CAMELS-GB: Hydrometeorological time series and landscape attributes for 671 catchments in Great Britain

Coxon, Gemma; Addor, Nans; Bloomfield, John P.; Freer, Jim; Fry, Matthew; Hannaford, Jamie; Howden, Nicholas J K; Lane, Rosanna; Lewis, Melinda; Robinson, E. L.; Wagener, Thorsten; Woods, Ross

doi:10.5194/essd-2020-49

Cited by 18 publications

(35 citation statements)

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“…This study highlights the need for additional efforts to investigate the nonlinear responses of floods to climate changes using a larger sample of catchments, which would hopefully achieve a universal understanding of how floods might evolve. For instance, the approach presented in this study can be applied for other large sample data sets (Addor et al, 2019; Alvarez‐Garreton et al, 2018; Coxon et al, 2020; Gudmundsson et al, 2018) to quantify the contribution of extreme precipitation to historical changes in floods for other parts of the world.…”

Section: Discussionmentioning

confidence: 99%

To What Extent Are Changes in Flood Magnitude Related to Changes in Precipitation Extremes?

Hong

Mei

Gronewold

2020

Geophysical Research Letters

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Despite increasing evidence of intensification of extreme precipitation events associated with a warming climate, the magnitude of peak river flows is decreasing in many parts of the world. To better understand the range of relationships between precipitation extremes and floods, we analyzed annual precipitation extremes and flood events over the contiguous United States from 1980 to 2014. A low correlation (less than 0.2) between changes in precipitation extremes and changes in floods was found, attributable to a small fraction of co-occurrence. The covariation between precipitation extremes and floods is also substantially low, with a majority of catchments having a coefficient of determination of less than 0.5, even among the catchments with a relatively high fraction of annual maxima precipitation that can be linked to floods. The findings indicate a need for more investigations into causal mechanisms driving a nonlinear response of floods to intensified precipitation extremes in a warming climate.

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Section: Discussionmentioning

confidence: 99%

To What Extent Are Changes in Flood Magnitude Related to Changes in Precipitation Extremes?

Hong

Mei

Gronewold

2020

Geophysical Research Letters

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“…If there is no uncertainty information for the watershed, simulated measurement uncertainty (e.g., adding random errors or multiplicative bias to the flow) is a good alternative. Uncertainty magnitudes can be taken from the literature (e.g., McMillan, Krueger, & Freer, 2012), or from a watershed with similar gauge type and channel stability where uncertainties are known (e.g., choosing one or more watersheds from Westerberg et al, 2016 or Coxon et al, 2015, 2020). Using a large number of samples, aggregate the resulting signature values to find the estimated distribution of the signature: an example is shown in Figure 7, with signature uncertainties commonly exceeding ±20%.…”

Section: Methods In Using Hydrologic Signaturesmentioning

confidence: 99%

A review of hydrologic signatures and their applications

McMillan

2020

WIREs Water

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Hydrologic signatures are quantitative metrics or indices that describe statistical or dynamical properties of hydrologic data series, primarily streamflow. Hydrologic signatures were first used in eco-hydrology to assess alterations in flow regime, and have since seen wide uptake across a variety of hydrological fields. Their applications include extracting biologically relevant attributes of streamflow data, monitoring hydrologic change, analyzing runoff generation processes, defining similarity between watersheds, and calibrating and evaluating hydrologic models. Hydrologic signatures allow us to extract meaningful information about watershed processes from streamflow series, and are therefore seeing increasing use in emerging information-rich areas such as global-scale hydrologic modeling, machine learning, and large-sample hydrology. This overview paper describes the background and development of hydrologic signature theory, reviews hydrologic signature use across a variety of applications, and discusses ongoing hydrologic signature research including current challenges. This article is categorized under: Science of Water > Science of Water K E Y W O R D S flow indices, flow metrics, hydrologic signatures 1 | INTRODUCTION 1.1 | Discovering the information in streamflow data Streamflow timeseries show patterns: flood peaks and low flow periods, daily changes and seasonal cycles. These patterns are examples of information in streamflow data. The information might describe how the stream reacts to changes in weather, or what magnitudes and rates of change of flow are usual for the stream. Streamflow patterns depend on the physical characteristics of the watershed, telling a story about the path of water from precipitation to streamflow. Flow patterns in turn affect the stream's environment, informing us about riparian conditions and habitats. This paper describes how hydrologists use hydrologic signatures to extract this wealth of information from streamflow. 1.2 | What is a hydrologic signature? Hydrologic signatures are quantitative metrics that describe statistical or dynamic properties of streamflow. They are also known as hydrologic metrics, hydrologic indices, or diagnostic signatures. Hydrologic signatures range from simple

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“…Rating curves are particularly uncertain in unstable river channels that adjust their form due to erosion or sediment deposits, ice build‐up, vegetation growth, and blocked wood debris, or after major floods (Lang, Pobanz, Renard, Renouf, & Sauquet, 2010; Mansanarez, Renard, Coz, Lang, & Darienzo, 2019). These biases and errors have been shown to be particularly pronounced for floods (Steinbakk et al, 2016) and low flows (Sörengård & Di Baldassarre, 2017) because these extreme events occur rarely and are difficult to measure with a high precision. Data access : Publicly available streamflow datasets are still rare because of data licensing restrictions, strict access policies, or the time required to make these datasets readily usable at the global scale (Coxon et al, 2020). Data access is often also hampered by storage in non‐centralized databases, which are maintained by regional rather than national authorities, and may only be accessible in the local language. Lack of spatial information : Observations of discharge and other hydrological variables, such as surface water storage in rivers, lakes, reservoirs, and wetlands, are currently available for selected locations and poorly observed at the global scale (Biancamaria, Lettenmaier, & Pavelsky, 2016).…”

Section: Datamentioning

confidence: 99%

Challenges in modeling and predicting floods and droughts: A review

et al. 2021

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Predictions of floods, droughts, and fast drought‐flood transitions are required at different time scales to develop management strategies targeted at minimizing negative societal and economic impacts. Forecasts at daily and seasonal scale are vital for early warning, estimation of event frequency for hydraulic design, and long‐term projections for developing adaptation strategies to future conditions. All three types of predictions—forecasts, frequency estimates, and projections—typically treat droughts and floods independently, even though both types of extremes can be studied using related approaches and have similar challenges. In this review, we (a) identify challenges common to drought and flood prediction and their joint assessment and (b) discuss tractable approaches to tackle these challenges. We group challenges related to flood and drought prediction into four interrelated categories: data, process understanding, modeling and prediction, and human–water interactions. Data‐related challenges include data availability and event definition. Process‐related challenges include the multivariate and spatial characteristics of extremes, non‐stationarities, and future changes in extremes. Modeling challenges arise in frequency analysis, stochastic, hydrological, earth system, and hydraulic modeling. Challenges with respect to human–water interactions lie in establishing links to impacts, representing human–water interactions, and science communication. We discuss potential ways of tackling these challenges including exploiting new data sources, studying droughts and floods in a joint framework, studying societal influences and compounding drivers, developing continuous stochastic models or non‐stationary models, and obtaining stakeholder feedback. Tackling one or several of these challenges will improve flood and drought predictions and help to minimize the negative impacts of extreme events. This article is categorized under: Science of Water > Science of Water

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CAMELS-GB: Hydrometeorological time series and landscape attributes for 671 catchments in Great Britain

Cited by 18 publications

References 58 publications

To What Extent Are Changes in Flood Magnitude Related to Changes in Precipitation Extremes?

To What Extent Are Changes in Flood Magnitude Related to Changes in Precipitation Extremes?

A review of hydrologic signatures and their applications

Challenges in modeling and predicting floods and droughts: A review

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