope profile
- 14. Sediment Yield vs Soil Loss (total for all elements) Uniform S - HRC Unif. S - ATL Complex S - HRC Comp. S - ALT SedimentYieldandSoilLoss(tons/ha/year) 0 3 6 Sediment Yield Soil Loss Point: Differences in soil loss & sediment yield due to slope shape (uniform vs complex) dominate differences due to change in ecosite cover condition
- 15. AGWA Rangeland Management Toolkit • Use of vegetation data for model parameterization – Vegetation Monitoring Data – Rangeland Health Data – NRCS Ecological Site Descriptions – Management treatment effects • Land cover modification – Use to incorporate rangeland improvements • Stock ponds / reservoirs • Buffer strips • Post-Fire effects • Multi-watershed analysis Post-Fire % Change } Or a Combination
- 16. Land-Cover Modification Tool Allows user to specify type and location of land-cover alterations by either drawing a polygon on the display, or specifying selected features from a polygon map (i.e. a pasture). Types of Land-Cover Changes: • Change entire user-defined area to new land cover (uniform) • Change land-cover type to another (random or patchy/fractal) • Can specify % success of change due to practice (e.g. Shrub management and removal) Large Area Application of RHEM • AGWA will – • Delineate drainage area • Discretize drainage area into hillslopes • Derive the complex slope profile of the hillslopes • AGWA tools will – • Allow incorporation of BMPs • Assess management scenarios • Transition to different ESD state
- 17. Key to Extending RHEM to Watershed Scales ・Obtaining RHEM parameters over large areas: - % plant form present - % Foliar cover - % Basal cover - % Rock cover - % Litter cover - % Cyptogram cover ・ HOW? (NRI, ESD & STM, ReGAP, remote sensing, ??) HUC – 12 Boundary 0 – 10 % INCREASE 25 – 30 % decrease 40 – 50 % decrease 0 – 10 % DECREASE n = 3577 hillslope model elements Example: Cienega Ck. CEAP Assessment (198 mi2) % Change in Sediment Yield from Pre-Conservation Condition (‘92) to Post-Cons. (2006) RHEM derived from NRI & PLANTS database by Ecological Site for three time periods: Historic Ref Cond., Pre- & Post Cons. Spending
- 18. Ecological Sites Loamy Upland 12-16” p.z. Allotments Until machine readable ESD and STM are available nationally what can be done to obtain RHEM parameters over large areas? How can NRI and local NRCS observations be utilized ? Could a expansion factor be developed using EcoSites and visual interpretation of aerial/satellite imagery + AGWA cover change tool? Can multi-band remote sensing assist ? ** * NRCS Field Pt. #1 NRCS Field Pt. #2
- 19. From Matt Jones 2018 SRM meeting
- 20. Remotely Sensed (Landsat) Veg. Cover Provides cover estimates throughout the year (~16-day intervals, 30 x 30 m) from 1984 to present For plant phenology in SW can use early summer image for shrub (mesquite canopy cover- CC) using SAVI and fall image for total CC post monsoon with SATVI Can then subtract the two images to estimate non-shrub green and senescent cciTNC = 0.69(ccg) + 9.24 R2 = 0.40* cciARS = 0.37(ccg) + 45.08 R2 = 0.47* 0 10 20 30 40 50 60 70 80 90 100 0 10 20 30 40 50 60 70 80 90 100 Ground-Measured Foliar Canopy Cover (%) Image-BasedFoliarCanopyCover(%) TNC ARS Linear (ARS)* Value is statistically significant (P ≤ 0.05). 1-to-1 (All data) (ARS data only) 1991 2007 2008 2011 CC (%) 1991 2007 2008 2011 CC (%) Shrub Canopy CoverHollifield-Collins
- 21. Foliar Cover to Litter and Basal For some ES, defensible regression between foliar cover and % litter and % basal have been found using NRI data Allows higher temporal frequency of RHEM parameter than NRI collects % change in SY from ’92 to ‘07 % change in SY from ’92 to ‘09 % change in SY from ’92 to ‘11 Negative % change in SY => a decrease -80 - 75 -5 - 0 50 - 250
- 22. Southwest Watershed Research Center Tucson - Tombstone, AZ Conclusions and Next Steps • AGWA is ready to ingest national EcoSite and State & Transition Model data to automatically derive RHEM parameters for modeling multiple hillslopes over large areas when it becomes available • In the meantime - • The AGWA Land Cover Change tool can be used to evaluate the hydrologic/erosion effects of management scenarios over large areas • Remote sensing (RS) can be used to effectively • Track the changes in foliar cover over time • Quantify shrub and non-shrub foliar cover changes from • Mechanical brush removal and fire • Next steps • With more NRI points attempt to build better regressions relating foliar cover to litter and basal cover for more ecosites. • Explore how RS & ES could be used to develop an image of states within a simplified STM model for that ES
- 23. THANK YOU - Questions I’d like to hear your thoughts and suggestions on obtaining RHEM parameters over large areas Dave Goodrich Dave.Goodrich@ars.usda.gov AGWA Training (free) at Univ. of Arizona (Typically Oct. and March) https://www.tucson.ars.ag.gov/kineros/ https://www.tucson.ars.ag.gov/agwa/
- 25. 1991 2007 2009 2011 CC (%) 1991 2007 2009 2011 CC (%) exclosure grazed pasture Exclosure Burn - 2009 Grazed 1991 2007 2009 2011 Prescribed burn in 2009 outlined by blue polygon Drought in summer monsoon in 2009 No grazing in exclosure If letters above bars are different they are statistically different at the (P=0.05) level
- 27. Mechanical grubbing in 2010 in 5 areas 2011 wildfires in green outline covering the corral and NE portion of the mule treatment areas 1991 2007 2009 2011
- 29. Remotely Sensed (Landsat) Veg. Cover Provides cover estimates throughout the year (~16-day intervals, 30 x 30 m) from 1984 to present For plant phenology in SW can use early summer image for shrub (mesquite canopy cover- CC) using SAVI and fall image for total CC post monsoon with SATVI Can then subtract the two images to estimate non-shrub green and senescent cciTNC = 0.69(ccg) + 9.24 R2 = 0.40* cciARS = 0.37(ccg) + 45.08 R2 = 0.47* 0 10 20 30 40 50 60 70 80 90 100 0 10 20 30 40 50 60 70 80 90 100 Ground-Measured Foliar Canopy Cover (%) Image-BasedFoliarCanopyCover(%) TNC ARS Linear (ARS)* Value is statistically significant (P ≤ 0.05). 1-to-1 (All data) (ARS data only) 1991 2007 2008 2011 CC (%) 1991 2007 2008 2011 CC (%) Shrub Canopy Cover
- 30. Stock Tanks • A common rangeland management is the installation of stock ponds to provide water to livestock. Stock ponds can also be viewed as storm water retention structures and sediment basins, common best management practices for flood and water quality mitigation.