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Summer field observations in five 2nd order streams (width 1–2 m, depth 5–15 cm, velocity 5–10 cm s–1) in Western Australia and south-east Queensland showed that daily maximum temperatures changed by ±4°C over distances of 600–960 m (travel time 2–3 h) immediately downstream from 40–70% step changes in riparian shade. There was a strong linear relationship between the rate of change of daily maximum temperature and the change of shade such that downstream from a 100% change of shade the heating/cooling rates are ±4°C h–1 and ±10°C km–1 (upper bound ±6°C h–1 and ±15°C km–1) respectively. These high rates only apply over short distances and travel times because downstream water temperatures adjust to the new level of shade and reach a dynamic equilibrium. Shade was too patchy in the study streams to measure how long water takes to reach equilibrium, however, using an existing computer model, we estimate that this occurs after ~1200 m (travel time 4 h). Further modelling work is desirable to predict equilibrium temperatures under given meteorological, flow and shade conditions. Nevertheless, landowners and regulators can use this information to determine whether the presence/absence of certain lengths of bankside shade are likely to cause desirable/undesirable temperature decreases/increases.

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A computer model for epilithic algae and grazer biomass in streams is modified to better predict the effects of temperature and is calibrated for diatoms and mayflies. Mayflies are predicted to maintain low diatom biomass provided that (1) temperatures remain within their preferred range (10-20ЊC); and (2) mayfly populations are not adversely affected by floods. Algal blooms are predicted to occur in mayfly-dominated streams above 20ЊC-temperatures common in pasture streams over summer. We hypothesize that mobile bed streams are susceptible to blooms during summer low flows following floods because (1) they usually lack temperature tolerant snail grazers; and (2) mayfly recovery lags behind algal regrowth, and there is a short period when algae escape from ''top-down'' grazer control.

Streamflow data are used for important environmental and economic decisions, such as specifying and regulating minimum flows, managing water supplies, and planning for flood hazards. Despite significant uncertainty in most flow data, the flow series for these applications are often communicated and used without uncertainty information. In this commentary, we argue that proper analysis of uncertainty in river flow data can reduce costs and promote robust conclusions in water management applications. We substantiate our argument by providing case studies from Norway and New Zealand where streamflow uncertainty analysis has uncovered economic costs in the hydropower industry, improved public acceptance of a controversial water management policy, and tested the accuracy of water quality trends. We discuss the need for practical uncertainty assessment tools that generate multiple flow series realizations rather than simple error bounds. Although examples of such tools are in development, considerable barriers for uncertainty analysis and communication still exist for practitioners, and future research must aim to provide easier access and usability of uncertainty estimates. We conclude that flow uncertainty analysis is critical for good water management decisions.