Investigating the relationship of scale and resilience in integrated water resource management in the Crocodile River, South Africa

The Crocodile River Catchment is a trans-boundary river that flows from South Africa into Mozambique traversing a variety of land use areas including forested upland areas to ecologically sensitive areas downstream in the "lowveld" region. The river also serves as a critical source of water for irrigation, mining and municipal water supply. These competing demands have put undue pressure on its water resources and the river is considered "oversubscribed" by governmental agencies. Water managers in the region are responsible for making critical decisions on water use allocations from the Crocodile River in a data-poor environment necessitating the use of models to simulate water use and management scenarios. Two major considerations in the interpretation of both observed and simulation data are the resolution of observation/prediction of hydrological events such as runoff, precipitation and groundwater movement and the resulting effects on management decisions which influence the ecological health, sustainability and resilience of the water catchment (Bloschl & Sivaplan, 1995).;The evaluation of hydrologic model behavior and performance at different scales is achievable using a variety of statistical measures that compare simulated and observed variables observed at the outlet of a catchment unit which in the South African context is at either the primary, secondary, quaternary or quinary scale. Single multiresponse efficiency criteria are traditionally used by hydrologists to provide information about the closeness of simulated outputs to observed data such as coefficient of efficiency and coefficient of determination. Owing to errors due to parameterization at different scales, these methods can be misleading and ambiguous resulting in incorrect verification of results used in making critical planning decisions. A combination of normalized goodness-of-fit measures, observation of bias and confidence intervals and graphical presentation gives a more comprehensive approach to validating hydrological model simulations and flow data. The analysis involves comparing the outputs of the model when parameterized at the quaternary and quinary scales.;Another tool for integrating environmental data, simulations and human interactions is the use of Bayesian networks in which water managers can combine and quantify variable factors such as economic output, ecological health and precipitation. While these models are inadequate in providing accurate system behavior of these outputs they have proved useful in integrating disparate sources of information to water managers that provide valuable insights in understanding the behavior of the Crocodile River system as a complex adaptive system. The process of configuring the Bayesian networks is performed iteratively. Sensitivity analysis on the different components of the system ensures that the model behavior aligns with reality. This approach presented demonstrates the application of Bayesian networks in the Crocodile River catchment of South Africa as qualitative and quantitative tool for strategic adaptive management. The Bayesian methodology approach proposed formalizes the reasoning and rules demonstrated in an influence diagram. The feasibility of this Bayesian network is shown in economic and ecological scenarios that are developed to demonstrate various system states based on management variables such as dam construction, sectoral economic contribution and ecological reserve implementation. The resulting analysis indicates that the habitat, riparian, invertebrate and fish indices have the greatest influence over the results of the ecological state. The results will be useful in ongoing catchment level ecological monitoring efforts and in the development of management scenarios for water supply and management.