Editors of several journals in the field of hydrology met during the General Assembly of the European Geosciences Union—EGU in Vienna in April 2017. This event was a follow-up of similar meetings held in 2013 and 2015. These meetings enable the group of editors to review the current status of the journals and the publication process, and to share thoughts on future strategies. Journals were represented at the 2017 meeting by their editors, as shown in the list of authors. The main points on invigorating hydrological research through journal publications are communicated in this joint editorial published in the above journals.@en

Precipitation (P) and potential evaporation (E_p) are commonly studied drivers of changing freshwater availability, as aridity (E_p/P) explains ∼90% of the spatial differences in mean runoff across the globe. However, it is unclear if changes in aridity over time are also the most important cause for temporal changes in mean runoff and how this degree of importance varies regionally. We show that previous global assessments that address these questions do not properly account for changes due to precipitation, and thereby strongly underestimate the effects of precipitation on runoff. To resolve this shortcoming, we provide an improved Budyko-based global assessment of the relative and absolute sensitivity of precipitation, potential evaporation, and other factors to changes in mean-annual runoff. The absolute elasticity of runoff to potential evaporation changes is always lower than the elasticity to precipitation changes. The global pattern indicates that for 83% of the land grid cells runoff is most sensitive to precipitation changes, while other factors dominate for the remaining 17%. This dominant role of precipitation contradicts previous global assessments, which considered the impacts of aridity changes as a ratio. We highlight that dryland regions generally display high absolute sensitivities of runoff to changes in precipitation, however within dryland regions the relative sensitivity of runoff to changes in other factors (e.g., changing climatic variability, CO₂-vegetation feedbacks, and anthropogenic modifications to the landscape) is often far higher. Nonetheless, at the global scale, surface water resources are most sensitive to temporal changes in precipitation.

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Precipitation (P) and potential evaporation (Ep) are commonly studied drivers of changing freshwater availability, as aridity (Ep/P) explains ∼90% of the spatial differences in mean runoff across the globe. However, it is unclear if changes in aridity over time are also the most important cause for temporal changes in mean runoff and how this varies across regions. Here, we resolve shortcomings of previous Budyko-based global assessments on the relative role of aridity for changes in water availability. We argue that previous assessments do not properly account for precipitation effects. To resolve this issue, the effects of changes in Ep and P need to be considered separately. We present a new global assessment of the elasticity of runoff to changes in precipitation, potential evaporation, and other factors. The global pattern suggests that for 83% of the land surface runoff is most sensitive to precipitation changes, while other factors dominate for the remaining 17%. Runoff elasticity to changes in potential evaporation is always lower than elasticity to precipitation, and in many arid regions this difference can reach an order of magnitude. Although surface water resources in dryland regions are highly sensitive to precipitation changes, their sensitivity to changes in other factors (e.g. changing climatic variability, CO2 – vegetation feedbacks and anthropogenic modifications to the landscape) is often far higher. Nonetheless, at the global scale we find precipitation changes have the greatest impact on water availability, which contrasts markedly with recent assessments.@en

River flooding can have severe societal, economic and environmental consequences. However, limited understanding of the regional differences in flood-generating mechanisms results in poorly understood historical flood trends and uncertain predictions of future flood conditions. To address this issue, we use a simple observation-based approach to decipher the dominant drivers of floods across large geographic regions. The generated process knowledge provides helpful context of the mechanisms that are of main interest when studying the (non)stationarity of flood response. Such assessments of floods trends across large regions always focus on frequently occurring events (e.g. annual peaks), whereas changes in very extreme but rare floods are only studied for a small number of locations that have exceptionally long observational records. Understanding changes in these extreme and rare floods is especially relevant as these events are often most damaging. Utilizing aggregate regional flood information, we show that during recent decades there is a strong decadal variability and an overall increase in both the frequency and magnitude of extreme floods across multiple continents. This observation-based assessment of extreme floods is broadly consistent with model predictions, but also highlights strong decadal variability. Because we mapped regional differences in flood generating mechanisms of more commonly occurring floods, there remains a need to identify the regional and hemispheric drivers that control changes in extreme floods.@en

Analyses of trends in observed floods often focus on relatively frequent events, whereas changes in rare floods are only studied for a small number of locations that have exceptionally long observational records. Understanding changes in rare floods is especially relevant as these events are often most damaging and influence the design of major structures. Here we provide an assessment of changes in the largest flood events (∼0.033 annual exceedance probability) observed during the period 1980-2009 for 1744 catchments located in Australia, Brazil, Europe and the United States. The occurrence of rare floods in spatial aggregate shows strong decadal variability and peaked around 1995. During the 30-year period there are overall increases in both the frequency and magnitude of extreme floods. These currently unattributed increases are strongest in Europe and the United States, and weakest in Brazil
and Australia.@en

In this synthesis paper addressing hydrologic scaling and similarity, we posit that roadblocks in the search for universal laws of hydrology are hindered by our focus on computational simulation (the third paradigm) and assert that it is time for hydrology to embrace a fourth paradigm of data-intensive science. Advances in information-based hydrologic science, coupled with an explosion of hydrologic data and advances in parameter estimation and modeling, have laid the foundation for a data-driven framework for scrutinizing hydrological scaling and similarity hypotheses. We summarize important scaling and similarity concepts (hypotheses) that require testing; describe a mutual information framework for testing these hypotheses; describe boundary condition, state, flux, and parameter data requirements across scales to support testing these hypotheses; and discuss some challenges to overcome while pursuing the fourth hydrological paradigm. We call upon the hydrologic sciences community to develop a focused effort towards adopting the fourth paradigm and apply this to outstanding challenges in scaling and similarity.

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The diversity in hydrologic models has historically led to great controversy on the "correct" approach to process-based hydrologic modeling, with debates centered on the adequacy of process parameterizations, data limitations and uncertainty, and computational constraints on model analysis. In this paper, we revisit key modeling challenges on requirements to (1) define suitable model equations, (2) define adequate model parameters, and (3) cope with limitations in computing power. We outline the historical modeling challenges, provide examples of modeling advances that address these challenges, and define outstanding research needs. We illustrate how modeling advances have been made by groups using models of different type and complexity, and we argue for the need to more effectively use our diversity of modeling approaches in order to advance our collective quest for physically realistic hydrologic models.

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