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2.3.1 Turbidity Index…………………………………………………………………...23 U UNIVERSITY OF CINCINNATI Date: I, , hereby submit this original work as part of the requirements for the degree of: in It is entitled: Student Signature: This work and its defense approved by: Committee Chair: Approval of the electronic document: I have reviewed the Thesis/Dissertation in its final electronic format and certify that it is an accurate copy of the document reviewed and approved by the committee. Committee Chair signature: Seasonal and Annual Changes in Water Quality in the Ohio River Using Landsat- based measures of Turbidity and Chlorophyll-a A thesis submitted to the Division of Graduate Studies and Research University of Cincinnati In partial fulfillment of the requirements for the degree of Masters of Arts Department of Geography University of Cincinnati February 2008 By SHAZIA BEE Bachelor of Science, Devi Ahilya University, Indore, India, 2005 Thesis Advisor and Committee Chair: Dr. Robert C Frohn ABSTRACT The aim of this research was to study the seasonal and annual changes in the water quality based on the landsat measures of turbidity and chlorophyll-a. The indices were applied to a 95 km segment of the Ohio River where the USEPA had collected actual turbidity and chlorophyll-a samples the same day as the Landsat-7 overpass. Pearson correlation coefficient was calculated for the chlorophyll-a and turbidity indices, which was -0.938. A regression model was also developed to quantify chlorophyll-a (dependent variable) from turbidity (independent variable). The regression model had R2 value of 0.879, indicating a good fit. For the annual analysis of water quality, only the turbidity index was taken into consideration. The turbidity level is constant in the years 2000 and 2001. There has been a significant decrease in the concentration of turbidity from the year 2002 indicating improvement in the water quality. Efforts taken by the government and other agencies to improve the water quality could be the reason for constant turbidity index. iii iv Acknowledgement My sincere thanks to my thesis advisor and committee chair Dr. Robert C. Frohn for his invaluable technical suggestion, guidance and support throughout the thesis work. I would like to sincerely thank, Dr. Robert South and Dr. Richard Beck for becoming a part of the thesis defense committee and for giving their precious time to review my thesis. I would like to thank, University of Cincinnati for providing me the opportunity for pursuing my Graduation in Geography department. A special thanks to my parents and brother for their constant encouragement and blessings that they have given me at every step of my life. I would like to thank all the fellow graduate students in the Geography department. Studying with them was an enriching and memorable experience. v Table of Contents List of Figures ………………………………………………………………………………….viii List of Tables ……………………………………………………………………………………ix 1 Introduction 1 1.1 Background and Literature Review……………………………………………………..…...3 1.1.1 Water Quality…………………………………………………...............................3 1.1.2 Water Quality, Chlorophyll-a and Turbidity………………………………….......6 1.1.3 Ohio River Water Quality……………………………………………..……….….7 1.1.4 Turbidity………………………………………………………………………….10 1.1.4.1 Turbidity and TSS …………………………………………………..…13 1.1.5 Chlorophyll-a …………………………………………………………………....14 1.1.5.1 Measuring Chlorophyll-a………………………………………………16 1.1.5.2 Changes in the concentration of Chlorophyll-a …………………..……17 2 Study Area 28 2.1 Methodology…………………………………………………………………………….…19 2.2 Landsat Measurements of Water Quality …………………………………………….........21 2.3 Rationale for using indices of turbidity and Chlorophyll-a .……………………………...22 2.3.1 Turbidity Index…………………………………………………………………...23 2.3.2 Chlorophyll-a Index……………………………………………………...............24 2.4 Seasonal and Annual Analysis of Turbidity and Chlorophyll-a .…………….....................30 vi 3 Results and Discussion 32 3.1 Seasonal Analysis of Turbidity and Chlorophyll-a………………………………………....32 3.2 Annual Analysis of Turbidity…………………………………………………………........36 4 Conclusion 39 References 40 vii LIST OF FIGURES Figure 1.1 Sources and types of nonpoint source pollution in affected US rivers and lakes….. ..4 Figure 1.2 Assessment of the occurrence of chemicals that can harm water quality……………5 Figure 1.3 A graphical model of alternative stable states in shallow lakes……………….……..6 Figure 1.4 The Ohio River basins………………………………………………………………..8 Figure 1.5 Turbidity in urban areas………………………………………………………….…..12 Figure 1.6 Turbidity and TSS……………………………………………………………..……..14 Figure 1.6 Chemical structure of chlorophyll-a ………………………...…………………..…...15 Figure 2.1 Satellite view of Ohio river……………….………………………………………….18 Figure 2.2 Study Area…………………………………………………………………………....19 Figure 2.3 Red and green energy increase at a higher rate than blue energy in turbid waters with increasing sediments …………………………………………………………………………….24 Figure 2.4 Changes in the spectral signature of water with algae present (Frohn and Autrey, 2009)….….25 Figure 2.5 Linear regression plot of actual turbidity (NTU) vs. the Turbidity Index……….......29 Figure 2.6 Linear regression plot of actual chlorophyll-a vs. the chlorophyll-a index.………....30 Figure 3.1 Seasonal variation in turbidity and chlorophyll-a………………………………..…..33 Figure 3.2 A strong negative correlation is observed between Chlorophyll-a and turbidity …....35 Figure 3.3 Regression plot for chlorophyll-a (dependent variable) and turbidity…………..…...35 Figure 3.4 Annual variation of the turbidity index………………………………………....……37 viii LIST OF TABLES Table 2.1 Pearson Correlation coefficients between image parameters and five measurements of water quality collected in the field.……………………………………………..………….…….27 Table 3.1 Chlorophyll-a and turbidity indices for seasonal analysis………………………….....34 Table 3.2 Turbidity index for the annual analysis from the year 1999 - 2007…………...….…..36 ix Chapter 1 Introduction Water quality monitoring is extremely essential and plays a key role in the management of environmental planning. Conventional field methods for monitoring water quality are time consuming and do not provide coverage over large area. Previous studies have demonstrated the capability of remote sensing with in-situ sampling data for measurement of water variables [24] (Klemas et al., 1974). When the water quality data from satellite images are combined with the data obtained from field measurements, water quality trends can be studied during different times of the year. The spatial and temporal coverage of remote sensing is very beneficial for measuring various water quality parameters like turbidity and chlorophyll-a. These data can be obtained for various time periods during the year, resulting in valuable information on the variability of water quality. For remote sensing of water bodies, the concept of understanding the absorption and reflectance of sunlight in the water bodies is very essential. The absorption and scattering of incident radiation is studied to determine the water quality, when various organic and inorganic materials are present in the water. It is very important to select landsat scenes carefully and special attention is needed for the seasonal conditions to obtain the best images. 1 Advanced developments in the field of computer science have enabled the extensive use of Landsat imagery. The integration of Landsat imagery with geographic information system technology is one of the great ideas whose time has come [25] (Faust et al. 1991). This integration gives better result due to the fact that the data structure for landsat imagery and the raster-based GIS is same. There are much common functionality among raster operations and the image processing techniques. Landsat-TM’s each scene covers a 185 x 170 km area. Each scene comprises of all 7 bands and each band has a discrete frequency range of the electromagnetic spectrum from the visible to thermal. Each band is acquired by measuring energy from the earth’s surface in their frequency range of the electromagnetic spectrum. Color images are comprised of three bands which are associated to red, blue and green. Generally, the following combination of color images is recommended: Bands 1, 2 and 3: images in "true color", with good penetration in water, enhancing the streams, the turbidity and the sediments. The vegetation appears in greenish tonalities. Bands 2, 3 and 4: It better defines the limits between ground and water, still keeping some details in not so deep waters and showing the differences in the vegetation that appears in red tonalities. Bands 3, 4 and 5: It shows more clearly the limits between ground and water, with more differentiated vegetation appearing in tonalities of green and rose. 2 Bands 2, 4 and 7: It shows the vegetation in green tones and allows to discriminate the humidity both in the vegetation and the ground. Each image pixel of Landsat TM has a spatial resolution of 30 meters (i.e., it represents a 30 meters square in the ground), with exception of band 6, which has a spatial resolution of 120 meters. 1.1 Background and Literature Review 1.1.1 Water Quality Water is one of the most significant of all the natural resources available on earth. Nearly 75% of the earth’s surface is covered with water. Despite the large quantity of water surrounding the earth, only 0.015 of the total water on the earth’s surface is available for human use. Since, there is only a very small percentage of fresh water available and it is quintessential for sustaining life, water needs to be protected and monitored. The Clean Water Act and Water Quality: In 1972 the United States Congress passed the Federal Water Pollution Control Act - commonly called the Clean Water Act (CWA). The purpose of the law is to restore and maintain the "chemical, physical and biological integrity of the Nation’s waters". The goal of this law was to ensure:[1] 1. clean water in our streams, lakes, wetlands, estuaries, and other water bodies, 2. that fish and associated populations can flourish and that game fish are safe for human consumption (fishable), 3. that the Nation’s water are safe for recreation (swimmable). 3 The Unites States EPA has set up criteria for water quality.
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