Abstract
The continuing decline in lake water levels is both a concern and daunting challenge to scientists and policymakers in this era, demanding a rethinking of technological and policy interventions in the context of broader political and socio-economic realities. It is self-evident that diverse factors interact in space and time in complex dynamics to cause these water-level changes. However, the major question demanding sound answers is how these factors interact and by what magnitude they affect lake water balance with time. This chapter uses Lake Victoria’s hydrological system to shed light on the extensive and flexible modelling and simulation capabilities availed by modern computer models to understand the bigger picture of water balance dynamics. The study used the 1950-2000 hydrological data and riparian population growth to develop a dynamic simulation model for the lake’s water level. The intuitive structure of the model provided clear insights into the combined influence of the main drivers of the lake’s water balance. The falling lake water levels appeared to be mainly due to dam outflows at the outlet and reduced rainfall over the lake. The ensuing conclusions stressed the need for checks against over-release of lake water for hydropower production and measures for sustainable land and water management in the entire basin.
TopBackground To The Study
By surface area, Lake Victoria is the largest tropical lake and the world’s second largest freshwater lake. It supports a dense riparian population exceeding 30 million and growing at an annual rate averaging 3%. The Lake Victoria basin has the highest population density increase of the world’s rural areas (GNF, 2005). It is evident that there is increasing pressure on the lake to meet the demands of the fast-growing population, economy, and ecosystem services. Like many lakes in the region, Lake Victoria is affected by problems of loss of species biodiversity, invasive species, eutrophication, and a water-level decline reported to be beyond two metres over the last decade. Destructive human activities aggravate this degradation (LVEMP, 2005).
The falling water level of Lake Victoria is outstanding among its many problems known in the public domain. Even the eleventh World Lakes Conference convened in Nairobi in October 2005 reached an international consensus that an “accelerated push” to save the lake was necessary to sustain its life-support functions (GNF, 2005). There are fears that the lake may go the fateful way of Lake Chad and the Aral Sea, both of which have virtually disappeared – exacerbated by the negative impact of destructive human activities in their basins. Urging greater environmental caution in water management, Gleick (2003) has detailed the need to choose “soft-path” solutions in the 21st century as opposed to “hard-path” solutions. The former type mainly involves efficiency measures that cut down on the wastage caused by mismanagement of available fresh water. The latter type of solutions involves expensive and massive physical structures and imposes adverse long-term costs on ecology and the human society in general.
Key Terms in this Chapter
Calibration: Refers to using known data to test if model results are close to the expected results.
Systems Thinking: A holistic concept of tackling problems and events by taking into account the larger scope in the complete environment.
State Variable: A quantifiable stock size that varies with time in a system depending on the sum of the inflow and outflow processes connected to it.
STELLA: Is a graphically interfaced dynamic modelling and simulation software system.
Altimetry: Technique for measuring altitude, applied to monitoring the water levels of large water bodies from space using satellite systems.
Converter: In dynamic modelling, a converter is a rate to which the system behaviour is so highly sensitive that even small changes to it can be noticed significantly in the state variables. Annual population growth rate is a fitting example in modelling population growth.
Validation: Refers to evaluating model reliability by comparing its output with extensive empirical findings.
Simulation: In modelling refers to predicting system behaviour by running a model using input data.
Geiod: Equipotential surface approximating the mean sea level.