First dynamic model of dissolved organic carbon derived directly from high-frequency observations through contiguous storms

Exploring hydrological controls on dissolved organic carbon export dynamics in a typical flash flood catchment using a process-based model

The dynamics of dissolved organic carbon (DOC) export from headwater catchments are of critical importance for the global carbon balance and are driven by complex runoff processes. Most previous studies have used statistical relationships between runoff and DOC concentration to estimate DOC export dynamics. Thus, the coupling mechanisms between runoff generation and DOC export dynamics at the process level were obscured in the fitting parameters and have rarely been addressed. In this study, high-frequency (hourly) discharge and DOC export from a typical flash flood experimental headwater catchment with an area of 1.8 km2 were simulated using a process-based model (INCA-C). The results showed that the INCA-C model successfully captured the hourly dynamics of both discharge and DOC concentrations with a Nash-Sutcliffe efficiency (NSE) of 0.47-0.81 and 0.28-0.70 among moderate events and 0.81-0.85 and 0.19-0.90 among extreme events, respectively. The DOC was exported with distinct concentration dynamics, fluxes, and contributions from the four flow pathways under different storm intensities. At higher intensities, the DOC fluxes were exported by subsurface flows, particularly from shallow organic soil, with greater peaks and shorter time-to-peaks. Exported DOC is primarily sourced from subsurface runoff from the mineral layer (73 %-77 %) during moderate events, whereas it is primarily sourced from subsurface runoff from the organic layer (61 %-79 %) during extreme events. The two contrasting contributions suggest that hydrological pathway controls and DOC dynamic patterns can shift owing to runoff generation influenced by storm intensity. The distinct and variable controls of different flow pathways on DOC export highlight the need to explain the role of hydrology in regulating DOC storm exports through process-based modelling.

A novel assessment considering spatial and temporal variations of water quality to identify pollution sources in urban rivers

It’s vital to explore critical indicators when identifying potential pollution sources of urban rivers. However, the variations of urban river water qualities following temporal and spatial disturbances were highly local-dependent, further complicating the understanding of pollution emission laws. In order to understand the successional trajectory of water qualities of urban rivers and the underlying mechanisms controlling these dynamics at local scale, we collected daily monitoring data for 17 physical and chemical parameters from seven on-line monitoring stations in Nanfeihe River, Anhui, China, during the year 2018. The water quality at tributaries were similar, while that at main river was much different. A seasonal ‘’turning-back” pattern was observed in the water quality, which changed significantly from spring to summer but finally changed back in winter. This result was possibly regulated by seasonally-changed dissolved oxygen and water temperature. Linear mixed models showed that the site 2, with the highest loads of pollution, contributed the highest (β = 0.316, P < 0.001) to the main river City Water Quality Index (CWQI) index, but site 5, the geographically nearest site to main river monitoring station, did not show significant effect. In contrast, site 5 but not site 2 contributed the highest (β = 0.379, P < 0.001) to the main river water quality. Therefore, CWQI index was a better index than water quality to identify potential pollution sources with heavy loads of pollutants, despite temporal and spatial disturbances at local scales. These results highlight the role of aeration in water quality controlling of urban rivers, and emphasized the necessity to select proper index to accurately trace the latent pollution sources.

Diurnal Patterns in Solute Concentrations Measured with In Situ UV-Vis Sensors: Natural Fluctuations or Artefacts?

In situ spectrophotometers measuring in the UV-visible spectrum are increasingly used to collect high-resolution data on stream water quality. This provides the opportunity to investigate short-term solute dynamics, including diurnal cycling. This study reports unusual changes in diurnal patterns observed when such sensors were deployed in four tropical headwater streams in Kenya. The analysis of a 5-year dataset revealed sensor-specific diurnal patterns in nitrate and dissolved organic carbon concentrations and different patterns measured by different sensors when installed at the same site. To verify these patterns, a second mobile sensor was installed at three sites for more than 3 weeks. Agreement between the measurements performed by these sensors was higher for dissolved organic carbon (r > 0.98) than for nitrate (r = 0.43–0.81) at all sites. Higher concentrations and larger amplitudes generally led to higher agreement between patterns measured by the two sensors. However, changing the position or level of shading of the mobile sensor resulted in inconsistent changes in the patterns. The results of this study show that diurnal patterns measured with UV-Vis spectrophotometers should be interpreted with caution. Further work is required to understand how these measurements are influenced by environmental conditions and sensor-specific properties.

Five Aluminum Seasonality Regimes Identified in Chronically Acidified Rivers of Nova Scotia

Despite reductions in acidic deposition, high freshwater Al concentrations continue to threaten acidified ecosystems across the northern hemisphere. Seasonally elevated Al concentrations may pose a particular threat to freshwater organisms. Despite this threat, there is a lack of understanding about the timing and drivers of seasonal Al fluctuations. Here, we address this knowledge gap by identifying seasonal patterns of Al and their drivers in 16 rivers across Nova Scotia, Canada. We identify five distinct Al regimes with different timing of seasonally elevated Al concentrations. Regimes are distinguished by correlation strength and direction between Al and base cations, total organic carbon, turbidity, and discharge. Most notably, regimes are distinguished by a gradient of Al-base cation decoupling as Ca and Mg concentration approaches 1.4 mg L^-1 and 0.6 mg L^-1, respectively. Seasonally elevated Al concentrations exceeded the 0.1-0.2 mg L^-1 World Health Organization drinking water guidelines in all regimes, and inorganic monomeric Al is projected to exceed the 15 μg L^-1 threshold for aquatic health in most rivers. This research highlights the complexity of seasonal Al dynamics and the importance of understanding seasonal variation of Al to quantify the impact of Al on human health, water treatment, and aquatic organisms.

Using in-situ optical sensors to study dissolved organic carbon dynamics of streams and watersheds: A review

It is important to understand how dissolved organic carbon (DOC) is processed and transported through stream networks because DOC is a master water quality variable in aquatic ecosystems. High-frequency sampling is necessary to capture important, rapid shifts in DOC source, concentration, and composition (i.e. quality) in streams. Until recently, this high-frequency sampling was logistically difficult or impossible. However, this type of sampling can now be conducted using in-situ optical measurements through long-term, field-deployable fluorometers and spectrophotometers. The optical data collected from these instruments can quantify both DOC concentration and composition properties (e.g., specific ultra-violet absorbance at 254nm, spectral slope ratio, and fluorescence index). Previously, the use of these sensors was limited to a small number of specialized users, mainly in Europe and North America, where they were used predominantly in marine DOC studies as well as water treatment and management infrastructure. However, recent field demonstrations across a wide range of river systems reveals a large potential for the use of these instruments in freshwater environments, heightening interest and demand across multiple environmental research and management disciplines. Hence, this review provides an up-to-date synthesis on 1) the use of spectroscopy as a diagnostic tool in stream DOC studies, 2) the instrumentation, its applications, potential limitations and future considerations, and 3) the new watershed DOC research directions made possible via these in-situ optical sensors.

Real-time monitoring of nutrients and dissolved organic matter in rivers: Capturing event dynamics, technological opportunities and future directions

Excessive riverine nutrient concentrations threaten aquatic ecosystem structure and functioning and can pose substantial risks to human health. Robust monitoring strategies are therefore required to generate reliable estimates of river nutrient loads and to improve understanding of the catchment processes that drive nutrient fluxes. Furthermore, these data are vital for prediction of future trends under changing environmental conditions and thus the development of appropriate mitigation measures. In recent years, technological developments have led to an increase in the use of in-situ nutrient analysers, which enable measurements at far higher temporal resolutions than can be achieved with discrete sampling and subsequent laboratory analysis. In this paper, we review the principles underlying the key techniques used for in-situ nutrient monitoring and highlight both the advantages, opportunities and challenges associated with high-resolution sampling programs. We then suggest how adaptive monitoring strategies, comprising several different temporal sample frequencies, controlled by one or more 'trigger variables' (e.g. river stage, turbidity, or nutrient concentration), can advance our understanding of catchment nutrient dynamics while simultaneously overcoming many of the practical and economic challenges encountered in typical in-situ river nutrient monitoring applications. We present examples of short-term variability in river nutrient dynamics, driven by complex catchment behaviour, which support our case for the development of monitoring systems that can adapt in real-time to rapid changes in environmental conditions. Finally, we suggest future research directions based on emerging technologies in this field.