Mapping turbidity in the Charles River, Boston using a high-resolution satellite

Water turbidity dynamics using random forest in the Yangtze River Delta Region, China

Turbidity is a water quality indicator that is essential for the sustainable development of aquatic ecosystems and the protection of biodiversity. The turbidity of different water surfaces and its response mechanisms to regional climatic factors and human activities in the Yangtze River Delta Region (YRDR), an important rapid economic development region in China, remain poorly understood. To enhance the knowledge of turbidity variations and dominant drivers of YRDR water surfaces, a complete long-term turbidity series was obtained using Landsat images from 1990 to 2020. The results show that the turbidity trend differed from -1.3 NTU/yr to 0.7 NTU/yr in different water surfaces. Turbidity decreased significantly in the mainstream of the Yangtze River (MYR), aquaculture ponds (AP) and other water bodies, whilst increasing significantly in the medium lakes (ML) and mainstream of the Qiantang River (MQR). Meanwhile, no significant changes in turbidity were observed in the great lakes (GL) and small lakes (SL). Rather than climatic factors, urbanisation and decreasing wastewater discharge were the dominant drivers of turbidity trends during the study period. In addition, ecological engineering in AP increased water transparency. The Three Gorges Dam also decreased turbidity in MYR. Increasing turbidity in the downstream of MQR was driven by increasing seasonal water surfaces and reclamation projects near Hangzhou Bay. GL faced no significant increase in turbidity due to the offset of afforestation to urbanisation-induced turbidity increase. These findings provide important information for government decision-making for subsequent aquatic environmental protection and restoration in the YRDR.

Quantile regression illuminates the successes and shortcomings of long-term eutrophication remediation efforts in an urban river system

Despite massive financial investment in mitigation, eutrophication remains a major water quality problem and management priority. Eutrophication science-well established for lakes-is not as well developed for rivers, and scientific understanding of how rivers respond to eutrophication management is far more limited. Long-term data are required to evaluate progress, but such datasets are relatively rare for rivers. We analyzed 23 years of water quality data for the Charles River, a major urban river system in the northeastern U.S.A., to examine nutrient and phytoplankton biomass (chl-a) responses to decades of phosphorus (P) management. Using the more novel and robust approach of quantile regression, we identified statistically and ecologically significant declines in both total phosphorus (TP) and chl-a over time, but only for middle percentiles. Statistically high concentrations of TP and chl-a persist-the segments of the data of greatest concern to managers and the public-and yet this critical result is concealed by statistical tests often employed in eutrophication studies that only evaluate mean changes. TP, temperature, precipitation, and river segment jointly explain the most chl-a variation observed at the decadal scale. Spatial variation is also considerable: despite a significant decline in TP, the impounded lower river exhibits no long-term trend in chl-a and continues to experience annual blooms of harmful cyanobacteria-a lagging response comparable to that of a recovering eutrophic lake. Despite long-term successes in reducing P, chl-a, and cyanobacteria in the Charles River system, we did not detect any significant, long-term change in the attainment of statutory compliance, illustrating the protracted and complex nature of the river's response. Our analysis demonstrates the need for high-frequency, long-term water quality data to evaluate the progress of eutrophication management in urban rivers, and the utility of quantile regression for detecting critical trends in the occurrence of statistically low-frequency but ecologically high-impact events, including blooms of harmful cyanobacteria.

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.