The Global Streamflow Indices and Metadata Archive (GSIM) – Part 2: Quality control, time-series indices and homogeneity assessment

Abstract

Abstract. This is Part 2 of a two-paper series presenting the Global Streamflow Indices and Metadata Archive (GSIM), which is a collection of daily streamflow observations at more than 30 000 stations around the world. While Part 1 (Do et al., 2018a) describes the data collection process as well as the generation of auxiliary catchment data (e.g. catchment boundary, land cover, mean climate), Part 2 introduces a set of quality controlled time-series indices representing (i) the water balance, (ii) the seasonal cycle, (iii) low flows and (iv) floods. To this end we first consider the quality of individual daily records using a combination of quality flags from data providers and automated screening methods. Subsequently, streamflow time-series indices are computed for yearly, seasonal and monthly resolution. The paper provides a generalized assessment of the homogeneity of all generated streamflow time-series indices, which can be used to select time series that are suitable for a specific task. The newly generated global set of streamflow time-series indices is made freely available with an digital object identifier at https://doi.pangaea.de/10.1594/PANGAEA.887470 and is expected to foster global freshwater research, by acting as a ground truth for model validation or as a basis for assessing the role of human impacts on the terrestrial water cycle. It is hoped that a renewed interest in streamflow data at the global scale will foster efforts in the systematic assessment of data quality and provide momentum to overcome administrative barriers that lead to inconsistencies in global collections of relevant hydrological observations.

Event‐based classification for global study of river flood generating processes

“…While daily time series data are not made available, the date and magnitude of annual maximum flow are published. A value is supplied if at least 350 days of reliable daily flow data are available for that station (Gudmundsson et al, ). For more information about the quality control both for the catchment delineation procedure and time series inhomogeneities refer to Gudmundsson et al ().…”

“…A value is supplied if at least 350 days of reliable daily flow data are available for that station (Gudmundsson et al, ). For more information about the quality control both for the catchment delineation procedure and time series inhomogeneities refer to Gudmundsson et al (). Only stations which have a high quality in regard to both aspects, determined through the provided quality flags, are kept for the analysis.…”

Observed Trends in Global Indicators of Mean and Extreme Streamflow

“…Annual time series information is available through indices computed from daily values that represent a wide range of flow properties at monthly, seasonal, and yearly resolution. Here the following indices are considered: Low flows are represented through time series of the annual minimum (MIN) and the annual 10th percentile (P10). Average flow conditions are characterized using the annual mean (MEAN) and the annual 50th percentile/median (P50). High flows are represented through time series of the annual maximum (MAX) and the annual 90th percentile (P90). Daily time series used to compute the GSIM indices underwent a formal quality assessment (Gudmundsson et al, ). The assessment utilized quality flags from individual data providers and automated screening methods that flag implausible values.…”

“…All streamflow indices considered are taken from the GSIM archive and are freely available from https://doi.org/10.1594/PANGAEA.887470 (Gudmundsson et al, ). Mr. Hong Xuan Do receives financial support from the Australia Award Scholarship (AAS) and D. R. Stranks Traveling Fellowship.…”

Climate and rivers

“…The climate indices, which included an aridity index, precipitation seasonality, transformed mean annual precipitation, mean annual potential evaporation, and potential evapotranspiration seasonality, were found to exhibit the strongest relationships with streamflow and were deemed as superior predictors of basin flow compared with physiographic factors (Beck et al, ). Other attempts at the global scale to produce information that paves the way for understanding climate–flow regime associations include that of Gudmundsson, Do, Leonard, and Westra (); Gudmundsson, Leonard, Do, Westra, and Seneviratne (), Barbarossa et al (), and Padron, Gudmundsson, Greve, and Seneviratne () who have produced a range of quality controlled time‐series indices relevant to establishing the nature of a river's flow regime. Understandably at the regional or national level, there are many variations on the broad flow regime types found at the global level because, as noted above, regime types exist on a continuum of climate gradients.…”