Graphical overview of water pollution and monitoring under conflict conditions. Water pollutants are grouped into conflict-related contaminants, including explosive compounds, ammunition additives, uranium and heavy metals; conventional pollutants, including nutrients, heavy metals and organic matter; and hazardous pollutants also occurring in civilian activities, including petroleum hydrocarbons, pesticides, phenols, pharmaceuticals, personal care products and microplastics. A hybrid monitoring concept combines laboratory ex situ analysis, field in situ measurements and remote monitoring. These monitoring approaches are supported by a four-level digital framework consisting of sensor networks, analytics and Big Data, decision support, and an integrative level. The article provides a critical assessment of the ability of routine water quality monitoring systems to operate under armed conflict conditions, using Ukraine as a case study. Conventional pollutants (metals, nutrients, organic contamination, and emerging environmental threats, including pharmaceuticals and microplastics), are provided. Particular attention is paid to substances that are specific to wartime conditions, including explosive compounds, fuel and lubricant components, and metals derived from munitions. It is shown that infrastructure damage, electricity shortages, restricted access to monitoring sites, and disruption of laboratory operations can distort results or fully halt classical ex situ monitoring, creating spatial and temporal data gaps. Against conflict specific requirements, including personnel safety, rapid diagnostics, and data continuity, the performance of laboratory, in situ, and remote sensing approaches are evaluated. The analysis supports implementation of hybrid monitoring architectures that combine satellite Earth observation, use of UAVs for sampling or reconnaissance, and mobile laboratories for confirmatory analysis, complemented by portable test systems for rapid screening. Priorities for digitalization of crisis monitoring are formulated, including deployment of IoT based sensors, data standardization, and development of a Big Data platform with an interactive map to support early warning systems and post war recovery planning.
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Kyrii et al. (2026) studied this question.
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