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Hydrology, Volume 12, Issue 8 (August 2025) – 2 articles

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11 pages, 15673 KiB  
Article
Automating GIS-Based Cloudburst Risk Mapping Using Generative AI: A Framework for Scalable Hydrological Analysis
by Alexander Adiyasa, Andrea Niccolò Mantegna and Irma Kveladze
Hydrology 2025, 12(8), 196; https://doi.org/10.3390/hydrology12080196 - 23 Jul 2025
Abstract
Accurate dynamic hydrological models are often too complex and costly for the rapid, broad-scale screening necessitated for proactive land-use planning against increasing cloudburst risks. This paper demonstrates the use of GPT-4 to develop a GUI-based Python 3.13.2 application for geospatial flood risk assessments. [...] Read more.
Accurate dynamic hydrological models are often too complex and costly for the rapid, broad-scale screening necessitated for proactive land-use planning against increasing cloudburst risks. This paper demonstrates the use of GPT-4 to develop a GUI-based Python 3.13.2 application for geospatial flood risk assessments. The study used instructive prompt techniques to script a traditional stream and catchment delineation methodology, further embedding it with a custom GUI. The resulting application demonstrates high performance, processing a 29.63 km2 catchment at a 1 m resolution in 30.31 s, and successfully identifying the main upstream contributing areas and flow paths for a specified area of interest. While its accuracy is limited by terrain data artifacts causing stream breaks, this study demonstrates how human–AI collaboration, with the LLM acting as a coding assistant guided by domain expertise, can empower domain experts and facilitate the development of advanced GIS-based decision-support systems. Full article
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15 pages, 2467 KiB  
Article
Definition of Groundwater Management Zones for a Fissured Karst Aquifer in Semi-Arid Northeastern Brazil
by Hailton Mello da Silva, Luiz Rogério Bastos Leal, Cezar Augusto Teixeira Falcão Filho, Thiago dos Santos Gonçalves and Harald Klammler
Hydrology 2025, 12(8), 195; https://doi.org/10.3390/hydrology12080195 - 23 Jul 2025
Abstract
The objective of this study is to define groundwater management zones for a complex deformed and fissured Precambrian karst aquifer, which underlies one of the most important agricultural areas in the semi-arid region of Irecê, Bahia, Brazil. It is an unconfined aquifer, hundreds [...] Read more.
The objective of this study is to define groundwater management zones for a complex deformed and fissured Precambrian karst aquifer, which underlies one of the most important agricultural areas in the semi-arid region of Irecê, Bahia, Brazil. It is an unconfined aquifer, hundreds of meters thick, resulting from a large sequence of carbonates piled up by thrust faults during tectonic plate collisions. Groundwater recharge and flow in this aquifer are greatly influenced by karst features, through the high density of sinkholes and vertical wells. Over the past four decades, population and agricultural activities have increased in the region, resulting in unsustainable groundwater withdrawal and, at the same time, water quality degradation. Therefore, it is important to develop legal and environmental management strategies. This work proposes the division of the karst area into three well-defined management zones by mapping karst structures, land use, and urban occupation, as well as the concentrations of chloride and nitrate in the region’s groundwater. Zone 1 in the north possesses the lowest levels of karstification, anthropization, and contamination, while zone 2 in the central region has the highest levels and zone 3 in the south ranging in-between (except for stronger karstification). The delimitation of management zones will contribute to the development and implementation of optimized zone-specific groundwater preservation and restoration strategies. Full article
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