Microplastic disposal into riverine ecosystems is an emergent ecological hazard that mainly originated from land-based sources. This paper presents a comprehensive review on physical processes involved in microplastics transport in riverine ecosystems. Microplastic transport is governed by physical characteristics (e.g., plastic particle density, shape, and size) and hydrodynamics (e.g., laminar and turbulent flow conditions). High-density microplastics are likely to prevail near riverbeds, whereas low-density particles float over river surfaces. Microplastic transport occurs either due to gravity-driven (vertical transport) or settling (horizontal transport) in river ecosystems. Microplastics are subjected to various natural phenomena such as suspension, deposition, detachment, resuspension, and translocation during transport processes. Limited information is available on settling and rising velocities for various polymeric plastic particles. Therefore, this paper highlights how appropriately empirical transport models explain vertical and horizontal distribution of microplastic in riverine ecosystems. Microplastics interact, and thus feedback loops within the environment govern their fate, particularly as these ecosystems are under increasing biodiversity loss and climate change threat. This review provides outlines for fate and transport of microplastics in riverine ecosystems, which will help scientists, policymakers, and stakeholders in better monitoring and mitigating microplastics pollution.

International Journal of Current Microbiology and Applied Sciences ISSN:2319-7692(Print), ISSN:2319-7706(Online) is a multidisciplinary peer-reviewed journal with reputable academics and experts as members of its Editorial Board. The Current Microbiology aims to publish all the latest and outstanding research articles. Review and letters in all areas of major importance to techniques of microbiology and applied research with publishes high quality of review and research articles on novel aspects of Microbiology including Environmental, Food, Agricultural, Medical, Pharmaceutical, Veterinary, Soil, Water and Biodeterioration.

Irrigation has a major role to play in the productivity of winter maize. Precise information about the quantity and quality of irrigation water is the key for higher productivity of winter maize. In the present study attempt has been made to asses the impact of different depth of irrigation water on crop yield and biomass of winter maize using FAO-Aquacrop Model. In the first case crop yield and biomass was simulated for irrigation water depth varied from 20 mm to 80 mm, keeping the irrigation water quality constant. Similarly, in another case the optimum irrigation depth was kept constant and irrigation water quality varied from 1 to 10 ds/m. The simulated crop yield and biomass increases up to 40 cm depth of irrigation water application for all three seasons. When a similar comparison was made for 30 cm depth of irrigation water application the simulated yield reduction was only 0.79%, 2.2% and 2.4 % for the year 2016-17, 2017-18 and 2018-19 respectively. The analysis suggested that this yield reduction can easily be compromised for saving 10 cm of irrigation water. This study indicated that 30 cm depth of irrigation water is optimum for Winter maize in BurhiGandak river basin of North Bihar In case of deficit irrigation of 20 cm depth of irrigation water application the simulated yield reduced by 14.4 %, 25.4 % and 11.4 % for the year 2016-17, 2017-18 and 2018-19 respectively. Assessment of response of different quality irrigation water on simulated crop yield and biomass of winter maize using FAO-Aquacrop model suggests that simulated yield was found maximum with 1 ds/m. The reduction in simulated yield with 10 ds/m water quality was observed maximum with a value of 41.3 %, 44.4 % and 38.4 % respectively for the year 2016-17, 2017-18 and 2018-19. FAO-Aquacrop model can be used as an important tool for efficient planning of irrigation water under diminishing water supply and deteriorating water quality.

The study develops a 2D hydrodynamic model using HEC-RAS to assess flood hazards and generate inundation maps for the lower Narmada basin in Gujarat, India. The model effectively simulates flood dynamics by integrating data, i.e. digital elevation models, stream gauge data, and land use and land cover information. Results indicate strong model performance, with R² and root mean square error (RMSE) values of 0.92 and 0.12 for calibration and 0.77 and 0.08 for validation. Approximately 326.45 km² of the basin is severely inundated during major flood events, with agriculture being most affected. The model's outputs, including depth maps, velocity maps, and water arrival time predictions, provide critical insights for flood management. Floodwaters take 110 h to reach nearby areas and 361 h to reach validation points from upstream dam releases, offering an 8-h window to alert residents of potential overflow conditions. This information is vital for early warning systems and evacuation planning.