Characterizing, understanding and better estimating uncertainties are key concerns for drawing robust conclusions when analyzing changing socio-hydrological systems. Here we suggest developing a perceptual model of uncertainty that is complementary to the perceptual model of the socio-hydrological system and we provide an example application to flood risk change analysis. Such a perceptual model aims to make all relevant uncertainty sources – and different perceptions thereof – explicit in a structured way. It is a first step to assessing uncertainty in system outcomes that can help to prioritize research efforts and to structure dialogue and communication about uncertainty in interdisciplinary work.
Ertsen discusses the representation of reality and uncertainty in our paper, raising three critical points. In response to the first, we agree that discussion of different interpretations of the concept of uncertainty is important when developing perceptual models – making different uncertainty interpretations explicit was a key motivation behind our method. Secondly, we do not, as Ertsen suggests, deny anyone who is not a “certified” scientist to have relevant knowledge. The elicitation of diverse views by discussing perceptual models is a basis for open discussion and decision making. Thirdly, Ertsen suggests that it is not useful to treat socio-hydrological systems as if they exist. We argue that we act as “pragmatic realists” in most practical applications by treating socio-hydrological systems as an external reality that can be known. But the uncertainty that arises from our knowledge limitations needs to be recognized, as it may impact on practical decision making and associated costs.
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.
Discharge data used to calibrate and evaluate hydrological models can be highly uncertain and this uncertainty affects the conclusions that we can draw from modelling results. We investigated the role of discharge data uncertainty and its representation in hydrological model calibration to give recommendations on methods to account for data uncertainty. We tested five different representations of discharge data uncertainty in calibrating the HBV-model for three Swiss catchments, ranging from using no information to using full empirical probability distributions for each time step. We developed a new objective function to include discharge data uncertainty, as quantified by these distributions directly in calibration to hydrological time series. This new objective function provided more reliable results than using no data uncertainty or multiple realizations of discharge time series. We recommend using the new objective function in combination with empirical or triangular distributions of the discharge data uncertainty.