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Alfonso L.,Hydroinformatics and Knowledge Management | Lobbrecht A.,Hydroinformatics and Knowledge Management | Lobbrecht A.,HydroLogic BV | Price R.,Hydroinformatics and Knowledge Management
Water Resources Research | Year: 2010

Data collection is a critical activity in the management of water systems because it supports informed decision making. Data are collected by means of monitoring networks in which water level gauges are of particular interest because of their implications for flood management. This paper introduces a number of modifications to previously published methods that use information theory to design hydrological monitoring networks in order to make the methods applicable to the design of water level monitors for highly controlled polder systems. The new contributions include the use of a hydrodynamic model for entropy analysis, the introduction of the quantization concept to filter out noisy time series, and the use of total correlation to evaluate the performance of three different pairwise dependence criteria. The resulting approach, water level monitoring design in polders (WMP), is applied to a polder in the Pijnacker region, Netherlands. Results show that relatively few monitors are adequate to collect the information of a polder area in spite of its large number of target water levels. It is found, in addition, that the directional information transfer DITYX is more effective in finding independent monitors, whereas DITYX is better for locating sets of monitors with high joint information content. WMP proves to be a suitable and simple method as part of the design of monitoring networks for polder systems. Copyright 2010 by the American Geophysical Union.


Alfonso L.,Hydroinformatics and Knowledge Management | Lobbrecht A.,Hydroinformatics and Knowledge Management | Lobbrecht A.,HydroLogic BV | Price R.,Hydroinformatics and Knowledge Management
Water Resources Research | Year: 2010

A method for siting water level monitors based on information theory measurements is presented. The first measurement is joint entropy, which evaluates the amount of information content that a monitoring set is able to collect, and the second measurement is total correlation, which evaluates the level of dependency or redundancy among monitors in the set. In order to find the most convenient set of places to put monitors from a large number of potential sites, a multiobjective optimization problem is posed under two different considerations: (1) taking into account the costs of placing new monitors and (2) considering the cost of placing monitors too close to hydraulic structures. In both cases, the joint entropy of the set is maximized and its total correlation is minimized. The costs are considered in terms of information theory units, for which additional terms affecting the objective functions are introduced. The proposed method is applied in a case study of the Delfland region, Netherlands. Results show that total correlation is an effective way to measure multivariate independency and that it must be combined with joint entropy to get results that cover a significant proportion of the total information content of the system. The maximization of joint entropy gives results that cover between 82% and 85% of the total information content. Copyright 2010 by the American Geophysical Union.

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