Suchergebnisse

Abstract. Scholars have unravelled the complexities and underlying uncertainties in coupled human and water systems in various fields and disciplines. These complexities, however, are not always reflected in the way in which the dynamics of human–water systems are modelled. One reason is the lack of social data time series, which may be provided by longitudinal surveys. Here, we show the value of collecting longitudinal survey data to enrich sociohydrological modelling of flood risk. To illustrate, we compare and contrast two different approaches (repeated cross-sectional and panel) for collecting longitudinal data and explore changes in flood risk awareness and preparedness in a municipality hit by a flash flood in 2018. We found that risk awareness has not changed significantly in the timeframe under study (1 year). Perceived preparedness increased only among those respondents who suffered low damage during the flood event. We also found gender differences across both approaches for most of the variables explored. Lastly, we argue that results that are consistent across the two approaches can be used for the parametrisation of sociohydrological models. We posit that there is a need to enhance the representation of socio-demographic heterogeneity in modelling human–water systems in order to better support risk management.

Abstract. Private risk reduction behaviours can significantly reduce the
negative impacts of flooding and flash floods. Over the past decades,
researchers have used various socio-cognitive models or threat and coping
mechanisms to explain individual protective behaviours. However, these
models ignore the fact that people are not equally ready to act upon a danger, and
they (the models) give limited insights into the effectiveness of communication
strategies to foster risk reduction behaviours. Therefore, we explored the
current state of homeowners' readiness to undertake risk reduction
behaviours in flood risk areas by applying a dynamic protection motivation
framework. We conducted a survey in an Italian municipality that experienced
severe flash flooding in September 2018. The results show that people are
motivated by different factors in prompting risk reduction behaviour based
on their chosen types of protective measures. For example, people that undertook
structural or avoidance measures are more likely to be motivated to protect
themselves by increased perceptions of vulnerability and response efficacy
and are less worried about expected flood losses compared to people that
undertook only basic emergency measures. In this paper, we argue how these
new insights contribute to targeting flood risk communication strategies to
groups of individuals characterized by different readiness stages and
motivations to protect themselves.

Abstract. Rainfall-induced debris flows in recently burned mountainous areas cause
significant economic losses and human casualties. Currently, prediction of
post-fire debris flows is widely based on the use of power-law thresholds and
logistic regression models. While these procedures have served with certain
success in existing operational warning systems, in this study we investigate
the potential to improve the efficiency of current predictive models with
machine-learning approaches. Specifically, the performance of a predictive
model based on the random forest algorithm is compared with current techniques
for the prediction of post-fire debris flow occurrence in the western United
States. The analysis is based on a database of post-fire debris flows
recently published by the United States Geological Survey. Results show that
predictive models based on random forest exhibit systematic and considerably
improved performance with respect to the other models examined. In addition,
the random-forest-based models demonstrated improvement in performance with
increasing training sample size, indicating a clear advantage regarding their
ability to successfully assimilate new information. Complexity, in terms of
variables required for developing the predictive models, is deemed important but
the choice of model used is shown to have a greater impact on the overall
performance.

We explore how to address the challenges of adaptation of water resources systems under changing conditions by supporting flexible, resilient and low-regret solutions, coupled with on-going monitoring and evaluation. This will require improved understanding of the linkages between biophysical and social aspects in order to better anticipate the possible future co-evolution of water systems and society. We also present a call to enhance the dialogue and foster the actions of governments, the international scientific community, research funding agencies and additional stakeholders in order to develop effective solutions to support water resources systems adaptation. Finally, we call the scientific community to a renewed and unified effort to deliver an innovative message to stakeholders. Water science is essential to resolve the water crisis, but the effectiveness of solutions depends, inter alia, on the capability of scientists to deliver a new, coherent and technical vision for the future development of water systems.

We explore how to address the challenges of adaptation of water resources systems under changing conditions by supporting flexible, resilient and low-regret solutions, coupled with on-going monitoring and evaluation. This will require improved understanding of the linkages between biophysical and social aspects in order to better anticipate the possible future co-evolution of water systems and society. We also present a call to enhance the dialogue and foster the actions of governments, the international scientific community, research funding agencies and additional stakeholders in order to develop effective solutions to support water resources systems adaptation. Finally, we call the scientific community to a renewed and unified effort to deliver an innovative message to stakeholders. Water science is essential to resolve the water crisis, but the effectiveness of solutions depends, inter alia, on the capability of scientists to deliver a new, coherent and technical vision for the future development of water systems.