Measurement Scale, Network Sampling Scale, and Groundwater Model Parameters

1996 ◽  
Vol 32 (1) ◽  
pp. 65-76 ◽  
Author(s):  
Roger Beckie
Keyword(s):  
Measurement Scale ◽  
Model Parameters ◽  
Groundwater Model ◽  
Network Sampling ◽  
Scale Network ◽  
Sampling Scale

scholarly journals Complexity versus simplicity: an example of groundwater model ranking with the Akaike Information Criterion

2012 ◽  
Vol 9 (8) ◽  
pp. 9687-9714 ◽  
Author(s):  
I. Engelhardt ◽  
J. G. De Aguinaga ◽  
H. Mikat ◽  
C. Schüth ◽  
O. Lenz ◽  
...  
Keyword(s):  
Akaike Information Criterion ◽  
Conceptual Models ◽  
Information Criterion ◽  
Model Parameters ◽  
Groundwater Model ◽  
Piezometric Head ◽  
Simulated Groundwater ◽  
Pumping Rates ◽  
Uncalibrated Model ◽  
Piezometric Heads

Abstract. A groundwater model characterized by a lack of field data to estimate hydraulic model parameters and boundary conditions combined with many piezometric head observations was investigated concerning model uncertainty. Different conceptual models with a stepwise increase from 0 to 30 adjustable parameters were calibrated using PEST. Residuals, sensitivities, the Akaike Information Criterion (AIC), and the likelihood of each model were computed. As expected, residuals and standard errors decreased with an increasing amount of adjustable model parameters. However, the model with only 15 adjusted parameters was evaluated by AIC as the best option with a likelihood of 98%, while the uncalibrated model obtained the worst AIC value. Computing of the AIC yielded the most important information to assess the model likelihood. Comparing only residuals of different conceptual models was less valuable and would result in an overparameterization of the conceptual model approach. Sensitivities of piezometric heads were highest for the model with five adjustable parameters reflecting also changes of extracted groundwater volumes. With increasing amount of adjustable parameters piezometric heads became less sensitive for the model calibration and changes of pumping rates were no longer displayed by the sensitivity coefficients. Therefore, when too many model parameters were adjusted, these parameters lost their impact on the model results. Additionally, using only sedimentological data to derive hydraulic parameters resulted in a large bias between measured and simulated groundwater level.

scholarly journals Coupling saturated and unsaturated flow: comparing the iterative and the non-iterative approach

2021 ◽  
Vol 25 (7) ◽  
pp. 4041-4059
Author(s):  
Natascha Brandhorst ◽  
Daniel Erdal ◽  
Insa Neuweiler
Keyword(s):  
Unsaturated Zone ◽  
Unsaturated Flow ◽  
Lower Boundary ◽  
3D Models ◽  
Specific Yield ◽  
Model Parameters ◽  
Test Cases ◽  
Iterative Approach ◽  
Groundwater Model ◽  
Fully Integrated

Abstract. Fully integrated three-dimensional (3D) physically based hydrologic models usually require many computational resources. For many applications, simplified models can be a cost-effective alternative. The 3D models of subsurface flow are often simplified by coupling a 2D groundwater model with multiple 1D models for the unsaturated zone. The crucial part of such models is the coupling between the two model compartments. In this work we compare two approaches for the coupling. One is iterative where the 1D unsaturated zone models go down to the impervious bottom of the aquifer, and the other one is non-iterative and uses a moving lower boundary for the unsaturated zone. In this context we also propose a new way of treating the specific yield, which plays a crucial role in linking the unsaturated and the groundwater model. Both models are applied to three test cases with increasing complexity and analyzed in terms of accuracy and speed compared to fully integrated model runs. The non-iterative approach is faster but does not yield a good accuracy for the model parameters in all applied test cases, whereas the iterative one gives good results in all cases. Which strategy is applied depends on the requirements: computational speed vs. model accuracy.

scholarly journals Hydrological Model for the Tude Å Catchment

1994 ◽  
Vol 25 (3) ◽  
pp. 145-166 ◽  
Author(s):  
Steen Christensen
Keyword(s):  
Field Data ◽  
Flow Model ◽  
Hydrological Model ◽  
Base Flow ◽  
Model Fit ◽  
Model Parameters ◽  
Groundwater Model ◽  
Confined Aquifer ◽  
Trial And Error ◽  
Actual Case

A numerical hydrological model has been developed for a 450 km2 Danish catchment using comprehensive field data. The model integrates a simple evapotranspiration model, a lumped flow model for a phreatic aquifer found in till, and a traditional two-dimensional groundwater model for a confined fluvio-glacial aquifer. A minimal but adequate number of model parameters were calibrated by trial and error to make the model fit 29-year time series of hydraulic head and stream runoff data. By simulating a “semi-natural” hydrological situation unaffected by withdrawals it is demonstrated that groundwater development can change the water balance considerably. In the actual case withdrawals induce a 25% increase in leakage from the phreatic to the confined aquifer, and reduce stream base flow by up to 30% in normal years, and up to 35% in dry years. On the other hand the reduction in base flow is considerably smaller for the upper stream catchments.

scholarly journals Development of a common scale for measuring healthy ageing across the world: results from the ATHLOS consortium

2020 ◽  
Author(s):  
Albert Sanchez-Niubo ◽  
Carlos G Forero ◽  
Yu-Tzu Wu ◽  
Iago Giné-Vázquez ◽  
Matthew Prina ◽  
...  
Keyword(s):  
Convergent Validity ◽  
Healthy Ageing ◽  
Measurement Scale ◽  
Model Parameters ◽  
Healthy Life ◽  
Irt Model ◽  
Item Functioning ◽  
Regression Framework ◽  
Common Scale ◽  
Project Data

Abstract Background Research efforts to measure the concept of healthy ageing have been diverse and limited to specific populations. This diversity limits the potential to compare healthy ageing across countries and/or populations. In this study, we developed a novel measurement scale of healthy ageing using worldwide cohorts. Methods In the Ageing Trajectories of Health-Longitudinal Opportunities and Synergies (ATHLOS) project, data from 16 international cohorts were harmonized. Using ATHLOS data, an item response theory (IRT) model was used to develop a scale with 41 items related to health and functioning. Measurement heterogeneity due to intra-dataset specificities was detected, applying differential item functioning via a logistic regression framework. The model accounted for specificities in model parameters by introducing cohort-specific parameters that rescaled scores to the main scale, using an equating procedure. Final scores were estimated for all individuals and converted to T-scores with a mean of 50 and a standard deviation of 10. Results A common scale was created for 343 915 individuals above 18 years of age from 16 studies. The scale showed solid evidence of concurrent validity regarding various sociodemographic, life and health factors, and convergent validity with healthy life expectancy (r = 0.81) and gross domestic product (r = 0.58). Survival curves showed that the scale could also be predictive of mortality. Conclusions The ATHLOS scale, due to its reliability and global representativeness, has the potential to contribute to worldwide research on healthy ageing.

scholarly journals Sequential and joint hydrogeophysical inversion using a field-scale groundwater model with ERT and TDEM data

2013 ◽  
Vol 17 (10) ◽  
pp. 4043-4060 ◽  
Author(s):  
D. Herckenrath ◽  
G. Fiandaca ◽  
E. Auken ◽  
P. Bauer-Gottwein
Keyword(s):  
Geophysical Data ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Data Sets ◽  
Groundwater Model ◽  
Field Scale ◽  
Geophysical Model ◽  
Time Domain Electromagnetic ◽  
Synthetic Groundwater ◽  
Airborne Geophysical Data

Abstract. Increasingly, ground-based and airborne geophysical data sets are used to inform groundwater models. Recent research focuses on establishing coupling relationships between geophysical and groundwater parameters. To fully exploit such information, this paper presents and compares different hydrogeophysical inversion approaches to inform a field-scale groundwater model with time domain electromagnetic (TDEM) and electrical resistivity tomography (ERT) data. In a sequential hydrogeophysical inversion (SHI) a groundwater model is calibrated with geophysical data by coupling groundwater model parameters with the inverted geophysical models. We subsequently compare the SHI with a joint hydrogeophysical inversion (JHI). In the JHI, a geophysical model is simultaneously inverted with a groundwater model by coupling the groundwater and geophysical parameters to explicitly account for an established petrophysical relationship and its accuracy. Simulations for a synthetic groundwater model and TDEM data showed improved estimates for groundwater model parameters that were coupled to relatively well-resolved geophysical parameters when employing a high-quality petrophysical relationship. Compared to a SHI these improvements were insignificant and geophysical parameter estimates became slightly worse. When employing a low-quality petrophysical relationship, groundwater model parameters improved less for both the SHI and JHI, where the SHI performed relatively better. When comparing a SHI and JHI for a real-world groundwater model and ERT data, differences in parameter estimates were small. For both cases investigated in this paper, the SHI seems favorable, taking into account parameter error, data fit and the complexity of implementing a JHI in combination with its larger computational burden.

scholarly journals Testing alternative uses of electromagnetic data to reduce the prediction error of groundwater models

2016 ◽  
Vol 20 (5) ◽  
pp. 1925-1946 ◽  
Author(s):  
Nikolaj Kruse Christensen ◽  
Steen Christensen ◽  
Ty Paul A. Ferre
Keyword(s):  
Electrical Resistivity ◽  
Hydraulic Conductivity ◽  
Prediction Error ◽  
Model Calibration ◽  
Hydrologic Model ◽  
Geophysical Data ◽  
Model Parameters ◽  
Calibration Data ◽  
Groundwater Model ◽  
And Inversion

Abstract. In spite of geophysics being used increasingly, it is often unclear how and when the integration of geophysical data and models can best improve the construction and predictive capability of groundwater models. This paper uses a newly developed HYdrogeophysical TEst-Bench (HYTEB) that is a collection of geological, groundwater and geophysical modeling and inversion software to demonstrate alternative uses of electromagnetic (EM) data for groundwater modeling in a hydrogeological environment consisting of various types of glacial deposits with typical hydraulic conductivities and electrical resistivities covering impermeable bedrock with low resistivity (clay). The synthetic 3-D reference system is designed so that there is a perfect relationship between hydraulic conductivity and electrical resistivity. For this system it is investigated to what extent groundwater model calibration and, often more importantly, model predictions can be improved by including in the calibration process electrical resistivity estimates obtained from TEM data. In all calibration cases, the hydraulic conductivity field is highly parameterized and the estimation is stabilized by (in most cases) geophysics-based regularization. For the studied system and inversion approaches it is found that resistivities estimated by sequential hydrogeophysical inversion (SHI) or joint hydrogeophysical inversion (JHI) should be used with caution as estimators of hydraulic conductivity or as regularization means for subsequent hydrological inversion. The limited groundwater model improvement obtained by using the geophysical data probably mainly arises from the way these data are used here: the alternative inversion approaches propagate geophysical estimation errors into the hydrologic model parameters. It was expected that JHI would compensate for this, but the hydrologic data were apparently insufficient to secure such compensation. With respect to reducing model prediction error, it depends on the type of prediction whether it has value to include geophysics in a joint or sequential hydrogeophysical model calibration. It is found that all calibrated models are good predictors of hydraulic head. When the stress situation is changed from that of the hydrologic calibration data, then all models make biased predictions of head change. All calibrated models turn out to be very poor predictors of the pumping well's recharge area and groundwater age. The reason for this is that distributed recharge is parameterized as depending on estimated hydraulic conductivity of the upper model layer, which tends to be underestimated. Another important insight from our analysis is thus that either recharge should be parameterized and estimated in a different way, or other types of data should be added to better constrain the recharge estimates.

scholarly journals Conceptualization and development of multi-layered groundwater model in transient condition

2021 ◽  
Vol 11 (10) ◽  
Author(s):  
Padam Jee Omar ◽  
Shishir Gaur ◽  
P. K. S. Dikshit
Keyword(s):  
Groundwater Flow ◽  
Water Resource ◽  
Groundwater Modeling ◽  
Ganga River ◽  
Population Increase ◽  
Model Parameters ◽  
Groundwater Model ◽  
Groundwater Head ◽  
Comparison Results ◽  
Groundwater Demand

AbstractEffective management of water resource is essential in arid and semi-arid areas of India. In Bihar, for drinking purpose humans, livestock is dependent on the groundwater as well as in agricultural areas groundwater plays an important role in irrigation directly or indirectly. There is rise in the groundwater demand due to rapid population increase and fast industrialization. To meet this groundwater demand, excessive withdrawal of groundwater is a point of concern due to limited storage of it. Assessment of the groundwater was done by preparing a numerical model of the groundwater flow. This model is capable of solving large groundwater problems and associated complexity with it. In this study, a transient multi-layered groundwater flow model was conceptualized and developed for the Koshi River basin. In north Bihar plains, the Koshi River is one of the biggest tributaries of the Ganga River system. Koshi originates from the lower part of Tibet and joins the Ganga River in Katihar district, Bihar, India. After model development, calibration of the model was also done, by considering three model parameters, to represent the actual field conditions. For validation of the model, fifteen observation wells have been selected in the area. With the help of observation well data, computed and observed heads were compared. Comparison results have been found to be encouraging and the computed groundwater head matched with the observed water head to a realistic level of accuracy. Developed groundwater model is used to predict the groundwater head and flow budget in the concerned area. The study revealed that groundwater modeling is an important method for knowing the behavior of aquifer systems and to detect groundwater head under different varying hydrological stresses. This type of study will be beneficial for the hydrologist and water resource engineers to predict the groundwater flow behavior, before implementing any project or to implement a correction scheme.

scholarly journals Sequential and joint hydrogeophysical inversion using a field-scale groundwater model with ERT and TDEM data

2013 ◽  
Vol 10 (4) ◽  
pp. 4655-4707 ◽  
Author(s):  
D. Herckenrath ◽  
G. Fiandaca ◽  
E. Auken ◽  
P. Bauer-Gottwein
Keyword(s):  
Parameter Estimates ◽  
Model Parameters ◽  
Groundwater Model ◽  
Field Scale ◽  
Geophysical Model ◽  
Geophysical Parameter ◽  
Coupling Constraints ◽  
Time Domain Electromagnetic ◽  
Synthetic Groundwater ◽  
Geometric Relationship

Abstract. Increasingly, ground-based and airborne geophysical datasets are used to inform groundwater models. Recent research focuses on establishing coupling relationships between geophysical and groundwater parameters. To fully exploit such information, this paper presents and compares a joint hydrogeophysical inversion (JHI) approach and sequential hydrogeophysical inversion (SHI) approach to inform a field-scale groundwater model with Time Domain Electromagnetic (TDEM) and Electrical Resistivity Tomography (ERT) data. The implemented SHI coupled inverted geophysical models with groundwater parameters, where the strength of the coupling was based on geophysical parameter resolution. To test whether the implemented SHI over- or underestimated the coupling strength between groundwater and geophysical model, we compared its results with a JHI in which a geophysical model is simultaneously inverted with a groundwater model using additional coupling constraints that explicitly account for an established petrophysical relationship and its accuracy. The first set of simulations for a synthetic groundwater model and TDEM data, employing a high-quality petrophysical and geometric relationship, showed improved estimates for groundwater model parameters that were coupled to relative well-resolved geophysical parameters. Compared to a SHI these improvements were insignificant and geophysical parameter estimates became slightly worse. In a second set of simulations, employing a low-quality petrophysical relationship, groundwater parameter improved less for both the SHI and JHI, where the SHI performed slightly better. For a real-world groundwater model and ERT data, different parameter estimates were obtained with a JHI and SHI. Parameter uncertainty was reduced but was similar for the SHI and JHI. The geometric constraint showed little impact while the petrophysical constraint showed significant changes in geophysical and groundwater parameters. For both cases investigated in this paper, the SHI seems favorable, taking in account parameter error, data fit and the complexity of implementing a JHI in combination with its larger computational burden.

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