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Inundation dynamics coupled with seasonal information is critical to study the wetland environment. Analyses based on remotely sensed data are the most effective means to monitor and investigate wetland inundation dynamics. For the first time, this study deployed an automated thresholding method to quantify and compare the annual inundation characteristics in dry and wet seasons in the Everglades, using Landsat imagery in Google Earth Engine (GEE). This research presents the long-term time series maps from 2002 to 2021, with a comprehensive spatiotemporal depiction of inundation. In this paper, we bridged the research gap of space-time analysis for multi-season inundation dynamics, which is urgently needed for the Everglades wetland. Within a GIS-based framework, we integrated statistical models, such as Mann–Kendall and Sen's Slope tests, to track the evolutionary trend of seasonal inundation dynamics. The spatiotemporal analyses highlight the significant differences in wet and dry seasons through time and space. The stationary or permanent inundation is more likely to be distributed along the coastal regions (Gulf of Mexico and Florida Bay) of the Everglades, presenting a warning regarding their vulnerability to sea level rise. [ABSTRACT FROM AUTHOR]

The Florida Everglades, the largest subtropical wetland in North America, is in the midst of one of the most comprehensive and expensive environmental restoration efforts in history. Over the past 150 years, the Everglades has suffered substantial degradation due to massive drainage projects, polluting agricultural practices, and urban population growth. Decades of scientific investigation have shown that phosphorus (P) pollution is a primary driver of this environmental decline. This paper reviews how and why specific P‐management goals and strategies have been adopted in support of Everglades restoration, focusing on the often‐contentious process for converting science into restoration policies and standards. We synthesize current P‐management successes, failures, and tradeoffs, including the challenge of balancing multiple hydrologic and water quality restoration goals with the priorities and values of a diverse group of stakeholders. We then highlight promising future directions for Everglades P policy and propose questions to help guide the discussion of future restoration priorities and research needs in this and other complex social–ecological systems. The overall goals of this review are thus twofold: (1) to support an in‐depth understanding of the past, present, and potential future of P management approaches in this globally unique social–ecological system; and (2) to provide a broader framework for understanding how the coevolution of science and policy can support or undermine large‐scale ecosystem restoration. [ABSTRACT FROM AUTHOR]

This special issue of Ecological Engineering provides an overview of research within the Everglades Stormwater Treatment Areas (STAs) over the past decade to understand the ecology and the biogeochemical processes that affect phosphorus (P) retention in these constructed wetlands. This research was established within the South Florida Water Management District's Restoration Strategies Science Plan (RSSP). The RSSP was developed in 2012, updated in 2018, and produced a total of 21 studies. The goal of RSSP research is improve understanding of the factors contributing to P retention, to support management of the STAs to attain and sustain a stringent outflow total P concentration goal (i.e., the Water Quality Based Effluent Limit or WQBEL) and to maintain the wetland plant communities used to achieve this goal. Compliance with the WQBEL will reduce P loads to the Everglades to support restore and maintain this special ecosystem. This synthesis paper presents an overview of the STAs and their purpose and then summarizes the findings from the publications included in this special issue as well as previous STA related research. From this synthesis, a list of potential management options to enhance P retention in the STAs is presented. • Stormwater Treatment Areas (STAs) built to reduce P in runoff entering the Everglades. • STA discharge must meet strict low P concentration limits. • P biogeochemistry research conducted to support management of the STAs. • P removed by particle settling, biogeochemical processes and plant uptake. • Fauna excretion, bioturbation, and internal loads substantially affect P retention. [ABSTRACT FROM AUTHOR]

Managed treatment wetlands technology is now used around the world to treat wastewater and stormwater by removing nutrients and other contaminants to obtain a desired water quality. In this paper we present a brief review of a large-scale application of the nature-based technology known as stormwater treatment areas (STAs). These STAs were constructed to treat agricultural and urban runoff to reduce outflow total phosphorus (TP) concentrations to <20 μg P L−1, which is required to protect downstream water quality and preserve the remaining Everglades ecosystem. Five STAs with a total area of approximately 25,000 ha were built at strategic locations to reduce TP loads to the Everglades Protection Area. For the past three decades, these Everglades STAs have done remarkable job by 70 to 85% TP load reduction, with an average outflow TP concentrations of 15-40 μg P L−1. In this Everglades STAs special issue, we present research findings on the influence of both external and internal drivers influencing STA performance and potential adaptive management strategies to enhance treatment efficiency to further reduce outflow TP concentrations. • Introduction of the Everglades STAs – largest constructed treatment wetland network in the world. • Everglades STAs serve as 'kidneys' of the Everglades ecosystem by reducing phosphorus loads to downstream waterbodies. • Phosphorus loading is one of the key drivers regulating treatment efficiency STAs. [ABSTRACT FROM AUTHOR]

Traditional economic forecasts had consistently underestimated the hypergrowth of South Florida and its need for freshwater from the 1970s through the 1990s. It was hypothesized that the continued rapid growth of urban and farm water use into the 2000–2030 period would undermine efforts to restore the Everglades. To test this hypothesis, the corresponding author had hybridized two widely used regional economic modeling tools: the static, single-period Impact Analysis for Planning (IMPLAN); and the dynamic multiperiod Regional Economic Modeling Inc. (REMI) to forecast population and water use for the period from 2010–2030. In the present paper, these early forecasts are compared to actual census and water use counts for 2010 and 2015. Some of these early forecasts are found to be surprisingly accurate while others seriously overshoot the mark. The on-target forecasts validate the basic hybrid model while the other "deviant" forecasts measure the success of the radical antidrought policies and the region's economic reaction to the financial collapse. This retrospective provides a new metric for measuring actual changes in the paradigm of water consumption. [ABSTRACT FROM AUTHOR]

The comment by Julian (2020) criticizes aspects of our paper, "Nitrogen enrichment, altered stoichiometry, and coral reef decline at Looe Key, Florida Keys, USA." The comment begins by misrepresenting our extensive literature review, while providing no justification for the claim of a "skewed reading." Julian's critique focused on methods of data handling, statistics, and spatial awareness, which we demonstrate in every case to be either irrelevant or incorrect. We provide additional supporting data that refute these claims. For example, Julian criticized the removal of data points below the method detection limits (MDLs), but when these points are included, the results do not change. Further, Julian criticized our removal of outliers, but so few points were excluded that it did not change the results of the statistical analyses. Julian also misinterpreted the methods of our correlation and stepwise regression analyses but did not dispute the Kruskal–Wallis tests of our 30-year dataset that revealed significant decadal changes. Julian's closing paragraph is replete with misinformation and demonstrates a lack of understanding as to how increased freshwater flows associated with Everglades Restoration have led to a worsening of algal blooms and coral decline in the Florida Keys National Marine Sanctuary (FKNMS). This comment represents a smokescreen to confuse the scientific community about the physical connectivity of the Everglades basin and the FKNMS. Past water management policies based on politics, not sound science, have caused irreparable and ongoing environmental damage to sensitive coral reef communities in the FKNMS. [ABSTRACT FROM AUTHOR]

The ability to simulate wetland phosphorus (P) concentration dynamics in the low-P domain (<20 μg/L of total P) has been poor. This paper develops a new model algorithm to describe P removal in Stormwater Treatment Areas (STAs) for Everglades restoration. It includes a performance review of previous low-P models. Analysis of inflow-outflow pulse responses at daily and monthly time steps in the STAs revealed surprisingly counterintuitive dynamics (lowest outflow concentrations occurring during highest flow events). Analysis of internal P concentration and flux data (from within STAs) informed new flow-dependent P removal and zero-order return flux formulations. The resulting parsimonious model is based directly on these two core equations. Calibration and testing are presented, using four independent datasets (6–36 month duration) including outflow P time series and internal water treatment profiles. This data-driven approach significantly improved dynamic simulations (R2 = 0.4–0.7) and identified the determinant role of internal P loading in low-P wetlands. • To date, no model has been able to capture very low wetland P concentration dynamics (<20 μg/L). • One reason is that observed pulse response dynamics in this range are rather counterintuitive. • Recent internal wetland data provides new insight on how these dynamics are generated. • A new parsimonious model captures observed data (R2 = 0.4–0.7) including internal water P profiles. • A major conclusion is that internal P loading is a main determinant of low-P wetland concentrations. [ABSTRACT FROM AUTHOR]

Kenaf (Hibiscus cannabinus L.) is a warm-season annual plant grown in the past for the bast fiber. In the last decades, this crop has been re-evaluated for many alternative industrial uses of its biomass (i.e., production of biofuel, biocomposite materials, bioproducts). In this paper, the interaction effects of sowing time (May and June) and plant population (P20 and P40, 20 and 40 plants m-2, respectively) on yield and some biomass parameters were analysed in two cultivars of kenaf (Tainung 2-TAI, and Everglades 41-EVER), in a two-year experiment in semi-arid environment, under irrigation. The aim of this paper was to assess the potential of this crop as an energy or industrial feedstock, in south Mediterranean environment where was never cultivated. Overall, plants from late sowing (June) were smaller and with less node, those at high plant density (P40) were thinner. In both seasons, plants of TAI were taller than those of EVER. Plant weight was greater in P20, and an overall significant negative correlation was found between plant weight and actual plant density (r = −0.76 **). The shift of sowing time reduced significantly the final dry biomass. Crop productivity did not change with plant density, however a higher percent bark corresponded to P40 in both years, cultivars, and sowing times, A simple model was developed to simulate and predict the course of LAI and dry biomass (AGB) with time, using field dataset of 2004, for calibration, and dataset of 2005, for validation. The minor response of LAI to plant population in 2005 led to a low accuracy of model approximation. This result suggests that other variables that are not considered in the model, may influence LAI. Nevertheless, the overall AGB model approximation of observed value was accurate. Concluding, the results revealed that biomass productivity is more influenced by sowing time than by plant density. However, plant population has been found to regulate the proportion of bark/core layers, with important implications for industrial (energy and pulp production) purposes. Further improvements on the simple model developed, e.g., including soil water nitrogen balances submodels, may be done, in order to explore the possibility of using the model under different conditions of soil water content and nitrogen fertilization. • Sowing time and plant density effects were studied in two cultivars of kenaf. • Dry biomass yield was significantly reduced shifting sowing from May to June. • Dry biomass did not change with plant density (20 or 40 plants m-2). • The % incidence of bark on core weight was greater in plants at higher density. • A simple model was developed to simulate and predict LAI and biomass in kenaf. [ABSTRACT FROM AUTHOR]

The Everglades is a complex, multiwetland ecosystem that is heavily managed to meet often-competing flood control, water supply, and environmental demands. Using objective measures to balance these demands through operational protocols has always been a challenge in the multibillion-dollar restoration plans for the ecosystem. Physically based models have been the primary tools for planning efforts but for such a complex system, they are laborious and computationally intensive. Development of optimal operations based on iterative runs of these models is a great challenge. This paper presents an inverse modeling framework for formal optimization suited for wetland system operations that helps overcome such limitations. Labor-intensive and computation-intensive physically representative models are emulated in each individual wetland area using an autoregressive artificial neural network with exogenous variables. Using prescribed inflow, outflow, and meteorological input data, such hydrologic model emulators aided by a dimension-reduction technique provide targeted spatial and temporal predictions for water level (stage) within each area of the Everglades, while excluding computation processes that are intensive but insignificant to the predictions. This computer software uses the augmented Lagrangian genetic algorithm technique (subject to linear and nonlinear constraints) to steer predictions of stage spatial variability within individual wetlands towards corresponding desired goals (including restoration targets). In the augmented Lagrangian genetic algorithm, flow releases are coded as the decision variables to be optimized subject to budget, intrahydraulic conveyance, flow capacity, and upstream storage constraints. Optimization is performed by dividing and solving a sequence of subproblems using the genetic algorithm procedures of initialization, selection, elitism, crossover, and mutation. As part of the process, Lagrangian and penalty parameters are updated, and optimization terminates when certain stopping criteria are met. Applying the technique reported in this paper to a specific Everglades restoration plan (the River of Grass Project) showed a sound hydrologic model emulator prediction when compared to the physical model for all wetland areas. Feeding optimal releases predicted by the computer software into a physical model showed equal or better matching of the restoration target with different release patterns compared to that of the physical model base run scenario. Results show that hydraulic conveyance limitations play a significant role in Everglades restoration. Also, results show that employing an adversity tradeoff matrix presented multiple so-called optimal solutions with different optimization weights and a powerful negotiation matrix. [ABSTRACT FROM AUTHOR]

Despite substantial investments in large-scale ecosystem restoration efforts, scientific information to inform restoration decision-making is often lacking. This gap between science and practice has been attributed to a number of factors, including the inherent complexity of environmental challenges, financial considerations, as well as a lack of communication between scientists, practitioners, and the public. Restoration of the Everglades (Florida, U.S.A.) is a multi-billion dollar state-federal partnership that entails restoring the flow of clean freshwater from Lake Okeechobee to the remnant Everglades, while ensuring flood protection and water supply for millions of people. We describe the role of a boundary organization, The Everglades Foundation, in coordinating, synthesizing, and communicating science related to the restoration of the Florida Everglades. Through the SERES (Synthesis of Everglades Restoration and Ecosystem Services) project, The Everglades Foundation established a credible team of scientific experts to address ecosystem responses to a suite of restoration scenarios, involving varying degrees of water storage and decompartmentalization. To ensure relevance of synthesis products, managers and practitioners from key agencies and organizations were consulted from the outset to understand the science management questions that were stalling on-the-ground action. Project results were conveyed in multiple formats to appeal to policymakers, practitioners, and scientists. For nonscientists, outcomes of four restoration scenarios on numerous ecosystem elements were compared to the base condition using sophisticated and accessible graphics and a nontechnical writing style. For scientists, additional information was made available through white papers, presentations, and peer-reviewed manuscripts explaining the science behind the syntheses, presented within this issue. [ABSTRACT FROM AUTHOR]

Although considered a sink of nutrients, limited information exists to verify phosphorus (P) and nitrogen (N) retention in drainage networks such as ditches and canals. Nutrient retention within two ditches on a cattle ranch in the greater Everglades region was measured using in-situ mesocosms. Phosphorus and N concentrations of water inside the mesocosms were increased or decreased to evaluate the effect of P and N concentration on P and N flux across the sediment-water interface. Ditch sediments possess high P retention capacity which was related to aluminum and iron contents. Soluble reactive P (SRP) retention over seven days varied between 13 and 55% of the starting water column concentration, though retention was significant after one day (p = 0.035). Significant P release, although observed only at one site, does indicate the potential for the ditch to be a source of P to downstream locations. The P uptake and release were greater and more rapid in a ditch with organic sediment and emergent macrophytes compared to a ditch with a mineral substrate. P retention over time was rate-limited by diffusion and sediment pore-water exchange. Nitrogen transformation processes were unsubstantial, possibly because in warm sub-tropical Florida most nitrate is denitrified in the presence of an energy source. Several empirical P models predicted (r 2 > 0.90) P retention based on the known water column SRP concentrations and hydraulic residence time. The residence time of the site (0.46 and 0.11 days for the two ditches) is not long enough to significantly reduce P loads passing through the ditches under the current drainage regime. Delaying the drainage by increased water retention as a voluntary Best Management Practice (BMP) or Payment for Environmental Services (PES) program can help increase the residence time to reduce P leaving the ranch. Although these results are derived from a cattle ranch, similar benefits can be expected for drainage ditches in other agricultural systems such as agronomic (e.g. sugarcane) or horticultural (e.g. citrus, vegetable) crops, and the models presented in this paper may be useful for basin-scale water quality management. [ABSTRACT FROM AUTHOR]

Eutrophication is a widespread global scale pollution problem. Agricultural areas are generally the main contributors to eutrophication, whereas sewage and industrial discharges, which usually receive some treatment prior to discharge, are a secondary source. This is mostly the case of the ultra-oligotrophic Florida Everglades, where natural water sources are often enriched by nutrients from large-scale industrial agricultural stormwater runoff. Remediation of these agricultural waters cannot be conducted with the usual environmental engineering solutions, and in this context ecological engineering approaches such as constructed wetlands are much more suitable. Moreover, these wetlands provide other ecosystem services such as carbon sequestration or habitat provisioning. In this paper we have implemented a mechanistic phosphorus model into a time-space-dependent mathematical simulation platform (COMSOL Multiphysics™) which has been calibrated with wetland mesocosm data. Subsequently we have evaluated different characteristics of constructed wetland physical elements such as internal walls and baffles, different types of inlets, parallel and series operation, and increase in hydraulic retention time (HRT) to study total phosphorus (TP) removal performance and to improve efficiency. Simulation results indicate that wetland mesocosm soils released dissolved organic phosphorus which was washed out together with the effluent, making very difficult to attain a concentration lower than a target of 10 μg TP L−1, as required to protect the Everglades. Simulations showed that the design based on combination of the bottom inlet together with parallel operation extensively improves efficiency. Target TP concentrations can be achieved with this design together with an increase on 25% of hydraulic retention time. With this study we demonstrate the usefulness of the model for detailed designs, opening the door for its use in field scale applications. Image 1 • Pollution caused by agricultural drainage waters is a worldwide problem. • Constructed wetlands are very suitable to prevent agricultural drainage pollution. • A complex model was developed to study phosphorus removal. • The model is very useful for detailed designs and field scale applications. [ABSTRACT FROM AUTHOR]

Global Navigation Satellite System-Reflectometry (GNSS-R) is a remote sensing technique that uses scattered navigation signals opportunistically for science applications. The Cyclone Global Navigation Satellite System (CYGNSS) is the first science-driven GNSS-R satellite mission. Although the CYGNSS mission is motivated and designed to better observe weather processes, the data are also useful for other applications, including surface hydrology. This paper aims to demonstrate that CYGNSS has a capability for frequent, high-resolution observations of the wetland dynamics across a wide range of timescales in the tropics. Using matched estimates of water depth from the Everglades Depth Estimation Network (EDEN), we develop methods for mapping inundation over the South Florida Everglades wetland region using CYGNSS data. CYGNSS enables inundation mapping at rapid timescales throughout the diverse Everglades ecosystem, and the data could be complementary to those of well-established observational platforms. The strengths of GNSS-R could be leveraged with the strengths of other techniques to enable studies of wetlands dynamically at short timescales. • Scattered navigation signals from land surfaces are sensitive to surface water. • Ground-based data used to train, validate spaceborne inundation mapping method. • Constellation of spacecraft (CYGNSS) captures short time scale processes. [ABSTRACT FROM AUTHOR]