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The generalised likelihood uncertainty estimation (GLUE) approach was applied to assess the performance of a distributed catchment model and to estimate prediction limits after conditioning based on observed catchment-wide streamflow. Prediction limits were derived not only for daily streamflow but also for piezometric levels and for extreme events. The latter analysis was carried out considering independent partial duration time series (PDS) obtained from the observed daily streamflow hydrograph. Important data uncertainties were identified. For streamflow the stage-discharge data analysis led to estimate an average data uncertainty of about 3 m³ s-1. For piezometric levels, data errors were estimated to be in the order of 5 m in average and 10 m at most. The GLUE analysis showed that most of the inspected parameters are insensitive to model performance, except the horizontal and vertical components of the hydraulic conductivity of one of the geological layers that have the most influence on the streamflow model performance in the application catchment. The study revealed a considerable uncertainty attached to the simulation of both high flows and low flows (i.e., in average terms 5 m³ s-1 before the Bayesian updating of the prediction limits). Similarly, wide prediction intervals were obtained for the piezometric levels in relevant wells, in the order of 3.3 and 1.5 m before and after the Bayesian updating of the prediction limits, respectively. Consequently, the results suggest that, in average terms, the model of the catchment predicts overall outputs within the limitations of the errors in the input variables. [ABSTRACT FROM AUTHOR]

In this paper we discuss the use of system dynamics as a methodology with which to address dynamically complex problems in water resources management. Problems in regional planning and river basin management, urban water management, flooding and irrigation exhibit important short-term and long-term effects, and are often contentious issues with high potential for conflict. We argue that system dynamics combined with stakeholder involvement provides an appropriate methodology to address these issues effectively. We trace the theoretical and practical evolution of system dynamics in these areas over the past 50 years. From this review of the literature and selected case studies we identify and discuss a number of best practices and common pitfalls in applications of system dynamics simulation. [ABSTRACT FROM AUTHOR]

This article discusses regional planning in the United States and the negative attitude of citizens regarding the practice. Vermont combines New England's strongest banking climate and strictest regional land-use planning. It is the only New England state that has not suffered a savings-and-loan collapse, and it has the region's most demanding statewide environmental regulations. Vermont's experience marks a fascinating turn in America's generations-long ambivalence toward regional land-use planning. Let us define regional planning as the regulation of land development projects that is conducted by governments above the municipal and county levels. Regional planning has traditionally foundered on the plain fact that many Americans truly loathe modem, centralized, regulatory government. In no area is the contradiction as apparent as in regional land-use planning. Regional planning in the United States has provably increased each year for at least the last two decades and it is likely to expand in coming years. This activity has been genuinely embraced at federal and state levels. And yet, it is hated anyway. The time has come to rework this complex tangle of attitudes and bring them more in line with reality, in the Vermont manner.

The author reflects on the benefits offered by urban areas in enhancing the life of the people and promoting development among communities. He asserts that urban areas should provide adequate resources, such as natural systems, in addressing the needs and demands of societies. The author contends that effective land and regional planning plays essential role towards urbanization.