Research Article
Assessment of Heavy Metal Contamination and Its Impact on Water Quality and Aquatic Life in Mine Surface Plant Areas
Issue:
Volume 10, Issue 2, June 2024
Pages:
27-35
Received:
25 April 2024
Accepted:
11 June 2024
Published:
20 August 2024
Abstract: The Copper mining industry accounts for the country’s largest export earning and creates several jobs. Despite this the mines have been known to be the major contributor to the environmental pollution. It has been observed that in one province of the country, there is high presence of iron and other heavy metals in the surrounding areas. Unfortunately these heavy metals find themselves in water bodies and consequently affect the aquatic life. This study was conducted to develop suitable machine learning prediction models that estimate the impact of mine pollutants on fish production in the Kalumbila area of North-Western Province. The Machine Learning techniques employed include Multiple Linear Regression (MLR), Artificial Neural Networks (ANN), Random Forest (RF) and K-Nearest Neighbors (KNN). These models were evaluated and, in terms of Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) with the values of 0.25 (25%) and 0.22 (22%) indicating that Random Forest appear to be the best-performing models in terms of prediction accuracy compared to other models. In addition, the RF model also achieved the highest R2 score of 0.94, indicating its ability to explain a greater proportion of the variance in the dependent variable compared to the other models. This means that RF provides a strong prediction accuracy than other models in terms of determining heavy metal contamination in impact on Water Quality and Aquatic Life in Mine Surface Plant Areas. Therefore this study shows the potential of Machine Learning models to assist decision makers in understanding the pollution levels in water bodies.
Abstract: The Copper mining industry accounts for the country’s largest export earning and creates several jobs. Despite this the mines have been known to be the major contributor to the environmental pollution. It has been observed that in one province of the country, there is high presence of iron and other heavy metals in the surrounding areas. Unfortunat...
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Research Article
Impacts of Climate Change on Streamflow on Dawa Sub-watershed, Genale-Dawa River Basin, Southern Ethiopia
Ayana Bulti*
,
Fentaw Abegaz
Issue:
Volume 10, Issue 2, June 2024
Pages:
36-47
Received:
28 June 2024
Accepted:
25 July 2024
Published:
20 August 2024
Abstract: Climate change is statistical variations over an extended period in the features of the climate system, such as variations in global temperatures and precipitation, caused by human and natural sources. In this study aimed to measure and examine how streamflow in the Dawa sub-basin, Genale Dawa River basin was affected by climate change. It used the average of five regional climate models from the Coordinated Regional Climate Downscaling Experiment (CORDEX) Africa, under two different scenarios of Representative Concentration Pathways: RCP4.5 and RCP8.5. The baseline scenario was based on the data from 1975 to 2005, while the future scenarios were based on the data from 2020s (2025–2054) and 2050s (2055–2084). The HBV hydrological model used to assess the impact on streamflow. The HBV model showed good statistical performance in simulating the impact of climate change on streamflow, with a coefficient of determination (R2) of 0.88 and Nash-Sutcliffe Efficiency (NSE) of 0.77 for monthly calibration, and R2 of 0.86 and NSE of 0.83 for monthly validation. The impacts quantified using the mean monthly changes in precipitation, maximum and minimum temperatures. The bias-corrected precipitation and temperature showed a reasonable increase in both future periods for both RCP 4.5 and RCP 8.5 scenarios. These changes in climate variables resulted in a decrease in mean annual streamflow by 1.6 and 3.5% for RCP 4.5 and by 4.6 and 4.9% for RCP 8.5 scenarios of the 2020s and 2050s, respectively. Based on the analysis that predicted a drop in precipitation during the months, and seasons and an increase in precipitation during the Belg season, with a corresponding decrease and rise in stream flow throughout the watershed. So to offset the variation in the watershed, community should adopt various; Soil and water conservation technologies, Using drought tolerant crops, Implementing various trees and appropriate design and applying a water harvesting structure like in-situ, internal or micro catchment, external or macro catchment water harvesting and Surface runoff harvesting. This result offers useful information for current and future water resource management in the basin and similar other watershed in the country.
Abstract: Climate change is statistical variations over an extended period in the features of the climate system, such as variations in global temperatures and precipitation, caused by human and natural sources. In this study aimed to measure and examine how streamflow in the Dawa sub-basin, Genale Dawa River basin was affected by climate change. It used the...
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