Evaluating the Impacts of Environmental and Anthropogenic Factors on Water Quality in the Bumbu River Watershed, Papua New Guinea
2. Study Area
3. Materials and Methods
3.1. Selection of Sampling Sites and Parameters for WQI
3.2. Water Sample Collection
3.3. Geo-Referencing of Sampling Points
3.4. Instrumental Analysis
3.4.1. Magnesium and Calcium Hardness, and Alkalinity
3.4.2. Calcium Hardness
3.4.4. Microbial Tests
3.4.5. Trace Heavy Metals Analysis (Pb, Hg, Mn, Fe, and Cd)
3.5. Selection of WQI Calculation Method: The CCME Index
3.5.1. Overview of CCME WQI
3.5.2. CCME WQI Calculation
3.6. Land Use Categorisation
3.7. Community Surveys Analysis
- Household general demographical information;
- Basic hygiene and sanitation;
- Major health and community concerns;
- Perception of community issues.
3.8. Correlation and Multivariate Analysis Methods
4.1. First Data Set (Water Samples) for WQI Evaluation
4.2. Second Data Set (Survey Analysis): Organisation into Macro-Categories
4.3. Third Data Set: Land Use Categorisation
4.4. PCA to Estimate the Correlation between WQ and Land Use
- Factor 1. This factor registers as a strong indicator of water clarity due to TDS, turbidity, conductivity, Fe, and temperature all being positively linked to the factor. The CCME WQI is also strongly negatively linked to this factor, indicating that the variations in these parameters are most highly associated with variation in the WQI. There is also a strong correlation with rainfall-runoff;
- Factor 2. This factor is mostly associated with urban conditions as reflected in the elevated loading values of variables such as highly urban, road runoff, and population/habitat;
- Factor 3. This factor is predominantly associated with semi-urban and green space variables, indicating that it is characterized by relatively less industrialized and urban conditions. Mg hardness is also positively linked to this factor. The variance of pH is negatively linked to this factor, indicating more acid conditions in these waters;
- Factor 4. This is a water hardness-related factor strongly associated to variables such as Ca hardness and Total Calcium. This is not surprising, as hardness is largely due to calcium carbonate (CaCO3);
- Factor 5. This factor has a strong positive connection to E. coli and regenerating forest conditions while being negatively associated with dense forest conditions, suggesting that E. coli concentrations are highest in areas associated with regenerating forests;
- Factor 6. This factor exhibited the highest negative association with the variable pertaining to Mn presence. Temperature and conductivity showed a somewhat strong positive association with this factor, although these parameters also exhibited a strong association with the clarity factor (Factor 1 mentioned above). Conductivity will considerably increase as temperature increases, so a correlation between the two parameters is expected.
4.5. Forward Regression to Estimate the Correlation between PCA and Surveys
4.6. Correlation between WQI and Surveys
4.7. Correlation between Surveys and Land Use
- The communities who live in the vicinity of the two highly urban stations have elevated perceptions of household health but low perceptions of community health;
- The communities who live in the vicinity of the nine dense forest stations have relatively high perceptions of community health but generally low to mid-range perceptions of household health scores;
- The communities who live in the vicinity of the four regenerating forest stations have generally low perceptions of household health but mixed results on perceptions of community health;
- The community/ies who live in the vicinity of the single semi-urban station scored high on both perceptions of community health and perceptions of household health;
- The communities who live in the vicinity of the six green space stations generally scored high in perceptions of household health but had mixed results on perceptions of community health.
5. Discussion and Conclusions
Data Availability Statement
Conflicts of Interest
Appendix A.1. Literature Review
- What elements are associated with water scarcity, waterborne diseases, and lack of access to clean water in populations globally and specifically in Papua New Guinea?
- What are the relationships between environmental and anthropogenic factors on water quality both globally and specifically in Papua New Guinea?
Appendix A.1.1. Search Strategy
|“Water Scarcity”||“Water Pollution”||“Water Borne Disease”||“Water Quality”||“Environmental Factors”||“Anthropogenic Factors”|
|“water supply”||“polluted water”||“waterborne diseases”||“water quality control”||“climatic factors”||“anthropogenic influence”|
|“water availability”||“freshwater pollution”||“water-borne disease”||“water quality standards”||“site factors”||“factores antropogénicos”|
|“water shortage”||“brackishwater pollution”||“waterborne illness”||“calidad de agua”||“ambient conditions”|
|“water deficit”||“water contamination”||“environmental conditions”|
|“escasez de agua”||“clean water”||“environmental variables”|
|“stream pollution”||“factores medioambientales”|
|“contaminación del agua”|
|Question||Main Terms||Expanded Terms|
|Review question 1||water scarcity||(“water scarcity” OR “water supply” OR “water availability” OR “water shortage” OR “water deficit” OR “Escasez de agua”) AND (“world” OR “global” OR “developing countr*” OR “Papua New Guinea”)|
|water pollution||(“water pollution” OR “polluted water” OR “freshwater pollution” OR “brackishwater pollution” OR “water contamination” OR “clean water” OR “Stream Pollution” OR “contaminación del agua”) AND (“world” OR “global” OR “developing countr*” OR “Papua New Guinea”)|
|water borne disease||(“water borne disease” OR “waterborne diseases” OR “water-borne disease” OR “waterborne illness”) AND (“world” OR “global” OR "developing countr*” OR “Papua New Guinea”)|
|Review question 2||Water quality, environmental factors, Anthropogenic factors|
- Web of Science
- European Environment Agency
- Stockholm International Water Institute
- Health Protection Agency, UK
- The US Environment Protection Agency
- World Health Organization
Inclusion Criteria and Screening Process
Appendix A.1.2. Main Factors Contributing to Water Scarcity and Water Scarcity Impacts
Appendix A.1.3. Factors and Impacts of Water Pollution
Appendix A.1.4. A World View of Water Pollution
- In rural areas, 70% of the population has access to a safe, convenient, and sustainable water supply.
- In urban areas, 95% of the population has access to a safe, convenient, and sustainable water supply.
- 100% of educational institutions and medical centres across the country have access to a safe, convenient, and sustainable water supply.
- In rural areas, 70% of the population has access to safe, convenient, and sustainable sanitation facilities.
- In urban areas, 85% of the population has access to safe, convenient, and sustainable sanitation facilities.
- 100% of educational institutions and medical centres have access to safe, convenient, and sustainable sanitation facilities.
- 100% of educational institutions and medical centres have handwashing facilities with running water and soap.
- 100% of the households that have access to an improved water supply practice total sanitation.
Appendix A.1.5. Water Quality Versus Anthropogenic and Environmental Factors
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|Excellent||95–100||The virtual absence of threat|
|Fair||65–79||Usually protected-occasional threats|
|Poor||0–44||Almost always threatened or impaired|
|Sample ID||CCME WQI|
|Rotated Component Matrix|
(Highest Loading of a Variate on a Single Factor Is Shown in BOLD)
|Rainfall normalized RUNOFF||0.900||−0.188||−0.160||0.115||−0.046||0.272|
|Road runoff IV||−0.039||0.981||−0.001||0.057||0.095||−0.008|
|Highly urban IV||−0.051||0.973||0.168||0.062||−0.021||0.055|
|Semi urban IV||−0.066||0.436||0.740||0.149||0.028||0.096|
|Green space IV||0.045||−0.235||0.738||−0.090||0.147||0.324|
|Regen forest IV||−0.247||−0.423||0.161||−0.016||0.800||0.115|
|Dense forest IV||0.165||−0.377||−0.560||−0.035||−0.649||−0.219|
|Model Summary—WQI vs. Health Value Scores|
|Model||r||R2||Adj. R2||Std. Error of the Estimate|
|Unstandardized Coefficients||Standardized Coefficients|
|Dependent Variable: CCME WQI|
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Doaemo, W.; Betasolo, M.; Montenegro, J.F.; Pizzigoni, S.; Kvashuk, A.; Femeena, P.V.; Mohan, M. Evaluating the Impacts of Environmental and Anthropogenic Factors on Water Quality in the Bumbu River Watershed, Papua New Guinea. Water 2023, 15, 489. https://doi.org/10.3390/w15030489
Doaemo W, Betasolo M, Montenegro JF, Pizzigoni S, Kvashuk A, Femeena PV, Mohan M. Evaluating the Impacts of Environmental and Anthropogenic Factors on Water Quality in the Bumbu River Watershed, Papua New Guinea. Water. 2023; 15(3):489. https://doi.org/10.3390/w15030489Chicago/Turabian Style
Doaemo, Willie, Mirzi Betasolo, Jorge F. Montenegro, Silvia Pizzigoni, Anna Kvashuk, Pandara Valappil Femeena, and Midhun Mohan. 2023. "Evaluating the Impacts of Environmental and Anthropogenic Factors on Water Quality in the Bumbu River Watershed, Papua New Guinea" Water 15, no. 3: 489. https://doi.org/10.3390/w15030489