Lessons learnt from checking the quality of openly accessible river flow data worldwide

Crochemore, Louise; Isberg, Kristina; Pimentel, Rafael; Pineda, Luis; Hasan, Abdulghani; Arheimer, Berit

doi:10.1080/02626667.2019.1659509

Cited by 64 publications

(40 citation statements)

References 34 publications

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“…Despite the large sample of river gauges, however, we experienced that it was not distributed well enough to cover the large domain. Screening of the gauged data quality showed that most regions worldwide have access to some highquality time series of river flow (Crochemore et al, 2019), but for the stepwise procedure applied here this was still not enough for many of the pre-defined calibration steps. Even when merging the original ESA land-cover classes before calibration (Table 4) sufficient gauged data were missing.…”

Section: Discussionmentioning

confidence: 99%

“…Of these, time series could be downloaded for 11 369, while 10 336 could only assist with metadata, such as upstream area, river name, elevation, or natural or regulated flow. The time series were screened for missing values, inconsistency, skewness, trends, inhomogeneity, and outliers (Crochemore et al, 2019). Stations representing the resolution of the model (≥ 1000 km 2 ) and with records of at least 10 consecutive years between 1981 and 2012 were considered for model evaluation.…”

Section: Observed River Flowmentioning

confidence: 99%

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Global catchment modelling using World-Wide HYPE (WWH), open data, and stepwise parameter estimation

Arheimer

Pimentel

Isberg

et al. 2020

Hydrol. Earth Syst. Sci.

103

133

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Abstract. Recent advancements in catchment hydrology (such as understanding catchment similarity, accessing new data sources, and refining methods for parameter constraints) make it possible to apply catchment models for ungauged basins over large domains. Here we present a cutting-edge case study applying catchment-modelling techniques with evaluation against river flow at the global scale for the first time. The modelling procedure was challenging but doable, and even the first model version showed better performance than traditional gridded global models of river flow. We used the open-source code of the HYPE model and applied it for >130 000 catchments (with an average resolution of 1000 km2), delineated to cover the Earth's landmass (except Antarctica). The catchments were characterized using 20 open databases on physiographical variables, to account for spatial and temporal variability of the global freshwater resources, based on exchange with the atmosphere (e.g. precipitation and evapotranspiration) and related budgets in all compartments of the land (e.g. soil, rivers, lakes, glaciers, and floodplains), including water stocks, residence times, and the pathways between various compartments. Global parameter values were estimated using a stepwise approach for groups of parameters regulating specific processes and catchment characteristics in representative gauged catchments. Daily and monthly time series (>10 years) from 5338 gauges of river flow across the globe were used for model evaluation (half for calibration and half for independent validation), resulting in a median monthly KGE of 0.4. However, the World-Wide HYPE (WWH) model shows large variation in model performance, both between geographical domains and between various flow signatures. The model performs best (KGE >0.6) in the eastern USA, Europe, South-East Asia, and Japan, as well as in parts of Russia, Canada, and South America. The model shows overall good potential to capture flow signatures of monthly high flows, spatial variability of high flows, duration of low flows, and constancy of daily flow. Nevertheless, there remains large potential for model improvements, and we suggest both redoing the parameter estimation and reconsidering parts of the model structure for the next WWH version. This first model version clearly indicates challenges in large-scale modelling, usefulness of open data, and current gaps in process understanding. However, we also found that catchment modelling techniques can contribute to advance global hydrological predictions. Setting up a global catchment model has to be a long-term commitment as it demands many iterations; this paper shows a first version, which will be subjected to continuous model refinements in the future. WWH is currently shared with regional/local modellers to appreciate local knowledge.

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Section: Discussionmentioning

confidence: 99%

Section: Observed River Flowmentioning

confidence: 99%

Global catchment modelling using World-Wide HYPE (WWH), open data, and stepwise parameter estimation

Arheimer

Pimentel

Isberg

et al. 2020

Hydrol. Earth Syst. Sci.

103

133

View full text Add to dashboard Cite

show abstract

“…In such scales, model calibration and verification procedures are usually straightforward and provide adequate performance for modeling purposes. Moreover, the information provided to users needs to (at least) be reliable and precise (Swart et al, 2017), which is a challenge for continental and global services, since their setup is strongly dependent on uncertain open global data sets (Crochemore et al, 2019;Kauffeldt et al, 2013) and hydrological models that can only represent limited but dominant processes (Archfield et al, 2015;Bierkens, 2015;Sood & Smakhtin, 2015).…”

Section: Introductionmentioning

confidence: 99%

Can Continental Models Convey Useful Seasonal Hydrologic Information at the Catchment Scale?

Crochemore

Ramos

Pechlivanidis

2020

Water Resources Research

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The development and availability of climate forecasting systems have allowed the implementation of seasonal hydroclimatic services at the continental scale. User guidance and quality of the forecast information are key components to ensure user engagement and service uptake, yet forecast quality depends on the hydrologic model setup. Here, we address how seasonal forecasts from continental services can be used to address user needs at the catchment scale. We compare a continentally calibrated process‐based model (E‐HYPE) and a catchment‐specific parsimonious model (GR6J) to forecast streamflow in a set of French catchments. Results show that despite expected high performance from the catchment setup against observed streamflow, the continental setup can, in some catchments, match or even outperform the catchment‐specific setup for 3‐month aggregations and threshold exceedance. Forecast systems can become comparable when looking at statistics relative to model climatology, such as anomalies, and adequate initial conditions are the main source of skill in both systems. We highlight the need for consistency in data used in modeling chains and in tailoring service outputs for use at the catchment scale. Finally, we show that the spread in internal model states varies largely between the two systems, reflecting the differences in their setups and calibration strategies, and highlighting that caution is needed before extracting hydrologic variables other than streamflow. We overall argue that continental hydroclimatic services show potential on addressing needs at the catchment scale, yet guidance is needed to extract, tailor and use the information provided.

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“…Ground measurement datasets are laden by inconsistencies between measuring stations, for instance offering different time periods, measuring frequencies, and technical qualities (W. A. Dorigo et al, ; Hannah et al, ; Harris et al, ; United Nations Environment Programme, ). Crochemore et al () provides a methodological framework for quality checking large‐sample river flow datasets.…”

Section: Dataset Usability Challenges For Comparative Studiesmentioning

confidence: 99%

A review of freely accessible global datasets for the study of floods, droughts and their interactions with human societies

et al. 2020

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The availability of planetary-scale geospatial datasets that can support the study of water-related disasters in the Anthropocene is rapidly growing. We review 124 global and free datasets allowing spatial (and temporal) analyses of floods, droughts and their interactions with human societies. Our collection of datasets is available in a descriptive list for download at https://zenodo.org/ record/3368882. The purpose of providing an overview of datasets across a wide range of hydrological and socioeconomic variables is to highlight research opportunities across scientific disciplines for the study of the watersociety interplay. Our collection of datasets confirms that the availability of geospatial data capturing hydrological hazards and exposure is far more mature than those capturing vulnerability aspects. We do not only highlight the unprecedented opportunities associated with these global datasets for the study of water-related disasters in the Anthropocene, but also discuss the challenges associated with their exploitation. These challenges include: (a) time varying datasets advised not to be used in time series analyses; (b) fine spatial resolution datasets advised not to be used in local scale studies; (c), datasets built by a wide variety of data sources prohibiting systematic uncertainty assessments; and (d) datasets built by covariate variables preventing interaction studies.

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Lessons learnt from checking the quality of openly accessible river flow data worldwide

Cited by 64 publications

References 34 publications

Global catchment modelling using World-Wide HYPE (WWH), open data, and stepwise parameter estimation

Global catchment modelling using World-Wide HYPE (WWH), open data, and stepwise parameter estimation

Can Continental Models Convey Useful Seasonal Hydrologic Information at the Catchment Scale?

A review of freely accessible global datasets for the study of floods, droughts and their interactions with human societies

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