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1. Removal of Fecal Indicator Bacteria by River Networks

   https://doi.org/10.3390/w14040617  

   Huang, Tao; Wollheim, Wilfred M.; Jones, Stephen H. (February 2022, Water)

   Fecal contamination is a significant source of water quality impairment globally. Aquatic ecosystems can provide an important ecosystem service of fecal contamination removal. Understanding the processes that regulate the removal of fecal contamination among river networks across flow conditions is critical. We applied a river network model, the Framework for Aquatic Modeling in the Earth System (FrAMES-Ecoli), to quantify removal of fecal indicator bacteria by river networks across flow conditions during summers in a series of New England watersheds of different characteristics. FrAMES-Ecoli simulates sources, transport, and riverine removal of Escherichia coli (E. coli). Aquatic E. coli removal was simulated in both the water column and the hyporheic zone, and is a function of hydraulic conditions, flow exchange rates with the hyporheic zone, and die-off in each compartment. We found that, at the river network scale during summers, removal by river networks can be high (19–99%) with variability controlled by hydrologic conditions, watershed size, and distribution of sources in the watershed. Hydrology controls much of the variability, with 68–99% of network scale inputs removed under base flow conditions and 19–85% removed during storm events. Removal by the water column alone could not explain the observed pattern in E. coli, suggesting that processes such as hyporheic removal must be considered. These results suggest that river network removal of fecal indicator bacteria should be taken into consideration in managing fecal contamination at critical downstream receiving waters. 

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2. Estimating a Directed Tree for Extremes

   Ngoc Mai Tran, Johannes Buck (October 2023, Journal of the Royal Statistical Society Series B Methodological)

   The Extremal River Problem has emerged as a flagship problem for causal discovery in extreme values of a network. The task is to recover a river network from only extreme flow measured at a set V of stations, without any information on the stations' locations. We present QTree, a new simple and efficient algorithm to solve the Extremal River Problem that performs very well compared to existing methods on hydrology data and in simulations. QTree returns a root-directed tree and achieves almost perfect recovery on the Upper Danube network data, the existing benchmark data set, as well as on new data from the Lower Colorado River network in Texas. It can handle missing data, has an automated parameter tuning procedure, and runs in time O(n |V|^2), where n is the number of observations and |V| the number of nodes in the graph. Furthermore, we prove that the QTree estimator is consistent under a Bayesian network model for extreme values with noise. We also assess the small sample behaviour of QTree through simulations and detail the strengths and possible limitations of QTree. 

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3. A Web-based System for Contagion Simulations on Networked Populations

   Ferdousi, T.; Kishore, A.; Machi, L.; Machi, D.; Kuhlman, C.; Ravi, S.S. (October 2022, IEEE eScience)

   Motivated by a wide range of applications, research on agent-based models of contagion propagation over networks has attracted a lot of attention in the literature. Many of the available software systems for simulating such agent-based models require users to download software, build the executable and set up execution environments. Further, running the resulting executable may require access to high performance computing clusters. Our work describes an open access software system (NetSimS) that works under the “Modeling and Simulation as a Service” (MSaaS) paradigm. It allows users to run simulations by selecting agent-based models and parameters, initial conditions, and networks through a web interface. The system supports a variety of models and networks with millions of nodes and edges. In addition to the simulator, the system includes components that allow users to choose initial conditions for simulations in a variety of ways, to analyze the data generated through simulations, and to produce plots from the data. We describe the components of NetSimS and carry out a performance evaluation of the system. We also discuss two case studies carried out on large networks using the system. NetSimS is a major component within net.science, a cyberinfrastructure for network science. Index Terms—Agent-Based Simulation, Contagion, Networks, Modeling and Simulation as a Service, Cyberinfrastructure 

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4. 1500, 500, and 450-year Sea Ice Models and Output Morphology Data, Colville River Delta, Alaska

   https://doi.org/10.18739/A2XG9FC7G  

   Cooper, Caroline; Eidam, Emily; Nienhuis, Jaap (January 2023, NSF Arctic Data Center)

   In this study, we developed a 1D Delft3D-FLOW model to simulate the temporal development of the Colville River Delta, Alaska during the most active Arctic seasons: break-up/freshet (spring), open-water (summer), and freeze-up (fall). Simulations focused on the deltaic clinoform (i.e., the cross-sectional view of a delta) and used a floating barge structure to mimic the effects of sea ice on surface waters. Delft3D simulations were coupled with modules written in MATLAB and outputs were process in MATLAB. Arctic delta morphology is impacted by seasonal sea ice coverage which significantly limits wave and river influences and alters river-to-ocean sediment dispersal. However, our knowledge of the morphologic influences of ice on delta morphology is relatively limited. To assess the role of sea ice, our study used a model to explore long-term Arctic delta development under seasonal ice, river, and wave conditions. Delta developmental simulations (spanning 1500 years) included ice-free and ice-affected cases. These cases consisted of simulations with and without waves to separately examine and compare sea ice, river, and wave impacts on Arctic delta evolution. Long-term delta developmental simulations showed ice-affected deltas form a compound clinoform morphology – a coupled subaerial and subaqueous delta separated by a subaqueous platform that resembles the shallow 2 meter platform observed offshore of Arctic deltas. In the model, the presence of nearshore sea ice and river forcing promoted sediment bypassing during break-up, forming a depocenter up to 6 km away from the river mouth and were the key drivers behind platform formation. Furthermore, six varying sea-ice characteristics (extent and thickness) were evaluated to examine effects on delta development for the first 500 years. We found that the compound clinoform morphology modulated by sea ice was heavily dependent on ice conditions, with closer and thicker sea ice produced a more elongated subaqueous platform. In addition to long-term delta developmental simulations, we examined two future scenarios (spanning 450 years) to assess future Arctic delta morphology with less seasonal sea ice coverage and larger waves as predicted by climate models. Modeled future simulations showed Arctic deltas may lose the shallow 2 meter platform feature on centennial timescales by (1) sediment infill or (2) wave erosion. This study highlights the importance of sea ice on Arctic delta morphology and the potential morphologic transitions these high-latitude deltas may experience as the Arctic continues to warm. The dataset includes an example model run file (Delft3D-FLOW and MATLAB) and output of results from the described simulations. Files include: 1) Example Delft3D-FLOW model setup file, MATLAB run script, and ice files for a 1500-year simulation. 2) Processed MATLAB structures and metadata for model results A) Long-term Delta Developmental Outputs (1500-year simulations) i) Ice-free ii) Ice-affected iii) Ice-free with waves iv) Ice-affected with waves B) Varying Sea Ice Characteristics Outputs (500-year simulations) i) Ice matrix (six simulations) C) Future Arctic Delta Scenarios Outputs (450-year simulations) i) Scenario A ii) Scenario B 

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5. Comparative Use of Hydrologic Indicators to Determine the Effects of Flow Regimes on Water Quality in Three Channels across Southern Florida, USA

   https://doi.org/10.3390/w13162184  

   Onwuka, Ikechukwu S.; Scinto, Leonard J.; Mahdavi Mazdeh, Ali (August 2021, Water)

   null (Ed.)

   This study determines the relationships between water flow and water quality in three types of channels in southern Florida, USA: Shark River Slough, Peace River, and Hillsboro Canal. Peace River most resembles a natural channel with floodplain connectivity, sinuosity, and uninhibited flow. Shark River Slough has a natural, shallow channel with sheet flow, while the Hillsboro Canal is the most modified channel due to dredging, straightening, and regulated flow. Hydrologic indices for each channel were estimated to characterize flow regimes and flow variability, while concentration–discharge (C–Q) relationships were determined to quantify the impact of flow regime on water quality. The greatest variability in flow occurred at the Hillsboro Canal, followed by Peace River and Shark River Slough. Connectivity to floodplains and long durations of low and high flow pulses at Peace River and Shark River Slough contributed to the dilution of water quality constituent concentrations at higher flows. Conversely, the channelized characteristics of the Hillsboro Canal resulted in an enrichment of constituents, especially during high flows. This study suggests that C–Q relationships can be used in canal discharge management to prevent water quality degradation of sensitive downstream wetland and aquatic ecosystems. 

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