SLIDE 1
REAL-TIME STORMWATER SYSTEMS Branko Kerkez Brandon Wong - - PowerPoint PPT Presentation
REAL-TIME STORMWATER SYSTEMS Branko Kerkez Brandon Wong - - PowerPoint PPT Presentation
REAL-TIME STORMWATER SYSTEMS Branko Kerkez Brandon Wong bkerkez@umich.edu bpwong@umich.edu Iot Information age 10 sq mi 9 Pond 10 sq mi 10 Pond 10 sq mi Bioswale 11 Pond 10 sq mi Bioswale 12 1 Pond 2 10 sq mi Bioswale 13
SLIDE 2
SLIDE 3
Iot Information age
SLIDE 4
SLIDE 5
SLIDE 6
SLIDE 7
SLIDE 8
SLIDE 9
10 sq mi
9
SLIDE 10
10 sq mi
Pond 10
SLIDE 11
10 sq mi
Pond Bioswale 11
SLIDE 12
10 sq mi
Pond 12 Bioswale
SLIDE 13
10 sq mi
Pond 13
1 2
Bioswale
SLIDE 14
Time Water level, erosion, etc. Pre-construction Post-construction 1 2 D
SLIDE 15
Site 1 Time Water level, erosion, etc. Pre-construction Post-construction 1 2 D
SLIDE 16
Site 1 Site 2 Time Water level, erosion, etc. Pre-construction Post-construction 1 2 D
SLIDE 17
Site 1 Site 2 Downstream Time Water level, erosion, etc. Pre-construction Post-construction 1 2 D
SLIDE 18
Site 1 Site 2 Downstream Time Water level, erosion, etc. Pre-construction Post-construction Better 1 2 D
SLIDE 19
Site 1 Site 2 Downstream Time Water level, erosion, etc. Pre-construction Post-construction Better Better 1 2 D
SLIDE 20
+ =
Site 1 Site 2 Downstream Time Water level, erosion, etc. Pre-construction Post-construction Better Better Worse? 1 2 D
SLIDE 21
!
Rain, soil moisture and water quality sensors measure real-time conditions of green and gray infrastructure Smart covers measure underground flows and water quality Smart ponds adapt to changing weather by managing storage and detention time Multiple smart valves coordinate flows to achieve system-level benefits
SLIDE 22
SLIDE 23
23
OPEN-STORM.ORG
SLIDE 24
24
SLIDE 25
Downstream point Time
Neighborhood 1 Neighborhood 2
Water level
Flooding/Erosion
SLIDE 26
Downstream point Time With Control Controller
Neighborhood 1 Neighborhood 2
Water level
Without Control Flooding/Erosion
SLIDE 27
27
SLIDE 28
Ellsworth
SLIDE 29
29
SLIDE 30
30
SLIDE 31
31
SLIDE 32
32
SLIDE 33
33
SLIDE 34
Wetland Basin
SLIDE 35
Wetland Basin
SLIDE 36
After
- 22.5 million Gallons
- $16/gal
- 800 lb/yr Total P
- Before
- 15 Million Gallons Storage
- $22/gal
- 600 lb/yr Total P
50% Increase in Capacity
SLIDE 37
does it scale?
SLIDE 38
Open-Storm Detroit Dynamics
Wendy Barrott Christopher Nastally Branko Kerkez Sara Troutman Abhiram Mullapudi Gregory Ewing
Utility-University Team
SLIDE 39
SLIDE 40
100+ Sensors 20+ Control Points
The Opportunity
SLIDE 41
The Plan
SLIDE 42
$131K
The Plan
SLIDE 43
$131K
The Plan
SLIDE 44
Nov 2017 – Nov 2018
Outcomes & Considerations 1. No New Construction 2. Maximize Storage 3. Reduce CSOs 4. Equalize Flows
$131K
The Plan
SLIDE 45
Existing SCADA Workflow
Sensors
SLIDE 46
Existing SCADA Workflow
Utility Server Sensors
SLIDE 47
Existing SCADA Workflow
Utility Server Raw Data Feeds Sensors
SLIDE 48
Existing SCADA Workflow
Utility Server Raw Data Feeds Pumps Valves Sensors
SLIDE 49
Existing SCADA Workflow
Utility Server Raw Data Feeds Pumps Valves Sensors
SLIDE 50
Analytics and Control
Utility Server Pumps Valves Sensors Visualization
Description of Smart Water System
SLIDE 51
Utility Server Visualization Pumps Valves Sensors
Quality Control
Description of Smart Water System
SLIDE 52
Utility Server Sensors
Quality Control Control Engine
Visualization Pumps Valves
Description of Smart Water System
SLIDE 53
Utility Server Sensors
Quality Control Control Engine Decision Dashboard
Visualization Pumps Valves
Description of Smart Water System
SLIDE 54
Utility Server Sensors
Quality Control Control Engine Decision Dashboard
Visualization Pumps Valves
Description of Smart Water System
SLIDE 55
SLIDE 56
Water Level (mm) Water Level (mm) Time
Real-time QA/QC
RAW WATER LEVEL DATA
SLIDE 57
RADAR PySWMM Hydraulic Model
Real-Time Forecasting
SLIDE 58
SLIDE 59
Existing Challenge
SLIDE 60
Existing Challenge
SLIDE 61
Existing Challenge
SLIDE 62
Existing Challenge
SLIDE 63
Implementation
!" = $" ⋅ &
'(,"
* = &
+,-. − 01234562 ⋅ 7
3 = 1 6 + 1 :
"
!" + * ;<,=>," = ;=?=">=@>A ⋅ !" − 3
SLIDE 64
Implementation
SLIDE 65
Implementation
SLIDE 66
Implementation
SLIDE 67
Implementation
SLIDE 68
SLIDE 69
SLIDE 70
Analysis and Implementation
Inflow to Treatment Facility (without forecasting)
Flow [cfs]
With Control (CSO 735 MG) Baseline (CSO 842 MG)
SLIDE 71
Flow [cfs]
With Control (CSO 30 MG) Baseline (CSO 130 MG)
Inflow to Treatment Facility (with forecasting)
Analysis and Implementation
SLIDE 72
VS
100 MG CSO Reduction Per Event Smart System 100 MG Storage for $500 Million Capital Improvements
Value Added
SLIDE 73
SLIDE 74
does it scale…more?
SLIDE 75
Multiuse flow management using real-time data
Is it possible to manage flow to stay within the natural range of variation that climate change threatens?
Dam management can reduce harm caused by extreme floods and droughts
SLIDE 76
Huron River Dams
SLIDE 77
USGS network
SLIDE 78
Summer 2018
SLIDE 79
79
Real-time dialog
SLIDE 80
Management Implications
Baseflow target at Kensington Baseflow is 58 cfs (50% August average daily exceedance flow) Target: Year round, keep flow above 46 cfs (20% less than baseflow)
58 cfs
SLIDE 81
Management Implications
Prevent any change in flow that exceeds 150% within a 12-hour period between April 15th and June 30th each year. Ideal target is <100% change in flow within a 12-hour period. Target would be to stay above 50 cfs, ideally 100 cfs.
>150% change in 11 hours
SLIDE 82
Clinton River
SLIDE 83
Clinton River
SLIDE 84
Clinton River
SLIDE 85
Fall 2018 Current Sensors
SLIDE 86
SLIDE 87
OPEN-STORM.ORG
SLIDE 88
demo
SLIDE 89
SLIDE 90
SLIDE 91
10 sq mi
91
SLIDE 92
Low cost sensor
92
SLIDE 93
Cloud-based logic
93
Low cost sensor
SLIDE 94
SLIDE 95
SLIDE 96
SLIDE 97
97
SLIDE 98
98
SLIDE 99
99
SLIDE 100
100
SLIDE 101
101
SLIDE 102
102
SLIDE 103
103
O Outlet 1 10 sq. mi.
SLIDE 104
104
O Outlet 1
SLIDE 105
105
O Outlet 1
SLIDE 106
106
O Outlet 1
SLIDE 107
O Outlet 1
SLIDE 108
Green infrastructure
Soil Moisture Depth Rain
SLIDE 109
109
Online materials
SLIDE 110
110
Washtenaw County WRC
SLIDE 111
111
Real-time results
SLIDE 112
112
Workshops and partnerships
Sierra Club “Rain gardens to the Rescue” CUAHSI 2017
SLIDE 113
Who’s heard about Mallets Creek?
SLIDE 114
114
SLIDE 115
SLIDE 116
How does the data help management? Example:
Flow management to support native fisheries of the Huron River
Rationale and Recommendations for Multiuse Management of Mainstem Dams
- 1. Prevent any change in flow that exceeds 150% within a 12-hour period between April 15th and June 30th each year.
Ideal target is <100% change in flow within a 12-hour period.
- 2. Ensure flows remain above 80% of baseflow (defined as 50% of August average daily exceedance flow from the last
10 years) at all times during the frost free season.
- 3. Release incoming water gradually in a way that approximates a more natural rise and fall of flow.
- 4. For impoundments with summer/winter lake levels, stretch the raising and lowering of lake levels out over a longer
period of time and adjust based on the availability of water such that spikes in flow are minimized and flow below the dam does not drop below the 70% exceedance flow (based on April 15-June 30 flows for the last 10 years).
SLIDE 117
Beyond Data: Enabling Conditions & Challenges
Helps:
- Huron River Dams Network
- Trusted Advisor in HRWC
- UM Partnership
Hinders:
- Lake Level Control Act
- Dam infrastructure
- Competing uses
SLIDE 118
SLIDE 119