1
|
Brighenti S, Colombo N, Wagner T, Pettauer M, Guyennon N, Krainer K, Tolotti M, Rogora M, Paro L, Steingruber SM, Del Siro C, Scapozza C, Sileo NR, Villarroel CD, Hayashi M, Munroe J, Liaudat DT, Cerasino L, Tirler W, Comiti F, Freppaz M, Salerno F, Litaor MI, Cremonese E, di Cella UM, Winkler G. Factors controlling the water quality of rock glacier springs in European and American mountain ranges. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 953:175706. [PMID: 39197760 DOI: 10.1016/j.scitotenv.2024.175706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/04/2024] [Revised: 08/13/2024] [Accepted: 08/20/2024] [Indexed: 09/01/2024]
Abstract
Rock glaciers (RGs) provide significant water resources in mountain areas under climate change. Recent research has highlighted high concentrations of solutes including trace elements in RG-fed waters, with negative implications on water quality. Yet, sparse studies from a few locations hinder conclusions about the main drivers of solute export from RGs. Here, in an unprecedented effort, we collected published and unpublished data on rock glacier hydrochemistry around the globe. We considered 201 RG springs from mountain ranges across Europe, North and South America, using a combination of machine learning, multivariate and univariate analyses, and geochemical modeling. We found that 35 % of springs issuing from intact RGs (containing internal ice) have water quality below drinking water standards, compared to 5 % of springs connected to relict RGs (without internal ice). The interaction of ice and bedrock lithology is responsible for solute concentrations in RG springs. Indeed, we found higher concentrations of sulfate and trace elements in springs sourcing from intact RGs compared to water originating from relict RGs, mostly in specific lithological settings. Enhanced sulfide oxidation in intact RGs is responsible for the elevated trace element concentrations. Challenges for water management may arise in mountain catchments rich in intact RGs, and where the predisposing geology would make these areas geochemical RG hotspots. Our work represents a first comprehensive attempt to identify the main drivers of solute concentrations in RG waters.
Collapse
Affiliation(s)
- Stefano Brighenti
- Competence Centre for Mountain Innovation Ecosystems, Free University of Bozen/Bolzano, Bolzano 39100, Italy
| | - Nicola Colombo
- Department of Agricultural, Forest and Food Sciences, University of Turin, Grugliasco 10095, Italy; Research Center on Natural Risk in Mountain and Hilly Environments - NatRisk, University of Turin, Grugliasco 10095, Italy
| | - Thomas Wagner
- Department of Earth Sciences, NAWI Graz Geocenter, University of Graz, Graz 8010, Austria. thomas.wagner@uni.-graz.at
| | - Michael Pettauer
- Institute of Applied Geosciences, Graz University of Technology, Graz 8010, Austria
| | - Nicolas Guyennon
- Water Research Institute, National Research Council of Italy, IRSA-CNR, Montelibretti 00010, Italy
| | - Karl Krainer
- Institute of Geology, University of Innsbruck, Innsbruck 6020, Austria
| | - Monica Tolotti
- Research and Innovation Centre, Fondazione Edmund Mach, San Michele All'Adige 38098, Italy
| | - Michela Rogora
- Water Research Institute, National Research Council of Italy, IRSA-CNR, Verbania 28925, Italy
| | - Luca Paro
- Dept. Natural and Environmental Risks, Environmental Protection Agency of Piemonte Region, Torino 10135, Italy
| | | | - Chantal Del Siro
- Institute of Earth Sciences, University of Applied Sciences and Arts of Southern Switzerland (SUPSI), Mendrisio CH-6850, Switzerland; Institute of Earth Surface Dynamics, University of Lausanne, Lausanne CH-1015, Switzerland
| | - Cristian Scapozza
- Institute of Earth Sciences, University of Applied Sciences and Arts of Southern Switzerland (SUPSI), Mendrisio CH-6850, Switzerland
| | - Noelia R Sileo
- CNEA, National Commision of Atomic Energy, Av. del Libertador 8250, CABA, Argentina
| | - Cristian D Villarroel
- CIGEOBIO-CONICET, Geosphere and Biosphere Research Center, Av. Ignacio de la Roza 727, San Juan, Argentina
| | - Masaki Hayashi
- Department of Earth, Energy, and Environment, University of Calgary, Calgary 2500, Canada
| | - Jeffrey Munroe
- Department of Earth & Climate Sciences, Middlebury College, Middlebury 05753, VT, USA
| | | | - Leonardo Cerasino
- Research and Innovation Centre, Fondazione Edmund Mach, San Michele All'Adige 38098, Italy
| | | | - Francesco Comiti
- Department of Land, Environment, Agriculture, and Forestry, University of Padova, Padova 35123, Italy
| | - Michele Freppaz
- Department of Agricultural, Forest and Food Sciences, University of Turin, Grugliasco 10095, Italy; Research Center on Natural Risk in Mountain and Hilly Environments - NatRisk, University of Turin, Grugliasco 10095, Italy
| | - Franco Salerno
- Institute of Polar Sciences, National Research Council of Italy, ISP-CNR, Milan 20126, Italy
| | - M Iggy Litaor
- MIGAL - Galilee Research Institute and Tel Hai College, Kiryat Shmona 11016, Israel
| | | | | | - Gerfried Winkler
- Department of Earth Sciences, NAWI Graz Geocenter, University of Graz, Graz 8010, Austria
| |
Collapse
|
2
|
Huang X, Liu Y, Stouffs R. Human-earth system dynamics in China's land use pattern transformation amidst climate fluctuations and human activities. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 954:176013. [PMID: 39277011 DOI: 10.1016/j.scitotenv.2024.176013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/04/2024] [Revised: 08/21/2024] [Accepted: 09/01/2024] [Indexed: 09/17/2024]
Abstract
Amid rapid environmental changes, the interplay between climate change and human activity is reshaping land use, emphasizing the significance of human-earth system dynamics. This study, rooted in human-earth system theory, explores the complex relationships between land use patterns, climate change, and human activities across China from 1996 to 2022. Using a comprehensive analytical framework that combines Geographical Detector (GeoDetector), Random Forest (RF) model, Data Envelopment Analysis (DEA), Spearman's rank correlation, and k-means clustering, we analyzed data from national land surveys, climate records, and nighttime light observations. Our findings indicate a significant, though regionally varied, transformation in land use: arable land decreased by 1.67 %, driven by intense urbanization and policy shifts, particularly in rapidly urbanizing Jiangsu province where arable land diminished by 19.19 %. In contrast, construction land in the northern regions increased by 225.91 million hectares. Climatic influences are apparent, with rising temperatures positively correlating with arable land expansion in the Northeast and Northwest, and urban land in Jiangsu province increasing by 35.51 %. Variations in precipitation patterns were linked to changes in forested areas. This study highlights the dynamic and intricate interactions within the human-earth system, stressing the urgent need for sustainable land management and climate adaptation strategies that improve land use efficiency and resilience. Our research offers a solid foundation for informed policy-making in land management and climate adaptation, advocating a human-earth system science approach to address future environmental and societal challenges.
Collapse
Affiliation(s)
- Xinxin Huang
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Yansui Liu
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China.
| | - Rudi Stouffs
- Department of Architecture, National University of Singapore, Singapore 117566, Singapore
| |
Collapse
|
3
|
Trok JT, Barnes EA, Davenport FV, Diffenbaugh NS. Machine learning-based extreme event attribution. SCIENCE ADVANCES 2024; 10:eadl3242. [PMID: 39167638 PMCID: PMC11338235 DOI: 10.1126/sciadv.adl3242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 07/15/2024] [Indexed: 08/23/2024]
Abstract
The observed increase in extreme weather has prompted recent methodological advances in extreme event attribution. We propose a machine learning-based approach that uses convolutional neural networks to create dynamically consistent counterfactual versions of historical extreme events under different levels of global mean temperature (GMT). We apply this technique to one recent extreme heat event (southcentral North America 2023) and several historical events that have been previously analyzed using established attribution methods. We estimate that temperatures during the southcentral North America event were 1.18° to 1.42°C warmer because of global warming and that similar events will occur 0.14 to 0.60 times per year at 2.0°C above preindustrial levels of GMT. Additionally, we find that the learned relationships between daily temperature and GMT are influenced by the seasonality of the forced temperature response and the daily meteorological conditions. Our results broadly agree with other attribution techniques, suggesting that machine learning can be used to perform rapid, low-cost attribution of extreme events.
Collapse
Affiliation(s)
- Jared T. Trok
- Department of Earth System Science, Stanford University, Stanford, CA, USA
| | - Elizabeth A. Barnes
- Department of Atmospheric Science, Colorado State University, Fort Collins, CO, USA
| | - Frances V. Davenport
- Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, CO, USA
| | - Noah S. Diffenbaugh
- Department of Earth System Science, Stanford University, Stanford, CA, USA
- Doerr School of Sustainability, Stanford University, Stanford, CA, USA
| |
Collapse
|
4
|
Leal Filho W, Dinis MAP, Nagy GJ, Fracassi U, Aina YA. A ticket to where? Dwindling snow cover impacts the winter tourism sector as a consequence of climate change. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 356:120554. [PMID: 38490001 DOI: 10.1016/j.jenvman.2024.120554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 02/21/2024] [Accepted: 03/04/2024] [Indexed: 03/17/2024]
Abstract
Climate change affects human activities, including tourism across various sectors and time frames. The winter tourism industry, dependent on low temperatures, faces significant impacts. This paper reviews the implications of climate change on winter tourism, emphasising challenges for activities like skiing and snowboarding, which rely on consistent snowfall and low temperatures. As the climate changes, these once taken-for-granted conditions are no longer as commonplace. Through a comprehensive review supported by up-to-date satellite imagery, this paper presents evidence suggesting that the reliability of winter snow is decreasing, with findings revealing a progressive reduction in snow levels associated with temperature and precipitation changes in some regions. The analysis underscores the need for concerted efforts by stakeholders who must recognize the reality of diminishing snow availability and work towards understanding the specific changes in snow patterns. This should involve multi-risk and multi-instrument assessments, including ongoing satellite data monitoring to track snow cover changes. The practical implications for sports activities and the tourism industry reliant on snow involve addressing challenges by diversifying offerings. This includes developing alternative winter tourism activities less dependent on snow, such as winter hiking, nature walks, or cultural experiences.
Collapse
Affiliation(s)
- Walter Leal Filho
- Department of Natural Sciences, Manchester Metropolitan University, Chester Street, Manchester M1 5GD, UK; Research and Transfer Centre "Sustainable Development and Climate Change Management" Hamburg University of Applied Sciences, Germany.
| | - Maria Alzira Pimenta Dinis
- Fernando Pessoa Research, Innovation and Development Institute (FP-I3ID), University Fernando Pessoa (UFP), Praça 9 de Abril 349, 4249-004 Porto, Portugal; Marine and Environmental Sciences Centre (MARE), University of Coimbra, Edifício do Patronato, Rua da Matemática, 49, 3004-517 Coimbra, Portugal.
| | - Gustavo J Nagy
- Instituto de Ecología y Ciencias Ambientales, Facultad de Ciencias, Universidad de la República (FC-UdelaR), Iguá 4225, Montevideo, Uruguay.
| | - Umberto Fracassi
- Istituto Nazionale di Geofisica e Vulcanologia, Via di Vigna Murata, 605, 00143 Rome, Italy.
| | - Yusuf A Aina
- Department of Geomatics Engineering Technology, Yanbu Industrial College, Yanbu, Saudi Arabia.
| |
Collapse
|