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Estuaries, in particular freshwater estuaries, provide valuable economic, social, and ecological services, but their ecosystems are often heavily stressed. Located in the Laurentian Great Lakes basin, Green Bay is a large freshwater estuary and a prominent example of a degraded ecosystem due to intensive human interventions and rapid development. Excessive amounts of contaminants and nutrients were discharged to the bay by inflowing tributaries for almost half a century, while in contrast Green Bay's seasonal‐, morphological‐, and physically‐restricted mixing is unable to export a significant portion of those materials out of the bay, that is, Green Bay behaves as an efficient retention basin for the Lake Michigan. Consequently, several environmental and public health‐related issues have risen in Green Bay and turned the lower bay into an area of environmental concern since the 1980s. To address these challenges, restoration programs were developed, including the development of monitoring programs, scientific research, and remedial action plans. There is a consensus that accelerated loading rates of contaminated and nutrient‐rich sediments are a major driver of the environmental crisis in the bay, yet the fate and transport patterns of Green Bay sediments are not clearly understood. While field observations in Green Bay are season‐limited and costly, advanced computing techniques provided opportunities to refine our understanding of sediment dynamics in this estuarine system. This review of existing knowledge on Green Bay sediment processes can help to better understand the interplay between sediments, and physical/biogeochemical activities in estuarine systems and contributes conceptually to the restoration of degraded aquatic ecosystems. This article is categorized under:Science of Water > Hydrological ProcessesScience of Water > Water QualityWater and Life > Stresses and Pressures on Ecosystems [ABSTRACT FROM AUTHOR]

One of the largest freshwater estuarine systems on Earth, Green Bay receives freshwater runoff from its land watershed and cold-water intrusions from Lake Michigan. Southern Green Bay is a designated area of concern (AOC) due to ecosystem degradation, contaminated sediments, and poor water quality. Successful restoration of aquatic systems requires a clear understanding of their circulation and thermal regimes. Using a state-of-the-art numerical ocean model, this study examines the effect of variability in tributary inflows and the related lake intrusions on the circulation and thermal regime in Green Bay and on the mass and heat fluxes between lower- and upper–Green Bay areas. Our findings indicate that tributaries influence the circulation and thermal regime, locally and throughout the bay, and that the impact is more significant in hydrologically wet years. Model simulations showed evidence of small net transport out of lower Green Bay. This analysis of the simultaneous effects of tributary flows and lake intrusions in Green Bay can contribute to understanding the dynamics of freshwater estuaries and improve the planning of future restoration projects. [ABSTRACT FROM AUTHOR]

Highlights • Joint analysis of human-landscape and climate drivers of lake shrinkage was performed. • Climate change is not the main cause of water level decline in Lake Urmia. • Agricultural vegetation expansion since 2000 has increased upstream water consumption. • Increased water consumption is the likely driver of Lake Urmia desiccation. Abstract Lake Urmia—a shallow endemic hypersaline lake in northwest Iran—has undergone a dramatic decline in its water level (WL), by about 8 m, since 1995. The primary cause of the WL decline in Lake Urmia has been debated in the scientific literature, regarding whether it has been predominantly driven by atmospheric climate change or by human activities in the watershed landscape. Using available climate, hydrological, and vegetation data for the period 1981–2015, this study analyzes and aims to explain the lake desiccation based on other observed hydro-climatic and vegetation changes in the Lake Urmia watershed and classical exploratory statistical methods. The analysis accounts for the relationships between atmospheric climate change (precipitation P, temperature T), and hydrological (soil moisture SM, and WL) and vegetation cover (VC; including agricultural crops and other vegetation) changes in the landscape. Results show that P, T, and SM changes cannot explain the sharp decline in lake WL since 2000. Instead, the agricultural increase of VC in the watershed correlates well with the lake WL change, indicating this human-driven VC and associated irrigation expansion as the dominant human driver of the Lake Urmia desiccation. Specifically, the greater transpiration from the expanded and increasingly irrigated agricultural crops implies increased total evapotranspiration and associated consumptive use of water (inherently related to the irrigation and water diversion and storage developments in the watershed). Thereby the runoff from the watershed into the lake has decreased, and the remaining smaller inflow to the lake has been insufficient for keeping up the previous lake WL, causing the observed WL drop to current conditions. [ABSTRACT FROM AUTHOR]

Summary It is a common practice to conduct the water budget or water balance analysis in a given area within a specified time in order to investigate the balance between the inputs and outputs of the water system. Such an analysis can be used for water management and water allocation in a designated study area. Due to appearance of an error in water balance equation because of difficulty in accurate estimation of its individual components, the main objective of the current paper was to apply a set of fuzzy coefficients to the components of the water balance equation in order to reduce this error. The fuzzy coefficients reflect the uncertainty and imprecision in evaluating each component, and minimize the overall error of the water balance equation. These coefficients are adjusted by an error minimization procedure, based on fuzzy regression concepts and using available recorded data for a given study area within a specified time scale. The adjusted coefficients can effectively estimate the water balance components in the future. In this study, four different models, representing different types of fuzzy coefficients, were considered and used for annual water balance of Azghand catchment in Khorasan Razavi Province, Iran as a case study. Analysis of results showed that all models were effective in reducing water balance error in Azghand catchment. The best model reduced the error up to 79% in terms of mean absolute error compared with error in water balance equation when conventional (with no correction coefficients) water balance analysis was conducted. Moreover, the results indicated that the performance of the proposed fuzzy models was not significantly sensitive to selection of confidence level in data ( h ) and improved slightly as h increased. [ABSTRACT FROM AUTHOR]

Understanding the climatic and direct human drivers of abrupt drying of lakes in many parts of the world is a high research priority, particularly for water resources management and restoration. Lake Urmia, a shallow endemic lake in north-west Iran and one of the major saltwater bodies on earth, has undergone a dramatic decline in its water level (WL) in the past decades, resulting in about 80% of loss in the lake's water content. Different explanations have been discussed regarding the primary cause of this WL decline, including climate change, and regional human-driven land- and water-use changes. This paper reports a comprehensive study of the possible primary drivers of the lake's desiccation. Using classical exploratory statistical methods, the analysis accounts for the relationships between climate change (precipitation P, temperature T), land-surface and hydrological evolution (soil moisture SM, and WL), and vegetation cover (VC) change in the region. The latter includes human-driven changes of irrigation and expansion of agricultural lands. Observations over the period 1981-2015 indicate that the observed variability in P, T, and SM cannot explain the sharp decline in the lake WL since 2000. Instead, land-surface analysis shows VC was nearly doubled after 2000 in the Lake Urmia watershed, indicating that the WL decline is mainly associated with human-driven agricultural increase of VC. The expansion of agricultural activities in the watershed has led to increasing transpiration and hence, total evapotranspiration, decreasing the runoff during the increase in VC (inherently including irrigation, storage, and water diversion). Our results are consistent with similar cases around the world identifying human activities and interventions as the main driver of hydrologic changes, while climate change will likely increasingly contribute to such changes and their impacts in the future. [ABSTRACT FROM AUTHOR]

Aquatic macrophytes in inland lakes provide a wide range of ecosystem services. Management efforts to restore aquatic macrophytes for ecosystem recovery need comprehensive understanding of the interaction between growth and nutrient removal efficiency. In contrasting hydrodynamic environments, we examined the growth and phosphorus accrual of two common submerged (Vallisneria natans) and emergent (Acorus calamus) macrophytes. Both biomass and nutrient storage of two macrophytes were observed with significant increases during the incubation period, suggesting the great potential of selected macrophytes in suppressing eutrophication in shallow lakes. Experimental results showed very opposite impacts of flowing water on two macrophyte types. The flowing water was observed to restrain submerged macrophyte's growth and nutrient accrual, but oppositely to stimulate the emergent type. Specifically, our study demonstrated an average reduction of 33.7% in individual plant biomass and 11.4% in nutrient inventory of V. natans, but an overall increase of 27.2% in biomass and 50.0% in nutrient inventory for A. calamus in flowing-water environments. We estimated a total removal of 470-ton phosphorus assuming the complete comeback of aquatic macrophytes in Lake Taihu, as much as 22% of the annual external loading. The results from this study could inform management of aquatic macrophytes at local and lake-wide scales. [ABSTRACT FROM AUTHOR]

Bathymetric changes within estuarine and coastal waters can alter the hydrodynamic evolution of sea level and currents, which in turn can influence the ecosystem by altering material property distributions. Here we apply the Tampa Bay Coastal Ocean Model (TBCOM), with an unstructured, high-resolution grid to investigate the hydrodynamic response to bathymetric changes at the periphery of the Tampa Bay mouth over a relatively small area when compared to the whole model domain. Two separate numerical experiments are conducted with the same forcing, one using the original bathymetry and the other employing a revised synthetic bathymetry. The simulated sea level, amplitude and phase of the M2 tide, and associated currents are compared for the two experiments. Significant changes in water level (up to+/-10 cm) and current velocities (up to 20 cm/s) are found in the shallow peripheral area with the two different bathymetric data sets. These bathymetric influences are not limited to the locations where the bathymetric changes occur; they also extend to remote areas of the bay. Since Tampa Bay bathymetry varies with storm-induced sediment redistributions and human actives such as shipping channel dredging and beach nourishment, these findings emphasize the need for accurate and updated bathymetry for coastal ocean modeling and applications. • The Hydrodynamic response to bathymetric changes is investigated for Tampa Bay. • Numerical experiments are conducted using original and synthetic bathymetry. • Local changes in tides and currents are found due to bathymetric changes. • These local changes can propagate throughout the bay. • Accurate bathymetry is essential for coastal ocean modeling applications. [ABSTRACT FROM AUTHOR]

Fox River is the main source of land-based pollutants that flows into the southern Green Bay of Lake Michigan. Evaluation of water quality is normally based on time consuming and expensive in situ measurements. Remotely sensed data is an efficient alternative for field monitoring because of its spatial and temporal coverage. In this study, remote sensing imagery combined with in situ measurements of water quality were used to estimate an empirical relationship between water surface reflectance and water quality parameters including water turbidity and Total Suspended Sediment (TSS). Surface reflectance values is obtained from MODerate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua satellite. The empirical equations were derived from data over summers 2011-13 and show high correlation coefficients of equal to 0.83 and 0.87 for TSS and turbidity respectively. The validity of the proposed equations was tested for summer 2014 data. The NRMSE for prediction of measured data by the proposed equations are 0.36 and 0.3 for TSS and turbidity. Remotely sensed data was also used to produce water quality maps to improve our understanding of the spatiotemporal variations of Fox River turbid plume. The proposed approach can be extended to other coastal regions of Great Lakes and provide a framework to study pollution transportation in coastal areas. [ABSTRACT FROM AUTHOR]