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H. Mwanake:
"Application of the MONERIS model in the Lake Naivasha Catchment, Kenya";
Betreuer/in(nen): N. Kreuzinger; Institut für Wassergüte, Ressourcenmanagement und Abfallwirtschaft, UNESCO-IHE, 2013; Abschlussprüfung: 04/2013.

The Lake Naivasha ecosystem is important in Kenya but it seems to be under pressure because of the economic activities like agriculture, water abstraction, geothermal power generation, keeping domestic animals, fishing and also tourism. However there is a concern that the Lake is continuously under the threat of cultural eutrophication. Questions have been raised as to what roles the Rivers Malewa and Gilgil play into the input of nutrients into the lake. This study seeks to assess the N and P situation in the Malewa and Gilgil Rivers. Establish the applicability of the MONERIS model in the catchment in order to know the contribution of Malewa and Gilgil Rivers to the input of nutrients loads particularly nitrates and phosphates into the Lake and identify the most important pathways for the river runoff and the nutrients emission and whether anthropogenic sources play a role.
This study found that the mean value for nutrient concentrations of the Malewa River were NO3 1.982 mg/l, NH4 0.201 mg/l, NO2 0 mg/l, DIN 2.184 mg/l, TN 10.696 mg/l, SRP 0.035 mg/l and TP 0.123 while for the Gilgil River NO3 2.091 mg/l, NH4 0.259 mg/l, NO2 0.001 mg/l, DIN 2.35 mg/l, TN 11.025 mg/l, SRP 0.031 mg/l and TP 0.105 mg/l. The discharge was found to vary within the sub catchments. The River flow within the catchment is dependent on base flow/ ground water which contribute up to 250 mm/yr. The average loads produced by the nine sub catchments include 237t/yr DIN, 256t/yr TN and 6t/yr for TP. The Malewa River sub catchments were found to contribute the higher loads compared to the Gilgil River sub catchments. The most important emission pathways for N was found to be the ground water which transports up to 11 kg N/(ha*yr) while for phosphorus, urban and surface runoff were the most important transporting up to 0.18 kg P/(ha*yr) and 0.1 kg P/(ha*yr) respectively. In both the TN and TP loads anthropogenic sources played a huge role. For TN 90 % agriculture and 10% households and urban areas while for TP 53% agriculture and 45% households and urban areas.
This study recommends that the sub catchment boundaries should be revised according to the hydrology rather than political. Lower Malewa, Middle Malewa, Upper Turasha and Mkungi Kitiri should be prioritized in order to manage loads and therefore eutrophication into the Lake.

MONERIS, Eutrophication, Nutrients Loads, Emission pathways and Sources