Top-down groundwater hydrograph time-series modeling for climate-pumping decomposition

Shapoori, V.; Peterson, T. J.; Western, Andrew W.; Costelloe, Justin F.

doi:10.1007/s10040-014-1223-0

Cited by 27 publications

(45 citation statements)

References 28 publications

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“…Below are details of additional settings: The two‐layer soil model with constrained soil evapotranspiration was used to produce a time series of free drainage from the deep layer. Pumping downscaling and estimation was undertaken using the calibration scheme outlined above and detailed in Figure S1. Convolution of the free drainage was done using the three‐parameter Pearson's HydroSight function. Convolution of the downscaled pumping at each production bore was done using the Ferris‐Knowles drawdown function (Ferris and Knowles ), which is an instantaneous form of the Theis equation. Following Shapoori et al (), Ferris‐Knowles was reformulated as an impulse response function for the drawdown per unit pumping volume:

θ_{F} (t) = \frac{α}{t} \exp (\frac{- r^{2} β}{t})

where r is the distance between the observation bore and the production bore and α and β are calibration parameters. Following Shapoori et al (), transmissivity ( T ) and storativity ( S ) were then estimated:

T = \frac{1}{4 π α}

S = 4 italicT β .

…”

Section: Methodsmentioning

confidence: 99%

“…It requires only existing data and is comparable to a very long‐term pumping test with multiple production bores, each having a differing and time‐varying extraction rate. When the complete history of groundwater usage is frequently metered (i.e., monthly), time‐series analysis allows the efficient estimation of aquifer properties and, when undertaken at many observation bores, a data‐driven estimation of aquifer heterogeneity (Shapoori et al ) and the cumulative impact of usage (Shapoori et al ). However, few regions have a complete and frequently metered record of groundwater usage and this inhibits estimation of the aquifer hydraulic properties from the groundwater hydrograph.…”

Section: Introductionmentioning

confidence: 99%

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Joint Estimation of Gross Recharge, Groundwater Usage, and Hydraulic Properties within HydroSight

Peterson

Fulton

2019

Groundwater

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Groundwater management decisions are often founded upon estimates of aquifer hydraulic properties, recharge and the rate of groundwater usage. Too often hydraulic properties are unavailable, recharge estimates are very uncertain, and usage is unmetered or infrequently metered over only recent years or estimated using numerical groundwater models decoupled from the drivers of drawdown. This paper extends the HydroSight groundwater time‐series package ( http://peterson-tim-j.github.io/HydroSight/) to allow the joint estimation of gross recharge, transmissivity, storativity, and daily usage at multiple production bores. A genetic evolutionary scheme was extended from estimating time‐series model parameters to also estimating time series of usage that honor metered volumes at each production bore and produces (1) the best fit with the observed hydrograph and (2) plausible estimates of actual evapotranspiration and hence recharge. The reliability of the approach was rigorously tested. Repeated calibration of models for four bores produced estimates of transmissivity, storativity, and mean recharge that varied by a factor of 0.22‐0.32, 0.13‐0.2, and 0.03‐0.48, respectively, when recharge boundary effects were low and the error in monthly, quarterly, and biannual metered usage was generally <10%. Application to the 30 observation bores within the Warrion groundwater management area (Australia), produced a coefficient of efficiency of ≥0.80 at 22 bores and ≥0.90 at 12 bores. The aquifer transmissivity and storativity were reasonably estimated, and were consistent with independent estimates, while mean gross recharge may be slightly overestimated. Overall, the approach allows greater insights from the available data and provides opportunity for the exploration of usage and climatic scenarios.

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θ_{F} (t) = \frac{α}{t} \exp (\frac{- r^{2} β}{t})

T = \frac{1}{4 π α}

S = 4 italicT β .

…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Joint Estimation of Gross Recharge, Groundwater Usage, and Hydraulic Properties within HydroSight

Peterson

Fulton

2019

Groundwater

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“…The basis of the approach is modeling of head time series using transfer function‐noise modeling with precipitation and evaporation as independent variables (Figure ). We use a setup that has proven itself in many practical applications (see e.g., Bakker et al ; Manzione et al ; Peterson and Western ; Shapoori et al ), consisting of: An impulse response function for precipitation which is used for convolution with the precipitation to give the transfer of the precipitation to its contribution to the piezometric head; An impulse response function for evaporation which is either a separately estimated function, or a factor times the function used for precipitation; A noise model with exponential decay. …”

Section: Methodsmentioning

confidence: 99%

“…The basis of the approach is modeling of head time series using transfer function-noise modeling with precipitation and evaporation as independent variables ( Figure 1). We use a setup that has proven itself in many practical applications (see e.g., Bakker et al 2007;Manzione et al 2010;Peterson and Western 2014;Shapoori et al 2015), consisting of:…”

Section: Transfer Function-noise Modelsmentioning

confidence: 99%

Automated Time Series Modeling for Piezometers in the National Database of the Netherlands

et al. 2018

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The Geological Survey of the Netherlands (TNO-GSN) maintains a public national database of groundwater head observations. Transfer function-noise modeling has been applied to the time series in order to extract the impulse response functions for precipitation and evaporation for each piezometer. An automated procedure has been developed to assess the quality of the time series and of the models. The time series models of sufficient quality offer far more homogeneous data on the piezometric head than the original measurements. This allows for improved mapping of the head at a specific date or of characteristics of the head like average summer or winter levels. Also, the separation of precipitation and evaporation from other influences is useful for groundwater management and policy. The individual time series models are available online with interactive graphics (https://www.grondwatertools.nl/grondwatertools-viewer). The spatial patterns of the impulse response function characteristics can support analyses of the groundwater system.

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“…Consequently, the plan mechanisms designed to manage the system under stress were not enacted. The same management plan is perceived differently based on climatic conditions, because clearly, both climate and management influence head levels and the respective impacts influencing an aquifer are difficult to disentangle [ Shapoori et al ., ].…”

Section: Introductionmentioning

confidence: 99%

Can we manage groundwater? A method to determine the quantitative testability of groundwater management plans

White

Peterson

Costelloe

et al. 2016

Water Resources Research

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Groundwater is the world's largest freshwater resource and due to overextraction, levels have declined in many regions causing extensive social and environmental impacts. Groundwater management seeks to balance and mitigate the detrimental impacts of development, with plans commonly used to outline management pathways. Thus, plan efficiency is crucial, but seldom are plans systematically and quantitatively assessed for effectiveness. This study frames groundwater management as a system control problem in order to develop a novel testability assessment rubric to determine if plans meet the requirements of a control loop, and subsequently, whether they can be quantitatively tested. Seven components of a management plan equivalent to basic components of a control loop were determined, and requirements of each component necessary to enable testability were defined. Each component was weighted based upon proposed relative importance, then segmented into rated categories depending on the degree the requirements were met. Component importance varied but, a defined objective or acceptable impact was necessary for plans to be testable. The rubric was developed within the context of the Australian groundwater management industry, and while use of the rubric is not limited to Australia, it was applied to 15 Australian groundwater management plans and approximately 47% were found to be testable. Considering the importance of effective groundwater management, and the central role of plans, our lack of ability to test many plans is concerning.

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Top-down groundwater hydrograph time-series modeling for climate-pumping decomposition

Cited by 27 publications

References 28 publications

Joint Estimation of Gross Recharge, Groundwater Usage, and Hydraulic Properties within HydroSight

Joint Estimation of Gross Recharge, Groundwater Usage, and Hydraulic Properties within HydroSight

Automated Time Series Modeling for Piezometers in the National Database of the Netherlands

Can we manage groundwater? A method to determine the quantitative testability of groundwater management plans

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