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US Army Corps of Engineers Engineer Research & Development Center ISCMEM Groups 2 and 4 Joint Webinar Presentations Training Range Environmental Evaluation.

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Presentation on theme: "US Army Corps of Engineers Engineer Research & Development Center ISCMEM Groups 2 and 4 Joint Webinar Presentations Training Range Environmental Evaluation."— Presentation transcript:

1 US Army Corps of Engineers Engineer Research & Development Center ISCMEM Groups 2 and 4 Joint Webinar Presentations Training Range Environmental Evaluation and Characterization System (TREECS™) Applications June 19, 2012 June 19, 2012

2 US Army Corps of Engineers Engineer Research & Development Center Outline Overview of TREECS – Billy Johnson TREECS Application to Borschi Watershed Overview of the Chernobyl Accident and Borschi Watershed – Boris Faybishenko Modeling of 90 Sr Transport for the Borschi Watershed – Mark Dortch TREECS Application to Artillery Impact Area (AIA) for RDX – Mark Dortch

3 US Army Corps of Engineers Engineer Research & Development Center Overview - Training Range Environmental Evaluation and Characterization System Billy E. Johnson, ERDC

4 US Army Corps of Engineers Engineer Research & Development Center TREECS Problem Statement Residues and disturbances from range operations can impact the environment, including human and ecological health off-range. Such impacts can impact environmental compliance and range sustainment. Residues and disturbances from range operations can impact the environment, including human and ecological health off-range. Such impacts can impact environmental compliance and range sustainment. Army live fire training and test ranges have unique environments in which low-order and unexploded ordnance (dud munitions) are likely to cause random and highly uncertain sources of munitions constituents (MC) contamination. Army live fire training and test ranges have unique environments in which low-order and unexploded ordnance (dud munitions) are likely to cause random and highly uncertain sources of munitions constituents (MC) contamination. An assessment tool is needed to forecast if, when, and at what level MC concentrations in off-range media (groundwater, surface water, and sediment) may exceed protective health benchmarks. An assessment tool is needed to forecast if, when, and at what level MC concentrations in off-range media (groundwater, surface water, and sediment) may exceed protective health benchmarks.

5 US Army Corps of Engineers Engineer Research & Development Center TREECS Solution / Approach Training Range Environmental Evaluation and Characterization System (TREECS) is a client-based system that provides forecasts of Munitions Constituents (MC) fate on and off range based on munitions use on range. Development Approach: Formulate and couple models of reduced form for MC fate/transport-transformation-sequestration in an integrated framework for fast assessments with a minimal amount of user input. Partners: PNNL, EPA, AEC, AIPH, ITL, and EL

6 US Army Corps of Engineers Engineer Research & Development Center TREECS Components Framework for Tier 1 and 2 assessments Framework for Tier 1 and 2 assessments Constituent databases Constituent databases Health Benchmark database Health Benchmark database Munitions database Munitions database MC residual mass loading module based on munitions use MC residual mass loading module based on munitions use GIS module GIS module Hydro-geo-characteristics toolkit (HGCT) for estimating input parameters Hydro-geo-characteristics toolkit (HGCT) for estimating input parameters Models for soil, surface water, vadose zone, and groundwater Models for soil, surface water, vadose zone, and groundwater Simplified user input interfaces for models (GUIs) Simplified user input interfaces for models (GUIs) Viewers for results Viewers for results Sensitivity and uncertainty module for Tier 2 assessments Sensitivity and uncertainty module for Tier 2 assessments

7 US Army Corps of Engineers Engineer Research & Development Center TREECS GIS Components - For opening individual GIS files - For saving individual GIS files - For resampling a grid - For zooming into an area in the workspace - For zooming out of an area in the workspace - For panning in the workspace - For creating a rectangular AOI shapefile in the workspace - For creating a polygon AOI shapefile in the workspace - For measuring length and area in the workspace - For converting a shapefile to a grid - For extracting a subset of a grid - For creating slope grid from DEM and performing simple arithmetic operations on a grid

8 US Army Corps of Engineers Engineer Research & Development Center TREECS HGCT To aid the user in determining input variables required by TREECS models To aid the user in determining input variables required by TREECS models – Soil Properties – Soil erosion rate – Hydrology (infiltration, runoff, ET, etc.) – Darcy velocity Allows point (single value) and spatially- varying composite estimates Allows point (single value) and spatially- varying composite estimates Spatial option requires use of GIS module in TREECS or externally developed map files (grids) Spatial option requires use of GIS module in TREECS or externally developed map files (grids)

9 US Army Corps of Engineers Engineer Research & Development Center Tiered Approach Tier 1 (screening) Tier 1 (screening) – Steady-state, no degradation, worse case, highly conservative – Requires little data – Can be applied very quickly – Indicates whether a problem could ever potentially exist; if so, proceed to Tier 2 Tier 2 (more comprehensive) Tier 2 (more comprehensive) – Time-varying, much more realistic and accurate – Requires more data – Requires more time to set up and apply, but still can be done relatively quickly – Can be used to determine when benchmark exceedence may occur – Useful for evaluating range management strategies

10 US Army Corps of Engineers Engineer Research & Development Center Tier 1 Conceptual Model

11 US Army Corps of Engineers Engineer Research & Development Center Tier 2 Conceptual Model

12 US Army Corps of Engineers Engineer Research & Development Center Constituent Selection View MC Properties Can use a user defined database (Create under Tools) Select Database Select MC

13 US Army Corps of Engineers Engineer Research & Development Center MC Residue Mass Loading Module (Operational Inputs) Provided by user Pulled from MIDAS Extract DB Constant in Tier 1 Can use a User Defined munitions database

14 US Army Corps of Engineers Engineer Research & Development Center MC Residue Mass Loading L i,k = Loading for constituent I for year k, g/yr DUD j,k = percent of duds for munitions item j for year k HO j,k = percent of high order detonations for munitions item j for year k LO j,k = percent of low order detonations for munitions item j for year k M i,j = mass of constituent i in munitions item j delivered to impact area, g/item N j,k = number of munitions item j fired for year k n= total number of munitions items used at AOI SYM j,k = percent of sympathetic detonation of duds for munitions item j for year k Y HOj,k = percent yield of munitions item j due to high order detonation for year k Y LOj,k = percent yield of munitions item j due to low order detonation for year k Y SYMj,k = percent yield of munitions item j due to sympathetic detonation for year k

15 US Army Corps of Engineers Engineer Research & Development Center MEPAS Vadose & Aquifer Models (Tier 2)

16 US Army Corps of Engineers Engineer Research & Development Center Surface Water Models, RECOVERY and CMS

17 US Army Corps of Engineers Engineer Research & Development Center Advanced Tier 2 Multiple AOIs Complex Pathways Multiple Receptors Future capabilities will include remediation and BMP modules

18 US Army Corps of Engineers Engineer Research & Development Center Benefits of using TREECS Allows the user to project future conditions -Answers the question of whether there will be a problem in the future Can be used to develop and assess mitigation scenarios Can be used to help optimize and prioritize data collection sites for future assessment activities Can be used in designing new training ranges to help minimize migration of MC

19 Europe Radioactive gases, aerosols and finely fragmented fuel were releases to the atmosphere: Fuel particles—finely dispersed, low volatility, settled primarily within the ChEZ Condensed components—from radioactive gases, settled primarily along the atmospheric flow pathways Hot particles—fuel particles, uranium dioxide, with a specific activity >10 5 Bq/g, size 1 to 100 µm, surface density ~ 1,600 per m 2, to ~0.5 m depth Russia Ukraine Belorus Overview of Chernobyl Accident Boris Faybishenko, LBNL Example of the autoradiography film of fuel particles in wetland sediment (Freed et al., 2003)

20 90 Sr in the Dnieper River reservoirs is still above of pre-accident levels. 137 Cs in the water at the lowest reservoir returned to its pre-accidental. There is a wealth of data within the Chernobyl Exclusion Zone and the cascade of 6 water reservoirs along the Dnieper River, which can provide important information for the testing and validation of models, parameter estimation, uncertainty quantification, and understanding conceptual models of flow and transport processes in surface water, vadose zone, and groundwater..

21 Borschi Watershed Monitoring Freed et al., Seasonal Changes of the 90 Sr Flux in the Borschi Stream, Chernobyl, ERSP, km south of ChNNP Area 8.5 km 2 Flows into the Chernobyl Cooling Pond drainage ditch and then into the Pripyat River Sandy soil underlain by clay marl Primarily formerly cultivated land and planted forests with two seasonal wetlands

22 Microbial communities Dissolved radionuclides Radionuclides in suspended sediments Radionuclides in bottom sediments Advection Diffusion/Dispersion Adsorption Desorption Adsorption Desorption Sedimentation Resuspension Uptake Post-Chernobyl Radionuclide Transport Processes in Surface Water Reservoirs Suspended sediments Modified after M.Zheleznyak Hot particles

23 US Army Corps of Engineers Engineer Research & Development Center Application of TREECS™ to Borschi Watershed for 90 Sr and AIA for RDX Mark Dortch, PhD, PE Contractor to the Environmental Lab, ERDC

24 US Army Corps of Engineers Engineer Research & Development Center Model Inputs in General MCs of interest and their properties MCs of interest and their properties Source zone inputs (e.g., range munitions use and associated parameters, or constituent loading rate) Source zone inputs (e.g., range munitions use and associated parameters, or constituent loading rate) Average annual hydrology and soil erosion (from HGCT) Average annual hydrology and soil erosion (from HGCT) Site specific media inputs (soil, vadose, groundwater, surface water, sediment) Site specific media inputs (soil, vadose, groundwater, surface water, sediment)

25 US Army Corps of Engineers Engineer Research & Development Center Tier 2 Application to Borschi Watershed near Chernobyl for 90 Sr

26 US Army Corps of Engineers Engineer Research & Development Center Borschi Watershed 3 km south of CNNP 3 km south of CNNP 8.5 km km 2 Sandy soil underlain by clay marl Sandy soil underlain by clay marl Primarily formerly cultivated land and planted forests with two seasonal wetlands Primarily formerly cultivated land and planted forests with two seasonal wetlands Flows into a cooling pond drainage ditch and then into the Pripyat River Flows into a cooling pond drainage ditch and then into the Pripyat River

27 US Army Corps of Engineers Engineer Research & Development Center Strontium-90 Half life = 29 years Half life = 29 years Specific radioactivity = 143 Ci/g Specific radioactivity = 143 Ci/g Approximate watershed inventory for year 2000 = 1.0 E13 Bq Approximate watershed inventory for year 2000 = 1.0 E13 Bq Watershed stream exit activity conc. (Bq/L) was monitored to estimate watershed export of 1.27 E10 to 1.62 E10 Bq/yr for 1999 – 2001, with average = 1.43 E10 Bq/yr, or annual export of 0.14% of 2000 inventory Watershed stream exit activity conc. (Bq/L) was monitored to estimate watershed export of 1.27 E10 to 1.62 E10 Bq/yr for 1999 – 2001, with average = 1.43 E10 Bq/yr, or annual export of 0.14% of 2000 inventory

28 US Army Corps of Engineers Engineer Research & Development Center Watershed Hydrology (Freed 2002) Average annual precipitation = 0.6 m/yr Average annual precipitation = 0.6 m/yr Rainfall is approximately 0.47 m/yr based on snow melt = 22 % of stream flow Rainfall is approximately 0.47 m/yr based on snow melt = 22 % of stream flow Stream flow = 15 – 20 % of precipitation Stream flow = 15 – 20 % of precipitation Stream flow for 1999 – 2000 = m/yr, or 16 % of average precip Stream flow for 1999 – 2000 = m/yr, or 16 % of average precip 80 % of stream flow is base flow from subsurface, or m/yr; results in runoff = m/yr 80 % of stream flow is base flow from subsurface, or m/yr; results in runoff = m/yr Groundwater recharge had to be estimated from water balance Groundwater recharge had to be estimated from water balance

29 US Army Corps of Engineers Engineer Research & Development Center Conceptual Site Model Surface Soil Vadose Zone Aquifer AOI = Borschi Watershed Watershed Outlet Runoff (Q) & Erosion Base flow = interflow Recharge Infiltration = Recharge + Interflow Sr(90) Model requires infiltration and % of infilt. going to interflow Infiltration = P – ET – Q

30 US Army Corps of Engineers Engineer Research & Development Center Required TREECS™ Models Only the Tier 2 soil model was needed (includes interflow pathway) Only the Tier 2 soil model was needed (includes interflow pathway) Vadose and aquifer models were not used since recharge was assumed to be lost Vadose and aquifer models were not used since recharge was assumed to be lost No surface water model was used since watershed outlet is considered to be part of AOI or location of soil model export flux No surface water model was used since watershed outlet is considered to be part of AOI or location of soil model export flux No AOI loading, only initial inventory in 2000 No AOI loading, only initial inventory in 2000

31 US Army Corps of Engineers Engineer Research & Development Center Soil Model Inputs Area = 8.5 E6 m 2 Area = 8.5 E6 m 2 Active soil layer = 0.2 m Active soil layer = 0.2 m Soil – water temperature = 7.7 deg C Soil – water temperature = 7.7 deg C Mobile Sr(90) Inventory conc. = 6.3 E-7 mg/kg (assumed 20% non-exchangeable adsorbed); did not matter whether in solid or non-solid form Mobile Sr(90) Inventory conc. = 6.3 E-7 mg/kg (assumed 20% non-exchangeable adsorbed); did not matter whether in solid or non-solid form Assumed loamy sand: 12 % water content, 1.49 g/cc bulk density, 44 % porosity Assumed loamy sand: 12 % water content, 1.49 g/cc bulk density, 44 % porosity Erosion rate = 2.5 E-6 m/yr based on USLE (insignificant amount) Erosion rate = 2.5 E-6 m/yr based on USLE (insignificant amount)

32 US Army Corps of Engineers Engineer Research & Development Center Soil Model Inputs, cont. Precip = 0.6 m/yr; rainfall = 0.47 m/yr Precip = 0.6 m/yr; rainfall = 0.47 m/yr Runoff = m/yr Runoff = m/yr Infiltration = m/yr with 80% of infiltration diverted to interflow (uncertain, so varied, i.e., doubled and halved, for sensitivity) Infiltration = m/yr with 80% of infiltration diverted to interflow (uncertain, so varied, i.e., doubled and halved, for sensitivity) K d = 76 L/kg (initial value based on one sediment measurement; treated as uncertain) K d = 76 L/kg (initial value based on one sediment measurement; treated as uncertain) t 1/2 = 29 yr t 1/2 = 29 yr Mw = 90 g/mol Mw = 90 g/mol

33 US Army Corps of Engineers Engineer Research & Development Center Baseline Results Year 2000 Compared to 1.43 E10

34 US Army Corps of Engineers Engineer Research & Development Center Evaluation of Uncertainties K d : conducted Monte Carlo simulation assuming normal distribution and varying between 100 and 300 L/kg with mean of 200 and Std of 33 K d : conducted Monte Carlo simulation assuming normal distribution and varying between 100 and 300 L/kg with mean of 200 and Std of 33 % non-exchangeable adsorbed Sr: did not vary and kept fixed at 20%; recognize that varying this has linear inverse affect on export % non-exchangeable adsorbed Sr: did not vary and kept fixed at 20%; recognize that varying this has linear inverse affect on export Infiltration & % interflow: doubling/halving improved estimate of ET but did not affect export in 2000; does slightly decrease export vs time Infiltration & % interflow: doubling/halving improved estimate of ET but did not affect export in 2000; does slightly decrease export vs time

35 US Army Corps of Engineers Engineer Research & Development Center Uncertainty Analysis for Varying K d Compared to 0.14 % observed

36 US Army Corps of Engineers Engineer Research & Development Center Conclusions Results are insensitive to distribution of inventory between solid- and non-solid-phases due to relatively fast dissolution rate of Sr particles. Results are insensitive to distribution of inventory between solid- and non-solid-phases due to relatively fast dissolution rate of Sr particles. Initial export (year 2000) is insensitive to the amount of infiltration and recharge as long as the same amount of interflow is used (0.078 m/yr) Initial export (year 2000) is insensitive to the amount of infiltration and recharge as long as the same amount of interflow is used (0.078 m/yr) Export of 90 Sr from the Borschi watershed to surface water is predominantly a result of soil pore water containing dissolved Sr being diverted to surface waters that eventually flow out of the watershed Export of 90 Sr from the Borschi watershed to surface water is predominantly a result of soil pore water containing dissolved Sr being diverted to surface waters that eventually flow out of the watershed

37 US Army Corps of Engineers Engineer Research & Development Center Conclusions, continued The percentage of non-exchangeable adsorbed Sr and the soil-water K d are the two most sensitive and uncertain factors affecting the amount of export The percentage of non-exchangeable adsorbed Sr and the soil-water K d are the two most sensitive and uncertain factors affecting the amount of export This application demonstrates how TREECS™ can be applied for a radionuclide. Such an application is accomplished by: This application demonstrates how TREECS™ can be applied for a radionuclide. Such an application is accomplished by: – Converting radioactivity to mass units for model input using the specific radioactivity of the radionuclide – Modeling the constituent mass as normally done – Converting the output mass concentration/flux values to radioactivity using the specific radioactivity of the radionuclide

38 US Army Corps of Engineers Engineer Research & Development Center Conclusions, continued Application of TREECS could be useful for the larger Pripyat and Dnieper River watersheds during the remediation evaluation process and for the feasibility study of the remediation and decommissioning of the Chernobyl cooling pond Application of TREECS could be useful for the larger Pripyat and Dnieper River watersheds during the remediation evaluation process and for the feasibility study of the remediation and decommissioning of the Chernobyl cooling pond

39 US Army Corps of Engineers Engineer Research & Development Center Tier 2 Application to an Artillery Impact Area (AIA) for RDX Beginning of stream model Modeled creek extended 4.4 km to a usage point Lake Terrain drains into small stream that flows into a creek; glacial till over bedrock 3 ranges fire 105, 60, and 81 mm artil./mortars into AOI

40 US Army Corps of Engineers Engineer Research & Development Center Conceptual Site Model Assumption: Runoff from AOI moves quickly and un-attenuated to creek AOI Soil Creek All net infiltration is diverted to soil interflow that exits to surface water X Target receptor Erosion and Runoff 4.4 km

41 US Army Corps of Engineers Engineer Research & Development Center Sources of Model Input Data Google Earth™ for watershed and AOI delineation and areas Google Earth™ for watershed and AOI delineation and areas NRCS Web Soil Survey (WSS) for AOI soil characteristics NRCS Web Soil Survey (WSS) for AOI soil characteristics Daily local air temperature and precip data for period of record from a met station near the site (used by HGCT) Daily local air temperature and precip data for period of record from a met station near the site (used by HGCT) Training ammunition usage reports for 2 years for estimating munitions constituents (MC) loadings Training ammunition usage reports for 2 years for estimating munitions constituents (MC) loadings Application of HGCT within TREECS Application of HGCT within TREECS

42 US Army Corps of Engineers Engineer Research & Development Center Estimating MC Loading Rate DODIC Rounds fired/yr Duds, % Low order, % Low order yield, % High order yield, % C445 (105 mm) C868 (81 mm) B642 (60 mm) Inputs Computed loading rate of RDX = 50 kg/yr (mostly from 105 mm low orders). Assumed a constant loading for 70 years

43 US Army Corps of Engineers Engineer Research & Development Center Key Inputs for Soil Model Soil characteristics (sandy loam, glacial till on top of bedrock) Soil characteristics (sandy loam, glacial till on top of bedrock) – Bulk density = 1.48 – Avg. vol. moisture content = 17% – Porosity = 44% Average annual hydrology/erosion from HGCT Average annual hydrology/erosion from HGCT – Precip/rainfall =1.1 and 1.0 m/yr – Infiltration = 0.25 m/yr – Runoff =.52 m/yr – 141 rainfall events/yr – ULSE estimated erosion = m/yr

44 US Army Corps of Engineers Engineer Research & Development Center Key Inputs for Soil Model (cont.) RDX F/T parameters RDX F/T parameters – Soil K d = 0.42 L/kg (from GUI utility) – Particle average initial diameter = 12 mm – No degradation RDX chemical-specific properties RDX chemical-specific properties – Solubility at 10.9 deg C = 29.3 mg/L – Henry’s law const. = 6.23E-8 atm m 3 /mol – Molecular Wt. = – Solid phase density = 1.8 g/cm 3

45 US Army Corps of Engineers Engineer Research & Development Center Key Inputs for Stream Model (used CMS) Model parameters Model parameters – 40 computational segments for 4.4 km – Flow Dispersion = 1 m 2 /sec – TSS = 3 mg/L – Sediment foc = 0.02 – Active sediment layer porosity = 0.7 Hydraulics Hydraulics – Estimated width = 10 m and depth = 0.3 m – Average flow = 0.27 m 3 /sec based on runoff depth and watershed area; resulting travel time of ½ day

46 US Army Corps of Engineers Engineer Research & Development Center Key Inputs for Stream Model RDX chemical-specific properties RDX chemical-specific properties – Same as for soil for MW, He – Molecular diffusivity = 5.9E-6 cm 2 /sec – K ow = 7.41 ml/ml (used to estimate K d ) Sedimentation Sedimentation – Assumed equilibrium or zero burial; assumed settling rate = 2 m/day resulting in computed resuspension = 2.5E-5 m/day

47 US Army Corps of Engineers Engineer Research & Development Center Ran both soil and stream model for 200 years with RDX loading extending over first 70 years, from approx to 2010

48 US Army Corps of Engineers Engineer Research & Development Center Computed RDX Water Total Concentration at Creek Usage Point

49 US Army Corps of Engineers Engineer Research & Development Center Comparison with Data Measured in Creek in 2003 Sediment: measured < RL (RL = 0.05 mg/kg) compared to model value of mg/kg or also < RL Sediment: measured < RL (RL = 0.05 mg/kg) compared to model value of mg/kg or also < RL Water: measured = 1.1 ppb compared to model value of 2.5 ppb Water: measured = 1.1 ppb compared to model value of 2.5 ppb Encouraging considering: assumed constant firing rate and assumed low order rate for 70 yrs, no loss between AOI-creek, no loss to GW, no degradation loss, constant and estimated creek flow rate

50 US Army Corps of Engineers Engineer Research & Development Center Other Validation Applications Installation No. AOIMCTarget Receiving Water 1Demo areaRDXGroundwater 2HE impact area SAFRs RDX, TNT, KClO 4 Pb, Cu Groundwater, lake 3HE impact area SAFRs RDX Pb Pond 4SAFRsPb, Cu, Zn, SbPond All model-computed results were within a factor of 10 of those observed. Agreement for HE was much better than for metals.

51 US Army Corps of Engineers Engineer Research & Development Center Conclusions/Recommendations With these models of reduced form, applications require a couple of days to discover info & set-up and less than one minute to simulate centuries With these models of reduced form, applications require a couple of days to discover info & set-up and less than one minute to simulate centuries Validation application results indicate TREECS™ can provide insightful predictions regarding MC fate down-gradient of ranges with predictions within an order of magnitude (or closer) of observed data Validation application results indicate TREECS™ can provide insightful predictions regarding MC fate down-gradient of ranges with predictions within an order of magnitude (or closer) of observed data The Monte Carlo uncertainty analysis feature in TREECS™ can be used to provide confidence bounds in predictions due to imprecise input estimates The Monte Carlo uncertainty analysis feature in TREECS™ can be used to provide confidence bounds in predictions due to imprecise input estimates


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