Abstract
Observational trend analysis is fundamental for documenting changes in river flows and placing extreme events in their longer-term historical context. Observations from near-natural catchments, i.e., with little or no alteration by humans, are of great importance in detecting and attributing streamflow trends. The purpose of this study is to analyze the annual and seasonal trends of stream discharge (mean, low and high flows) in a headwater catchment in NW Spain, i.e., in the wettest corner of the Iberian Peninsula. The results showed no significant decrease in the mean annual stream discharge. However, significantly lower summer and autumn mean stream discharge and an increase in low flow period were detected, in addition to lesser autumn high flow. The rainfall pattern followed an upward trend, but was not significant. This different pattern shown by rainfall and discharge indicates that is not sufficient to explain the observed trend in stream discharge. Air temperature, most notably by enhancing evapotranspiration, may explain the altered patterns of stream discharge.
Highlights
Due to the incalculable value of water as an asset for all, both in the present and in the future, and the importance of streamflow as an indicator of long-term hydro-climatic changes, curbing and quantifying changes in streamflow series have become essential for water resource planning and management [1,2]
The annual streamflow in the study catchment varied from 0.08 m3 s−1 (2016/2017) to 0.273 m3 s−1 (2009/2010), with a mean annual stream discharge of 0.181 m3 s−1, a standard deviation of 0.05 m3 s−1 and a variation coefficient of 29%, which denotes a marked inter-annual fluctuation
Streamflow was observed to be concentrated in the winter season (0.306 m3 s−1 ), whereas summer exhibited the lowest stream discharge (0.058 m3 s−1 )
Summary
Due to the incalculable value of water as an asset for all, both in the present and in the future, and the importance of streamflow as an indicator of long-term hydro-climatic changes, curbing and quantifying changes in streamflow series have become essential for water resource planning and management [1,2]. Streamflow integrates the influence of atmospheric variables over a catchment and, presumably, if consistent changes in rainfall and other climate variables (winds, atmosphere/heat fluxes) are observed, these should be reflected in the catchment scale. This is not so obvious, because catchment characteristics (geology, slope, soils) impact rainfall-runoff transformation properties [3,4,5]. Human activities can greatly influence the river systems and make it difficult for trend detection and attribution [6,7] Against this background, streamflow measures in natural or near-natural rivers become of prime importance in understanding hydrological processes in an area and identifying and attributing emerging trends [8,9,10]. Several studies have highlighted the importance of the hydrological modelling components in the Hydrology 2020, 7, 97; doi:10.3390/hydrology7040097 www.mdpi.com/journal/hydrology
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