The development of regionalised hydrological models or procedures for estimating flow duration statistics has been the subject of international research since the 1970s. Historically these models have been based on multivariate statistical models that relate flow statistics to the physical and climatic characteristics of a catchment. The a priori classification of catchments has often been a component of this analysis. This paper discusses the background to the development of such models, with particular emphasis on the United Kingdom; it describes a new region of influence approach to estimating flow duration statistics and compares the performance of this method with current multivariate regression based methods for estimating flow duration statistics within the United Kingdom.

Direct underwater observation of micro-habitat use by 1838 young Atlantic salmon Salmo salar [mean L T 7·9 3·1(..) cm, range 3-19] and 1227 brown trout Salmo trutta (L T 10·9 5·0 cm, range 3-56) showed both species were selective in habitat use, with differences between species and fish size. Atlantic salmon and brown trout selected relatively narrow ranges for the two micro-habitat variables snout water velocity and height above bottom, but with differences between size-classes. The smaller fishes <7 cm held positions in slower water closer to the bottom. On a larger scale, the Atlantic salmon more often used shallower stream areas, compared with brown trout. The larger parr preferred the deeper stream areas. Atlantic salmon used higher and slightly more variable mean water velocities than brown trout. Substrata used by the two species were similar. Finer substrata, although variable, were selected at the snout position, and differences were pronounced between size-classes. On a meso-habitat scale, brown trout were more frequently observed in slow pool-glide habitats, while young Atlantic salmon favoured the faster high-gradient meso-habitats. Small juveniles <7 cm of both species were observed most frequently in riffle-chute habitats. Atlantic salmon and brown trout segregated with respect to use of habitat, but considerable niche overlap between species indicated competitive interactions. In particular, for small fishes <7 cm of the two species, there was almost complete niche overlap for use of water depth, while they segregated with respect to water velocity. Habitat suitability indices developed for both species for mean water velocity and water depth, tended to have their optimum at lower values compared with previous studies in larger streams, with Atlantic salmon parr in the small streams occupying the same habitat as favoured by brown trout in larger streams. The data indicate both species may be flexible in their habitat selection depending on habitat availability. Species-specific habitat overlap between streams may be complete. However, between-species habitat partitioning remains similar. 2002 The Fisheries Society of the British Isles

Information on the magnitude and variability of flow regimes at the river reach scale is a central component of most aspects of water resource and water quality management. However, many decisions are made within catchments for which there are no measured flow data. To meet this challenge, a suite of modelling techniques to assist in the estimation of natural and artificially influenced river-flows at ungauged sites has been developed. This paper summarises these models and how they are incorporated within the GIS framework of the Low Flows 2000 software package. The paper will also describe the implementation of Low Flows 2000 within England and Wales by the Environment Agency, and the use of the system in supporting the implementation of the Environment Agency's Catchment Abstraction Management Strategy. This strategy is focused on the delivery of sustainable abstraction licensing and will contribute to the implementation of the Water Framework Directive within England and Wales.

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Traditionally, the estimation of Mean Flow (MF) in ungauged catchments has been approached using conceptual water balance models or empirical formulae relating climatic inputs to stream flow. In the UK, these types of models have difficulty in predicting MF in low rainfall areas because the conceptualisation of soil moisture behaviour and its relationship with evaporation rates used is rather simplistic. However, it is in these dry regions where the accurate estimation of flows is most critical to effective management of a scarce resource. A novel approach to estimating MF, specifically designed to improve estimation of runoff in dry catchments, has been developed using a regionalisation of the Penman drying curve theory. The dynamic water balance style Daily Soil Moisture Accounting (DSMA) model operates at a daily time step, using inputs of precipitation and potential evaporation and simulates the development of soil moisture deficits explicitly. The model has been calibrated using measured MFs from a large data set of catchments in the United Kingdom. The performance of the DSMA model is superior to existing established steady state and dynamic water-balance models over the entire data set considered and the largest improvement is observed in very low rainfall catchments. It is concluded that the performance of all models in high rainfall areas is likely to be limited by the spatial representation of rainfall.