Gretchen R. Miller

Texas A&M University;Texas Water Observatory | Associate Professor

Subject Areas: Ecohydrology, groundwater, soil-plant-atmosphere continuum, Earth system modeling

 Recent Activity

ABSTRACT:

The Theis equation models the drawdown in an unconfined aquifer and may be used to analyze the results of pump tests conducted on a confined aquifer. A classic equation in hydrogeology, this example has been programmed into a Jupyter notebook. This educational resources is targeted at upper-level undergraduate students and is intended to supplement lectures or homework assignments on well hydraulics. The primary learning objectives are to: recognize the Theis equation in its inverse form, use iterative solving methods to match a model to data, and find the values of transmissivity and storativity determined by an aquifer test. Secondary objectives are to: refresh skills associated with scientific and programming and learn to use a Jupyter notebook. Data used in analysis is derived from Problem 4.4.6 in Todd and Mays, 2005. An introductory Jupyter Notebook on the Theis equation is also available; see link in related resources.

**Open in native Jupyter Notebook format by clicking the blue "open with" button in the top right corner on Hydroshare. Requires numypy, matplotlib, and math libraries; Python 3 Scientific environment recommended.**

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ABSTRACT:

The Theis equation models the drawdown in an unconfined aquifer based on a given pumping rate, transmissivity, and storativity. A classic equation in hydrogeology, this example has been programmed into a Jupyter notebook. This educational resources is targeted at upper-level undergraduate students and is intended to supplement lectures or homework assignments on well hydraulics. The primary learning objectives are to identify the purpose of the equation, determine appropriate inputs and outputs, and predict the extent of drawdown around a well. Secondary objectives are to refresh skills associated with scientific and programming and learn to use a Jupyter notebook. A companion notebook to be used for pump test analysis is also available (see related resources).

**Open in native Jupyter Notebook format by clicking the blue "open with" button in the top right corner on Hydroshare. Requires numypy, matplotlib, and math libraries; Python 3 Scientific environment recommended.**

Show More

ABSTRACT:

Fog patterns were determined using web camera images collected at half-hour intervals and uploaded to the PhenoCam network. These images were analyzed to determine fog presence and intensity using the K-Means iterative algorithm, as implemented in Python. Atmospheric conditions were clustered into five different categories: clear, overcast, light fog, medium fog, and heavy fog. Ecohydrological variable data was gathered from sensors placed within the forest and at a nearby weather station. The quantified fog data was then compared with the ecohydrological variables; the diurnal patterns of fog and precipitation were determined over the entire dataset and during dry and wet months. In April, rain was present 2% of the time and fog was present in 68% of the images and in September rain was present 18% of the time and fog was present in 40% of the images. Occurrence of heavy fog conditions are consistently higher in January and December but daily appeared to be highest in the early mornings. A generalized linear model was used to relate fog occurrence with temperature, relative humidity, solar radiation, and wind speed.

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ABSTRACT:

Recovery of injected water is one of the most important aspects of an aquifer storage and recovery (ASR) system and is determined by hydrogeologic, operational, and chemical factors. A common series of reactions resulting in deterioration of water quality is the release of arsenic via pyrite oxidation. Previous work suggests system performance can be affected by altering pumping rates while maintaining a constant volume; this is verified in the conservative transport portion of the study. In addition, this study explores the effect of altered pumping rates on arsenic release via pyrite oxidation. A single ASR well in a confined homogeneous aquifer was simulated for a range of hydraulic gradients and storage durations for ten cycles to quantify the effect of pumping rates on system performance for conservative transport using numerical modeling. Reactive transport capabilities were added to a subset of these models to analyze the effects of altering pumping rates on arsenic release via pyrite dissolution. The simulation results showed that performance improved with higher injection and extraction rates for all combinations of hydraulic gradient and storage period considered, although the magnitude of improvement over the baseline scenario was greater for higher hydraulic gradients and longer storage periods. Extraction rates were more influential on system performance than injection rates, with the best and worst performance experienced during the fast and slow extraction scenarios, respectively. Longer storage periods result in more total arsenic released and higher average recovered arsenic concentrations. Injection and extraction rates have their own impact on arsenic release via pyrite dissolution. Injection rates control the spatial extent of dissolved oxygen around the well, with higher rates resulting in a larger extent. Extraction rates affected the amount of arsenic released by controlling the residence time of dissolved oxygen. Higher extraction rates resulted in less residence time of dissolved oxygen and less arsenic released overall. Both higher extraction and injection rates resulted in lower recovered arsenic concentrations; however, regardless of pumping rate, recovered arsenic concentrations were below the EPA’s MCL by the second cycle. Results also highlight the need to manage sorbed arsenic and the injected water plume carefully in aquifers containing arsenic-bearing pyrite lest arsenic migrates beyond the well’s capture zone and affects downgradient users.

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ABSTRACT:

As more ASR systems are employed for management of water resources, the skillful operation of multiwell ASR systems has become very important to improve their performance. In this study, we developed MODFLOW and MT3DMS models to simulate a multiwell ASR system in a synthetic aquifer to assess effects of hydrogeological and operational factors on the performance of the multiwell ASR system. We evaluated a simplified (dual well) ASR system in comparison with complex system (3, 4, 5 and 7 well systems). Recovery and energy efficiencies were calculated using the model simulations. Factors such as higher hydraulic conductivity and longitudinal dispersivity significantly reduced the recovery and energy efficiencies of the system. In contrast, increasing the volume of recharged water increased the recovery efficiency, however the energy efficiency was reduced. Recovery and energy efficiencies also plummet when there is an increase in the underlying regional gradient and the designed storage duration. Operating the system multiple times can yield higher volume of potable water, but the energy efficiency may not vary significantly after the second operating cycle. Single well systems and multiwell systems exhibit similar responses to changes in physical factors, although operational factors have a more pronounced effect on the multiwell systems. One of the major findings was that fewer wells in a multiwell ASR system can yield higher volume of potable water and better output with respect to the electrical power being consumed. The results provide design engineers with guidelines for optimizing performance of the multiwell ASR systems.

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Composite Resource Composite Resource
Brazos River Alluvium Aquifer - Conceptual Model Testing
Created: Jan. 29, 2019, 10:21 p.m.
Authors: Tayyab Mehmood · Knappett, Peter · Gretchen Miller

ABSTRACT:

Quantitative characterization of the dynamics of water exchange fluxes between rivers and aquifers is necessary for water resources management, water quality, environment and ecology of the river-aquifer systems. The main uncertain factors for predicting river–aquifer exchange fluxes are aquifer and riverbed properties. In this study, we characterize the flux exchange dynamics between Brazos River Alluvium Aquifer and Brazos River, TX, USA, using alternative conceptual models. Six alternative conceptual models for the connection between the river and the aquifer, having varying aquifer lithology and river incision levels and incorporating processes such as river bed clogging and seepage face flow, are numerically modeled in HYDRUS 2D using small-scale, high-resolution transects across the river. Modeled results are tested against observed heads in three wells and finally a best-fit conceptual model is used to quantify river-aquifer flux exchange dynamics. Additionally we focused on how factors such as aquifer lithology, river channel incision, water table conditions, seepage face boundaries, and low-conductivity river-bed effect hydraulic head distribution and the corresponding flux exchange dynamics. Our results demonstrate that only a small portion of the aquifer close to the river channel is well-connected with the river and a major portion of the aquifer is disconnected. The proposed conceptual model predicts a) much frequent flux reversals (changes between gaining and losing conditions) and b) much smaller amount of recharge and discharges compared to that of the conceptual model which has been assumed by earlier studies; a reduction of 151% in recharge and 116% in discharges. These results suggest that the magnitude and dynamics of water flux exchange between the river and the aquifer are independent of the hydraulic gradients in the wider disconnected aquifer and are determined by the hydraulic gradients in the connected aquifer close to the river. The results also demonstrate that river-aquifer flux exchange is sensitive to aquifer lithology, river incision depth, and river-bed clogging. While different settings of aquifer lithology and river incision can produce very similar heads in the wider aquifer, the hydraulic head distribution close to the river and hence the river-aquifer flux exchange varies quite drastically from model to model. River-bed clogging decreases the magnitude of fluxes and effects hydraulic head in the aquifer, especially in the vicinity of the river channel, depending upon the gaining and losing river conditions. Furthermore, seepage face flow could be of the same order as that of flows through river-bed depending upon aquifer lithology and corresponding river incision depth.

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Composite Resource Composite Resource

ABSTRACT:

Mexico is known to heavily rely on groundwater resources for the production of food commodities, and most of this production is located in water stressed regions. This study explores the embedded, or virtual, water in the agricultural goods produced in Mexico, tracking its changes over the period of 2007 to 2013 at a regional and county level. Using data sets on agricultural production obtained from Mexico’s government agencies and hydrometeorological datasets from the National Oceanic and Atmospheric Administration (NOAA), we applied previously established methods to estimate the water volumes allocated for crop production. We estimated the water footprint of crop production (WFP), per tonnage of production (WFUton) and per value of production in Mexican pesos (WFUpesos) for both rainfed and irrigated crops. We further subdivided irrigation into that provided by groundwater and that provided by surface water. The total water footprint of crop production (WFP) in Mexico for both rainfed and irrigated crops over the period of 2007-2013 averaged 1.61 X 10^11 m3 per year. The portion that comes directly from rainfall averaged 8.43 X 10^10 m3 per year and the portion from surface water and groundwater averaged 7.67 X 10^10 m3 per yr. Metrics related to irrigation with surface and groundwaters (i.e., blue water) use peaked during the 2011 drought, although the ratio of groundwater to surface water use stayed roughly the same. Additionally, in all but one year, the blue water volumes required by crops exceeded that reported by irrigation districts, implying some underreporting may be occurring. Although previous studies have quantified Mexico’s water footprint at the country scale, this is the first to our knowledge to address embedded water at the very fine county/municipio scale. This allowed us to identify the regions with high appropriation of freshwater resources for agricultural production and compare them to regions with ongoing groundwater depletion.

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MODFLOW Model Instance Resource MODFLOW Model Instance Resource
Brazos River Alluvium Aquifer GAM
Created: Feb. 2, 2020, 11:26 a.m.
Authors: Pena Rodriguez, Aaron · Miller, Gretchen R.

ABSTRACT:

Brazos River Alluvium Aquifer Groundwater Availability Model (GAM) from the Texas Water Development Board (TWDB)

MODFLOW USG beta model created by INTERA Inc. for the TWDB (2016).

The data files are inside the .rar file.

To access this data, please contact at aaron.pena.hydro@tamu.edu

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Collection Resource Collection Resource

ABSTRACT:

The Groundwater Availability Models (GAMs) were commissioned b the Texas Water Development Board (TWDB) and created with hydrological, climatic, and geological data from the state to model its aquifers behavior. Their main objective is as a tool to aid in the planning and management of the groundwater resources in the state to accomplish the TWDB 2017 water plan (currently adopted).
This set of GAMs has been translated from their original MOFLOW version to MODFLOW 2000 for uniformity and all can be run either in MODFLOW or in GMS (Aquaveo 2017).

To access this data, please contact at aaron.pena.hydro@tamu.edu

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MODFLOW Model Instance Resource MODFLOW Model Instance Resource
Edwards Balcones Fault Zone, North
Created: March 5, 2020, 2:52 p.m.
Authors: Pena Rodriguez, Aaron · Miller, Gretchen R.

ABSTRACT:

Edwards Balcones Fault Zone North, Availability Model (GAM) from the Texas Water Development Board (TWDB)

MODFLOW 2000 beta model for the TWDB (2016).

To access this data, please contact at aaron.pena.hydro@tamu.edu

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MODFLOW Model Instance Resource MODFLOW Model Instance Resource

ABSTRACT:

Edwards Balcones Fault Zone San Antonio Groundwater Abailiabilty Model for the Texas Water Development Board 2004

To access this data, please contact at aaron.pena.hydro@tamu.edu

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MODFLOW Model Instance Resource MODFLOW Model Instance Resource

ABSTRACT:

Edwards Balcones Fault Zone Springs Groundwater Abailiabilty Model for the Texas Water Development Board

To access this data, please contact at aaron.pena.hydro@tamu.edu

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MODFLOW Model Instance Resource MODFLOW Model Instance Resource
Edwards Trinity Plateau
Created: March 6, 2020, 6:08 a.m.
Authors: Pena Rodriguez, Aaron · Miller, Gretchen R.

ABSTRACT:

Edwards Trinity Plateau Groundwater Availability Model for the Texas Water Development Board

To access this data, please contact at aaron.pena.hydro@tamu.edu

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MODFLOW Model Instance Resource MODFLOW Model Instance Resource
Carrizo-Wilcox South
Created: March 6, 2020, 6:32 a.m.
Authors: Pena Rodriguez, Aaron · Miller, Gretchen R.

ABSTRACT:

Carrizo-Wilcox South Groundwater Abailiavility Model for the Texas Development Board

To access this data, please contact at aaron.pena.hydro@tamu.edu

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MODFLOW Model Instance Resource MODFLOW Model Instance Resource
Carrizo-Wilcox North
Created: March 6, 2020, 6:56 a.m.
Authors: Pena Rodriguez, Aaron · Miller, Gretchen R.

ABSTRACT:

Carrizo-Wilcox North Groundwater Availability Model for the Texas Water Development Board MODFLOW 2000

To access this data, please contact at aaron.pena.hydro@tamu.edu

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MODFLOW Model Instance Resource MODFLOW Model Instance Resource
Carrizo-Wilcox Center
Created: March 6, 2020, 7:01 a.m.
Authors: Pena Rodriguez, Aaron · Miller, Gretchen R.

ABSTRACT:

Carrizo-Wilcox Central Section Groundwater Availability Model for the Texas Water Development Board, MODFLOW 2000

To access this data, please contact at aaron.pena.hydro@tamu.edu

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MODFLOW Model Instance Resource MODFLOW Model Instance Resource
Gulf Coast Center
Created: March 6, 2020, 8:05 a.m.
Authors: Pena Rodriguez, Aaron · Miller, Gretchen R.

ABSTRACT:

Gulf Coast Center Groundwater Availability Model for the Texas Water Development Board, Modflow 2000

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MODFLOW Model Instance Resource MODFLOW Model Instance Resource
Gulf Coast North
Created: March 6, 2020, 8:06 a.m.
Authors: Pena Rodriguez, Aaron · Miller, Gretchen R.

ABSTRACT:

Gulf Coast North Groundwater Availability Model for the Texas Water Development Board, Modflow 2000

To access this data, please contact at aaron.pena.hydro@tamu.edu

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MODFLOW Model Instance Resource MODFLOW Model Instance Resource
Gulf Coast South
Created: March 6, 2020, 8:30 a.m.
Authors: Pena Rodriguez, Aaron · Miller, Gretchen R.

ABSTRACT:

Gulf Coast South Groundwater Availability Model for the Texas Water Development Board, MODFLOW 2000

To access this data, please contact at aaron.pena.hydro@tamu.edu

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MODFLOW Model Instance Resource MODFLOW Model Instance Resource
Hueco Mesilla Bolson
Created: March 6, 2020, 8:47 a.m.
Authors: Pena Rodriguez, Aaron · Miller, Gretchen R.

ABSTRACT:

Hueco Mesilla Bolson Groundwater Availability Model for the Texas Water Development Board, MODFLOW 2000

To access this data, please contact at aaron.pena.hydro@tamu.edu

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MODFLOW Model Instance Resource MODFLOW Model Instance Resource
Ogallala North
Created: March 6, 2020, 8:53 a.m.
Authors: Pena Rodriguez, Aaron · Miller, Gretchen R.

ABSTRACT:

Ogallala South Groundwater Availability Model for the Texas Water Development Board, MODFLOW 2000

To access this data, please contact at aaron.pena.hydro@tamu.edu

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MODFLOW Model Instance Resource MODFLOW Model Instance Resource
Ogallala South
Created: March 6, 2020, 9:13 a.m.
Authors: Pena Rodriguez, Aaron · Miller, Gretchen R.

ABSTRACT:

Ogallala South Groundwater Availability Model for the Texas Water Development Board, MODFLOW 2000

To access this data, please contact at aaron.pena.hydro@tamu.edu

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MODFLOW Model Instance Resource MODFLOW Model Instance Resource
Trinity Hill
Created: March 6, 2020, 9:45 a.m.
Authors: Pena Rodriguez, Aaron · Miller, Gretchen R.

ABSTRACT:

Trinity Hill Groundwater Availability Model for the Texas Water Development Board, MODFLOW 2000

To access this data, please contact at aaron.pena.hydro@tamu.edu

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MODFLOW Model Instance Resource MODFLOW Model Instance Resource
Trinity North
Created: March 6, 2020, 9:51 a.m.
Authors: Pena Rodriguez, Aaron · Miller, Gretchen R.

ABSTRACT:

Trinity North Groundwater Availability Model for the Texas Water Development Board, MODFLOW 2000

To access this data, please contact at aaron.pena.hydro@tamu.edu

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Composite Resource Composite Resource

ABSTRACT:

Modeled data from the Texas Water Development Board's Groundwater Availability Models (GAMs) utilized for the recharge uncertainty analysis.
It contains each one of the head files for the 16 GAMs utilized for the analysis and the 11 recharge scenarios modeled in each one of them (50 to 150% in 10% increments).
The river data reflects each river that crosses into each GAM and the baseflow data for each one of them, the mean baseflow for each recharge scenario and the standard deviation.

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Composite Resource Composite Resource
Multiwell Aquifer Storage and Recovery System Modeling
Created: April 16, 2020, 1:02 a.m.
Authors: Majumdar, Saheli · Miller, Gretchen R. · Zhuping Sheng

ABSTRACT:

As more ASR systems are employed for management of water resources, the skillful operation of multiwell ASR systems has become very important to improve their performance. In this study, we developed MODFLOW and MT3DMS models to simulate a multiwell ASR system in a synthetic aquifer to assess effects of hydrogeological and operational factors on the performance of the multiwell ASR system. We evaluated a simplified (dual well) ASR system in comparison with complex system (3, 4, 5 and 7 well systems). Recovery and energy efficiencies were calculated using the model simulations. Factors such as higher hydraulic conductivity and longitudinal dispersivity significantly reduced the recovery and energy efficiencies of the system. In contrast, increasing the volume of recharged water increased the recovery efficiency, however the energy efficiency was reduced. Recovery and energy efficiencies also plummet when there is an increase in the underlying regional gradient and the designed storage duration. Operating the system multiple times can yield higher volume of potable water, but the energy efficiency may not vary significantly after the second operating cycle. Single well systems and multiwell systems exhibit similar responses to changes in physical factors, although operational factors have a more pronounced effect on the multiwell systems. One of the major findings was that fewer wells in a multiwell ASR system can yield higher volume of potable water and better output with respect to the electrical power being consumed. The results provide design engineers with guidelines for optimizing performance of the multiwell ASR systems.

Show More
Composite Resource Composite Resource

ABSTRACT:

Recovery of injected water is one of the most important aspects of an aquifer storage and recovery (ASR) system and is determined by hydrogeologic, operational, and chemical factors. A common series of reactions resulting in deterioration of water quality is the release of arsenic via pyrite oxidation. Previous work suggests system performance can be affected by altering pumping rates while maintaining a constant volume; this is verified in the conservative transport portion of the study. In addition, this study explores the effect of altered pumping rates on arsenic release via pyrite oxidation. A single ASR well in a confined homogeneous aquifer was simulated for a range of hydraulic gradients and storage durations for ten cycles to quantify the effect of pumping rates on system performance for conservative transport using numerical modeling. Reactive transport capabilities were added to a subset of these models to analyze the effects of altering pumping rates on arsenic release via pyrite dissolution. The simulation results showed that performance improved with higher injection and extraction rates for all combinations of hydraulic gradient and storage period considered, although the magnitude of improvement over the baseline scenario was greater for higher hydraulic gradients and longer storage periods. Extraction rates were more influential on system performance than injection rates, with the best and worst performance experienced during the fast and slow extraction scenarios, respectively. Longer storage periods result in more total arsenic released and higher average recovered arsenic concentrations. Injection and extraction rates have their own impact on arsenic release via pyrite dissolution. Injection rates control the spatial extent of dissolved oxygen around the well, with higher rates resulting in a larger extent. Extraction rates affected the amount of arsenic released by controlling the residence time of dissolved oxygen. Higher extraction rates resulted in less residence time of dissolved oxygen and less arsenic released overall. Both higher extraction and injection rates resulted in lower recovered arsenic concentrations; however, regardless of pumping rate, recovered arsenic concentrations were below the EPA’s MCL by the second cycle. Results also highlight the need to manage sorbed arsenic and the injected water plume carefully in aquifers containing arsenic-bearing pyrite lest arsenic migrates beyond the well’s capture zone and affects downgradient users.

Show More
Composite Resource Composite Resource

ABSTRACT:

Fog patterns were determined using web camera images collected at half-hour intervals and uploaded to the PhenoCam network. These images were analyzed to determine fog presence and intensity using the K-Means iterative algorithm, as implemented in Python. Atmospheric conditions were clustered into five different categories: clear, overcast, light fog, medium fog, and heavy fog. Ecohydrological variable data was gathered from sensors placed within the forest and at a nearby weather station. The quantified fog data was then compared with the ecohydrological variables; the diurnal patterns of fog and precipitation were determined over the entire dataset and during dry and wet months. In April, rain was present 2% of the time and fog was present in 68% of the images and in September rain was present 18% of the time and fog was present in 40% of the images. Occurrence of heavy fog conditions are consistently higher in January and December but daily appeared to be highest in the early mornings. A generalized linear model was used to relate fog occurrence with temperature, relative humidity, solar radiation, and wind speed.

Show More
Composite Resource Composite Resource

ABSTRACT:

The Theis equation models the drawdown in an unconfined aquifer based on a given pumping rate, transmissivity, and storativity. A classic equation in hydrogeology, this example has been programmed into a Jupyter notebook. This educational resources is targeted at upper-level undergraduate students and is intended to supplement lectures or homework assignments on well hydraulics. The primary learning objectives are to identify the purpose of the equation, determine appropriate inputs and outputs, and predict the extent of drawdown around a well. Secondary objectives are to refresh skills associated with scientific and programming and learn to use a Jupyter notebook. A companion notebook to be used for pump test analysis is also available (see related resources).

**Open in native Jupyter Notebook format by clicking the blue "open with" button in the top right corner on Hydroshare. Requires numypy, matplotlib, and math libraries; Python 3 Scientific environment recommended.**

Show More
Composite Resource Composite Resource

ABSTRACT:

The Theis equation models the drawdown in an unconfined aquifer and may be used to analyze the results of pump tests conducted on a confined aquifer. A classic equation in hydrogeology, this example has been programmed into a Jupyter notebook. This educational resources is targeted at upper-level undergraduate students and is intended to supplement lectures or homework assignments on well hydraulics. The primary learning objectives are to: recognize the Theis equation in its inverse form, use iterative solving methods to match a model to data, and find the values of transmissivity and storativity determined by an aquifer test. Secondary objectives are to: refresh skills associated with scientific and programming and learn to use a Jupyter notebook. Data used in analysis is derived from Problem 4.4.6 in Todd and Mays, 2005. An introductory Jupyter Notebook on the Theis equation is also available; see link in related resources.

**Open in native Jupyter Notebook format by clicking the blue "open with" button in the top right corner on Hydroshare. Requires numypy, matplotlib, and math libraries; Python 3 Scientific environment recommended.**

Show More