Modelling the ecological aspects of bankside reservoirs and implications for management

Bankside storage reservoirs are used as a major water supply resource in th e lower Thames Valley, England. They form the link between the River Thames and the water treatment works of the Greater London area. The reservoirs a ct as both a water reserve in times of low river flows, and a quality 'buff er' between the river and the treatment works. The load on the water treatm ent works (particulate material, physico-chemical characteristics) primaril y reflects the water qualities of the reservoirs. Management of such reserv oirs thus seeks to reduce the adverse impacts which would otherwise arise f rom direct river use, and to ensure as far as possible that the ecological processes within the reservoirs do not introduce new challenges to the wate r treatment. Reservoir management clearly needs a good understanding of tho se ecological processes and their interactions, and, hopefully, a means to exploit that understanding in hindcasting to explain past events, in foreca sting near- or far-future events, and to help in exploring operational opti ons to ameliorate any foreseable difficulties. The reservoirs consist of a variety of configurations, physical dimensions and operational circumstance s. They have, importantly, basically simple morphologies, known hydraulic r egimes and physico-chemical qualities. Nonetheless, they appear to behave e ssentially as small (1-50 Mm(3)), eutrophic lakes; and various aspects of t heir ecology has been studied for the past 65 years. Their attributes and o perational involvement make them ideal candidates for ecological modelling, which has been applied to them in varying extents for the past 30 years. T he major conclusion which may be drawn from these studies is that even in s uch relatively simple water bodies, current (and probably future) models ca n only encompass their broad ecological characteristics. Detailed operation al needs have to be met by a variety of modelling approaches, mainly predic ated on the basis of only being able to know a lot about a little or a litt le about a lot. The operational needs for modelling fall into the following broad types: (a) understanding: why did those events occur, or where is ou r ignorance greatest? (b) short-term forecasts: how will the current situat ion develop in the short-term (weeks)? (c) what-if considerations: what wou ld happen if some management facility were employed or used differently? (d ) optimisation: what are the optimal volume- quality supply arrangements? ( e) long-term prediction: what is the longer-term (years) outlook under fore seeable scenarios? (f) projective evaluation: how would potential, as yet n on-existant reservoirs behave under prescribed circumstances? Examples of h ow these needs have been met are outlined, with examples ranging from simpl e models of the diatom ecology of the reservoirs to much broader trophic-dy namic descriptions which can allow expression of fish-zooplankton-phytoplan kton interactions. This is crucial for present and future management of cya nobacterial phases. It is clear that considerable management insight and co ntrol can result from modelling assistance, but only if the appropriate que stions are asked. Whilst simple short-term modelling is less demanding, any attempt to model the full complexity of the ecology of even these relative ly simple water-bodies is probably doomed to founder on complexity-understa nding difficulties, unless these are resolved to much more constrained syst em aspects. This is particularly so for the qualitative biology. The best that may presently be foreseen is for development of the newer mul ti-biological type models, with reasonably realistic and dynamic physical a nd chemical environment sub-models, being able to manifest the general char acteristics of the ecosystem in question. Despite such difficulties, new re servoir management insights and approaches will inevitably be founded on cr itical modelling of those ecosystems.