"Artificial Intelligence (AI) Aided Assessment of the Impact of Rice Farming on Nyando Wetland, Kisumu County, Kenya"

The application of Artificial Intelligence (AI) in assessing the effects of rice production on Nyando Wetlands in Kisumu County presents an innovative approach to environmental monitoring and sustainable agriculture.According to Omondi et al. [1], AI-driven remote sensing and Geographic Information System (GIS) technologies enable real-time analysis of land use changes, water quality variations, and biodiversity loss caused by rice farming activities.Mutua & Kipkorir [2] posits that machine learning models can process satellite imagery and hydrological data to detect wetland degradation patterns, helping policymakers and conservationists make informed decisions.In view of Odhiambo et al. [3], AI-powered predictive analytics can assess the long-term impacts of agrochemical use on water bodies, providing insights into pollution levels and their effects on aquatic ecosystems.Additionally, AI-driven simulations allow for scenario modeling, helping researchers evaluate the potential outcomes of different rice farming practices on wetland sustainability [4].Nyaboke et al. [5] further contended that AI-integrated Internet of Things (IoT) sensors can monitor soil quality, water pH, and nutrient levels, optimizing rice farming while minimizing environmental degradation.The integration of AI in monitoring Nyando Wetlands can support sustainable agricultural practices by promoting precision farming, reducing excessive water usage, and minimizing chemical runoff [6].Leveraging AI technology in environmental management ensures a datadriven approach to balancing food security with wetland conservation, ultimately fostering ecological sustainability in Kisumu County.