The influence of erosion sources on sediment-related water quality attributes

Suspended fine sediment has a significant impact on freshwater quality variables such as visual clarity (VC). However, freshwater quality is related to the attributes of the catchment sources contributing fine sediment to the stream network. Here, the extent to which an array of sources defined spatially according to erosion process and geological parent material may be discriminated and classified based on sediment-related water quality (SRWQ) attributes that potentially affect VC was examined. Erosion sources were sampled across two New Zealand catchments representing six types of erosion and eight parent materials. Erosion source measurements focused on particle size, organic matter content, and light beam attenuation (which is convertible to VC). The source data were analysed to: 1) evaluate source variability using a combination of Kruskal-Wallis and principal component analysis; 2) reclassify sources using a Random Forest model; and 3) demonstrate how erosion source affects VC for a range of theoretical sediment concentrations (SC) using a simple empirical model. The results indicate that SRWQ attributes show significant variation across erosion sources. The extent to which attributes differed between sources often related to whether there was a strong association between a specific erosion process and parent material. The 19 a priori source classifications were reduced to 5 distinct sources that combined erosion process and parent material (i.e., bank erosion-alluvium; mass movement-ancient volcanics; mass movement-sedimentary; surficial erosion; gully-unconsolidated sandstone). At low SC, the impact of erosion source on VC became most evident ranging from 2.6 to 5.6 m at SC of 5 g m^-3. These findings show how catchment sources of sediment, in addition to sediment concentration, influence VC, and highlight the need to consider quality as well as quantity of material supplied to stream networks when planning erosion control.

Abundance of Benthic Algae in Forestry Watersheds and the Associated Forest Cover Factors

We analyzed the abundance of benthic algae in nine forested headwater watersheds in south-central Chile to study the relationship between the variability of the abundance of benthic algae and physicochemical parameters and forest cover factors. Between 10 November 2015 and 18 August 2016, we sampled benthic algae and physicochemical parameters in the streams and characterized forest cover factors in each of the study watersheds. We found that physicochemical parameters and forest cover factors have contrasting effects on abundance. More specifically, the following observations were made: (1) maximum diversity and abundance occurred in watersheds covered with Pinus radiata, (2) seasonal ranks did not influence the abundance of benthic algae, (3) benthic algae abundance is controlled by rank dissimilarities in type of vegetation, solar radiation, volume, density age, canopy openness, native forest area, plantation area and harvested area, and (4) regression analysis of genera exhibited significant variability with physicochemical parameters (water temperature, pH, ammonium, nitrate, phosphorus, solar radiation) and forest cover factors (volume, density, age, native forest area, plantation area and harvested area); however, these effects were not seen in all genera. Factors related to the benthic algae compartment showed the highest sensitivity to forest cover, emphasizing their value as biological indicators of water quality and stream ecological integrity.

Research Trends in the Use of Remote Sensing for Inland Water Quality Science: Moving Towards Multidisciplinary Applications

Remote sensing approaches to measuring inland water quality date back nearly 50 years to the beginning of the satellite era. Over this time span, hundreds of peer-reviewed publications have demonstrated promising remote sensing models to estimate biological, chemical, and physical properties of inland waterbodies. Until recently, most of these publications focused largely on algorithm development as opposed to implementation of those algorithms to address specific science questions. This slow evolution contrasts with terrestrial and oceanic remote sensing, where methods development in the 1970s led to publications focused on understanding spatially expansive, complex processes as early as the mid-1980s. This review explores the progression of inland water quality remote sensing from methodological development to scientific applications. We use bibliometric analysis to assess overall patterns in the field and subsequently examine 236 key papers to identify trends in research focus and scale. The results highlight an initial 30 year period where the majority of publications focused on model development and validation followed by a spike in publications, beginning in the early-2000s, applying remote sensing models to analyze spatiotemporal trends, drivers, and impacts of changing water quality on ecosystems and human populations. Recent and emerging resources, including improved data availability and enhanced processing platforms, are enabling researchers to address challenging science questions and model spatiotemporally explicit patterns in water quality. Examination of the literature shows that the past 10–15 years has brought about a focal shift within the field, where researchers are using improved computing resources, datasets, and operational remote sensing algorithms to better understand complex inland water systems. Future satellite missions promise to continue these improvements by providing observational continuity with spatial/spectral resolutions ideal for inland waters.

Autotrophic nitrate uptake in river networks: A modeling approach using continuous high-frequency data

High-frequency sensor measurements enable calculation of continuous autotrophic nitrate uptake rate based on its intrinsic relationship with gross primary production (GPP). The spatiotemporally available data offer prospects to advance process understandings across scales. We used continuous 15-min data (2011-2015) from a forest upstream reach and an agricultural downstream reach of the Selke River, Germany. Based on the high-frequency data, we developed a parsimonious approach for regionalizing the autotrophic uptake rate, considering effects of global radiation and riparian shading. For networked modeling, we integrated this approach into the fully distributed mesoscale hydrological nitrate model (mHM-Nitrate). Daily GPP-based uptake rate calculations showed distinct seasonal patterns and ranges in the agricultural and forest streams (mean values were 80.9 and 15.5 mgNm^-2d^-1, respectively). Validation in the two streams showed acceptable performance (R² = 0.47 and 0.45, respectively) and spatial transferability of the regionalization approach, given its parsimony. Networked modeling results showed high spatiotemporal variability in nitrate transport and uptake throughout the river network. The magnitude of gross uptake increased, whereas uptake efficiency decreased significantly along stream order. Longitudinal analysis in the main stem of the Selke River revealed that riparian shading and inter-annual hydrochemical variations strongly influenced daily dynamics of the uptake efficiency. This study provides a parsimonious and transferable procedure for regionalizing in-stream autotrophic nitrate uptake based on high-frequency data at reach scale. Integrating this approach in the mHM-Nitrate model allows detailed nitrate transport and in-stream uptake processes to be investigated throughout river networks.

Resilience of river flow regimes

Landscape and climate alterations foreshadow global-scale shifts of river flow regimes. However, a theory that identifies the range of foreseen impacts on streamflows resulting from inhomogeneous forcings and sensitivity gradients across diverse regimes is lacking. Here, we derive a measurable index embedding climate and landscape attributes (the ratio of the mean interarrival of streamflow-producing rainfall events and the mean catchment response time) that discriminates erratic regimes with enhanced intraseasonal streamflow variability from persistent regimes endowed with regular flow patterns. Theoretical and empirical data show that erratic hydrological regimes typical of rivers with low mean discharges are resilient in that they hold a reduced sensitivity to climate fluctuations. The distinction between erratic and persistent regimes provides a robust framework for characterizing the hydrology of freshwater ecosystems and improving water management strategies in times of global change.

Light-mediated thresholds in stream-water nutrient composition in a river network

The elemental composition of solutes transported by rivers reflects combined influences of surrounding watersheds and transformations within stream networks, yet comparatively little is known about downstream changes in effects of watershed loading vs. in-channel processes. In the forested watershed of a river under a mediterranean hydrologic regime, we examined the influence of longitudinal changes in environmental conditions on water-column nutrient composition during summer base flow across a network of sites ranging from strongly heterotrophic headwater streams to larger, more autotrophic sites downstream. Small streams (0.1-10 km2 watershed area) had longitudinally similar nutrient concentration and composition with low (approximately 2) dissolved nitrogen (N) to phosphorus (P) ratios. Abrupt deviations from this pattern were observed in larger streams with watershed areas > 100 km2 where insolation and algal abundance and production rapidly increased. Downstream, phosphorus and silica concentrations decreased by > 50% compared to headwater streams, and dissolved organic carbon and nitrogen increased by approximately 3-6 times. Decreasing dissolved P and increasing dissolved N raised stream-water N:P to 46 at the most downstream sites, suggesting a transition from N limitation in headwaters to potential P limitation in larger channels. We hypothesize that these changes were mediated by increasing algal photosynthesis and N fixation by benthic algal assemblages, which, in response to increasing light availability, strongly altered stream-water nutrient concentration and stoichiometry in larger streams and rivers.