%0 Journal Article
%T Regionalization of patterns of flow intermittence from gauging station records
%A T. H. Snelder
%A T. Datry
%A N. Lamouroux
%A S. T. Larned
%J Hydrology and Earth System Sciences Discussions
%D 2013
%I Copernicus Publications
%R 10.5194/hessd-10-1511-2013
%X Understanding large-scale patterns in flow intermittence is important for effective water resource management. We used daily flow records from 628 gauging stations on rivers with minimally modified flows distributed throughout France to predict regional patterns of flow intermittence. For each station we calculated two annual times-series describing flow intermittence; the frequency of zero-flow periods (consecutive days of zero-flow) in each year of record (FREQ; yr 1), and the total number of zero-flow days in each year of record (DUR; days). These time series were used to calculate two indices for each station, the mean annual frequency of zero-flow periods (mFREQ; yr 1), and the mean duration of zero-flow periods (mDUR; days). Approximately 20% of stations had recorded at least one zero-flow period. Dissimilarities between pairs of gauges calculated from the annual times-series (FREQ and DUR) and geographic distances were weakly correlated, indicating that there was little spatial synchronization of zero-flow. A flow-regime classification for the gauging stations discriminated intermittent and perennial stations, and an intermittence classification grouped intermittent stations into three classes based on the values of mFREQ and mDUR. We used Random Forest (RF) models to relate the flow-regime and intermittence classifications to several environmental characteristics of the gauging station catchments. The RF model of the flow-regime classification had a cross-validated Cohen's kappa of 0.47, indicating fair performance and the intermittence classification had poor performance (cross-validated Cohen's kappa of 0.35). Both classification models identified significant environment-intermittence associations, in particular with regional-scale climate patterns and also catchment area, shape and slope. However, we suggest that the fair-to-poor performance of the classification models is because intermittence is also controlled by processes operating at scales smaller than catchments, such as groundwater-table fluctuations and seepage through permeable channels. We suggest that high spatial heterogeneity in these small-scale processes partly explains the low spatial synchronization of zero-flows. While 20% of gauges were classified as intermittent, the flow-regime model predicted 39% of all river segments to be intermittent, indicating that the gauging station network under-represents intermittent river segments in France. Predictions of regional patterns in flow intermittence provide useful information for applications including environmental flow-setting,
%U http://www.hydrol-earth-syst-sci-discuss.net/10/1511/2013/hessd-10-1511-2013.pdf