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Continuous streamflow is critical for sustaining ecological systems and ensuring water resource security. Understanding controls on and changes in flows, including the seasonality of baseflow, is therefore an important task. Baseflow seasons have typically been investigated separately, potentially missing hydroecologically important timing changes. Instead, we apply a functional data analysis clustering approach to seasonal patterns of baseflow hydrographs for 671 catchments across Great Britain (GB). The baseflow clusters are characterized as early-, mid-, and late-season peaks. The spatial distribution of the baseflow seasonality clusters is closely connected to the baseflow index and a partition tree shows the influence of catchment topological, hydrogeological and soil factors. Changes in timing of baseflow seasonality are compared to climate seasonality. In GB there appears to be a small but systematic influence of a warming climate on baseflow seasonality via effective rainfall with a tendency for earlier seasonal baseflow peaks, with greater timing changes in snow-influenced catchments. [ABSTRACT FROM AUTHOR]

The Coln is an ecologically sensitive river in a limestone dominated catchment with no major tributaries. Three in‐line turbidity sensors were installed to monitor changes in the dynamics of suspended sediment transport from headwaters to the confluence. The aims were to (i) provide estimates of yield (t km−2 year−1) and likely drivers of suspended sediment over ~3 years and (ii) assess turbidity dynamics during storm events in different parts of the catchment. In addition, the sensor installation allowed a novel wavelet analysis based on identifying groups of turbidity peaks to estimate transport times of suspended sediment through the catchment. Yearly suspended sediment yields calculated for the upper catchment were typically less than 4 t ha−1 year−1 being similar to other UK limestone or chalk‐based rivers. Time series autoregressive integrated moving average models including explanatory variable regression modelling indicated that river discharge, groundwater level and water temperature were all significant predictors of turbidity levels throughout the year. However, high model residuals demonstrate that the models failed to capture random turbidity events. Five parts of the time series data were used to examine sediment dynamics. Plots of scaled discharge verses turbidity demonstrated that in the upper catchment, after initial suspended sediment generation, sediment quickly became limited. In the lower catchment, hysteresis analysis suggested that sediment dilution occurred, due to increasing base flow. The novel wavelet analysis demonstrated that during winter 'sediment events' identified as groups of turbidity peaks, took ~18 h to pass from the first sensor in the upper catchment to the second sensor (10.3 km downstream of sensor 1) and 24 h to the third sensor (23.3 km from sensor 1). The work demonstrates the potential for using multiple turbidity sensors and time series statistical techniques in developing greater understanding of suspended sediment dynamics and associated poor water quality in ecologically sensitive rivers. [ABSTRACT FROM AUTHOR]

Baseflow is the delayed component of streamflow from subsurface storage and is critical for sustaining ecological flows and ensuring water resource security. Understanding controls on and changes in baseflow, including the seasonality of baseflow, is therefore an important task. Baseflow seasonality has typically been investigated using pre-defined hydrological seasons. Instead, here, we investigate baseflow seasonality using data-led approaches that identify and cluster average annual baseflow hydrographs that exhibit early-, mid-, or late-seasonality. We apply a novel functional data analysis (FDA) approach and examine temporal changes in the timing of seasonal peaks in annual standardised baseflow hydrographs for 671 catchments across Great Britain (GB). We use data from the CAMELS-GB dataset for the period 1976 to 2015 split into two twenty-year time blocks (1976-1995 and 1996-2015). Functional clustering enables groups of catchments with similar distributions between time blocks to be identified. Changes in baseflow seasonality with time are investigated by identifying and characterising catchments that move between functional clusters and time blocks, while analysis of the timing of baseflow peaks provides additional temporal resolution to the early-, mid-, and late-season discretisation generated by the functional clustering. The analysis shows that baseflow seasonality has a spatio-temporally coherent structure across GB and catchment characteristics are a first order control on the form of seasonal baseflow clusters. Changes in climate are inferred to be the first order control on changes in baseflow seasonality between the two time blocks. A change to earlier seasonal baseflow in snowmelt influenced catchments in upland northern GB is associated with systematic warming across the two time blocks, and a move to earlier (later) baseflow seasonality across lowland southern, central and eastern (western, north-western and northern) catchments in GB is associated with earlier (later) seasonality in effective rainfall (defined as precipitation minus potential evapotranspiration). These changes in baseflow seasonality in non-snow-melt influenced catchments are consistent with the proposition that, in temperate environments, climate warming leading to vegetation phenology-mediated changes in evapotranspiration may be modifying the timing of hydrological cycles. [ABSTRACT FROM AUTHOR]