Navigating Hydrological Challenges in a Changing Climate: Lessons and Innovations

A special issue of Geosciences (ISSN 2076-3263). This special issue belongs to the section "Hydrogeology".

Deadline for manuscript submissions: 30 September 2025 | Viewed by 670

Special Issue Editors

LEN Technologies, 12139 Westwood Hills Dr., Oak Hill, VA 20171, USA
Interests: hydrology; water resources; climate change; ensemble modeling; data assimilation; flood
Special Issues, Collections and Topics in MDPI journals
California Department of Water Resources, 1416 9th Street, Sacramento, CA 95814, USA
Interests: hydrology; climate change; hydrodynamics; water quality; machine learning
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Kumoh National Institute of Technology, Gumi, Republic of Korea
Interests: urban flood; hydrologic modeling; data assimilation; climate change adaptation; deep learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The global climate is undergoing unprecedented changes, with profound implications for hydrological systems worldwide. As the frequency and intensity of extreme weather events increase, the need for innovative and sustainable water management strategies becomes more critical than ever. This Special Issue invites original research papers that explore the latest advancements in hydrology, water quality, climate change adaptation, and sustainable water management.

Topics of interest include but are not limited to:

Hydrological modeling and forecasting: Advanced modeling techniques for predicting hydrological processes under changing climate conditions.
Water quality assessment and management: Strategies for monitoring and improving water quality in the face of climate-related challenges.
Climate change adaptation and mitigation: Innovative approaches to adapting to and mitigating the impacts of climate change on hydrological systems.
Sustainable water resource management: Strategies for ensuring equitable and sustainable access to water resources in a changing climate.
Machine learning and artificial intelligence: Applications of these technologies for hydrological modeling, prediction, and decision-making.
Case studies and lessons learned: Real-world examples of successful water management strategies and the challenges faced.

Dr. Haksu Lee
Dr. Minxue He
Dr. Seong Jin Noh
Guest Editors

Manuscript Submission Information

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Keywords

  • hydrology
  • climate change
  • water resources
  • machine learning
  • artificial intelligence
  • water quality
  • extreme events

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Published Papers (1 paper)

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Research

28 pages, 8775 KiB  
Article
Assessing Shallow Groundwater Depth and Electrical Conductivity in the Brazilian Semiarid: A Geostatistical Analysis
by Thayná Alice Brito Almeida, Luiz Carlos da Silva Boaventura, Marcos Vinícius da Silva, Carolyne Wanessa Lins de Andrade Farias, Aline Maria Soares das Chagas, Rodrigo Soares da Costa, Cláudio Vinícius de Souza Moura and Abelardo Antônio de Assunção Montenegro
Geosciences 2025, 15(4), 136; https://doi.org/10.3390/geosciences15040136 - 4 Apr 2025
Viewed by 213
Abstract
The Brazilian semiarid region faces water scarcity, with alluvial aquifers playing a crucial role in agricultural water security. This study assesses the spatiotemporal variability of groundwater quantity and salinity, analyzing natural and anthropogenic impacts, including post-pandemic trends. The investigation was developed in the [...] Read more.
The Brazilian semiarid region faces water scarcity, with alluvial aquifers playing a crucial role in agricultural water security. This study assesses the spatiotemporal variability of groundwater quantity and salinity, analyzing natural and anthropogenic impacts, including post-pandemic trends. The investigation was developed in the Mimoso Alluvial Valley (MAV), Pernambuco State, mainly used for communal irrigation supply. The spatiotemporal dynamics of land use (LUC) was performed based on data provided by Mapbiomas for the years 2012, 2016, 2019, and 2023. Geostatistical analysis was applied for mapping water table levels and salinity. Changes in LUC suggest possible forest regeneration influenced by climatic factors and anthropogenic pressure alleviation. Electrical conductivity (EC) and groundwater level (GWL) exhibited medium to high variability. Temporal trends highlight climatic influences, groundwater abstraction, and recharge/discharge dynamics. Pre-2019 years were classified as dry, whereas the 2019–2023 years ranged from rainy to extremely rainy, leading to lower EC and GWL variability in 2023. Additionally, the COVID-19 pandemic temporarily reduced agriculture, lowering salinity and aiding groundwater recovery. The spatial analysis revealed critical distribution patterns, highlighting the interaction between natural processes and human activities. These findings provide valuable insights for optimizing irrigation and environmental strategies, supporting long-term groundwater sustainability in semiarid regions. Full article
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