Highlight articles

The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500

This study provides the future greenhouse gas (GHG) concentrations under the new set of so-called SSP scenarios (the successors of the IPCC SRES and previous representative concentration pathway (RCP) scenarios). The projected CO ₂ concentrations range from 350 ppm for low-emission scenarios by 2150 to more than 2000 ppm under the high-emission scenarios. We also provide concentrations, latitudinal gradients, and seasonality for most of the other 42 considered GHGs.

Revisiting the global hydrological cycle: is it intensifying?

We overview and retrieve a great amount of global hydroclimatic data sets. We improve the quantification of the global hydrological cycle, its variability and its uncertainties through the surge of newly available data sets. We test (but do not confirm) established climatological hypotheses, according to which the hydrological cycle should be intensifying due to global warming. We outline a stochastic view of hydroclimate, which provides a reliable means of dealing with its variability.

Survival of the Qaidam mega-lake system under mid-Pliocene climates and itsrestoration under future climates

During the Pliocene, the Qaidam Basin on the Tibetan Plateau contained a mega-lake system. During the Pleistocene, it disappeared almost completely. Today, hyperarid climates prevail in the low-altitude parts of the basin. This study reveals that today’s mean water balance of the Qaidam Basin is nearly zero and is positive during warmer, less dry years. The results explain how the mega-lake system could survive for a long time in the past and could eventually be restored in the future.

Why does a conceptual hydrological model fail to correctly predict discharge changes in response to climate change?

We investigate why a conceptual hydrological model failed to correctly predict observed discharge changes in response to increasing precipitation and air temperature in 156 Austrian catchments. Simulations indicate that poor model performance is related to two problems, namely a model structure that neglects changes in vegetation dynamics and inhomogeneities in precipitation data caused by changes in stations density with time. Other hypotheses did not improve simulated discharge changes.

Towards an objective assessment of climate multi-model ensembles – a casestudy: the Senegalo-Mauritanian upwelling region

The most robust representation of climate is usually obtained by averaging a large number of simulations, thereby cancelling individual model errors. Here, we work towards an objective way of selecting the least biased models over a certain region, based on physical parameters. This statistical method based on a neural classifier and multi-correspondence analysis is illustrated here for the Senegalo-Mauritanian region, but it could potentially be developed for any other region or process.

RainNet v1.0: a convolutional neural network for radar-based precipitation nowcasting

In this study, we present RainNet, a deep convolutional neural network for radar-based precipitation nowcasting, which was trained to predict continuous precipitation intensities at a lead time of 5 min. RainNet significantly outperformed the benchmark models at all lead times up to 60 min. Yet, an undesirable property of RainNet predictions is the level of spatial smoothing. Obviously, RainNet learned an optimal level of smoothing to produce a nowcast at 5 min lead time.

Changing global cropping patterns to minimize national blue water scarcity

Previous studies on water saving through food trade focussed either on comparing water productivities among countries or on analysing food trade in relation to national water endowments. Here, we consider, for the first time, both differences in water productivities and water endowments to analyse national comparative advantages. Our study reveals that blue water scarcity can be reduced to sustainable levels by changing cropping patterns while maintaining current levels of global production.

Linking economic and social factors to peak flows in an agricultural watershed using socio-hydrologic modeling

We describe a socio-hydrologic model that couples an agent-based model (ABM) of human decision-making with a hydrologic model. We establish this model for a typical agricultural watershed in Iowa, USA, and simulate the evolution of large discharge events over a 47-year period under changing land use. Using this modeling approach, relationships between seemingly unrelated variables such as crop markets or crop yields and local peak flow trends are quantified.

Comparing Palmer Drought Severity Index drought assessments using the traditional offline approach with direct climate model outputs

Many previous studies using offline drought indices report that future warming will increase worldwide drought. However, this contradicts observations/projections of vegetation greening and increased runoff. We resolved this paradox by re-calculating the same drought indices using direct climate model outputs and find no increase in future drought as the climate warms. We also find that accounting for the impact of CO ₂ on plant transpiration avoids the previous overestimation of drought.

Wetropolis extreme rainfall and flood demonstrator: from mathematical design to outreach

Wetropolis is a table-top demonstration model with extreme rainfall and flooding, including random rainfall, river flow, flood plains, an upland reservoir, a porous moor, and a city which can flood. It lets the viewer experience extreme rainfall and flood events in a physical model on reduced spatial and temporal scales with an event return period of 6.06 min rather than, say, 200 years. We disseminate its mathematical design and how it has been shown most prominently to over 500 flood victims.

HS Hydrological Sciences Highlight articles

Highlight articles

The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500

Revisiting the global hydrological cycle: is it intensifying?

Survival of the Qaidam mega-lake system under mid-Pliocene climates and itsrestoration under future climates

Why does a conceptual hydrological model fail to correctly predict discharge changes in response to climate change?

Towards an objective assessment of climate multi-model ensembles – a casestudy: the Senegalo-Mauritanian upwelling region

RainNet v1.0: a convolutional neural network for radar-based precipitation nowcasting

Changing global cropping patterns to minimize national blue water scarcity

Linking economic and social factors to peak flows in an agricultural watershed using socio-hydrologic modeling

Comparing Palmer Drought Severity Index drought assessments using the traditional offline approach with direct climate model outputs

Wetropolis extreme rainfall and flood demonstrator: from mathematical design to outreach

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