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Semi-arid river basins often rely on reservoirs for water supply. Small reservoirs may impact on large-scale water availability both by enhancing availability in a distributed sense and by subtracting water for large downstream user communities, e.g. served by large reservoirs. Both of these impacts of small reservoirs are subject to climate change. Using a case-study on North-East Brazil, this paper shows that climate change impacts on water availability may be severe, and impacts on distributed water availability from small reservoirs may exceed impacts on centralised water availability from large reservoirs. Next, the paper shows that the effect of small reservoirs on water availability from large reservoirs may be significant, and increase both in relative and absolute sense under unfavourable climate change.

This paper considers aspects of environmental social science research in the UK and explores an obvious bias towards the development of instruments to manage demand as an adaptation to climate change, and consequently the predominance of interest in the customer from a demand-side perspective. In the case of water, this has resulted in an inappropriate mixing of individualist research methods designed to measure public perceptions of risk and water-based practices, with mass consumption data that cannot be specifically linked to the individual. This mixing has a tendency to reinforce a long-standing blame culture that drives interest in the development of behaviour change initiatives while the relatively unchallenged hydraulic mission to provide safe drinking water and sanitation progresses. With this in mind this paper reviews examples of water use research from California, Australia, and the UK and highlights the more effective routes to understanding water customers and developing behaviour change initiatives that utilise stages of change models and grounded techniques incorporating qualitative and quantitative data from individual sources. A secondary aim is to argue for re-framing the relations between various actors in a changing climate to allow the development of new policy approaches, learning, and openness, from industry, regulators, and customers, based on new theories from the field.

Socio-economic change, severe droughts, and environmental concerns focus attention on sustainability of water supplies and the ability of water utilities to meet levels of service. Traditionally, water management has been supply-side dominated and long-term demand forecasting has received relatively little attention. However, it is increasingly recognised that water demand management could be a ‘low regret’ adaptation measure (both financially and environmentally) given large uncertainties about future non-climate and climate pressures. This paper begins with a brief history of household water demand management in the UK. We then review approaches to water demand estimation and forecasting over the short- (daily to season) and long-term (years to decade) and note the paucity of studies on weather and climate. We discuss peak household water use behaviours identified from metering trials, micro-component diary-based studies, and statistical techniques for long-term demand forecasting. We refer to the Anglian Water Services (AWS) ‘Golden 100’ data to illustrate the significant practical and conceptual issues faced when mining household water use data for weather signals, especially when the data are noisy and originally intended for other applications. Further research is needed into the relationships between climate variables and household micro-component water use, especially for peak demands.

Climate change studies for West Africa tend to predict a reduced potential for farming that will affect the food security situation of an already impoverished population. However, these studies largely ignore farmers' adaptations and market adjustments that mitigate predicted negative effects. The paper attempts to fill some of this gap through a spatially explicit evaluation of the impact of climate change on farm income in the Oueme River Basin (ORB), Benin. The ORB is in many respects representative for the middle belt of West Africa where the predominantly sparse occupation leaves potential for migration from more densely populated areas. We apply a number of structural, spatially explicit relationships estimated for the whole territory of Benin to simulate conditions in the ORB proper that are similar to those currently prevailing in the drier North, and the more humid South. Our scenario results factor out for the main crops cultivated the constituent effects on yields, area, and revenue per ton. We find that under average climate change conditions the current low yields are not reduced, provided that cropping patterns are adjusted, while price increases partly compensate for the remaining adverse effects on farmer income. Consequently, without any policy intervention, farm incomes remain relatively stable, albeit at low levels and with increased occurrence of crop failures after extreme droughts. Scenario simulations show that there are also beneficial aspects that can, with adequate interventions, even turn losses into gains. Main channel for improvement would be the reduction of fallow, which is particularly promising because it requires few adjustments in prevailing farming practices, exploits the potential of uncultivated land and improves the water use efficiency. It also enables the Basin's capacity to absorb future migrant flows from more severely affected neighboring Sahelian areas. © 2011 The Author(s).

Water scarcity threatens economic growth, social cohesion, and environmental sustainability in many deltas. This situation is likely to worsen due to future climate change. To reduce water scarcity and limit salt water intrusion in deltas, many countries have launched policies to allocate water resources. However, it is difficult to develop long-term adaptive water management policies due to large uncertainties. In this paper, we present a Robust Assessment Model for Water Allocation (RAMWA) to support decision making about water release of different key reservoirs under future climate change. The model was applied in the Pearl River basin, China to improve reservoir management, to ensure sufficient flow into the delta to reduce salt intrusion, and to provide sufficient freshwater for human and industrial consumption. Results show that performance of the existing water allocation plans reduces under climate change, as the plans are unable to sustain the required minimum river discharge. However alternatives generated by a Generic Evolutionary Algorithm (GEA) suggest that new plans can be developed which ensure minimum flows into the delta under most future climate change scenarios. The GEA plans perform better than existing plans because rather than following a fixed allocation schedule, the optimal water release for each reservoir is recalculated every 10 days based on observed discharge and storage in key reservoirs.