Our Project . . .
Freshwater inflows: Determining flow regimes in the face of land use, climate change, and other unknowns Balancing Freshwater Inflows OBJECTIVE 1 OBJECTIVE 2 OBJECTIVE 3 OBJECTIVE 4 Collaborate with Develop shared Examine the effects of Improve inputs to the intended users to systems learning land use and climate TxBLEND salinity identify and conduct a among the local in a Changing Environment change on freshwater model of the Texas priority research stakeholders and inflows to the Water Development project related to a scientists for Guadalupe and Board. focal species construction of a Mission‐Aransas. mentioned in the system dynamics BBEST report. model.
Science to Policy Timeline Forecasted Texas Commission precipitation rates on Environmental • Introduce project to intended users (i.e., workshops, interviews) • Gather data for land use and climate scenario analysis Quality • Begin circulation study Year 1 • Identify focal species study with intended users Human water demand with • Begin mediated modeling changes in land use and More informed climate users for BBEST, • Analyze land use and climate scenarios BBASC, & public Texas Water • Continue circulation study comment • Collect data for priority research project Development Year 2 • Update intended users through a series of workshops Board • Expand mediated modeling effort TxBLEND
Indicator • Summarize results of land use and climate change analysis species • Analyze and summarize circulation datasets • Analyze and summarize results from priority research topic • Discuss results with intended users Year 3 • Disseminate results to wider audience
Computer model
Project Team Members
Zack Darnell, Ph.D. Applied Science Team
Kristin Hicks Project Team
Paulami Banerjee Collaboration Team
1 Circulation Objective 2 Freshwater inflows: Circulation
Seahorse current meters Tilt Current Meters
INCLINOMETER
Deployment / Retrieval Methods
PVC stake base
1 Deployment Data Deployment Data
Deployments: Stations: 15 in Aransas, 1 Copano, and 2345678 Mesquite Bays 9101112131415 June 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30123456 Deployment period: 7 8 9 10 11 12 13 2-3 weeks 14 15 16 17 18 19 20 July 21 22 23 24 25 26 27 28293031123 Logging interval: 45678910 1 reading per 2 min 11 12 13 14 15 16 17 18 19 20 21 22 23 24 August 25 26 27 28 29 30 31
Deployment Data Deployment Data Stick plot Stick plot
Strong Northward flow
Weak Northeastward flow
Strong Southward flow
Time
Deployment Data Deployment Data Histogram Summary Histogram Summary
2 Deployment Data Histogram Summary
Next Steps
• Continue monitoring 15 stations
• Determine flow patterns under different wind and tidal conditions
• Relocate meters as needed
• Buy additional meters
Inform the TxBLEND Model
3 All Wind Onshore North (68%)
Onshore South (24%) Offshore South (6%)
Offshore North (3%)
4 9/16/2013
May 30, 2012 Workshop
Everyone identifies their place in the estuary and shares ideas about Model Development important species, water circulation, and future September 12, 2013 land use. Port Aransas, TX Participants draw concept maps of management issues and challenges.
September 2012 Workshops Individuals ask: Participants develop a What do I want/need from the estuary? qualitative model of the estuary. What concerns/worries do I have about the Part I: Individuals estuary’s ability to satisfy my wants/needs into the identify needs and future? concerns about the estuary into the future. This leads to specific Given these wants/needs; what single question is questions. most important for the model to answer?
The results are the basis for model development. September 2012 Workshops Part II: Groups examine the May workshop model and ask questions the model might address. What concerns/worries do you have about the What do you want/need ? estuary’s ability to satisfy your wants/needs into the future?
Category No. Category No.
Sustainable Fisheries 16 Freshwater Inflows 22
Estuary Health 15 Estuary Health 14
Biodiversity 10 Human Impacts 14
Clean Water 7 Toxic Pollution 12
1 9/16/2013
Model Development Preliminary Model Question: Ask a specific question. How do freshwater inflows affect Keep it simple –you can always add. blue crab populations in the Mission‐Aransas and Copano Bay Use existing resources. system?
January 17, 2013 Workshop April 16, 2013 Workshop First draft of the Blue Crab Model. Second draft of the Blue Crab Model.
How is this model useful to you? How can the model How can it be be improved? improved?
How can the model be used?
Some of the updates you asked for… How you said this model might be used Make it easier to pause model to change parameters to for estuary management? approximate freshwater pulses and/or hurricane events. Harvest /fishery management Remove Whooping Cranes from model if they do not impact crab populations –make it real. Estuary health/restoration
Make model output user friendly to help us understand Water flow issues model results better. Outreach Documentation added to ‘Info’ tab and technical details of the model are available online. Crane issues
2 9/16/2013
Today….
An updated version of the model based on your feedback in April.
Opportunity to run simulations of this model.
Provide feedback on ways this model can be useful to you.
3 9/16/2013
Focal species for determining freshwater inflow needs of the Focal Species Mission-Aransas Estuary We chose studies for this project with consideration to:
• Input from stakeholders and interested parties
Ed Buskey • Study recommendations Research Coordinator, Mission-Aransas made in the BBASC Work Plan NERR for Adaptive Management Marine Science Institute The University of Texas at Austin
Adaptive Management Plan Adaptive Management Plan
The BBASC Work Plan for Adaptive Management includes The BBASC Work Plan for Adaptive Management includes five focal species study recommendations five focal species study recommendations
– Rangia clam investigations – Rangia clam investigations 1 1 – Life cycle habitat and salinity studies for blue crab and white shrimp – Life cycle habitat and salinity studies for blue crab and white shrimp
– Distribution and abundance of marsh vegetation in the Guadalupe – Distribution and abundance of marsh vegetation in the Guadalupe estuary delta estuary delta 2 2 – Habitat suitability models for eastern oysters, blue crabs, and white – Habitat suitability models for eastern oysters, blue crabs, and white
Priority Tier Priority shrimp Tier Priority shrimp
– Role of Cedar Bayou in the exchange of water and meroplankton to – Role of Cedar Bayou in the exchange of water and meroplankton to 3 3 the Guadalupe estuary the Guadalupe estuary
Presentation outline / line-up
• Rangia studies: TAMUCC / ECSC field work – Maria Rodriguez & Jana Gray • Possible Rangia studies UTMSI Key Indicator Species in MANERR: • Blue Crab studies Rangia cuneata – Larval behavior / recruitment: Kimberly Bittler – Citizen science project update Presented by: – Blue crabs and whoopers: TAP lawsuit Jana Gray Maria C. Rodriguez
1 9/16/2013
Can Rangia shells reveal patterns of Pacific Geoduck: northeast Pacific Ocean salinity? • Rangia larvae have requirement for low salinity growth increments in – Growth rings of living clams reveal year born hinge plate • Rangia growth may be higher during periods of high flow/low salinity – Compare width of growth rings to records of salinity and inflow • Rangia mortality may be high during periods of low flow/high salinity – Once yearly growth patterns established, determine if dead Rangia (empty shells) died during periods of low/flow high salinity
Bryan Black
Annual water temperature in NE Pacific Freshwater mussels (Margaritifera, Gonidea)
3 geoduck growth-increment chronology instrumental record 2 1 0 -1 -2
Temperature anomaly Temperature 1880 1900 1920 1940 1960 1980 2000 3 2 Year 1 0
1. geoduck an indicator of water temperature Anomaly -1 -2 freshwater mussel river discharge 2. long-lived: can use to hind-cast temperature -3 1960 1970 1980 1990 2000 2010 Year
mussel growth an indicator of river discharge (flow)
Rangia Bivalve shell chemistry records floods & temperature (Ben Walther)
Is Rangia growth-increment width an indicator of Winter temperature, flow, or something else like salinity? Temps Flood 18 13 -3.0 Stable isotopes (δ O and δ C) from growth increments give time series of: Questions to answer: -1.5 • Temperature • Freshwater inflow 1) Longevity of Rangia in TX bays – 10-15 years 0.0 Reconstruct environmental 2) Are growth increments well-defined and able to be O (‰)
18 conditions from isotopic records measured? - Yes δ 3) Can growth chronologies be developed? 1.5 Example: oyster shell in Aransas Bay 4) If so, how do they relate to climate? 3.0 048121620 Distance from umbo (mm) Time Oldest Most recent Image: http://txmarspecies.tamug.edu
2 9/16/2013
Megalopal recruitment into the MANERR – Citizen Science Project
The role of tidal salinity signals in blue crab recruitment in Mission-Aransas Estuary, TX
Kimberly Bittler, Lindsay Scheef, Ed Buskey
Volunteer-driven research Sampling sites
• Daily sampling • Volunteers enable research that would otherwise be logistically impossible
Lindsay Sheef data summary Lots of samples taken Lots left to count!
3 9/16/2013
Blue crab megalopae abundance
Suction sampling Volunteer T-shirt design
(Orth and Van Montfrans 1987)
Lawsuit: The Aransas Project (TAP) vs. Court Case (continued) Shaw et. al • TAP sued TCEQ officials under the • TAP asked the court to declare that Endangered Species Act for an illegal “take” TCEQ’s water management practices of the endangered Whooping Crane in 2008- 2009 violate the Endangered Species Act • TAP claimed that TCEQ’s water management • Require TCEQ apply for incidental take practices, combined with drought caused permits for issuance of new water permits hyper-saline conditions in the bays for San Antonio and Guadalupe Rivers • This in turn caused a reduction in the cranes’ • Endangered Species Act would then primary food source (blue crabs and wolfberries) and fresh drinking water require TCEQ to work with USFWS to • This lead to the deaths of 23 cranes formulate a Habitat Conservation Plan based on best available science
4 9/16/2013
Options to increase water to bays Questions?
• Cancel unused water rights • Increase return of treated wastewater to rivers • Use funds from oil spill settlement to purchase water rights
5 9/16/2013
Key Indicator Species in MANERR: Purpose Rangia cuneata • Determine – Present Status – Distribution – Abundance
Presented By: Jana Gray Maria C. Rodriguez
http://www.lakescientist.com/
R. cuneata R. cuneata
• Long posterior lateral tooth • Distinct pallial sinus • Thick, heavy shell
• Prominent, distinct umbo near the anterior (http://txmarspecies.tamug.edu) end
Habitat and Range Texas distribution
• Chesapeake Bay, down the east coast to the tip of Florida • Nueces River • Throughout the GOM • Green Lake • Along the eastern side of Mexico • Mission Lake • Campeche • San Jacinto River • Becoming invasive in Europe • Delta distributaries of Trinity River • Neches River • Sabine River • St. Charles Bay • Hynes Bay • Matagorda Bay • Lavaca Bay • Upper Galveston Bay • Trinity Bay (http://www.twdb.texas.gov/) • East Bay • Sabine Lake (http://eol.org)
1 9/16/2013
Environmental Conditions Materials
• Salinity – 0‐25psu • Usually established in areas of 0‐15psu • Temperature – 2‐30° C along eastern coast of US – 10‐32° C in the US GOM – 25‐31° in Mexican waters • Spawning triggered by certain salinity and temperature changes • Sediments – Prefer sand but can be found in mud and gravel • Depth – Less than 6m
Photo credit: Jana Gray 2013
Methods Findings
• Weekly sampling • Only live shells found in Aransas River – Aransas River system • Dead shell found everywhere else – Mission River system ©The University of Texas at Austin
Photo credit: Jana Gray 2013
References Auil‐Marshalleck, S., Robertson, C., Sunley, A., Robinson, L. (2000) Preliminary review of life history and abundance of the Atlantic Rangia Future Directions (Rangia cuneata) with implications for management in the Galveston Bay, Texas. Management Data Series, 171, 1‐31 Cain, T. D. (1973) The combined of temperature and salinity on embryos and larvae of the clam R. cuneata. Marine Biology, 21, 1‐6. Cain, T.D. (1975) Reproduction and recruitment of the brackish water clam Rangia cuneata in the James River, Virginia. Fishery Bulletin, 73: 412‐430. Dillon, T. M. (1977) Mercury and the estuarine marsh clam, Rangia cuneata Gray. I. toxicity. Archives of Environmental Contamination and Toxicology, 6, 249‐255. • Measure distribution and abundance Fairbanks, L. D. (1963) Biodemographic studies of the clam Rangia cuneata Gray. Tulane Studies in Geology, 1, 3‐44. Harrel, R. C. (1993) Origin and decline of the estuarine clam Rangia cuneata in the Neches River, Texas. American Malacological Bulletin, 10, 153‐159. • Seek out possible “refuge populations” Hopkins, S. H. (1970) Studies on brackish water clams of the genus Rangia in Texas. Proceedings of the National Shellfisheries Association, 60, 5‐6. Jamison, J.L. (1990) Sensory evaluation studies to solve food science problems associated with the market development on Rangia clams. Gulf – &South Atlantic Fisheries Development Foundation Inc. Larger populations farther up the river that seed LaSalle, M. W., de la Cruz, A. A. (1985) Common Rangia. Biological Report, 82: 1‐13 McConnell, M.A., Harrel, R.C. (1995) The estuarine clam Rangia cuneata (Gray) as a biomonitor of heavy metals under laboratory and field the smaller populations under favorable conditions. American Malacological Bulletin, 11(2), 191‐201 Montagna, P.A. and T. Palmer. (2012) Impacts of Droughts and Low Flows on Estuarine Health and Productivity. Final Report to the Texas Water Development Board, Project for Interagency Agreement conditions 1100011150. Harte Research Institute, Texas A&M University‐Corpus Christi, Corpus Christi, Texas. 142 pp. Olsen, L.A. (1976) Reproductive cycles of Polymesoda caroliniana (Bosc) and Rangia cuneata (Gray) with aspects of desiccation in the adults and fertilization and early larval stages in Polymesoda caroliniana. Ph.D. Dissertation. Florida State University, Tallahassee. • Sample further up the Aransas River 116. Rudinskaya, L.V., Gusev, A.A. (2012) Invasion of the North American wedge clam Rangia cuneata (G.B. Sowerby I, 1831) (Bivalvia: Mactridae) in the Vistula Lagoon of the Baltic Sea. Russian Journal of Biological Invasions. 3(3), 220‐229. Verween, A. Kerckhof, F., Vincx, M., Degraer, S. (2006) First European record of the invasive brackish water clam Rangia cuneata (G.B. Sowerby I, 1831) (Bivalvia: Mactridae). Aquatic Invasions. 1(4), 198‐203. Wakida‐Kusunoki, A.T., MacKenzie, Jr. C.L. (2004) Rangia and Marsh Clams, Rangia cuneata, R.flexuosa, and Polymesoda caroliniana, in Eastern Mexico: Distribution, Biology and Ecology, and Historical Fisheries. Marine Fisheries Review. 66(3), 13‐20. Wong, W.H., Rabalais, N.N. (2010) Abundance and ecological significance of the clam Rangia cuneata (Sowerby, 1831) in the upper Barataria Estuary (Louisiana, USA). Hydrobiologia. 651, 305‐315.
2 9/16/2013
Special Thanks
• Dr. Wes Tunnell • Shanna Madsen • Rick Kalke • Jay Tarkington • NOAA ECSC • Harte Research Institute tamucc.edu
3 9/16/2013
Introduction
• Freshwater Inflows The role of tidal salinity signals in – Senate Bill 3 blue crab recruitment in Mission‐ – Can be limited in TX Aransas Estuary, TX • Blue Crabs Kimberly Bittler, Lindsay Scheef, Ed – Commercial blog.nwf.org Buskey – Ecological role – May be linked to freshwater inflows
Fooddestination.blogspot.com
Selective Tidal Stream Transport Selective Tidal Stream Transport
Ocean Estuary Ocean Estuary
Salinity
1 9/16/2013
Selective Tidal Stream Transport Selective Tidal Stream Transport
Ocean Estuary Ocean Estuary
Keep swimming due to turbulence
Salinity
Selective Tidal Stream Transport Selective Tidal Stream Transport
Ocean Estuary Ocean Estuary
Stop swimming as turbulence decreases Decrease in salinity with slack tide
Does it work here in the Mission‐ Rates of daily maximum salinity change from Aransas? August 2007 – January 2012 • Freshwater inflows episodic • Variable salinity gradient ebb
• Do not have a reliable tidal salinity signal flood Frequency
0.000 0.001 0.002 0.003 0.004 0.005
2 9/16/2013
Rates of daily maximum salinity change from Rates of daily maximum salinity change from August 2007 – January 2012 August 2007 – January 2012
ebb ebb But major Maximum differences are at response in flood the lowest rates flood original tidal stream transport
Frequency studies in NC Frequency
0.000 0.001 0.002 0.003 0.004 0.005 0.000 0.001 0.002 0.003 0.004 0.005
Objectives Methods
• Re‐test responses of megalopae to changes in salinity – Repeat Tankersley et al. 1995 study Controled rate • Model salinity responses of megalopae onto of salinity changes occurring in field change
Salty water in
Methods Methods BEFORE AFTER BEFORE AFTER
1 up 4 up
3 9/16/2013
Methods Methods BEFORE AFTER BEFORE AFTER
1 up 4 up 1 up 4 up
(4‐1)/4 = 3/4 = (4‐1)/4 = 3/4 = 75 % net response 75 % net response
(our experiment uses 30 megalopae)
Methods Vertical response to salinity change BEFORE AFTER TX NC(Tank)
50 This behavior 40 (%) drives transport 30 on the
Flood tide Response 20 over the ebb tide Net 10
0 0 0.001 0.002 0.003 0.004 ‐10 Rate of salinity increase (ppt/s)
Vertical response to salinity change Vertical response to salinity change
TX NC(Tank) TX NC(Tank)
50 50 Lower peak response 40 40 Don’t Respond to high rates (%) (%)
30 30
Response 20 Response 20
Net 10 Net 10
0 0 0 0.001 0.002 0.003 0.004 0 0.001 0.002 0.003 0.004 ‐10 ‐10 Rate of salinity increase (ppt/s) Rate of salinity increase (ppt/s)
4 9/16/2013
Responses to salinity change in ocean Vertical response to salinity change water
25 TX NC(Tank) Decrease 50 20 Increase (%) 40 15 (%)
10 30 response 5 Response
20 Net
High variability in response 0 Net 10 ‐5 0 27 March 4 June 21 June 0 0.001 0.002 0.003 0.004 ‐10 Rate of salinity increase (ppt/s)
Responses to salinity change in ocean Summary of behavior experiments water
25 Decrease • TX megalopae respond to lower rates of 20 Increase salinity increases (%) 15 • TX megalopae have a dampened response at
10 High high rates of change variability response 5 in • High variability in responses of TX megalopae Net response 0 – Variation is not due to varied water conditions
‐5 – Variation is due to megalopae 27 March 4 June 21 June
What does this mean for What does this mean for recruitment in Mission‐Aransas? recruitment in Mission‐Aransas?
Find out with a model…
5 9/16/2013
Predicting tides Predicting tides
1.7 1.7 0.0015 (m) (m) 1.68 1.68 (m/s)
0.001 1.66 1.66
height height 0.0005 1.64 1.64 height 1.62 1.62 0 tidal tidal
tidal 1.6 1.6 ‐0.0005 in 1.58 1.58 1.56 1.56 ‐0.001 predicted predicted
1.54 1.54 ‐0.0015 Change
Predicting tides Salinity‐Recruitment Model
1.7 Flood tide Ebb tide 0.0015 35 (m) 1.68
(m/s) 30
0.001 1.66 25
height 0.0005 1.64 (ppt) height
20 1.62 0 tidal 15 tidal 1.6 ‐0.0005 in Salinity 1.58 10 1.56 ‐0.001 5 predicted
1.54 ‐0.0015 Change 0
Salinity‐Recruitment Model Salinity‐Recruitment Model
35 0.003 35 Flood tide Ebb tide 0.003 30 0.002 30 0.002 (ppt/s) (ppt/s) 25 25 0.001 0.001 (ppt) (ppt)
20 20 0 0 salinity salinity 15 15 in in ‐0.001 ‐0.001
Salinity 10 Salinity 10 5 ‐0.002 5 ‐0.002 change change 0 ‐0.003 0 ‐0.003
6 9/16/2013
Salinity‐Recruitment Model Salinity‐Recruitment Model Only active at night
35 Flood tide Ebb tide 0.003 35 Flood tide Ebb tide 0.003 30 0.002 30 0.002 (ppt/s) (ppt/s) 25 25 0.001 0.001 (ppt) (ppt)
20 20 0 0 salinity salinity 15 15 in in ‐0.001 ‐0.001
Salinity 10 Salinity 10 5 ‐0.002 5 ‐0.002 change change 0 ‐0.003 0 ‐0.003
Salinity‐Recruitment Model Salinity‐Recruitment Model
tankersleyNC (Tankersley) Flood tide Ebb tide bittlerTX 35 0.003 50 30 0.002 40 (ppt/s) 25 0.001
(ppt) Max rate selected 30 20 0 salinity
for use in model 15 20 in ‐0.001 Salinity 10 response
‐0.002 10
5 net
change 0 ‐0.003 % 0 1.00E0 (control)‐05 1.00E‐04 1.00E‐03 1.00E‐02 ‐10 Rate ppt s‐1 ‐20
Salinity‐Recruitment Model Salinity‐Recruitment Model
Rate calculated in Rate calculated in tankersleyNC (Tankersley) field on ebb or tankersleyNC (Tankersley) field on ebb or flood tide flood tide bittlerTX bittlerTX 50 50
40 40 NC (Tankersley) response = 32% 30 30
20 20
response response TX response = 10% 10 10 net net
% 0 % 0 1.00E0 (control)‐05 1.00E‐04 1.00E‐03 1.00E‐02 1.00E0 (control)‐05 1.00E‐04 1.00E‐03 1.00E‐02 ‐10 ‐10 Rate ppt s‐1 Rate ppt s‐1 ‐20 ‐20
7 9/16/2013
50 SC Salinity‐Recruitment Model 40 CE AB
(ppt) 30
[% response on flood tide] 20 salinity 10 – 0 15 [% response on ebb tide] Net.BTX 10 Net.TNC = 5 0 (%/day) NET flux (% per day) ‐5 Flux
‐10 Net ‐15
50 SC 50 SC 40 CE 40 CE AB AB
(ppt) 30 (ppt) 30
20 20 salinity 10 Over the time salinity 10 0 series, NC are 0 twice as likely 15 10
(%/day) to be ‐1% Net.BTX 10 transported out Net.BTX flux 5 on ebb tide by Net.TNC 5 salinity 0 ‐2%
0 Average (%/day) (%/day) ‐5 ‐5 Flux Flux
‐10 ‐10 Net Net ‐15 ‐15
50 SC 40 CE Salinity‐Recruitment Model AB
(ppt) 30
20 Assumptions: salinity 10 • Salinity ONLY factor that matters 0 Megalopae in TX can be transported out of estuary on – No pressure, chemistry, etc. 10 ebb tide during drought 5 Net.BTX • No seasonal flux in supply 0 • No source‐sink dynamics (%/day) ‐5 Flux ‐10 Net ‐15
8 9/16/2013
Salinity‐Recruitment Model Summary
Assumptions: • Megalopae in TX are more sensitive than NC • Salinity ONLY factor that matters megalopae to salinity changes – No pressure, chemistry, etc. • Heightened sensitivity is adaptive to • No seasonal flux in supply recruitment in long term in Mission‐Aransas • No source‐sink dynamics • Can be transported out during drought years
OCEAN ESTUARY
9 9/16/2013
Freshwater Inflows: Determining flow regimes in the face of land use, climate change, and other unknowns Land Use and Climate Change Scenarios: Modeling changes in water use and runoff OBJECTIVE 1OBJECTIVE 2 OBJECTIVE 3OBJECTIVE 4
Collaborate with Develop shared Examine the effects intended users to Improve inputs to systems learning of land use and identify and the TxBLEND among the local climate change on conduct a priority salinity model of stakeholders and Dr. Kiersten Madden freshwater inflows research project the Texas Water to the Guadalupe‐San related to a focal scientists for Stewardship Coordinator Development Board. Antonio and Mission‐ species mentioned in construction of a Mission‐Aransas National Estuarine Research Reserve system dynamics Aransas. the BBEST report. model.
www.missionaransas.org 09/12/13 www.missionaransas.org 09/12/13
Scenario Based Study Area Planning Research
Land Use/Land Cover Open Water Developed, Open Space Developed, Low Intensity Developed, Medium Intensity Monitor Create Developed, High Intensity Indicators Scenarios Barren Land Deciduous Forest Scenarios are Evergreen Forest plausible futures that Mixed Forest allow you to envision Shrub/Scrub and evaluate outcomes Grassland/Herbaceous of potential decisions in Evaluate Hay/Pasture the context of different Scenarios Cultivated Crops sets of background Woody Wetlands conditions. Emergent Herbaceous Wetlands
www.missionaransas.org 09/12/13 www.missionaransas.org 09/12/13
CLIMATE CHANGE EMISSIONS SCENARIOS Scenario 1 Scenario 2 Scenario 3 Scenario 4 Scenario 5 A2 (High) A2 (High) A2 (High) A2 (High) A2 (High) Scenarios 2020 2020 2020 2020 2020 Annual Fall Winter Spring Summer
From: IPCC Report, 2007
Scenario 6 Scenario 7 Scenario 8 Scenario 9 Scenario 10 A2 (High) A2 (High) A2 (High) A2 (High) A2 (High) 2060 2060 2060 2060 2060 Annual Fall Winter Spring Spring Accounts for changes in . . . Socio-economics
Scenario 11 Scenario 12 Scenario 13 Scenario 14 Scenario 15 B1 (Low) B1 (Low) B1 (Low) B1 (Low) B1 (Low) Demographics Timeframe: 2020 2020 2020 2020 2020 2020, 2060 Annual Fall Winter Spring Summer Technology Emissions: A2 (High), B1 (Low) Scenario 16 Scenario 17 Scenario 18 Scenario 19 Scenario 20 B1 (Low) B1 (Low) B1 (Low) B1 (Low) B1 (Low) Approach: 2060 2060 2060 2060 2060 Annual, Seasonal Annual Fall Winter Spring Spring
www.missionaransas.org 09/12/13 www.missionaransas.org 09/12/13
1 9/16/2013
Future Land Use Future Land Use
This scenario consists of a low population projection and a slightly This is the highest compact development ICLUS population pattern, which results in projection and for most the least altered areas in the U.S. landscape for most areas represents a “worst case” of the U.S.. pattern of development. B1: Rapid social development LAND USE LAND USE in developing regions. Commercial/Industrial A2: Slower rate of economic Commercial/Industrial growth. Population rises rapidly Urban (<0.25 acres/unit) Urban (<0.25 acres/unit) until mid-century, then falls Suburban (0.25 – 2 acres/unit) Restricted flow of people and Suburban (0.25 – 2 acres/unit) below replacement levels. ideas across regions. Exurban (2 – 40 acres/unit) Exurban (2 – 40 acres/unit) Fertility and average U.S. Fertility and average U.S. Rural (>40 acres/unit) Rural (>40 acres/unit) household size decrease. household size increase. Domestic migration is low, Domestic migration is high, but net international but net international migration is high. migration is moderate. ICLUS: INTEGRATED CLIMATE AND LAND USE SCENARIOS ICLUS: INTEGRATED CLIMATE AND LAND USE SCENARIOS
www.missionaransas.org 01/17/13 www.missionaransas.org 01/17/13
Create land use scenarios Create indicators measuring impacts (economic, social, 1 environmental) Numeric Build-out Area = 5 acres Mathematical calculation based on Density = 1 DU/acre Create 3D visual models area and density rules. OUTPUT: Calculated Number Numeric DUs = 5
Project impacts into the future 2 Spatial Build-out Creates map layer with points or Physical shape restricts polygons representing buildings by development. possible locations. Spatial DUs = 4 OUTPUT: Points on map Experiment interactively and see changes
www.missionaransas.org 09/12/13 www.missionaransas.org 09/12/13
Too time consuming . . . A simpler approach . . .
Number of dwelling units = 1 Size of Parcel (acres) / Size of the dwelling unit (acres/unit)
Population = Number of dwelling Units * Average 2 Household Size
LAND USE Commercial/Industrial Residential Water Use = Urban (<0.25 acres/unit) Population (people) * Water Use Suburban (0.25-2 acres/unit) Assumption (gal/person/day) Exurban (2-40 acres/unit) 3 Rural (>40 acres/unit)
www.missionaransas.org 09/12/13 www.missionaransas.org 09/12/13
2 9/16/2013
Verifying and refining assumptions . . . Indicator: Population
Average County Household Size POPULATION Kerr 2.35 From: IPCC Report, 2007 Size of dwelling unit : Gillespie 2.38 Bandera 2.49 1 Rural: > 40 acres/unit --> 500 acres/unit Kendall 2.70 Exurban: 2 – 40 acres/unit --> 25 acres/unit Blanco 2.50 Bexar 2.78 Suburban: 0.25 – 2 acres/unit --> 0.5 acre/unit Medina 2.91 Urban: < 0.25 acre/unit --> 0.2 acre/unit Atascosa 2.99 Comal 2.64 Hays 2.69 Caldwell 2.82 Guadalupe 2.83 Wilson 2.89 Gonzales 2.69 Average Household Size Karnes 2.66 2 DeWitt 2.53 Victoria 2.75 Goliad 2.57 Bee 2.74 Calhoun 2.75 Refugio 2.59 Aransas 2.43 San Patricio 2.97 A2 B1 www.missionaransas.org 09/12/13 www.missionaransas.org 09/12/13
Verifying and refining assumptions . . . Indicator: Residential Water Use
3 RESIDENTIAL WATER USE
Assumptions:
A2 B1 www.missionaransas.org 09/12/13 www.missionaransas.org 09/12/13
Indicator: Residential Water Use Land Cover / Land Use
RESIDENTIAL WATER USE New Assumptions: 77
77 92 92 92 97 97 77
A2 B1 www.missionaransas.org 09/12/13 www.missionaransas.org 09/12/13
3 9/16/2013
Indicator: Land Use Indicator: Land Use
Developed Open Space Developed B1 EMISSIONS A2 EMISSIONS Open Space SCENARIO SCENARIO
Developed Developed Low Low Intensity Developed Developed Developed Developed Intensity High Medium High Medium Intensity Intensity Intensity Intensity
www.missionaransas.org 09/12/13 www.missionaransas.org 09/12/13
Indicator: Land Cover Indicator: Land Cover
B1 EMISSIONS SCENARIO A2 EMISSIONS SCENARIO
Shrub/Scrub Shrub/Scrub
Pasture/Hay Pasture/Hay
Forest Forest
Cultivated Cultivated Cropland Cropland Herbaceous/ Herbaceous/ Grassland Wetlands Grassland Wetlands
www.missionaransas.org 09/12/13 www.missionaransas.org 09/12/13
Irrigation Indicator: Irrigation
CULTIVATED CROPLAND IRRIGATION WATER USE
Irrigation Water Use = Acres of Cropland * Water Use Assumption (inches/acre/year) * % of Acres Irrigated Assumption
Source: “Status and Trends of Irrigated Agriculture in Texas” (TWRI, 2012)
A2 B1 A2 B1 www.missionaransas.org 09/12/13 www.missionaransas.org 09/12/13
4 9/16/2013
Indicator: Irrigation Indicator: Irrigation
Assumptions: IRRIGATION WATER USE Assumptions: 50% IRRIGATION WATER USE 50% 15 18 18 35% 15 35% 17 17 15 17 17 17 17 25% 15 15 25% 15 18 18 35% 50%
A2 B1 A2 B1
www.missionaransas.org 09/12/13 www.missionaransas.org 09/12/13
Indicator: Irrigation from Surface Water Next Steps
IRRIGATION Continue to refine indicators . . . SURFACE WATER Add county specific groundwater : surface water ratios Add county specific estimates of # of acres irrigated
Develop additional indicators . . . Livestock water use (NRCS: Converting forage to animal unit) Commercial/Industrial water use
Begin modeling runoff
A2 B1
www.missionaransas.org 09/12/13 www.missionaransas.org 09/12/13
Elevation (USGS: NED) Precipitation (PRISM/Climate Wizard)
Runoff Modeling Nonpoint-Source Runoff Modeling Pollution and Erosion Comparison Tool
Soils (NRCS: SSURGO) LULC (USGS: NLCD/EPA: ICLUS)
Land Cover Elevation Precipitation Hydrologic Soils Group Soil Erodibility Rainfall Erosivity
www.missionaransas.org 09/12/13 www.missionaransas.org 09/12/13
5 9/16/2013
Questions
This project is funded by the National Estuarine Research Reserve System Science Collaborative, a partnership of the National Oceanic and Atmospheric Administration and the University of New Hampshire.
www.missionaransas.org 09/12/13
6 Announcements and Announcements and Updates Updates
October 16, 2013 CHARM Speaker Series th Preserving our CHARM in the Freshwater inflows, nutrients and September 28 is National Estuaries Day! Midst of Growth and Change ecosystem function in the Mission‐Aransas Bay Education Center Estuary Tangled Turtles and Globetrotting Trash & Rockport, Texas Dr. Edward J. Buskey Wednesdays, 11am ‐ 12pm Research Coordinator, NERR; Director, Aransas National Wildlife Clean‐Up GOMRI DROPPS Consortium September 18, 2013 Housing and Growth Trends: National to Local October 30, 2013 Talk to Colleen McCue, Dr. Shannon Van Zandt, AICP Costs and Benefits of Renewable Energy in [email protected] or Director, Center for Housing & Urban Texas Development, Texas A&M University 361‐749‐3153 about Dr. Joshua Linn Fellow, Resources for the Future volunteering!
Announcements and Announcements and Updates Updates
Oct 30th Staying Productive on the Go: Mobile Technology Training Café Contact [email protected] for details Save‐the‐date
Nov 9th Egery Flats Clean‐Up 8:00a.m.‐12noon Thursday, April 10, 2014 Nov 11th Coastal Planning Tools Next Meeting Workshop Contact [email protected]
Questions, comments, or suggestions
www.missionaransas.org [email protected]
1