hydrologic impact assessment of land cover change...
TRANSCRIPT
The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249 1
Hydrologic Impact Assessment of Land Cover Change and
Stormwater Management using the Hydrologic Footprint Residence
Dr. Marcio Giacomoni Assistant Professor
Department of Civil and Environmental Engineering
Flow
2014 Low Impact Development (LID) in Houston Workshop Rice University – April 3rd 2014
The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249 2
Hydrologic Impacts of Urbanization • Land cover change and urbanization alters
natural hydrologic flow regime
0
20
40
60
80
100
120
0 20 40 60 80 100 120 140
Flow
Time
Pre-DevelopmentPost-Development
∆t
∆Q
The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249 3
• The effects are more frequent and severe floods which cause: – Erosion – Property losses due to flooding – Loss of habitat/Ecological degradation
• Downstream communities are directly dependent on the: – duration – frequency – magnitude of high and low flows
Effects of Hydrologic Alteration
The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249 4
LIDs and BMPs • Low Impact Development (LID) and Best
Management Practice (BMP) are strategies to mitigate the impacts of urbanization
• BMPs are typically defined as storage facilities: – Detention ponds
• LIDs are structures designed to enhanced infiltration and control runoff generation at the source: – Pervious Pavements – Biogardens/Swales – Infiltration trenches – …
www.metaefficient.com, http://www.wild-wonderings.blogspot.com/ http://www.physics.tamu.edu/NewPB.html, TAMU Campus Masterplan, p 140
The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249 5
Evaluating BMPs and LID • Peak Flow is commonly used to assess impact
of development • Criteria: Pre-development peak flow should not
be exceeded • Qpeak is it sufficient?
Qpeak?
The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249 6
∆t 0
20
40
60
80
100
120
0 50 100 150 200
Q
Time
Pre-DevelopmentPost-DevelopmentReservoir
∆Q
Hydrological Alteration
The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249 7
Hydrologic Footprint Residence • Develop a new metric to quantify the effects
of development in downstream communities that take into account more than just peak flow
• How to represent the increase in runoff and temporal alteration?
Giacomoni, M., Zechman, E., and Brumbelow, K. (2012). ”Hydrologic Footprint Residence: Environmentally Friendly Criteria for Best Management Practices.” J. Hydrol. Eng., 17(1), 99–108.
The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249 8
Hydrologic Footprint Residence • The HFR of a specific storm event and segment
of stream reach is defined as the area of land that is inundated and the duration over which the flood wave passes through the reach.
Time (hr)
Flow
(ft³/
s) Inundated Response Curve
Time (hr)
Inun
date
d Ar
ea (a
cres
) Time (hr)
Wat
er D
epth
(ft)
0
0
2
2
2
4
4
4
3
3
3 𝐻𝐻𝐻 = � 𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼 𝐴𝐴𝐼𝐼 𝐼 . 𝐼𝐼
𝑇
𝑡=0
t =0
1
1
1
t =1 t =2
t =3
L
The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249 9
Hydrologic Footprint Residence • Evaluate the change of inundated floodplain
areas and the duration of a flood’s residence • Units: Area and Time [acre-hours]
The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249 10
Case Study: Village Creek Watershed • Drainage area: 370 km² • High rates of urbanization
0
10000
20000
30000
40000
50000
60000
70000
Area
(acr
es)
Crops/Grassland/Pasture
Forest/Wetland
High DensityUrban/Transportation
Low Density Urban
Water
1973 1979 1986
1992 2001 2009
The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249 11
Modeling Framework CA Land Cover Change
Model
Hydrologic Model
Hydraulic Model
Initial Land Cover
Rainfall (Design Storm)
Projected Land Cover
Runoff Hydrographs
Stream Geomorphology (Cross-Sections)
Water Surface Elevation
HFR
Giacomoni, M.H., G. Ryan, E.M. Zechman “Hydrologic Impact Assessment of Land Use Change Using the Hydrologic Footprint Residence”. J American Water Resources Association (Accepted).
The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249 12
( ) ( ) ( )1( , ) ( , ) ( , ) ( , ) ( , )1 1 1t t tx y x y x y x y x yL N DMR DmR DCa Rdα β γ µ ε+ = × + × − + × − + × − + ×
• Simulates the sprawl of urban areas • Likelihood of a cell to change its state to urban is a
function of: Number of
Developed Neighbors
Normalized Distance to
Major Roads
Normalized Distance to Minor
Roads
Random Variable
Normalized Distance to Central
Areas
Existing Development New Development
Time t Time t+1
( )1( , )If 1 Change State to Urbantx yL tθ+ ≥ + →
Cellular Automata Land Cover Change Model
The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249 13
Land Cover Change: 1973 - 2050
0%10%20%30%40%50%60%70%80%90%
100%
1970 1980 1990 2000 2010
Urb
an L
and
Cov
er
Predicted Observed
The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249 14
Modeling/HFR Calculation • Hydrologic Model:
– SWAT – 95 subcatchments – Hourly time step
• Hydraulic Model: – HEC-RAS – 22.14 Km – 124 cross sections
Legend Village Creek Watershed
The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249 15
Legend Water Bodies Urban Residential Commercial/Transportation Forest Agriculture
Management Scenarios • Existing Development • Future Development • Future Development/BMP • Future Development/LID
2010
Legend Village Creek Watershed
2035 Legend
Water Bodies Urban Residential Commercial/Transporation New Urban Development Forest Agriculture
The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249 16
Hydrographs and Inundated Land Curves (2-yr storm)
0
500
1000
1500
2000
0 20 40 60 80 100 120
Flow
(cfs
)
Time (hours)
Present Future BMP LID
50
70
90
110
130
150
170
0 20 40 60 80 100 120
Inun
date
d Ar
ea (A
cres
)
Time (hours)
Present Future BMP LID
The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249 17
Peak Flow and HFR Results
Scenario
2-yr storm
Peak Flow
(cfs)
Reduction
(%)
HFR
(ac-hrs)
Reduction
(%)
Existing 1737 - 10,580 -
Future 1922 10.6% 10,913 3.1%
Future/BMP 1393 -19.8% 10,987 3.8%
Future/LID 1783 2.6% 10,628 0.4%
The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249 18
Peak Flow and HFR Results
Scenario
100-yr storm
Peak Flow
(cfs)
Reduction
(%)
HFR
(ac-hrs)
Reduction
(%)
Existing 6735 - 28,257 -
Future 7425 10.2% 30,979 9.6%
Future/BMP 5606 -16.8% 28,267 0.0%
Future/LID 6904 2.5% 28,637 1.3%
The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249 19
Observations • 2-yr storm
– Detention pond has lower peak flow than LID – LID has lower HFR than detention pond
• 10-yr and 100-yr storms – Detention pond has lower peak flow than LID – Detention pond has lower HFR than LID
• Adoption of combination of LID and BMP controls a wide spectrum of storms: – Better mimicking smaller and frequent storms – Providing necessary flood control during intense events
The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249 20
Stormwater Footprint Calculator (SFC) • Scott et al. (2014) developed an SFC:
– Education tool developed to improve knowledge and change attitudes and behavior regarding stormwater sustainability
• Participant’s answer about lot/neighborhood- level land use is used to compute HFR and Peak Flow
Scott T., Politte A., Saathoff S., Collard S., Berglund E., Barbour J., & Sprintson A. 2014. An evaluation of the Stormwater Footprint Calculator and the Hydrological Footprint Residence for communicating about sustainability in stormwater management. Sustainability: Science, Practice, & Policy 10(1) Published online Feb 21, 2014. http:///archives/vol10iss2/1210-048.scott.html
The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249 21
Stormwater Footprint Calculator (SFC) • An experiment (N = 510) undergraduate students was
used to test the SFC as a tool for: – communicating about stormwater management – compare HFR vs Peak Flow
• Results support: – improves knowledge about the causes of stormwater
runoff – LID technologies – HFR is a viable alternative to conventional engineering
metrics for communicating a stormwater footprint
Scott T., Politte A., Saathoff S., Collard S., Berglund E., Barbour J., & Sprintson A. 2014. An evaluation of the Stormwater Footprint Calculator and the Hydrological Footprint Residence for communicating about sustainability in stormwater management. Sustainability: Science, Practice, & Policy 10(1) Published online Feb 21, 2014. http:///archives/vol10iss2/1210-048.scott.html
The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249 22
In Summary • A modeling framework that includes a Land Cover
Change model, hydrologic, and hydraulic modeling to assess impact of urbanization and stormwater management
• A new metric designed to assess the impacts of urbanization on the hydrological flow regime by measuring inundated area and timing of flow
• HFR can better quantify alterations of the flow regime compared to the use of the peak flow only
• HFR can help better communicate stormwater concepts such as LID to the public
The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249 23
QUESTIONS?