01-05 December 2025
INCOIS, Hyderabad, India.
| Abstract Submission No. | ABS-02-0279 |
| Title of Abstract | IMPLEMENTATION OF RIVER RUNOFF AND ITS IMPACTS ON SALINITY IN A REGIONAL OCEAN MODEL FOR THE NORTH INDIAN OCEAN USING MOM6 |
| Authors | Remya R*, Abhishek Chatterjee , Sajidh C K, Prerna Singh |
| Organisation | INCOIS, HYDERABAD |
| Address | Project Scientist II, OMDA, INCOIS, Hyderabad, Telangana, India Pincode: 500090 E-mail: r.remabhai-p@incois.gov.in |
| Country | India |
| Presentation | Oral |
| Abstract | The northern Indian Ocean is significantly affected by several major river systems that discharge into the Bay of Bengal and the Arabian Sea, delivering substantial amounts of freshwater, sediments, and nutrients. These inputs influence ocean salinity, circulation patterns, marine ecosystems, and regional climate. Ocean models that do not adequately represent the spatial and temporal variability of river discharge often exhibit salinity biases, particularly in the northern Bay of Bengal, where riverine input is most pronounced. In such models, the absence of river runoff generally results in higher-than-observed salinity levels. Accurately capturing salinity dynamics in ocean models is crucial for reliable predictions of oceanic and atmospheric processes in both the Bay of Bengal and the Arabian Sea. This study employs the Modular Ocean Model Version 6 (MOM6), which incorporates the Arbitrary-Lagrangian-Eulerian (ALE) remapping method for hybrid vertical coordinates, to simulate coastal and open-ocean dynamics along the Indian coast. The regional model domain spans from 32°E to 108°E and from 8°S to 30°N, covering areas strongly influenced by river discharge. Freshwater fluxes from 24 major rivers along the Indian coast are incorporated at surface grid points adjacent to land, enabling a more realistic representation of riverine impacts on salinity and circulation. MOM6 includes optional parameters to enhance vertical mixing at river input locations, as well as tunable settings such as the salinity restoration timescale, the maximum salinity difference for restoring, horizontal and vertical mixing coefficients, and tidal mixing parameterization. Initial simulations show that including river runoff significantly reduces the high salinity bias seen in models without runoff. However, a freshwater bias remains in the northern Bay of Bengal due to an underestimation of salinity in the model. The sensitivity of various model parameterizations on the salinity bias is investigated to improve the fidelity of the model simulations. |
| Are you part of IIOE-2 endorsed project | no |
| Keywords | River runoff, salinity simulation, MOM6, mixing, hybrid vertical coordinates |
| For Awards | yes |
| Date Of Birth | 20-05-1985 |
| ECSN Registration Number | IIOE2-ECSN-0167 |