Applications%20of%20landscape%20analyses%20and%20ecosystem%20modeling%20to%20investigate%20land-water%20nutrient%20coupling%20processes%20in%20the%20Guadalupe%20Estuary,%20Texas

1
Applications of landscape analyses and ecosystem
modeling to investigate land-water nutrient
coupling processes in the Guadalupe Estuary, Texas

• Sandra Arismendez, Hae-Cheol Kim, Jorge Brenner
• and Paul Montagna
• Harte Research Institute for Gulf of Mexico
  Studies
• Texas AM University Corpus Christi
• March 2009

2
Introduction

• Nutrient enrichment resulting from nonpoint
  sources of pollution is the largest pollution
  problem facing coastal U.S. waters (Howarth et al
  2000).
• More than 60 of coastal U.S. waters are
  moderately to severely degraded.
• Coastal waters along the Gulf of Mexico have been
  identified as those among the most severely
  degraded.
• Comprehensive studies that address the effects of
  land-water nutrient coupling processes along the
  Texas coast are lacking.

3
Research Objectives

• To characterize the San Antonio and Guadalupe
  River Basins.
• To determine effects of basin characteristics on
  nutrient concentrations.
• To determine estuarine ecosystem response to the
  addition of varying nutrient concentrations from
  the two river basins.

4
Approach
National Land Cover Dataset (1992, 2001)
TCEQ Historical Water Quality Monitoring
Data (1968-2007)
Landscape Analysis
Estuary Ecosystem Response Box Model
5
Study Area

• Two River Basins
• Guadalupe
• San Antonio
• Four HUCs in each basin
• Guadalupe Estuary
• Centrally located along Texas coast
• Microtidal
• Small bay area but large watershed relative to
  other Texas systems

6
Basin Characteristics
Characteristic 1 San Antonio River Basin 2 Guadalupe River Basin
Size (ha) 1.08 x 106 1.55 x 106
Human Population 1.8 x 106 4.0 x 105
Permitted Point Sources 83 industrial 34 municipal 51 industrial 19 municipal
1San Antonio River Basin Highlights Report
2003 2Guadalupe River Basin Highlights Report 2006
7
Precipitation and Flow
3Annual Average Flow GRB 56.76 m3/s (2004.62
cfs ) SARB 22.61 m3/s (798.39 cfs ) 3USGS, Water
Resources Data
Annual Average Precipitation 1GRB 76-94
cm/yr 2SARB 66-97 cm/yr
1Guadalupe River Basin Highlights Report 2006
2San Antonio River Basin Highlights Report 2003
8
Landscape Analysis

• ArcGIS
• Two years 1992, 2001
• 21 LULC categories
• Aggregated similar categories
• Developed
• Water
• Agriculture
• Barren
• Wetlands
• Forest
• Shrubland

(2001 National Land Cover Data)
9
Land Use Change
From 2 to 6
From 7 to 13
10
NLCD and TCEQ WQ Correlation

• PC scores for 1992 and 2001 only
• Positive correlation
• Areas with higher nutrients reflect areas with
  more developed land use
• Areas with lower nutrients reflect areas with
  less developed land use

R 0.70
Less nutrients
More nutrients
11
Nitrogen Concentrations (1976-2007)

• Long-term DIN concentration
• GRB lt SARB
• Flow vs DIN
• Positive correlation in GRB
• Negative correlation
• in SARB

Mean 284.06 uM Min 98.52 uM Max 738.23 uM
12
Model Inputs

• DIN loads from coastal HUCs used as model inputs
• Load comparison - 1992 vs. 2001
• Highest flows ever recorded in both basins in
  1992
• 2001 was a moderate flow year
• DIN loads differed in Guadalupe but not much
  difference in Lower San Antonio
• What does this mean?

13
Landscape Analysis Conclusions

• Basin characteristics are different, thereby
  influencing nutrient concentrations
• As developed land use increases, nutrients
  increase
• High river flow events in a river with high
  nutrient concentrations (SARB) appears to have a
  negative effect on DIN concentrations.
• High river flow events in the GRB appears to
  result in increased DIN concentrations.
• Increased flows do not affect loads in SARB as
  much as it affects loads in GRB.

14
A generic ecosystem model (3 components with 2
boundary conditions)

• Mass-balance model
• Two boundaries LGRW LSRW
• Three components Nutrient (DIN) Phytoplankton
  Zooplankton
• Re-mineralization and implicit sinking (or
  horizontal exchange) were assumed to be 50,
  respectively
• ?1 hr RK 4th order scheme

15
Why Phytoplankton?Phytoplankton are Indicators
of Water Quality, Climate Change

• Primary producer that can maintain food web by
  providing organic carbon upper trophic levels
  (food source)
• Carbon sequestration (deterring climate change)
• Biofuel (energy source)
• But too much? gt Eutrophication causing
  deterioration of water quality, hypoxia, etc.

NSF Polar Program
16
Model Results (steady-state case)

• No boundaries open, thus, mass conserved
• Each state variables approach steady state
  solutions

17
Boundary Conditions (DIN loadings)

• Monthly climatology (1976-2007)
• Flow rate (m3 s-1)
• DIN concentration (mg at-N m3)
• DIN Loading
• Flow rate DIN volume

18
Model Results

• No loadings (both boundaries shut down) Initial
  nitrogen pool for DIN, Phyto and Zoo will get
  eventually depleted
• When LSRW (2nd panel) or LGRW (3rd panel) were
  open discharged DIN kept nitrogen pool for DIN,
  Phyto and Zoo to a certain level
• LSRW and LGRW had a different timing, duration
  and magnitude in responses of DIN, Phyto and Zoo

19
Model Conclusions and Discussion

• Estuary response differs with respect to varying
  nutrient concentrations.
• Increases in nutrient concentrations due to human
  alterations of the landscape may result in future
  eutrophic conditions in the Guadalupe Estuary.
• Which nutrient species is more limiting to
  phytoplankton, nitratenitrite and/or ammonium?
• What is the role of DON?
• What is the proper mixing time scale?
• What is the true story in San Antonio Bay, then?

20
Estuary PCA Comparison

• Nitrogen species exhibit different behavior

21
Future Work

• Implement watershed model (e.g. SPARROW,
  ArcHydro)
• Develop nutrient budgets
• Develop a more realistic ecosystem loadings-based
  model
• Expand work to other river basins along Texas
  coast

22
Study Area Mission-Aransas Estuary, Texas
Mission River
Aransas River
Copano Bay
Aransas Bay

• 20 yr average salinity (psu)
• Copano Bay 17.1
• Aransas Bay 20.3

Discharge from upstream gauge (Mooney, 2008)
Did any changes in oyster populations occur
because of the changing salinities from 2007?
2008?
23
Corpus Christi Bay Hypoxia
24
(No Transcript)
25
(No Transcript)
26
(No Transcript)
27
Acknowledgements

• NOAA, Educational Partnership Grant,
  Environmental Cooperative Science Center
• Harte Research Institute for Gulf of Mexico
  Studies

28
Bio-Physical Coupling(Ecosystem model structure
within box)

• N Nutrients
• P Phytoplankton
• Z Zooplankton
• D Detritus
• B Benthos
• Solid arrow Explicit coupling
• Dotted arrow Indirect coupling with benthos

P
N
Z
D
B
29
Model Results
30
Guadalupe Estuary Box Model
Upstream Boundary Guadalupe, San Antonio Box
(Bay) Downstream Boundary Gulf Inlet
31
NLCD Analysis 1992, 2001
32
TCEQ Water Quality Analysis