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  • 1
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    Toward Large‐Scale Soil Moisture Monitoring Using Rail‐Based Cosmic Ray Neutron Sensing (2023)
    Altdorff, Daniel ; Oswald, Sascha E. ; Zacharias, Steffen ; [et al.]
    Details
    Publication Date: 2023-12-14
    Description: Cosmic ray neutron sensing (CRNS) has become a promising method for soil water content (SWC) monitoring. Stationary CRNS offers hectare‐scale average SWC measurements at fixed locations maintenance‐free and continuous in time, while car‐borne CRNS roving can reveal spatial SWC patterns at medium scales, but only on certain survey days. The novel concept of a permanent mobile CRNS system on rails promises to combine the advantages of both methods, while its technical implementation, data processing and interpretation raised a new level of complexity. This study introduced a fully automatic CRNS rail‐borne system as the first of its kind, installed within the locomotive of a cargo train. Data recorded from September 2021 to July 2022 along an ∼9 km railway segment were analyzed, as repeatedly used by the train, supported by local SWC measurements (soil samples and dielectric methods), car‐borne and stationary CRNS. The results revealed consistent spatial SWC patterns and temporary variation along the track at a daily resolution. The observed variability was mostly related to surface features, seasonal dynamics and different responses of the railway segments to wetting and drying periods, while some variations were related to measurement uncertainties. The achieved medium scale of SWC mapping could support large scale hydrological modeling and detection of environmental risks, such as droughts and wildfires. Hence, rail‐borne CRNS has the chance to become a central tool of continuous SWC monitoring for larger scales (≤10‐km), with the additional benefit of providing root‐zone soil moisture, potentially even in sub‐daily resolution.
    Description: Key Points: The first rail‐borne Cosmic ray neutron sensing system for automatic and continuous soil water content monitoring at the hectare scale is presented. The system provided almost uninterrupted data from September 2021 to July 2022 along a 9 km railway track in the Harz low mountains, Germany. Results showed spatial pattern, related to surface features, seasonal change, and individual responses of railway parts to wetting and drying.
    Description: Helmholtz Centre for Environmental Research GmbH
    Description: Havelländische Eisenbahn Gesellschaft
    Description: Deutsche Forschungsgemeinschaft
    Description: Modular Observation Solutions for Earth Systems
    Description: Terrestrial Environmental Observatories in Germany
    Description: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/O1MHKR
    Description: http://www.nmdb.eu/
    Keywords: ddc:622.15 ; continuous soil moisture monitoring ; soil moisture products ; hydrological observations ; automatic geophysical roving ; root zone soil water ; time‐series soil water content mapping
    Language: English
    Type: doc-type:article
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  • 2
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    From Dynamic Groundwater Level Measurements to Regional Aquifer Parameters— Assessing the Power of Spectral Analysis (2022)
    Details
    Publication Date: 2022-10-18
    Description: Large‐scale groundwater models are required to estimate groundwater availability and to inform water management strategies on the national scale. However, parameterization of large‐scale groundwater models covering areas of major river basins and more is challenging due to the lack of observational data and the mismatch between the scales of modeling and measurements. In this work, we propose to bridge the scale gap and derive regional hydraulic parameters by spectral analysis of groundwater level fluctuations. We hypothesize that specific locations in aquifers can reveal regional parameters of the hydraulic system. We first generate ensembles of synthetic but realistic aquifers which systematically differ in complexity. Applying Liang and Zhang’s (2013), https://doi.org/10.1016/j.jhydrol.2012.11.044, semi‐analytical solution for the spectrum of hydraulic head time series, we identify for each ensemble member and at different locations representative aquifer parameters. Next, we extend our study to investigate the use of spectral analysis in more complex numerical models and in real settings. Our analyses indicate that the variance of inferred effective transmissivity and storativity values for stochastic aquifer ensembles is small for observation points which are far away from the Dirichlet boundary. Moreover, the head time series has to cover a period which is roughly 10 times as long as the characteristic time of the aquifer. In deterministic aquifer models we infer equivalent, regionally valid parameters. A sensitivity analysis further reveals that as long as the aquifer length and the position of the groundwater measurement location is roughly known, the parameters can be robustly estimated.
    Description: Plain Language Summary: We build large‐scale (regional) computer models of the subsurface flow conditions in order to quantify the long‐term shift in groundwater storage and response on the national level under changing climatic conditions and increasing human water demands. These models must be fed with hydrogeological parameters obtained from subsurface observation wells, drilling logs, and hydraulic tests in conjunction with (hydro)geological and geostatistical methods. In some regions these wells are sparsely distributed and derived parameters are representative only for small areas. We hypothesize that groundwater level records can reveal regional aquifer information when analyzed in the spectral domain. In order to bridge that scale gap and because groundwater level time series are generally available, we propose to infer regional parameters by analyzing the frequency content (spectrum) of long groundwater level time series. The required parameters were determined using mathematical formulations of the theoretical spectrum for simplified settings. We tested the methodology in computer models with limited complexity and found that the groundwater level time series indeed contain regional information if the time of observation is sufficiently long. Lastly, we apply the spectral analysis to real groundwater data to test the capability of the method to infer regional aquifer parameters in real aquifers.
    Description: Key Points: We successfully tested the spectral analysis of groundwater level fluctuations in numerical models and obtained regional aquifer parameters. In a sensitivity analysis of the spectral analysis using field data, the storativity and the response times could be robustly estimated. The application of the suggested methodology to the field data from a catchment in central Germany produced plausible results.
    Description: Helmholtz Centre for Environmental Research (UFZ)
    Description: Global Resource Water
    Description: German Federal Ministry of Education and Research (BMBF)
    Description: IDAEA‐CSIC
    Description: Barcelona City Council
    Description: https://github.com/ufz/ogs5
    Description: https://geostat-framework.github.io/
    Keywords: ddc:551.49
    Language: English
    Type: doc-type:article
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  • 3
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    Defining Hydrogeological Site Similarity with Hierarchical Agglomerative Clustering (2022)
    Blackwell Publishing Ltd | Malden, US
    Details
    Publication Date: 2024-02-28
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Hydrogeological information about an aquifer is difficult and costly to obtain, yet essential for the efficient management of groundwater resources. Transferring information from sampled sites to a specific site of interest can provide information when site‐specific data is lacking. Central to this approach is the notion of site similarity, which is necessary for determining relevant sites to include in the data transfer process. In this paper, we present a data‐driven method for defining site similarity. We apply this method to selecting groups of similar sites from which to derive prior distributions for the Bayesian estimation of hydraulic conductivity measurements at sites of interest. We conclude that there is now a unique opportunity to combine hydrogeological expertise with data‐driven methods to improve the predictive ability of stochastic hydrogeological models.〈/p〉
    Description: 〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉〈italic〉Article impact statement〈/italic〉: This article introduces hierarchical clustering as a method for defining a notion of site similarity; the aim of this method is to improve the derivation of prior distributions in Bayesian methods in hydrogeology.〈/p〉
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Description: https://github.com/GeoStat-Bayesian/geostatDB
    Description: https://github.com/GeoStat-Bayesian/exPrior
    Description: https://github.com/GeoStat-Bayesian/siteSimilarity
    Keywords: ddc:551.49 ; hydrogeological sites ; hydrogeological modeling
    Language: English
    Type: doc-type:article
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  • 4
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    How to Find Aquifer Statistics Utilizing Pumping Tests? Two Field Studies Using welltestpy (2021)
    Blackwell Publishing Ltd | Malden, US
    Details
    Publication Date: 2022-04-01
    Description: We present a workflow to estimate geostatistical aquifer parameters from pumping test data using the Python package welltestpy. The procedure of pumping test analysis is exemplified for two data sets from the Horkheimer Insel site and from the Lauswiesen site, Germany. The analysis is based on a semi‐analytical drawdown solution from the upscaling approach Radial Coarse Graining, which enables to infer log‐transmissivity variance and horizontal correlation length, beside mean transmissivity, and storativity, from pumping test data. We estimate these parameters of aquifer heterogeneity from type‐curve analysis and determine their sensitivity. This procedure, implemented in welltestpy, is a template for analyzing any pumping test. It goes beyond the possibilities of standard methods, for example, based on Theis' equation, which are limited to mean transmissivity and storativity. A sensitivity study showed the impact of observation well positions on the parameter estimation quality. The insights of this study help to optimize future test setups for geostatistical aquifer analysis and provides guidance for investigating pumping tests with regard to aquifer statistics using the open‐source software package welltestpy.
    Description: Article impact statement: We present a workflow to infer parameters of subsurface heterogeneity from pumping test data exemplified at two sites using welltestpy.
    Description: German Federal Environmental Foundation (DBU) http://dx.doi.org/10.13039/100007636
    Keywords: ddc:551.49
    Language: English
    Type: doc-type:article
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