{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T09:00:24Z","timestamp":1790240424439,"version":"4.1.0"},"reference-count":47,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2026,9,19]],"date-time":"2026-09-19T00:00:00Z","timestamp":1789776000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Water ecosystems face increasing threats from pollution, climate change, and extreme hydrological events, while conventional monitoring systems often provide limited adaptability and spatial coverage. This paper proposes a 6G-enabled smart watershed monitoring framework integrating Flying Ad Hoc Networks (FANETs), Internet of Things (IoT) sensors, deep learning, and Multi-Agent Deep Reinforcement Learning (MADRL). Cooperative unmanned Aerial Vehicles (UAVs) interact with terrestrial IoT nodes through a simulated 5G\/6G communication environment, while deep learning models support water-quality prediction and ecological-risk assessment. The MADRL framework enables UAV agents to collaboratively optimize sensing coverage, data collection, energy consumption, and pollution-event response under dynamic environmental conditions. The framework is evaluated in a Python-based simulation environment using five UAVs and distributed IoT sensing nodes under normal and pollution-affected watershed scenarios with communication impairments and environmental disturbances. Performance is compared with centralized static monitoring, rule-based UAV patrol, and single-agent reinforcement learning using spatial coverage, pollution-detection latency, prediction accuracy, false-alarm rate, energy consumption, and communication metrics. Results show approximately 40% higher spatial coverage, 60% faster pollution-event detection, 15% higher water-quality prediction accuracy, and 35% lower false-alarm rates than the considered baselines. The results also indicate improved communication resilience and energy-aware UAV coordination. As the evaluation is simulation-based, these findings demonstrate computational feasibility and comparative effectiveness under the specified assumptions rather than physical deployment. Real-world UAV testbed and watershed validation remain important future directions.<\/jats:p>","DOI":"10.3390\/s26185922","type":"journal-article","created":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T10:21:48Z","timestamp":1790072508000},"page":"5922","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["6G-Enabled FANET\u2013IoT Framework for Intelligent Watershed Monitoring Using Multi-Agent Deep Reinforcement Learning"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-1909-4406","authenticated-orcid":false,"given":"Rizwan","family":"Raza","sequence":"first","affiliation":[{"name":"Computer Science Department, COMSATS University Islamabad, Attock Campus, Attock 43600, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9968-0330","authenticated-orcid":false,"family":"Zahoor-ur-Rehman","sequence":"additional","affiliation":[{"name":"Computer Science Department, COMSATS University Islamabad, Attock Campus, Attock 43600, Pakistan"},{"name":"Department of Computer Engineering, Faculty of Computer and Information Sciences, Sakarya University, Serdivan 54187, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0815-4883","authenticated-orcid":false,"given":"Muddasar","family":"Naeem","sequence":"additional","affiliation":[{"name":"AIR Lab, Universit\u00e0 Giustino Fortuanto, 82100 Benevento, Italy"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"funding-acquisition","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8737-2154","authenticated-orcid":false,"given":"Farhan","family":"Aadil","sequence":"additional","affiliation":[{"name":"Computer Science Department, COMSATS University Islamabad, Attock Campus, Attock 43600, Pakistan"},{"name":"Department of Computer Engineering, Sivas University of Science and Technology, Sivas 58000, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"software","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-7204-183X","authenticated-orcid":false,"given":"Faheem","family":"Shehzad","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Information Technology (DIETI), University of Naples \u201cFederico II\u201d, 80138 Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"methodology","vocabulary":"credit"},{"role":"software","vocabulary":"credit"},{"role":"project-administration","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8177-032X","authenticated-orcid":false,"given":"Antonio","family":"Coronato","sequence":"additional","affiliation":[{"name":"AIR Lab, Universit\u00e0 Giustino Fortuanto, 82100 Benevento, Italy"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"project-administration","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"450","DOI":"10.1111\/brv.12914","article-title":"Extreme weather events threaten biodiversity and functions of river ecosystems: Evidence from a meta-analysis","volume":"98","author":"Sabater","year":"2023","journal-title":"Biol. 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