A structure-preserving numerical approach for simulating algae blooms in marine water bodies of western Patagonia

TL;DR

This paper introduces a novel, structure-preserving numerical model for simulating algae blooms in Patagonian fjords, balancing complexity and applicability due to data scarcity, and validated through a case study of a winter bloom.

Contribution

It presents a new two-layer, mass-conserving model with a structure-preserving integrator and a genetic algorithm calibration, tailored for the unique conditions of Patagonian water bodies.

Findings

Successfully simulated a winter algae bloom in a Patagonian fjord.

Demonstrated the model's ability to estimate biomass fluxes accurately.

Provided insights into nutrient dynamics driven by wind-induced mixing.

Abstract

Patagonian fjords' area is one of the largest estuarine regions in the world. Every one of its water bodies displays a unique hydrodynamic behavior with enormous effects on the biogeochemical characteristics of the ecosystems. In this context, algal blooms are ecological phenomena of major relevance. Numerical simulation has proved to be a promising tool to understand their impacts. It has not been used for studying algal blooms in this zone. This article focuses on proposing a novel numerical model for simulating brief algal blooms occurring in water bodies of western Patagonia. The proposed model presents a trade-off between complexity and applicability since field-data sparsity in the zone discourages using more sophisticated approaches. The model is based on a two-layer description of the water column. The first layer represents the euphotic zone where an embedded biogeochemical model of NPZD-type is used to model a mass-conserving trophic web. High intensity wind drives the water column mixing, introducing an upward flux of nutrients that boosts high rates of primary production. A time-dependent Gaussian pulse is used to describe this process. Mass losses due to detritus sinking are also included. Then, the ecosystem's dynamics is represented by means of an externally forced, non-autonomous system of ordinary differential equations which is characterized by strictly positive trajectories but that it is not longer mass-conserving. A structure-preserving time integrator based on a splitting-composition technique is designed for solving the system's equations. It is cast as a three-steps algorithm and provides an exact estimations of biomass fluxes. Additionally, a genetic algorithm-based tool is used to calibrate the model's parameters in realistic scenarios. The proposed model is applied im a detailed study of a winter bloom in an austral fjord.