## 2 Materials and Methods
### Sampling and Monitoring Parameters  
The monitoring sites and sampling strategy were planned to cover a wide range of factors contributing to the water quality of the river, taking into account tributaries and point sources whose effluents end up in the lake and have a substantial impact on the water quality of the lake. The criteria for selecting monitoring points were hydrological, with confluence of sub-basins having distinct characteristics and land use types, with the intention of transferring parameters to unmonitored sub-basins. Furthermore, factors such as availability of point and non-point sources, land use type, and urban and wastewater drains were considered in the selection of monitoring sites. Hence, a total of nineteen (19) monitoring stations were selected (Table 1 and Figure 1). Four (4) monitoring sites were selected purposively at the Wesha, Hallow, Wedessa, and Tikur-Wuha river mouths of the respective sub-watersheds. Eleven (11) monitoring sites were distributed evenly along the entire course of Lake Hawassa for water quality monitoring. Three (3) monitoring sites were selected near the industrial disposal site, and one (1) was at the health care center. The monitoring sites in the Tikur-Wuha catchment were Wesha River (MS1), Hallo River (MS2), and Wedessa River (MS3), which are located in the upstream part of Lake Hawassa, where agricultural runoff from the catchment flows directly or through its tributaries into the Cheleleka wetland. The three rivers were purposively selected based on their size and spatial location to represent their respective sub-basins. Monitoring station 6 (MS6) is a critical area with mostly fresh water where factories discharge their effluent into the Tikur-Wuha River, and the river eventually flows into Lake Hawassa. This is an area where river inputs to the lake are high. Figure 1: Study area map and monitoring station locations (**a**) = countries sharing boundaries with Ethiopia, (**b**) = major river basins in Ethiopia, (**c**) = Rift Valley lake basin and (**d**) = Lake Hawassa sub-basin and monitoring stations). Monitoring sites for point sources were selected from available industries in the catchment that directly or indirectly feed Lake Hawassa. The selected sites were the St. George Brewery factory, BGI (MS4), and the Moha soft drink factory (MS5), whose effluents discharge into the Cheleleka wetland and eventually enter Lake Hawassa via Tikur-Wuha River, as well as the Referral Hospital (MS15) and Hawassa Industrial park (MS19), which discharge their effluents directly in to Lake Hawassa. The monitoring stations for Lake Hawassa were selected based on the presence of major pollution sources in the lake, existence of point sources, health facilities, industrial effluent emission sites, availability of boating and recreational activities, presence of service rendering facilities such as Haile and Lewi resorts, fish market (Amora-Gedel and Gudumale), and also the central part of the lake where the disturbance is minimum. For this purpose, eight (8) monitoring sites were selected in the eastern part (northeast to southeast) of the lake and designated as MS7, MS8, MS9, MS10, MS11, MS12, MS13, and MS14. The other three (3) monitoring sites were located on the western (northwest to southwest) sides of the lake and were designated as MS16 for the local village Ali-Girma site (opposite Haile Resort), MS17 for Sima site that is opposite side of Mount Tabor, and MS18 for Dore-Bafana Betemengist site. In this part of the lake, although there is no point source pollution, there is enormous anthropogenic activity in the form of non-point source pollution from recreational activities, agricultural runoff, and animal waste. The analyses of physicochemical water quality parameters at selected sites and periods were conducted from May 2020 to January 2021 to see seasonal variation. Sample collection for the wet season was event-based, i.e., samples were collected after rainfall events. The coordinates of each sampling stations was determined using GNSS.