Regionalization of patterns of flow intermittence from gauging station records

Understanding large-scale patterns in flow inter- mittence is important for effective river management. The duration and frequency of zero-flow periods are associated with the ecological characteristics of rivers and have impor- tant implications for water resources 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 sta- tion we calculated two annual times series describing flow intermittence; the frequency of zero-flow periods (consec- utive 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 cal- culate two indices for each station, the mean annual fre- quency 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 pe- riod in their record. 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 discrim- inated intermittent and perennial stations, and an intermit- tence 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 in- termittence classifications to several environmental charac- teristics 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 intermit- tence classification had poor performance (cross-validated Cohen's kappa of 0.35). Both classification models iden- tified significant environment-intermittence associations, in particular with regional-scale climate patterns and also catch- ment area, shape and slope. However, we suggest that the fair-to-poor performance of the classification models is be- cause intermittence is also controlled by processes operat- ing at scales smaller 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 inter- mittent, the flow-regime model predicted 39 % of all river segments to be intermittent, indicating that the gauging sta- tion network under-represents intermittent river segments in France. Predictions of regional patterns in flow intermittence provide useful information for applications including envi- ronmental flow setting, estimating assimilative capacity for contaminants, designing bio-monitoring programs and mak- ing preliminary predictions of the effects of climate change on flow intermittence.