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: dsahoo@tamu.edu

(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

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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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Poster # 33