Articles | Volume 28, issue 12
https://doi.org/10.5194/hess-28-2661-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-28-2661-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A comprehensive framework for stochastic calibration and sensitivity analysis of large-scale groundwater models
Andrea Manzoni
Dipartimento di Ingegneria Civile e Ambientale (DICA), Politecnico di Milano, 20133 Milano, Italy
Giovanni Michele Porta
Dipartimento di Ingegneria Civile e Ambientale (DICA), Politecnico di Milano, 20133 Milano, Italy
Laura Guadagnini
Dipartimento di Ingegneria Civile e Ambientale (DICA), Politecnico di Milano, 20133 Milano, Italy
Alberto Guadagnini
Dipartimento di Ingegneria Civile e Ambientale (DICA), Politecnico di Milano, 20133 Milano, Italy
Monica Riva
CORRESPONDING AUTHOR
Dipartimento di Ingegneria Civile e Ambientale (DICA), Politecnico di Milano, 20133 Milano, Italy
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Stefano Conversi, Daniela Carrion, Francesco Gioia, Alessandra Norcini, and Monica Riva
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W12-2024, 19–27, https://doi.org/10.5194/isprs-archives-XLVIII-4-W12-2024-19-2024, https://doi.org/10.5194/isprs-archives-XLVIII-4-W12-2024-19-2024, 2024
David Luttenauer, Aronne Dell'Oca, Alberto Guadagnini, Sylvain Weill, and Philippe Ackerer
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-73, https://doi.org/10.5194/hess-2024-73, 2024
Preprint under review for HESS
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Land Surface Model outputs (evaporation, transpiration, groundwater recharge) are influenced by uncertain parameters. Global sensitivity metrics provide a ranking of the importance of uncertain factors. Evaporation is directly influenced by the net radiation and by the parameters associated with the top litter layer. Transpiration appears as mainly influenced by the vegetation characteristics and by albedo. Groundwater recharge is influenced mainly by soil-related parameters.
S. Conversi, D. Carrion, A. Norcini, and M. Riva
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 1363–1371, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1363-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1363-2023, 2023
Yaniv Edery, Martin Stolar, Giovanni Porta, and Alberto Guadagnini
Hydrol. Earth Syst. Sci., 25, 5905–5915, https://doi.org/10.5194/hess-25-5905-2021, https://doi.org/10.5194/hess-25-5905-2021, 2021
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The interplay between dissolution, precipitation and transport is widely encountered in porous media, from CO2 storage to cave formation in carbonate rocks. We show that dissolution occurs along preferential flow paths with high hydraulic conductivity, while precipitation occurs at locations close to yet separated from these flow paths, thus further funneling the flow and changing the probability density function of the transport, as measured on the altered conductivity field at various times.
Giulia Ceriotti, Claudio Geloni, Matilde Dalla Rosa, Alberto Guadagnini, and Giovanni Porta
Hydrol. Earth Syst. Sci., 25, 3539–3553, https://doi.org/10.5194/hess-25-3539-2021, https://doi.org/10.5194/hess-25-3539-2021, 2021
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Understanding the natural generation of CO2 in sedimentary basins is key to optimizing exploitation of natural resources and exploring feasibility of carbon capture and storage. We present a novel modeling approach to estimate the probability of CO2 generation caused by geochemical reactions at high temperatures and pressure in realistic sedimentary basins. Our model allows estimation of the most probable CO2 source depth and generation rate as a function of the composition of the source rock.
Chuan-An Xia, Xiaodong Luo, Bill X. Hu, Monica Riva, and Alberto Guadagnini
Hydrol. Earth Syst. Sci., 25, 1689–1709, https://doi.org/10.5194/hess-25-1689-2021, https://doi.org/10.5194/hess-25-1689-2021, 2021
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Our study shows that (i) monitoring wells installed with packers provide the (overall) best conductivity estimates; (ii) conductivity estimates anchored on information from partially and fully screened wells are of similar quality; (iii) inflation of the measurement-error covariance matrix can improve conductivity estimates when a simplified flow model is adopted; and (iv) when compared to the MC-based EnKF, the MEs-based EnKF can efficiently and accurately estimate conductivity and head fields.
Aronne Dell'Oca, Alberto Guadagnini, and Monica Riva
Hydrol. Earth Syst. Sci., 24, 3097–3109, https://doi.org/10.5194/hess-24-3097-2020, https://doi.org/10.5194/hess-24-3097-2020, 2020
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Permeability of natural systems exhibits heterogeneous spatial variations linked with the size of the measurement support scale. As the latter becomes coarser, the system appearance is less heterogeneous. As such, sets of permeability data associated with differing support scales provide diverse amounts of information. In this contribution, we leverage information theory to quantify the information content of gas permeability datasets collected with four diverse measurement support scales.
Martina Siena and Monica Riva
Hydrol. Earth Syst. Sci., 22, 2971–2985, https://doi.org/10.5194/hess-22-2971-2018, https://doi.org/10.5194/hess-22-2971-2018, 2018
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The development of sustainable strategies for groundwater resources exploitation in coastal regions is subordinated to the characterization of seawater intrusion (SWI) phenomena. We develop a numerical model tailored to a real coastal aquifer to investigate quantitatively the joint effects of hydraulic properties heterogeneity and pumping configuration on saltwater inland penetration and saltwater–freshwater mixing. Our results allowed identifying efficient scenarios for the reduction of SWI.
Aronne Dell'Oca, Monica Riva, and Alberto Guadagnini
Hydrol. Earth Syst. Sci., 21, 6219–6234, https://doi.org/10.5194/hess-21-6219-2017, https://doi.org/10.5194/hess-21-6219-2017, 2017
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We propose new metrics to assist global sensitivity analysis of Earth systems. Our approach allows assessing the impact of model parameters on the first four statistical moments of a target model output, allowing us to ascertain which parameters can affect some moments of the model output pdf while being uninfluential to others. Our approach is fully compatible with analysis in the context of model complexity reduction, design of experiment, uncertainty quantification and risk assessment.
A. Guadagnini, S. P. Neuman, T. Nan, M. Riva, and C. L. Winter
Hydrol. Earth Syst. Sci., 19, 729–745, https://doi.org/10.5194/hess-19-729-2015, https://doi.org/10.5194/hess-19-729-2015, 2015
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Previously we have shown that many earth-system and other variables can be viewed as samples from scale mixtures of truncated fractional Brownian motion or fractional Gaussian noise. Here we study statistical scaling of extreme absolute increments associated with such samples. As a real example we analyze neutron porosities from deep boreholes in diverse depositional units. Phenomena we uncover are relevant to the analysis of fluid flow and solute transport in complex hydrogeologic environments.
M. Riva, S. P. Neuman, and A. Guadagnini
Nonlin. Processes Geophys., 20, 549–561, https://doi.org/10.5194/npg-20-549-2013, https://doi.org/10.5194/npg-20-549-2013, 2013
Related subject area
Subject: Groundwater hydrology | Techniques and Approaches: Stochastic approaches
Towards a community-wide effort for benchmarking in subsurface hydrological inversion: benchmarking cases, high-fidelity reference solutions, procedure and a first comparison
An ensemble-based approach for pumping optimization in an island aquifer considering parameter, observation and climate uncertainty
Improving understanding of groundwater flow in an alpine karst system by reconstructing its geologic history using conduit network model ensembles
The effects of rain and evapotranspiration statistics on groundwater recharge estimations for semi-arid environments
Characterization of the highly fractured zone at the Grimsel Test Site based on hydraulic tomography
Influence of low-frequency variability on high and low groundwater levels: example of aquifers in the Paris Basin
Technical note: Using long short-term memory models to fill data gaps in hydrological monitoring networks
Technical note: Discharge response of a confined aquifer with variable thickness to temporal, nonstationary, random recharge processes
Data assimilation with multiple types of observation boreholes via the ensemble Kalman filter embedded within stochastic moment equations
A field evidence model: how to predict transport in heterogeneous aquifers at low investigation level
3D multiple-point statistics simulations of the Roussillon Continental Pliocene aquifer using DeeSse
Technical Note: Improved sampling of behavioral subsurface flow model parameters using active subspaces
Efficient screening of groundwater head monitoring data for anthropogenic effects and measurement errors
Regionalization with hierarchical hydrologic similarity and ex situ data in the context of groundwater recharge estimation at ungauged watersheds
Long-term groundwater recharge rates across India by in situ measurements
Stochastic hydrogeology's biggest hurdles analyzed and its big blind spot
Contributions to uncertainty related to hydrostratigraphic modeling using multiple-point statistics
Recent trends of groundwater temperatures in Austria
Moment-based metrics for global sensitivity analysis of hydrological systems
Multiple-point statistical simulation for hydrogeological models: 3-D training image development and conditioning strategies
Characterizing the spatiotemporal variability of groundwater levels of alluvial aquifers in different settings using drought indices
Testing the use of standardised indices and GRACE satellite data to estimate the European 2015 groundwater drought in near-real time
Modeling 3-D permeability distribution in alluvial fans using facies architecture and geophysical acquisitions
A Bayesian consistent dual ensemble Kalman filter for state-parameter estimation in subsurface hydrology
Technical note: Application of artificial neural networks in groundwater table forecasting – a case study in a Singapore swamp forest
Regional analysis of groundwater droughts using hydrograph classification
Scalable statistics of correlated random variables and extremes applied to deep borehole porosities
Observed groundwater temperature response to recent climate change
The effect of training image and secondary data integration with multiple-point geostatistics in groundwater modelling
Is high-resolution inverse characterization of heterogeneous river bed hydraulic conductivities needed and possible?
Investigation of solute transport in nonstationary unsaturated flow fields
Extended power-law scaling of heavy-tailed random air-permeability fields in fractured and sedimentary rocks
Stochastic analysis of field-scale heat advection in heterogeneous aquifers
Groundwater flow inverse modeling in non-MultiGaussian media: performance assessment of the normal-score Ensemble Kalman Filter
Extended power-law scaling of air permeabilities measured on a block of tuff
Quantifying flow and remediation zone uncertainties for partially opened wells in heterogeneous aquifers
Bayesian approach for three-dimensional aquifer characterization at the Hanford 300 Area
Spectral approach to seawater intrusion in heterogeneous coastal aquifers
Teng Xu, Sinan Xiao, Sebastian Reuschen, Nils Wildt, Harrie-Jan Hendricks Franssen, and Wolfgang Nowak
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-60, https://doi.org/10.5194/hess-2024-60, 2024
Revised manuscript accepted for HESS
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We provide a set of benchmarking scenarios for geostatistical inversion, and we encourage the scientific community to use these to compare their newly developed methods. To facilitate transparent, appropriate, and uncertainty-aware comparison of novel methods, we also provide accurate reference solutions, a high-end reference algorithm, and a diverse set of benchmarking metrics, all of which are publicly available. With this, we seek to foster more targeted and transparent progress in the field.
Cécile Coulon, Jeremy T. White, Alexandre Pryet, Laura Gatel, and Jean-Michel Lemieux
Hydrol. Earth Syst. Sci., 28, 303–319, https://doi.org/10.5194/hess-28-303-2024, https://doi.org/10.5194/hess-28-303-2024, 2024
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In coastal areas, groundwater managers require information on the risk of well salinization associated with various pumping scenarios. We developed a modeling approach to identify the optimal tradeoff between groundwater pumping and probability of salinization, considering model parameter and historical observation uncertainty as well as uncertainty in sea level and recharge projections. The workflow can be implemented in a wide range of coastal settings.
Chloé Fandel, Ty Ferré, François Miville, Philippe Renard, and Nico Goldscheider
Hydrol. Earth Syst. Sci., 27, 4205–4215, https://doi.org/10.5194/hess-27-4205-2023, https://doi.org/10.5194/hess-27-4205-2023, 2023
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From the surface, it is hard to tell where underground cave systems are located. We developed a computer model to create maps of the probable cave network in an area, based on the geologic setting. We then applied our approach in reverse: in a region where an old cave network was mapped, we used modeling to test what the geologic setting might have been like when the caves formed. This is useful because understanding past cave formation can help us predict where unmapped caves are located today.
Tuvia Turkeltaub and Golan Bel
Hydrol. Earth Syst. Sci., 27, 289–302, https://doi.org/10.5194/hess-27-289-2023, https://doi.org/10.5194/hess-27-289-2023, 2023
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Groundwater is an essential resource affected by climate conditions and anthropogenic activities. Estimations of groundwater recharge under current and future climate conditions require long-term climate records that are scarce. Different methods to synthesize climate data, based on observations, are used to estimate groundwater recharge. In terms of groundwater recharge estimation, the best synthesis method is based on the daily statistics corrected to match the observed monthly statistics.
Lisa Maria Ringel, Mohammadreza Jalali, and Peter Bayer
Hydrol. Earth Syst. Sci., 26, 6443–6455, https://doi.org/10.5194/hess-26-6443-2022, https://doi.org/10.5194/hess-26-6443-2022, 2022
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Fractured rocks host a class of aquifers that serve as major freshwater resources worldwide. This work is dedicated to resolving the three-dimensional hydraulic and structural properties of fractured rock. For this purpose, hydraulic tomography experiments at the Grimsel Test Site in Switzerland are utilized, and the discrete fracture network is inverted. The comparison of the inversion results with independent findings from other studies demonstrates the validity of the approach.
Lisa Baulon, Nicolas Massei, Delphine Allier, Matthieu Fournier, and Hélène Bessiere
Hydrol. Earth Syst. Sci., 26, 2829–2854, https://doi.org/10.5194/hess-26-2829-2022, https://doi.org/10.5194/hess-26-2829-2022, 2022
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Aquifers often act as low-pass filters, dampening high-frequency (intra-annual) and amplifying low-frequency (LFV, multi-annual to multidecadal) variabilities originating from climate variability. By processing groundwater level signals, we show the key role of LFV in the occurrence of groundwater extremes (GWEs). Results highlight how changes in LFV may impact future GWEs as well as the importance of correct representation of LFV in general circulation model outputs for GWE projection.
Huiying Ren, Erol Cromwell, Ben Kravitz, and Xingyuan Chen
Hydrol. Earth Syst. Sci., 26, 1727–1743, https://doi.org/10.5194/hess-26-1727-2022, https://doi.org/10.5194/hess-26-1727-2022, 2022
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We used a deep learning method called long short-term memory (LSTM) to fill gaps in data collected by hydrologic monitoring networks. LSTM accounted for correlations in space and time and nonlinear trends in data. Compared to a traditional regression-based time-series method, LSTM performed comparably when filling gaps in data with smooth patterns, while it better captured highly dynamic patterns in data. Capturing such dynamics is critical for understanding dynamic complex system behaviors.
Ching-Min Chang, Chuen-Fa Ni, We-Ci Li, Chi-Ping Lin, and I-Hsien Lee
Hydrol. Earth Syst. Sci., 25, 2387–2397, https://doi.org/10.5194/hess-25-2387-2021, https://doi.org/10.5194/hess-25-2387-2021, 2021
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A transfer function to describe the variation in the integrated specific discharge in response to the temporal variation in the rainfall event in the frequency domain is developed. It can be used to quantify the variability in the integrated discharge field induced by the variation in rainfall field or to simulate the discharge response of the system to any varying rainfall input, at any time resolution, using the convolution model.
Chuan-An Xia, Xiaodong Luo, Bill X. Hu, Monica Riva, and Alberto Guadagnini
Hydrol. Earth Syst. Sci., 25, 1689–1709, https://doi.org/10.5194/hess-25-1689-2021, https://doi.org/10.5194/hess-25-1689-2021, 2021
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Our study shows that (i) monitoring wells installed with packers provide the (overall) best conductivity estimates; (ii) conductivity estimates anchored on information from partially and fully screened wells are of similar quality; (iii) inflation of the measurement-error covariance matrix can improve conductivity estimates when a simplified flow model is adopted; and (iv) when compared to the MC-based EnKF, the MEs-based EnKF can efficiently and accurately estimate conductivity and head fields.
Alraune Zech, Peter Dietrich, Sabine Attinger, and Georg Teutsch
Hydrol. Earth Syst. Sci., 25, 1–15, https://doi.org/10.5194/hess-25-1-2021, https://doi.org/10.5194/hess-25-1-2021, 2021
Valentin Dall'Alba, Philippe Renard, Julien Straubhaar, Benoit Issautier, Cédric Duvail, and Yvan Caballero
Hydrol. Earth Syst. Sci., 24, 4997–5013, https://doi.org/10.5194/hess-24-4997-2020, https://doi.org/10.5194/hess-24-4997-2020, 2020
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Due to climate and population evolution, increased pressure is put on the groundwater resource, which calls for better understanding and models. In this paper, we describe a novel workflow to model the geological heterogeneity of coastal aquifers and apply it to the Roussillon plain (southern France). The main strength of the workflow is its capability to model aquifer heterogeneity when only sparse data are available while honoring the local geological trends and quantifying uncertainty.
Daniel Erdal and Olaf A. Cirpka
Hydrol. Earth Syst. Sci., 24, 4567–4574, https://doi.org/10.5194/hess-24-4567-2020, https://doi.org/10.5194/hess-24-4567-2020, 2020
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Assessing model sensitivities with ensemble-based methods can be prohibitively expensive when large parts of the plausible parameter space result in model simulations with nonrealistic results. In a previous work, we used the method of active subspaces to create a proxy model with the purpose of filtering out such unrealistic runs at low cost. This work details a notable improvement in the efficiency of the original sampling scheme, without loss of accuracy.
Christian Lehr and Gunnar Lischeid
Hydrol. Earth Syst. Sci., 24, 501–513, https://doi.org/10.5194/hess-24-501-2020, https://doi.org/10.5194/hess-24-501-2020, 2020
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A screening method for the fast identification of well-specific peculiarities in hydrographs of groundwater head monitoring networks is suggested and tested. The only information required is a set of time series of groundwater head readings all measured at the same instants of time. The results were used to check the data for measurement errors and to identify wells with possible anthropogenic influence.
Ching-Fu Chang and Yoram Rubin
Hydrol. Earth Syst. Sci., 23, 2417–2438, https://doi.org/10.5194/hess-23-2417-2019, https://doi.org/10.5194/hess-23-2417-2019, 2019
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Estimates of hydrologic responses at ungauged watersheds can be conditioned on information transferred from other gauged watersheds. This paper presents an approach to consider the variable controls on information transfer among watersheds under different conditions while at the same time featuring uncertainty representation in both the model structure and the model parameters.
Soumendra N. Bhanja, Abhijit Mukherjee, R. Rangarajan, Bridget R. Scanlon, Pragnaditya Malakar, and Shubha Verma
Hydrol. Earth Syst. Sci., 23, 711–722, https://doi.org/10.5194/hess-23-711-2019, https://doi.org/10.5194/hess-23-711-2019, 2019
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Groundwater depletion in India has been a much-debated issue in recent years. Here we investigate long-term, spatiotemporal variation in prevailing groundwater recharge rates across India. Groundwater recharge rates have been estimated based on field-scale groundwater-level measurements and the tracer injection approach; recharge rates from the two estimates compared favorably. The role of precipitation in controlling groundwater recharge is studied.
Yoram Rubin, Ching-Fu Chang, Jiancong Chen, Karina Cucchi, Bradley Harken, Falk Heße, and Heather Savoy
Hydrol. Earth Syst. Sci., 22, 5675–5695, https://doi.org/10.5194/hess-22-5675-2018, https://doi.org/10.5194/hess-22-5675-2018, 2018
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This paper addresses questions related to the adoption of stochastic methods in hydrogeology, looking at factors such as environmental regulations, financial incentives, higher education, and the collective feedback loop involving these factors. We show that stochastic hydrogeology's blind spot is in focusing on risk while ignoring uncertainty, to the detriment of its potential clients. The imbalance between the treatments of risk and uncertainty is shown to be common to multiple disciplines.
Adrian A. S. Barfod, Troels N. Vilhelmsen, Flemming Jørgensen, Anders V. Christiansen, Anne-Sophie Høyer, Julien Straubhaar, and Ingelise Møller
Hydrol. Earth Syst. Sci., 22, 5485–5508, https://doi.org/10.5194/hess-22-5485-2018, https://doi.org/10.5194/hess-22-5485-2018, 2018
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The focus of this study is on the uncertainty related to using multiple-point statistics (MPS) for stochastic modeling of the upper 200 m of the subsurface. The main research goal is to showcase how MPS methods can be used on real-world hydrogeophysical data and show how the uncertainty related to changing the underlying MPS setup propagates into the finalized 3-D subsurface models.
Susanne A. Benz, Peter Bayer, Gerfried Winkler, and Philipp Blum
Hydrol. Earth Syst. Sci., 22, 3143–3154, https://doi.org/10.5194/hess-22-3143-2018, https://doi.org/10.5194/hess-22-3143-2018, 2018
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Climate change is one of the most pressing challenges modern society faces. Increasing temperatures are observed both above ground and, as discussed here, in the groundwater – the source of most drinking water. Within Austria average temperature increased by 0.7 °C over the past 20 years, with an increase of more than 3 °C in some wells and temperature decrease in others. However, these extreme changes can be linked to local events such as the construction of a new drinking water supply.
Aronne Dell'Oca, Monica Riva, and Alberto Guadagnini
Hydrol. Earth Syst. Sci., 21, 6219–6234, https://doi.org/10.5194/hess-21-6219-2017, https://doi.org/10.5194/hess-21-6219-2017, 2017
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We propose new metrics to assist global sensitivity analysis of Earth systems. Our approach allows assessing the impact of model parameters on the first four statistical moments of a target model output, allowing us to ascertain which parameters can affect some moments of the model output pdf while being uninfluential to others. Our approach is fully compatible with analysis in the context of model complexity reduction, design of experiment, uncertainty quantification and risk assessment.
Anne-Sophie Høyer, Giulio Vignoli, Thomas Mejer Hansen, Le Thanh Vu, Donald A. Keefer, and Flemming Jørgensen
Hydrol. Earth Syst. Sci., 21, 6069–6089, https://doi.org/10.5194/hess-21-6069-2017, https://doi.org/10.5194/hess-21-6069-2017, 2017
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We present a novel approach for 3-D geostatistical simulations. It includes practical strategies for the development of realistic 3-D training images and for incorporating the diverse geological and geophysical inputs together with their uncertainty levels (due to measurement inaccuracies and scale mismatch). Inputs consist of well logs, seismics, and an existing 3-D geomodel. The simulation domain (45 million voxels) coincides with the Miocene unit over 2810 km2 across the Danish–German border.
Johannes Christoph Haas and Steffen Birk
Hydrol. Earth Syst. Sci., 21, 2421–2448, https://doi.org/10.5194/hess-21-2421-2017, https://doi.org/10.5194/hess-21-2421-2017, 2017
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We show that the variability of groundwater levels within an Alpine river valley is more strongly affected by human impacts on rivers than by extreme events in precipitation. The influence of precipitation is found to be more pronounced in the shallow wells of the Alpine foreland. Groundwater levels, river stages and precipitation behave more similar under drought than under flood conditions and generally exhibit a tendency towards more similar behavior in the most recent decade.
Anne F. Van Loon, Rohini Kumar, and Vimal Mishra
Hydrol. Earth Syst. Sci., 21, 1947–1971, https://doi.org/10.5194/hess-21-1947-2017, https://doi.org/10.5194/hess-21-1947-2017, 2017
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Summer 2015 was extremely dry in Europe, hampering groundwater supply to irrigation and drinking water. For effective management, the groundwater situation should be monitored in real time, but data are not available. We tested two methods to estimate groundwater in near-real time, based on satellite data and using the relationship between rainfall and historic groundwater levels. The second method gave a good spatially variable representation of the 2015 groundwater drought in Europe.
Lin Zhu, Huili Gong, Zhenxue Dai, Gaoxuan Guo, and Pietro Teatini
Hydrol. Earth Syst. Sci., 21, 721–733, https://doi.org/10.5194/hess-21-721-2017, https://doi.org/10.5194/hess-21-721-2017, 2017
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We developed a method to characterize the distribution and variance of the hydraulic conductivity k in a multiple-zone alluvial fan by fusing multiple-source data. Consistently with the scales of the sedimentary transport energy, the k variance of the various facies decreases from the upper to the lower portion along the flow direction. The 3-D distribution of k is consistent with that of the facies. The potentialities of the proposed approach are tested on the Chaobai River megafan, China.
Boujemaa Ait-El-Fquih, Mohamad El Gharamti, and Ibrahim Hoteit
Hydrol. Earth Syst. Sci., 20, 3289–3307, https://doi.org/10.5194/hess-20-3289-2016, https://doi.org/10.5194/hess-20-3289-2016, 2016
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We derive a new dual ensemble Kalman filter (EnKF) for state-parameter estimation. The derivation is based on the one-step-ahead smoothing formulation, and unlike the standard dual EnKF, it is consistent with the Bayesian formulation of the state-parameter estimation problem and uses the observations in both state smoothing and forecast. This is shown to enhance the performance and robustness of the dual EnKF in experiments conducted with a two-dimensional synthetic groundwater aquifer model.
Yabin Sun, Dadiyorto Wendi, Dong Eon Kim, and Shie-Yui Liong
Hydrol. Earth Syst. Sci., 20, 1405–1412, https://doi.org/10.5194/hess-20-1405-2016, https://doi.org/10.5194/hess-20-1405-2016, 2016
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This study applies artificial neural networks (ANN) to predict the groundwater table variations in a tropical wetland in Singapore. Surrounding reservoir levels and rainfall are selected as ANN inputs. The limited number of inputs eliminates the data-demanding restrictions inherent in the physical-based numerical models. The forecast is made at 4 locations with 3 leading times up to 7 days. The ANN forecast shows promising accuracy with decreasing performance when leading time progresses.
J. P. Bloomfield, B. P. Marchant, S. H. Bricker, and R. B. Morgan
Hydrol. Earth Syst. Sci., 19, 4327–4344, https://doi.org/10.5194/hess-19-4327-2015, https://doi.org/10.5194/hess-19-4327-2015, 2015
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To improve the design of drought monitoring networks and water resource management during episodes of drought, there is a need for a better understanding of spatial variations in the response of aquifers to major meteorological droughts. This paper is the first to describe a suite of methods to quantify such variations. Using an analysis of groundwater level data for a case study from the UK, the influence of catchment characteristics on the varied response of groundwater to droughts is explored
A. Guadagnini, S. P. Neuman, T. Nan, M. Riva, and C. L. Winter
Hydrol. Earth Syst. Sci., 19, 729–745, https://doi.org/10.5194/hess-19-729-2015, https://doi.org/10.5194/hess-19-729-2015, 2015
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Previously we have shown that many earth-system and other variables can be viewed as samples from scale mixtures of truncated fractional Brownian motion or fractional Gaussian noise. Here we study statistical scaling of extreme absolute increments associated with such samples. As a real example we analyze neutron porosities from deep boreholes in diverse depositional units. Phenomena we uncover are relevant to the analysis of fluid flow and solute transport in complex hydrogeologic environments.
K. Menberg, P. Blum, B. L. Kurylyk, and P. Bayer
Hydrol. Earth Syst. Sci., 18, 4453–4466, https://doi.org/10.5194/hess-18-4453-2014, https://doi.org/10.5194/hess-18-4453-2014, 2014
X. L. He, T. O. Sonnenborg, F. Jørgensen, and K. H. Jensen
Hydrol. Earth Syst. Sci., 18, 2943–2954, https://doi.org/10.5194/hess-18-2943-2014, https://doi.org/10.5194/hess-18-2943-2014, 2014
W. Kurtz, H.-J. Hendricks Franssen, P. Brunner, and H. Vereecken
Hydrol. Earth Syst. Sci., 17, 3795–3813, https://doi.org/10.5194/hess-17-3795-2013, https://doi.org/10.5194/hess-17-3795-2013, 2013
C.-M. Chang and H.-D. Yeh
Hydrol. Earth Syst. Sci., 16, 4049–4055, https://doi.org/10.5194/hess-16-4049-2012, https://doi.org/10.5194/hess-16-4049-2012, 2012
A. Guadagnini, M. Riva, and S. P. Neuman
Hydrol. Earth Syst. Sci., 16, 3249–3260, https://doi.org/10.5194/hess-16-3249-2012, https://doi.org/10.5194/hess-16-3249-2012, 2012
C.-M. Chang and H.-D. Yeh
Hydrol. Earth Syst. Sci., 16, 641–648, https://doi.org/10.5194/hess-16-641-2012, https://doi.org/10.5194/hess-16-641-2012, 2012
L. Li, H. Zhou, H. J. Hendricks Franssen, and J. J. Gómez-Hernández
Hydrol. Earth Syst. Sci., 16, 573–590, https://doi.org/10.5194/hess-16-573-2012, https://doi.org/10.5194/hess-16-573-2012, 2012
M. Siena, A. Guadagnini, M. Riva, and S. P. Neuman
Hydrol. Earth Syst. Sci., 16, 29–42, https://doi.org/10.5194/hess-16-29-2012, https://doi.org/10.5194/hess-16-29-2012, 2012
C.-F. Ni, C.-P. Lin, S.-G. Li, and J.-S. Chen
Hydrol. Earth Syst. Sci., 15, 2291–2301, https://doi.org/10.5194/hess-15-2291-2011, https://doi.org/10.5194/hess-15-2291-2011, 2011
H. Murakami, X. Chen, M. S. Hahn, Y. Liu, M. L. Rockhold, V. R. Vermeul, J. M. Zachara, and Y. Rubin
Hydrol. Earth Syst. Sci., 14, 1989–2001, https://doi.org/10.5194/hess-14-1989-2010, https://doi.org/10.5194/hess-14-1989-2010, 2010
C.-M. Chang and H.-D. Yeh
Hydrol. Earth Syst. Sci., 14, 719–727, https://doi.org/10.5194/hess-14-719-2010, https://doi.org/10.5194/hess-14-719-2010, 2010
Cited articles
AdB-Po: Piano di Gestione del distretto idrografico del fiume Po al 2021, https://www.adbpo.it/PianoAcque2021/PdGPo2021_22dic21/, 2021 (in Italian).
Agenzia Regionale per la Protezione Ambientale Piemonte: Portale acque, Agenzia Regionale per la Protezione Ambientale Piemonte [data set], https://www.arpa.piemonte.it/rischinaturali/accesso-ai-dati, 2020 (in Italian).
Agrawala, S.: Climate change in the European Alps: adapting winter tourism and natural hazards management, OECD (Organisation for Economic Co-operation and Development, https://doi.org/10.1787/9789264031692-en, 2007.
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop evapotranspiration: Guidelines for computing crop water requirements, FAO Irrigation and Drainage Paper No. 56, Food and Agriculture Organization of the United Nations, ISBN 92-5-104219-5, 1998.
Amanambu, A. C., Obarein, O. A., Mossa, J., Li, L., Ayeni, S. S., Balogun, O., Oyebamiji, A., and Ochege, F. U.: Groundwater system and climate change: Present status and future considerations, J. Hydrol., 589, 125163, https://doi.org/10.1016/j.jhydrol.2020.125163, 2020.
Antonellini, M., Mollema, P., Giambastiani, B., Bishop, K., Caruso, L., Minchio, A., Pellegrini, L., Sabia, M., Ulazzi, E., and Gabbianelli, G.: Salt water intrusion in the coastal aquifer of the southern Po Plain, Italy, Hydrogeol. J., 16, 1541–1556, https://doi.org/10.1007/s10040-008-0319-9, 2008.
Balestrini, R., Delconte, C. A., Sacchi, E., and Buffagni, A.: Groundwater-dependent ecosystems as transfer vectors of nitrogen from the aquifer to surface waters in agricultural basins: The fontanili of the Po Plain (Italy), Sci. Total Environ., 753, 141995, https://doi.org/10.1016/j.scitotenv.2020.141995, 2021.
Bianchi Janetti, E., Guadagnini, L., Riva, M., and Guadagnini, A.: Global sensitivity analyses of multiple conceptual models with uncertain parameters driving groundwater flow in a regional-scale sedimentary aquifer, J. Hydrol., 574, 544–556, https://doi.org/10.1016/j.jhydrol.2019.04.035, 2019.
Bianchi Janetti, E., Riva, M., and Guadagnini, A.: Natural springs protection and probabilistic risk assessment under uncertain conditions, Sci. Total Environ., 751, 141430, https://doi.org/10.1016/j.scitotenv.2020.141430, 2021.
Bilke, L., Fischer, T., Naumov, D., Lehmann, C., Wang, W., Lu, R., Meng, B., Rink, K., Grunwald, N., Buchwald, J., Silbermann, C., Habel, R., Günther, L., Mollaali, M., Meisel, T., Randow, J., Einspänner, S., Shao, H., Kurgyis, K., Kolditz, O., and Garibay, J.: OpenGeoSys, Version 6.4.3, Zenodo [code], https://doi.org/10.5281/zenodo.7092676, 2022.
Bonafè, G., Morgillo, A., and Minguzzi, E.: Weather types and wind patterns classification in the Po Valley, during the PEGASOS field campaign (summer 2012), in: EGU General Assembly Conference Abstracts, p. 11939, 2014.
Bozzola, M. and Swanson, T.: Policy implications of climate variability on agriculture: Water management in the Po river basin, Italy, Environ. Sci. Policy, 43, 26–38, https://doi.org/10.1016/j.envsci.2013.12.002, 2014.
Campolongo, F., Cariboni, J., and Saltelli, A.: An effective screening design for sensitivity analysis of large models, Environ. Modell. Softw., 22, 1509–1518, https://doi.org/10.1016/j.envsoft.2006.10.004, 2007.
Carcano, C. and Piccin, A.: Geologia degli acquiferi Padani della Regione Lombardia Regione Lombardia, Eni Divisione Agip, https://www.cartografia.regione.lombardia.it/metadata/acquiferi/doc/ (last access: 1 October 2022), 2001.
Carrera, J. and Neuman, S. P.: Estimation of Aquifer Parameters Under Transient and Steady State Conditions: 1. Maximum Likelihood Method Incorporating Prior Information, Water Resour. Res., 22, 199–210, https://doi.org/10.1029/WR022i002p00199, 1986.
Colombani, N., Volta, G., Osti, A., and Mastrocicco, M.: Misleading reconstruction of seawater intrusion via integral depth sampling, J. Hydrol., 536, 320–326, https://doi.org/10.1016/j.jhydrol.2016.03.011, 2016.
Dagdia, Z. C. and Mirchev, M.: When Evolutionary Computing Meets Astro- and Geoinformatics, in: Knowledge Discovery in Big Data from Astronomy and Earth Observation, edited by: Škoda, P. and Adam, F., Elsevier, 283–306, https://doi.org/10.1016/B978-0-12-819154-5.00026-6, 2020.
d'Andrimont, R., Verhegghen, A., Lemoine, G., Kempeneers, P., Meroni, M., and van der Velde, M.: From parcel to continental scale – A first European crop type map based on Sentinel-1 and LUCAS Copernicus in-situ observations, Remote Sens. Environ., 266, 112708, https://doi.org/10.1016/j.rse.2021.112708, 2021.
De Caro, M., Perico, R., Crosta, G. B., Frattini, P., and Volpi, G.: A regional-scale conceptual and numerical groundwater flow model in fluvio-glacial sediments for the Milan Metropolitan area (Northern Italy), Journal of Hydrology: Regional Studies, 29, 100683, https://doi.org/10.1016/j.ejrh.2020.100683, 2020.
de Graaf, I., Condon, L., and Maxwell, R.: Hyper-Resolution Continental-Scale 3-D Aquifer Parameterization for Groundwater Modeling, Water Resour. Res., 56, e2019WR026004, https://doi.org/10.1029/2019WR026004, 2020.
De Lange, W. J., Prinsen, G. F., Hoogewoud, J. C., Veldhuizen, A. A., Verkaik, J., Oude Essink, G. H. P., Van Walsum, P. E. V., Delsman, J. R., Hunink, J. C., Massop, H. T. L., and Kroon, T.: An operational, multi-scale, multi-model system for consensus-based, integrated water management and policy analysis: The Netherlands Hydrological Instrument, Environ. Modell. Softw., 59, 98–108, https://doi.org/10.1016/j.envsoft.2014.05.009, 2014.
Dell'Oca, A., Riva, M., and Guadagnini, A.: Moment-based metrics for global sensitivity analysis of hydrological systems, Hydrol. Earth Syst. Sci., 21, 6219–6234, https://doi.org/10.5194/hess-21-6219-2017, 2017.
Dell'Oca, A., Riva, M., and Guadagnini, A.: Global Sensitivity Analysis for Multiple Interpretive Models With Uncertain Parameters, Water Resour. Res., 56, e2019WR025754, https://doi.org/10.1029/2019WR025754, 2020.
Dell'Oca, A., Manzoni, A., Siena, M., Bona, N. G., Moghadasi, L., Miarelli, M., Renna, D., and Guadagnini, A.: Stochastic inverse modeling of transient laboratory-scale three-dimensional two-phase core flooding scenarios, Int. J. Heat Mass. Tran., 202, 123716, https://doi.org/10.1016/j.ijheatmasstransfer.2022.123716, 2023.
Dripps, W. R. and Bradbury, K. R.: A simple daily soil-water balance model for estimating the spatial and temporal distribution of groundwater recharge in temperate humid areas, Hydrogeol. J., 15, 433–444, https://doi.org/10.1007/s10040-007-0160-6, 2007.
Elsasser, H. and Bürki, R.: Climate change as a threat to tourism in the Alps, Clim. Res., 20, 253–257, https://doi.org/10.3354/cr020253, 2002.
ESA: Copernicus DEM, ESA [data set], https://doi.org/10.5270/ESA-c5d3d65, 2019.
Éupolis Lombardia: Piano di Tutela delle Aque - revisione dei corpi idrici lombardia, 2016.
European Environment Agency (EEA): CORINE Land Cover 2018, EEA [data set], https://doi.org/10.2909/71c95a07-e296-44fc-b22b-415f42acfdf0, 2018.
Farinotti, D., Pistocchi, A., and Huss, M.: From dwindling ice to headwater lakes: Could dams replace glaciers in the European Alps?, Environ. Res. Lett., 11, 054022, https://doi.org/10.1088/1748-9326/11/5/054022, 2016.
Fratianni, S. and Acquaotta, F.: The Climate of Italy, Landscapes and Landforms of Italy, Springer International Publishing, 29–38, https://doi.org/10.1007/978-3-319-26194-2_4, 2017.
Geuzaine, C. and Remacle, J.-F.: Gmsh: A 3-D finite element mesh generator with built-in pre- and post-processing facilities, Int. J. Numer. Meth. Eng., 79, 1309–1331, https://doi.org/10.1002/nme.2579, 2009.
Giuliano, G.: Ground water in the PO basin: some problems relating to its use and protection, Sci. Total Environ., 171, 17–27, 1995.
Grimm, M., Jones, R. J. A., Rusco, E., and Montanarella, L.: Soil Erosion Risk in Italy: a revised USLE approach, European Soil Bureau Research Report No. 11, EUR 20677 EN, 28 pp., Office for Official Publications of the European Communities, Luxembourg, 2023.
Guadagnini, L., Menafoglio, A., Sanchez-Vila, X., and Guadagnini, A.: Probabilistic assessment of spatial heterogeneity of natural background concentrations in large-scale groundwater bodies through Functional Geostatistics, Sci. Total Environ., 740, 140139, https://doi.org/10.1016/j.scitotenv.2020.140139, 2020.
Hargreaves, G. H. and Samani, Z. A.: Reference Crop Evapotranspiration from Temperature, Appl. Eng. Agric., 1, 96–99, https://doi.org/10.13031/2013.26773, 1985.
Hendricks Franssen, H. J., Alcolea, A., Riva, M., Bakr, M., van der Wiel, N., Stauffer, F., and Guadagnini, A.: A comparison of seven methods for the inverse modelling of groundwater flow. Application to the characterisation of well catchments, Adv. Water Resour., 32, 851–872, https://doi.org/10.1016/j.advwatres.2009.02.011, 2009.
Højberg, A. L., Troldborg, L., Stisen, S., Christensen, B. B. S., and Henriksen, H. J.: Stakeholder driven update and improvement of a national water resources model, Environ. Modell. Softw., 40, 202–213, https://doi.org/10.1016/j.envsoft.2012.09.010, 2013.
ISPRA: Reticolo Idrografico Nazionale, ISPRA [data set], https://geodati.gov.it/resource/id/ispra_rm:01Idro250N_DT (last access: 1 October 2022), 2010.
ISTAT: Public water supply use, ISTAT [data set], http://dati.istat.it/, 2020.
Kazakis, N., Busico, G., Colombani, N., Mastrocicco, M., Pavlou, A., and Voudouris, K.: GALDIT-SUSI a modified method to account for surface water bodies in the assessment of aquifer vulnerability to seawater intrusion, J. Environ. Manage., 235, 257–265, https://doi.org/10.1016/j.jenvman.2019.01.069, 2019.
Khan, S., Grudniewski, P., Muhammad, Y. S., and Sobey, A. J.: The benefits of co-evolutionary Genetic Algorithms in voyage optimisation, Ocean Eng., 245, 110261, https://doi.org/10.1016/j.oceaneng.2021.110261, 2022.
Kim, K. B., Kwon, H.-H., and Han, D.: Exploration of warm-up period in conceptual hydrological modelling, J. Hydrol., 556, 194–210, https://doi.org/10.1016/j.jhydrol.2017.11.015, 2018.
Manzoni, A.: manzoniandrea/Large_Basin_Scale_Recarge_Rate: Large_Basin_Scale_Recarge_Ratev1.0.0, Version Large_Basin_Scale_Recarge_Ratev1.0.0, Zenodo [code], https://doi.org/10.5281/zenodo.10013442, 2023.
Manzoni, A.: manzoniandrea/Large-scaleGWFlow: largeScale, Version v1.0.6, Zenodo [code], https://doi.org/10.5281/zenodo.10664413, 2024.
Manzoni, A., Porta, G. M., Guadagnini, L., Guadagnini, A., and Riva, M.: Probabilistic reconstruction via machine-learning of the Po watershed aquifer system (Italy), Hydrogeol. J., 31, 1547–1563, https://doi.org/10.1007/s10040-023-02677-8, 2023.
Mather, B., Müller, R. D., O'Neill, C., Beall, A., Vervoort, R. W., and Moresi, L.: Constraining the response of continental-scale groundwater flow to climate change, Sci. Rep.-UK, 12, 4539, https://doi.org/10.1038/s41598-022-08384-w, 2022.
Maxwell, R. M., Condon, L. E., and Kollet, S. J.: A high-resolution simulation of groundwater and surface water over most of the continental US with the integrated hydrologic model ParFlow v3, Geosci. Model Dev., 8, 923–937, https://doi.org/10.5194/gmd-8-923-2015, 2015.
Mishra, S. K. and Singh, V. P.: Soil Conservation Service Curve Number (SCS-CN) Methodology, Springer Science & Business Media, https://doi.org/10.1007/978-94-017-0147-1, 2003.
Molnau, M. and Bissell, V.: A continuous frozen ground index for flood forecasting, in: Proceedings 51st Annual Meeting Western Snow Conference, Vancouver, 19–21 April 1983, 109–119, 1983.
Morgan Jr., G. M.: A General Description of the Hail Problem in the Po Valley of Northern Italy, J. Appl. Meteorol., 12, 338–353, https://doi.org/10.1175/1520-0450(1973)012<0338:AGDOTH>2.0.CO;2, 1973.
Morris, M. D.: Factorial Sampling Plans for Preliminary Computational Experiments, Technometrics, 33, 161–174, https://doi.org/10.2307/1269043, 1991.
Muñoz-Sabater, J., Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., Martens, B., Miralles, D. G., Piles, M., Rodríguez-Fernández, N. J., Zsoter, E., Buontempo, C., and Thépaut, J.-N.: ERA5-Land: a state-of-the-art global reanalysis dataset for land applications, Earth Syst. Sci. Data, 13, 4349–4383, https://doi.org/10.5194/essd-13-4349-2021, 2021.
Naz, B. S., Sharples, W., Ma, Y., Goergen, K., and Kollet, S.: Continental-scale evaluation of a fully distributed coupled land surface and groundwater model, ParFlow-CLM (v3.6.0), over Europe, Geosci. Model Dev., 16, 1617–1639, https://doi.org/10.5194/gmd-16-1617-202, 2023.
Nespoli, M., Cenni, N., Belardinelli, M. E., and Marcaccio, M.: The interaction between displacements and water level changes due to natural and anthropogenic effects in the Po Plain (Italy): The different point of view of GNSS and piezometers, J. Hydrol., 596, 126112, https://doi.org/10.1016/j.jhydrol.2021.126112, 2021.
Neuman, S. P.: Maximum likelihood Bayesian averaging of uncertain model predictions, Stoch. Env. Res. Risk A., 17, 291–305, https://doi.org/10.1007/s00477-003-0151-7, 2003.
OpenStreetMap: OpenStreetMap database [PostgreSQL], OpenStreetMap Foundation, Cambridge, UK, https://gisdata.mapog.com/italy/Municipality%20level%204 (last access: 1 October 2022), 2021.
Panzeri, M., Riva, M., Guadagnini, A., and Neuman, S. P.: EnKF coupled with groundwater flow moment equations applied to Lauswiesen aquifer, Germany, J. Hydrol., 521, 205–216, https://doi.org/10.1016/j.jhydrol.2014.11.057, 2015.
Pianosi, F., Beven, K., Freer, J., Hall, J. W., Rougier, J., Stephenson, D. B., and Wagener, T.: Sensitivity analysis of environmental models: A systematic review with practical workflow, Environ. Modell. Softw., 79, 214–232, https://doi.org/10.1016/j.envsoft.2016.02.008, 1 May 2016.
Poggio, L., de Sousa, L. M., Batjes, N. H., Heuvelink, G. B. M., Kempen, B., Ribeiro, E., and Rossiter, D.: SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty, SOIL, 7, 217–240, https://doi.org/10.5194/soil-7-217-2021, 2021.
Razavi, S. and Gupta, H. V.: What do we mean by sensitivity analysis? The need for comprehensive characterization of “global” sensitivity in Earth and Environmental systems models, Water Resour. Res., 51, 3070–3092, https://doi.org/10.1002/2014WR016527, 2015.
Regione Emilia-Romagna and ENI-AGIP: Riserve idriche sotterranee della Regione Emilia-Romagna. S.EL.CA, Firenze, 1998 (in Italian).
Regione Emilia-Romagna: Piezometrie e qualità delle acque sotterranee nella pianura emiliano-romagnola, Regione Emilia-Romagna [data set], https://ambiente.regione.emilia-romagna.it/it/geologia/cartografia/webgis-banchedati/piezometrie-qualita-acque-sotterranee (last access: 1 October 2022), 2020.
Regione Emilia-Romagna: Riserve idriche sotterranee della Regione Emilia-Romagna, 1998 (in Italian).
Regione Lombardia: Banca dati geologica sottosuolo, Regione Lombardia [data set], https://www.geoportale.regione.lombardia.it/metadati?p_p_id=detailSheetMetadata_WAR_gptmetadataportlet&p_p_lifecycle=0&p_p_state=normal&p_p_mode=view&_detailSheetMetadata_WAR_gptmetadataportlet_identifier=r_lombar%3Aad085d2a-519f-4ed6-a84f-b81de6cec1db&_jsfBridgeRedirect=true (last access: 1 August 2022), 2016.
Regione Lombardia and ENI-AGIP: Geologia degli acquiferi padani della Regione Lombardia. S.EL.CA, Firenze, 2002 (in Italian).
Regione Lombardia: Geoportale della Lombardia, Regione Lombardia [data set], https://www.geoportale.regione.lombardia.it/ (last access: 1 March 2022), 2021.
Regione Piemonte: Geoportale Piemonte, Regione Piemonte [data set], https://www.geoportale.piemonte.it/geonetwork/srv/eng/catalog.search#/metadata/r_piemon:023ef6df-b781-4751-b5d2-a442427916d0 (last access: 1 June 2022), 2022.
Ricci Lucchi, F., Colalongo, M. L., Cremonini, G., Gasperi, G. F., Iaccarino, S., Papani, G., Raffi, S., and Rio, D.: Evoluzione sedimentaria e paleogeografica del margine appenninico (Sedimentary and palaeogeographic evolution of the Apenninic margin), Guida alla geologia del margine appenninico padano, Guide geologiche regionali, Soc. Geol. Ital., 17–46, 1982.
Rink, K., Bilke, L., and Kolditz, O.: Visualisation Strategies for Modelling and Simulation Using Geoscientific Data, in: 1st Workshop on Visualisation in Environmental Sciences (EnvirVis), EuroVis 2013, Leipzig, Germany, 17–18 June 2013, The Eurographics Association, 47–51, https://doi.org/10.2312/PE.EnvirVis.EnvirVis13.047-051, 2013.
Riva, M., Guadagnini, A., Neuman, S. P., Janetti, E. B., and Malama, B.: Inverse analysis of stochastic moment equations for transient flow in randomly heterogeneous media, Adv. Water Resour., 32, 1495–1507, https://doi.org/10.1016/j.advwatres.2009.07.003, 2009.
Roland, C. J., Zoet, L. K., Rawling, J. E., and Cardiff, M.: Seasonality in cold coast bluff erosion processes, Geomorphology, 374, 107520, https://doi.org/10.1016/j.geomorph.2020.107520, 2021.
Rossi, M., Donnini, M., and Beddini, G.: Nationwide groundwater recharge evaluation for a sustainable water withdrawal over Italy, Journal of Hydrology: Regional Studies, 43, 101172, https://doi.org/10.1016/j.ejrh.2022.101172, 2022.
Schaap, M. G., Leij, F. J., and van Genuchten, M. T.: ROSETTA: a computer program for estimating soil hydraulic parameters with hierarchical pedotransfer functions, J. Hydrol., 251, 163–176, https://doi.org/10.1016/S0022-1694(01)00466-8, 2001.
Schroeder, W., Martin, K., and Lorensen, B.: The Visualization Toolkit, 4th edn., edited by: Squillacote, A., Kitware, 528 pp., ISBN-10: 193093419X, ISBN-13: 978-1930934191, 2006.
SEDAC: Gridded Population of the World (GPWv4), Version 4: Population Density, Revision 11, SEDAC [data set], https://doi.org/10.7927/H49C6VHW, 2018.
Shrestha, P., Sulis, M., Masbou, M., Kollet, S., and Simmer, C.: A scale-consistent terrestrial systems modeling platform based on COSMO, CLM, and ParFlow, Mon. Weather Rev., 142, 3466–3483, https://doi.org/10.1175/MWR-D-14-00029.1, 2014.
Shuler, C., Brewington, L., and El-Kadi, A. I.: A participatory approach to assessing groundwater recharge under future climate and land-cover scenarios, Tutuila, American Samoa, Journal of Hydrology: Regional Studies, 34, 100785, https://doi.org/10.1016/j.ejrh.2021.100785, 2021.
Siena, M. and Riva, M.: Impact of geostatistical reconstruction approaches on model calibration for flow in highly heterogeneous aquifers, Stoch. Env. Res. Risk A., 34, 1591–1606, https://doi.org/10.1007/s00477-020-01865-2, 2020.
Simoncini, D. and Zhang, K. Y. J.: Population-Based Sampling and Fragment-Based De Novo Protein Structure Prediction, in: Encyclopedia of Bioinformatics and Computational Biology, edited by: Ranganathan, S., Gribskov, M., Nakai, K., and Schönbach, C., Elsevier, 774–784, https://doi.org/10.1016/B978-0-12-809633-8.20507-4, 2019.
Soltani, S. S., Fahs, M., Bitar, A. A., and Ataie-Ashtiani, B.: Improvement of soil moisture and groundwater level estimations using a scale-consistent river parameterization for the coupled ParFlow-CLM hydrological model: A case study of the Upper Rhine Basin, J. Hydrol., 610, 127991, https://doi.org/10.1016/j.jhydrol.2022.127991, 2022.
Sophocleous, M. and Perkins, S. P.: Methodology and application of combined watershed and ground-water models in Kansas, J. Hydrol., 236, 185–201, https://doi.org/10.1016/S0022-1694(00)00293-6, 2000.
Storn, R. and Price, K.: A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces, J. Global Optim., 11, 341–359, https://doi.org/10.1023/A:1008202821328, 1997.
Thornthwaite, C. W.: An Approach toward a Rational Classification of Climate, Geogr. Rev., 38, 55–94, https://doi.org/10.2307/210739, 1948.
Thornthwaite, C. W. and Mather, J. R.: The water balance, Publications in Climatology, Drexel Institute of Technology, Laboratory of Climatology, 1955.
Thornthwaite, C. W. and Matter, J. R.: Instructions and Tables for Computing Potential Evaporation and the Water Balance, Climatology, Drexel Institute of Technology, Laboratory of Climatology, 1957.
Trunfio, G. A.: A Cooperative Coevolutionary Differential Evolution Algorithm with Adaptive Subcomponents, Procedia Comput. Sci., 51, 834–844, https://doi.org/10.1016/j.procs.2015.05.209, 2015.
Tusar, T. and Filipic, B.: Differential evolution versus genetic algorithms in multiobjective optimization, Evolutionary Multi-Criterion Optimization, Springer Berlin Heidelberg, 257–271, https://doi.org/10.1007/978-3-540-70928-2_22, 2007.
Vrugt, J. A., Stauffer, P. H., Wöhling, Th., Robinson, B. A., and Vesselinov, V. V.: Inverse Modeling of Subsurface Flow and Transport Properties: A Review with New Developments, Vadose Zone J., 7, 843–864, https://doi.org/10.2136/vzj2007.0078, 2008.
Westenbroek, S. M., Engott, J. A., Kelson, V. A., and Hunt, R. J.: SWB Version 2.0 – A soil-water-balance code for estimating net infiltration and other water-budget components, U.S. Geological Survey, Techniques and Methods 6–A59, https://doi.org/10.3133/tm6A59, 2018.
Wriedt, G., Van der Velde, M., Aloe, A., and Bouraoui, F.: Estimating irrigation water requirements in Europe, J. Hydrol., 373, 527–544, https://doi.org/10.1016/j.jhydrol.2009.05.018, 2009.
Yang, Z., Tang, K., and Yao X.: Large scale evolutionary optimization using cooperative coevolution, Inform. Sciences, 178, 2985–2999, https://doi.org/10.1016/j.ins.2008.02.017, 2008.
Ye, M., Pohlmann, K. F., Chapman, J. B., Pohll, G. M., and Reeves, D. M.: A model-averaging method for assessing groundwater conceptual model uncertainty, Ground Water, 48, 716–728, https://doi.org/10.1111/j.1745-6584.2009.00633.x, 2010.
Zhang, J., Felzer, B. S., and Troy, T. J.: Extreme precipitation drives groundwater recharge: the Northern High Plains Aquifer, central United States, 1950–2010, Hydrol. Process., 30, 2533–2545, https://doi.org/10.1002/hyp.10809, 2016.
Zhou, H., Gómez-Hernández, J. J., and Li, L.: Inverse methods in hydrogeology: Evolution and recent trends, Adv. Water Resour., 63, 22–37, https://doi.org/10.1016/j.advwatres.2013.10.014, 2014.
Zhou, Y. and Li, W.: A review of regional groundwater flow modeling, Geosci. Front., 2, 205–214, https://doi.org/10.1016/j.gsf.2011.03.003, 2011.
Short summary
We introduce a comprehensive methodology that combines multi-objective optimization, global sensitivity analysis (GSA) and 3D groundwater modeling to analyze subsurface flow dynamics across large-scale domains. In this way, we effectively consider the inherent uncertainty associated with subsurface system characterizations and their interactions with surface waterbodies. We demonstrate the effectiveness of our proposed approach by applying it to the largest groundwater system in Italy.
We introduce a comprehensive methodology that combines multi-objective optimization, global...