The ecological impact of changes in river flow may be explored through the simulation of ecologically relevant flow indicators. Traditional approaches to model parameterization are not well-suited for this. To this end, this paper considers the ability of a modified covariance approach, applied to five hydrologically diverse catchments. An overall improvement in consistency is observed, whilst timing and rate of change represent the best and worst replicated indicators respectively.

Floods and droughts cause significant damages and pose risks to lives worldwide. In a climate change context this work identifies hotspots across Great Britain, i.e. places expected to be impacted by an increase in floods and droughts. By the 2080s the western coast of England and Wales and northeastern Scotland would experience more floods in winter and droughts in autumn, with a higher increase in drought hazard, showing a need to adapt water management policies in light of climate change.

We assessed the effects of different modes of operating reservoir on its ability to moderate water shortage impacts caused by climate change. The operating rule approach was enhanced by hedging using multiple zones and monthly rationing ratios for curtailment of water release. The results showed that basic hedging with single zone and constant rationing ratio caused significant reduction in water shortage during severe droughts. More complex operation modes produced only modest improvement.

This paper investigated the long-term trends in precipitation from 16 stations located in the lower Shire catchment in Malawi over the period 1953–2010. The results indicate that annual precipitation has increased, whereas, monthly precipitation revealed an upward trend in wet seasons (November to April) and a downward trend in dry seasons (May to October). The monthly peak trend analysis has shown upward trend in rainy months at all stations.

In this study, multi-layer perceptron (MLP) artificial neural networks have been applied to forecast one-month-ahead inflow for the Ubonratana reservoir, Thailand. This is necessary because without knowing the expected inflow, one would not know the amount of water to allocate at the start of each month. As expected, knowing the inflow through our forecasts significantly improved the performance of the Ubonratana reservoir, the test case. We expect the study to have utility for other systems.