There has been a resurgence of interest in the construction of large dams worldwide. This study examined many dams from around the world (>10,000) and compared them to a comprehensive dataset developed for Australia (224) to provide insights that might otherwise not be apparent from examining just one or several dams. The dam datasets (ICOLD and ANCOLD) largely confirm existing narratives on Australian dam construction. Compared to dams from Rest of the World (RoW), Australian dams were found to: have larger reservoir capacities and spillway capacities for a given catchment area;have higher dam walls for a given capacity; andresult in higher degrees of river regulation.A range of general relationships among reservoir capacities, reservoir surface areas, and catchment areas are presented which can be used in reconnaissance or pre-feasibility studies and for global hydrologic modelling when dam and reservoir information are required as input.
Major restructuring including commercialisation of the water authorities in Australia during the past several decades has resulted in the loss of much valuable information on dam infrastructure costs. This paper sets out to provide an Australian perspective on dam costs and dam cost overruns, examine patterns of dam costs and cost overruns, and develop a good predictor of costs and cost overruns for the Australian situation. Several cost metrics, dam costs and related data, were collated for 98 dams constructed across Australia since 1888. Dam costs, operation and maintenance (O&M) costs, and construction overrun costs were related to independent variables including dam site terrain characteristics and catchment and climate attributes. Each metric was related through multiple regression to mainly physical and climate attributes associated with the dam. Multiple correlation coefficients account for between 50% and 80% of the variance in the dependent variable. The exceedance range (defined as 75% exceedance to 25% exceedance) of final dam costs (2016 AUD) (98 dams) is from $393 per ML of reservoir storage to $2040 per ML. Annual O&M costs (33 dams), expressed as a % of final dam cost, varies from 0.14% to 0.35%, though these O&M costs do not include major upgrades. The results of this study of Australian dams are in keeping with international studies that have found the estimated costs of large infrastructure projects are systematically biased downwards. In this study the median and mean cost overruns (40 dams), expressed as a percentage of the dam cost estimated immediately prior to construction, are 49% and 120% respectively with the smallest and largest cost overrun values being −48% and 825% respectively. Based on the available data dam cost overruns appear to be more prevalent in sedimentary rock than hard rock (e.g. igneous and metamorphic rocks) settings. The strong likelihood of dam cost overruns occurring has implications to forecasted benefit-cost ratios, and supports assertions that large dam cost and contingency estimates should be checked at pre-feasibility and feasibility stages by an independent organisation and by persons highly experienced in dam design, construction and costing.
Abstract The majority of the world’s population growth to 2050 is projected to occur in the tropics. Hence, there is a serious need for robust methods for undertaking water resource assessments to underpin the sustainable management of water in tropical regions. This paper describes the largest and most comprehensive assessment of the future impacts of runoff undertaken in a tropical region using conceptual rainfall–runoff models (RRMs). Five conceptual RRMs were calibrated using data from 115 streamflow gauging stations, and model parameters were regionalized using a combination of spatial proximity and catchment similarity. Future rainfall and evapotranspiration projections (denoted here as GCMES) were transformed to catchment-scale variables by empirically scaling (ES) the historical climate series, informed by 15 global climate models (GCMs), to reflect a 1°C increase in global average surface air temperature. Using the best-performing RRM ensemble, approximately half the GCMES used resulted in a spatially averaged increase in mean annual runoff (by up to 29%) and half resulted in a decrease (by up to 26%). However, ~70% of the GCMES resulted in a difference of within ±5% of the historical rainfall (1930–2007). The range in modeled impact on runoff, as estimated by five RRMs (for individual GCMES), was compared to the range in modeled runoff using 15 GCMES (for individual RRMs). For mid- to high runoff metrics, better predictions will come from improved GCMES projections. A new finding of this study is that in the wet–dry tropics, for extremely large runoff events and low flows, improvements are needed in both GCMES and rainfall–runoff modeling.
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