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J.Q. Wu, S. Dun, W.J. Elliot, H. Rhee J.R. Frankenberger, D.C. Flanagan P.W. Conrad, R.L. McNearny.

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Presentation on theme: "J.Q. Wu, S. Dun, W.J. Elliot, H. Rhee J.R. Frankenberger, D.C. Flanagan P.W. Conrad, R.L. McNearny."— Presentation transcript:

1 J.Q. Wu, S. Dun, W.J. Elliot, H. Rhee J.R. Frankenberger, D.C. Flanagan P.W. Conrad, R.L. McNearny

2 Introduction A crucial component of planning surface mining operations as regulated by the National Pollutant Discharge Elimination System (NPDES) is to estimate potential environmental impacts during and after mining operations Reliable watershed hydrology and erosion models are effective and efficient tools for evaluating postmining site-specific sediment control and reclamation plans for the NPDES

3 Objectives The objectives of this workshop are  To introduce the newly developed WEPP-Mine, an online GIS interface for the USDA’s WEPP model, as a management tool for western alkaline surface mines  To apply WEPP-Mine, in a case application, to evaluate pre- and postmining watershed hydrological and erosion processes and impacts of BMPs at the Big Sky Mine, eastern Montana, USA  To obtain feedback from and exchange with stakeholders (state regulatory personnel, researchers, private consultants) and other workshop attendees to further refine WEPP-Mine

4 WEPP WEPP (Water Erosion Prediction Project) was initiated in 1985 as a new ‐ generation water erosion prediction technology for use by federal action agencies involved in soil and water conservation and environmental planning and assessment WEPP was developed by the USDA ‐ ARS with user requirements collected from the Bureau of Land Management (BLM), Forest Service (FS), and Soil Conservation Service (SCS) The WEPP model is a result of a large team efforts involving many scientists and experts

5 WEPP cont’d WEPP was intended to replace empirically- based erosion prediction technologies (e.g., USLE) for assessing the soil erosion impact of diverse land uses ranging from cotton fields to mountain forests It simulates many of the physical processes important in water erosion, including infiltration, runoff, ET, percolation, subsurface lateral flow, raindrop and flow detachment, sediment transport, deposition, plant growth, residue decomposition, and changes in soil properties

6 WEPP cont’d The WEPP model can be used for common hillslope applications or on watersheds In addition to WEPP core codes, the current version includes a parameter database and various interfaces, including a GIS and web ‐ based interfaces WEPP technologies have been successfully used in the evaluation of important natural resources issues throughout the US and in many other countries

7 WEPP Watershed WEPP discretizes a watershed into hillslopes, channel segments, and impoundments An impoundment can be on the channel network or at the foot of a hillslope

8 WEPP Inputs Climate  Observed daily values of precipitation (amount, duration, relative time to peak, relative peak intensity), temperatures (max, min), solar radiation, and wind (direction, speed)  Generated with CLIGEN, an auxiliary stochastic climate generator Topography Slope orientation, slope length, and slope steepness at points along the slope profile

9 WEPP Inputs cont’d Soil  Surface soil hydraulic properties, erosion parameters, and texture data for the soil profile  Soil properties of multiple layers to a maximum depth of 1.8 m can be input Land management  Information and parameters for plant growth, tillage, plant and residue management, initial conditions, contouring, subsurface drainage, and crop rotation

10 WEPP Outputs Event-by-event summary of runoff and soil erosion Graphical output for soil detachment and sedimentation along a slope profile Daily water balance Plant growth and residue decomposition Snow accumulation and snowmelt and soil frost and thaw Dynamic change of soil properties Sediment yield Return-period analysis

11 WEPP Impoundments WEPP simulates foothill small ponds behind  Filter fence  Straw bales WEPP also simulates sediment ponds with hydraulic structures  Drop spillway  Perforated riser  Culvert  Emergency spillway  Rock-fill check dam

12 Drop Spillway

13 Perforated Riser

14 Culvert

15 Emergency Spillway

16 Rock-fill Check Dam

17 Filter Fence

18 WEPP Application to Mining Areas To simulate the effect of mining operations on soil erosion and to evaluate sediment control BMPs, typical WEPP applications to mining areas may involve the assessment of  Premining condition as a baseline against which other scenarios can be compared  Postmining with revegetation  Postmining with revegetation and a sediment pond  Postmining with revegetation and a silt fence

19 WEPP-Mine WEPP-Mine was developed based on the USDA’s online GIS interface for the WEPP model It provides functions specifically for applications to mining areas  Using user-specified DEMs  Using reclamation maps  Simulating watershed-specific sediment ponds It can be accessed using a web browser at http://wepponlinegis.bsyse.wsu.edu/osm http://wepponlinegis.bsyse.wsu.edu/osm

20 WEPP-Mine Inputs USGS 30-m DEM USGS 2006 National Land Cover NRCS SSURGO soil data Spatial data automatically retrieved from the online servers by default Soil and landuse can also be customized within the WEPP-Mine interface Special permission is required for uploading user- specified DEMs and reclamation maps

21 WEPP-Mine Inputs cont’d CLIGEN-generated climate based on long-term monthly statistics is currently used (the use of observed climatic data will be implemented) The CLIGEN database includes more than 2,600 weather stations across the US Weather statistics of the station closest to the watershed outlet is used by default PRISM 800-m gridded monthly averages is applied to the monthly statistics to account for location and elevation differences from the CLIGEN station

22 WEPP-Mine Outputs Channel network Subcatchments Watershed summary Average annual values of the simulation results Return-period and frequency analysis Flowpath soil loss map Representative hillslope runoff map Representative hillslope soil detachment map Representative hillslope soil loss map

23 WEPP-Mine Output cont’d

24 General Steps for WEPP-Mine Applications Select area of interest Generate channel network Select watershed outlet and discretize watershed and subwatersheds View watershed summary Customize watershed inputs Run WEPP Analyze WEPP simulation results

25 Computer Requirement A computer connected to internet A web browser Following instructions on the web page (select and click buttons)

26 Premining Simulation WEPP simulation for the premining conditions can be accomplished by following the general steps for WEPP-Mine application without customizing watershed inputs

27 Premining Simulation cont’d

28 Postmining Simulation User-specified DEM is used for topographical inputs for postmining conditions A reclamation map can be uploaded for postmining soils and land managements Soils at the disturbed mining areas are composed of mine spoils and a 0.6-m top soil layer if top soil is applied during reclamation Postmining top soil is a mixture of the onsite soil described in the SSURGO database Surface soil hydraulic and erosion parameters were adjusted according to reclamation stages

29 Postmining Soil and Landuse Map unitDescriptionLand ManagementsSurface Soils 0Undisturbed or No DataShrubSM Shrub 1Disturbed—FacilitiesPoor grassPaved or Bare Rock 2Not ReclaimedBareMine Spoil 3Pre-ReclamationBareRegraded Mine Spoil 4Natural RevegetationPoor grassSM Top Soil 5Seed Phase IGood grassSM Sod Grass 6Seed Phase IIGood grassSM Bunch Grass 7Trail-completeLow traffic roadSM Skid

30 User-Specified Maps The required format includes  Raster map in ASCII  30-m resolution  UTM projection  0 for “no data” The corresponding projection file for the map needs to be loaded The IP address of a user is verified for uploading files to the WEPP-Mine server

31 User-Specified DEM

32 Reclamation Map

33 Sediment Pond After a watershed is discretized, one can specify sediment ponds Impoundment inputs include dimensions of the pond and related hydraulic structure parameters Default pond dimensions (stage-area-length relationship) are determined based on horizontal areas encircled by two half ellipses separated by the widest line of the area Inputs for chosen hydraulic structures of a pond are shown after clicking the “Set Structure Parameters” button User inputs override the default values

34 Sediment Pond cont’d

35

36 Case Application

37 Study Site WEPP-Mine was applied to Watershed III in Area A, Big Sky Mine, a major surface coal mine in southeast Montana

38 Big Sky Mine Area A Mining completed in 1989 Major reclamation activities (regrading, topsoil replacement, and revegetation) completed in 1992 Since 1984, many watersheds in the Big Sky Mine have been monitored for channel flow and water quality

39 Field Observations

40 WEPP Simulations Four WEPP runs were made to examine model performance in simulating the effect of three sediment control BMPs  Premining (natural) condition  Postmining with revegetation  Postmining with revegetation and a sediment pond  Postmining with revegetation and a silt fence

41 Inputs for Premining Oldest DEM available for the study area NRCS SSURGO soil data USGS National Land Cover dataset for landuse and management Soil and management data acquired using the online WEPP GIS interface

42 Postmining with Revegetation Topographic map taken from the “Big Sky Mine 2008 Annual Report” Soil and management data for the disturbed areas from the reclamation and bond status report Soil and management data prepared based on field observations

43 Watershed Delineation: Premining and Postmining Topographic, soil, landuse, and management conditions vary from the mining to postmining period and differ from the natural, premining conditions

44 Sediment Pond A sediment pond set near the outlet of the watershed  Volume 60,000 m 3  One culvert 2.4 m above bottom  Culvert i.d. 18 cm

45 Silt Fence A silt fence set on the toe of a hillslope near the watershed outlet  Fence height 1m Curtsey: USDA Forest Service Rocky Mountain Research Station Forestry Sciences Laboratory, Moscow, ID

46 Return-period Analysis 25-yr WEPP simulations were carried out using observed precipitation and temperature for 1984–2009 from Colstrip climate station (5 mi northwest of the site) and other required climate data generated using CLIGEN Return-period analyses were performed on field observations and WEPP simulations Runoff and sediment yields of WEPP-simulated events with a return period of 2, 5, 10, or 20 yr were compared with field observations

47 Return-period Analysis Return periods were estimated using Chow’s frequency factor method and Gumbel’s distribution with an annual maxima series following Patra (2000) T: the specified return period X T : the estimated value for a return period T X m and s x : the mean and standard deviation of the annual maxima of the events

48 Results

49 Results cont’d Runoff, mmSediment Yield, kg/ha Return Period (yr) 251020251020 Observed 0.72.33.34.30.82.02.73.5 Simulated Premining 2.76.89.512.11200300041005200 Postmining & Revegetation 6.815.921.927.77600203002870036700 Postmining & Sediment pond 6.115.021.026.73300108001570020400 Postmining & Silt fence 6.815.921.927.76700178002520032200

50 Results cont’d WEPP overestimated observed runoff and sediment yield However, WEPP simulation results showed the effectiveness of the sediment control practices A silt fence near the watershed outlet would help to reduce sediment yield slightly from the postmining revegetation condition WEPP simulations indicated a sediment pond to be more effective, with a reduction of sediment yield of 50%

51 Summary WEPP-Mine was developed as a management tool for evaluating potential environmental impacts during and after mining operations WEPP-Mine was applied to a watershed in Area A, Big Sky Mine, southeastern Montana, to assess watershed hydrology and erosion as impacted by surface coal mining activities and postmining reclamation and sediment control practices Three commonly used BMPs: revegetation, sediment basin, and silt fence were evaluated as postmining reclamation management plans Additionally, a baseline scenario, the premining condition, was simulated

52 Summary cont’d The WEPP simulations demonstrated the effectiveness of the sediment control practices Future efforts are needed to  Further evaluate the WEPP-Mine performance through systematic and statistical comparison of model results and long-term field observations for different mines under different geographic conditions in the western US  Continually refine and develop functions (filter fence, buffer zone) specific for mining applications  Develop a comprehensive database of soil and management for alkaline mines in the western US for using WEPP-Mine

53 Acknowledgment Funding support from OSM; in-kind support from WSU, US Forest Service, and USDA NSERL Technical exchanges with and support from P. Clark and D. Matt Funding and technical support and data and information from MT DEQ, T. Golnar, J. Calabrese, Dr. E. Hinz. Funding and technical support and assistance in field work from Rosebud Mine engineers and staff

54

55 Resources and References http://www.ars.usda.gov/Research/docs.htm?docid=10621 (This USDA NSERL site contains extensive documentation and references on the WEPP model, including the free model downloads) http://www.ars.usda.gov/Research/docs.htm?docid=10621 Key references on the overview of the WEPP model  Flanagan, D.C., Livingston, S.J. (Eds.), 1995. USDA-Water Erosion Prediction Project User Summary. NSERL Rep. No. 11, Natl. Soil Erosion Res. Lab., USDA ARS, West Lafayette, IN, 139 pp.  Flanagan, D.C., Nearing, M.A. (Eds.), 1995. USDA-Water Erosion Prediction Project: Hillslope Profile and Watershed Model Documentation. NSERL Rep. No. 10, Natl., oil Erosion Res. Lab., USDA ARS, West Lafayette, IN, 298 pp.  Flanagan, D.C., Ascough II., J.C., Nicks, A.D., Nearing, M.A., Laflen, J.M., 1995. Overview of the WEPP erosion prediction model. In: Flanagan, D.C., Nearing, M.A. (Eds.), USDA-Water Erosion Prediction Project Hillslope Profile and Watershed Model Documentation. NSERL Rep. 10, Natl. Soil Erosion Res. Lab., USDA ARS, West Lafayette, IN (Chapter1).  Laflen, J.M., Lane, L.J., Foster, G.R., 1991. WEPP—a next generation of erosion prediction technology. J. Soil Water Conserv. 46, 34–38.  Laflen, J.M., Elliot, W.J., Flanagan, D.C., Mayer, C.R., Nearing, M.A., 1997. WEPP-predicting water erosion using a process-based model. J. Soil Water Conserv. 52, 96–102.  Laflen, J.M., Flanagan, D.C., Engel, B.A., 2004. Soil erosion and sediment yield prediction accuracy using WEPP. Am. Water Res. Assoc. 40, 289–297. Selected papers on modifying and applying the WEPP model by Dr. J. Wu’s group Pieri, L., M. Bittelli, J.Q. Wu, S. Dun, D.C. Flanagan, P. Rossi Pisa, F. Ventura, and F. Salvatorelli, 2007. Using the Water Erosion Prediction Project (WEPP) model to simulate field-observed runoff and erosion in the Apennines Mountain Range, Italy, J. Hydrol. 336, 84–97. Zhang, J.X., K-T Chang, and J.Q. Wu, 2008. Effects of DEM resolution and source on soil erosion modelling: a case study using the WEPP model, Int. J. Geogr. Info. Sci. 22, 925–942. Dun, S., J.Q. Wu, W.J. Elliot, P.R. Robichaud, D.C. Flanagan, J.R. Frankenberger, R.E. Brown, and A.C. Xu, 2009. Adapting the Water Erosion Prediction Project (WEPP) model for forest applications, J. Hydrol. 466, 46–54. Dun, S., J.Q. Wu, D.K. McCool, J.R. Frankenberger, and D.C. Flanagan, 2010. Improving frost simulation subroutines of the Water Erosion Prediction Project (WEPP) Model, Trans. ASABE. 53, 1399–1411.


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