WATER TABLE VARIABILITY ON THE PITTED KARST PLAIN, YUCATÁN, MEXICO
A thesis submitted To Kent State University in partial Fulfillment of the requirements for the Degree of Master of Arts
by
Jennifer Lynn Burrell December, 2011
Thesis written by Jennifer Lynn Burrell B.S., Kent State University, 2008 M.A., Kent State University, 2011
Approved By
______, Dr. Mandy Munro-Stasiuk, Advisor
______, Dr. Mandy Munro-Stasiuk, Chair, Department of Geography
______, Dr. John R. D. Stalvey, Associate Dean, College of Arts and Sciences
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TABLE OF CONTENTS
Page
LIST OF FIGURES…………………………………………………………………….. vii
LIST OF TABLES……………………………………………………………………… x
ACKNOWLEDGEMENTS…………………………………………………………….. xi
CHAPTER 1
INTRODUCTION …………………………………………………….….…...... 1
1.1 Introduction………………………………………………………...... 1
1.2 Characteristics of Study Area……………..…………….….……………... 4
1.2.1 Climate……………………………………………….………..….. 4
1.2.2 Geology and Topography…………………………….……...….... 6
CHAPTER 2
BACKGROUND AND PREVIOUS RESEARCH…………………...….....….. 10
2.1 Introduction………………………...... ……….... 10
2.2 Karst Topography and Processes……………………………………...... 10
2.2.1 Aquifer Dynamics and Regional Hydrology…………………..…..12
2.2.2 Affects of Faulting and Fracturing on Karst…………………...... 15
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2.2.3 Karstic Sinkholes…………………………………………………. 16
2.3 Sinkhole Classification on the Yucatán Peninsula………………………... 18
2.4 Human Adaptation and Use of Landscape………………………………... 19
CHAPTER 3
APPLICATION OF GPR TO A KARST LANDSCAPE…………………….... 22
3.1 Introduction………………………………………………………....…...... 22
3.2 Methods…………………………………………………...…………...... 24
3.2.1 Operational Issues and Errors…………………………...…...... 27
3.3 Results…………………………………………………………………...... 28
3.4 Summary………………………………………………………………...... 33
CHAPTER 4
WATER LEVEL FLUCTUATIONS IN A YUCATÁN CENOTE……..…...... 34
4.1 Introduction……………………………………………………………...... 34
4.2 Methods………………………………………………………………...... 35
4.3 Results…………………………………………………………………...... 38
4.3.1 Descriptive Water Logger Data Statistics………………………... 38
4.3.2 The Effects of Tropical Cyclones on Water Level………...….….. 39
4.3.3 Spikes and Cycles………………...……………………………..... 47
4.3.4 Daily Maximum and Minimum Depth………………………...... 48
4.4 Summary of Results……………………………………………………..… 50
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CHAPTER 5
SOIL MOISTURE AND PRECIPITATION………………………………...... 53
5.1 Introduction……………………………………………………………...... 53
5.2 Soil Moisture……………………………………………………….…...... 54
5.2.1 Methods…………………………………………………….…...... 54
5.2.2 Results………………………………………………………....….. 56
5.3 Precipitation…………………………………………………………...... 59
5.3.1 Methods………………………………………………………...... 59
5.3.2 Results………………………………………………………..….... 60
5.4 Summary…………………………………………………………………... 66
CHAPTER 6
DISCUSSION……………………………………………………………...….... 67
6.1 Introduction…………………………………………………………...... 67
6.2 GPR Analysis…………………………………………………………...... 67
6.3 Water Logger Analysis……………………………………………………. 68
6.4 Soil Moisture Analysis………………………………………………...... 72
6.5 Water Logger, Soil Moisture, and Precipitation Relationships…………… 74
6.5.1 Water Logger and Soil Moisture……………………………...... 74
6.6 Summary……………………………………………………………...... 78
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CHAPTER 7
CONCLUSION………………………………………………………………..... 79
7.1 Concluding Remarks……………………………………………………..... 79
7.2 Limitation of the Study………………………………………………...... 80
7.3 Suggestions for Future Work……………………………………….……... 81
REFERENCES……………………………………………………………………...... 83
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LIST OF FIGURES
Figure 1.1 Map of Mexico with Enlargement of Study Area…………………………... 3
Figure 1.2 Climate Classification for the Yucatán Peninsula………………………..…. 4
Figure 1.3 Average Annual Precipitation for the State of Yucatán…………………..… 5
Figure 1.4 Digital Elevation Model of Yucatán Peninsula……………………………... 6
Figure 1.5 Archaeological site of Xuenkal…………………………………………...... 8
Figure 1.6 Hacienda Kancaba………………………………………………………...... 8
Figure 1.7 Geological Impacts of Yucatán Peninsula from Chicxulub Impact Crater…. 9
Figure 2.1 Collapsed Banana Hole…………………………………………………...... 17
Figure 2.2 Cockpit Country, Jamaica…………………………………………...... 17
Figure 2.3 Sinkhole Classification……………………………………………………... 18
Figure 2.4 Example of Container Gardening in Yucatán…………………………..…... 20
Figure 2.5 Present Day Cultivated Rejollada…………………………………………... 21
Figure 3.1 GPR Configuration……………………………………………………...... … 23
Figure 3.2 Cenote Types……………………………………………………………...… 25
Figure 3.3 Hacienda Kancaba with Marked GPR Transect…………………………...... 25
Figure 3.4 Satellite Image of Archaeological Site Xuenkal……………………………. 26
Figure 3.5 GPR S-N Transect Through Rejollada 3…………………………………..... 29
Figure 3.6 GPR W-E Transect Through Rejollada 3………………………………...... 29
Figure 3.7 GPR Transects Through Rejollada 3………………………………………... 30
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Figure 3.8 GPR Transect of Cenote, 400 ns Time Window…………………………..... 32
Figure 3.9 GPR Transect of Cenote, 800 ns Time Window…………………………..... 32
Figure 4.1 HOBO Water Level Logger………………………………………………… 35
Figure 4.2 Installed HOBO Water Level Logger…………………………………...... 36
Figure 4.3 Water Level Data with Anomalous Spike…………………………………... 37
Figure 4.4 Average Daily Sensor Depth for Study Period………...……………………. 39
Figure 4.5 Precipitation Map, June 21, 2010…………………………………………….40
Figure 4.6 Precipitation Map, September 16, 2010…………………………………...... 40
Figure 4.7 Precipitation Map, October 13, 2010……………………………………….. 41
Figure 4.8 Radar Images of Tropical Cyclone Alex…………………………………..... 42
Figure 4.9 Radar Image of Tropical Cyclone Karl………………………………....…... 42
Figure 4.10 Water Logger Response to Tropical Cyclones Alex, Karl, and Paula…...... 44
Figure 4.11 Water Level Response to Precipitation Events A, B, C, and D………...... 46
Figure 4.12 Periodogram of Water Logger Dataset…………………………………….. 47
Figure 4.13 Distribution of Daily Maxima and Minima………………………………... 48
Figure 4.14 Occurrence Distribution of Maximum Sensor Depth..………….……...... 49
Figure 4.15 Occurrence Distribution of Minimum Sensor Depth………...…………..... 49
Figure 5.1 Satellite Image of Rejollada 3…………...………………………………….. 55
Figure 5.2 Microclimate Station Setup……...... …………….………………….…….. 55
Figure 5.3 Soil Moisture Content……………………………………………………...... 57
Figure 5.4 Daily Soil Moisture Averages………………………………………………. 57
Figure 5.5 Soil Moisture Content from Tropical Cyclones Alex, Karl, and Paula...... 58
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Figure 5.6 Soil Moisture Response to Precipitation Events A, B, C, and D…….…….... 59
Figure 5.7 Valladolid in Relationship to Espita……………………………………….... 60
Figure 5.8 Total Daily Precipitation, Valladolid……………………………………….. 62
Figure 5.9 Monthly Averaged Precipitation, Valladolid…………………………….…. 62
Figure 5.10 Valladolid Precipitation During Tropical Cyclone Alex……………...... 63
Figure 5.11 Precipitation Map, June 27, 2010…………………………………...... …. 64
Figure 5.12 Precipitation Map, June 28, 2010………………………………………….. 64
Figure 5.13 Valladolid Precipitation During Tropical Cyclones Karl and Paula…….… 65
Figure 6.1 Precipitation Events A, B, C, and D and Water Logger Response…………. 71
Figure 6.2 Precipitation Events A, B, C, and D and Soil Moisture Response…...... 73
Figure 6.3 Water Level and Soil Moisture Response to Precipitation Event D………... 75
Figure 6.4 Water Logger Dataset with Trend Line……………………………...... ….. 77
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LIST OF TABLES
Table 1 Soil Moisture and Sensor Depth Correlation……………………………….….. 74
Table 2 Sensor Depth, Soil Moisture, and Precipitation Correlation……………….….. 77
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ACKNOWLEDGEMENTS
Completion of this thesis is the result of a determined, stubborn little girl finding her voice and path in life. I had expected no less from myself and this expectation fueled me to continue. I would like to thank God for giving me the strength, and at the eleventh hour, patience to complete this. Without that I may have given in and given up.
For my parents, who unfortunately had to be there for all of the lows that accompanied so many of the highs. Thank you for an ear to listen, a shoulder to cry on, and that voice in my head that wouldn‟t let me give up.
To my advisor Dr. Mandy Munro-Stasiuk, thank you for creating a project that appealed to all of my interests and for guiding me through these unknown waters. Thank you to my other committee members Dr. Scott Sheridan and Dr. Kam Manahan.
Dr. Scott Sheridan, thank you for going above and beyond to help me when I asked for it and for all of your patience.
This has been an experience and an adventure, thank you.
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CHAPTER 1
INTRODUCTION
1.1 Introduction
Currently, knowledge of karstic groundwater characteristics on the northern
Yucatán Peninsula, Mexico is poor. Because of the presence of karst landscape and variable weather conditions in a hot climate, the geohydrology of the region has the potential to be complex. First, the study area is only between 10 and 28 m above sea level. This means that the ground water table is relatively close to the ground surface and therefore extremely vulnerable to contamination. Also low-lying terrains near the ocean allow water table interaction with the surrounding ocean sometimes resulting in mixing and contamination of the freshwater supply for the region (e.g. Beddows, 2004). Second, daily and seasonal weather and rainfall patterns can have profound effects on the groundwater system (Sánchez-Pinto et al., 2005). This is particularly noticeable in tropical regions, like Yucatán, Mexico, due to the volume and intensity of rainfall at certain times of the year, as well as the preponderance of warm temperatures which accelerate denudation (Corbel, 1959, in Ford and Williams, 2007). Third, vegetation distribution and density strongly affect the infiltration rate of any surface water (Ford and
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Williams, 2007). Finally, the extreme permeability and solubility of the bedrock results in the complete lack of surface water (Gelting, 1995). The purpose of this research is to determine the impact of localized precipitation events on the water table, using the case study of a small cenote at Hacienda Kancaba as well as a sinkhole at Xuenkal. Both sites are near Espita, Yucatán, Mexico (Figure 1.1). Specifically this study asks and addresses the following questions:
1. Does the water table surface configuration change relative to the surface
geomorphology, specifically sinkholes?
2. Do local water levels variability and local soil moisture variability?; And,
3. Is there a relationship between local water table fluctuations and atmospheric
pressure and rainfall patterns?
These research questions are addressed via analysis of ground penetrating radar data and through statistical comparisons of water level data from one cenote at Hacienda
Kancaba, hydroclimatological data collected from one sinkhole at the archaeological site of Xuenkal, and regional weather data collected via the National Climatic Data Center
(NCDC).
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Figure 1.1 Map of Yucatán with enlargement of study area (image Google Earth).
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1.2 Characteristics of the Study Area
1.2.1 Climate
The Northern Yucatán Peninsula is classified as Tropical Savanna (Köppen Aw)
(Figure 1.2) with annual temperatures averaging 25°C (77°F). With a long dry season, the area is dominated by subtropical high pressure that is followed by a short wet season that occurs between June and October. This is when moisture laden air from the Gulf of
Mexico moves ashore bringing rains with it (Munro-Stasiuk & Manahan, 2010).
Precipitation averages about 1100 mm a year for north central Yucatán (SARH, 1989)
(Figure 1.3), with the majority of this occurring during the wet season. Precipitation is higher for the southern part of the peninsula with decreasing trends towards the north
(Gelting, 1995). The northwestern coast experiences the lowest volumes of precipitation
Figure 1.2 Climate classification for the Yucatán Peninsula (Board of Regents, The University of Texas System, 1975)
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Figure 1.3 Average annual precipitation for the state of Yucatán (González-Herrera et al., 2002) for the peninsula (Gelting, 1995). Potential evapotranspiration rates found for the peninsula by Bauer-Gottwein et al. (2011) ranged from 850 to 1,600 mm/year and displayed a gradient of NW-SE with the highest amounts also in the northwest. Gondwe et al. (2010) found actual evapotranspiration rates for the peninsula to be between 937 and 995 mm/year. Although the Yucatán Peninsula receives precipitation and has high levels of humidity, the majority of the region is lacking surface water or streams due to the local geology, topography, and atmospheric conditions.
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1.2.2 Geology and Topography
The Yucatán Peninsula is a Tertiary age limestone platform (Weidie, 1985) that is divided into two different terrains; the flat, low-lying northern section and the hilly southern section (Figure 1.4). A low dip angle towards the north is due to the Ticul fault located in the southwestern section of the peninsula. The fault roughly trends WNW to
ESE and separates the uplifted Sierrita de Ticul southern section of the peninsula from the Northern Pitted Karst Plain (Figure 1.4). The Northern Pitted Karst Plain is nearly flat with surface elevation averaging 15 m above mean sea level (Escolero et al., 2005) and is composed of hard limestone that formed from the solution and
Figure 1.4 Digital Elevation Model of northern Yucatán Peninsula showing major physiographic regions and locations of ancient Maya sites ( Munro- Stasiuk and Manahan, 2010).
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precipitation of calcium carbonate (González-Herrera et al., 2002). The Southern Hilly
Karst Plain has elevations up to 150 m above sea level (Escolero et al., 2005). The field sites of Xuenkal and Hacienda Kancaba (Figure 1.5 and 1.6), located 8 km west and 4 km north of the modern town of Espita, Yucatán, respectively, are in the flat northern lowlands. This landscape is characterized by thousands of sinkholes and virtually no surface water. The lack of surface water is the result of high infiltration rates on the peninsula due to the underlying fractured limestone. The limestone of the northern
Yucatán Peninsula is deposited on a highly fractured surface as the result of an asteroid impact that occurred 65 million years ago that formed what has become known as the
Chicxulub impact crater (Figure 1.7) (Penfield & Camargo, 1981, in Pope et al., 1993).
When uplift of the Yucatán Peninsula occurred, normal faults formed in the overlying limestone over the crater rim and extensive fracturing occurred over much of the landscape (Figure 1.7) (Pope et al., 1993). The normal faults along the rim created a ring fault. This fault forced the groundwater to move along the crater rim creating a ring of caves and caverns which ultimately resulted in the formation of the well-known “Ring of
Cenotes”. This fracturing and faulting has shaped the cavern systems as well as the surface geomorphology. Together, these features create established conduits that direct groundwater that enhances further fracturing of the landscape.
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Figure 1.5 Archaeological site of Xuenkal and marked Rejolladas 1 & 3 (Google Earth)
Figure 1.6 Hacienda Kancaba (Google Earth)
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Figure 1.7 Major geology and Ring of Cenotes and fractures resulting from the Chicxulub impact (Pope et al., 1993)
CHAPTER 2
BACKGROUND AND PREVIOUS RESEARCH
2.1 Introduction
Though extensive research exists to explain processes of water table variability along Caribbean karst coastlines (e.g. Beddows, 2004; Moore et al., 1992; Mylorie et al.,
2003) few studies (e.g. Bauer-Gottwein et al., 2011) have been focused on aquifer and water table dynamics of the inland Yucatán Peninsula. Literature that addresses these dynamics in Yucatán is concentrated mostly in the northwest part of the peninsula because that is where the capital of the state, Mérida, is located (e.g. Escolero et al., 2007;
Sánchez-Pinto et al., 2005; Marin et al., 2000; Pacheco & Cabrera, 1997). This chapter discusses the relevant background and literature for this research which will help understand processes near Espita, Yucatán, Mexico. This includes: karst geomorphology, aquifer dynamics, fracturing, and human adaptation to the Yucatán Peninsula.
2.2 Karst Topography and Processes
Karst topography is defined in introductory textbooks as “…an area with many sinkholes and a cave system beneath the land surface … usually lacking a surface stream”
(Plummer 2005, 279). The bedrock type is usually highly soluble and porous carbonate- dominated which allows for quick percolation of surface water into the underlying rock.
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This results in a lack of surface streams, which is a major characteristic of karst areas.
Infiltrated water saturates the bedrock and the water flows through porous rock and/or bedrock caverns. This flow erodes weak areas in rock, creating conduits, caves, and often results in complete collapse of cave roofs to form sinkholes at the land surface
(Mylroie and Carew, 2003).
There are three types of karst: temperate, tropical, and Caribbean (De Blij et al.,
2004). Small solution depressions, extensive cave networks, and disappearing streams characterize temperate karst. Tropical karst forms faster and is usually characterized by vegetated, steep-sided hills and larger solution depressions. Caribbean karst is associated with flat-lying limestones dominated by sinkholes (De Blij et al., 2004) and is the rarest of the three types. The warm low-lying area of the Yucatán Peninsula and the karst that composes the peninsula is a great example of the description provided by Esteban (1991) of karst for his Caribbean karst model. The Caribbean karst model describes karst as being affected by minor tectonics, shallow burial of carbonates, and is restricted to tropical or semi-arid locations along with area-based mineralogy of the carbonate rocks.
This general description matches the geology of the region. For this study, the term
Caribbean karst as described by De Blij (2004) will be used to refer to the karst of the
Yucatán Peninsula. The peninsula, approximately 300,000 km2, is a limestone platform formed from the solution and precipitation of calcium carbonate which then cemented shell fragments and loose grains into a hardened layer of rock (Bauer-Gottwein et al.,
2011; González-Herrera et al., 2002; Lesser & Weidie, 1988). Uplift of the Yucatán
Peninsula exposed this rock and the landscape is now characterized by thousands of
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sinkholes that occur in varying densities overlaying the karstic aquifer (Munro-Stasiuk &
Manahan, 2010). Sinkholes are prevalent due to weathering of the limestone which is exacerbated by the high permeability of the rock allowing for rapid infiltration of precipitation (Gelting, 1995).
2.2.1 Aquifer Dynamics and Regional Hydrology
Karstic aquifers provide storage for freshwater and the local geology controls how the water flows through the area. If near the coastline, and the water table intersects sea level, tides can affect how far saltwater intrudes inland (Ataie-Ashtiani, 1999). This intrusion can have effects on the vertical placement of the freshwater lens in the aquifer.
The saltwater intrusion has been found as far as 90 km inland (Steinich and Marin, 1996).
The thickness of the freshwater lens has been found to increase as you move east across the peninsula. Northwest Yucatán along the coast has a freshwater lens thickness of 15 m, 45 m at Mérida, Yucatán, and about 120 m 90 km inland from the west coast (Steinch and Marin, 1996; Steinich and Marin, 1997). The shape of the shoreline can also affect the placement of the saltwater intrusion (Ataie-Ashtiani, 1999).
Groundwater flow in the peninsula has not been clearly defined. Flow in the northwest region has been found to flow southeast to northwest as well as north to south, to the south of Mérida (Steinich and Marin, 1996; Steinich and Marin, 1997; Marin et al.,
2000; Villasuso Pino et al., 2011). Flow direction along the eastern portion appears to be towards the coast (Moore et al., 1992; Beddows, 2004). Back and Hanshaw (1970),
González-Herrera et al. (2002), and Sanchez-Pinto et al. (2005) discuss overall flow
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across the Peninsula as starting from the Sierrita de Ticul and flowing towards the north/northeast towards the coast. Although literature discussing flow direction of the interior of the peninsula is lacking, other literature has demonstrated a difference in direction between the northwestern region and the eastern region.
Most studies of karstic aquifers have concentrated on areas at or near the coast or completely inland where they are unaffected by the coast. As demonstrated above, there appears to be few studies demonstrating the overall karstic aquifer behavior from inland to the coast. Beddows (2004) started to address a connection between coast and inland aquifer dynamics by studying the flow of conduits of the aquifer, along the Caribbean coast of the Yucatán Peninsula. She believed these can explain the changing behavior of the aquifer. White (2003) recognized that the conduits as well as the surrounding rock matrix need to be accounted for as both significantly affect how the aquifer works.
Serfes (1991) noted that tide fluctuations produce pressure waves that are detected throughout adjacent aquifers. Conduits provide the connection between the coast and the inland. Gelting (1995) noted that water in Yucatán not only infiltrated quickly, but also flows through interconnected solution channels and fractures that eventually connected to the coast where the groundwater discharged. Gelting (1995) also noted that other types of aquifers do not behave like this for they need a built up of pressure to drive the water through the pore spaces. However, the Yucatán Peninsula is unique because the rock matrix allows for rapid flow throughout the aquifer. The unfortunate side effect of this is that a low pressure head relates to a lower storage capacity of the aquifer which results in
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a thinner freshwater lens (Gelting, 1995). The aquifer is essentially too efficient in transporting and discharging groundwater. .
Limestone, like that of Florida and Caribbean islands, which is generally younger and often has very high rock matrix permeability (White, 2003) allows water to infiltrate the ground quickly. In an overview of groundwater recharge, De Vries and Simmers
(2002) discuss three types of recharge: direct, indirect, and localized recharge. These types are dependent upon interactions between climate, local geology, soil type, and vegetation cover. They state that a poorly vegetated, permeable surface, and near-surface porous bedrock combined with high-intensity rainfall make for favorable recharge conditions. The Yucatán Peninsula under these criteria can be considered as having recharge favorable conditions and therefore high infiltration rates. Rapid rates of infiltration make an aquifer susceptible to contamination (Marin and Perry, 1994;
Pacheco & Cabrera, 1997; Pacheco et al., 2001) from expanding urban centers or from pesticides and fertilizers used in farming. Pacheco and Cabrera (1997) found that contamination rates on the northern Yucatán Peninsula are usually highest during the rainy season due to high infiltration rates. However, later, Pacheco et al. (2001) found that contamination was lowest during the rainy season due to the dilution of contaminates. They were studying nitrate concentrations in both studies. These two studies demonstrate how difficult this region is to understand in terms of contamination potential and contaminant transport. Understanding groundwater flow through a karstic aquifer allows for mitigation measures against possible contamination of the freshwater supply.
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2.2.2 Affects of Faulting and Fracturing on Karst
A slight elevation change in a landscape can be enough to provide a gradient that will allow water to flow through karst with a higher velocity. Typically this occurs as a result of uplift or folding. Uplift usually results in faulting which in turn results in complex barriers to water flow. In a karst landscape that means there are new concentrated opportunities for karst features to develop along paths of water flow. Bense et al. (2003) points out that faults can completely alter an area‟s hydrogeology. For example, Pope et al. (1993) noted that the crater rim of the Chicxulub impact on the
Yucatán Peninsula, which is a ring fault, acts as a barrier to groundwater flow. Rather than crossing the fault, groundwater flow concentrates along the fault, enhancing karstic processes. This has resulted in the formation of the famous Ring of Cenotes (Pope et al.,
1993) - sinkholes with standing water - which formed due to roof collapse along the fault.
This major ring fault also partially affects the current study area which is to the east of the crater. Due to instabilities associated with the ring fault, the limestone is pervasively fractured (Lesser & Weidie, 1988), resulting in the formation of thousands of sinkholes, many of them dry, that often align themselves with regional joint trends in the bedrock
(Munro-Stasiuk & Manahan, 2010). The fractures are linear weaknesses in bedrock that facilitate water flow. Siemers and Dreybrodt (1998) noted that fractures are the first paths that water chooses, and they can be widened and deepened into much larger conduits. Since these fractures help direct flow, sinkholes and cave systems usually tend to develop along them (Pope et al., 1993) Lesser and Weidie (1988) also noted that the
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central region of the Yucatán Peninsula is pervasively fractured which permits rapid infiltration of groundwater further demonstrating fractures as being the preferential paths.
2.2.3 Karstic Sinkholes
Sinkholes are formed from water eroding away enough limestone in subterranean caverns that the roofs of the caverns can collapse, especially if the caverns become devoid of water which tends to have a buoyant affect on the roofs, thus preventing collapse (Ford & Williams, 2007). This results in a depression (sinkhole) at the land surface. A sinkhole then becomes a part of the overall subsurface system since it is a place of aquifer recharge (Salvati & Sasowsky, 2002). Sinkholes can be filled with water or can be filled with soil. This all depends on the relationship of the water table with the sinkhole. Regional names exist for sinkholes across the world with each describing a particular kind of sinkhole (for example see sinkhole classification scheme for the
Yucatán Peninsula below). Such variations are cenotes from Yucatán, banana holes from the Bahamas (Figure 2.1) (Harris, 1995; Mylroie and Carew, 2003), and cockpits from
Jamaica (Figure 2.2) (Field, 2002).
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Figure 2.1 A collapsed Banana Hole, Bahamas (Karst Waters Institute)
Figure 2.2 Cockpit country, Jamaica (Jamaica Forestry Department, IKONOS images)
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2.3 Sinkhole Classification on the Yucatán Peninsula
In Yucatán, sinkholes have an indigenous classification based on where the bases are relative to the water table. There are three types: cenotes, rejolladas, and dzadzob
(Figure 2.3). Cenotes have standing water year-round due to exposure of the water table
(Munro-Stasiuk & Manahan, 2010). Rejolladas do not intersect the water table, but rather sit just above it and are thus dry and collect soil. Previous work at the study site has shown that Yucatán sinkholes remain replete with lush vegetation during the dry season while the surrounding terrain becomes completely defoliated (Munro-Stasiuk &
Manahan, 2010). This was tied to the thick soils in the base of the sinkholes as well as access of tree roots directly to the water table. Dzadzob are situated in the middle of the spectrum of Yucatán sinkholes. These collapses simply touch the water table and tend to develop swampy areas at their bases (Houck, 2006; Munro-Stasiuk & Manahan, 2010).
Figure 2.3 Sinkhole classification form Munro-Stasiuk et al., (2011)
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2.4 Human Adaptation and Use of Landscape
Sinkholes in Yucatán have been used to tap into the water table to provide irrigation both by ancient and modern inhabitants (Fedick & Morrison, 2004). Ancient
Maya settlements often clustered around sinkholes and, therefore, past and present populations have recognized that the sinkholes were their way of accessing water. This was shown when the Spanish conquistadors invaded the Yucatán Peninsula in 1517. The
Maya would flee into the hills to escape them, but before doing so they would burn their villages and fill their wells with stones knowing the conquistadors were desperate for water and were not used to a landscape lacking surface water (Back, 1995). The conquistadors were slowed down when they had to stop to clear out and reestablish the wells.
Due to lack of water and the harsh, dry climate, soil is scarce, especially nutrient-rich soil. So, Maya would transport soil from areas of accumulation, such as rejolladas, to their plots of land in order to grow crops (Back, 1994). They would also cultivate small soil pockets found in the bedrock. The depressions in the bedrock (Figure 2.4) were used as “container gardening” according to Fedick et al. (2008). The bedrock would hold onto soil as well as moisture allowing plants and trees to grow. Rejolladas were also cultivated if near a settlement and this still occurs today. In Espita and Xuenkal many rejolladas are cultivated and planted with important fruit crops (Figure 2.5) (Arden,
2007). The Ancient Maya also utilized caves by building ladders so they could reach the deep water levels and bring the water to the surface by using clay jars (Back, 1995).
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Figure 2.4 Examples of bedrock solution depressions used for container gardening (Fedick et al., 2008)
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Figure 2.5 A present day cultivated rejollada near Epsita, Mexico (Ardren, 2007)
CHAPTER 3
APPLICATION OF GPR TO A KARST LANDSCAPE
3.1 Introduction
The environmental applications of ground penetrating radar (GPR) are extensive.
GPR has been used to examine sorted sediments (e.g. Froese et al., 2005; Moore et al.,
2004), glacier thickness, structure, and bed configuration (e.g. Moorman and Michel,
2000), the structure of karst terrain (e.g. Chamberlain et al., 2000), water table configuration (e.g. Doolittle et al., 2006; Turesson, 2006), and soil water content
(Huisman et al., 2001). GPR has also been used extensively in the archeological community where it has successfully detected buried structures (Sternberg and McGill,
1995; Hruska and Fuchs, 1999; Leckebusch, 2003) and urns (Cezar et al., 2001).
GPR cannot directly photograph the subsurface, rather it images the reflected radar signals. It operates similarly to continuous seismic-reflection profiling, which has been successfully used to study aquifers (Beres Jr. and Haeni, 1991). In terms of karstic landscapes, Al-fares et al. (2002) found GPR was successful in imaging shallow features such as bedding planes as well as caves and conduits. Chamberlain et al. (2000) found
GPR was successful in investigating subsurface structures in limestone which they confirmed by borehole data from their study area.
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GPR operates by emitting radio waves into the ground by a transmitter. A receiver, which is in a fixed geometry to the transmitter (Figure 3.1), receives the reflections from the subsurface. These reflections become the “images” of the subsurface.
Although GPR has variable results when used to locate water tables, the goal was to determine if GPR could be a noninvasive method as well as a cost effective way to locate the water table near Espita, Mexico.
Figure 3.1 GPR configuration (Image M. Munro-Stasiuk). In this case one person is operating the data collector, one is moving the transmitter, and one is moving the receiver. Transmitter and receiver are moved 50 cm every measurement and kept 2 m apart.
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3.2 Methods
PulseEkko Pro GPR was used in two sinkhole environments: rejolladas and the ground surface above a cenote. It should be noted that although cenotes are usually seen and described as open sinkholes that have exposed the water table, the cenote used in this study is not the stereotypical cenote which would normally have vertical walls with water exposed at the bottom. Rather, it is comparable to a cave in the Hall (1936) classification
(Figure 3.2). A cave-shaped cenote is described as having one entrance that is horizontal.
GPR survey lines were run over two rejolladas located at the Xuenkal archaeological site as well as over the cenote located at Hacienda Kancaba (Figure 3.3).
The rejolladas at Xuenkal have been designated as Rejollada 1 (R1) and Rejollada 3 (R3)
(Figure 3.4). This designation arises from previous and current work being done in the study area by multiple researchers.
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Figure 3.2 Schematic of the four cenote types from Hall (1936). D type is shape of cenote used in this study.
Figure 3.3 Hacienda Kancaba with labeled GPR transects (Image from Google Earth)
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Figure 3.4 Satellite image of Xuenkal showing locations of Rejollada 1 and 3 (Munro-Stasiuk et al., 2011)
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Two lines were run inside Rejollada 1, one trending north-south and the other trending east-west. The lines intersected in the center of the rejollada. 50 MHz antennas were used. Standard recommended spacing of 2 m between the transmitter and receiver were used, along with a step size (distance moved between measurements) of 50 cm for both lines. Thus a single pulse of radar was transmitted into the ground each time the system was moved, and a single trace of reflection data was generated. These traces, when displayed next to each other, create the reflection profiles.
Two lines were also run in Rejollada 3 using the same set-up as described above.
Rejollada 3 is also the location of four microclimate weather stations that were installed along a north-south line (see Chapter 5).
The GPR run at Hacienda Kancaba consisted of two survey lines that used a 50
MHz antenna. The time window was changed from 400 to 800 ns. This allows greater depth of penetration of the signal, or rather reflections from deeper targets have more time to be recorded.
GPR reflection data was analyzed using PulseEkko Pro GPR software. This software compiled the data into a reflection profile. Different filtering and processing techniques were used on the profiles to establish the best display of the data.
3.2.1 Operational Issues and Errors
There were errors in data gathering that come from the system itself and from setup of the equipment. The GPR system contains self-generated signals after the transmitted signal. The ground response is usually hidden and can be disregarded.
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Sometimes the system residual response is subtracted in an attempt to improve the received signal if it can be estimated (Jol, 2009). The equipment itself carries electrical currents since the antennas are connected to batteries with cables. This current can interfere with data collection although this did not appear to be the case for this study.
Another error that cannot be quantified is maintenance of antenna distance and ensuring antennae contact with the ground. This was a persistent problem during this study. At times, the antennas were not moved equal distances creating a slightly skewed transect. This was in part due to terrain interference, but at other times it was the product of human error in placing the antennas. If the antennas are not placed fully on the ground due to roots, brush, or timing of placement and firing of transmitter, the antennas end up directing more of the signal upward into the air therefore reducing antenna efficiency
(Jol, 2009). This problem therefore may have resulted in a muting of the signals presented in this study.
3.3 Results
GPR proved effective at imaging the ground however it was unable to detect the water table with certainty. After changing the setting on the unit, using a dewow filter, and applying an AGC (Automatic Gain Control) to the data during processing, the GPR still failed to show, at least in any discernable way, the water table (Figures 3.5 and 3.6 ).
The AGC enhances weak signals at depth, but yet the water table was still not detected.
During data collection in Rejollada 1, equipment malfunctions resulted in unusable data.
However Rejollada 3 data was good. R3 data was compared to R3 data acquired by
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Munro-Stasiuk & Manahan (2010) which used 100 and 200 MHz antennas, and the same processing, and although differing antenna strengths were used, it still failed to detect the water table (Figure 3.7). Limestone composes the base of the rejolladas with soils accumulating in the depressions. The thickness of this accumulation prevented the GPR signal from penetrating through to bedrock, since soil typically absorbs the transmitting wave. On some images there are some flat, more noticeable single reflectors at depth.
However, they are far from obvious as the water table and without borehole data, the water table could not be definitively identified.
Figure 3.5 GPR south-north transect through Rejollada 3
Figure 3.6 GPR west-east transect through Rejollada 3
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Figure 3.7 GPR transects at Rejollada 3 (Munro-Stasiuk & Manahan (2010)
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Results from the cenote also failed to show the water table even with the change in the time window. There is a possible reflection that may represent the water table at about 8 m depth on the transect (Figures 3.8 and 3.9). Although it was thought that the cenote GPR transects would demonstrate the water table well, this was not the case. Also, spatially, this reflector appears to be isolated adding to the level of uncertainty in terms of identification. It is likely that along part of the transect the signal was lost in the underlying cavern and therefore could not reach the water and return the signal.
Thick Soil
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Figure 3.8 GPR transect of cenote using 400 ns time window
Figure 3.9 GPR transect of cenote using 800 ns time window
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3.4 Summary
GPR can be a very useful tool, but it has to be used in the right conditions. The combination of thick soils, fine-grained bedrock, and vegetative cover caused GPR to not be successful in this study. The signal was lost to air when the antennas were not in direct contact with ground due to vegetative debris or when passing through the cenote cavern. The signal was also absorbed in the thick soils of the rejolladas. However, with better vegetation clearing of transect lines and verifying depth to the water table in the study area could allow greater success in the operation of GPR. Verification of the depth of the water table to test the accuracy of the GPR proved useful for Estrada-Medina et al.
(2010). They ran GPR in a quarry with a known depth of 1 m to the underlying aquifer.
Knowing the depth and that the aquifer was so close to the surface allowed them to verify the GPR results. GPR has not been refined to the point of being able to pinpoint features in all terrains or situations.
CHAPTER 4
WATER LEVEL FLUCTUATIONS IN A YUCATÁN CENOTE
4.1 Introduction
Water level fluctuations on the Yucatán Peninsula have the potential to disrupt the local water supply. This study was conducted to investigate fluctuations occurring in the aquifer system of Espita, Yucatán by installing a water level logger to see if an overall fluctuation could be detected. If an overall change, no matter the source, was occurring then this could shed light on hydrogeologic flow and water supply to the region. Studies have shown that saltwater intrudes into unconfined aquifers, like the Yucatán aquifer
(e.g. Ataie-Ashtiani et al., 1999; Back, 1995; Bauer-Gottwein et al., 2011; Beddows,
2004; Steinich & Marin, 1996). Some studies have found that saltwater can intrude as far as 90 km inland (Steinich & Marin, 1996). Saltwater intrusions create fluctuations in the water as well as make the aquifer more vulnerable to contamination (Marin and Perry,
1994). Espita is too far inland to be affected by intrusions from the west or east of the peninsula; however it is about 65 km from the north coast. This means that Espita‟s water table may experience fluctuations due to saltwater intrusion. If a change in water level is detected in this study, then the next step would be to determine if saltwater intrusion is the possible source of the fluctuating water level or if this effect is insignificant to the overall system of Espita. Other sources are also explored as the causal mechanisms for fluctuations. 34
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4.2 Methods
A HOBO Water Level Logger (Onset Computer Corporation) was installed in the cenote at Kancaba to monitor water levels (Figure 4.1 and 4.2). The gauge is a pressure based device that takes readings every 30 minutes. An average standard atmospheric pressure of 1014 hPa was used to derive the absolute sensor depth in meters during processing using HOBOware software. 1014 hPa was based on Soler-Bientz et al. (2009) findings for Mérida, Yucatán, which is close in latitude to Espita. The logger was placed
80 cm below the water surface. The height of the water table in the area is about 2-4 m above sea level (González-Herrera et al., 2002; Gondwe et al., 2010; Lesser & Weidie,
1988).
Figure 4.1 HOBO water level logger installed in cenote (Image Onset Computer Corporation)
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Figure 4.2 Installed HOBO water level logger (red circle)
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Sensor depth was recorded April 4, 2010 - March 8, 2011. However, anomalous readings were generated early May 2010 through June 16, 2010 (Figure 4.3). This spike appears to be uncharacteristic of the dataset. Above normal sensor depths were recorded during this period. It was later determined that the water level logger had been removed from the cenote, and while still attached to its mooring, it was laying on a wall adjacent to the cenote out of water. It was placed back into the water early June 2010. Due to the uncertainty of time out of water and the corresponding anomaly, April 4, 2010 – June 16,
2010 has been removed from the dataset and ignored in all subsequent analyses.
Figure 4.3 Water level data not normalized. Red circle indicates anomalous spike.
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Water logger data was imported into Microsoft Excel for processing. Data were averaged for easier analysis and comparison. A 24-hour average better reflected daily change in the water table and therefore the change from day-to-day was calculated. Daily maximum and minimum depths of the sensor were extracted as well as monthly averages calculated. A distribution of the time at which these depths occurred was derived and plotted using Microsoft Excel. A spectral analysis was run on the complete dataset as well as the daily maximum and minimum to discern whether cyclic patterns exist in the data. The spectral analysis and plots were executed in R software package.
4.3 Results
4.3.1 Descriptive Water Logger Data Statistics
The water logger averaged a depth of 0.9220 m and ranged from 0.569 m to 1.142 m for the study period of June 17, 2010 – March 8, 2011. Sensor depth is the proxy for water fluctuations therefore there was a total annual change of 0.573 meters (Figure 4.4).
The sensor registers a change when pressures change in the water; as water levels rise the sensor sits at a greater depth and is subjected to higher pressure. The converse is true when water levels go down. An average daily reading for the study period was 0.9227 m.
The day-to-day difference averaged 0.0036 m.
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Figure 4.4 Average daily sensor depth for study period
4.3.2 The Effects of Tropical Cyclones on Water Level
The Yucatán peninsula is susceptible to tropical cyclones. After analyzing the
2010 hurricane season through regional precipitation maps provided by Mexico‟s
National Meteorological Service (Figure 4.5, 4.6, & 4.7), analysis of precipitation data from Valladolid and soil moisture data, as well as radar images from NASA of two of the tropical cyclones (Figure 4.8 & 4.9), three named tropical cyclones were determined to have affected the peninsula. Two passed over the peninsula and one passed to the east of the peninsula in the Yucatán Channel. The named storms and the dates they affected the peninsula are: Alex (June 27-28), Karl (September 15-16), and Paula (October 13).
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Figure 4.5 Precipitation map June 21, 2010 for tropical cyclone Alex (CONAGUA)
Figure 4.6 Precipitation map for September 16, 2010 for tropical cyclone Karl (CONAGUA)
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Figure 4.7 Precipitation map for October 13, 2010 for tropical cyclone Paula (CONAGUA)
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Figure 4.8 Radar images of tropical cyclone Alex (Image NASA Goddard / MODIS Rapid Response Team)
Figure 4.9 Radar image of tropical cyclone Karl (Image NOAA/NASA GOES Project)
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The data were analyzed closer during storm times to see if the cenote level suggested a rapid recharge rate (Figure 4.10). This would conclusively show that there was a connection between the groundwater system and atmospheric moisture since these were known time-constrained precipitation events. Using 24-hr average, a time period of seven days, starting with the day the tropical cyclone made landfall, was analyzed. Water level in general did rise with each one. During Alex, water level dropped at first, but began rising after the second day. Water level with Karl rose, dropped the second day out from landfall, but rebounded with increases over the next couple of days. With Paula, the most rapid response in water level was seen. Paula rose 0.023 m in the first day.
Although the area received rainfall, the cenote did not respond with a sharp rise in water level to the influx of precipitation suggesting a rapid or instantaneous response is not present.
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Figure 4.10 Water logger readings during the 3 named tropical cyclones. Data not normalized.
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During analysis of tropical cyclone precipitation effects, it was realized that there were other precipitation events that occurred that were of greater magnitude than the three chosen tropical cyclones. Therefore, four other precipitation events (designated
Event A, Event B, Event C, and Event D) were analyzed using daily average sensor depth for one week starting on the day of the precipitation event. Similar patterns were seen with these events, as were seen with the tropical cyclones, however, increases in water level were more uniform in the precipitation events than with the tropical cyclones
(Figure 4.11). Tropical cyclone events showed more variability in response to an influx of precipitation. Tropical cyclone and precipitation events suggest there is a lag present for both did not reach peak readings until the second or third day. These results are significant as they suggest there is little connection between precipitation patterns and instantaneous water level fluctuations, and that the hydrodynamics are more internally than externally driven.
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Figure 4.11 Water level response to precipitation events A, B, C, and D
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4.3.3 Spikes and Cycles
The water logger data appears visually to have a cyclic pattern (Figure 4.12). A spectral analysis was performed to see if indeed there was a discernable pattern to the data. Peaks occurred at 16, 11, 7, 6, and 5 days as well as 24 hr and 12 hr. The 24 hr and
12 hr cycle represents diurnal variation (A) and tidal fluctuations (B), respectively. The other peaks‟ sources are unclear. These may be inherent fluctuations within the aquifer system.
Figure 4.12 Periodogram of water logger dataset. (A) Diurnal cycle (B) Tidal cycle
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4.3.4 Daily Maximum and Minimum Depth
Daily maximum and minimum depth were also analyzed. Through the study period the maxima and minima noticeably occurred at similar times (Figure 4.13).
Maxima (blue) clustered around 0300 GMT and 1500 GMT. Minima (red) clustered around 0000 and 2100 GMT. Another cluster was of minima around 0900 GMT. Figure
4.14 shows the count of the distribution for maximum depth and Figure 4.15 shows the count of the distribution for minimum depth. The distribution of times reveals double peaks for maximum and minimum. Double peaks correspond with what Bartzokas et al.
(1995) and Dai and Wang (1999) found with daily global pressure tides. It appears that the water in the cenote is responding to atmospheric pressure which is most likely the 24 hr and 12 hr tidal cycle.
Figure 4.13 Distribution of Daily Maxima and Minima
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Figure 4.14 Occurrence distribution of maximum sensor depth
Figure 4.15 Occurrence distribution of minimum sensor depth
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4.4 Summary of Results
From the water logger data a cyclic pattern was determined. The pattern suggests the fluctuations are a response to diurnal and tidal fluctuations. With tidal fluctuations there is the increased probability for a saltwater intrusion. There was some concern that a windmill and solar water pump that pumps water from the cenote for use at Hacienda
Kancaba might have an effect on the water level. The solar water pump is model 11
SQFlex-2 by Grundfos. Pumping occurs when the solar panels receive enough sunlight to power the pump and the windmill pumps predominantly during the wet season for that is when most active winds occur. During optimal operation of the solar water pump the pumping could possibly cause the maxima and minima peaks. The start and end times of daily operation of the pump roughly coincide with the peaks, which would mean the double minimum is a result of pumping and not from atmospheric pressure tides. A possibility is that the water level would rise through the day then decrease through the night creating a sinusoidal curve if it were not for the pumping causing a depression of water in the cenote.
Although pumping may be a source for the double peaks, it cannot be confirmed as the cause. González-Herrera et al. (2002) and Sánchez- Pinto et al., (2005) found that during pumping there is minimum drawdown of the groundwater with only a small cone of depression forming followed by quick stabilization of the water table of the Yucatán
Peninsula. This means that although water is being pumped out, the water level is not responding much. It is likely that a very high hydraulic conductivity rapidly disperses any effects of pumping. It was found that groundwater flow in the state of Yucatán was
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not altered due to high aquifer transmissivity (González-Herrera et al., 2002). However, there still remain two possibilities for the daily maxima and minima: atmospheric fluctuations or water removal due to pumping.
Another influencing factor is tropical cyclones and precipitation events. In this study, tropical cyclones appear to have minimal affect on rapid water level fluctuation response in the cenote. Tropical cyclones as well as other precipitation events did show a rise in the water table, but usually the peak of this rise occurred a day or two out from the initial event. Therefore, the water level responds to an influx of precipitation, but does not peak on the same day as the event, which suggests a lag in the aquifer system. A quick response was hypothesized, so it was surprising when this did not occur in this study. Marin et al. (1990) however, did observe quick rises in the water table after
Hurricane Gilbert passed over the peninsula. However, there are some inconsistencies with the Marin et al. (1990) paper that may explain why in this study a quick response was not seen. It is not clear what “fast” or “quick” rising means in the Marin et al. (1990) paper. In some locations Hurricane Gilbert rainfall was measured 5 days after the hurricane had passed. These values were compared to readings taken a day before the hurricane made landfall. The preceding readings had already shown a rise due to non- hurricane related precipitation. This casts a doubt on how “quickly” the aquifer responded to Hurricane Gilbert. In other locations the level was observed during
Gilbert‟s passing, but these values were compared to values in July. Gilbert occurred in
September and as was stated earlier in the paper, there was precipitation in the area before Gilbert arrived. Although this study did not show a rapid response, tropical
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cyclones and the other precipitation events did have a general pattern of rising after the initial event suggesting a lag in the aquifer system. So, perhaps precipitation events affect the water level, but an instantaneous response by the aquifer does not exist, at least in the cenote used in this study.
CHAPTER 5
SOIL MOISTURE AND PRECIPITATION
5.1 Introduction
The groundwater and aquifer dynamics can be complex considering that local geology as well as all points of entry to the system. Soil moisture content can help to shed light on the groundwater and aquifer dynamics of the Yucatán region. Recharge rates to the system are hard to estimate, but soil moisture content measurements can help to understand how quickly water can reach the groundwater system. Though the peninsula is porous limestone, there are pockets of soil in many locations. Specifically, the thickest soils collect in the rejolladas. These thick soils, in comparison to the surrounding bare bedrock, hold water for some time instead of allowing water to quickly infiltrate into the porous bedrock.
Precipitation also tends to be a driving factor in groundwater recharge. However, the largest rain events known to have impacted the Peninsula during the study period had little impact on recharge as measured in the cenote. Therefore soil moisture and precipitation were also measured to help create a clearer picture of the overall input to the groundwater system. Knowing rainfall events and then tracking how long the soil holds that moisture furthers the understanding of the interactions between ground and surface.
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5.2 Soil Moisture
5.2.1 Methods
Soil moisture data were gathered from December 25, 2009 to March 26, 2011 from a HOBO (Onset Computer Corporation) microclimate station that was installed at the bottom of Rejollada 3 in the study area (Figure 5.1 & 5.2). The station takes readings every 30 minutes and being at the bottom has the advantage of measuring the moisture content at the point that is closest to the water table in the rejollada. Readings were averaged daily as well as monthly using Microsoft Excel. Graphs were plotted using
Excel.
Subsets were analyzed for the named tropical cyclones of 2010 that were previously determined to have affected the peninsula (Alex - June 27-28, Karl -
September 15-16, and Paula - October 13). The four other Precipitation events (EA, EB,
EC, ED) were also analyzed for soil moisture response. Data used for the tropical cyclones and precipitation events were daily average for one week starting with the day of the precipitation event.
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Figure 5.1 Satellite image of Xuenkal showing Rejollada 3. White plus signs mark microclimate station locations (Munro-Stasiuk & Manahan, 2010)
Figure 5.2 Microclimate station setup in Rejollada 3
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5.2.2 Results
The total average soil moisture for the dataset was 16.1% with a range of 34.3%
(maximum 39.5%; minimum 5.2%). Data were also averaged for daily and monthly means as a way to normalize the data and to allow to be compared to the water logger and precipitation datasets. The 24-hour average moisture content was 16.1% with the maximum being 30.7% and the minimum 5.4% for the study period. The soil moisture content did show normal trends with the rise in moisture during the wet season and then subsequent drop during the dry season (Figures 5.3 and 5.4).
As expected the soil moisture increased as the three tropical cyclones passed over the region (Figure 5.5). This conclusively shows that the area experienced rain from the storms even though the center of the storms did not pass directly over Espita. Soil moisture spiked several times during Karl suggesting that these were rainbands passing through. The soil only maintained the higher moisture content as the storm passed through and a little after it had passed. This suggests that although the soil can retain high moisture levels, it does not hold these raised levels for an extended period of time without additional inputs. This is most likely due to rapid infiltration rates as well as high evapotranspiration rates.
The other precipitation events demonstrated similar patterns (Figure 5.6). The soil moisture responds quickly to the input of precipitation and then decreases again after the event.
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Figure 5.3 Soil moisture content for entire dataset
Figure 5.4 Daily soil moisture averages
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Figure 5.5 Soil moisture content from passing tropical cyclones Alex, Karl, Paula.
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Figure 5.6 Soil moisture content response to precipitation events A, B, C, and D
5.3 Precipitation
5.3.1 Methods
Precipitation data were gathered from the National Climatic Data Center (NCDC) for
the station of Valladolid, Yucatán (Figure 5.7). The period from December 25, 2009 to
March 31, 2011 was acquired and was chosen so that it covered the soil moisture and
water logger dataset time periods. Valladolid was chosen because it was the closest
weather station to the study site (39 km south) that continually collected data. This
station unfortunately does not have continuous reporting. For this reason, some days are
missing from this dataset. However, the NCDC has checked the validity of the record
and found no errors in reporting.
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Figure 5.7 The state of Yucatán showing the location of Valladolid in relationship to Espita (Google Earth)
Precipitation is reported as a 24-hour total in inches, but has been converted into millimeters. 1200 UTC has been chosen as the reporting time due to more records available than the 0000 UTC record. Graphs were plotted using Microsoft Excel.
Subsets of the data were analyzed for tropical cyclones to confirm which storms affected the area. However, with missing days, the record skews surface conditions slightly.
5.3.2 Results
Precipitation averaged 2.6 mm/day for the time period and the range of the data is
86.6 mm/day (maximum 86.6 mm/day; minimum 0 mm/day). As with soil moisture,
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precipitation data follows normal trends of increasing during the wet season and then dropping, often to zero precipitation, during the dry season (figure 5.8 and 5.9).
A tropical cyclone‟s spatial distribution and speed can be estimated from the rainfall rates for the region. For example, though Alex came ashore on the 27th it did not have its largest impact on Valladolid and Espita until the 28th into the 29th (Figure 5.10).
Regional precipitation maps provided by Mexico‟s National Meteorological Service
(Figure 5.11 and 5.12) were used in conjunction with the precipitation data (Figure 5.13) to determine which tropical cyclones had affected the area during the 2010 hurricane season.
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Figure 5.8 Total Daily Precipitation from Valladolid with tropical cyclones Alex, Karl, and Paula, and precipitation events A, B, C, and D marked.
Figure 5.9 Monthly average precipitation at Valladolid
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Figure 5.10 Precipitation for Valladolid during passage of tropical cyclone Alex. Missing data has been marked.
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Figure 5.11 Precipitation map of June 27, 2010 (CONAGUA)
Figure 5.12 Precipitation map of June 28, 2010 (CONAGUA)
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Figure 5.13 Precipitation data for Karl (September 15-16, 2010) and Paula (October 13, 2010). Missing data has been marked.
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5.4 Summary
Soil moisture follows the trends of the wet/dry season, but it never reaches zero.
This demonstrates that the soil does retain moisture which means the rejolladas remain moist year round.
Response was seen immediately by the soil moisture with the three tropical cyclones. Although they did not pass directly over the study area, the soil moisture and precipitation show that outer bands did reach the area. Soil moisture responded quickly to precipitation events, but moisture content decreased with increasing time.
CHAPTER 6
DISCUSSION
6.1 Introduction
Ground penetrating radar, water level, soil moisture, and precipitation data were gathered and analyzed individually to determine if they offered an explanation or cause for water level fluctuations. However, since the karstic aquifer system is complex in that varying factors can influence groundwater flow, the data need to be examined together to look at the interactions of the system. This chapter explores relationships between the datasets and what this means for water level fluctuations near Espita, Mexico.
6.2 GPR Analysis
GPR was successful in imaging layers of soil, and bedrock, but it failed convincingly to detect the water table. Thick soils and residual soil moisture content no doubt had an effect on the radar recordings. Doolittle et al. (2006) found that course- textured soils allowed for large and abrupt volumetric changes across the water table which presents a strong reflection on a radar record. However, fine-textured soils and rocks block the reflection by masking the volumetric changes. Also, finer textured soil allows for a larger capillary fringe (Doolittle et al., 2006) which disperses the reflection from the true water table making detection on a radar record more difficult. Daniels et al.
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(2005) describe the water table typically identified on GPR profiles as not being the true water table, but rather the upper boundary of the capillary fringe and any water table measurements from GPR is highly dependent on the local geology. Based on this, the one location where the water table may be present is not convincing.
Residual soil moisture could also have been a factor in detecting the water table.
Although it was dry and the rainy season had not yet begun, there were still storm bands that moved through the area. This may have provided enough moisture for the thick soils to mask the water table just as the capillary fringe does. Soil content could also be a minor factor in GPR success in this study area. It might prove helpful for future studies in the area to perform soil analysis. Anchuela et al. (2009) stated that a handicap for the penetration depth of GPR systems is high clay content. The soils in the rejolladas have high clay content (Munro-Stasiuk and Manahan, 2010) which may account for the lack of signal penetration.
6.3 Water Logger Analysis
The major observation in the water logger dataset is the daily double maximum and minimum peaks. The double maximum peak represents when the sensor is at its greatest depth. This occurs around 0300 GMT and 1500 GMT. The double minimum peak, when the sensor is at its shallowest depth, occurs around 0000 GMT and 2100
GMT. The times that these seem to occur suggest that the water is responding to what is known as an atmospheric tide. Bartzokas et al. (1995) and Dai and Wang (1999) found that there are global pressure tides that occur daily. For the tropics, atmospheric pressure
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minima occur around 4am and 4pm and maxima peak at 10am and 10pm local time. The maximum peaks, as well as 2100 GMT minimum, correspond with the standard for the tropics. However, the second minimum is somewhat unexplained. The maxima and minima are usually 12 hours apart. In the case of this study maxima follow this rule, but the minima do not. The data need to be compared to real-time atmospheric pressure data near the cenote in order to determine if these maxima and minima are truly representing atmospheric pressure tides or if another variable is acting on the water. Atmospheric tides are manifested from astronomical solar and lunar tides. Pull from the sun and moon effect the Earth creating an earth tide. The atmosphere is disturbed and sent into motion in the form of a ripple, just like a ripple on a body of water. Besides the atmospheric disturbance, the actual stress within the Earth affects pore space. Inkenbrandt et al.
(2005) found that as the sun and moon pass over an area, bedrock dilates due to gravitational forces. This changes the groundwater potential. When the dilation occurs the aquifer expands as a result of the pore space expanding. This allows for more water to be held in the pore space therefore decreasing the groundwater potential or in other words dropping the water table level. However, Inkenbrandt et al. (2005) caution that a false potential change could be recorded due to barometric pressure changes, and therefore barometric effects need to be quantified in order to get a true change of groundwater potential. This reinforces the need for having a weather station at the cenote.
There was some concern that a windmill and solar water pump that pumps water from the cenote for use at Hacienda Kancaba might have an effect on the water level.
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Pumping occurs when the solar panels receive enough sunlight to power the pump and the windmill pumps predominantly during the wet season when the winds are strongest.
During optimal operation of the solar water pump the pumping could possibly cause the maxima and minima peaks. The early morning minimum was thought to not be present and instead two minima in the afternoon three hours apart were present. However, a smaller cluster was noticed around 0900 GMT. This would be the missing morning minimum and is also 12 hours apart from the 2100 GMT cluster as literature suggests it should. The presence of the third minimum cluster is most likely related to the daily end of the pumping. The end of pumping occurs around the time the water is experiencing an atmospheric pressure tide, therefore amplifying the low reading creating a greater minimum at a later time. This masks the 0900 GMT low. So, the pumping has an effect on the water level by creating a third minimum however, as a possible source for both maxima and minima peaks, it cannot be confirmed as the cause.
Water level response to precipitation events, including tropical cyclones, appears to have a lag. The cenote water level began to rise with the influx of water, but did not peak until two or three days after the precipitation event (Figure 6.1). If water infiltrates instantaneously than the peak would occur on the same day as the event.
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Figure 6.1 Precipitation events A, B, C, and D and water logger sensor response
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6.4 Soil Moisture Analysis As soil moisture content was analyzed for the different tropical cyclones and other precipitation events, it was noticed that the soil registered the rainfall events, but moisture levels would drop by the third day from the event. In most cases the soil moisture did not peak on the first day, but rather rose or fluctuated until it reached its peak by the second or third day (6.2). Dropping soil moisture levels after a couple of days demonstrate that although soil retains some moisture, most of the precipitation infiltrated deeper into the ground and/or was lost to evapotranspiration. Gondwe et al. (2010) found the daily average evapotranspiration rate for the whole peninsula varied from 0.99 – 6.93 mm/day depending on the location on the peninsula. Areas close to the coast experienced a higher rate due to more vegetation and a closer water table to the surface. Though the study area is in the interior of the peninsula, Rejollada 3 is densely vegetated during the wet season and therefore would experience higher rates of evapotranspiration which demonstrates conditions similar to locations near the coast. Munro-Stasiuk et al. (2011) found that
Rejollada 3 retained lush vegetation through the dry season and it has a humid environment due to feedback between soil moisture, evapotranspiration from vegetation, and atmospheric heating. So, although soil moisture is lost to evapotranspiration, moisture levels remain relatively high.
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Figure 6.2 Precipitation events A, B, C, and D and soil moisture response
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6.5 Water Logger, Soil Moisture, and Precipitation Relationships
6.5.1 Water Logger and Soil Moisture
Water logger data were compared to soil moisture to determine if the microclimate stations could be used as a proxy for local precipitation and to help determine recharge to the system. If there is a correlation then this means the water level changed as soil moisture changed. Unfortunately, no correlation was found. Both daily average and daily difference were compared from the water logger and the microclimate station. Table 1 shows the correlation coefficients that were found.
Table 1 Correlation between soil moisture and sensor depth Daily Average -0.22167
Daily Difference -0.01855
Although the analysis between water logger and soil moisture returned no correlation a second correlation was run between water logger and precipitation.
Gondwe et al. (2010) found in their study area that the water level responded by increasing during rainfall events. Some areas reacted more rapidly and to a greater degree than other areas, but all areas did increase in reaction to the rainfall. The water logger data for Hacienda Kancaba did behave this way. The cenote used in the study did not instantaneously respond to precipitation events; however it does appear to respond a few days after the event. An exact timeframe for response cannot be determined during
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the wet season (during which this study took place). Due to this, lag time is masked in the system. Analyzing the water level response to February 11, 2011 however does allow for an improved estimation of cenote response time (Figure 6.3). The cenote did not peak in water level on the day the event occurred, but did rise for two days afterwards.
This particular event occurs during the dry season which means there are limited precipitation events so minimal interference from subsequent events. Comparing this to the soil moisture content during this period reveals almost an identical pattern (Figure
6.3) suggesting that although correlations are lacking there is, at least visually, a relationship between water level and soil moisture response during these rain events.
Figure 6.3 Water level and soil moisture response to precipitation event D, February 11, 2011
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A correlation analysis between water level and precipitation returned that there was not only no correlation, but it was an inverse relationship (Table 2). This result is surprising and slightly counterintuitive. However, discovering the relationship of the water level not instantaneously responding to rainfall events explains why precipitation and water level do not correlate. This relationship accompanied by pattern of response to precipitation events reveals quite a bit about the internal dynamics of this karstic aquifer system.
Precipitation data location may also have partly influenced the lack of a correlation. When an analysis was run between soil moisture and precipitation data, a correlation was found, but not as strong as expected (Table 2). This demonstrates well the differences in the spatial distribution of precipitation in the region and the effect of dense vegetation. Unless it is a widespread rain event (i.e. tropical cyclone or large storm system), precipitation has a very local effect. If there is a lag in the system response then this too will cause a weaker correlation. A weather station at Hacienda Kancaba would yield better and more useful data.
A weaker correlation between soil moisture and precipitation is attributed partially to spatial variability of rainfall, but also the lag that is present in the system. For similar reasons to why precipitation and water level did not correlate, a lag would mask soil moisture response to precipitation events.
Besides the several day lag that is present in both water level and soil moisture response to precipitation events, there appears to be a longer lag to the overall response of the system. Observing the full water level dataset the water level is not at its highest
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during the wet season; it is highest a month to two months after the peak of the wet season (Figure 6.4). This lag would represent a broader regional aquifer response.
Table 2 Correlation of sensor depth and soil moisture with precipitation data Daily Sensor Depth Average and -0.24933
24-hr Total Precipitation
Daily Soil Moisture Average and 0.3330
24-hr Total Precipitation
Figure 6.4 Full dataset of water logger sensor depth with trend line
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6.6 Summary
GPR was not an effective method in this study. It failed to show the water table with any certainty; however it did reinforce the current literature that thick soils and fine- grained rock are not ideal conditions for GPR. There is room for refinement of operation of the GPR by doing separate soil analyses and experiments on areas where the depth to the water table is exactly known. From these experiments GPR can be adjusted and hopefully become better at locating and imaging the water table.
Water level, soil moisture, and precipitation measurements provided an interesting look at the inputs to the aquifer. Spatial variations in precipitation proved to be an important component in using precipitation data from a station far from the study area. In Yucatán, meteorological data must be acquired at the study site in order to obtain a true idea of water table response to precipitation and atmospheric pressure.
Soil moisture rose as tropical cyclones passed over the peninsula proving that though it was not directly overhead, outer bands of the storms did pass through the area.
The water table did rise with the passage of tropical cyclones, but not right away and fluctuated in that rise in some cases. This is different than what was found in the literature which suggested a rapid instant response. Two lags were identified; a lag consisting of a couple of days in response to precipitation events and an overall two month delay in the system. Further investigation into other cenotes in the area would offer an interesting look into the connectedness of the cenotes of the Espita area which would describe the local characteristics of the local aquifer as well as overall regional aquifer dynamics of the peninsula interior.
CHAPTER 7
CONCLUSION
7.1 Concluding Remarks
Groundwater dynamics of the northern Yucatán Peninsula are related to a number of factors. While the surface seems harsh and unforgiving with its lack of surface water, people and civilizations as a whole have survived here. So, how can a landscape that should be barren and void of life be actually thriving and sustainable? It is directly related to the presence of groundwater only a few meters below the land surface.
Groundwater flow and aquifer dynamics need to be understood in this region on the local scale. With complete dependence upon this groundwater, contamination or a well going dry would be detrimental to society. Instead of a regional approach, a local one is needed when studying aquifer dynamics of the Yucatán Peninsula. Studying the local variables of geology, topography, and groundwater response will describe the dynamics of the aquifer more thoroughly than any regional analysis.
Water level data show fluctuations that are due to atmospheric pressure changes, but also other fluctuations that are most likely inherent within the system. A representation of a component of the overall karstic aquifer dynamics on the local system can be seen in the two month lag. Unexplained fluctuations detected through the spectral
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analysis could be unknown pore-space pressure change connections with the coasts due to tides and possible saltwater intrusion. Also, rain events occurring on the southwest of the peninsula or even seismic-related changes in the Earth can have an effect on pressure within the system. The area is too easily affected by changing conditions around it to pinpoint the exact source of change. However, one thing is clear in this region and that is it is very susceptible to pressure changes, be it internally or atmospherically.
It is suggested here that the Yucatán aquifer is controlled by local dynamics as well as regional dynamics. Therefore the area should be analyzed locally first then apply local results regionally for a holistic view of the peninsula. Also, the aquifer, at least north-central Yucatán, is controlled by horizontal flow of groundwater. This can explain the two-day lag in the system that was seen in the cenote. The two-month lag can be attributed to regional northerly horizontal groundwater flow. These lags combine to create the response times and variability seen in the cenote used in this study.
7.2 Limitations of the Study
This study was conducted, in part, as an exploration of methods that can be used for future groundwater studies in Espita. GPR did not perform to the level that was hoped for, but it has room for improvements given a soil study and verification of the depth to the water table. The GPR unit did fail at times due to battery life or due to fiber optic wires becoming loose because they were delicate and easily pulled. Data were checked for interruptions in readings and as stated in chapter 3 errors were encountered and accounted for in the data collection.
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Water level measurements were too focused on one cenote. To be able to connect this cenote to the larger picture of the entire karstic aquifer dynamics a network of water level loggers are needed. The system has too many interacting variables for just one logger.
Precipitation data from Valladolid were missing for some days and given its spatial relationship to Espita would have precipitation when Espita did not. Detections in aquifer response times, especially lag times, are not truly known because of this.
Microclimate stations had probe and entire unit failures resulting in only the one station viable enough to use in this study. The extreme heat of the region played a part in this as it drained the batteries and overheated the units.
7.3 Suggestions for Future Work
Research will continue in this region for it offers an interesting hydrological and anthropological mystery, however a joint effort might serve as a better approach than individual studies. A network of monitoring and field sites need to be compiled if the true dynamics of this system are to ever be understood. A „big picture” approach will reveal system response times as well as what areas are dependent upon one another, if any. This approach can be accomplished by uniting efforts and research of the region from those in contaminate hydrology, urban planning, anthropology, agriculture, and physical sciences. There are too many resources needed to execute a comprehensive study of the region. However, if research is shared and local studies are pooled together in an open communicative format, a broader picture of the dynamics of the region can be
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gained. A broader picture of Yucatán aquifer dynamics can help predict contaminate flows, water shortages, and plan for sustainability. The peninsula has survived this long without this knowledge, but with expanding cities (i.e. Mérida) that do not have a sewage system or treatment plant, the risk of the water supply becoming contaminated increases every minute. Plan now, mitigate now, and then the people of Yucatán will have one less worry in the future.
REFERENCES
Al-fares, W., M. Bakalowicz, R. Guérin, and M. Dukhan. 2002. Analysis of the karst
aquifer structure of the Lamalou area (Hérault, France) with ground penetrating
radar. Journal of Applied Geophysics 51 (2-4): 97-106.
Anchuela, Ó. P., A. Casas-Sainz, M. A. Soriano, and A. Pocoví-Juan. 2009. Mapping
subsurface karst features with GPR: Results and limitations. Environmental Geology
58 (2): 391-9.
Ardren, Traci. 2007. Regional investigations at the Cupul Province trading center of
Xuenkal: Proyecto arqueológico Xuenkal. Foundation For The Advancement of
Mesoamerican Studies, INC.
Ataie-Ashtiani, B., R. E. Volker, and D. A. Lockington. 1999. Tidal effects on sea water
intrusion in unconfined aquifers. Journal of Hydrology 216 (1-2): 17-31.
Back, W. and B. B. Hanshaw. 1970. Comparison of chemical hydrogeology of the
carbonate peninsulas of Florida and Yucatan. Journal of Hydrology 10 : 330.
Back, W. 1995. Water management by early people in the Yucatán, Mexico.
Environmental Geology 25 (4): 239-42.
Bartzokas, A., C. C. Repapis, and D. A. Metaxas. 1995. Temporal variations of
atmospheric tides over Athens, Greece. Meteorology and Atmospheric Physics 55 (1-
2): 113.
83
84
Bauer-Gottwein, Peter, Bibi R. N. Gondwe, Guillaume Charvet, Luis E. Marín, Mario
Rebolledo-Vieyra, and Gonzalo Merediz-Alonso. 2011. Review: The Yucatán
Peninsula karst aquifer, Mexico. Hydrogeology Journal 19 (3): 507-24.
Beddows, P. A. 2004. Groundwater hydrology of a coastal conduit carbonate aquifer:
Caribbean Coast of the Yucatán Peninsula, México. PhD Thesis, School of
Geographical Sciences, University of Bristol.
Bense, V. F., R. T. Van Balen, and J. J. De Vries. 2003. The impact of faults on the
hydrogeological conditions in the Roer Valley Rift System: An overview.
Netherlands Journal of Geosciences 82 (1): 41-54.
Beres Jr, M., and F. P. Haeni. 1991. Application of ground-penetrating-radar methods in
hydrogeologic studies. Ground Water 29 (3): 375.
Cezar, G. da S., P. L. F. Rocha, A. Buarque, and A. Costa. 2001. Two Brazilian
archaeological sites investigated by GPR: Serrano and Morro Grande. Journal of
Applied Geophysics 47 : 227.
Chamberlain, A. T., W. Sellers, C. Proctor, and R. Coard. 2000. Cave detection in
limestone using ground penetrating radar. Journal of Archaeological Science 27 :
957.
Corbel, J. 1959. Erosion en terrain calcaire. In Karst Hydrogeology and Geomorphology,
eds. D. Ford and P. Williams, 77. West Sussex, England: John Wiley & Sons Ltd.
Dai, A. and J. Wang. 1999. Diurnal and semidiurnal tides in global surface pressure
fields. Journal of the Atmospheric Sciences 56 : 3874.
85
Daniels, J. J., B. Allred, A. Binley, D. Labrecque, and D. Alumbaugh. 2005.
Hydrogeophysical case studies in the vadose zone. In Hydrogeophysics, eds. Y.
Rubin and S. S. Hubbard, 413-440. Netherlands: Springer.
De Blij, H. J., P. O. Muller, and R. S. Williams. 2004. Physical geography
the global environment. Third ed.Oxford University Press.
De Vries, J. J. and I. Simmers. 2002. Groundwater recharge: an overview of processes
and challenges. Hydrogeology Journal 10 : 5.
Doolittle, J. A., B. Jenkinson, D. Hopkins, M. Ulmer, W. Tuttle. 2006. Hydropedological
investigations with ground-penetrating radar (GPR): Estimating water-table depths
and local ground-water flow pattern in areas of coarse-textured soils. Geoderma 131
(3-4): 317.
Escolero, O., L. E. Marin, B. Steinich, J. A. Pacheco, A. Molina Maldonado, J. M.
Anzaldo. 2005. Geochemistry of the hydrogeological reserve of Mérida, Yucatán,
Mexico. Geofísica Internacional 44 (3): 301.
Escolero, O., L. E. Marin, E. Domínguez-Mariani, S. Torres-Onofre. 2007. Dynamic of
the freshwater-saltwater interface in a karstic aquifer under extraordinary recharge
action: The Merida Yucatán case study. Environmental Geology 51 (5): 719.
Esteban M. 1991. Palaeokarst: Practical Applications. In Palaeokarsts and Palaeokarstic
Reservoirs. P.R.I.S. Occassional Publication Series, eds. V. P. Wright., M.
Esteban,and P. L. Smart, 89.
86
Estrada-Medina, H. W. Tuttle, R. C. Graham, M. F. Allen, J. J. Jiménez-Osornio. 2010.
Identification of underground karst features using ground-penetrating radar in
northern Yucatán, Mexico. Vadose Zone Journal 9 (3): 653.
Fedick, S. L., and B. A. Morrison. 2004. Ancient use and manipulation of landscape in
the Yalahau region of the northern Maya lowlands. Agriculture and Human Values
21 (2): 207.
Fedick, S. L., M. De Lourdes Flores Delgadillo, S. Sedov, E. Solleiro Rebolledo, and S.
Palacios Mayorga. 2008. Adaptation of Maya homegardens by “container
gardening” in limestone bedrock cavities. Journal of Ethnobiology 28 (2): 290.
Field, Malcolm S. 2002. A lexicon of cave and karst terminology with special reference
to environmental karst hydrology. National Center for Environmental Assessment-
Washington Office, Karst Waters Institute. http://www.karstwaters.org/glossary.htm
(accessed August 2011).
Ford, D. and P. Williams. 2007. Karst Hydrogeology and Geomorphology. West Sussex,
England: John Wiley & Sons Ltd.
Froese, D.G., D. G. Smith, and D.T. Clement. 2005. Characterizing large river history
with shallow geophysics: Middle Yukon River, Yukon Territory and Alaska.
Geomorphology 67 : 391.
Gelting, R. J. 1995. Water and population in the Yucatán Peninsula. Working Paper,
International Institute for Applied Systems Analysis WP-95-87.
Gondwe, B. R. N., S. Lerer, S. Stisen, L. Marin, M. Rebolledo-Vieyra, G. Merediz-
Alonso, and P. Bauer-Gottwein. 2010. Hydrogeology of the south-eastern Yucatán
87
Peninsula: New insights from water level measurements, geochemistry, geophysics
and remote sensing. Journal of Hydrology 389 (1-2): 1.
González-Herrera, R., I. Sánchez-y-Pinto, and J. Gamboa-Vargas. 2002. Groundwater-
flow modeling in the Yucatán karstic aquifer, Mexico. Hydrogeology Journal 10 (5):
539.
Hall, F. G. 1936. Physical and chemical survey of cenotes of Yucatán. In The Cenotes of
Yucatán, A Zoological and Hydrographic survey, eds. A. S. Pearse, E. P. Creaser,
and F. G. Hall, 5. Carnegie Institution of Washington.
Harris, J. G., J. E. Mylroie, and J. L. Carew. 1995. Banana holes: Unique karst features of
the Bahamas. Carbonates and Evaporites 10 (2): 215.
Houck, C. W., 2006: Cenotes, Wetlands, and Hinterland Settlement. In Lifeways in the
Northern Maya Lowlands: New Approaches to Archaeology in the Yucatan
Peninsula. eds. J. Mathews and B. Morrison (eds.)University of Arizona Press, 56.
Tucson.
Hruska, J., and G. Fuchs. 1999. GPR prospection in ancient Ephesos. Journal of Applied
Geophysics 41 : 293.
Huisman, J. A., C. Sperl, W. Bouten, and J. M. Verstraten. 2001 Soil water content
measurements at different scales: accuracy of time domain reflectometry and ground
penetrating radar. Journal of Hydrology 245 : 48.
Inkenbrandt, P. C., P. K. Doss, T. J. Pickett, and R. J. Brown. 2005. Barometric and
earth-tide induced water-level changes in the Inglefield sandstone in southwestern
Indiana. Proceedings of the Indiana Academy of Science 114 (1): 1.
88
Jol, H.M. ed. 2009. Ground Penetrating Radar: Theory and Applications. Netherlands:
Elsevier Science.
Leckebusch, J., 2003. Ground-penetrating radar: A modern three-dimensional
prospection method. Archaeological Prospection 10 : 213.
Lesser, J. M. and A. E. Weidie. 1988. Region 25, Yucatán Peninsula. In Hydrogeology,
eds. W. Bak, J. Rosenshein, and R. Seaber, 237. Geological Society of America.
Marin, L. E., E. C. Perry, K. O. Pope, C. E. Duller, C. J. Booth, and M. Villasuso. 1990.
Hurricane Gilbert: Its effects on the aquifer in Northern Yucatán, Mexico. In
Selected Papers on Hydrogeology: from the 28th International Geological Congress,
Washington, D. C., U. S. A. July 9-19, 1989, eds. E. S. Simpson and J. M. Sharp,
111.
Marin, L. E. and E. C. Perry. 1994. The hydrogeology and contamination potential of
northwestern Yucatán, Mexico. Geofísica Internacional 33 (4): 619.
Marín, L. E., B. Steinich, J. Pacheco, and O. A. Escolero. 2000. Hydrogeology of a
contaminated sole-source karst aquifer, Merida, Yucatán, Mexico. Geofisica
International 39 (4): 359.
Moore, L. J., H. M. Jol, G. M. Kaminsky, S. Kruse, and S. Vanderburgh. 2004. Annual
layers revealed by GPR in the subsurface of a prograding coastal barrier, southwest
Washington, U.S.A. Journal of Sedimentary Research 74 : 690.
Moore, Y. H., R. K. Stoessell, and D. H. Easley. 1992. Fresh-Water/Sea-water
relationship within a ground-water flow system, northeastern coast of the Yucatán
Peninsula. Ground Water 30 (3): 343.
89
Moorman, B. J., and F. A. Michel. 2000. Glacial hydrological system characterization
using ground-penetrating radar. Hydrological Processes 14 : 2645.
Munro-Stasiuk, M. J. and T. K. Manahan. 2010. Investigating ancient Maya agricultural
adaptation through ground penetrating radar (GPR) analysis of karst terrain,
Northern Yucatán, Mexico. Acta Carsologica 39 (1): 123-36.
Munro-Stasiuk, M. J., S. C. Sheridan, and T. K. Manahan. 2011. Rejolladas (dry
sinkholes) as microclimatological niches in Yucatán, Mexico. Papers of the Applied
Geography Conference 34 : 48.
Mylroie, J. E. and J. L. Carew. 2003. Karst development on carbonate islands.
Speleogenesis and Evolution of Karst Aquifers 1 (2): 1.
National Climatic Data Center. Online Climate Data Directory.
http://lwf.ncdc.noaa.gov/oa/climate/climatedata.html#surface (Accessed July, 2011).
Pacheco, J. and A. Cabrera. 1997. Groundwater contamination by nitrates in the Yucatán
Peninsula, Mexico. Hydrogeology Journal 5 (2): 47.
Pacheco, J., L. Marin, A. Cabrera, B. Steinich, O. Escolero. 2001. Nitrate temporal and
spatial patterns in 12 water-supply wells, Yucatán, Mexico. Environmental Geology
40 (6): 708.
Penfield, G. T. and A. Camargo. 1981. Definition of a major igneous zone in the Central
Yucatán Platform with aeromagnetics and gravity. In Surficial Geology of the
Chicxulub Impact Crater, Yucatán, Mexico, 93. Earth, Moon, and Planets 63 : 93
Plummer, C. C., D. McGeary, and D. H. Carlson. 2005. Physical Geology. 10th ed. New
York, NY: McGraw Hill Higher Education.
90
Pope, K. O., A. C. Ocampo, and C. E. Duller. 1993. Surficial geology of the Chicxulub
impact crater, Yucatán, Mexico. Earth, Moon, and Planets 63 : 93.
Salvati, R. and I. D. Sasowsky. 2002. Development of collapse sinkholes in areas of
groundwater discharge. Journal of Hydrology 264 : 1.
Sánchez-Pinto, I., R. González-Herrera, and E. Perry. 2005. Hydrodynamic behavior of
the Yucatán aquifer. A perspective on the hydraulic conductivity estimation. In
Espelunc@ digital, Ciudad de La Habana, Cuba, ed.L. F. Molerio León, 2 : 8.
SARH, 1989. Sinopsis Geohidrologica del Estado de Yucatán [Geohydrologic synopsis
of the State of Yucatan]. Secretaria de Agricultura y Recursos Hidraulicos.
Subsecretaria de Infraestructura Hidraulica. Direccion General de Administracion y
Control de Sistemas Hidrologicos, Mexico, DF.
Serfes, M. E. 1991. Determining the mean hydraulic gradient of ground water affected by
tidal fluctuations. Ground Water 29 (4): 549.
Siemers, J. and W. Dreybrodt. 1998. Early development of karst aquifers on percolation
networks of fractures in limestone. Water Resources Research 34 (3): 409.
Soler-Bientz, R., S. Watson, and D. Infield. 2009. Preliminary study of long-term wind
characteristics of the Mexican Yucatán Peninsula. Energy Conversion and
Management 50 : 1773.
Steinich, B. and L. E. Marin. 1996. Hydrogeological investigations in northwestern
Yucatán, Mexico, using resistivity surveys. Ground Water 34 (4): 640.
Steinich, B. and L. E. Marin. 1997. Determination of flow characteristics in the aquifer of
the Northwestern Peninsula of Yucatán, Mexico. Journal of Hydrology 191 : 315.
91
Sternberg, B. K., and J. W. McGill. 1995 Archaeology studies in southern Arizona using
ground penetrating radar. Journal of Applied Geophysics 33 : 209.
Turesson. A. 2006. Water content and porosity estimated from ground-penetrating radar
and resistivity. Journal of Applied Geophysics 58 : 99.
Villasuso Pino, M. J., I. A. Sánchez y Pinto, C. Canul Macario, R. Casares Salazar, G.
Baldazo Escobedo, J. Souza Cetina, P. Poot Euán, C. Pech Arguelles. 2011.
Hydrogeology and conceptual model of the karstic coastal aquifer in Northern
Yucatán State, Mexico. Tropical and Subtropical Agroecosystems 13 : 243.
Weidie, A. E. 1985. Geology of Yucatán Platform. In Geology and Hydrogeology of the
Yucatán and Quaternary Geology of Northeastern Yucatán Peninsula, eds. W.
Ward, A. Weidie, and W. Back, New Orleans Geological Society, 1.
White, W. B. 2003. Conceptual models for karstic aquifers. Speleogenesis and Evolution
of Karst Aquifers 1 (1): 1.