|   | 
Details
   web
Records
Author Seidl, C.; Wheeler, S.A.; Page, D.
Title Understanding the global success criteria for managed aquifer recharge schemes Type Journal Article
Year 2024 Publication Journal of Hydrology Abbreviated Journal
Volume 628 Issue Pages 130469
Keywords Managed Aquifer Recharge (MAR), Fuzzy-set Qualitative Comparative Analysis, Water banking, Groundwater, Water management, Water storage
Abstract (down) Water availability and quality issues will only gain importance in the future, with climate change impacts putting increasing pressure on global water resources. Dealing with these challenges requires drawing on all available water management tools, including Managed Aquifer Recharge (MAR). Although MAR has seen increasing global implementation during the last half a century, it is still often overlooked as a management tool. While technical, bio-physical, and hydrogeological aspects of MAR are well researched, this cannot be said for socio-economic and other governance factors. Where information is available, this study seeks to understand the conditions necessary for MAR success. We apply fuzzy-set Qualitative Comparative Analysis on 313 world MAR applications, and also model separately for high- and low-middle-income countries. Results show that sophisticated hydrogeological site understanding and scheme operation is paramount for MAR success, as is utilizing natural water sources for high value end uses. Successful high-income country MAR schemes tend to be large and utilize natural water sources and sophisticated water injection and treatment methods to augment potable water supply; while successful low-middle-income country schemes are not large, older than 20 years, and use gravity infiltration methods and (limited) no water treatment. These findings will help inform the future suitability of MAR application design and its likely success within various contexts.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0022-1694 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number THL @ christoph.kuells @ Seidl2024130469 Serial 273
Permanent link to this record
 

 
Author Hubbard, B.E.; Gallegos, T.J.; Stengel, V.; Hoefen, T.M.; Kokaly, R.F.; Elliott, B.
Title Hyperspectral (VNIR-SWIR) analysis of roll front uranium host rocks and industrial minerals from Karnes and Live Oak Counties, Texas Coastal Plain Type Journal Article
Year 2024 Publication Journal of Geochemical Exploration Abbreviated Journal
Volume 257 Issue Pages 107370
Keywords Critical minerals, Hyperspectral, Industrial minerals, Mine waste, Texas coastal plain, Uranium
Abstract (down) VNIR-SWIR (400–2500 nm) reflectance measurements were made on the surfaces of various cores, cuttings and sample splits of sedimentary rocks from the Tertiary Jackson Group, and Catahoula, Oakville and Goliad Formations. These rocks vary in composition and texture from mudstone and claystone to sandstone and are known host rocks for roll front uranium occurrences in Karnes and Live Oak Counties, Texas. Spectral reflectance profiles, 569 in total, were reduced to 125 representative spectral signatures, which were analyzed using the U.S. Geological Survey’s (USGS) Material Identification and Characterization Algorithm (MICA). MICA uses an automated continuum-removal procedure together with a least-squares linear regression to determine the fit of observed sample spectral absorption features to those of reference mineral standards in a spectral library. The reference minerals include various clay, mica, carbonate, ferric and ferrous iron minerals and their mixtures. In addition, absorption feature band-depth analysis was done to identify rock surfaces exhibiting absorption features related to uranium and zeolite minerals, which were not included in the command files used to execute MICA. Rocks from each of the four geologic units produced broadly similar spectral signatures as a result of comparable mineral compositions, but there were some notable differences. For example, Ca- and Na-montmorillonite was matched most frequently to the spectral absorption features in 2-μm (∼2000–2500 nm) wavelengths, while goethite occurred often at 1-μm (∼400–1000 nm) wavelengths. The latter is related to limonitic iron-staining in and around oxidized zones of the uranium roll front as described in previous papers. Rocks of the Jackson Group differed from those of the Catahoula, Oakville and Goliad units in that the former exhibited spectral features we interpret as being due to the presence of lignite-bearing mudstone layers. Goliad rocks exhibit spectral features related to dolomite, gypsum, anhydrite, and an unidentified green clay mineral that is possibly glauconite. Jackson Group rocks also exhibit weak but well-resolved absorption features at 964 and 1157 nm related to either or both zeolite minerals clinoptilolite and heulandite. These zeolite minerals and a few spectra exhibiting hydrous silica absorption features are indicative of alteration of volcanic glass in tuffaceous mudstone and claystone layers. A few sample spectra exhibited strong absorption features at around 1135 nm related to the uranium mineral coffinite. Both the 1135 nm coffinite and 1157 nm zeolite absorption features overlap somewhat, potentially making them difficult to distinguish without additional hyperspectral field, laboratory or remote sensing data. The results of this study were compared to mixtures of minerals described for ore, gangue and alteration minerals in deposit models for sandstone-hosted uranium, sedimentary bentonite and sedimentary zeolite. Use of these spectra can help facilitate mapping of both waste materials from the legacy mining of the above commodities, as well as future exploration and resource assessment activities.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0375-6742 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number THL @ christoph.kuells @ hubbard_hyperspectral_2024 Serial 178
Permanent link to this record
 

 
Author Marteleto, T. de P.; Abreu, A.E.S. de; Barbosa, M.B.; Yoshinaga-Pereira, S.; Bertolo, R.A.; Enzweiler, J.
Title Groundwater apparent ages and isotopic composition in Crystalline, Diabase and Tubarão aquifers contact area in Campinas, Southeastern Brazil Type Journal Article
Year 2024 Publication Journal of South American Earth Sciences Abbreviated Journal
Volume 135 Issue Pages 104783
Keywords Fractured aquifer, Groundwater mixing, Isotopes, Water management
Abstract (down) This study refines the hydrogeological conceptual model of an area with three interconnected aquifers, namely the Crystalline Aquifer System (CAS – igneous and metamorphic rocks), which is in contact with the Tubarão Aquifer System (TAS – sedimentary rocks) and the Diabase Aquifer System (DAS – diabase rocks). The detailed investigation involved geophysical logging and hydraulic and hydrodynamic characterization with straddle packers in a local tubular well, in which groundwater presents high uranium concentrations. Hydrogeochemical and isotope (δ2H, δ18O, 3H, δ13C, 14C) analysis in this well and in other three neighboring wells, with lower U concentrations, showed that ancient and modern waters (3H from <0.8 to 1.12 TU, 14C from 69.43 to 78.72 pMC) mix within the aquifer. During groundwater pumping, vertical fractures in the diabase aquifer possibly induce water mixing and recharge of the deeper levels of the aquifers from shallow layers. The high [U] are related to ancient waters from a confined aquifer hosted in CAS that reaches the wells through hydraulically active fractures located deeper than 159 m depth. Groundwater apparent ages do not increase systematically with depth, revealing a complex circulation model for CAS. The results obtained from the other wells, which are all located on drainage lineaments, reveal that one extracts modern water from DAS and TAS, another one extracts modern and ancient water from DAS and CAS, and the third extracts only ancient water from CAS, confirming the complexity of the local hydrogeology. Regarding regional groundwater management, the study revealed the need to characterize the sources of groundwater in each well, in order to protect modern waters from anthropogenic contamination and to protect ancient groundwater from overexploitation, as CAS hosts groundwaters recharged thousands of years ago or more.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0895-9811 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number THL @ christoph.kuells @ Depaulamarteleto2024104783 Serial 221
Permanent link to this record
 

 
Author Singh, A.; Patel, S.; Bhadani, V.; Kumar, V.; Gaurav, K.
Title AutoML-GWL: Automated machine learning model for the prediction of groundwater level Type Journal Article
Year 2024 Publication Engineering Applications of Artificial Intelligence Abbreviated Journal
Volume 127 Issue Pages 107405
Keywords AutoML, Bayesian optimisation, Groundwater, Machine learning
Abstract (down) Predicting groundwater levels is pivotal in curbing overexploitation and ensuring effective water resource governance. However, groundwater level prediction is intricate, driven by dynamic nonlinear factors. To comprehend the dynamic interaction among these drivers, leveraging machine learning models can provide valuable insights. The drastic increase in computational capabilities has catalysed a substantial surge in the utilisation of machine learning-based solutions for effective groundwater management. The performance of these models highly depends on the selection of hyperparameters. The optimisation of hyperparameters is a complex process that often requires application-specific expertise for a skillful prediction. To mitigate the challenge posed by hyperparameter tuning’s problem-specific nature, we present an innovative approach by introducing the automated machine learning (AutoML-GWL) framework. This framework is specifically designed for precise groundwater level mapping. It seamlessly integrates the selection of best machine learning model and adeptly fine-tunes its hyperparameters by using Bayesian optimisation. We used long time series (1997-2018) data of precipitation, temperature, evaporation, soil type, relative humidity, and lag of groundwater level as input features to train the AutoML-GWL model while considering the influence of Land Use Land Cover (LULC) as a contextual factor. Among these input features, the lag of groundwater level emerged as the most relevant input feature. Once the model is trained, it performs well over the unseen data with a strong correlation of coefficient (R = 0.90), low root mean square error (RMSE = 1.22), and minimal bias = 0.23. Further, we compared the performance of the proposed AutoML-GWL with sixteen benchmark algorithms comprising baseline and novel algorithms. The AutoML-GWL outperforms all the benchmark algorithms. Furthermore, the proposed algorithm ranked first in Friedman’s statistical test, confirming its reliability. Moreover, we conducted a spatial distribution and uncertainty analysis for the proposed algorithm. The outcomes of this analysis affirmed that the AutoML-GWL can effectively manage data with spatial variations and demonstrates remarkable stability when faced with small uncertainties in the input parameters. This study holds significant promise in revolutionising groundwater management practices by establishing an automated framework for simulating groundwater levels for sustainable water resource management.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0952-1976 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number THL @ christoph.kuells @ singh_automl-gwl_2024 Serial 168
Permanent link to this record
 

 
Author Pisa, P.F.; Nehren, U.; Sebesvari, Z.; Rai, S.; Wong, I.
Title Chapter 17 – Nature-based solutions to reduce risks and build resilience in mountain regions Type Book Chapter
Year 2024 Publication Safeguarding Mountain Social-Ecological Systems Abbreviated Journal
Volume Issue Pages 115-126
Keywords Nature-based solutions, mountains, climate change adaptation, disaster risk reduction, ecosystem services, SDGs
Abstract (down) Nature-based solutions (NbS) are increasingly recognized as effective environmental-management measures to address societal challenges such as climate change, water and food security, and disaster risk reduction, thus contributing to human well-being and protecting biodiversity. In addition to being particularly susceptible to these challenges, mountain areas are prone to multihazard conditions, due to their steep topography and particular climatic conditions. NbS can contribute greatly to the sustainable development of mountain ecosystems. This chapter presents examples of NbS in mountain areas around the globe that demonstrate how this approach contributes to achieving sustainable development.
Address
Corporate Author Thesis
Publisher Elsevier Place of Publication Editor Schneiderbauer, S.; Pisa, P.F.; Shroder, J.F.; Szarzynski, J.
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-0-12-822095-5 Medium
Area Expedition Conference
Notes Approved no
Call Number THL @ christoph.kuells @ Fontanellapisa2024115 Serial 263
Permanent link to this record