AFCEE MAROS 3.0 New Release
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1 Monitoring and Remediation Optimization System Software 3.0 AFCEE MAROS 3.0 New Release Mindy Vanderford, Ph.D. GSI ENVIRONMENTAL INC Houston and Austin, TX (713) Overview: MAROS 3.0 New Release Goals and Objectives Software Structure and New Features Detailed Descriptions Wrap Up Questions? 2 1
2 MAROS the origin How can we get more meaning from the data we collect? 3 MAROS the origin What makes a good data collection network? 4 2
3 MAROS the origin Good Networks Meets goals Not too much, not too little Reveal what has happened Help prepare for what will happen 5 Method: Good Networks What are we looking for? Variability vs. Consistency Increasing / Decreasing vs. Stable Expected vs. Interesting Moving vs. Stationary Where is most of the mass? RATE SCALE VARIABILITY 6 3
4 Goals: MAROS Reduce monitoring effort Demonstrate Plume Stability Reduce Long-Term O&M Costs Reduce Number of Wells Reduce Sampling Frequency Make Recommendations for improving network for long-term O&M 7 MAROS 2.X Concentration Trends Total mass and distribution Spatial uncertainty Sampling frequency 8 4
5 Goals: MAROS Improve analysis of existing data Demonstrate Remedial Performance Best Choice wells and frequency Support Cessation of Active Remedies Support Exit Strategies Make Recommendations for improving network to attain closure 9 Pantex Monitoring Perched Optimization Groundwater Remedial MAROS 2.2 Action MAROS Objectives 3.0 Limited Individual Well Statistics Limited spatial analysis options Limited User choice and interactivity Usability issues Limited data export options Expanded Individual Well Statistics Improved spatial analysis More User choice and comparison options for spatial analysis Improve Usability More export opportunities and options 10 5
6 Overview: MAROS 3.0 New Release Goals and Objectives Software Structure and New Features Detailed Description Conclusions Questions 11 Data Input Individual Well Analysis Plume-Level Analysis Spatial and Temporal Optimization Data Export 12 6
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8 Software: Data Input Site Details- Data checker NEW! MAROS 2.2 Monitoring Objectives- NEW! Primary Source, Tail, Delineation Secondary - Sources, Remedy, Delineation Priority COCs Cleanup Goals Priority by Well NEW!
9 17 Software: Data Input Moment Analysis Options Moved to Site Details Export MAROS 3.0 Archive File Data Consolidation First consolidation for Individual Well Analysis Second consolidation under Plume Analysis 18 9
10 19 Software: Individual Well Analysis Summary Statistics NEW! Detection Frequencies Kaplan-Meier Ave., Median, SD. Outliers by Dixon s Shapiro-Wilk Normality Statistical Trends Mann-Kendall Linear Regression 20 10
11 21 Software: Individual Well Analysis Data Sufficiency NEW Location! Attainment of Cleanup Goals Number of Samples to Attain Goals Well Scoring NEW! Individual Well Summary Well Score prioritization Priority COC Detection frequency Median above MCL MK Trend Recent Sample above MCL COV Distribution 22 11
12 Well Priority Decision Logic High scoremost important 23 Software: Individual Well Analysis Export NEW! Screen by Screen - spreadsheet Reports link on screen Graphs link on screen Access Database default export button Note: Export Results here- Data consolidation can change under spatial analysis section
13 25 Spatial Geometry Engine Voronoi Areas/Delaunay Triangles: Estimate mass & distribution of mass Spatial Uncertainty 13
14 Software: Plume-Level Analysis Moment Analysis Expanded Data Input Choice- NEW!* Wells to include Missing Sample Events Data Consolidation Moments As in MAROS 2.2 * Requires new data consolidation 27 Software: Plume-Level Analysis Percent Mass by Well NEW! Voronoi Area Estimate mass in well area Percent mass and area each well monitors 28 14
15 29 Software: Plume-Level Analysis MAROS Analysis Aggregate Trends Source and Tail Two custom groups NEW! Aggregate MK Trend % Mass for the well group NEW! Monitoring System Category 30 15
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17 Moment Analysis Choose Wells & Data range Calculate Voronoi Area Compare original network to new network Spatial Optimization Calculate SF, RE, COV Good Networks Wells evenly spaced Low uncertainty between wells Each well has purpose Rank Wells Recommend New Locations Recommend Wells to Eliminate Return to Moment Analysis to Test New Network 33 Software: Optimization Optimization Spatial Slope Factor/Delaunay Decision Logic NEW! Frequency Individual Well Network Level NEW! *Note: Data Consolidation from Plume-Level Analysis 34 17
18 Software: Spatial Optimization Spatial Optimization Slope Factor/Delaunay From MAROS 2.2 Decision Logic NEW! Voronoi Areas Slope Factor and Relative Error Concentration 35 Software: Spatial Optimization Spatial Optimization Decision Logic NEW! Interactive Multiple Well Configurations Well Sufficiency Well Redundancy 36 18
19 Software: Spatial Optimization Decision Logic NEW! Uncertainty High SF, RE, COV new well Low SF, RE, COV - redundant Voronoi Area Large new well Small redundant Interior vs. Hull wells Trends
20 Software: Spatial Optimization Spatial Optimization Well Redundancy Lowest 25% Rank User can choose to eliminate Return to Moment Analysis Re-run stats 39 Software: Optimization Optimization Frequency Individual Well Network Level NEW! 40 20
21 Software: Optimization Individual Well Sampling Frequency Summary info NEW! Reporting Frequency Travel Time Current Sampling Frequency Modified CES Method 41 Software: Optimization Network Sampling Frequency NEW! Based on Zeroth Moment Rate of change of mass Coefficient of variation Correlation (R2) Recommendation 42 21
22 43 Software: Export Options MAROS Output Screen by Screen spreadsheet cut and paste as you go Reports Print as you go Output view and print reports Graphs View and Print 44 22
23 Software: Export Options MAROS Output Excel Tables Multiple tables default Single Tables Access Database Multiple Tables default User choses Tables
24 QUESTIONS? 47 Overview: MAROS 3.0 New Release Goals and Objectives Software Structure and New Features Detailed Description Conclusions 48 24
25 Overview: MAROS 3.0 New Release Detailed Description- New Features Individual Well Statistics Plume-Level Analysis Optimization
26 Software: Individual Well Statistics Individual Well Concentrations Summary Statistics Statistical Trends Attainment of Goals Well Score How much? How often? When? Where? Lognormal? Normal? Outliers? Increasing or Decreasing? Variable? Clean? Important? 51 Software: Individual Well Analysis Summary Statistics NEW! Detection Frequencies Kaplan-Meier Ave., Median, SD. Outliers by Dixon s Shapiro-Wilk Normality 52 26
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28 55 Summary Statistics Export Spreadsheet Export Database Export Reports Export Graphs 56 28
29 57 Software: Plume-Level Analysis Plume-Level Analysis Moment Analysis Well % Mass & Area Trend by Area Mass by Area How much mass? Where? How is it changing? Which wells monitor the most mass? Which wells monitor the most area? Increasing or Decreasing? Variable? 58 29
30 Software: Moment Analysis User Choice More User Choice Well Choice Time Frame/Sample Events Missing Sample Results 59 Software: Moment Analysis 60 30
![Software: Plume Mass by Well Voronoi Area Mass = Area * [C] * Thickness * Porosity](/docs-images/76/73037919/images/31-2.jpg "61 Software: Plume Mass by Well Choose Sample Event % Plume Mass % Plume Area 62")
31 Software: Plume Mass by Well Voronoi Area Mass = Area * [C] * Thickness * Porosity 61 Software: Plume Mass by Well Choose Sample Event % Plume Mass % Plume Area 62 31
32 Software: Plume Area Trends Plume Area Trends Source Wells Tail Wells 2 Custom Groups Choose Wells 63 Software: Plume Area Trends 64 32
33 65 Software: Spatial Optimization Spatial Optimization Decision Logic Theory Spatial Optimization is dependent on goals of the program It is hard to automate diverse goals. Give the User useful information to make their own decisions
34 Software: Spatial Optimization Spatial Optimization Slope Factor Delaunay Triangulation Voronoi Areas Relative Error and Variability Trends Concentration Uncertainty between wells? Size of monitoring area? Variability in uncertainty? Increasing or Decreasing? Variable? Magnitude of concentration? 67 Moment Analysis Choose Wells & Data range Calculate Voronoi Area Compare original network to new network Spatial Optimization Calculate SF, RE, COV Good Networks Wells evenly spaced Low uncertainty between wells Each well has purpose Rank Wells Recommend New Locations Recommend Wells to Eliminate Return to Moment Analysis to Test New Network 68 34
35 Software: Spatial Optimization Spatial Optimization Decision Logic NEW! Well Sufficiency Hull vs. Interior Well Downgradient Hull Baseline VA vs. Ave MK Trend COV SF 69 Software: Spatial Optimization Spatial Optimization Uncertainty Slope Factor Uncertainty between points normalized by maximum of estimated or known result Relative Error Uncertainty between points normalized by maximum of known result Coefficient of Variation Variability in uncertainty between points over time 70 35
36 Software: Spatial Optimization Slope Factor and Relative Error N 3 N 2 Delaunay triangle d 02 d 03 d 04 N 0 d 01 N 1 Estimated concentration of node: N 4 Voronoi diagram d 05 N 5 where, M = number of triangles surrounding the node SF 1, well is important; SF 0, well is not important 71 Software: Spatial Optimization Slope Factor and Relative Error N 3 N 2 Delaunay triangle d 02 d 03 d 04 N 0 d 01 N 1 N 4 d 05 Voronoi diagram N 5 Varies over orders of magnitude RE 10000, well is important; RE 0, well is not important COV standard deviation/mean for all sample events 72 36
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38 Save Table for Later Comparison
39 77 Compare network stats before and after optimization 78 39
40 Software: Frequency Optimization Frequency Optimization Reporting frequency Current Frequency Transport-based Frequency Decision logic How often do I sample now? How fast is groundwater moving? How fast are concentrations changing? Variability? Increasing or Decreasing? Variable? 79 Software: Optimization Optimization Frequency Individual Well Network Level NEW! 80 40
41 Software: Optimization Individual Well Sampling Frequency Summary info NEW! Reporting Frequency Travel Time Current Sampling Frequency Modified CES Method 81 Current Sampling Frequency by well [samples/year] ½ * Distance to source /seepage velocity [years] Network Average 82 41
42 Software: Optimization Network Sampling Frequency NEW! Based on Zeroth Moment Rate of change of mass Coefficient of variation Correlation (R2) Recommendation 83 User supplies R 2 and COV cutoff 84 42
43 85 Slope COV R2 Result All < User cutoff < User Cutoff Keep current sample frequency (Average current) < 0 (negative) < User cutoff >= User Cutoff 2 steps less frequent All >=User < User Cutoff 1 step more frequent cutoff < 0 (negative) >=User cutoff >=User cutoff 1 step less frequent Mass = 0 Do not calculate Minimum of the reporting frequency or the transport-based frequency 86 43
44 Software: Export and Output Export and Output 87 Software: Export Options MAROS Output Screen by Screen spreadsheet cut and paste as you go Reports Print as you go Output view and print reports Graphs Databases 88 44
45 Datasheet View by Screen 89 Reports 90 45
46 Graphs 91 Databases 92 46
47 Pantex Monitoring Perched Optimization Groundwater Remedial MAROS 3.0 Action Objectives Expanded Individual Well Statistics Improved spatial analysis More User choice and comparison options for spatial analysis Improve Usability More export opportunities and options Goals and COC Choice NEW! Individual Statistics NEW! Plume mass by well NEW! Aggregate Trends NEW! Spatial Decision Logic NEW! Travel time data NEW! Frequency Network Level NEW! 93 QUESTIONS? 94 47
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