Abstract. Over history, humankind has tended to settle near streams because of the role of rivers as transportation corridors and the fertility of riparian areas. However, human settlements in floodplains have been threatened by the risk of flooding. Possible responses have been to resettle away and/or modify the river system by building flood control structures. This has led to a complex web of interactions and feedback mechanisms between hydrological and social processes in settled floodplains. This paper is an attempt to conceptualise these interplays for hypothetical human-flood systems. We develop a simple, dynamic model to represent the interactions and feedback loops between hydrological and social processes. The model is then used to explore the dynamics of the human-flood system and the effect of changing individual characteristics, including external forcing such as technological development. The results show that the conceptual model is able to reproduce reciprocal effects between floods and people as well as the emergence of typical patterns. For instance, when levees are built or raised to protect floodplain areas, their presence not only reduces the frequency of flooding, but also exacerbates high water levels. Then, because of this exacerbation, higher flood protection levels are required by society. As a result, more and more flooding events are avoided, but rare and catastrophic events take place.
Abstract. The objective of this assessment is to compare studies predicting runoff hydrographs in ungauged catchments. The aim is to learn from the differences and similarities between catchments in different locations, and to interpret the differences in performance in terms of the underlying climate and landscape controls. The assessment is performed at two levels. The Level 1 assessment is a metaanalysis of 34 studies reported in the literature involving 3874 catchments. The Level 2 assessment consists of a more focused and detailed analysis of individual basins from selected studies from Level 1 in terms of how the leave-one-out cross-validation performance depends on climate and catchment characteristics as well as on the chosen regionalisation method. The results indicate that runoff-hydrograph predictions in ungauged catchments tend to be more accurate in humid than in arid catchments and more accurate in large than in small catchments. The dependence of performance on elevation differs by regions and depends on how aridity varies with elevation and air temperature. The effect of the parameter regionalisation method on model performance differs between studies. However, there is a tendency towards a somewhat lower performance of regressions than other methods in those studies that apply different methods in the same region. In humid catchments spatial proximity and similarity methods perform best while in arid catchments similarity and parameter regression methods perform slightly better. For studies with a large number of catchments (dense stream gauge network) there is a tendency for spatial proximity and geostatistics to perform better than regression or regionalisation based on simple averaging of model parameters from gauged catchments. There was no clear relationship between predictive performance and the number of regionalised model parameters. The implications of the findings are discussed in the context of model building.
Abstract. There is growing concern that flooding is becoming more frequent and severe in Europe. A better understanding of flood regime changes and their drivers is therefore needed. The paper reviews the current knowledge on flood regime changes in European rivers that has been obtained through two approaches. The first approach is the detection of change based on observed flood events. Current methods are reviewed together with their challenges and opportunities. For example, observation biases, the merging of different data sources and accounting for non-linear drivers and responses. The second approach consists of modelled scenarios of future floods. Challenges and opportunities are discussed again such as fully accounting for uncertainties in the modelling cascade and feedbacks. To make progress in flood change research, we suggest that a synthesis of these two approaches is needed. This can be achieved by focusing on flood-rich and flood-poor periods rather than on flood trends only, by formally attributing causes of observed flood changes, by validating scenarios against observed flood regime dynamics, and by developing low-dimensional models of flood changes and feedbacks. The paper finishes with a call for a joint European flood change research network.
Abstract. The objective of this paper is to assess the performance of methods that predict low flows and flood runoff in ungauged catchments. The aim is to learn from the similarities and differences between catchments in different places, and to interpret the differences in performance in terms of the underlying climate-landscape controls. The assessment is performed at two levels. The Level 1 assessment is a metaanalysis of 14 low flow prediction studies reported in the literature involving 3112 catchments, and 20 flood prediction studies involving 3023 catchments. The Level 2 assessment consists of a more focused and detailed analysis of individual basins from selected studies from Level 1 in terms of how the leave-one-out cross-validation performance depends on climate and catchment characteristics as well as on the regionalisation method. The results indicate that both flood and low flow predictions in ungauged catchments tend to be less accurate in arid than in humid climates and more accurate in large than in small catchments. There is also a tendency towards a somewhat lower performance of regressions than other methods in those studies that apply different methods in the same region, while geostatistical methods tend to perform better than other methods. Of the various flood regionalisation approaches, index methods show significantly lower performance in arid catchments than regression methods or geostatistical methods. For low flow regionalisation, regional regressions are generally better than global regressions.
The objective of this assessment is to compare studies predicting runoff hydrographs in ungauged catchments. The aim is to learn from the differences and similarities between catchments in different locations, and to interpret the differences in performance in terms of the underlying climate and landscape controls. The assessment is performed at two levels. The Level 1 assessment is a meta-analysis of 34 studies reported in the literature involving 3874 catchments. The Level 2 assessment consists of a more focused and detailed analysis of individual basins from selected studies from Level 1 in terms of how the leave-one-out cross-validation performance depends on climate and catchment characteristics as well as on the chosen regionalisation method. The results indicate that runoff hydrograph predictions in ungauged catchments tend to be more accurate in humid than in arid catchments and more accurate in large than in small catchments. The dependence of performance on elevation differs by regions and depends on how aridity varies with elevation and air temperature. The effect of parameter regionalisation method on model performance differs between studies. However, there is a tendency towards a somewhat lower performance of regressions than other methods in those studies that apply different methods in the same region. In humid catchments spatial proximity and similarity methods perform best while in arid catchments similarity and parameter regression methods perform slightly better. For studies with a large number of catchments (dense stream gauge network) there is a tendency for spatial proximity and geostatistics to perform better than regression or regionalisation based on simple averaging of model parameters from gauged catchments. There was no clear relationship between predictive performance and the number of regionalised model parameters. The implications of the findings are discussed in the context of model building
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