Climate change impact assessment on a tropical river resilience using the Streeter-Phelps dissolved oxygen model

Abstract

This paper provides a technical analysis of a river’s current and future resilience in a watershed with intensive agricultural and fishing activities. The study area was the last section of the Culiacan River corresponding to the river mouth over a lagoon system. Dissolved oxygen modeling was performed using the Streeter-Phelps model to evaluate the river self-depuration capability using Biochemical Oxygen Demand, dissolved oxygen, streamflow, and water temperature data from 2013 to 2020. Fieldwork was carried out to establish the geomorphological characteristics of the river by determining stream velocity, width, and depth and the location of nine sources of pollution on the river. The modeling was performed for three groups of months with different temperatures, identified by hierarchical cluster analysis. Estimates were made for future scenarios, assessing the effect of climate change on the Culiacan River’s self-depuration capability. The results showed that most of the year, the degradation rate of the system results in rapid assimilation of organic matter. However, the modeling indicates that the river would lose its resilience capability under climate change. Thus, it is essential to implement wastewater treatment systems to reduce the environmental impact on the aquatic ecosystem in the river and the lagoon system.

Water Quality Prediction in Urban Waterways Based on Wavelet Packet Denoising and LSTM

“…Existing water quality prediction models can be divided into two types: mechanistic and non-mechanistic models [7,8] . Mechanistic models, such as the Streeter Phelps (S-P) model [9][10][11][12] , QUAL2E model [13][14][15] , Water Quality Analysis Simulation Program (WASP) [15][16][17] , Soil and Water Assessment Tool (SWAT) [18][19][20] , etc., are based on physical and chemical principles and require a large amount of basic and long-term monitoring data. However, such data are often unavailable or incomplete in practice, which limits the applicability and accuracy of mechanistic models.…”

Water Quality Prediction in Urban Waterways Based on Wavelet Packet Denoising and LSTM

“…Existing water quality prediction models can be divided into two types: mechanistic and non-mechanistic models [7,8] . Mechanistic models, such as the Streeter Phelps (S-P) model [9][10][11][12] , QUAL2E model [13][14][15] , Water Quality Analysis Simulation Program (WASP) [15][16][17] , Soil and Water Assessment Tool (SWAT) [18][19][20] , etc., are based on physical and chemical principles and require a large amount of basic and long-term monitoring data. However, such data are often unavailable or incomplete in practice, which limits the applicability and accuracy of mechanistic models.…”