Hydrological Information Referral Service Infohydro

The publication intends to demonstrate and illustrate important steps and lessons learned to take into account when developing a climate change adaptation strategy for water management in the basin or transboundary context. It aims to compile, analyse, publish and disseminate lessons learned and good practices on water and adaptation to climate change in transboundary basins. It includes lessons learnt and good practices from the programme of pilot projects under the UNECE Convention on the Protection and Use of Tranbsboundary Watercourses and International Lakes implemented since 2010 in cooperation with partner organizations such as OSCE and UNDP in the framework of the Environment and Security Initiative. It also includes lessons and examples from numerous other organizations working on water and climate change in transboundary basins, such as the International Union for Conservation of Nature (IUCN), the Global Water Partnership and many others.

The debate on how mankind should respond to climate change is diverse, as the appropriate strategy depends on global as well as local circumstances. As scientists are denied the possibility of conducting experiments with the real climate, only climate models can give insights into man-induced climate change, by experimenting with digital climates under varying conditions and by extrapolating past and future states into the future. But the ‘nature’ of models is a purely representational one. A model is good if it is believed to represent the relevant processes of a natural system well. However, a model and its results, in particular in the case of climate models which interconnect countless hypotheses, is only to some extent testable, although an advanced infrastructure of evaluation strategies has been developed involving strategies of model intercomparison, ensemble prognoses, uncertainty metrics on the system and component levels. The complexity of climate models goes hand in hand with uncertainties, but uncertainty is in conflict with socio-political expectations. However, certain predictions belong to the realm of desires and ideals rather than to applied science. Today’s attempt to define and classify uncertainty in terms of likelihood and confidence reflect this awareness of uncertainty as an integral part of human knowledge, in particular on knowledge about possible future developments. The contributions in this book give a first hand insight into scientific strategies in dealing with uncertainty by using simulation models and into social, political and economical requirements in future projections on climate change. Do these strategies and requirements meet each other or fail? The debate on how mankind should respond to climate change is diverse, as the appropriate strategy depends on global as well as local circumstances. As scientists are denied the possibility of conducting experiments with the real climate, only climate models can give insights into man-induced climate change, by experimenting with digital climates under varying conditions and by extrapolating past and future states into the future. But the 'nature' of models is a purely representational one. A model is good if it is believed to represent the relevant processes of a natural system well. However, a model and its results, in particular in the case of climate models which interconnect countless hypotheses, is only to some extent testable, although an advanced infrastructure of evaluation strategies has been developed involving strategies of model intercomparison, ensemble prognoses, uncertainty metrics on the system and component levels. The complexity of climate models goes hand in hand with uncertainties, but uncertainty is in conflict with socio-political expectations. However, certain predictions belong to the realm of desires and ideals rather than to applied science. Today's attempt to define and classify uncertainty in terms of likelihood and confidence reflect this awareness of uncertainty as an integral part of human knowledge, in particular on knowledge about possible future developments. The contributions in this book give a first hand insight into scientific strategies in dealing with uncertainty by using simulation models and into social, political and economical requirements in future projections on climate change. Do these strategies and requirements meet each other or fail? Gabriele Gramelsberger is Principal Investigator of the Collaborative Research Project is Principal Investigator of the Collaborative Research Project

The purpose of this Sourcebook is to provide advice on how to incorporate disaster risk reduction and resilience building into the watershed management process. As an increasingly heavier toll is exerted on agriculture and food systems by drought, floods, wildfires, and other extreme events, adopting risk reduction and management practices must become an integral part of watershed management. While the steps involved to incorporate resilience building are similar to those routinely carried out in integrated watershed management, this Sourcebook stresses the importance of understanding disaster and climate risks, adopting a landscape approach and targeting vulnerable groups (e.g. women, youth, indigenous people, others) at all stages of planning and implementing watershed management.