Assessing Climate Variability and Anthropogenic Activity on
Estuarine Environmental Flows Using Signal Processing TechniquesDebabrata Sahoo1, Patricia K. Smith2, and Fuqing Zhang3
1 2 Biological and Agricultural Engineering, 3Department of Atmospheric Sciences, Texas A&M University, College Station, TX 77843
Introduction:
The study of environmental inflows is an evolving science (NRC, 2005). Adequate
environmental inflows are needed for proper ecological maintenance of aquatic ecosystems
such as estuaries. Estuarine freshwater inflows are influenced by the land use/land cover
(LULC), water management practices in the contributing watershed, and climate variability,
particularly in watersheds that are experiencing rapid human induced disturbances. San
Antonio, TX, the 8th largest city in the US, is situated in the San Antonio River basin. The
basin encompasses 11000 square kms from the headwaters to the point at which this river
joins with the Guadalupe River, before draining into Gulf of Mexico. Rapid urbanization has
not only changed the land use and land cover in this river basin, but also has increased the
number of point sources such as WWTPs. Studies in the river basin suggest that change in
land use has primarily been an increase in impervious surface. Increase in impervious surface
can change the flow regime by altering timing, magnitude, scale, and frequency of freshwater
inflows. This study used signal processing techniques to assess the scale and frequency
modulation in the environmental flow; and evaluated the possible linkage of climate
variability or anthropogenic activity to it.
Figure 1: San Antonio River Basin showing major streams, and USGS gauging stations
References:
Arnold, J. G, Allen, P. M., 1999. Automated method for estimating baseflow and groundwater recharge from stream flow records. Journal of
the American Water Resources Association 35, 411-424.
NRC., 2005. The science of instream flows: A review of Texas instream flow program. Washington D. C. National Academy Press.
Sahoo, D., and P. Smith. 2007. Analysis of seasonal environmental flows to a gulf coast estuary in a rapidly urbanizing semi-arid coastal
river basin (Submitted to the Journal of Hydrology).
Sahoo, D., P. Smith, and F. Zhang. 2007. Characterization of freshwater inflows draining to a gulf coast estuary in a rapidly urbanizing
coastal watershed using wavelet techniques (Submitted to Estuarine Coastal and Shelf Science).
Address for Communication:
Debabrata Sahoo,
Graduate Research Assistant,
Biological and Agricultural Engineering,
Texas A and M University,
College Station, TX-77843-2114,
Email: [email protected]
(b) (c)
Methodology:
This study used 63 years (1940-2003) of daily average flow data from the most
downstream USGS gauging station number 08188500 (Figure 1), and rainfall from NCDC
COOP ID 413618 situated near the USGS gauging station (Figure 1). Average daily data was
aggregated to estimate seasonal flow and seasonal rainfall (December-March, April-July, and
August-November). A baseflow separation filter (Arnold, and Allen, 1999) was used to
separate baseflow. Wavelet analysis was conducted using MATLAB. Wavelet analysis of the
hydrologic stream flow data helps to understand the cyclic changes and patterns present in the
time series. It helps to link these cyclic changes to river basin water management to maintain
estuarine ecological health. For the current analysis, a complex Morlet wavelet function was
used. The wavelet transformation Wn is the convolution of a vector x (with time dimension n)
with a wavelet function ψ
(1)
where s is the scale, or dilation, n' – n shows the number of points from time series origin
(translation), δt is the time interval, N is the number of points. In this analysis, a complex
Morlet wavelet function ψ0(η), which is commonly used for signals with strong wave-like
features (such as streamflow data), was used and is calculated as:
(2)
where ω0 is the non-dimensional wave number and η is a time parameter (non-dimensional,
also could represent other metrics such as distance). Results and Discussion:
Time series analysis of seasonal environmental flow (Figure 2) suggested an increasing trend in total seasonal flow, and total base flow in all of the seasons. An increasing trend in runoff was only observed in the winter (Dec-Mar)
time series (also see: Sahoo and Smith, 2007). Historic rainfall analysis suggested no increasing trend. The increase in total flow and baseflow could possibly be attributed to increasing number of WWTPs in the City of San Antonio region
(Figure 3). Historic land use land cover data analysis suggested an increase of about 5% in urban impervious layer from 1987 to 2003 in the study region (Sahoo and Smith, 2007). Wavelet analysis (Figure 4) suggested presence of dominant
frequencies in 19-25 years scale, cycling every 20-25 years, in all the time series. Similarly, 9-15 years scale, cycling every 10 years, in most of the time series. However, this observation was not seen in total runoff for Dec-Mar, and
Aug-Nov (Figure 4 c). Detail analysis of base flow in this scale for Aug-Nov suggested some shift of higher frequencies towards 1980; this could possibly influenced by WWTPs. however, in general, analysis suggested total flow to have
similarity with base flow. Close look of runoff and rainfall (Figure 4 c and d) analysis at 9-13 years scale suggests some repeatability of higher frequencies in both the domain (Sahoo et al., 2007); however runoff scale has slightly shifted after
1980, although rainfall scale remained the same. This could possibly be attributed to increase in impervious surfaces.
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Figure 2: Comparison of seasonal Total flow, Baseflow, Runoff, and Rainfall (a) Dec-Mar, (b) Apr-Jul, and (c) Aug-Nov
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Figure 3: Two WWTPs discharges in San Antonio
River Basin
Figure 4: Wavelet comparison of seasonal (from top to bottom) Dec-Mar, Apr-Jul, and Aug-Nov (a) Total flow, (b) Baseflow, (c) Runoff, and (d) Rainfall
∑−
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−=
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)'(N
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δψ
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0)(ηηωπηψ −−= ee
i
Poster # 33