Impact of Population Growth on the Water Quality of Natural Water Bodies

Abstract

Human activities pose a significant threat to the water quality of rivers when pollution exceeds the threshold limit. Urban activities in particular are highlighted as one of the major causes of contamination in surface water bodies in Asian countries. Evaluation of sustainable human population capacities in river watersheds is necessary to maintain better freshwater ecosystems in a country while achieving its development goals as a nation. We evaluated the correlation between the growth rate of the population in a watershed area and water quality parameters of a river ecosystem. The Kelani River in Sri Lanka was selected for the study. The highest correlation coefficients of 0.7, 0.69, 0.69 (p < 0.01) corresponding to biochemical oxygen demand (BOD), dissolved oxygen (DO) and total coliform (TC) were obtained with the population in watersheds of the Kelani river in Sri Lanka. Thus, we propose a quantitative approach to estimating the population capacity of watersheds based on water quality classification standards (WQCS), employing the Bayesian network (BN) classification model. The optimum population ranges were obtained from the probability distribution table of the population node in the BN. The results showed that the population density should be approximately less than 2375 to keep the water quality in the watershed for bathing and drinking purposes and approximately less than 2672 for fish and other aquatic organisms. This research will offer a means that can used to understand the impact of population on water quality in river basins and confer direct influence on natural water bodies.

Challenges in Biodiversity Conservation in a Highly Modified Tropical River Basin in Sri Lanka

“…The extent of pollution strongly correlates with population density across the watershed. In the lower basin, where 25% of the national population resides (>6 million, density > 2500 km −2 ), the integrated pollution index consistently underperformed water-quality standards for consumption, recreation, and aquatic biodiversity [37]. In the coastal reaches, biological oxygen demands (BOD) have reached 17 mg L −1 , while pH has fallen to 5.3, with higher conductivity (>0.2 ms cm −1 ); total colifom counts as high as 1500 cells 100 mL −1 have been reported even in the middle reaches [37].…”

“…In the lower basin, where 25% of the national population resides (>6 million, density > 2500 km −2 ), the integrated pollution index consistently underperformed water-quality standards for consumption, recreation, and aquatic biodiversity [37]. In the coastal reaches, biological oxygen demands (BOD) have reached 17 mg L −1 , while pH has fallen to 5.3, with higher conductivity (>0.2 ms cm −1 ); total colifom counts as high as 1500 cells 100 mL −1 have been reported even in the middle reaches [37]. Although nutrient spiraling and flushing remediate pollution during the high-discharge wet season (800-1800 m 3 s −1 ), pollutant resident time can be much higher during low-flow dry (20-25 m 3 s −1 ) season [38,53].…”

Applications of Bayesian Networks as Decision Support Tools for Water Resource Management under Climate Change and Socio-Economic Stressors: A Critical Appraisal

“…Effects of numerous climatic drivers have been considered, including sea-level rise on water supply management (e.g., [2]), and on water quality management (e.g., [49]); precipitation and temperature on groundwater management (e.g., [63,64,67]), on reservoir management (e.g., [135]), on water supply management (e.g., [3,132]), on water quality management (e.g., [27,43,45] and on nutrient management (e.g., [119,126]) and precipitation on water supply and demand management (e.g., [18,127,130,131]). Similarly, the non-climatic drivers that have been considered, have included effects of population growth on water supply and demand management (e.g., [128]), and on water quality management (e.g., [41]); crop production changes in irrigation system management (e.g., [96,102]); population growth and agricultural production on water supply and demand management (e.g., [128]); agricultural production on irrigation water management (e.g., [93][94][95]100]), on water supply management (e.g., [85]), and on groundwater management (e.g., [67]); changes in domestic use and in agricultural and industrial production on water supplies and demand management (e.g., [127]).…”

Evaluation of water quality parameters using numerical modeling approach for the El-Salam Canal in Egypt

“…Overall, the COD profile trend is increasing with increasing phytoplankton in summer which is due to the addition of El-Serw and Hadous drains in El-Salam Canal. From this finding, it can be agreed that water quality is a function of both natural water climate and anthropogenic sources (Onuoha et al, 2018;Rashid and Romshoo, 2013;Ratemo, 2018;Liyanage and Yamada, 2017). The sustainable riverine ecosystem depends mainly on the DO and stream temperature of the aquatic biochemistry (Abdul-Aziz and Ishtiaq, 2014;Dick et al, 2016;Mader et al, 2017).…”