**1. Introduction**

As a result of rapid urbanization, population expansion and concomitant technological developments, substantial strain is being placed on the water systems around the world, making quality of water a matter of global significance [1]. The waters of an ecosystem have a symbiotic relationship with the health and welfare of the resident communities consuming it [2]. Study of the probable impacts of various sources on water quality has been elegantly summarized by a conceptual framework put forward by Granger et al. [3] that can arguably be described as the process of:


Previous studies have revealed that immediate landscape features and land use patterns significantly influence water quality [4–11]. Nevertheless, these topographical features are susceptible to alterations and are usually examined under Land Use/Land Cover Change (LULCC) initiatives. LULCC can be defined as a convoluted process of transformation of landscape and its related patterns of utility due to environmental and human-induced interactions [12]. These interactions in turn have a corresponding e ffect on the physicochemical composition of water. Given these interdependencies, water systems are best identified through river basins and watersheds that comprise a uniquely integrated hydrological network through which precipitation runo ff flows into a specific larger body of water such as a river, lake or ocean. The network of streams across a drainage basin is the conduit for all precipitation deposited onto the catchment area in its journey to reach the sea. In passing through the catchment area, precipitation receives the detritus of human existence as well as the accumulation of geologic minerals dissolved and granulated to such a degree as to be mobile in the air and on the earth's surface [13]. These constituents in water are indicative of the impact of various environmental and anthropogenic parameters.

With respect to the aforementioned context, the Morobe Development Foundation (MDF) has undertaken a study to understand the mutual dependency that exists between waters of the Bumbu Watershed and the residents of communities of Lae in Papua New Guinea who rely on these waters for their continued existence and sustainability. Resident communities utilize water of the Bumbu river primarily for drinking and sanitation purposes, but simultaneously, they lack access to proper toilet facilities and a treated water supply. This problem is compounded by untreated sewage and the dumping of pollutants by industries established in the vicinity. As a result, water quality has become a serious concern in the region exposing human health to various risks in the form of skin infections and waterborne diseases [14]. The study seeks to fill a gap to address the risks to human health and security created by poor water quality by analyzing influence of di fferent factors on the Bumbu basin.

The protocol developed in this study is designed to explore the relationship between the spatial distribution of diverse factors that have the potential to influence water quality, and the spatial distribution of measured water quality. The use of spatial analysis and corresponding tools for this purpose incorporates a divergent approach in comparison to methods such as pH Redox Equilibrium modeling (phreeqc), which is designed to explore the mechanistic relationship between water composition and the actual geological and hydrological conditions a ffecting it. Once an exploratory study using the protocol developed in this work is completed, a more detailed approach in the latter direction can be taken up for the Bumbu Watershed. Consequently, to study this relationship, we utilized available Geographic Information System (GIS) methodologies to develop a protocol which not only measures the influence of anthropogenic and environmental factors on runo ff but also has the capability to be extended to socio-economic parameters such as community health, pollution, waste disposal, crime and sanitation. The evolution of Geographic Information System (GIS) has led to the advancement of analytical tools to comprehend the interrelationship existing between land use and the corresponding quality of water, which in turn has led to commendable contributions in watershed managemen<sup>t</sup> [8–10]. With respect to this initial research, we consider roads, streets, rainfall patterns, forested and industrialized landscapes as examples of factors that present a possible correlation with runo ff water quality. Data for such features often exist in a variety of formats familiar to spatial analysts—i.e., in vectorized and/or gridded databases depending on the data source (these formats will be explained in more detail in further sections).

In pursuit of the above objective, a review of available literature, databases and analytic techniques has been conducted to gather relevant insights. Guoyu Xu et al. [4] studied the e ffect of multiple temporal and spatial scales on the quality of water across 32 sampling sites in the Wujiang River Watershed in China. They examined eight variables as possible indicators of quality, utilized Partial Least Scale (PLS) regression and found that quality was influenced by landscape configuration, composition and precipitation. The levels of Dissolved Oxygen (DO) were found to be higher in dry season and higher levels of other contaminants were found during the wet season. Only landscape level metrics in periods of rainfall were found to be related to organic matter. They also concluded that watershed bu ffer areas involving small patches of cropland with high aggregation of forested areas lead to better quality of water. Likewise, Xiao et al. [6] investigated the relationship between water quality and landscape metrics at multiple spatial scales in di fferent seasons. For this purpose, they took into consideration 34 sampling sites across Huzhou City. They utilized stepwise regression and found that built-up land "has a role in influencing" water quality at a smaller scale, whereas at a local scale, multiple land use categories can be expected to impose an influence. Total Nitrogen (TN) was found to be negatively correlated with the index of build-up land, whereas landscape index of forest was positively correlated with it. Moreover, Putro et al. [7] investigated the impact of land use pattern and climate on the quantity and quality of water across two urbanized catchment areas and two rural catchment areas located in the United Kingdom. Using multivariate regression models, they assessed the influence of rainfall and urbanization on the trends in the DO, runo ff and temperature of the water network involved. They found that temperature and dissolved oxygen variation with respect to catchment in urban areas are not driven by climatic variables. The temperature, total runo ff and DO displayed an upward trend for urban catchments, but the same was not true for undeveloped catchments. In another study conducted by Lintern et al. [5], the authors studied existing literature to understand how spatial variability of landscape characteristics and interseasonal variation lead to variations in water quality. They analyzed di fferent correlations that exist for di fferent landscape characteristics including land use, geology, topography, hydrology, soil type and climate through a rigorous literature review. For example, their review revealed that rainfall is positively correlated with Electrical Conductivity (EC) for developed landscape factors such as urban areas, and negatively correlated with EC for undeveloped factors such as grasslands. Similarly, topography depicted by slope/elevation for undeveloped landscape was positively related with Total Suspended Solids (TSS), Total Phosphorus (TP) and Total Kjeldahl Nitrogen (TKN), whereas slope/elevation for developed landscape factors was negatively related to the same constituents. The authors stressed the need to consider the relation existing between the numerous catchment characteristics, impact of the spatial setting of di fferent landscape features, interannual and interseasonal variability to comprehend the relationship existing between water quality and landscape features. Their paper revealed the wide range of factors that can influence runo ff and highlighted the need to take into account a wide range of environmental data.

In this preliminary study, we elaborate how we measured the relative influence of the di fferent factors indicative of environmental and anthropogenic impact on surface runo ff at the respective water sampling sites using GIS tools and techniques. We also discuss the relevance of this protocol to the ability to use the factor runo ff importance values and to be able to accommodate other parameters such as water, sanitation and hygiene (WASH) practices and other socio-economic factors for our future water quality studies. With the livelihood, health and welfare of the communities dependent on the waters of the Bumbu Watershed, it has become a necessity to explore the relationship that exists between the anthropogenic and environmental factors influencing runo ff, WASH conditions, physiochemical analysis of the waters of the Bumbu and the corresponding water quality. This protocol is the first major step, and a stepping-stone in this direction. In Section 2, we elucidate the methodology and the protocol involved based on the di fferent formats and characteristics of the available factors. In Section 3, we present our results related to the computations of raw runo ff and relative impact of the factors. In Section 4, we discuss our findings, and our plans to utilize the protocol and its results in our upcoming water quality studies.
