Human Population Effects on the Ulsoor Lake Fish Survival

Abstract

In this paper, we introduce a model to study the effects of human populations on fish survival in aquatic media. Directly, this occurs by fishing. Indirectly instead this is related to other human actions that lead to organic pollution and consequently low dissolved oxygen(DO) levels, thereby harming the aquatic fauna. Mathematically, we consider various nonlinear processes involving human population, organic pollutants, bacteria, DO and fish population. In the present study, our aim is to investigate the effect of depleted level of DO on the survival of fish populations in such an aquatic system. The case study in consideration is represented by the Ulsoor lake, Bengaluru, India. Into it, huge amounts of sewage were discharged and resulted in reduction of DO level and massive fish mortality. Equilibria are analyzed for feasibility and stability, substantiated via numerical simulations. Global sensitivity analysis identifies the important parameters having a significant impact on the fish population. The Partial Rank Correlation Coefficients (PRCCs) values of fish population in the lake with respect to input parameters of the system show that the growth rate of humans in the lake watershed has maximum negative correlation while the growth in the fish population due to DO has maximum positive correlation with the density of fish population in the lake. The results show that increase in human population may decrease fish population in the system to very low values. However, by controlling additional dissolved organic loads coming from domestic sewage, farm waste and many other sources, the level of DO can be brought back to values that allow fish survival. Maintaining it at these levels would preserve the ecosystem.

On a spatiotemporal model for pollutants and dissolved oxygen in a river

“…where the first strict inequality used P * (x) ⩽ P (x) < h c • e a 1 d 1 L (see ( 4)) and the definition of c * in (18), and the second strict inequality used the assumption a1 d1 ⩾ a2 d2 ,…”

“…All these models are linear. For models describing the nonlinear process in water bodies involving interactions of DO with organic pollutants, bacteria, and other biological populations, we refer readers to [6,13,16,18,19], where the models are governed by a set of ODEs and both theoretical and numerical results are obtained. In contrast, works based on PDE models are relatively fewer, especially from a mathematical point of view.…”