**4. Discussion**

The protocol developed in this study follows and expands upon the conceptual framework of Granger et al. [3] in identifying potential sources of impact on water quality, their mobilization by rainfall and their delivery across the landscape by a stream network. The methodologies presented in

this study facilitate assessment of the relative importance/concentrations of different environmental and anthropogenic factors, enabling investigation of their potential impact on runoff water quality. Initially, the factors which we considered for this purpose include Road/Streets, Dense Forests, Regenerating Forests, Green Space, Highly Urban, Semi-Urban and Habitation/Population. This was followed by the application of different techniques and tools for each category characterized by line, point and raster-based GIS layers. The raw runoff values for the various factors were computed by utilizing DEM, spatial interpolation, classification methods and GIS software functionalities such as WATERSHED and RUNOFF features. The raw runoff values for each of the factors at the 22 water sampling sites are listed in Table 2. As stated in the previous section, we made use of normalized rainfall runoff values to determine the potential impact of the various factors. Figures 11 and 12 represent the spatial distribution of the relative importance values of the factors involved. Table 3 indicates the corresponding importance values at the 22 sampling sites. For instance, considering Sampling Site number 22, one can observe that the runoff importance is negligible from several factors indicative of varying vegetation density and is significantly greater from highly urban and semi-urban areas. This would imply a higher impact of urban areas on surface runoff and would indicate a greater concentration/impact of constituents contributed by urban factors. Similar observations can be made at other water sampling sites. One can observe that the runoff at each of the 22 sites involves considerable levels of varying influences from a variety of factors. This indicates the range of potential challenges possible to runoff quality in form of organic matter, coliforms, geochemical and natural ingredients to a name a few. However, to explore the exact nature of relationship existing between these factors and the waters of the watershed, a detailed correlation analysis is needed, which we discuss in more detail below.

In our upcoming studies, we plan to study how the runoff importance values for different factors are associated with the physical and chemical composition of the Bumbu waters by performing a detailed and thorough water quality study. This would include collection of water samples at the 22 sites followed by physicochemical analysis. Furthermore, a factor analysis/principal component analysis (FA/PCA) can also be performed as performed in earlier studies [28–31]. This would help us in understanding several relationships with respect to the waters of the Bumbu Watershed. For instance, whether Total Suspended Solids (TSS) and turbidity are correlated with surface runoff due to rainfall events, and to what extent and degree. Another example could be measuring the variation of DO, Electrical Conductivity (EC) and Thermotolerant Coliforms (TC), which are related to organic matter pollution. Some other examples would include evaluating how pH, alkalinity, temperature and metallic ions vary with different levels of vegetation and urbanization in the vicinity of the sampling points. Measuring the water quality index at the water sampling sites using available standards and guidelines such as those drafted by the Canadian Council of Ministers of the Environment (CCME) will also be a necessary step to comprehend how quality of water is related to the runoff importance values computed in this study [32]. We also plan to undertake a community-wide household survey to gather relevant WASH-related data such as sources of drinking water, toilet facilities, water storage and waste disposal methods used in proximity to our 22 water sampling sites. Additionally, we intend to gather community data based on parameters such as health, crime and pollution. Health-related parameters may include variables such as presence of stomach ailment, skin infections, HIV/AIDS and respiratory illness. Although crime and HIV may seem to be far-reaching candidates for correlation with water quality, the study's fundamental objective is to provide a method to explore if such non-intuitive correlations exist, and to provide a reasonable protocol for exploration, analysis and resolution of the complex questions they raise. As mentioned earlier, these types of data are constrained to be point sources of information and can be utilized easily by our protocol as implemented in the case of rainfall. All these inputs together with the anthropogenic and environmental factors form an array of socio-economic environmental (SEE) inputs. Finally, we intend to perform a correlation analysis to determine how the runoff importance values calculated from this study vary with accepted measures of water quality, e.g., the Canadian Ministers of the Environment Water Quality Index, different SEE

factors as well as physicochemical parameters of water. Several multivariate analytical techniques such as Pearson and Spearman correlation, numerous regressions models and other statistical tools are available and have been used previously in this regard [4–9,28–31].

Our study is bound by data limitations such as the utilization of data collected by McAlpine et al. (1975) [27]. Although climate patterns are changing, McAlpine data represent the best current available estimate of rainfall patterns across Morobe Province to reliably perform spatial interpolation for the Bumbu basin. Another limitation is imposed by the utilization of a 30 m DEM despite our e fforts to obtain a DEM of higher resolution for the watershed. Due to imprecision of the DEM, there is discrepancy between derived stream lines and observed streams, a shortcoming that we attempted to rectify as explained in Section 2.6. Despite the above limitations which we tried to overcome, the uniqueness of our approach lies in the fact that the protocol we developed not only takes into account various environmental and anthropogenic factors but also has the potential to accommodate the various socio-economic factors such as community and household health, crime and waste disposal.
