A variety of indices for characterising hydrological drought have been devised which, in general, are data demanding and computationally intensive. On the contrary, for meteorological droughts very simple and effective indices such as the Standardised Precipitation Index (SPI) have been used. A methodology for characterising the severity of hydrological droughts is proposed which uses an index analogous to SPI, the Streamflow Drought Index (SDI). Cumulative streamflow is used for overlapping periods of 3, 6, 9 and 12 months within each hydrological year. Drought states are defined which form a non-stationary Markov chain. Prediction of hydrological drought based on precipitation is also investigated. The methodology is validated using reliable data from the Evinos river basin (Greece). It can be easily applied within a Drought Watch System in river basins with significant storage works and can cope with the lack of streamflow data.
A conventional approach for the economic estimation of direct flood damage to buildings is using the method of depth-damage functions. However, there are few publications that describe in detail the derivation of depth-damage functions based on actual flood damage data. It still remains an open issue whether a site-specific depthdamage function can be applied to another region with similar climate and building conditions. This paper aims at demonstrating a step-by-step methodology for devising depth-damage functions using data from a flood event which occurred in Moschato, a suburb of Athens, Greece in July 2002. It also compares the developed depth-damage functions to functions from other areas with similar conditions. In the case study, the damage percentage is calculated per category of flood-affected property on the basis of relief payments. The replacement cost of the affected components of a building structure and the market value of each category of flood-affected property are estimated in order to develop depth-damage relationships for building structures. The local depth-damage function for residential use is compared to generalized functions and a site-specific function developed for the urban area of Palermo, Italy. Differences and similarities in damage datasets are examined and explained by related causative factors such as structural or architectural features of buildings. Finally, the application of both of the above functions to a third case (the Erasinos river basin in Attica, Greece) resulted in a fair difference (9 %) in the estimation of the expected average annual direct damage to residential buildings.
A parametric rule for multireservoir system operation is formulated and tested. It is a generalization of the well‐known space rule of simultaneously accounting for various system operating goals, in addition to the standard goal of avoiding unnecessary spills, including avoiding leakage losses, avoiding conveyance problems, taking into account the impacts of the reservoir system topology, and assuring satisfaction of secondary uses. Theoretical values of the rule's parameters for each one of these isolated goals are derived. In practice, parameters are evaluated to optimize one or more objective functions selected by the user. The rule is embedded in a simulation model so that optimization requires repeated simulations of the system operation with specific values of the parameters each time. The rule is tested on the case of the multireservoir water supply system of the city of Athens, Greece, which is driven by all of the operating goals listed above. Two problems at the system design level are tackled. First, the total release from the system is maximized for a selected level of failure probability. Second, the annual operating cost is minimized for given levels of water demand and failure probability. A detailed simulation model is used in the case study. Sensitivity analysis of the rule's parameters revealed a subset of insensitive parameters that allowed for rule simplification. Finally, the rule is validated through comparison with a number of heuristic rules also applied to the test case. Appendices are available on microfiche. Order from AmericanGeophysical Union, 2000 Florida Avenue, N.W., Washington, DC 20009. Document 97WR01034M; $2.50. Payment must accompany order.
Conventionally droughts are studied in terms of their dimensions (severity, duration and areal extent), without specifying the affected system. The paper presents an innovative system-based approach for drought analysis, which can lead to rational decisions for combating drought. Concepts of water scarcity (drought, water shortage, aridity and desertification) are viewed within the perspective of this new approach. The paper focuses also on operational water management in the presence of drought. Starting from the needs for such management, the affected system is defined and the related quantities are identified. Also, sub-systems are considered which allow the establishment of the link between specific variables Water Resour Manage
Abstract. The HYDROGEIOS modelling framework represents the main processes of the hydrological cycle in heavily modified catchments, with decision-depended abstractions and interactions between surface and groundwater flows. A semi-distributed approach and a monthly simulation time step are adopted, which are sufficient for water resources management studies. The modelling philosophy aims to ensure consistency with the physical characteristics of the system, while keeping the number of parameters as low as possible. Therefore, multiple levels of schematization and parameterization are adopted, by combining multiple levels of geographical data. To optimally allocate human abstractions from the hydrosystem during a planning horizon or even to mimic the allocation occurred in a past period (e.g. the calibration period), in the absence of measured data, a linear programming problem is formulated and solved within each time step. With this technique the fluxes across the hydrosystem are estimated, and the satisfaction of physical and operational constraints is ensured. The model framework includes a parameter estimation module that involves various goodness-of-fit measures and state-of-the-art evolutionary algorithms for global and multiobjective optimization. By means of a challenging case study, the paper discusses appropriate modelling strategies which take advantage of the above framework, with the purpose to ensure a robust calibration and reproduce natural and human induced processes in the catchment as faithfully as possible.
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