Evaluating seasonal variation in macronutrient levels and their impact on water quality in urban coastal waters: A case study in nutrient management along the North Colombo coast of Sri Lanka

Macronutrients are vital for sustaining marine food webs and primary production. However, their overabundance through riverine inflows and untreated wastewater discharges causes adverse ecological changes, especially in developing countries, necessitating effective nutrient management for ecosystem preservation. We assessed macronutrient enrichment and dispersion patterns in the north Colombo coast of Sri Lanka, an urban estuary stressed by untreated wastewater discharge from sewer channels and macronutrients from the Kelani River. Maximum concentrations of NO-3- N, total dissolved nitrogen, PO3- 4-P and total dissolved phosphorus were 0.085, 0.74, 0.70, and 0.79 mg/L, respectively, while the dissolved oxygen levels and temperature ranged from 6.42 to 8.62 mg/L and from 28.1 to 30.8 0C during January 2023. The estuary was a nitrogen-limited ecosystem, with the Kelani River being the primary source of NO-3- N. Although nutrient levels were within water quality guidelines, understanding how pollutants disperse during a catastrophic discharge is crucial for risk management. Simulated dispersion patterns using Delft3D revealed that NO-3-N and other solutes introduced through the Kelani River accumulate near the breakwaters of the Colombo harbor complex during the Northeast monsoon, primarily due to seasonal wave and wind conditions. The accumulation of the limiting nutrient increased the risk of eutrophication and harmful algal blooms by non-indigenous toxic algae species introduced by untreated ballast water disposal. The findings elucidate the critical role of breakwaters in retaining solutes and emphasize the influence of morphological, climatic, and topographical factors on dispersion patterns in coastal ecosystems. The study provides an example for developing countries to integrate cost-effective monitoring technologies and numerical modelling into coastal management, facilitating data-driven decision making for effective environmental management.