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Open Access Theses & Dissertations
2015-01-01 Predicting Irrigation Efficiency in the Rio Grande Project Gerardo Melendez University of Texas at El Paso, [email protected]
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This is brought to you for free and open access by DigitalCommons@UTEP. It has been accepted for inclusion in Open Access Theses & Dissertations by an authorized administrator of DigitalCommons@UTEP. For more information, please contact [email protected]. PREDICTING IRRIGATION EFFICIENCY IN THE RIO GRANDE PROJECT
Gerardo Melendez
Department of Civil Engineering
APPROVED:
Shane Walker, Ph.D., Chair
John Walton, Ph.D.
Stanley Mubako, Ph.D.
Charles Ambler, Ph.D. Dean of the Graduate School
Copyright ©
by
Gerardo Melendez
2015
DEDICATION
This thesis is dedicated to my mother, who has helped me immensely throughout all my years in school and work. Without her help, this thesis may not have been written. Thanks, Mom! PREDICTING IRRIGATION EFFICIENCY IN THE RIO GRANDE PROJECT
by
GERARDO MELENDEZ, B.S. in Environmental Science, Biology Concentration
THESIS
Presented to the Faculty of the Graduate School of
The University of Texas at El Paso
in Partial Fulfillment
of the Requirements
for the Degree of
MASTER OF SCIENCE IN ENVIRONMENTAL ENGINEERING
Department of Civil Engineering
THE UNIVERSITY OF TEXAS AT EL PASO
December 2015 ACKNOWLEDGEMENTS
I would like to thank Dr. John Walton, retired professor at UTEP, for his help and guidance with this thesis, and his tough teaching of hydraulics and other related classes which gave me a basis for understanding this research topic. I would also like to thank Filiberto “Bert”
Cortez of Reclamation – El Paso, TX, for his assistance with this study and in helping me better understand the Rio Grande Project. Also, I would like to acknowledge Dr. Shane Walker and Dr.
Stanley Mubako, professors at UTEP, for their help with this thesis.
v ABSTRACT
Surface water losses in the Bureau of Reclamation’s (USBR) Rio Grande Project have become more prevalent within the past few years of the drought of the 2000’s. Simple regressions were performed in order to find correlations and determine factors that may affect the flows within the Rio Grande Project. Correlations were found in the difference between Rio Grande below Caballo flows and Rio Grande at El Paso flows, and between the diversion ratio and groundwater levels. Caballo Reservoir release amounts were found to be fairly well correlated with the difference between the Rio Grande below Caballo and the Rio Grande at El Paso gaging stations. The higher the release from Caballo, the lower the percent difference between the two gages. Groundwater levels data was taken from a United States Geological Survey (USGS) well section in the City of Las Cruces, New Mexico. The well section is located in a major losing reach of the Lower Rio Grande River. Groundwater levels and the diversion ratio were found to be highly correlated for certain wells. Groundwater levels have been declining in this section as the diversion ratio has also been declining. A declining diversion ratio points to dropping groundwater levels. The previous year’s groundwater levels could potentially be used to get an estimate of the diversion ratio for an upcoming irrigation season. Wells LC-2A and LC-3A had the highest r-squared results for predicting the upcoming irrigation season’s diversion ratio using the previous year’s groundwater levels. The best prediction of the diversion ratio was with LC-2A with USGS approved and provisional data with an r-squared value of 0.92, and the correlation was: Diversion Ratio = 1.5847 – 0.0252 (LC-2A depth in feet). Further future study is needed to confirm this method, and to find other factors that could better predict river efficiency. Increased Caballo Reservoir release amounts from high storage and/or snowmelt runoff could potentially increase groundwater basin storage and increase the diversion ratio for the Rio Grande Project.
vi TABLE OF CONTENTS
ACKNOWLEDGEMENTs...... v
ABSTRACT ...... vi
TABLE OF CONTENTS ...... vii
LIST OF TABLES ...... ix
LIST OF FIGURES ...... x
1. INTRODUCTION ...... 1
1.1. Historical Background of the Rio Grande Project ...... 6
1.2. Diversion Ratio ...... 7
1.3. Current Conditions ...... 10
1.4. Goals and Objectives ...... 11
2. METHODOLOGY ...... 13
2.1. Rio Grande Project Water Budget ...... 13
2.2. Diversion Ratio ...... 15
2.3. Water Use from Caballo Gaging Station to El Paso Gaging Station ...... 20
2.4. Precipitation ...... 22
3. RESULTS ...... 23
3.1. Rio Grande Project Water Budget ...... 23
3.2. Diversion Ratio Correlations ...... 24 3.2.1. Correlations with Groundwater Levels ...... 24 3.2.2. Correlations with Release Volumes ...... 32
vii 3.3. Water Use from Caballo Gaging Station to El Paso Gaging Station ...... 36
3.4. Precipitation ...... 37
4. DISCUSSION ...... 40
4.1. Diversion Ratio Synopsis ...... 40
4.2. Rincon and Mesilla Valley Aquifer Systems ...... 41 4.2.1. Rincon Valley ...... 42 4.2.2. Mesilla Valley ...... 43 4.2.3. Precipitation ...... 47
5. CONCLUSIONS ...... 48
REFERENCES ...... 50
APPENDIX A. RIO GRANDE PROJECT DIVERSIONS AND DIVERSION RATIOS SINCE 1908 (UNPUBLISHED INTERNAL DATA FROM U.S. BUREAU OF RECLAMATION – EL PASO) ...... 53
APPENDIX B. DIVERSION RATIOS (USBR, INTERNAL) AND GROUNDWATER LEVELS (USGS, 2015) ...... 55
APPENDIX C. ESTIMATED PRECIPITATION VOLUME IN ACRE FEET USING PRECIPITATION DATA FROM LAS CRUCES, NM (NCDC, 2014) ...... 56
Appendix D. Diversion Ratio correlations with USGS Well Data ...... 57
APPENDIX E - ALLOCATION CHARGES AND CORRESPONDING DIVERSION RATIO FOR YEARS 2008 TO 2014 (USBR, INTERNAL) ...... 68
VITA ...... 81
viii LIST OF TABLES
Table 1. 2008 Allocation Charges (USBR, internal) ...... 68
Table 2. 2009 Allocation Charges (USBR, internal) ...... 69
Table 3. 2010 Allocation Charges (USBR, internal) ...... 70
Table 4. 2011 Allocation Charges (USBR, internal) ...... 72
Table 5. 2012 Allocation Charges (USBR, internal) ...... 75
Table 6. 2013 Allocation Charges (USBR, internal) ...... 76
Table 7. Additional Information for 2013 Allocation Charges (USBR, internal) ...... 78
Table 8. 2014 Allocation Charges (USBR, internal) ...... 78
ix LIST OF FIGURES
Figure 1. Map of major dams and diversions on the Rio Grande (USFW, 2015) ...... 2
Figure 2. Map of the Rio Grande Project with Study Area (USBR, 2015) ...... 4
Figure 3. Rio Grande below Caballo Annual Flows and Diversions, 1918 to 2014 (USBR, internal) ...... 7
Figure 4. Diversion Ratio since 1918 (Appendix A)...... 8
Figure 5. Diversion Diagram of Applied Irrigation and Return Flows (Esslinger, 2008) ...... 9
Figure 6. Plot of Annual Differences Between RGBC (USBR - internal) and RGEP (IBWC, 2014), and RGBC Releases...... 15
Figure 7. Map of USGS Mesilla Basin observation-well network in New Mexico and Texas. LC well section is labeled A – A’ here (USGS, 2015) ...... 17
Figure 8. USGS Las Cruces Well Field (USGS, 2015)...... 18
Figure 9. Caballo Release (blue), Rio Grande at El Paso flows (red), Caballo minus El Paso flows (purple), and Percent Difference between Caballo and El Paso flows (green), 1938 to 2013 (data for Caballo from USBR,internal, data for El Paso flows from IBWC, 2015)...... 21
Figure 10. Well LC-2A, Depth to Groundwater (USGS, 2015) & Diversion Ratio (USBR, unpublished) ...... 25
Figure 11. Well LC-2C, Depth to Groundwater (USGS, 2015) & Diversion Ratio (USBR, unpublished) ...... 25
Figure 12. Well LC-3A, Depth to Groundwater (USGS, 2015) & Diversion Ratio (USBR, unpublished) ...... 26
Figure 13. Well LC-3C, Depth to Groundwater (USGS, 2015) & Diversion Ratio (USBR, unpublished) ...... 26
Figure 14. Well LC-2A; Diversion Ratio (USBR, unpublished) correlation with (a) Current Year Depth to Groundwater (USGS) and (b) Previous Year Depth to Groundwater (USGS), 1985 to 2011 (only USGS-approved water level data) ...... 28
Figure 15. Well LC-2A; Diversion Ratio (USBR, unpublished) & (a) Current Year Depth to Groundwater (USGS, 2015)), 1985 to 2014. Diversion Ratio (USBR, unpublished) & (b) Previous Year Depth to Groundwater (USGS, 2015), 1985 to 2013 (approved and provisional data)...... 29
x Figure 16. Well LC-3A; Diversion Ratio (USBR, unpublished) & (a) Current Year Depth to Groundwater (USGS, 2015), 1985 to 2011 Well LC-3A; Diversion Ratio (USBR, unpublished) & (b) Previous Year Depth to Groundwater (USGS, 2015), 1985 to 2011. (only USGS-approved water level data) ...... 30
Figure 17. Well LC-3A; Diversion Ratio (USBR, unpublished) & (a) Current Year Depth to Groundwater (USGS, 2015), 1985 to 2014, Diversion Ratio (USBR, unpublished) & (b) Previous Year Depth to Groundwater (USGS, 2015), 1985 to 2013 (approved and provisional data)...... 31
Figure 18. Diversion Ratio & Release, 1938 to 2013 (USBR, internal) ...... 33
Figure 19. Diversion Ratio & (a) Release, 1985 to 2014, Diversion Ratio & (b) Previous Year’s Release, 1985 to 2013 (USBR, internal) ...... 34
Figure 20. Groundwater Levels (USGS, 2015) & (a) Release (USBR, internal) 1985 to 2014, Groundwater Levels (USGS, 2015) and (b) Previous Year’s Release (USBR, internal), 1985 to 2013 ...... 35
Figure 21. Percent Difference of Caballo Release and El Paso flows versus Caballo Release, 1938 to 2013 (USBR, internal & IBWC, 2014)...... 37
Figure 22. Precipitation (NCDC, 2014) Volume and (a) Percent Difference of Caballo and El Paso Flows (USBR, internal and IBWC, 2015) Precipitation (NCDC, 2014) Volume and (b) Absolute Difference of Caballo and El Paso Flows (USBR, internal and IBWC, 2015) ...... 38
Figure 23. Precipitation (NCDC, 2014) Volume and Diversion Ratio (USBR, unpublished)...... 39
Figure 24. Well LC-3C; Diversion Ratio (USBR, unpublished) & (a) Current Year Depth to Groundwater (USGS, 2015), 1985 to 2011, Diversion Ratio (USBR, unpublished) & (b) Previous Year Depth to Groundwater (USGS, 2015), 1985 to 2011 ...... 57
Figure 25. Well LC-2C; Diversion Ratio (USBR, unpublished) & (a) Current Year Depth to Groundwater (USGS, 2015), 1985 to 2011, Diversion Ratio (USBR, unpublished) & (b) Previous Year Depth to Groundwater (USGS, 2015), 1985 to 2011 ...... 58
Figure 26. Well LC-2C; Diversion Ratio (USBR, unpublished) & (a) Current Year Depth to Groundwater (USGS, 2015), 1985 to 2014, Diversion Ratio (USBR, unpublished) & (b) Previous Year Depth to Groundwater (USGS, 2015), 1985 to 2013 ...... 59
Figure 27. Well LC-2B; Diversion Ratio (USBR, internal) & (a) Current Year Depth to Groundwater (USGS, 2015), 1985 to 2011, Diversion Ratio (USBR, internal) & (b) Previous Year Depth to Groundwater (USGS, 2015), 1985 to 2010 ...... 60
Figure 28. Well LC-2B; Diversion Ratio (USBR, internal) & Current Year Depth to Groundwater (USGS, 2015), 1985 to 2014, Diversion Ratio (USBR, internal) & Previous Year Depth to Groundwater (USGS, 2015), 1985 to 2013 ...... 61
xi Figure 29. Rio Grande below Picacho Bridge river stage in 1985 & 1986 (Nickerson and Myers, 1993) ...... 62
Figure 30. LC-1 Groundwater Levels for 1985 and 1986 (Nickerson and Myers, 1993) ...... 63
Figure 31. LC-2 Groundwater Levels for 1985 and 1986 (Nickerson and Myers, 1993) ...... 64
Figure 32. LC-3 Groundwater Levels for 1985 and 1986 (Nickerson and Myers, 1993) ...... 65
Figure 33. LC-1, LC-2, and LC-3 Well Section Levels (Gastelum and others, 2012) ...... 66
Figure 34. Map of 2012 Seepage Study (Gunn and Roark, 2012) ...... 67
xii 1. INTRODUCTION
The Rio Grande River begins at the headwaters in the San Juan Mountains of southern
Colorado and flows down to its mouth in the Gulf of Mexico near Brownsville, Texas (TX), as shown in Figure 1. The flow of the river is mostly supplied by winter precipitation that falls in the San Juan Mountains of Colorado, and to a lesser extent in the mountains in northern New
Mexico (NM). A series of dams were built along the river in order to collect the spring snowmelt hydrograph and store it for agricultural use later on in the season. The first major dam of the river is Cochiti Dam upstream of Albuquerque, NM, and the last major dam is Falcon Dam located upstream of McAllen, TX. Irrigation water is typically released throughout the spring, summer, and fall months in order to provide water for farms and for municipal uses as well.
1
Figure 1. Map of major dams and diversions on the Rio Grande (USFW, 2015)
This study focuses on a part of the river sometimes referred to as the “Lower Rio
Grande” but is also known as the Bureau of Reclamation’s “Rio Grande Project”. The Rio
Grande Project begins with Elephant Butte and Caballo Reservoirs located in New Mexico and ends at the Fort (Ft.) Quitman gaging station in Ft. Quitman, TX (Figure 2). The river water in this section is reserved mainly for irrigation in southern New Mexico and El Paso County, TX, but is also used directly for municipal purposes by the City of El Paso, TX, and indirect municipal uses by El Paso TX, Las Cruces, NM, and other municipalities in or near the valley, as well as industrial uses. Indirect use is when groundwater is extracted for municipal and industrial use leading to lowered return flows into the river and greater canal and river losses as well. Most
2 of the water released in this reach gets used before it reaches the Ft. Quitman gaging station. A series of negotiated agreements allow for water to be allocated to different sections of lands and water rights owners within this reach. Three major entities split the river water in this section.
One of these entities is in Southern New Mexico and is named the Elephant Butte Irrigation
District (EBID). Another entity is part of El Paso County in Texas and is known as the El Paso
County Water Improvement District #1 (EP#1). The last entity is the country of Mexico. The two irrigation districts and the Bureau of Reclamation are bound by an “Operating Agreement”
(USBR, 2015) which allocates a certain amount of water to each district and Mexico according to irrigable acreage, current and forecasted supply, and treaties and laws.
3 STUDY AREA
Figure 2. Map of the Rio Grande Project with Study Area (USBR, 2015)
4 Rio Grande water is stored at Elephant Butte and Caballo Reservoirs as Rio Grande
Project water. This water is used from Below Caballo Dam all the way down to Ft. Quitman, TX.
This includes water for farmlands in the Rincon Valley of Southern New Mexico, the Mesilla
Valley from Las Cruces, NM to El Paso, TX, and the El Paso Valley in El Paso County, TX. The water is used by farmers in Southern New Mexico, El Paso County, TX, and Hudspeth County,
TX, as well as the city of El Paso for drinking water, and the country of Mexico for irrigation
(EPWU, 2015). The water supply from the Rio Grande is extremely critical for farmers and the city of El Paso. The river diminishes the necessity to pump groundwater in order to supply the city of El Paso with drinking water, and for the livelihood of farmers in this region. In the desert southwest, the river is critical for meeting all water needs. Using river water for irrigation also helps flush the salts out of the croplands, which improves crop quality and quantity.
Groundwater is generally considered to be more saline in this region, and could affect the quality and quantity of crops. It can also make the farmland soil saltier. Scofield states that “The use of irrigation water containing a high percentage of sodium tends to impair the physical condition of the soil whereas the use of water having a low percentage of sodium tends to maintain a good physical condition or to improve a poor physical condition that has been caused by the deflocculation of the clay fraction” (Scofield, 1938, p. 5). Wilson and others summarize the water quality in the region. “The dissolved solids in groundwater at moderate depths in the
Rincon and Mesilla Valleys may average about 1,000 ppm, with 35 to 50 percent sodium. This water is suitable for irrigation, but not as good as river water, being classed as good to permissible. The quality of the water is poorer at the lower ends of the Rincon and Mesilla
Valleys than at the upper ends, except in the vicinity of Radium Springs. In general, deeper wells
5 in the Mesilla Valley supply better water except in the lower end of the Mesilla Valley where the quality apparently becomes worse with depth” (Wilson and others, 1981).
The amount of water allowed to be delivered in this section of the Rio Grande depends on the total water supply available and stored in Elephant Butte and Caballo Reservoirs for the season. The deliverable water amount also depends on the snowmelt runoff forecasts and the forecast at the Rio Grande at San Marcial, NM gaging station, as well as current credits or debits as per the Rio Grande Compact. Different entities up and down the river from the state of
Colorado to Hudspeth County all share the water according to the rights they have to it. Different treaties, laws, and compacts allow for the allocation of water to different entities. Federal, state, and local agencies all take part in accounting for the water that gets delivered and transferred.
1.1. HISTORICAL BACKGROUND OF THE RIO GRANDE PROJECT
Historically, the annual Rio Grande water supply has been through both plenteous and scarce periods since the inception of the project. Hamilton and Maddock, 1993 state that the average inflow into Elephant Butte Reservoir from 1915 to 1990 was 872,588 acre-feet with a standard deviation of 537,969 acre feet (coefficient of variation equals 0.62). "This high standard deviation reflects the incredibly variable nature of annual precipitation events and runoff within the region" (Hamilton and Maddock, 1993). The water from the river depends on snowmelt from the Southern Colorado Rocky Mountains as well as the mountains in Northern
New Mexico. This hinges on the amount of precipitation, mainly snowfall that falls in these mountains. Therefore, it can be said that the climate has been oscillating through wet and dry periods since the creation of the Project (Figure 3). For example, during the early 1940’s, the Rio
Grande experienced some of the highest flows in recent history. Then, in the 1950’s, a severe drought set in, and the river was reduced to meager flows. This caused a lot of worrying for
6 farmers and municipalities who depended on the river. Thus, many resorted to pumping water from the ground since the unreliability of the water supply of the river was realized (Frenzel and
Anderholm, 1992). This also led the El Paso Water Utilities to purchase more land for water rights, and drill many more wells since the reduced river flows were unexpected and caused a shortage for the city of El Paso. Then, the river experienced another upsurge in supply in the
1980’s and 1990’s. In the 2000’s, the river went through a series of droughts peaking in 2013.
Throughout droughts, farmers and municipalities rely heavily on groundwater, which further reduces the groundwater levels and groundwater storage in the region.
Rio Grande Below Caballo Flows and Diversions
2,000,000 Rio Grande Below Caballo Flows Total Diversions 1,800,000
1,600,000
1,400,000
1,200,000 Acre Feet 1,000,000
800,000
600,000
400,000
200,000
0 1915 1935 1955 1975 1995 2015 YEAR Source: internal data from U.S. Bureau of Reclamation – El Paso (unpublished)
Figure 3. Rio Grande below Caballo Annual Flows and Diversions, 1918 to 2014
(USBR, internal)
1.2. DIVERSION RATIO
One of the aspects of the agreement and the water accounting for the project is a parameter called the “diversion ratio”. The diversion ratio is simply the total diversion flows
7 divided by the total water released from Caballo Reservoir (Figure 3), which is located about 30 miles below Elephant Butte Dam. This is called the “raw” diversion ratio and is shown in Figure
4. Since the inception of the Operating Agreement of 2008 (USBR, 2015), the calculation of the official diversion ratio changed, but it has not been different from the “raw” diversion ratio in recent years (personal communication with Filiberto Cortez of Reclamation, 2015). The diversion ratio is an indicator of how efficient of the lower Rio Grande.
1.600
1.400
1.200
1.000
0.800
0.600 Diversion Ratio
0.400
0.200
0.000 1900 1920 1940 1960 1980 2000 2020 Calendar Year
Source: internal data from U.S. Bureau of Reclamation – El Paso (unpublished)
Figure 4. Diversion Ratio since 1918 (Appendix A)
The diversion ratio has steadily stayed above 1.0 since the beginning of the Rio Grande
Project, with an average diversion ratio of 1.18 from 1919 to 2010 (Figure 4). Some exceptions were the early years of the project from 1918 to 1922, 1956, 1978, and the wet years of 1986 and
1987. This means that historically, there has been more water diverted downstream at the delivery points than the volume released from Caballo Reservoir, and that there were accretions in the river system. The accretions were due to return flows from drains that were
8 supplementing the river flow (Figure 5). However, recently, from 2003 to 2014, the diversion ratio has been creeping lower and lower below 1.0. This means that the losses have been steadily increasing in the river system. These losses are calculated after the season, and can be troublesome for water managers who forecast a certain amount of water to be released, but less water is able to be diverted to the farmers and municipalities later on in the year. Currently, the previous year’s diversion ratio is used to forecast the present year’s diversion ratio, or estimated losses or accretions.
Figure 5. Diversion Diagram of Applied Irrigation and Return Flows (Esslinger, 2008)
Even during the fluctuations of river flows of the last century, the diversion ratio has remained consistently around 1.0 for the history of the project, either above or slightly below
(Appendix A & Figure 4). The reason that the diversion ratio goes above 1.0 is due to the system of drains that allow for return flows (Figure 5). One of the purposes of the drains is to collect excess salts so that agricultural crops are not harmed by water logging or excess salinity
(Weeden and Maddock, 1999). This system of drains allows for the return of irrigation water
9 from irrigated fields and canal seepage, as well as groundwater seepage to reenter the river system once again during periods where groundwater levels are higher. In other words, the efficiency of the river system has been above 100% for the majority of the Project history. This may also have been due to the lower groundwater pumping that had occurred in the Rio Grande
Valley because of higher flows during wet years and lesser demand during the drought years of the previous century as opposed to the drought of this century. The lower demand may have been due to a lower population in the region during the past century. “The significant increase in population within the Mesilla groundwater basin and adjacent areas has resulted in competition for existing groundwater resources” (Nickerson and Myers, 1993). Also, the operating agreement, which was enacted in 2008, adjusts allocations of surface water to account for increased groundwater pumping by New Mexico farmers at the cost of less surface water deliveries. As groundwater pumping across the region rises during drought years in order to alleviate the reduced surface water allocations, the groundwater levels drop and more surface water losses occur in the river. The New Mexico farmers are then forced to turn to groundwater to make up the difference due to the reduction in Project surface water (Bushnell, 2013) and even more surface water losses occur resulting in a downward spiral of surface water losses for
Southern New Mexico farmers.
1.3. CURRENT CONDITIONS
Currently, since 2010, for the first time in the history of the Rio Grande Project, the diversion ratio has been consistently falling below 1.0, even falling as low as 0.66 in 2013, the lowest recorded diversion ratio since 1922. This has raised some concerns and eyebrows as to why the river system’s efficiency has fallen this low due to the historical astounding efficiency of the river. Even during the severe drought of the 1950’s, the lowest recorded diversion ratio
10 during this period was 0.95 in 1956. The only other time this happened was during the 1918 to
1922 period, which also saw an unusual period of low diversion ratios, one as low as 0.27 in
1919. After this period, the diversion ratio has been above 0.94 up to the year 2004 when it dropped to 0.84, then back up to 0.95 and above for the next six years to 2010, before falling consecutively during the drought years of 2011 to 2014 (Appendix A & Figure 4). This means that there is more water being lost in the river system. The reasons for this points to groundwater levels, and/or increases in groundwater pumping. According to Nickerson and Myers, 1993,
“groundwater pumping for irrigation of crops accounts for much of the annual groundwater withdrawal in the Mesilla Valley” (Nickerson and Myers, 1993). This creates a problem for water managers who work with farmers to allocate irrigation water based on supply. With a declining diversion ratio, less water will be able to be allocated to farmers and municipalities, specifically the El Paso Water Utilities, than what is released.
1.4. GOALS AND OBJECTIVES
The purpose of this study was to find factors and possibly predictors for the losses in the river system, and to generally assess the water budget and water use in the Rincon and Mesilla
Valleys. These factors and predictors could aid water managers in making decisions that could improve efficiency in the Rio Grande Project and help stakeholders in the region who depend on the river. Specifically, a predictor for the current year’s diversion ratio or losses would help water managers make predictions as to how efficient the river will behave each season. A predictor for the diversion ratio in the river would be a good management tool for water managers to use for an upcoming season so that farmers and stakeholders can better plan crop cycles and choices, and water usage. It would be beneficial for many planning engineers in the municipal water industry, as well as those in the agricultural industry who can plan which crops
11 to plant, and to ascertain how much groundwater may be needed to be pumped in order supplement surface water deliveries.
12 2. METHODOLOGY
For this study, Microsoft Excel was used for the regression analysis of many comparisons. Aquarius Time-Series software by Aquatic Informatics was also used for compiling data into annual averages.
2.1. RIO GRANDE PROJECT WATER BUDGET
The water budget for the Rio Grande Project begins each year with the amount of water stored in the Elephant Butte and Caballo Reservoirs. Then Rio Grande Compact credits and debits for Colorado and New Mexico are also taken into account. The budget is sent out to the districts and Mexico, and a certain amount of water is allocated to all water rights owners within each district. Every water rights owner within each district gets an equal amount of water per acre based on the amount of project water available, regardless of total land area per water user.
The average release for accounting purposes under the Rio Grande Compact is
790,000 acre-ft/yr. This is considered a full allocation for a given irrigation year. According to the D-2 curve mentioned in the 2008 Operating Agreement (USBR, 2015), a release of 763,840 acre-ft will deliver 931,840 acre-ft to the diversions under normal conditions (i.e., a diversion ratio of 1.22). The D-2 curve was constructed using data from water years 1951 to 1978. This is also about the same as the average diversion ratio for this time period (Appendix A).
Mexico’s allotment is first subtracted (USBR, 2015). Then, the project water is split between EBID and EP#1. EBID gets 57% of the project water, and EP#1 gets 43%, according to the Operating Agreement of 2008 (USBR, 2015). This ratio is based on the amount of irrigated lands within each district within the Rio Grande Project. EBID has 89,310 authorized acres, and
EP#1 has 68,200 authorized acres (Figure 2). The Operating Agreement of 2008 changed this
13 allocation percentage by allowing the districts to receive a limited amount of carry-over project water for future years (Bushnell, 2013
An equation for the flow of water at the Rio Grande at El Paso gaging station may be described beginning with the releases at Caballo Reservoir (Figure 2). Then, the river is diverted at the major diversion points beginning with Percha Dam about one mile downstream of Caballo
Reservoir, followed by Leasburg Diversion Dam, Mesilla Diversion Dam, and finally American
Diversion Dam which diverts water to Mexico and to the Lower Valley in the city of El Paso,
TX. The Rio Grande at El Paso gaging station is about one mile upstream from the American
Diversion Dam. Therefore, the flow differences between the Caballo gaging station and the El
Paso gaging station is the water that is used in the Mesilla and Rincon valleys. Downstream of the El Paso gaging station, American Dam splits water for Mexico and farmers in the Lower
Valley of El Paso, TX. A simple equation of water in the Rio Grande Project would be:
Equation 1. Rio Grande at El Paso Flows (RGEP) = Caballo Release (RGBC) +
Precipitation/Runoff + Return Flows + Groundwater gains – Diversion flows
above RGEP gage – Groundwater losses and withdrawals – Evapotranspiration.
The City of Las Cruces pumps about 19,000 ac-ft/yr from the Mesilla Bolson (Soular,
2012) and returns about 10,000 ac-ft/yr of treated sewage effluent to the river (City of Las
Cruces, 2015). According to Weeden and Maddock (1999), “Analysis of the water budget for a single season can be very misleading. The water budget is strongly dependent on the volume of water released from Caballo Reservoir and does vary greatly from season to season and often varies significantly year to year.”
14 450,000 Difference vs Reservoir Release 1938-2013
400,000 1995 1994
350,000 1998 20051958 1986 1960199620012002 198219852000 197319832009 199719931945 198019891948 300,000 1965 19662007197019691959 1987 198420102008 1990 1943 198119621976194019991939 194719461988 195319521961 1992 1957 19711963197919911974 1944 250,000 19491950 2012 1968 1942 1938 1967 1975 20041951 200,000 19781977 1956 2003 1941 y = -2E-07x2 + 0.5109x + 43878 AnnualDifference (acre ft) 2011 R² = 0.6827 2006 150,000 19551954 1964 1972 2013 100,000
50,000
27000 27000
0 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 Reservoir Release
Figure 6. Plot of Annual Differences Between RGBC (USBR - internal) and
RGEP (IBWC, 2014), and RGBC Releases
2.2. DIVERSION RATIO
The groundwater levels used for this study were the LC-2 and LC-3 sections of groundwater wells A-A’ (Figure 7 & Figure 8) managed by the USGS within the city of Las
Cruces, NM. The equations for the diversion ratios can be written as;
15 Equation 2. Diversion Ratio (Pre Operating Agreement) = Total Diversion Flows /
Total Caballo Release
Equation 3. Diversion Ratio (Post Operating Agreement) = Total Charges to Mexico,
EBID, and EP#1 / Total Caballo Release
The diversion ratios before the enactment of the Operating Agreement of 2008 were calculated by summing the annual diversions in acre feet measured at the main diversion points.
This would have included return flows from drainage canals throughout the year. The main diversions were the diversion to Mexico, Leasburg Canal, Westside Canal, Eastside Canal, Del
Rio Lateral, Riverside Canal, and Franklin Canal (Appendix A). When the Operating Agreement was enacted in 2008, the calculation of the diversion ratio was changed to Equation 3. The total charges were only for the irrigation season, and not the entire year as before. As mentioned earlier, the diversion ratio in the Operating Agreement has not been much different from the
“raw” diversion ratio in recent years (personal communication with Filiberto Cortez of
Reclamation, 2015).
In this study, the raw diversion ratios were calculated using Appendix A for years 1918 to
2009. In years 2010 to 2014, the diversion ratios from Appendix E were used and were also confirmed with Filiberto Cortez of Reclamation.
16
Figure 7. Map of USGS Mesilla Basin observation-well network in New Mexico and
Texas. LC well section is labeled A – A’ here (USGS, 2015)
17
Figure 8. USGS Las Cruces Well Field (USGS, 2015)
18 The Mesilla groundwater basin observation well network was established in 1983 to monitor groundwater levels. The Las Cruces observation well section is at the western edge of the City of Las Cruces, NM. Observation well groups at the Las Cruces hydrologic section are completed in the Rio Grande flood-plain alluvium/Santa Fe Group aquifer system at depths ranging from 30 to 327 feet below land surface. The shallow floodplain alluvium LC-C wells are at depths ranging from 30 to 45 feet below land surface. The LC-B wells are completed in the
Santa Fe Group at depths ranging from 95 to 115 feet below land surface. The LC-A wells are also completed in the Santa Fe Group at depths ranging from 295 to 327 feet below land surface
(Figure 8). Water levels in the LC-B and LC-A wells represent the potentiometric head at depth within the upper Santa Fe Group (Nickerson and Myers, 1993). Estimated aquifer thickness at the Las Cruces hydrologic section is about 3,800 feet (Hawley, 1984, pi. 6). Wells LC-2F and
LC-3D are about 700 feet deep (Figure 8) and are in a section from 400 feet to 1400 feet below the water table where sand and gravel are most common, followed by silt and clay sediments
(Wilkins, 1998; Myers & Orr, 1985).
These wells were chosen because the data collected from these wells is continuous and instantaneous, and in some cases, goes back to 1985. Also, this data goes through a thorough review process. Only these sections from the USGS Mesilla Groundwater Monitoring network contained real-time continuous data up to 2014. Other sections contained groundwater level measurements, but were sporadic and not continuous. The LC-1 well section had instantaneous data only up to 2010. Therefore, the data from the other sections would not represent a fair average of the changing groundwater levels throughout a given year, or take into account the lower diversion ratios in recent years. The data from 1985 to 2011 has been reviewed and approved by the USGS. Thus, more data was available from these sections in order to study this
19 correlation. At the time of this analysis, groundwater data in years 2012, 2013, and 2014 were not yet reviewed by the USGS and were considered provisional.
The diversion ratio was compared with the annual average groundwater depths of all LC-
2 and LC-3 wells. Some wells such as LC-2B, LC-2F, and LC-3D had missing data for a number of years, and/or had missing data during some of the year making the averages unrepresentative of an actual annual average (Error! Reference source not found.). Therefore, these wells were not considered to be accurate for analyzing the connection between the diversion ratio and groundwater levels. The diversion ratios for years 1986, 1987, and 1995 were not used in this analysis due to the unusually high releases during these years, which would have decreased the diversion ratio because of the higher wastes of water during these years, and would not be representative of a “normal” year of a full allocation of around 700,000 acre feet where water would be used more efficiently (Appendix B). Two separate correlations were reviewed for each well using only the approved data by the USGS, and the other including the approved and provisional USGS data. Incomplete averages were not included in these evaluations. Averages were considered to be incomplete if there were a few months of data gaps for a given year.
Also compared were the release amounts and diversion ratio, the groundwater levels for well LC-2A and release amounts, the previous year’s release amounts and diversion ratio, as well as the previous year’s release amount and groundwater levels for well LC-2A, all from 1985 to
2014.
2.3. WATER USE FROM CABALLO GAGING STATION TO EL PASO
GAGING STATION
The difference in annual flows between Rio Grande Below Caballo gaging station and the Rio Grande at El Paso gaging station was analyzed. This gives an impression of the
20 evapotranspiration in this reach as mentioned in the water budget above. This reach includes both the Rincon and Mesilla valleys. Figure 9 is a graph that shows the flows, the differences, and percent differences between the two gages. It further shows that there seems to be a correlation between release amounts and percent differences between the two gages. When there are higher releases from Caballo Reservoir, the percent difference between the two gages is small, but when there are lower releases, the percent difference is higher. This means that a higher percentage of the total release is used in these valleys during lower flows, and a lower percentage of the release is used when the flows are higher. A regression analysis was performed on percent difference and Caballo release flowrates in cubic feet per second (cfs) and volumes in acre-feet (ac-ft).
Figure 9. Caballo Release (blue), Rio Grande at El Paso flows (red), Caballo minus El
Paso flows (purple), and Percent Difference between Caballo and El Paso flows (green),
1938 to 2013 (data for Caballo from USBR,internal, data for El Paso flows from IBWC,
2015). 21 2.4. PRECIPITATION
Precipitation in this river section regards precipitation that falls in the Lower Rio Grande
Project area, and not total Rio Grande Basin precipitation. The climate of the area can be described as dry and hot. Using climate data from the Western Regional Climate Center ("EL
PASO WSO AP, TEXAS.") for El Paso, TX, the average annual rainfall is 8.56 inches, with most precipitation occurring during the monsoon season that runs from July through September.
“Precipitation events during this time period are usually due to convection and result in brief, heavy rainfall” (Weeden and Maddock, 1999).
Could precipitation amounts in the region influence the diversion ratio? The precipitation data going back to 1945 was observed using precipitation data acquired from NOAA. The precipitation gage used for this site was in Las Cruces, NM. Annual precipitation volume was simply estimated using the measured annual precipitation multiplied by the total acreage in the
Rincon and Mesilla Valleys (Appendix B). Infiltration and evaporation of precipitation was not taken into account for this analysis. This precipitation volume was compared with the difference in flows between the Caballo and El Paso gaging stations. Also compared was the estimated precipitation volume with the diversion ratio.
22 3. RESULTS
3.1. RIO GRANDE PROJECT WATER BUDGET
Looking at Figure 6, the highest difference between the Caballo and El Paso flows from 1938 to
2013 occurred in 1995 with a difference of about 394,000 acre feet. Taking into account
Canutillo well field pumping by the El Paso Water Utilities of about 23,000 acre feet for 1995 and City of Las Cruces estimated usage of 9,000 acre feet using current data, potential evapotranspiration between RGBC and RGEP could be estimated at about 362,000 acre feet. If estimated precipitation volume is also taken into account, 63,884 acre feet in 1995 (Appendix C), then the potential evapotranspiration could be about 298,000 acre feet. Some of this may be regarded as seepage that recharges the groundwater aquifers. However, since this maximum occurred in 1995 during a high release season when groundwater levels in Las Cruces, NM were higher (Appendix B) and thus groundwater storage could have been considered “normal,” groundwater recharge to the aquifers in 1995 may be considered negligible.
According to Nickerson and Myers, much of the applied irrigation water is intercepted by evapotranspiration before it reaches the water table. “Discharge from evaporation occurs from freestanding water surfaces in irrigated fields and conveyance channels” (Nickerson and Myers,
1993). Evapotranspiration is considered a major source of discharge from the Mesilla Valley
(Peterson and others, 1984, p. 39). One study concluded that average on-farm efficiency in the
Mesilla Valley is 64% and EBID conveyance efficiency of 54% for years 2008, 2010, and 2011
(Rasool and others, 2013).
From 1938 to 2013, the average annual Caballo Release is 656,000 acre feet, the average
El Paso flow is 388,000 acre feet, the average difference is 268,000 acre feet, the average
Canutillo Well field withdrawal is 19,000 acre feet per year, and the latest average Las Cruces
23 usage is about 9,000 acre feet per year. Therefore the average evapotranspiration for this reach could be estimated at around 240,000 acre feet per year. Adding an annual precipitation average volume of 74,177 acre feet (Appendix C), this average is 166,000 acre feet per year. Liu and
Sheng calculated that 288,000 acre feet per year are consumed in this reach per year (Liu and
Sheng, 2011).
3.2. DIVERSION RATIO CORRELATIONS
3.2.1. CORRELATIONS WITH GROUNDWATER LEVELS
A correlation was discovered between the diversion ratio and groundwater levels in the
Mesilla Valley Region of Southern New Mexico. The correlation acknowledges that groundwater levels play an important role in the losses in the river. Better collection of well data will need to be ensured, and further future analysis of this correlation will need to be performed if this correlation is used for predicting future diversion ratios in this river system.
Some graphs below show an instant connection between annual average groundwater levels and the diversion ratio (Figure 10-13). These show the gradual groundwater levels declines as well as the gradual decrease in the diversion ratio. It can be seen that there is a correlation between the two (R2 > 0.8). Also, when the groundwater levels decline suddenly as in
Figure 11, the diversion ratio will decline suddenly as well.
24
Figure 10. Well LC-2A, Depth to Groundwater (USGS, 2015) & Diversion
Ratio (USBR, unpublished)
Figure 11. Well LC-2C, Depth to Groundwater (USGS, 2015) & Diversion
Ratio (USBR, unpublished)
25
Figure 12. Well LC-3A, Depth to Groundwater (USGS, 2015) & Diversion Ratio (USBR,
unpublished)
Figure 13. Well LC-3C, Depth to Groundwater (USGS, 2015) & Diversion Ratio (USBR,
unpublished)
26
The results for the correlations between can be seen in Figure 14 to 17 and Appendix D.
The figures with the higher correlations were placed in the text, while the figures with the lower correlations were placed in Appendix B. From these results, the best fit models occur for wells
LC-2A (Figure 14 & Figure 15) especially when including the USGS provisional data, followed by wells LC-3A (Figure 16 & Figure 17) and LC-3C (Appendix D). Wells LC-2A, LC-3A, and
LC-3C are well represented by a linear fit model, as opposed to LC-2C (Appendix D) which is best represented by a power fit trend. Well LC-2B (Appendix D) had high r-squared results, but there were not enough data points to conclude that it is an accurate predictor for diversion ratios.
Well LC-3C had high r-squared results, but an analysis that included the provisional data could not be performed because years 2012, 2013, and 2014 were considered to be incomplete averages (Appendix B). Groundwater levels in all wells for year 2012 were considered to be incomplete averages. This may have been due to funding shortages for data collection. It can be seen from Error! Reference source not found. that wells LC-2B, LC-2F, and LC-3D had many years of missing data, and therefore an accurate analysis for these wells could not be performed.
The r-squared values for wells LC-2F and LC-3D are not high and should be ignored. Again, the diversion ratios for years 1986, 1987, and 1995 were not used due to higher than average releases which would have led to greater wastes in the river system and lower diversion ratios (Appendix
B).
27 (a)
(b)
Figure 14. Well LC-2A; Diversion Ratio (USBR, unpublished) correlation with
(a) Current Year Depth to Groundwater (USGS) and (b) Previous Year Depth to
Groundwater (USGS), 1985 to 2011 (only USGS-approved water level data)
28 (a)
(b)
Figure 15. Well LC-2A; Diversion Ratio (USBR, unpublished) & (a) Current Year Depth
to Groundwater (USGS, 2015)), 1985 to 2014. Diversion Ratio (USBR, unpublished) &
(b) Previous Year Depth to Groundwater (USGS, 2015), 1985 to 2013 (approved and
provisional data)
29 (a)
(b)
Figure 16. Well LC-3A; Diversion Ratio (USBR, unpublished) & (a) Current Year Depth
to Groundwater (USGS, 2015), 1985 to 2011 Well LC-3A; Diversion Ratio (USBR,
unpublished) & (b) Previous Year Depth to Groundwater (USGS, 2015), 1985 to 2011.
(only USGS-approved water level data)
30 (a)
(b)
Figure 17. Well LC-3A; Diversion Ratio (USBR, unpublished) & (a) Current Year Depth
to Groundwater (USGS, 2015), 1985 to 2014, Diversion Ratio (USBR, unpublished) &
(b) Previous Year Depth to Groundwater (USGS, 2015), 1985 to 2013 (approved and
provisional data)
31
To summarize, LC-2A (Figure 14 & Figure 15) had the highest r-squared values for correlating the diversion ratio from current year and previous year groundwater depths. The r- squared results were 0.87 and 0.81, respectively, using only the approved USGS data, and 0.92 and 0.86, respectively, which included the USGS provisional data for years 2013 and 2014. The best prediction of the diversion ratio was with LC-2A with USGS approved and provisional data with an r-squared value of 0.92 (Figure 15(a)), and the correlation is shown in Equation 4:
Equation 4. Diversion Ratio = 1.5847 – 0.0252 (LC-2A depth to groundwater in feet)
Well LC-3A (Figure 16 & Figure 17) had the next best results with current and previous year groundwater depths and diversion ratio correlations at 0.81 and 0.80 respectively, and 0.89 and 0.84 respectively which include the USGS provisional data for years 2013 and 2014. Well
LC-3C (Appendix D) also had high results at 0.81 for both current and previous year’s groundwater levels using only the approved USGS data, but provisional data for years 2013 and
2014 could not be included because of incomplete averages for these years. It would be interesting to compare groundwater levels and diversion ratios in the future for well LC-3C if more complete data is available. This is also the case for LC-2B, LC-2F, and LC-3D (Appendix
B). Well LC-2C (Appendix D) had high power fit correlations for current year groundwater levels and diversion ratios at 0.86 for approved data only, and 0.88 including provisional data.
However, the previous year’s correlation was at 0.69 for only approved data, and 0.63 which included provisional data.
3.2.2. CORRELATIONS WITH RELEASE VOLUMES
Figure 18 shows the diversion ratio and release from 1938 to 2013. From this figure, it can be seen that the releases from 1938 to 2013 do not play a significant role in affecting the
32 diversion ratio overall, with an r-squared value of 0.13. There are stronger correlations for release amounts and the diversion ratio (Figure 19) and for the release amounts and groundwater levels from 1985 to 2014 (Figure 20), with an r-squared value of 0.61 and 0.56 respectively, but not enough to conclude that there is a strong correlation. An analysis of earlier release amounts and groundwater levels could not be made because the groundwater level data for the USGS
Mesilla Groundwater Section does not extend far back enough for this analysis. 1985 is the earliest year that instantaneous and continuous groundwater levels data begins.
Figure 18. Diversion Ratio & Release, 1938 to 2013 (USBR, internal)
33 (a)
(b)
Figure 19. Diversion Ratio & (a) Release, 1985 to 2014, Diversion Ratio & (b) Previous
Year’s Release, 1985 to 2013 (USBR, internal)
34 (a)
(b)
Figure 20. Groundwater Levels (USGS, 2015) & (a) Release (USBR, internal) 1985 to
2014, Groundwater Levels (USGS, 2015) and (b) Previous Year’s Release (USBR,
internal), 1985 to 2013
35 3.3. WATER USE FROM CABALLO GAGING STATION TO EL PASO
GAGING STATION
A linear regression had an r-squared value of 0.685 for the percent difference, and an exponential regression shows an r-squared of 0.76 for the percent difference and release (Figure
21). The percent difference results are identical in both acre feet and cfs. This shows that there is a correlation between release amounts and percent differences between the two gages. Figure 21 shows that as releases are low, the percent differences between the two gages are higher, and that they taper down as releases increase. This may show that there is a required amount of water that must be lost in these valleys before the percent differences go down. With declining groundwater levels and storage, more water will have to be “lost” in order to return to “normal” conditions.
The plot of releases versus the absolute differences of the two gages (Figure 6) shows that the maximum difference or maximum evapotranspiration/usage in the two valleys occurred in the years of the mid to late 1990’s and 1986. The maximum evapotranspiration of about
400,000 acre feet occurs at a release of around one million acre feet. However, the percent difference for this amount of release is about 32% (Figure 21). The highest percent differences occur at releases around 100,000 acre feet.
36
Figure 21. Percent Difference of Caballo Release and El Paso flows versus Caballo
Release, 1938 to 2013 (USBR, internal & IBWC, 2014)
3.4. PRECIPITATION
No high correlation or r-squared value was found between the two comparisons. The r- squared values were 0.06 for precipitation volume and percent difference (Figure 22), and 0.004 for precipitation volume and absolute difference (Figure 22). Precipitation runoff helps increase the diversion ratio because Caballo releases will be cut when there is significant runoff and the water from precipitation reaching the river is diverted. However, based on this analysis, estimated precipitation runoff in this area does not have a great impact on the overall diversion ratio (Figure 23).
37
(a) Precipitation Volume vs % Difference 0.90 0.80 y = -1E-06x + 0.5305 0.70 R² = 0.0557 0.60 0.50 % Difference Regression 0.40 Series1 0.30 0.20 Linear (Series1) 0.10 0.00 0 50000 100000 150000 200000 Precipitation Volume (Acre ft.)
(b) Precipitation vs Absolute Difference 450000 400000 y = 0.1502x + 258631 R² = 0.0036 350000 300000 Absolute Difference 250000 Regression (Acre ft.) 200000 Series1 150000 Linear (Series1) 100000 50000 0 0 50000 100000 150000 200000 Precipitation Volume (Acre ft.)
Figure 22. Precipitation (NCDC, 2014) Volume and (a) Percent Difference of Caballo and
El Paso Flows (USBR, internal and IBWC, 2015) Precipitation (NCDC, 2014) Volume
and (b) Absolute Difference of Caballo and El Paso Flows (USBR, internal and IBWC,
2015)
38
Figure 23. Precipitation (NCDC, 2014) Volume and Diversion Ratio (USBR, unpublished)
39 4. DISCUSSION
4.1. DIVERSION RATIO SYNOPSIS
This study indicates that the diversion ratio is best predicted by the groundwater levels in the LC-2 and LC-3 well sections of the northern Mesilla Valley. This is also the area where the greatest losses occur in the whole section as discussed below. It can also be expected that the higher the release, the lower the percent difference between the Caballo gaging station and the El
Paso gaging station. Wells LC-2A and LC-3A had the highest r-squared values for predicting the diversion ratio using the previous year’s average groundwater depth. The r-squared values for current years in Wells LC-2A, LC-2C, LC-3A, and LC-3C were all above 0.80, with LC-2A having the highest r-squared value at 0.86 and 0.92 which included provisional data from the
USGS. This means that the groundwater levels in this reach have a correlation with the final annual diversion ratio.
Wells LC-2B and LC-3C should not be regarded for predicting current diversion ratios due to the absence of good data even though the r-squared values were considered high. Further evaluation of Wells LC-2B and LC-3C will have to be done when enough complete current data is gathered in order to confirm whether or not these wells are an accurate indicator of predicting diversion ratios. This is also the case for all of the wells.
The correlation between river losses and groundwater levels could be explained by
Darcy’s Law (Q = KA (h1-h2)/L) which states that the larger the difference between the heads h2 and h1, the larger the flow. In this case, h1 would represent the river levels, and h2 would represent the groundwater levels. If h1 is fairly consistent and does not change significantly, but h2 does decrease significantly, then this will increase the difference between h1 and h2 and hence will increase the vertical flow from the river, canals, and drains to/from the groundwater.
40 This is the case for different groundwater levels between aquifer depths (Figure 29-32,
Appendix D), and for horizontal flow for groundwater levels for wells of the same depth at distances away from the river (Figure 33, Appendix D) as discussed below. The recharge flow will also depend on the hydraulic conductivity (K) of the aquifers, which further depends on aquifer grain size. In all, this means that the losses from the river will increase as groundwater levels decrease.
When water is applied to the fields, a portion of this water seeps into the shallow groundwater and is returned to the system by the irrigation drains (Figure 5). The drain return flow allows water reuse that increases the efficiency of the river system above 100%. However, when groundwater levels decline, drains no longer flow or flow more slowly and less water returns to the river. Likewise when farmers, municipalities, and industries pump from the aquifer, the major effect is lowered drain flows with increased seepage to the aquifers from the river and canals to a smaller extent.
4.2. RINCON AND MESILLA VALLEY AQUIFER SYSTEMS
The two main groundwater basins along the Rio Grande in this reach are the
Palomas/Rincon and Mesilla basins (Wilkins, 1998). The Jornada del Muerto basin is separated from the Mesilla basin by the Jornada fault zone (Seager and others, 1987), but there may be some water passing through the fault zone (Nickerson and Myers, 1993). Little underflow enters the Mesilla Valley through the alluvium from Selden Canyon in the Rincon Valley (Frenzel,
1992). It is estimated that there are 50 million acre feet of groundwater storage in the top 100 feet of saturated basinfill in the Mesilla, Jornada, and Palomas/Rincon groundwater basins (Cook and Balleau, 1998). One study describes the Rincon and Mesilla Valleys to be gaining reaches using a trend-outflow method, but concluded that more studies are needed for this method (Liu
41 and Sheng, 2011). Weeden and Maddock state that the Rio Grande is predominantly a gaining stream until roughly five miles north of Mesilla Dam due to the geology of the area at which point it changes to a predominantly losing stream (Weeden and Maddock, 1999). Municipal and industrial pumping is negligible in the Rincon Valley area, while it is a significant portion of groundwater withdrawals in the Mesilla Basin (Wilson and others, 1981). Information on groundwater resources of the Mesilla Basin is abundant; however, data for the Rincon Valley area and Selden Canyon are incomplete (Weeden and Maddock, 1999). In their models, Weedon and Maddock found that municipal and industrial pumping appears to decrease Rio Grande flow, especially towards the lower end of the Mesilla Valley, possibly due to Canutillo Wellfield pumping (Weeden and Maddock, 1999).
4.2.1. RINCON VALLEY
The Rincon Valley where the Palomas basin sits (Wilkins, 1998) is made of flood-plain alluvium which forms a long, narrow, and continuous aquifer two miles wide and about 60 to 80 feet deep. Wilson and others describe that the Santa Fe group in this section is mostly made of a thick sequence of clay that underlies the floodplain alluvium. Recharge to the flood-plain alluvium is from irrigation, seepage from the Rio Grande and canals, precipitation, and surface and subsurface inflows from tributary arroyos. Over many years, the balance between recharge and discharge from this aquifer is about equal. The Rincon Valley groundwater levels may decline as much as 10 feet during years of very little surface water delivery and much groundwater pumping. However, hydrographs show rapid recovery of the water table in those years when large surface water allotments are available. Approximately 540,000 acre feet of fresh and slightly saline water are in storage in the flood plain alluvium aquifer of the Rincon
(Wilson and others, 1981). A seepage study done in 1974 and 1975 in the Rincon Valley shows
42 that the Rio Grande is a gaining reach from Caballo Reservoir to Hatch, NM, and slightly gaining in 1974 and slightly losing in 1975 from Hatch, NM to the southern end of the Rincon
Valley (Wilson and others, 1981).
Terracon and others describe some of the hydrologic behavior of the Rincon Valley.
“Average water levels within the valley do not appear to be decreasing over time, though a significant amount of seasonal fluctuation may occur. Water is replaced fairly quickly in the alluvial aquifer, due to its high transmissivity and proximity to the Rio Grande. Removing water from the floodplain aquifer probably has a larger effect on surface water levels than groundwater levels. Overall, water levels in the shallow aquifer in the valley have fluctuated 2 to 3 feet, but remain essentially constant. Hydrographs of wells, which have water levels exceeding 100 feet, indicate an overall decrease in water levels. Wells with water levels exceeding 100 feet, which have been monitored for more than 20 years, have experienced declines ranging from 1.9 to 3.3 feet per year, with total drawdown ranging from 33 to 94 feet.” (Terracon and others, 2004).
Thus, it can be determined that the Rincon Valley aquifer system is much smaller in scale in comparison to the Mesilla Valley, and that for the most part, it is not considered a significantly losing section of the Rio Grande.
4.2.2. MESILLA VALLEY
The Mesilla Valley is more than 50 miles long and as much as 5 miles wide (Wilson and others, 1981). The Rio Grande floodplain alluvium primarily consists of poorly sorted gravel and coarse to medium grained sand with thin interbedded clay lenses. From 100 to 327 feet below the land surface, the Santa Fe Group primarily consists of alternating layers of coarse to fine grained sand and silty clay with numerous gravel lenses (Nickerson and Myers, 1993). One test hole in the Mesquite area unraveled fluvial deposits in the Santa Fe group about 2,000 feet deep (Wilson
43 and others, 1981). Water in the Rio Grande flood-plain alluvium/Santa Fe Group aquifer system occurs under unconfined and semiconfined (leaky-confined) conditions. Gravel and coarse grained sand within the upper 150 feet of the aquifer have a much greater permeability than deeper sediments of predominantly finer grain size. Horizontal permeability in the aquifer system usually exceeds vertical permeability by several orders of magnitude. The permeability of the aquifer system generally decreases with depth. (Nickerson and Myers, 1993).
Nickerson and Myers state that the “Rio Grande streamflow is a major source of recharge to the aquifer system of the Mesilla Valley. Most recharge to the aquifer system is from Rio
Grande seepage in losing reaches of the stream, seepage from irrigation canals, and infiltration of applied irrigation water” (Nickerson and Myers 1993). Surface water losses in the canals that reach the groundwater table is probably 40 to 60 percent of total conveyance losses (Richardson and others, 1972, p. 61). Conveyance losses from irrigation canals in the Mesilla Valley normally range from 35 to 50 percent of the total diversion of irrigation water from the Rio Grande
(Peterson and others, 1984, p. 28). Seepage rates of losing reaches of the Rio Grande may fluctuate with annual and seasonal variations in streamflow (Nickerson and Myers, 1993).
In their study, Nickerson and Myers observed that “groundwater levels in nearby observation wells in the Mesilla Valley correspond to changes in river stages and indicate significant recharge to the aquifer at the river. The rapid response of groundwater levels to the abrupt rise in river stage indicates a significant hydraulic connection between the river and the shallow flood-plain alluvium. The water table in the aquifer system decreases with distance from the river at the hydrologic sections, which indicates horizontal groundwater flow away from the
Rio Grande. The potentiometric head also decreases with depth below land surface, which indicates a downward, vertical direction of groundwater flow within the aquifer system.
44 Downward vertical hydraulic gradients were recorded in all well groups at the Mesilla Valley hydrologic sections” (Nickerson and Myers, 1993).
Figure 29-32 in Appendix D show the response times of well sections LC-1, LC-2, and
LC-3 to Rio Grande flows in years 1985 and 1986 (Nickerson and Myers, 1993). These graphs show that the farther and deeper the wells are from the Rio Grande, the slower and less significant the response becomes. In 1985 and 1986, “the Rio Grande was in hydraulic connection with the aquifer system and lost or gained water by seepage through the riverbed in the direction of decreasing hydraulic head. Recorded hydraulic gradients from the river to the aquifer identify the Rio Grande as a losing river at the Las Cruces hydrologic section, Mesquite hydrologic section, and Canutillo well-field hydrologic section” (Nickerson and Myers, 1993).
Nickerson and Myers state that from previous seepage investigations conducted during steady low flow conditions, the Rio Grande is usually a losing stream along most of the 62 mile reach in the Mesilla Valley (Nickerson and Myers 1993). In a June 2012 seepage study from
Caballo gaging station to the El Paso gaging station (Gunn and Roark, 2014), it was observed that the most significant losses occur in the Haynor Bridge (Rincon Valley) gaging station to
Mesilla Dam (Mesilla Valley) reach. This was one of four reaches in the study (Figure 34,
Appendix D). Reach number 2, which was from Rio Grande at Haynor Bridge to Rio Grande below Mesilla Dam, had the highest calculated loss at 234 cfs, which according to the study, was considered “substantial.” The LC well fields are located in this reach. In comparison, Reaches 1,
3, and 4 (Figure 34, Appendix D) had losses of 66.8 cfs, 33.0 cfs, and 50.7 cfs, respectively.
Gastelum and others, 2012, point to two areas in the Mesilla Valley where the contour levels suggest high groundwater pumping areas; the city of Las Cruces, and the Canutillo Well Field area. The contour levels along the Rio Grande for years 1998 and 2007 show that the reach near
45 the LC (USGS A-A’) (Figure 7) well section is a losing reach. From studying these contours along the river, the losing reach appears to run from where the Rio Grande enters the Mesilla
Valley to a few miles below the USGS B-B’ well section near Mesquite, NM . River mile reach
1289 to 1299 where the LC well section is located is identified to be where most of the river losses occur in the Mesilla Valley. The Mesilla Valley in general is dominated by losses rather than gains (Gastelum and others, 2012). Slight river gains have been reported in the short upstream reach from Leasburg Dam to about 6 miles north of Las Cruces (Wilson and others,
1981, p. 66) and immediately upstream from the El Paso Narrows in the extreme southern end of the Mesilla Valley (Peterson and others, 1984, p. 29).
Peterson and others say that “during wet years with relatively high streamflow, the groundwater table may rise above the riverbed. Under these conditions, the Rio Grande is considered hydraulically connected to the aquifer; seepage rates are proportional to the hydraulic conductivity of the aquifer and the hydraulic gradient between the river and the groundwater table. During dry years with relatively low streamflow and increased groundwater withdrawals, groundwater levels may drop as much as 10 feet below the riverbed” (Peterson and others, 1984, p. 32). Recently, groundwater levels in well LC-2A have dropped about 22 feet, and 30, 31, and
25 feet in wells LC-3A, LC-3C, and LC-3D, respectively over some years (Appendix B & Figure
33). There is no doubt that the recent drought has contributed to these significant groundwater level drops.
A higher than average release season could potentially raise groundwater levels significantly which would reduce flows from the river to the groundwater over time based on decreasing head differences, and thus reduce river losses and increase the diversion ratio. This should be taken into consideration when planning an irrigation season at time when there is
46 ample storage in the reservoirs and/or there is a forecasted high snowmelt runoff from the Rio
Grande basin mountain ranges. If this is the case, the diversion ratio may potentially increase significantly from one year to another.
4.2.3. PRECIPITATION
Precipitation in the Las Cruces Area did not have a strong correlation with the diversion ratio (Figure 23), or with the difference between the Caballo and El Paso gaging stations (Figure
22). Aquifer recharge from precipitation on the Mesilla Valley floor is not considered significant.
The average annual precipitation for the Las Cruces area is about 8.4 inches. Most of the rainfall that penetrates the soil returns to the atmosphere by evapotranspiration before it reaches the water table (Wilson and others, 1981, p. 7). Some recharge may occur from infiltration along arroyo channels during brief periods of flow after intense rainfall (Nickerson and Myers, 1993).
47 5. CONCLUSIONS
A simple water budget between the Rio Grande below Caballo and Rio Grande at El Paso gaging stations was analyzed in order to find factors that may affect efficiency in this river reach so that an attempt can be made to find predictors for efficiency. An efficiency prediction tool may benefit water managers so that they can make better decisions about how to improve water use in this dry region. Other factors that were analyzed included groundwater levels, release amounts, and precipitation. To summarize, the higher the release from Caballo Reservoir, the smaller the percent differences become between the Rio Grande Below Caballo and Rio Grande at El Paso gaging stations. The maximum estimated evapotranspiration for this reach is at about
298,000 acre feet. However, with declining groundwater levels and groundwater storage, this maximum could increase due to higher recharge rates that would be needed in order to get groundwater conditions back to “normal.” Strong correlations were found between the diversion ratio and groundwater levels in the USGS LC-2 and LC-3 well sections of Las Cruces, NM. The best prediction of the diversion ratio was with LC-2A with USGS approved and provisional data with an r-squared value of 0.92 (Figure 15(a)), and the correlation is shown in Equation 4:
Diversion Ratio = 1.5847 – 0.0252 (LC-2A depth to groundwater in feet)
This correlation affirms that declining groundwater levels are the driving force behind increasing losses in the river system, and are reducing drainage flows that return to the river, all of which lower the diversion ratio. Due to this, seepage from the river and irrigation systems that normally returns to the river via drains is instead replenishing the aquifers. Estimated precipitation runoff does not have a significant impact on the overall diversion ratio, though it may help somewhat increase it.
48 The previous year’s groundwater levels could potentially help water managers estimate what the diversion ratio will be for an upcoming irrigation season. Wells LC-2A and LC-3A had the highest r-squared results for predicting the upcoming irrigation season’s diversion ratio. This may help water managers who work with farmers and other stakeholders in the region to use water more efficiently and would further help prevent financial losses from unexpected water shortages. More data collection of water data in this region is needed so that further studies can be done to more accurately assess the water balance in the river.
The correlation between the diversion ratio and groundwater levels at the LC well section in Las Cruces, NM may be due to the fact that groundwater levels were used from a major losing reach in a section of the Rio Grande. These correlations may change if another reach of the river is deemed to be a major losing reach, or if other reaches begin to have a larger impact in groundwater recharge. Monitoring of water data in this region is crucial for better understanding the dynamics of the river and aquifer system. Other well sections may provide better correlations in the future if there are more well data collection efforts. Since recharge to the aquifer is from the Rio Grande and irrigation (Figure 4), return flows from drainage canals will increase return flows into the Rio Grande and thus will increase the diversion ratio. Since groundwater levels and drainage return flows are linked, studying the relation between the return flows and efficiency should also be considered.
49 REFERENCES
Ahadi, Rasool, Zohrab Samani, and Rhonda Skaggs. 2013. "Evaluating on-farm irrigation efficiency across the watershed: A case study of New Mexico's Lower Rio Grande Basin." Agricultural water management 124:52-57.
Bushnell Esq, Darcy S. 2013 “Texas v. New Mexico and Colorado”, No. CV No. 22O141 ORG (U.S. Jan. 8, 2013).1 Executive Summary Texas wants to sue New Mexico in the U.S. Supreme Court, http://uttoncenter.unm.edu/pdfs/2013-05-16_BushnellTx-NM-Final.pdf
City of Las Cruces. 2015. Web. http://www.las-cruces.org/en/departments/utilities/wastewater- resources Accessed 2015-OCT-26
Cook, M, and P Balleau. 1998. "Groundwater modeling in the lower Rio Grande." 43rd Annual Water Conference Proceedings,‘‘Water Challenges on the Lower Rio Grande.
Crilley, DM, AM Matherne, Nicole Thomas, and SE Falk. 2013. Seepage investigations of the Rio Grande from below Leasburg Dam, Leasburg, New Mexico, to above American Dam, El Paso, Texas, 2006-13. US Geological Survey.
EPWU. 2015. “Juarez Water Officials Visit Water Treatment Plant." El Paso Water Utilities - http://epwu.org/whatsnew/367130731.html. Accessed 2015-OCT-07
Esslinger, Gary L. 2008. Lower Rio Grande Project Operating Agreement: Settlement of Litigation 6, http://wrri.nmsu.edu/publish/watcon/proc53/esslinger. pdf presented at Surface Water Opportunities in New Mexico, WRRI (Oct. 2008)
Frenzel, Peter F, Charles A Kaehler, and Scott K Anderholm. 1992. Geohydrology and simulation of ground-water flow in the Mesilla Basin, Dona Ana County, New Mexico, and El Paso County, Texas, with a section on water quality and geochemistry.
Frenzel, Peter F. 1992. Simulation of ground-water flow in the Mesilla Basin, Dona Ana County, New Mexico, and El Paso County, Texas. US Geological Survey; Books and Open-File Reports [distributor].
Gastélum, Jesús, Zhuping Sheng, and Ari Michelsen. 2012. "Understanding Surface Water and Groundwater Interactions in the Mesilla Basin." World Environmental and Water Resources Congress 2012@ sCrossing Boundaries.
Gunn, Mark A, and D Michael Roark. 2014. Seepage investigation on the Rio Grande from below Caballo Reservoir, New Mexico, to El Paso, Texas, 2012. US Geological Survey.
Hamilton, Susan Lynne. 1993. "Application of a ground-water flow model to the Mesilla Basin, New Mexico and Texas."
50 Hawley, John W, John F Kennedy, and Bobby J Creel. 2001. "The Mesilla Basin Aquifer System of New Mexico, West Texas, and Chihuahua—An Overview of Its Hydrogeologic Framework and Related Aspects of Groundwater Flow and Chemistry." Aquifers of West Texas: Texas water development board, Report 356:76-99.
IBWC. 2014. Rio Grande Historical Mean Daily Discharge Data. Rio Grande Historical Mean Daily Discharge Data. International Boundary and Water Commission..http://www.ibwc.state.gov/Water_Data/histflo1.htm. Accessed 2014-NOV- 03
Liu, Yi, and Zhuping Sheng. 2011. "Trend-outflow method for understanding interactions of surface water with groundwater and atmospheric water for eight reaches of the Upper Rio Grande." Journal of Hydrology 409 (3):710-723.
Myers, Robert Gene, and Brennon R Orr. 1985. Geohydrology of the aquifer in the Santa Fe group, northern west mesa of the Mesilla Basin near Las Cruces, New Mexico. US Geological Survey.
NCDC. 2014. Hourly Precipitation Data Publications - Select State | IPS | National Climatic Data Center (NCDC) (Hourly Precipitation Data Publications - Select State | IPS | National Climatic Data Center (NCDC)) http://www.ncdc.noaa.gov/IPS/hpd/hpd.html;jsessionid=70959E3BAB0EBD686CEF54D D6B4F4E8C?_page=0&jsessionid=70959E3BAB0EBD686CEF54DD6B4F4E8C&state =NM&_target1=Next+%3E Accessed 2014-NOV-16
Nickerson, E. L., and R. G. Myers. 1993a. Geohydrology of the Mesilla ground-water basin, Dona Ana County, New Mexico, and El Paso County, Texas. In Water-Resources Investigations Report.
Nickerson, Edward L, and Robert Gene Myers. 1993b. Geohydrology of the Mesilla ground- water basin, Dona Ana County, New Mexico, and El Paso County, Texas. US Geological Survey, Water Resources Division; US Geological Survey, Earth Science Information Center, Open-File Reports Section [distributor].
Nickerson, Edward L. 1986. Selected geohydrologic data for the Mesilla Basin, Doña Ana County, New Mexico, and El Paso County, Texas. US Geological Survey.
Peterson, David M, Raz Khaleel, and John W Hawley. 1984. "Quasi three-dimensional modeling of groundwater flow in the Mesilla Bolson, New Mexico and Texas."
Richardson, Gary Lee, Thomas G Gebhard, and Willem Brutsaert. 1972. Water table investigation in the Mesilla Valley: Engineering Experiment Station, New Mexico State University.
Scofield, Carl S. 1938. Quality of water of the Rio Grande Basin above Fort Quitman, Texas, analytical data. US Geological Survey;.
51 Soular, Diana Alba. "Increased Groundwater Pumping Stirs Concern." Las Cruces Sun-News. Las Cruces Sun-News, 10 May 2012. http://archive.lcsun-news.com/las_cruces- news/ci_20597247/increased-groundwater-pumping-stirs-concern
Terracon, John Shomaker. 2004. "Inc., Livingston Associates, LLC, Inc., Zia Engineering and Environmental, Inc., and Sites Southwest, 2004." The New Mexico Lower Rio Grande Regional Water Plan.
USBR. 2015. Rio Grande Project Operations. United States Bureau of Reclamation. http://www.usbr.gov/uc/albuq/rm/RGP/ Accessed 2015-DEC-17.
USFW. 2015. Dams and diversions along the Rio Grande (Visuals:) United States Fish and Wildlife Service http://www.learner.org/courses/envsci/visual/visual.php?shortname=rio_grande Accessed 2015-OCT-07
USGS. 2015. Monitoring Network of the Ground-Water Flow System and Stream-Aquifer Relations in the Mesilla Basin, Doña Ana County, New Mexico and El Paso County, Texas (USGS New Mexico Water Projects: Mesilla Basin Monitoring Program) United States Geological Survey http://nm.water.usgs.gov/projects/mesilla/ Accessed 2015- DEC-16
Weeden Jr, A Curtis. 1999. "Simulation of groundwater flow in the Rincon Valley area and Mesilla Basin, New Mexico and Texas."
Wilkins, DW. 1998. Summary of the southwest alluvial basins regional aquifer-system analysis in parts of Colorado, New Mexico, and Texas.
Wilson, Clyde A., Geological Survey (U.S.), and New Mexico. State Engineer Office. 1981. Water resources of the Rincon and Mesilla valleys and adjacent areas, New Mexico, Technical report / New Mexico State Engineer. Santa Fe, N.M.: New Mexico State Engineer.
WRCC. 2015. EL PASO WSO AP, TEXAS (- Climate Summary). Western Regional Climate Center http://www.wrcc.dri.edu/cgi-bin/cliMAIN.pl?tx2797 Accessed 2015-OCT-05
52 APPENDIX A. RIO GRANDE PROJECT DIVERSIONS AND
DIVERSION RATIOS SINCE 1908 (UNPUBLISHED
INTERNAL DATA FROM U.S. BUREAU OF
RECLAMATION – EL PASO)
Franklin Canal Franklin PasoEl Valley
Below Caballo
Rio Grande at Rio Grande
Total Rincon
Arrey Canal Arrey
Rio Grande Rio Grande
and Mesilla Mesilla and
Diversions Diversions
Leasburg Leasburg Riverside Diversion
Westside Westside
Eastside Eastside
El Paso El
Del Rio
Mexico
Lateral
YEAR Valley
Canal Canal Canal Canal
Ratio
Total
1908 107855 107855 1909 158628 158628 1910 95865 95865 1911 155145 155145 1912 127077 127077 1913 109956 109956 1914 190433 42599 233032 1915 157916 82873 240789 1916 184070 157503 61603 120774 523950 1917 220935 149211 89833 459979 1918 696054 60,000 10798 228411 131219 80231 135818 646477 0.93 1919 674237 60,000 118641 178641 0.27 1920 881272 60,000 60085 212799 129937 71663 474484 102956 102956 637440 0.72 1921 979908 60,000 65952 264474 210502 76665 617593 97361 97361 774954 0.79 1922 999175 60,000 87866 298318 243814 80243 710241 132196 132196 902437 0.9 1923 844461 60,000 74243 329889 248511 103701 756344 157390 157390 973734 1.15 1924 1002537 60,000 87735 362321 284394 118598 853048 171580 171580 1084628 1.08 1925 817408 60,000 88931 318986 272019 99394 779330 148760 148760 988090 1.21 1926 761607 60,000 94314 265113 242148 86781 688356 128051 128051 876407 1.15 1927 880961 60,000 105013 256863 251835 92225 705936 138298 138298 904234 1.03 1928 835061 60,000 128279 259698 250064 105479 743520 198694 141648 340342 1143862 1.37 1929 701819 60,000 100005 254346 220364 81300 656015 193462 112425 305887 1021902 1.46 1930 793353 60,000 100028 231088 230507 94409 656032 188713 103595 292308 1008340 1.27 1931 750760 60,000 98577 210655 240188 93735 643155 164307 109827 274134 977289 1.3 1932 831741 60,000 97981 220007 243497 90899 652384 156194 111941 268135 980,519 1.18 1933 826126 60,000 97674 223910 232542 84994 639120 161695 113683 275378 974,498 1.18 1934 803646 60,000 108871 210543 222345 82919 624678 173177 126896 300073 984751 1.23 1935 636387 60,000 66688 123130 159745 55053 404616 131756 114516 246272 710888 1.12 1936 747055 60,000 78413 216715 193914 68015 557057 206300 123558 329858 946915 1.27 1937 758474 60,000 77917 191461 192609 76457 538444 217255 133408 350663 949107 1.25 1938 780334 28,358 79250 206802 202637 78883 567572 554952 278948 137873 416821 1012751 1.3 1939 789059 60,562 84216 230643 222422 90641 627922 511495 282186 142915 425101 1113585 1.41 1940 731890 58,240 80882 218991 199666 81402 580941 453795 269165 141037 410202 1049383 1.43 1941 704258 55,327 72778 139146 182465 73111 467500 511333 283767 132975 416742 939569 1.33 1942 1795948 1943 911923 59,194 105180 219947 226354 90817 642298 631791 365316 173391 538707 1240199 1.36 1944 866234 61,396 108194 204343 215064 88376 615977 611908 316479 149663 466142 1,143,515 1.32 1945 882202 60,039 103797 218160 231874 97898 651729 568798 281730 150490 432220 1143988 1.3 1946 763749 60,129 99656 205686 211093 86775 603210 498009 242019 133648 375667 1039006 1.36 1947 724923 58,006 86789 190633 200108 78730 556260 458727 210902 126670 337572 951838 1.31 1948 741174 60,699 85763 183788 201880 83361 554792 431598 216623 124491 341114 956605 1.29 1949 712235 60,268 87586 188725 205200 88437 569948 463553 242638 127363 370001 1000217 1.4 1950 719338 60,605 89334 193999 196270 83002 562605 472640 220145 126006 346151 969,361 1.35 1951 469455 33,100 55133 100346 126470 50868 332817 252000 109983 87848 197831 563748 1.2 1952 543979 49,900 64798 100576 132704 56243 354321 283618 125181 86586 211767 615,988 1.13
53 1953 528620 37,800 63183 100381 139575 55583 358722 264602 114198 86059 200257 596779 1.13 1954 244155 10,100 26965 50442 90028 37382 204817 93709 27255 43339 70594 285511 1.17 1955 219156 8,200 19918 35500 80769 22592 158779 67067 19285 38628 57913 224892 1.03 1956 246139 7,900 24157 35332 83342 27061 169892 57444 19356 36132 55488 233280 0.95 1957 397092 23,300 35474 121718 124044 33396 314632 139594 44132 69075 113207 451139 1.14 1958 737127 60,100 99100 162547 179556 62933 504136 392830 198437 113104 311541 875778 1.19 1959 687409 60,100 96105 160502 165533 68612 490752 385833 195312 135539 330851 881703 1.28 1960 705161 60,300 98731 155425 173498 70845 498499 378122 203106 145111 348217 907016 1.29 1961 561695 48,600 71708 124477 161082 61903 419170 300823 139336 130167 269503 737273 1.31 1962 651940 60,100 76487 146097 171504 70290 464378 376178 205448 132817 338265 862743 1.32 1963 517169 39,700 74555 135217 160429 60452 430653 263714 130836 113923 244759 715112 1.38 1964 206081 6,700 26073 78122 81150 18787 204132 64312 23159 47333 70492 281323 1.37 1965 505606 36,700 59530 78896 109273 40148 287847 202391 106193 71273 177466 502014 0.99 1966 610330 49,600 84028 122265 140949 56773 404015 308774 159563 105900 265463 719078 1.18 1967 456585 29,800 66260 122355 133518 56481 378614 232723 132036 99784 231820 640235 1.4 1968 505673 39,700 88629 148319 165957 64399 467304 264388 124508 80301 204809 711814 1.41 1969 667658 59,900 90615 167893 200971 71655 531134 365381 206420 105525 311945 902978 1.35 1970 661118 60,100 98436 164664 190128 68856 522084 360683 201055 117836 318891 901073 1.36 1971 498375 34,800 62580 131528 154491 56838 405437 244147 155926 82983 238909 679146 1.36 1972 260902 16,100 31613 86394 98120 29554 245681 133566 87563 45403 132966 394747 1.51 1973 617462 60,000 64506 121101 169859 70155 425621 301766 190324 72943 263267 748888 1.21 1974 640852 60,100 74620 140914 184792 72712 473038 382894 236001 86323 322324 855462 1.34 1975 580607 60,100 75148 123584 177892 72077 448701 360967 228020 81082 309102 817903 1.41 1976 679684 60,200 90153 144906 202493 83615 521167 402796 261443 83980 345423 926790 1.36 1977 417495 24,800 46336 83429 109628 36625 276018 214577 134896 67543 202439 503257 1.21 1978 356169 14,900 31014 51917 74928 25936 183795 155984 97182 51525 148707 347401 0.98 1979 568687 60,000 72984 101254 144317 55950 374505 312558 177174 77050 254224 688729 1.21 1980 658694 60,000 89486 140521 175716 65742 471465 354008 226296 91954 318250 849715 1.29 1981 608163 60,000 80723 113304 161157 63759 418943 333330 174948 86493 261441 740384 1.22 1982 643169 60,000 87808 120992 177777 66819 453396 326592 184984 87941 272925 786321 1.22 1983 648380 60,000 82336 126510 187680 63580 460106 331945 173897 89028 262925 783031 1.21 1984 653151 60,000 83851 118804 169142 68134 439931 359348 189775 85384 275159 775091 1.19 1985 677397 60,000 97789 127664 172536 69539 467528 359919 200662 81392 282054 809581 1.2 1986 1396186 0.73 1987 1376121 0.81 1988 838011 60,000 106211 158759 190518 77286 532774 569956 261721 96063 357784 950559 1.13 1989 736865 60,000 110684 148352 192385 77278 528699 428156 235981 91150 327131 915830 1.24 1990 680106 60,000 89457 124524 175888 63511 453380 391901 203288 81747 285035 798415 1.17 1991 625956 60,000 84044 131960 161447 58822 436273 372078 172489 110652 283141 779413 1.25 1992 734981 60,000 89246 143498 210841 66930 510515 470359 210395 105180 315575 886090 1.21 1993 823244 60,000 102060 151509 222333 76060 551962 508005 260073 100259 360332 972294 1.18 1994 893383 60,000 127077 169329 241924 91037 629367 508593 248223 97248 345471 1034838 1.16 1995 1096161 1 1996 774335 60,000 107262 141965 226110 87608 562945 446835 212208 102107 314315 937260 1.21 1997 798621 60,000 112068 146934 223607 85690 568299 483092 209383 94259 303642 931941 1.17 1998 808661 60,000 109517 150783 223325 84188 567813 456584 216843 72536 289379 917192 1.13 1999 735467 60,000 90553 131919 201519 74850 4126 502967 457373 222676 62485 285161 848128 1.15 2000 751373 60,000 102601 140936 204111 82042 3435 533125 433256 190630 59740 250370 843495 1.12 2001 786549 60,000 101558 152834 212374 83818 3757 554341 453491 221920 89290 311210 925551 1.18 2002 801147 60,325 103349 138317 204145 78538 3118 527467 473505 226600 82850 309450 897242 1.12 2003 364528 13,590 45820 44970 83620 29350 1674 205434 172330 77140 49320 126460 345484 0.95 2004 399519 13,922 43168 18944 93096 28707 649 184564 186902 99235 38543 137778 336264 0.84 2005 676031 58091 84014 99189 165644 59710 3429 411986 329796 128612 50376 178988 649065 0.96 2006 434228 27112 51824 56723 107490 39255 1976 257268 278511 98670 36655 135325 419705 0.97 2007 636730 51245 70516 73382 147029 52822 3128 346877 337852 159812 51981 211793 609915 0.96 2008 675479 56048 69574 87461 160409 56676 3203 377323 377850 163771 48728 212499 645870 0.96 2009 693289 58688 64419 86738 149306 55325 3072 358860 382038 189933 60073 250006 667554 0.96 2010 659679 56883 56132 74317 148352 50499 2628 331928 363823 0 304937 304937 693748 0.98 2011 396444 25650 12387 14325 18077 9679 54468 230397 262677 262677 342795 0.87 2012 371521 132965 0.79 2013 168641 57447 0.66 2014 305091 0.79
54 APPENDIX B. DIVERSION RATIOS (USBR, INTERNAL) AND
GROUNDWATER LEVELS (USGS, 2015)
Diversion Year Ratio LC-2A LC-2B LC-2C LC-2F LC-3A LC-3C LC-3D
1/1/1985 1.195 16.177 8.984 5.062 21.005 19.326 1/1/1986 0.73 14.71 7.849 4.051 18.508 15.781 1/1/1987 0.81 14.386 7.668 4.423 17.371 14.055 1/1/1988 1.134 13.322 8.107 6.035 16.276 13.003 1/1/1989 1.243 13.826 7.886 5.233 16.566 13.314 1/1/1990 1.174 14.755 8.813 5.357 18.636 16.571 1/1/1991 1.245 15.289 5.57 19.357 17.256 1/1/1992 1.206 15.409 5.292 19.465 17.269 1/1/1993 1.181 16.321 5.231 19.866 17.393 1/1/1994 1.158 15.963 5.05 19.127 16.183 1/1/1995 1.00 16.036 4.83 18.893 15.482 1/1/1996 1.21 15.998 5.946 19.092 15.753 1/1/1997 1.167 17.168 9.408 5.741 20.511 17.676 1/1/1998 1.134 17.809 8.973 5.592 21.179 18.077 1/1/1999 1.153 17.638 5.7 21.729 19.36 1/1/2000 1.123 17.974 5.686 22.824 20.775 1/1/2001 1.177 18.451 5.657 23.415 21.259 1/1/2002 1.12 19.12 5.665 20.709 24.288 22.358 26.46 1/1/2003 0.948 21.394 6.9 23.998 26.737 24.784 30.929 1/1/2004 0.842 23.868 7.799 26.263 30.609 28.529 36.262 1/1/2005 0.96 23.257 10.727 6.493 25.808 31.113 29.124 37.845 1/1/2006 0.967 24.621 11.969 6.669 27.831 31.746 29.122 38.385 1/1/2007 0.958 25.5 12.223 6.577 28.876 33.338 30.932 39.5 1/1/2008 0.956 24.207 11.786 6.447 27.011 33.064 30.795 38.566 1/1/2009 0.963 24.965 11.947 6.31 27.797 35.006 32.059 41.485 1/1/2010 0.98 26.881 12.783 6.699 30.284 35.969 33.745 41.438 1/1/2011 0.865 30.069 15.137 8.023 33.333 39.117 35.588 46.21 1/1/2012 0.79 32.115 17.742 10.786 36.767 42.707 41.255 46.157 1/1/2013 0.66 35.412 21.078 14.369 38.237 44.891 41.768 50.765 1/1/2014 0.71 36.442 21.578 14.489 39.24 46.374 44.343 51.05
Flooding years are 1986, 1987, and 1995
Incomplete Average Provisional USGS Data Fair Average
55 APPENDIX C. ESTIMATED PRECIPITATION VOLUME IN ACRE
FEET USING PRECIPITATION DATA FROM LAS
CRUCES, NM (NCDC, 2014)
1945 53952 1968 110849 1991 123389 1946 58664 1969 100244 1992 92837 1947 53615 1970 28954 1993 80800 1948 1971 48566 1994 68598 1949 87534 1972 102769 1995 63884 1950 46544 1973 76930 1996 52269 1951 52353 1974 116403 1997 87705 1952 49659 1975 68008 1998 60348 1953 32152 1976 65146 1999 77266 1954 51594 1977 73562 2000 83662 1955 84840 1978 126082 2001 44189 1956 40148 1979 78865 2002 64135 1957 71712 1980 67755 2003 46376 1958 130203 1981 81473 2004 110680 1959 47807 1982 66242 2005 91407 1960 65062 1983 61274 2006 119349 1961 84672 1984 116067 2007 86607 1962 53783 1985 105630 2008 78359 1963 51426 1986 109417 2009 73815 1964 30469 1987 77182 2010 79034 1965 69774 1988 94602 2011 57906 1966 82821 1989 75246 2012 46291 1967 70870 1990 80211 2013 54036
Normal 81726 Wet Year Acre ft. Dry Year Las Cruces 1958=Afton NM Precip
56 APPENDIX D. DIVERSION RATIO CORRELATIONS WITH USGS
WELL DATA
(a)
(b)
Figure 24. Well LC-3C; Diversion Ratio (USBR, unpublished) & (a) Current Year Depth
to Groundwater (USGS, 2015), 1985 to 2011, Diversion Ratio (USBR, unpublished) &
(b) Previous Year Depth to Groundwater (USGS, 2015), 1985 to 2011 57 (a)
(b)
Figure 25. Well LC-2C; Diversion Ratio (USBR, unpublished) & (a) Current Year Depth
to Groundwater (USGS, 2015), 1985 to 2011, Diversion Ratio (USBR, unpublished) &
(b) Previous Year Depth to Groundwater (USGS, 2015), 1985 to 2011
58 (a)
(b)
Figure 26. Well LC-2C; Diversion Ratio (USBR, unpublished) & (a) Current Year Depth
to Groundwater (USGS, 2015), 1985 to 2014, Diversion Ratio (USBR, unpublished) &
(b) Previous Year Depth to Groundwater (USGS, 2015), 1985 to 2013
59 (a)
(b)
Figure 27. Well LC-2B; Diversion Ratio (USBR, internal) & (a) Current Year Depth to
Groundwater (USGS, 2015), 1985 to 2011, Diversion Ratio (USBR, internal) & (b)
Previous Year Depth to Groundwater (USGS, 2015), 1985 to 2010
60 (a)
(b)
Figure 28. Well LC-2B; Diversion Ratio (USBR, internal) & (a) Current Year Depth to
Groundwater (USGS, 2015), 1985 to 2014, Diversion Ratio (USBR, internal) &
(b) Previous Year Depth to Groundwater (USGS, 2015), 1985 to 2013
61
Figure 29. Rio Grande below Picacho Bridge river stage in 1985 & 1986 (Nickerson and
Myers, 1993)
62
Figure 30. LC-1 Groundwater Levels for 1985 and 1986 (Nickerson and Myers, 1993)
63
Figure 31. LC-2 Groundwater Levels for 1985 and 1986 (Nickerson and Myers, 1993)
64
Figure 32. LC-3 Groundwater Levels for 1985 and 1986 (Nickerson and Myers, 1993)
65
Figure 33. LC-1, LC-2, and LC-3 Well Section Levels (Gastelum and others, 2012)
66
Figure 34. Map of 2012 Seepage Study (Gunn and Roark, 2012)
67
APPENDIX E - ALLOCATION CHARGES AND CORRESPONDING
DIVERSION RATIO FOR YEARS 2008 TO 2014 (USBR,
INTERNAL)
Table 1. 2008 Allocation Charges (USBR, internal)
1 Rio Grande Project Diversion Allocations (End of irrigation season, 2008 103108) ac-ft
2 Elephant Butte Reservoir Storage 582,902
3 Caballo Reservoir Storage 17,272
4 Total Rio Grande Project Storage 600,174
5 Estimated Rio Grande Compact Credit Waters (65,500)
6 Estimated San Juan-Chama Water (27,730)
7 Water Released from Storage 674,724
8 Total Usable Water Available for Release 1,181,668
9 Carryover Obligation using Estimated Diversion Ratio 106,982
10 Total Usable Water Available for Current Year Allocation 790,000
11 EBID Allocation Balance (Previous Year) -
12 EPCWID Allocation Balance (Previous Year) 106,982
13 EBID Estimated Allocation Balance (End-of-Year) -
14 EPCWID Estimated Allocation Balance (End-of-Year) 138,000
15 Storage for EBID and EPCWID Estimated Allocation Balance (End-of-Year) 138,000
16 Estimated Release of Current Usable Water 758,982
17 Estimated End-of-Year Release for Diversion Ratio 675,090
18 D1 Delivery 524,685
19 Mexico's Current Diversion Allocation 60,000
20 Gross D2 Diversion Allocation 958,055
68 21 EPCWID ACE Conservation Credit 16,818
22 Net D2 Diversion Allocation for EBID and EPCWID 898,055
23 D2 Diversion Allocation for EPCWID 388,192
24 EPCWID Diversion Allocation (w/o Conservation Credit) 495,174
25 EPCWID Diversion (w/o Conservation Credit or 67/155ths of Row 30) 357,174
26 Diversion Ratio 1.000
27 Diversion Ratio Adjustment -
28 Sum of Release and Diversion Ratio Adjustment 758,982
29 EBID D2 Diversion Allocation 509,864
30 Difference between EBID Diversion Ratio Allocation and D2 Diversion Allocation -
31 EBID Diversion Ratio Allocation 324,990
32 EBID Diversion Allocation 324,990
33 Total EBID Diversion Allocation (includes 88/155th of Value in Row 30) 324,990
34 Total EPCWID Allocation (includes Row 21 and 67/155th of Value in Row 30) 495,174
35 Total EBID, EPCWID, and Mexico Allocation 880,164
Table 2. 2009 Allocation Charges (USBR, internal)
1 Rio Grande Project Diversion Allocations ( EO OCT 2009 Project Data) ac-ft
2 Elephant Butte Reservoir Storage 454,530
3 Caballo Reservoir Storage 26,100
4 Total Rio Grande Project Storage 480,630
5 Estimated Rio Grande Compact Credit Waters (126,600)
6 Estimated San Juan-Chama Water (37,298)
7 Water Released from Storage 693,289
8 Total Usable Water Available for Release 1,010,021
9 Carryover Obligation using Estimated Diversion Ratio 235,960
10 Total Usable Water Available for Current Year Allocation 774,061
11 EBID Allocation Balance (Previous Year) (4,304)
12 EPCWID Allocation Balance (Previous Year) 232,882
69 13 EBID Estimated Allocation Balance (End-of-Year) 51,301
14 EPCWID Estimated Allocation Balance (End-of-Year) 232,915
15 Storage for EBID and EPCWID Estimated Allocation Balance (End-of-Year) 287,972
16 Estimated Release of Current Usable Water 722,049
17 Estimated End-of-Year Release for Diversion Ratio 748,600
18 D1 Delivery 494,175
19 Mexico's Current Diversion Allocation 56,082
20 Gross D2 Diversion Allocation 942,117
21 EPCWID ACE Conservation Credit 17,988
22 Net D2 Diversion Allocation for EBID and EPCWID 886,035
23 D2 Diversion Allocation for EPCWID 382,996
24 EPCWID Diversion Allocation (w/o Conservation Credit) 615,878
25 EPCWID Diversion (w/o Conservation Credit or 67/155ths of Row 30) 382,963
26 Diversion Ratio 0.98696
27 Diversion Ratio Adjustment (9,418)
28 Sum of Release and Diversion Ratio Adjustment 712,631
29 EBID D2 Diversion Allocation 503,039
30 Difference between EBID Diversion Ratio Allocation and D2 Diversion Allocation -
31 EBID Diversion Ratio Allocation 255,598
32 EBID Diversion Allocation 255,598
33 Total EBID Diversion Allocation (includes 88/155th of Value in Row 30) 251,294
34 Total EPCWID Allocation (includes Row 21 and 67/155th of Value in Row 30) 633,866
35 District to District Allocation Transfer (OA 1.11 Excess Carryover Balance) 80,879
36 Total EBID Diversion Allocation (After Transfer) 332,173
37 Total EPCWID Allocation (After Transfer) 552,987
38 Total EBID, EPCWID, and Mexico Allocation 941,242
Table 3. 2010 Allocation Charges (USBR, internal)
Rio Grande Project Diversion Allocations ( Data as of 10/31/ 2010 Project Data) (WY 1 2010) ac-ft
2 Elephant Butte Reservoir Storage 372,460
70 3 Caballo Reservoir Storage 18,380
4 Total Rio Grande Project Storage 390,840 (101,300 5 Estimated Rio Grande Compact Credit Waters )
6 Estimated San Juan-Chama Water (60,796)
7 Water Released from Storage 659,679
8 Total Usable Water Available for Release 888,423
9 Carryover Obligation using Estimated Diversion Ratio 278,835 1 0 Total Usable Water Available for Current Year Allocation 609,588 1 1 EBID Allocation Balance (Previous Year) 40,343 1 2 EPCWID Allocation Balance (Previous Year) 232,915 1 3 EBID Allocation Balance (End-of-Year) 0 1 4 EPCWID Allocation Balance (End-of-Year) 0 1 5 Storage for EBID and EPCWID Allocation Balance (End-of-Year) 0 1 6 Current Usable Water 888,423 1 7 End-of-Year Release for Diversion Ratio 659,679 1 8 D1 Delivery 442,651 1 9 Mexico's Current Diversion Allocation 50,235 2 0 Gross D2 Diversion Allocation 725,537 2 1 EPCWID ACE Conservation Credit 0 2 2 Net D2 Current Year Diversion Allocation for EBID and EPCWID 675,302 2 3 D2 Current Year Diversion Allocation for EPCWID 291,905 2 4 Total EPCWID Diversion Allocation (w/o Conservation Credit) 524,820 2 5 EPCWID Diversion (w/o Conservation Credit or 67/155ths of Row 30) 524,820 2 6 Diversion Ratio 0.98 2 7 Diversion Ratio Adjustment (17,768) 2 8 Sum of Release and Diversion Ratio Adjustment 870,655 2 9 EBID D2 Current Year Diversion Allocation 383,397 3 0 Difference between EBID Diversion Ratio Allocation and D2 Diversion Allocation 0
71 3 1 EBID Diversion Ratio Allocation 255,257 3 2 EBID Diversion Allocation 255,257 3 3 Total EBID Diversion Allocation (includes 88/155th of Value in Row 30) 295,600 3 4 Total EPCWID Allocation (includes Row 21 and 67/155th of Value in Row 30) 524,820 3 5 District to District Allocation Transfer **(See foot note below) 10,271 3 6 Total EBID Diversion Allocation (After Transfer) 305,871 3 7 Total EPCWID Allocation (After Transfer) 514,549 3 8 Total EBID, EPCWID, and Mexico Allocation 870,655 3 9 EPCWID 2010 Allocation Charges (calculated) 514,549 4 0 EBID 2010 Allocation Charges (calculated) 305,871 4 1 EPCWID 2010 Allocation Charges (actual) 304,937 4 2 EBID 2010 Allocation Charges (actual) 282,082 4 3 Mexico 2010 Allocation Charges (actual) 56,883 4 4 Difference in Mexico's Charges and Allocation -6,648 4 5 EPCWID Share -2,874 4 6 EBID Share -3,775
Table 4. 2011 Allocation Charges (USBR, internal)
1 Rio Grande Project Diversion Allocations ( Data as of Oct. 31, 2011) ac-ft
2 Elephant Butte Reservoir Storage 208,055
3 Caballo Reservoir Storage 10,141
4 Total Rio Grande Project Storage 218,196
5 Estimated Rio Grande Compact Credit Waters (132,038)
6 Estimated San Juan-Chama Water (55,781)
7 Water Released from Storage 396,444
8 Total Usable Water Available for Release 426,821
9 Carryover Obligation using Estimated Diversion Ratio 281,459
10 Total Usable Water Available for Current Year Allocation 145,362 72 11 EBID Allocation Balance (Previous Year) 20,015
12 EPCWID Allocation Balance (Previous Year) 224,348
13 EBID Allocation Balance (End-of-Year) 0
14 EPCWID Allocation Balance (End-of-Year) 0
15 Storage for EBID and EPCWID Allocation Balance (End-of-Year) 0
16 Current Usable Water 426,821
17 End-of-Year Release for Diversion Ratio 397,426
18 D1 Delivery 226,006
19 Mexico's Current Diversion Allocation 25,649
20 Gross D2 Diversion Allocation 104,495
21 EPCWID ACE Conservation Credit (evaluation postponed until EOY) 0
22 Net D2 Current Year Diversion Allocation for EBID and EPCWID 78,847
23 D2 Current Year Diversion Allocation for EPCWID 34,082
24 Total EPCWID Diversion Allocation (w/o Conservation Credit) 258,430
25 EPCWID Diversion (w/o Conservation Credit or 67/155ths of Row 30) 258,430
26 Diversion Ratio 0.868
27 Diversion Ratio Adjustment (56,255)
28 Sum of Release and Diversion Ratio Adjustment 370,566
29 EBID D2 Current Year Diversion Allocation 44,765
30 Difference between EBID Diversion Ratio Allocation and D2 Diversion Allocation 21,708
31 EBID Diversion Ratio Allocation 66,473
32 EBID Diversion Allocation 44,765
33 Total EBID Diversion Allocation (includes 88/155th of Value in Row 30) 77,104
34 Total EPCWID Allocation (includes Row 21 and 67/155th of Value in Row 30) 267,814
35 District to District Allocation Transfer (OA 1.11 Excess Carryover Balance) 0
36 Total EBID Diversion Allocation (After Transfer) 77,104
37 Total EPCWID Allocation (After Transfer) 267,814
38 Total EBID, EPCWID, and Mexico Allocation 370,566 39 EPCWID 2011 Allocation Charges (calculated) - 40 EBID 2011 Allocation Charges (calculated) - 41 EPCWID 2011 Allocation Charges (actual) - 42 EBID 2011 Allocation Charges (actual) -
73 43 Mexico 2011 Allocation Charges (actual) - 44 Difference in Mexico's Charges and Allocation - 45 EPCWID Share - 46 EBID Share -
74 Table 5. 2012 Allocation Charges (USBR, internal)
1 Rio Grande Project Diversion Allocations ( Data as of Nov. 1, 2012) ac-ft
2 Elephant Butte Reservoir Storage 114,212
3 Caballo Reservoir Storage 5,775
4 Total Rio Grande Project Storage 119,987
5 Estimated Rio Grande Compact Credit Waters (65,189)
6 Estimated San Juan-Chama Water (44,420)
7 Water Released from Storage 371271
8 Total Usable Water Available for Release 381,649
9 Carryover Obligation using Estimated Diversion Ratio 33,463
10 Estimate End-of-Season Adjustment of Project Water Due to Evaporation -
11 Total Usable Water Available for Current Year Allocation 348,186
12 EBID Allocation Balance (Previous Year) 17,333
13 EPCWID Allocation Balance (Previous Year) 9,042
14 EBID Allocation Balance (End-of-Year) 0
15 EPCWID Allocation Balance (End-of-Year) 0
16 Storage for EBID and EPCWID Allocation Balance (End-of-Year) 0
17 Current Usable Water 381,649
18 End-of-Year Release for Diversion Ratio 371,271
19 D1 Delivery 204,399
20 Mexico's Current Diversion Allocation 23,196
21 Multiyear Extreme Drought D2 Correction Factor 0.88
22 Gross D2 Diversion Allocation 330,733
23 EPCWID ACE Conservation Credit (evaluation postponed until EOY) 0
24 Net D2 Current Year Diversion Allocation for EBID and EPCWID 307,536
25 D2 Current Year Diversion Allocation for EPCWID 132,935
26 Total EPCWID Diversion Allocation (w/o Conservation Credit) 141,977
27 EPCWID Diversion (w/o Conservation Credit or 67/155ths of Row 30) 141,977
28 Diversion Ratio 0.788
29 Diversion Ratio Adjustment (80,842)
75 30 Sum of Release and Diversion Ratio Adjustment 300,807
31 EBID D2 Current Year Diversion Allocation 174,601
32 Difference between EBID Diversion Ratio Allocation and D2 Diversion Allocation
33 EBID Diversion Ratio Allocation 118,300
34 EBID Diversion Allocation 118,300
35 Total EBID Diversion Allocation (includes 88/155th of Value in Row 30) 135,633
36 Total EPCWID Allocation (includes Row 21 and 67/155th of Value in Row 30) 141,977
37 District to District Allocation Transfer (OA 1.11 Excess Carryover Balance)
38 Total EBID Diversion Allocation (After Transfer) 135,633
39 Total EPCWID Allocation (After Transfer) 141,977
40 Total EBID, EPCWID, and Mexico Allocation 300,807 41 EPCWID 2012 Allocation Charges 136,380 42 EBID 2012 Allocation Charges 133,060 43 EPCWID 2012 Allocation Charges EOY Balance 5,597 44 EBID 2012 Allocation Charges EOY Balance 2,573 45 Mexico 2012 Allocation Charges 23,187 46 Difference in Mexico's Charges and Allocation 47 EPCWID Share - 48 EBID Share - *As of 7/29/2012 per URGWOM **Final Release Data - USBR 2013 Table 6. 2013 Allocation Charges (USBR, internal)
1 Rio Grande Project Diversion Allocations (Data as of October 31, 2013) ac-ft
2 Elephant Butte Reservoir Storage 163,572
3 Caballo Reservoir Storage 39,578
4 Total Rio Grande Project Storage 203,150
5 Estimated Rio Grande Compact Credit Waters (21,635)
6 Estimated San Juan-Chama Water (30,944)
7 Water Released from Storage 168,201
8 Total Usable Water Available for Release 318,772
9 Carryover Obligation using Estimated Diversion Ratio 11,424
76 1 0 Estimate End-of-Season Adjustment of Project Water Due to Evaporation - 1 1 Total Usable Water Available for Current Year Allocation 307,348 1 2 EBID Allocation Balance (Previous Year) 2,021 1 3 EPCWID Allocation Balance (Previous Year) 5,176 1 4 EBID Allocation Balance (End-of-Year) 0 1 5 EPCWID Allocation Balance (End-of-Year) 0 1 6 Storage for EBID and EPCWID Allocation Balance (End-of-Year) 0 1 7 Current Usable Water 318,772 1 End-of-Year Release for Diversion Ratio (Actual release from June 1 to July 17, 8 2013) 168,201 1 9 D1 Delivery 36,645 2 0 Mexico's Current Diversion Allocation 4,159 2 1 Multiyear Extreme Drought D2 Correction Factor 0.88 2 2 Gross D2 Diversion Allocation 282,656 2 3 EPCWID ACE Conservation Credit (evaluation postponed until EOY) 0 2 4 Net D2 Current Year Diversion Allocation for EBID and EPCWID 278,498 2 5 D2 Current Year Diversion Allocation for EPCWID 120,383 2 6 Total EPCWID Diversion Allocation (w/o Conservation Credit) 125,559 2 7 EPCWID Diversion (w/o Conservation Credit or 67/155ths of Row 30) 125,559 2 8 Diversion Ratio 0.630 2 9 Diversion Ratio Adjustment (117,946) 3 0 Sum of Release and Diversion Ratio Adjustment 200,826 3 1 EBID D2 Current Year Diversion Allocation 158,115 3 2 Difference between EBID Diversion Ratio Allocation and D2 Diversion Allocation 0 3 3 EBID Diversion Ratio Allocation 69,088 3 4 EBID Diversion Allocation 69,088 3 5 Total EBID Diversion Allocation (includes 88/155th of Value in Row 30) 71,109 3 6 Total EPCWID Allocation (includes Row 21 and 67/155th of Value in Row 30) 125,559
77 3 7 District to District Allocation Transfer (OA 1.11 Excess Carryover Balance) 0 3 8 Total EBID Diversion Allocation (After Transfer) 71,109 3 9 Total EPCWID Allocation (After Transfer) 125,559 4 0 Total EBID, EPCWID, and Mexico Allocation 200,826 * Per URGWOM - EOP 8/1/2013 via HDB Releases from Storage ended on July 17th due to low storage by mutual agreement of Project ** water users Table 7. Additional Information for 2013 Allocation Charges (USBR, internal)
Final Final Charge Allocation EBID 54,002 57,448 EPCWID 53,530 47,376 Mexico 3,709 3,665 Total 111,241 108,489 Caballo Release 169,414 168,201 Diversion Ratio 0.656622 0.6613575 Table 8. 2014 Allocation Charges (USBR, internal)
1 Rio Grande Project Final Annual Allocation (Storage Data as of July 1, 2014) ac-ft 225,98 2 Elephant Butte Reservoir Storage 5
3 Caballo Reservoir Storage 30,608
4 Total Rio Grande Project Storage 256,593
5 Estimated Rio Grande Compact Credit Waters -73,078
6 Estimated San Juan-Chama Water -24,642
7 Water Released from Storage 164877 323,75 8 Total Usable Water Available for Release 0
9 Carryover Obligation using Estimated Diversion Ratio 4,235 1 Estimate End-of-Season Adjustment of Project Water for Reservoir Evaporation/Dead 0 storage -5,600 1 313,91 1 Total Usable Water Available for Current Year Allocation 5 1 2 EBID Allocation Balance (Previous Year) 3,008 1 3 EPCWID Allocation Balance (Previous Year) -6,487
78 1 4 EBID Allocation Balance (End-of-Year) 0 1 5 EPCWID Allocation Balance (End-of-Year) 0 1 6 Storage for EBID and EPCWID Allocation Balance (End-of-Year) 0 1 318,15 7 Current Usable Water 0 1 318,15 8 End-of-Year Release for Diversion Ratio 0 1 160,51 9 D1 Delivery 7 2 0 Mexico's Current Diversion Allocation 18,216 2 1 Multiyear Extreme Drought D2 Correction Factor 0.75 2 247,48 2 Gross D2 Diversion Allocation 9 2 3 EPCWID ACE Conservation Credit (evaluation postponed until EOY) 7,485 2 229,27 4 Net D2 Current Year Diversion Allocation for EBID and EPCWID 3 2 5 D2 Current Year Diversion Allocation for EPCWID 99,105 2 6 Total EPCWID Diversion Allocation (w/o Conservation Credit) 92,618 2 7 EPCWID Diversion (w/o Conservation Credit or 67/155ths of Row 30) 92,618 2 8 Diversion Ratio 0.710 2 9 Diversion Ratio Adjustment -92,171 3 225,97 0 Sum of Release and Diversion Ratio Adjustment 9 3 130,16 1 EBID D2 Current Year Diversion Allocation 8 3 2 Difference between EBID Diversion Ratio Allocation and D2 Diversion Allocation 0 3 104,65 3 EBID Diversion Ratio Allocation 1 3 104,65 4 EBID Diversion Allocation 1 3 107,65 5 Total EBID Diversion Allocation (includes 88/155th of Value in Row 30) 9 3 100,10 6 Total EPCWID Allocation (includes Row 21 and 67/155th of Value in Row 30) 3 3 7 District to District Allocation Transfer (OA 1.11 Excess Carryover Balance) 0 3 107,65 8 Total EBID Diversion Allocation (After Transfer) 9 3 100,10 9 Total EPCWID Allocation (After Transfer) 3 4 225,97 0 Total EBID, EPCWID, and Mexico Allocation 9 ^ Figures Current as of July 1, 2014
79 * Estimated per URGWOM Model - NM Credit - 68.4 KAF & CO Credit - 4.67 KAF ** Total SJC water reflects the 12 KAF transfer - Figures estimated per URGWOM EOP June 30, 2014 - / Based on May - August Release Period - Final Allocation Carryover based on charges and June 2013 Final Allocation + 2014 Weighted Diversion Ratio // Figure Based on MultiYear Drought Analysis
80 VITA
Gerardo “Jerry” Melendez was born in El Paso, TX to Rutilo and Martha Melendez. He graduated from Coronado High School in 2003 and attended the University of Texas at El Paso from 2003 to 2007 where he completed his coursework for a Bachelor’s degree in Environmental
Science, Biology Concentration. Soon after, he began a job as a hydrologic technician in El Paso,
TX working for the United States Geological Survey until 2011. While working in the USGS,
Jerry mainly managed stream gage data collection and computed streamflow records for the
Pecos River in Texas and other streams and arroyos in Far West Texas. He also assisted USGS scientists with specialized hydrological projects that were occurring during his time there. In
2012, Jerry was hired by the United States Bureau of Reclamation – El Paso, TX Field Office as a student hydrologic technician/engineer where he managed the data collection and streamflow computation of the Rio Grande below Caballo gaging station, a critical site for Rio Grande
Compact water accounting. Currently, Jerry is still employed by the Bureau of Reclamation.
E-mail Address: [email protected]
This thesis was typed by Gerardo Melendez.
81