Analysis of the interannual variability of annual daily extreme water levels in the St Lawrence River and Lake Ontario from 1918 to 2010

We compared the interannual variability of annual daily maximum and minimum extreme water levels in Lake Ontario and the St Lawrence River (Sorel station) from 1918 to 2010, using several statistical tests. The interannual variability of annual daily maximum extreme water levels in Lake Ontario is characterized by a positive long‐term trend showing two shifts in mean (1929–1930 and 1942–1943) and a single shift in variance (in 1958–1959). In contrast, for the St Lawrence River, this interannual variability is characterized by a negative long‐term trend with a single shift in mean, which occurred in 1955–1956. As for annual daily minimum extreme water levels, their interannual variability shows no significant long‐term change in trend. However, for Lake Ontario, the interannual variability of these water levels shows two shifts in mean, which are synchronous with those for maximum water levels, and a single shift in variance, which occurred in 1965–1966. These changes in trend and stationarity (mean and variance) are thought to be due to factors both climatic (the Great Drought of the 1930s) and human (digging of the Seaway and construction of several dams and locks during the 1950s). Despite this change in means and variance, the four series are clearly described by the generalized extreme value distribution. Finally, annual daily maximum and minimum extreme water levels in the St Lawrence and Lake Ontario are negatively correlated with Atlantic multidecadal oscillation over the period from 1918 to 2010. Copyright © 2013 John Wiley & Sons, Ltd.     

Rainfall partitioning through a mixed cedar swamp and associated C and N fluxes in Southern Ontario,Canada

Partitioning of rainfall through a forest canopy into throughfall, stemflow, and canopy interception is a critical process in the water cycle, and the contact of precipitation with vegetated surfaces leads to increased delivery of solutes to the forest floor. This study investigates the rainfall partitioning over a growing season through a temperate, riparian, mixed coniferous‐deciduous cedar swamp, an ecosystem not well studied with respect to this process. Seasonal throughfall, stemflow, and interception were 69.2%, 1.5%, and 29.3% of recorded above‐canopy precipitation, respectively. Event throughfall ranged from a low of 31.5 ± 6.8% for a small 0.8‐mm event to a high of 82.9 ± 2.4% for a large 42.7‐mm event. Rain fluxes of at least 8 mm were needed to generate stemflow from all instrumented trees. Most trees had funnelling ratios <1.0, with an exponential decrease in funnelling ratio with increasing tree size. Despite this, stand‐scale funnelling ratios averaged 2.81 ± 1.73, indicating equivalent depth of water delivered across the swamp floor by stemflow was greater than incident precipitation. Throughfall dissolved organic carbon (DOC) and total dissolved nitrogen (TDN) averaged 26.60 ± 2.96 and 2.02 ± 0.16 mg L^?1, respectively, which were ~11 and three times above‐canopy rain levels. Stemflow DOC averaged 73.33 ± 7.43 mg L^?1, 35 times higher than precipitation, and TDN was 4.45 ± 0.56 mg L^?1, 7.5 times higher than rain. Stemflow DOC concentration was highest from Populus balsamifera and TDN greatest from Thuja occidentalis trees. Although total below‐canopy flux of TDN increased with increasing event size, DOC flux was greatest for events 20–30 mm, suggesting a canopy storage threshold of DOC was readily diluted. In addition to documenting rainfall partitioning in a novel ecosystem, this study demonstrates the excess carbon and nitrogen delivered to riparian swamps, suggesting the assimilative capacity of these zones may be underestimated.     

Effect of rainfall uncertainty on the performance of physically based rainfall–runoff models

This paper analyses the effect of rain data uncertainty on the performance of two hydrological models with different spatial structures: a semidistributed and a fully distributed model. The study is performed on a small catchment of 19.6 km² located in the north‐west of Spain, where the arrival of low pressure fronts from the Atlantic Ocean causes highly variable rainfall events. The rainfall fields in this catchment during a series of storm events are estimated using rainfall point measurements. The uncertainty of the estimated fields is quantified using a conditional simulation technique. Discharge and rain data, including the uncertainty of the estimated rainfall fields, are then used to calibrate and validate both hydrological models following the generalized likelihood uncertainty estimation (GLUE) methodology. In the storm events analysed, the two models show similar performance. In all cases, results show that the calibrated distribution of the input parameters narrows when the rain uncertainty is included in the analysis. Otherwise, when rain uncertainty is not considered, the calibration of the input parameters must account for all uncertainty in the rainfall–runoff transformation process. Also, in both models, the uncertainty of the predicted discharges increase in similar magnitude when the uncertainty of rainfall input increase.     

Development of a rain‐on‐snow detection algorithm using passive microwave radiometry

Currently observed climate warming in the Arctic has numerous consequences. Of particular relevance, the precipitation regime is modified where mixed and liquid precipitation can occur during the winter season leading to rain‐on‐snow (ROS) events. This phenomenon is responsible for ice crust formation, which has a significant impact on ecosystems (such as biological, hydrological, ecological and physical processes). The spatially and temporally sporadic nature of ROS events makes the phenomenon difficult to monitor using meteorological observations. This paper focuses on the detection of ROS events using passive microwave (PMW) data from a modified brightness temperature (T_B) gradient approach at 19 and 37 GHz. The approach presented here was developed empirically for observed ROS events with coincident ground‐based PMW measurements in Sherbrooke, Quebec, Canada. It was then tested in Nunavik, Quebec, with the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR‐E). We obtained a detection accuracy of 57, 71 and 89% for ROS detection for three AMSR‐E grid cells with a maximum error of 7% when considering all omissions and commissions with regard to the total number of AMSR‐E passes throughout the winter period. Copyright © 2016 John Wiley & Sons, Ltd.     

A novel approach for estimating karst groundwater recharge in mountainous regions and its application in Switzerland

A pragmatic and simple approach for estimating the groundwater recharge of karst aquifers in mountainous regions by extrapolation of the hydrological regimes of gauged and well‐documented systems is presented. Specific discharge rates are derived using annual precipitation and spring measurements by taking into account catchment size and elevation, which are assumed to be the dominant factors. Reference sites with high data reliability are used for calibration and regional extrapolation. This is performed with normalized values employing spatial precipitation deviations and correlation with the elevation of the catchment areas. A tiered step procedure provides minimum and maximum normalized gradients for the relationship between recharge quantity and elevation for karst regions. The normalized recharge can therefore be obtained and extrapolated for any location using the spatial precipitation variability to provide an estimate of annual groundwater recharge. The approach was applied to Switzerland (approximately 7500 km² of karst terrain situated between 200 and over 4000 m a.s.l.) using annual precipitation data from meteorological stations for the years 2000 to 2011. Results show that the average recharge rates of different Swiss karst domains range from 20 to 46 L/km²s, which corresponds to an infiltration ratio between 0.6 and 0.9 of total precipitation. Despite uncertainties inherent in the approach, these results provide a benchmark for renewable karst groundwater resources in Switzerland of about 8.4 km³/year. The approach can be applied to any other mountainous karst region, that is, where a clear relationship between elevation, precipitation and recharge can be assumed. Copyright © 2015 John Wiley & Sons, Ltd.     

Evaluating suspended sediment and turbidity reduction projects in a glacially conditioned catchment through dynamic regression and fluvial process-based modelling

Elevated turbidity (T_n) and suspended sediment concentrations (SSC) during and following flood events can degrade water supply quality and aquatic ecosystem integrity. Streams draining glacially conditioned mountainous terrain, such as those in the Catskill Mountains of New York State, are particularly susceptible to high levels of T_n and SSC sourced from erosional contact with glacial-related sediment. This study forwards a novel approach to evaluate the effectiveness of stream restoration best management practices (BMPs) meant to reduce stream T_n and SSC, and demonstrates the approach within the Stony Clove sub-basin of the Catskills, a water supply source for New York City. The proposed approach is designed to isolate BMP effects from natural trends in T_n and SSC caused by trends in discharge and shifts in average T_n or SSC per unit discharge (Q) following large flood events. We develop Dynamic Linear Models (DLMs) to quantify how T_n-Q and SSC-Q relationships change over time at monitoring stations upstream and downstream of BMPs within the Stony Clove and in three other sub-basins without BMPs, providing observational evidence of BMP effectiveness. A process-based model, the River Erosion Model, is then developed to simulate natural, hydrology-driven SSC-Q dynamics in the Stony Clove sub-basin (absent of BMP effects). We use DLMs to compare the modelled and observed SSC-Q dynamics and isolate the influence of the BMPs. Results suggest that observed reductions in SSC and T_n in the Stony Clove sub-basin have been driven by a combination of declining streamflow and the installed BMPs, confirming the utility of the BMPs for the monitored hydrologic conditions.     

Using stable isotopes to understand seasonal and interannual dynamics in moisture sources and atmospheric circulation in precipitation

Stable isotopes in precipitation are useful tracers to strengthen understanding of climate change and hydrological processes. In this study, the moisture sources of 190 precipitation events in Beijing were analysed using the Hybrid Single‐particle Lagrangian Integrated Trajectory model, based on which we studied the relation between variations in precipitation δ¹⁸O and dynamics in moisture sources and atmospheric circulation in seasonal and interannual timescales. Categorization of 7 groups of moisture sources was performed, among which oceanic moisture sources presented lower δ¹⁸O in precipitation than continental moisture sources. The results show that seasonal variations of precipitation δ¹⁸O were caused by changes of moisture sources. In summer, moisture from proximal oceans dominated vapour transport to Beijing due to increasing monsoon strength and resulted in a relatively small variation of precipitation δ¹⁸O. At the interannual timescale, the variations of δ¹⁸O in summer precipitation were related to dynamics in oceanic moistures, showing depleted values when the contribution of oceanic moistures, especially the proportion of long‐distance oceanic moisture, was high. Further analysis indicated that changes of oceanic moisture sources were controlled by the strength of summer monsoons. These findings address the complexity of moisture sources in midlatitude monsoon areas and suggest that isotopic signals in precipitation have the potential to deduce changes in moisture sources and atmospheric circulation and can therefore serve for palaeoclimate reconstruction.     

Reaction softening by dissolution–precipitation creep in a retrograde greenschist facies ductile shear zone,New Hampshire,USA

We describe strain localization by a mixed process of reaction and microstructural softening in a lower greenschist facies ductile fault zone that transposes and replaces middle to upper amphibolite facies fabrics and mineral assemblages in the host schist of the Littleton Formation near Claremont, New Hampshire. Here, Na‐poor muscovite and chlorite progressively replace first staurolite, then garnet, and finally biotite porphyroblasts as the core of the fault zone is approached. Across the transect, higher grade fabric‐forming Na‐rich muscovite is also progressively replaced by fabric‐forming Na‐poor muscovite. The mineralogy of the new phyllonitic fault‐rock produced is dominated by Na‐poor muscovite and chlorite together with late albite porphyroblasts. The replacement of the amphibolite facies porphyroblasts by muscovite and chlorite is pseudomorphic in some samples and shows that the chemical metastability of the porphyroblasts is sufficient to drive replacement. In contrast, element mapping shows that fabric‐forming Na‐rich muscovite is selectively replaced at high‐strain microstructural sites, indicating that strain energy played an important role in activating the dissolution of the compositionally metastable muscovite. The replacement of strong, high‐grade porphyroblasts by weaker Na‐poor muscovite and chlorite constitutes reaction softening. The crystallization of parallel and contiguous mica in the retrograde foliation at the expense of the earlier and locally crenulated Na‐rich muscovite‐defined foliation destroys not only the metastable high‐grade mineralogy, but also its stronger geometry. This process constitutes both reaction and microstructural softening. The deformation mechanism here was thus one of dissolution–precipitation creep, activated at considerably lower stresses than might be predicted in quartzofeldspathic rocks at the same lower greenschist facies conditions.     

Differing controls on river‐ and lake‐water hydrogen and oxygen isotopic values in the western United States

Surface water oxygen and hydrogen isotopic values are commonly used as proxies of precipitation isotopic values to track modern hydrologic processes while proxies of water isotopic values preserved in lake and river sediments are used for paleoclimate and paleoaltimetry studies. Previous work has been able to explain variability in USA river‐water and meteoric‐precipitation oxygen isotope variability with geographic variables. These studies show that in the western United States, river‐water isotopic values are depleted relative to precipitation values. In comparison, the controls on lake‐water isotopic values are not well constrained. It has been documented that western United States lake‐water input values, unlike river water, reflect the monthly weighted mean isotopic value of precipitation. To understand the differing controls on lake‐ and river‐water isotopic values in the western United States, we examine the seasonal distribution of precipitation, evaporation and snowmelt across a range of seasonality regimes. We generate new predictive equations based on easily measured factors for western United States lake‐water, which are able to explain 69–63% of the variability in lake‐water hydrogen and oxygen isotopic values. In addition to the geographic factors that can explain river and precipitation values, lake‐water isotopic values need factors related to local hydrologic and climatic characteristics to explain variability. Study results suggest that the spring snowmelt runs off the landscape via rivers and streams, depleting river and stream‐water isotopic values. By contrast, lakes receive seasonal contributions of precipitation in proportion to the seasonal fraction of total annual precipitation within their watershed. Climate change may alter the ratio of snow to rain fall, affecting water resource partitioning between rivers and lakes and by implication of groundwater. Paleolimnological studies must account for the multiple drivers of water isotopic values; likewise, studies based on the isotopic composition of fossil material need to distinguish between species that are associated with rivers versus lakes. Copyright © 2010 John Wiley & Sons, Ltd.