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    Introduction.

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    Macropores and water flow in soils revisited

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    The original review of macropores and water flow in soils by Beven and Germann is now 30 years old and has become one of the most highly cited papers in hydrology. This paper attempts to review the progress in observations and theoretical reasoning about preferential soil water flows over the intervening period. It is suggested that the topic has still not received the attention that its importance deserves, in part because of the ready availability of software packages rooted firmly in the Richards domain, albeit that there is convincing evidence that this may be predicated on the wrong experimental method for natural conditions. There is still not an adequate physical theory linking all types of flow, and there are still not adequate observational techniques to support the scale dependent parameterizations that will be required at practical field and hillslope scales of application. Some thoughts on future needs to develop a more comprehensive representation of soil water flows are offered

    Uncertainty estimation in fluvial flood forecasting applications

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    A risk-based decision framework is outlined for the selection of uncertainty estimation techniques for use in real-time flood forecasting applications. The framework aims to achieve a balance between the operational requirements for probabilistic information and their use, and typical hydrological and operational constraints, such as catchment response times and computer processing power. A typology of techniques is introduced that employs the three overall categories of forward uncertainty propagation, probabilistic data assimilation and probabilistic forecast calibration. The relative strengths and limitations of each general category are contrasted, and illustrated using examples for a range of techniques and case study catchments across the UK. In conclusion, an indication is given of future research requirements in probabilistic flood forecasting

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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