High Plains Aquifer Groundwater Availability Studypanhandlewater.org/pwpg_notices/2011/PWPG 2-15-11 PPT.pdf · 2011. 2. 18. · Presentation outline ... The most recent compilation
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U.S. Department of the Interior U.S. Geological Survey High Plains Aquifer Groundwater Availability Study Natalie Houston, P.G. Hydrologist Texas Water Science Center
U.S. Department of the InteriorU.S. Geological Survey
High Plains Aquifer Groundwater Availability Study
Natalie Houston, P.G.HydrologistTexas Water Science Center
Presentation outline
Overview of the USGS Groundwater Resources Program
Overview of the High Plains Groundwater Availability Study Water budget estimates and methods used Remotely sensed evapotranspiration data Preliminary results Northern High Plains groundwater flow model
Mission: To provide objective scientific information and develop interdisciplinary understanding necessary to assess and quantify the availability and sustainability of the Nation’s groundwater resources.
U.S. Geological SurveyGroundwater Resources Program
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The High Plains Groundwater Availability Study is part of the National USGS Groundwater Resources Program, regional groundwater studies. The project began in April of 2009
Framework for Groundwater Availability at aRegional Scale: Principal Aquifers
Source: U.S. Geological Survey National Atlas of the United States; http://nationalatlas.gov/atlasftp.html
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The 62 nationally defined Principal Aquifers are the framework for a National assessment of groundwater availability although not the only source for aquifer selection.
Source: Maupin and Barber, 2005
Total Withdrawals by Aquifer in US--2000
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The U.S. Geological Survey (USGS) partners with State and local agencies to compile estimates of ground-water/surface-water withdrawals for the Nation at 5-year intervals. The USGS has done this since 1950. The most recent compilation is shown above for 2000. The 2000 compilation was the first time ground-water withdrawals were organized by principal aquifers. Maupin and Barber in 2005 produced this compilation from 2000 data ranking the total groundwater withdrawals by aquifers for irrigation, public-supply, and self-supplied industrial water uses. Domestic self-supplied withdrawals are not included in this compilation. The report for these data are in Open File Report (OFR) 2010-1223. Fresh groundwater withdrawals for irrigation, public supply, and self-supplied industrial uses was 92% of groundwater withdrawals for all water uses. Irrigation is the largest type water use.
Regional-Scale Approach to a National Assessment
http://water.usgs.gov/ogw/gwrp/activities
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These are the priority aquifers that are either underway or have been completed, the study duration is 3 years The Central Valley, Denver Basin, and Southeast Coastal Plain availability started in 2004 and were completed in 2007 The Lake Michigan Basin study was completed in 2008, and the Mississippi embayment study was completed in 2009 The goal is to have 4 studies in any year & start new study each year.
http://pubs.usgs.gov/fs/2010/3008/
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A fact sheet and a new boundary for the aquifer were both published in 2010. Here is the URLfor the fact sheet.
http://pubs.usgs.gov/ds/543/
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And here is the URL for the boundary. It is available for download as a feature class on the High Plains groundwater availability webpage. The revisions in Texas were fairly simple, the USGS adopted the official Ogallala aquifer extent published by the Texas Water Development Board. The high plains aquifer as defined by the USGS is analogous to the Ogallala aquifer rather than the high plains aquifer defined by Texas.
High Plains Aquifer: Stratigraphy Northern High Plains
Source: Robson and Banta, 1995
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The USGS High Plains aquifer includes the underlying Arikaree Formation, and the Brule Formation (where it is permeable), These formations are mostly in the northwestern part of the aquifer. as well as the overlying quaternary deposits. In New Mexico and Easter Nebraska adjacent hydraulically connected Quaternary deposits that do not have underlying Ogallala Formation are also included.
High Plains Aquifer: Stratigraphy Southern High Plains
Source: Dutton and others, 2003
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Whereas in Texas the Ogallala Formation is generally not subdivided. As this graphic depicts the High Plains aquifer as defined in Texas includes underlying Cretaceous beds. High Plains aquifer nationally (USGS) is defined differently than the state of Texas defines it.
Groundwater flow models in the High Plains Aquifer since RASA
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The Regional Aquifer-System Analysis (RASA) Program of the U.S. Geological Survey was started in 1978 and was completed in 1995. Since Rasa several groundwater flow models have been completed. This graphic by no means contains all of the models. Since rasa however, no regional model has been completed in the northern high plains.
High Plains Aquifer: Work Plan
1. Refine both pre-development and current water budgets for the entire High Plains aquifer.
2. Develop a methodology using remotely sensed data and land-cover modeling to estimate evapotranspiration and irrigation through space and time.
3. Construct a MODFLOW groundwater flow model for the northern High Plains aquifer using updated data and advances in technology.
4. Assess groundwater availability for the northern High Plains aquifer. Use the MODFLOW ground-water flow model for the northern High Plains aquifer to extrapolate the effects of predicted natural (climatic) and anthropogenic stresses on the revised water budgets. Evaluate long-term water supply for the northern High Plains aquifer.
High Plains Aquifer – Analysis Areas
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By convention we split the High Plains aquifer 3 study units, the northern
Central and Southern High Plains
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Central and Southern high plains.
Simplistic Water Budgets
Task 1: Refine Water Budgets for Entire High Plains Aquifer
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The primary focus of this study in the Central and Southern High Plains is the refinement, comparison and analysis of components of the predevelopment and current water budget
Water Budget Components Analyzed
Precipitation Evapotranspiration Recharge Surface water Groundwater fluxes
to and from adjacent units Irrigation Groundwater in
storage.
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Multiple sources of information were compiled to estimate the average annual volumes of water associated with individual water-budget components of the High Plains landscape and aquifer for pre-groundwater development (pre-1950) and current (2000 through 2009) time periods.
Methods used to estimate components of the water budget
SOWAT—SOil WATer Balance ModelDesigned primarily to estimate irrigation pumpage
SWB— A Modified Tornthwaite-Mather Soil-Water-Balance Code
Designed primarily to estimate recharge BFI program version 4.15— Base Flow Index
program version 4.15 A Computer program for determining an Index to
Base Flow
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SOWAT -uses known information about precipitation, ET, soil properties, land cover, and irrigation practices to compute the unknown quantities of groundwater withdrawals for irrigation and potential recharge. SWB—A Modified Thornthwaite-Mather Soil-Water-Balance Code for Estimating Groundwater Recharge Uses spatial data, along with daily tabular climate data to estimate recharge and irrigation Recharge calculations are made on a rectangular grid of computational elements that may be easily imported into a regional groundwater-flow model. Recharge estimates calculated by the code may be output as daily, monthly, or annual values. BFI program version 4.15 (Wahl and Wahl, 2007). This program uses daily streamflow measurements to identify storm runoff peaks, separate base flow from runoff, and calculate a base-flow index
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Sowat is A regional-scale soil water balance hydrologic model developed by the Columbia Plateau water availability study The model uses the relationship between climate, soils, land cover and irrigation data to compute monthly irrigation requirements And surplus moisture available for recharge The model runs on a monthly time step Is written in python And reads all spatial data directly from raster files in ESRI grid format
SOil WATer Balance Model
▲SM = PR + IR – ETa – DR - GF
Soil Moisture Storage (SM)
Maximum Allowable Depletion (MAD)
Soil Moisture Capacity (SMC)
Actual evapotranspiration (ETa)
Irrigation (IR) Precipitation (PR)
Direct runoff (DR)
Groundwater flux (GF)
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In the SOWAT model, simulated soil moisture is compared with the estimated soil moisture required to support crops. If simulated soil moisture is less than the soil-moisture target then irrigation is supplied until the soil moisture fills to capacity. For puposes of this study, the soil moisture target was set to 50 percent of the available water capacity (AWC) of the soil. This percentage was based on water requirements for crops common to the High Plains (corn, wheat, sorghum, and cotton) (Kirkpatrick and others, 2006; McMahon and others, 2007). The maximum allowable depletion is the fraction of the soil water capacity that can be depleted before crop productivity will suffer.
Soil and Land cover Input Rasters LC = Land cover (categorical) AWC = Available water capacity GW = Fraction of irrigation supplied by
groundwater
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The model computes initial soil moisture conditions for each month using the previous months available water capacity layer Monthly actual ET was estimated using remotely sensed temperature data and regional climate data in a simplified surface energy balance (SSEB) model. The SSEB model uses 1-km thermal data available since March, 2000 from the MODIS satellite thermal sensors to compute actual ET land cover type. This is a categorical variable spatially distributed by (irrigated, native vegetation, or developed/open water), The fraction of irrigation supplied by groundwater is also a raster just not depicted
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Four land-cover classes are used as input for SOWAT: irrigated agriculture, nonirrigated agriculture and native vegetation, and developed lands and water bodies. Because the available land-cover data set only identified agricultural land and not irrigated fields, the irrigated cells were identified using both the National Land Cover Database (NLCD) for 2001 (Multi-Resolution Land Characteristics Consortium, 2001) and delineated irrigated land for 2002 from remotely sensed imagery (Brown and others, 2008). The NLCD and irrigated land datasets were combined. If a cell identified as agriculture from the NLCD also was identified as irrigated, then the cell was classified as irrigated agriculture in the SOWAT model (fig. 14). The irrigated cells classified in the land-cover grid identify where SOWAT will allow irrigation if a soil-moisture deficit exists for that cell during the simulation time
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The AWC of the soil is defined as the amount of water the soil is able to store. The AWC of soils in the High Plains in the upper 59 inches (1,500 millimeters) of soil was derived from STATSGO available soil water capacity (derived from STATSGO data) is defined as the amount of water that should be available to plants if the soil were at field capacity.
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Here is a graphic of actual evapotranspiration computed using a energy balance method, and effective precipitation. Notice the precipitation raster doesn’t look like your traditional southeast – northwest trending bands That is because unlike the Columbia Plateau the input for the SOWAT model in the High Plains needed to account for large gradients in precipitation, snowmelt, and runoff. Therefore, our team created an “effective” precipitation data set to account for snowmelt and variable runoff without having to modify the programming of the SOWAT model. We obtained precipitation, snowmelt, and runoff from the National Weather Service Sacramento Soil Moisture Accounting Model. Effective precipitation used in the SOWAT model was computed as precipitation plus snowmelt minus runoff.
http://pubs.usgs.gov/tm/tm6-a31/
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Another method we used to estimate some of the components of the water budget was the SWB model.
R = (P + snowmelt + inflow) –sources
(interception + outflow + ET) – ∆S soil
sinks
SWB – Daily Soil Water Budget
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The SWB model is also a regional scale soil water balance model The model layout is a grid, with each cell attributed with soil properties and daily climate data. It uses a modified Thornthwaite-Mather soil-water accounting method to track the soil water in each cell with time (Thornthwaite and Mather, 1957). Recharge is the surplus water in the soil column between the ground surface and the bottom of the root zone. Surplus water is computed by subtracting the sum of the outputs (evapotranspiration, runoff, interception) from the inputs (precipitation, snowmelt, runoff from adjacent cells). Runoff and ET are also computed using one of several methods. For purposes of this report, the Hargreaves-Samani (1985) method is used with daily high and low temperature and precipitation. Physical parameters that control flow and loss of water on the ground surface and within the soil include the soil available water capacity (AWC) and hydrologic soil group, the land use, and the direction of surface flow, which is used for routing runoff. Soil properties are derived from Natural Resource Conservation Service State Soil Geographic (STATSGO2) Database (U.S. Department of Agriculture, 2006). Land use for each cell includes agricultural land, urban land, types of forest and grassland (Multi-Resolution Land Characteristics Consortium, 2001).
Variables Sources R = Recharge P = Precipitation Snowmelt Inflow = Flow from adjacent cells from flow
direction grid Sinks Interception = Amount of rainfall that is presumed
trapped and either evaporated or transpiredOutflow = Surface runoffET = Evapotranspiration∆S = Change in soil moisture
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Precipitation was from interpolated daily precipitation measured at weather stations for SWB SWB calculates actual ET internally using an empirical equation to calculate potential ET and soil moisture; as soil moisture decreases, actual ET also decreases.
Task 2: Remote Sensing of Actual Evapotranspiration
Image courtesy of NASA
MODIS instrument aboard 2 satellites, Terra and Aqua Terra passes from north to south across the equator in the morning Aqua passes south to north over the equator in the afternoon Acquires data in 36 spectral bands View the entire Earths surface every 1 to 2 days
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Monthly actual ET was estimated using remotely sensed temperature data Modis – Moderate Resolution Imaging Spectoradiometer – is a sensor or instrument on 2 satellites Data for an area is acquired every 8 days. 8-day Average MODIS Land Surface Temperature Periods: May 1 - 8, May 9 - 16, …., Sep 22 - 29 Year: 2002 – 2006* Resolution: 1 km Daily Reference ET Global Data Assimilation System (GDAS) 6-hourly weather parameters FAO Penman-Monteith Reference ET 1 degree downscaled to 0.1 degree
Simplified Surface Energy Balance (SSEB) Approach
Adapted the “hot” and “cold” pixel concept from SEBAL (Bastiaanssen et al., 1998).
Assumes a linear relationship between latent heat flux (ET) and land surface temperature.
Actual evapotranspiration (Eta) is a product of ET fraction and reference ET.
Senay, Budde, Verdin and Melesse, 2007. Sensors, 7, 979-1000.
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Gabriel Senay, with EROS developed a model called the Simplified Surface Energy Balance Approach or (SSEB) for short which Uses 1-km land surface thermal (temperature) data obtained from MODIS to identify Cold pixels in heavily irrigated area where actual ET = reference ET and Hot pixels in barren or fallow areas where actual ET is near zero
Preliminary Results
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These results are preliminary.
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Early results show that the SOWAT model appears to be underestimating withdrawals
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And over estimating recharge
Luckey and others, 1988, Effects of future ground-water pumpage on the High Plains Aquifer in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming, U.S. Geological Survey Professional Paper 1400-E
Task 3: Develop a groundwater flow model of the northern High Plains aquifer
High Plains RASA 1980’s Aquifer Base
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Currently we are constructing the Northern High Plains model.
Aquifer Base Surfaces Developed After RASA
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Improving the Hydro-stratigraphic Framework is a goal Point data from the various models were compiled and integrated into a geodatabase.
Expand and refine using newer test holes
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New test hole data were added in South Dakota, Kansa, Wyoming, Colorado and Nebraska We are refining the existing structure and hope to publish a new base of the high plains aquifer feature class The cell size has been reduced to 1 km, better representation of streams in the groundwater flow model Intend to use the farm process to estimate water availability
Summary
Refine water budgets for the entire High Plains aquifer
Remote sensing techniques for evapotranspiration and irrigation
Construct a MODFLOW groundwater -flow model for the northern High Plains aquifer, using updated data and advanced approaches, such as Farm Process
Assess groundwater availability for the northern High Plains aquifer
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Essentially an analysis and comparison of selected water-budget components of the High Plains aquifer, Predevelopment and 2000-2009
Website
http://txpub.usgs.gov/HPWA/index.html
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Can subscribe to an RSS feed and obtain updates to the study at a frequency of your choice.
Project Team
Steven M. Peterson, P.G. High Plains Groundwater Availability Study Project Manager U.S. Geological Survey Nebraska Water Science Office telephone: 402.328.41511 E-mail: [email protected]
Scott Christenson Hydrologist –Emeritus U.S. Geological Survey New Mexico Water Science Center Office telephone: 505.830.796 E-mail: [email protected]
Sarah Falk Hydrologist U.S. Geological Survey New Mexico Water Science Center Office telephone: 505.830.7952 E-mail: [email protected]
Amanda Saunders Flynn Physical Scientist U.S. Geological Survey Nebraska Water Science CenterOffice telephone: 402.328.4144 E-mail: [email protected]
Sophia GonzalesGeographer U.S. Geological Survey Texas Water Science Center Office telephone: 512.927.3507 E-mail: [email protected]
Sharon L. QiHydrologist U.S. Geological Survey Colorado Water Science Center Office telephone: 360.993.8977 E-mail: [email protected]
Derek Ryter, Ph.D. P.G. Physical Scientist U.S. Geological Survey Nebraska Water Science Center Office telephone: 402.328.4123 E-mail: [email protected]
Jennifer S. Stanton Hydrologist U.S. Geological Survey Nebraska Water Science CenterOffice telephone: 402.261.0458 E-mail: [email protected]
