A global classification of river regimes

Haines, Allison; Finlayson, Brian; McMahon, Thomas A.

doi:10.1016/0143-6228(88)90035-5

Cited by 181 publications

(166 citation statements)

References 3 publications

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“…Latitudinal patterns in the extra-tropics are also quite distinct, with high-flow seasons often occurring across similar months in the year. These broad temporal patterns are consistent with previous find- ings (e.g., Burn and Arnell, 1993;Dettinger and Diaz, 2000;Haines et al, 1988); however, this analysis goes further by not being constrained to large-scale patterns for seasonal definition (via clustering) and also providing a sense of the reliability of the defined high-flow seasons. Specifically, the defined PM (Fig.…”

Section: Conclusion and Discussionsupporting

confidence: 90%

“…For observations, this is attributable, at least in part, to reservoirs and dams along the Mississippi, Missouri and Danube rivers. Additionally, relatively constant streamflow patterns are identified in both observations and modeled output, consistent with previous studies reporting these flow regimes as uniform or perpetually wet (Burn and Arnell, 1993;Dettinger and Diaz, 2000;Haines et al, 1988). Minor high-flow seasons may also play a role.…”

Section: Observed Versus Modeled High-flow Seasonssupporting

confidence: 86%

“…This is advantageous for many reasons, including hydrologic assessment in ungauged and poorly gauged basins and also for investigating flood season timing within large basins having diverse physical processes, for example, how the PM may shift along long rivers (e.g., Congo River) or basins with both snowmelt and raindominated processes. These spatially heterogeneous highflow seasons at high resolution have the potential to characterize streamflow regimes better than previous studies (e.g., Dettinger and Diaz, 2000;Haines et al, 1988). Additional analysis to include upstream management and regulations is required to further classify global streamflow regimes and major high-flow seasons (or the elimination of them) for specific sub-basin-level hydrologic applications.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

“…Haines et al (1988) cluster 969 world rivers into 15 categories based on seasonality and average monthly streamflow data, and (Döll and Lehner, 2002) with separation of large basins (Ward et al, 2014). present one of the first maps providing a global classification.…”

Section: Introductionmentioning

confidence: 99%

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Defining high-flow seasons using temporal streamflow patterns from a global model

Lee

Ward

Block

2015

Hydrol. Earth Syst. Sci.

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Abstract. Globally, flood catastrophes lead all natural hazards in terms of impacts on society, causing billions of dollars of damages annually. Here, a novel approach to defining high-flow seasons (3-month) globally is presented by identifying temporal patterns of streamflow. The main high-flow season is identified using a volume-based threshold technique and the PCR-GLOBWB model. In comparison with observations, 40 % (50 %) of locations at a station (subbasin) scale have identical peak months and 81 % (89 %) are within 1 month, indicating fair agreement between modeled and observed high-flow seasons. Minor high-flow seasons are also defined for bi-modal flow regimes. Identified major and minor high-flow seasons together are found to well represent actual flood records from the Dartmouth Flood Observatory, further substantiating the model's ability to reproduce the appropriate high-flow season. These high-spatial-resolution high-flow seasons and associated performance metrics allow for an improved understanding of temporal characterization of streamflow and flood potential, causation, and management. This is especially attractive for regions with limited observations and/or little capacity to develop early warning flood systems.

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Section: Conclusion and Discussionsupporting

confidence: 90%

Section: Observed Versus Modeled High-flow Seasonssupporting

confidence: 86%

Section: Conclusion and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Defining high-flow seasons using temporal streamflow patterns from a global model

Lee

Ward

Block

2015

Hydrol. Earth Syst. Sci.

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“…If the objective is, instead, the assessment of water availability, the streamflow indexes to be predicted may be for example mean annual or monthly flows (e.g. Haines et al, 1988;Holmes et al, 1999;Viglione et al, 2006) or low flow percentiles (e.g. Nathan and McMahon, 1990;Laaha and Bloeschl, 2006;Vezza et al, 2010) or the entire flow duration curve (e.g.…”

Section: E Toth: Catchment Classificationmentioning

confidence: 99%

Catchment classification based on characterisation of streamflow and precipitation time series

Toth

2013

Hydrol. Earth Syst. Sci.

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Abstract. The formulation of objective procedures for the delineation of homogeneous groups of catchments is a fundamental issue in both operational and research hydrology. For assessing catchment similarity, a variety of hydrological information may be considered; in this paper, gauged sites are characterised by a set of streamflow signatures that include a representation, albeit simplified, of the properties of fine time-scale flow series and in particular of the dynamic components of the data, in order to keep into account the sequential order and the stochastic nature of the streamflow process.The streamflow signatures are provided in input to a clustering algorithm based on unsupervised SOM neural networks, obtaining groups of catchments with a clear hydrological distinctiveness, as highlighted by the identification of the main patterns of the input variables in the different classes and the interpretation of their interrelations. In addition, even if no geographical, morphological nor climatological information is provided in input to the SOM network, the clusters exhibit an overall consistency as far as location, altitude and precipitation regime are concerned.In order to assign ungauged sites to such groups, the catchments are represented through a parsimonious set of morphometric and pluviometric variables, including also indexes that attempt to synthesise the variability and correlation properties of the precipitation time series, thus providing information on the type of weather forcing that is specific to each basin. Following a principal components analysis, needed for synthesizing and better understanding the morpho-pluviometric catchment properties, a discriminant analysis finally assigns the ungauged catchments, through a leave-one-out cross validation, to one of the above identified hydrologic response classes. The approach delivers a quite satisfactory identification of the membership of ungauged catchments to the streamflow-based classes, since the comparison of the two cluster sets shows a misclassification rate of around 20 %.Overall results indicate that the inclusion of information on the properties of the fine time-scale streamflow and rainfall time series may be a promising way for better representing the hydrologic and climatic character of the study catchments.

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Global-scale analysis on future changes in flow regimes using Gini and Lorenz asymmetry coefficients

et al. 2014

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By introducing two scalar quantities, namely, the Gini and Lorenz asymmetry coefficients, we examined their characteristics and applicability to the global analysis of changes in river flow regimes under future climate change. First, by applying these coefficients to river discharge data, we showed that various types of flow-duration curves can be interpreted quantitatively in terms of the seasonal inequality in the discharge (i.e., the unevenness of the temporal distribution of river discharge). Their statistical characteristics, based on five theoretical distribution functions frequently used in hydrological analysis, were also shown. Next we used these coefficients to evaluate the seasonal inequality of major global rivers using the global hydrological model H08 for four 30 year time spans (1960-1989, 2010-2039, 2040-2069, and 2070-2099) under four climate-change scenarios. We used ensembles of hydrological simulation results with five general circulation models. From the analysis of the Gini coefficient, future changes in seasonal inequality show a contrasting geographical pattern: a decreasing trend at high northern latitudes and an increasing trend in most other areas. The Lorenz asymmetry coefficient shows large changes at high northern latitudes, attributable to major shifts in the flow regime accompanied by different snow-melting properties under different future climate scenarios. Although a flow-duration curve is a pictorial representation of river discharge suitable for one specific site, by depicting the geographical distribution of these two coefficients along river channels, different characteristics of flow-duration curves at different sites can be detected, even within the same river basin.

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A global classification of river regimes

Cited by 181 publications

References 3 publications

Defining high-flow seasons using temporal streamflow patterns from a global model

Defining high-flow seasons using temporal streamflow patterns from a global model

Catchment classification based on characterisation of streamflow and precipitation time series

Global-scale analysis on future changes in flow regimes using Gini and Lorenz asymmetry coefficients

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