Smart Classifiers and Bayesian Inference for Evaluating River Sensitivity to Natural and Human Disturbances: A Data Science Approach

Excessive rates of channel adjustment and riverine sediment export represent societal challenges; impacts include: degraded water quality and ecological integrity, erosion hazards to infrastructure, and compromised public safety. The nonlinear nature of sediment erosion and deposition within a watershed and the variable patterns in riverine sediment export over a defined timeframe of interest are governed by many interrelated factors, including geology, climate and hydrology, vegetation, and land use. Human disturbances to the landscape and river networks have further altered these patterns of water and sediment routing. An enhanced understanding of river sediment sources and dynamics is important for stakeholders, and will become more critical under a nonstationary climate, as sediment yields are expected to increase in regions of the world that will experience increased frequency, persistence, and intensity of storm events. Practical tools are needed to predict sediment erosion, transport and deposition and to characterize sediment sources within a reasonable measure of uncertainty. Water resource scientists and engineers use multidimensional data sets of varying types and quality to answer management-related questions, and the temporal and spatial resolution of these data are growing exponentially with the advent of automated samplers and in situ sensors (i.e., “big data”). Data-driven statistics and classifiers have great utility for representing system complexity and can often be more readily implemented in an adaptive management context than process-based models. Parametric statistics are often of limited efficacy when applied to data of varying quality, mixed types (continuous, ordinal, nominal), censored or sparse data, or when model residuals do not conform to Gaussian distributions. Data-driven machine-learning algorithms and Bayesian statistics have advantages over Frequentist approaches for data reduction and visualization; they allow for non-normal distribution of residuals and greater robustness to outliers. This research applied machine-learning classifiers and Bayesian statistical techniques to multidimensional data sets to characterize sediment source and flux at basin, catchment, and reach scales. These data-driven tools enabled better understanding of: (1) basin-scale spatial variability in concentration-discharge patterns of instream suspended sediment and nutrients; (2) catchment-scale sourcing of suspended sediments; and (3) reach-scale sediment process domains. The developed tools have broad management application and provide insights into landscape drivers of channel dynamics and riverine solute and sediment export

A systematic review of studies on freshwater lakes of Ethiopia

Study Region: The study covers the freshwater lakes of Ethiopia, which constitute about 87 billion cubic meters of water volume. The lakes are facing continued ecosystem degradation threats. Study Focus: The aim of this study was to make an inventory of existing literature regarding the freshwater lakes of Ethiopia and identify gaps and priorities for future research directions. This was done through a systematic review of published scientific literature related to the lakes and characterizing each study based on different criteria. New Hydrological Insights for the Region: We found a total of 231 articles on freshwater lakes of Ethiopia published in peer-reviewed journals between 1930 and March 2021. Most studies were focused on hydrochemical and biological characteristics of lakes, with less attention to physical structure and processes (including siltation, lake morphometry and catchment biophysical characteristics). Furthermore, (a) less attention was given to the spatial and temporal dynamics of variables that affect the freshwater lakes, (b) there was limited linkage between landscape hy drological dynamics and freshwater lakes and (c) the smaller highland lakes were given limited attention. Future research should be oriented to the study of the relationship between catchment biophysical dynamics and lake hydrological characteristics

Comparative limnology of high-elevation lakes and reservoirs and their downstream effects

Reservoirs are abundant worldwide, and have profound effects on downstream flow, water chemistry, and downstream biotic communities. However, studies focused on reservoir effects rarely contrast them with lakes, which provide a comparison of natural climatic conditions without the influence of reservoir management. I compared five high-elevation lakes and five reservoirs in the Sierra Nevada, over three years which encompassed a wide range of snowpacks and flow regimes. I sampled lake, reservoir, and outlet stream water chemistry year-round across the three years to quantify seasonal effects of reservoir management. In addition to outlet water chemistry, I collected benthic macroinvertebrates from lake and reservoir outlets during the ice-free season in conjunction with discharge to determine the effects of reservoir management on downstream invertebrate communities. In 2017, I measured aquatic carbon dioxide and diffusive flux from lakes and reservoirs, beginning under ice and until the end of the ice free season, to determine potential sources of high-elevation aquatic CO2 supersaturation and characterize ice-free season CO2 temporal dynamics. Lake and reservoir nutrient concentrations did not differ in any season or year across the study period. Linear mixed models developed surface and bottom water nutrient concentrations showed that the primary controls were related to basin characteristics and snowpack, but reservoir management in the form of seasonal drawdown was a significant predictor of surface nitrate and both hypolimnetic ammonium and SRP, and indicated that reservoir water deep-release export diminished hypolimnetic nutrient accumulation. Reservoir mean annual discharge was elevated relative to lakes, which in summer and fall of 2016 and 2017 caused significantly higher export of nutrients from reservoirs. However, elevated ammonium export did not cause divergence of lake and reservoir invertebrate assemblages in those seasons, nor did they differ in any season. Other flow metrics, such as peak annual flow and the recession period, were similar between lake and reservoir outlets across years despite reservoir management. Instead, non-metric multidimensional scaling showed that invertebrate communities were related to elevated flow, but not related to low flow metrics such as baseflow and minimum flows, which were greater below reservoirs. Reservoir management altered flow regimes and nutrient flux, but interannual climactic variability was more important for determining invertebrate community structure. Carbon dioxide was supersaturated in lake and reservoir surface waters for most of the ice-free season of 2017 despite low rates of ecosystem metabolism. Diffusive flux highest for the first 40 days after ice-off, and did not differ significantly between lakes and reservoirs, but was low relative to other water bodies. Linear mixed modeling indicated that the summer CO2 concentrations were primarily related to the duration of ice cover, allowing CO2 to accumulate under ice, which indicates that annual snowpack is a major determinant of summer CO2 evasion

Spatial and temporal variations of inundation and their influence on ecosystem services from a shallow coastal lake. A case study of Soetendalsvlei in the Nuwejaars catchment, South Africa

Philosophiae Doctor - PhDEnhancing our understanding of wetland properties and the ecosystem services provided by wetlands within a dynamic landscape, is fundamental to ensuring appropriate management strategies for enhanced biodiversity and ecosystem benefits. With increased anthropogenic activities and the impacts of climatic variability, a better understanding of the factors influencing the water balance dynamics of wetlands can provide insight into how wetlands respond to change. The main aim of the research was to improve the understanding of the spatial and temporal availability of water and storage of a depression wetland in a semi-arid climate, and to relate these to ecosystem functions. As ecosystems are intricately connected to society, a secondary aim of the research was to gain insight to how wetland ecosystems, within a changing climate and landscape, provide benefits to society, and add value to human-wellbeing. Soetendalsvlei, a shallow freshwater depression, and one of the few coastal freshwater lakes of South Africa, was the focus of the research

Analysis of spatial and temporal heterogeneities of methane emissions of reservoirs by correlating hydro-acoustic with sediment parameters

The quantification of methane emissions from reservoirs is still imprecise. This study aims on the improvement of methods to understand the relevant processes causing heterogeneities. By conducting hydro-acoustic surveys, morphometric information was obtained. Seabed classification was conducted, including extensive ground truthing, which allowed spatial interpolation. It was possible to link the sediment distribution to quality parameters and to characteristics determining methane production