Nans Addor

Fathom

Hydrological signatures are now used for a wide range of purposes, including catchment classification, process exploration and hydrological model calibration. The recent boost in the popularity and number of signatures has however not been accompanied by the development of clear guidance on signature selection, meaning that signature selection is o...

The findings of hydrological modeling studies depend on which model was used. Although hydrological model selection is a crucial step, experience suggests that hydrologists tend to stick to the model they have experience with, and rarely switch to competing models, although these models might be more adequate given the study objectives. To gain qua...

Large-sample hydrology (LSH) relies on data from large sets (tens to thousands) of catchments to go beyond individual case studies and derive robust conclusions on hydrological processes and models. Numerous LSH datasets have recently been released, covering a wide range of regions and relying on increasingly diverse data sources to characterize ca...

High-quality datasets are essential to support hydrological science and modeling. Several CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) datasets exist for specific countries or regions, however these datasets lack standardization, which makes global studies difficult. This paper introduces a dataset called Caravan (a series...

High-quality datasets are essential to support hydrological science and modeling. Several CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) datasets exist for specific countries or regions, however these datasets lack standardization, which makes global studies difficult. This paper introduces a dataset called \emph{Caravan} (a...

The assessment of climate change impacts on water resources and flood risk is typically underpinned by hydrological models calibrated and selected based on observed streamflow records. Yet, changes in climate are rarely accounted for when selecting hydrological models, which compromises their ability to robustly represent future changes in catchmen...

This study employs a stochastic hydrologic modeling framework to evaluate the sensitivity of flood frequency analyses to different components of the hydrologic modeling chain. The major components of the stochastic hydrologic modeling chain, including model structure, model parameter estimation, initial conditions, and precipitation inputs were exa...

Hydrological models are usually systems of nonlinear differential equations for which no analytical solutions exist and thus rely on numerical solutions. While some studies have investigated the relationship between numerical method choice and model error, the extent to which extreme precipitation such as that observed during hurricanes Harvey and...

Water resource management (WRM) practices, such as groundwater and surface water abstractions and effluent discharges, may impact baseflow. Here the CAMELS-GB large-sample hydrology dataset is used to assess the impacts of such practices on Baseflow Index (BFI) using statistical models of 429 catchments from Great Britain. Two complementary modelli...

This paper presents the Australian edition of the Catchment Attributes and Meteorology for Large-sample Studies (CAMELS) series of datasets. CAMELS-AUS (Australia) comprises data for 222 unregulated catchments, combining hydrometeorological time series (streamflow and 18 climatic variables) with 134 attributes related to geology, soil, topography,...

Riverine flood hazard is the consequence of meteorological drivers, primarily precipitation, hydrological processes and the interaction of floodwaters with the floodplain landscape. Modeling this can be particularly challenging because of the multiple steps and differing spatial scales involved in the varying processes. As the climate modeling comm...

The assessment of climate change impacts on water resources and flood risk is typically underpinned by hydrological models calibrated and selected based on observed streamflow records. Yet, changes in climate are rarely accounted for when selecting hydrological models, which compromises their ability to robustly represent future changes in catchmen...

Water resource management (WRM) practices, such as abstractions and discharges, may impact baseflow. Here the CAMELS-GB large-sample hydrology dataset is used to assess the impacts of such practices on baseflow index (BFI) using statistical models of 429 catchments from Great Britain. Two complementary modelling schemes, multiple linear regression...

In many mountainous regions, winter precipitation accumulates as snow that melts in the spring and summer, which provides water to one billion people globally. Climate warming and earlier snowmelt compromise this natural water storage. Although snowpack trend analyses commonly focus on the snow water equivalent (SWE), we propose that trends in the...

This study assesses sources of variance in stochastic hydrologic modelling to support flood frequency analyses. The major components of the modelling chain, including model structure, model parameter estimation, initial conditions, and precipitation inputs were examined across return periods from 2 to 100,000 years at two watersheds representing di...

Hydrological models are usually systems of nonlinear differential equations for which no analytical solutions exist and thus rely on approximate numerical solutions. While some studies have investigated the relationship between numerical method choice and model error, the extent to which extreme precipitation like that observed during hurricanes Ha...

This paper presents the Australian edition of the Catchment Attributes and Meteorology for Large-sample Studies (CAMELS) series of datasets. CAMELS-AUS comprises data for 222 unregulated catchments, combining hydrometeorological timeseries (streamflow and 18 climatic variables) with 134 attributes related to geology, soil, topography, land cover, a...

There is an urgent need for the climate community to translate their meteorological drivers into relevant hazard estimates. This is especially important for the climate attribution and climate projection communities as we seek to understand how anthropogenic climate change has, and will, impact our society. This can be particularly challenging beca...

We present the first large-sample catchment hydrology dataset for Great Britain, CAMELS-GB (Catchment Attributes and MEteorology for Large-sample Studies). CAMELS-GB collates river flows, catchment attributes and catchment boundaries from the UK National River Flow Archive together with a suite of new meteorological time series and catchment attrib...

Exploring water fluxes between hydrological model (HM) components is essential to assess and improve model realism. Many classical metrics for HM diagnosis rely solely on streamflow and hence provide limited insights into model performance across processes. This study applies an information theory measure known as "transfer entropy" (TE) to systema...

In many mountainous regions, winter precipitation accumulates as snow that melts in spring and summer providing water to one billion people globally. As the climate warms and snowmelt occurs earlier, this natural water storage is compromised. While snowpack trend analyses commonly focus on snow water equivalent (SWE), we propose that trends in accu...

We introduce a new catchment dataset for large-sample hydrological studies in Brazil. This dataset encompasses daily time series of observed streamflow from 3679 gauges, as well as meteorological forcing (precipitation, evapotranspiration, and temperature) for 897 selected catchments. It also includes 65 attributes covering a range of topographic,...

Anticipating and adapting to climate change impacts on water resources requires a detailed understanding of future hydroclimatic changes and of stakeholders' vulnerability to these changes. However, impact studies are often conducted at a spatial scale that is too coarse to capture the specificity of individual catchments, and, importantly, the cha...

Abstract. We introduce a new catchment dataset for large-sample hydrological studies in Brazil. This dataset encompasses daily time series of observed streamflow from 3713 gauges, as well as meteorological forcing (precipitation, evapotranspiration and temperature) for 897 selected catchments. It also includes 63 attributes covering a range of topo...

Abstract. We present the first large-sample catchment hydrology dataset for Great Britain, CAMELS-GB (Catchment Attributes and MEteorology for Large-sample Studies). CAMELS-GB collates river flows, catchment attributes and catchment boundaries from the UK National River Flow Archive together with a suite of new meteorological timeseries and catchme...

This article provides relevant information to understand (i) hydrological climate change impact research, (ii) the steps to perform an impact study, and (iii) the main challenges encountered in an impact study and how they can be addressed. Hydrological climate change research is an active field of research and although much progress has been made,...

Anticipating and adapting to climate change impacts on water resources requires a detailed understanding of future hydroclimatic changes and of stakeholders' vulnerability to these changes. However, climate change impact studies are often conducted at a spatial scale that is too coarse to capture the specificity of individual catchments, and more i...

Anticipating and adapting to climate change impacts on water resources requires a detailed understanding of future hydroclimatic changes and of stakeholders' vulnerability to these changes. However, climate change impact studies are often conducted at a spatial scale that is too coarse to capture the specificity of individual catchments, and more i...

We introduce the first catchment dataset for large sample studies in Chile. This dataset includes 516 catchments; it covers particularly wide latitude (17.8 to 55.0°S) and elevation (0 to 6993ma.s.l.) ranges, and it relies on multiple data sources (including ground data, remote-sensed products and reanalyses) to characterise the hydroclimatic condi...

Water managers are actively incorporating climate change information into their long- and short-term planning processes. This is generally seen as a step in the right direction because it supplements traditional methods, providing new insights that can help in planning for a non-stationary climate. However, the continuous evolution of climate chang...

Variables simulated by climate models are usually evaluated independently. Yet, climate change impacts often stem from the combined effect of these variables, making the evaluation of intervariable relationships essential. These relationships can be evaluated in a statistical framework (e.g., using correlation coefficients), but this does not test...

Hydrologic projections are of vital socio-economic importance. However, they are also prone to uncertainty. In order to establish a meaningful range of storylines to support water managers in decision making, we need to reveal the relevant sources of uncertainty. Here, we systematically and extensively investigate uncertainty in hydrologic projecti...

We introduce the first catchment data set for large sample studies in Chile (South America). The data set includes 516 catchments and provides catchment boundaries, daily streamflow records and basin-averaged time series of the following hydrometeorological variables: 1) daily precipitation retrieved from four gridded sources; 2) daily maximum, min...

Hydrological signatures are now used for a wide range of purposes, including catchment classification, process exploration and hydrological model calibration. The recent boost in the popularity and number of signatures has however not been accompanied by the development of clear guidance on signature selection, meaning that signature selection is o...

Hydrological signatures are now used for a wide range of purposes, including catchment classification, process exploration and hydrological model calibration. The recent boost in the popularity and number of signatures has however not been accompanied by the development of clear guidance on signature selection, meaning that signature selection is o...

We present a new data set of attributes for 671 catchments in the contiguous United States (CONUS) minimally impacted by human activities. This complements the daily time series of meteorological forcing and streamflow provided by Newman et al. (2015b). To produce this extension, we synthesized diverse and complementary data sets to describe six ma...

Hydrologic projections are of vital socio-economic importance. Yet, they are also prone to uncertainty. In order to establish a meaningful range of storylines to support water managers in decision making, we need to reveal the relevant sources of uncertainty. Here, we systematically and extensively investigate uncertainty in constrained hydrologic...

Study region: The hydropower reservoir of Gigerwald is located in the alpine valley Calfeisental in eastern Switzerland. The lake is fed by runoff from rain, snow melt and ice melt from a few small glaciers, as well as by water collected in a neighbouring valley. Study focus: Water resources in the Alps are projected to undergo substantial changes...

Bias-adjustment methods usually do not account for the origins of biases in climate models and instead perform empirical adjustments. Biases in the synoptic circulation are for instance often overlooked when post-processing regional climate model (RCM) simulations driven by general circulation models (GCMs). Yet considering atmospheric circulation...

Climate model simulations are routinely compared to observational data sets for evaluation purposes. The resulting differences can be large and induce artifacts if propagated through impact models. They are usually termed „model biases‟, suggesting that they exclusively stem from systematic models errors. Here we explore for Switzerland the contrib...

In the context of climate change, both climate researchers and decision makers deal with uncertainties, but these uncertainties differ in fundamental ways. They stem from different sources, cover different temporal and spatial scales, might or might not be reducible or quantifiable, and are generally difficult to characterize and communicate. Hence...

Projections of discharge are key for future water resources management. These projections are subject to uncertainties, which are difficult to handle in the decision process on adaptation strategies. Uncertainties arise from different sources such as the emission scenarios, the climate models and their post-processing, the hydrological models and n...

river runoff . groundwater temperature 0 0 0 — For all greenhouse gas scenarios, a shift in runoff regime type is projected to occur in most catchments in Switzerland, with lower summer runoff and higher winter runoff, hut little change in the total annual volume. — Limiting emissions to RCP3PD levels would reduce the impacts on mean winter and sum...

The Sihl River flows through Zurich, Switzerland's most populated city, for which it represents the largest flood threat. To anticipate extreme discharge events and provide decision support in case of flood risk, a hydrometeorological ensemble prediction system (HEPS) was launched operationally in 2008. This model chain relies on limited-area atmos...

Als Folge der Hochwasserabflüsse der Shil im August 2005 wurden hydrologische Studien durchgeführt die zeigen, dass am Standort Zürich Hochwasserereignisse mit Spitzen von 310 bis 600 m3s-1 möglich sind. Aufgrund dieser Erkenntnisse beschloss das Amt für Abfall, Energie und Luft AWEL, ein regionales Hochwasserwarnsystem zur Verbesserung der Hochwas...

Marine ecological genomics can be defined as the application of genomic sciences to understand the structure and function of marine ecosystems. In this field of research, the analysis of genomes and metagenomes of environmental relevance must take into account the corresponding habitat (contextual) data, e.g. water depth, physical and chemical para...