Barnes, B. B., Hu, C., Holekamp, K. L., Blonski, S., Spiering, B. A., Palandro, D., et al. (2014). Use of Landsat data to track historical water quality changes in Florida Keys marine environments. Remote Sensing of Environment, 140, 485–496.
Abstract: Satellite remote sensing has shown the advantage of water quality assessment at synoptic scales in coastal regions, yet modern sensors such as SeaWiFS or MODIS did not start until the late 1990s. For non-interrupted observations, only the Landsat series have the potential to detect major water quality events since the 1980s. However, such ability is hindered by the unknown data quality or consistency through time. Here, using the Florida Keys as a case study, we demonstrate an approach to identify historical water quality events through improved atmospheric correction of Landsat data and cross-validation with concurrent MODIS data. After aggregation of the Landsat-5 Thematic Mapper (TM) 30-m pixels to 240-m pixels (to increase the signal-to-noise ratio), a MODIS-like atmospheric correction approach using the Landsat shortwave-infrared (SWIR) bands was developed and applied to the entire Landsat-5 TM data series between 1985 and 2010. Remote sensing reflectance (RRS) anomalies from Landsat (2 standard deviations from a pixel-specific monthly climatology) were found to detect MODIS RRS anomalies with over 90% accuracy for all three bands for the same period of 2002–2010. Extending this analysis for the entire Landsat-5 time-series revealed RRS anomaly events in the 1980s and 1990s, some of which are corroborated by known ecosystem changes due in part to changes in local freshwater flow. Indeed, TM RRS anomalies were shown to be useful in detecting shifts in seagrass density, turbidity increases, black water events, and phytoplankton blooms. These findings have large implications for ongoing and future water quality assessment in the Florida Keys as well as in many other coastal regions.
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Bastola, S., & Misra, V. (2015). Seasonal hydrological and nutrient loading forecasts for watersheds over the Southeastern United States. Environmental Modelling & Software, 73, 90–102.
Abstract: We show useful seasonal deterministic and probabilistic prediction skill of streamflow and nutrient loading over watersheds in the Southeastern United States (SEUS) for the winter and spring seasons. The study accounts for forecast uncertainties stemming from the meteorological forcing and hydrological model uncertainty. Multi-model estimation from three hydrological models, each forced with an ensemble of forcing derived by matching observed analogues of forecasted quartile rainfall anomalies from a seasonal climate forecast is used. The attained useful hydrological prediction skill is despite the climate model overestimating rainfall by over 23% over these SEUS watersheds in December–May period. The prediction skill in the month of April and May is deteriorated as compared to the period from December–March (zero lead forecast). A nutrient streamflow rating curve is developed using a log linear tool for this purpose. The skill in the prediction of seasonal nutrient loading is identical to the skill of seasonal streamflow forecast.
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Canfield Jr., D. E., Hoyer, M. V., Bachmann, R. W., Bigham Stephens, D., & Ruiz-Bernard, I. (2016). Water quality changes at an Outstanding Florida Water: influence of stochastic events and climate variability. Lake and Reservoir Management, 32(3), 297–313.
Abstract: The Santa Fe Lake System (SFS) is an Outstanding Florida Water system in northern peninsular Florida and receives special protection from governmental agencies to prevent impairment of water quality from anthropogenic activities. Since 1986, periods of sudden nutrient increases and declines have occurred along with changes in water clarity documented within a 28-year monthly database. Changes were linked to stochastic events such as an influx of gulls in 1986, the adjacent 5100-ha Dairy Road forest fire in 2007, 3 Category 3 hurricanes that struck Florida in 2004, and droughts. However, increasing trends at SFS were also observed for the yearly measured minimum water chemistry values, as were synchronous changes in these baseline conditions at other nearby lakes, suggesting the lakes were being impacted by a regional environmental factor. These changes corresponded to a period of decreasing precipitation and were related to climate variability, perhaps reflecting phase changes in the Atlantic Multidecadal Oscillation. The possible mechanism for the observed changes most likely relates to alterations in regional precipitation/evaporation rates and resulting changes in groundwater chemistry and hydrology. Long-term trends in water quality at SFS may reverse if Florida enters a long-term period of increasing precipitation.
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Harborne, A. R., Rogers, A., Bozec, Y. - M., & Mumby, P. J. (2017). Multiple Stressors and the Functioning of Coral Reefs. Annu. Rev. Mar. Sci., 9(1), 445–468.
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Havens, K. E., & Ji, G. (2018). Multiyear oscillations in depth affect water quality in Lake Apopka. Inland Waters, 8(1).
Abstract: We evaluated the effects of multiyear oscillations in depth on water quality in Lake Apopka, a shallow hypereutrophic lake on the Florida peninsula. A 17-year record of monthly data on rainfall, mean depth, total phosphorus (TP), total nitrogen (TN), chlorophyll a (Chl-a), and Secchi disk (SD) transparency was used to quantify relationships. We also looked for long-term trends because the lake has been the subject of major watershed and in-lake programs to reduce concentrations of TP and Chl-a. The dataset (1999 to 2016) included 4 high-water events and 3 drought events. We found no long-term trends in TP or SD and only minor long-term increases in Chl-a and TN. By contrast, all of the water quality attributes were significantly related to mean depth (p < 0.001). Water quality deteriorated with each drought and improved with each high-water period. The results illustrate how variation in climate can control water quality in shallow lakes with legacy nutrients in the sediments. When depth and volume are reduced during droughts in Lake Apopka, the likely scenario is a concentration of nutrients and solutes in the water column as well as greater net effects of benthivorous fish in mobilizing nutrients from the sediments and in creating turbidity. Because shallow lakes are more sensitive to changes in depth than deeper lakes, they can serve as early warning sites for effects of climate change on lake ecosystems.
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Ji, G., & Havens, K. (2019). Periods of Extreme Shallow Depth Hinder but Do Not Stop Long-Term Improvements of Water Quality in Lake Apopka, Florida (USA). Water, 11(3).
Abstract: We recently documented that during times of extreme shallow depth, there are severe effects on the water quality of one of the largest shallow lakes in the southeastern USA-Lake Apopka. During those times, total phosphorus (TP), total nitrogen (TN), chlorophyll-a (Chl-a) and toxic cyanobacteria blooms increase, and Secchi transparency (SD) declines. The lake recovers when water levels rise in subsequent years. In this paper, we determined whether extreme shallow depth events, particularly when they re-occur frequently, can stop the long-term recovery of a shallow eutrophic lake undergoing nutrient reduction programs. Apopka is an ideal location for this case study because the State of Florida has spent over 200 million USD in order to reduce the inputs of P to the lake, to build large filter marshes to treat the water, and to remove large quantities of benthivorous fish that contribute to internal P loading. We obtained data from 1985 to 2018, a period that had relatively stable water levels for nearly 15 years, and then three successive periods of extreme shallow depth, and we examined the long-term trends in TP, TN, Chl-a, and SD. There were significant decreasing trends in all of these water quality variables, and even though water quality deteriorated during periods of extreme shallow depth, and reduced the slope of the long-term trends, it did not stop the recovery. However, in the future, if climate change leads to more frequent shallow depth events, which in lakes such as Apopka, result in the concentration of water and nutrients, it is unclear whether the resilience we document here will continue, vs. the lake not responding to further nutrient input reductions.
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Julian, P., & Osborne, T. Z. (2018). From lake to estuary, the tale of two waters: a study of aquatic continuum biogeochemistry. Environ Monit Assess, 190(2).
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Kannan, N., & Anandhi, A. (2020). Water Management for Sustainable Food Production. Water, 12(3), 778.
Abstract: The agricultural community has a challenge of increasing food production by more than 70% to meet demand from the global population increase by the mid-21st century. Sustainable food production involves the sustained availability of resources, such as water and energy, to agriculture. The key challenges to sustainable food production are population increase, increasing demands for food, climate change, and climate variability, decreasing per capita land and water resources. To discuss more details on (a) the challenges for sustainable food production and (b) mitigation options available, a special issue on "Water Management for Sustainable Food Production" was assembled. The special issue focused on issues such as irrigation using brackish water, virtual water trade, allocation of water resources, consequences of excess precipitation on crop yields, strategies to increase water productivity, rainwater harvesting, irrigation water management, deficit irrigation, and fertilization, environmental and socio-economic impacts, and irrigation water quality. Articles covered several water-related issues across the U.S., Asia, Middle-East, Africa, and Pakistan for sustainable food production. The articles in the special issue highlight the substantial impacts on agricultural production, water availability, and water quality in the face of increasing demands for food and energy.
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Le, C., Hu, C., English, D., Cannizzaro, J., & Kovach, C. (2013). Climate-driven chlorophyll-a changes in a turbid estuary: Observations from satellites and implications for management. Remote Sensing of Environment, 130, 11–24.
Abstract: Significant advances have been made in ocean color remote sensing of turbidity and water clarity for estuarine waters, yet accurate estimations of chlorophyll-a concentrations (Chla in mg m− 3) has been problematic, posing a challenge to the research community and an obstacle to managers for long-term water quality assessment. Here, a novel empirical Chla algorithm based on a Red-Green-Chorophyll-Index (RGCI) was developed and validated for MODIS and SeaWiFS observations between 1998 and 2011. The algorithm showed robust performance with two independent datasets, with relative mean uncertainties of ~ 30% and ~ 50% and RMS uncertainties of ~ 40% and ~ 65%, respectively, for Chla ranging between 1.0 and > 30.0 mg m− 3. These uncertainties are comparable or even lower than those reported for the global open oceans when traditional blue-green band ratio algorithms are used.
A long-term Chla time series generated from SeaWiFS and MODIS observations showed excellent agreement between sensors and with in situ measurements. Substantial variability in both space and time was observed in the four bay segments, with higher Chla in the upper bay segments and lower Chla in the lower bay segments, and higher Chla in the wet season and lower Chla in the dry season. On average, river discharge could explain ~ 60% of the seasonal changes and ~ 90% of the inter-annual changes, with the latter mainly driven by climate variability (e.g. El Niño and La Niña years) and anomaly events (e.g. tropical cyclones). Significant positive correlation was found between monthly mean Chla anomalies and monthly Multivariate ENSO Index (MEI) (Pearson correlation coefficient = 0.43, p < 0.01, N = 147), with high Chla associated with El Niño and lower Chla associated with La Niña. Further, a Water Quality Decision Matrix (WQDM) was established from satellite observations, providing complementary and more reliable information to the existing WQDM based on less synoptic and less frequent field measurements. The satellite-derived WQDM and long-term time-series data support the decision making efforts of the management agencies that regulate nutrient discharge to the bay. Similar approaches may be established for other estuaries where field data are much more limited than for Tampa Bay.
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Majsztrik, J. C., Fernandez, R. T., Fisher, P. R., Hitchcock, D. R., Lea-Cox, J., Owen, J. S., et al. (2017). Water Use and Treatment in Container-Grown Specialty Crop Production: A Review. Water Air Soil Pollut, 228(4).
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McCarthy, M. J., Colna, K. E., El-Mezayen, M. M., Laureano-Rosario, A. E., Méndez-Lázaro, P., Otis, D. B., et al. (2017). Satellite Remote Sensing for Coastal Management: A Review of Successful Applications. Environmental Management, 60(2), 323–339.
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Obeysekera, J., Graham, W., Sukop, M. C., Asefa, T., Wang, D., Ghebremichael, K., et al. (2017). Implications of climate change on Florida's water resources. In E. P. Chassignet, J. W. Jones, V. Misra, & J. Obeysekera (Eds.), Florida's climate: Changes, variations, & impacts (pp. 83–124). Gainesville, FL: Florida Climate Institute.
Abstract: Water resources systems in Florida are unique and exhibit significant diversity in hydrogeologic characteristics and in rainfall and temperature patterns. In many parts of the state, both surface and groundwater systems are complex, highly interconnected, and any change in hydrologic drivers such as rainfall or temperature has the potential to impact the water resources of the urban, agricultural, and ecological systems. Because of this diversity, it is not possible to present a single overall outlook regarding the implications of climate change on the water resources of the state. This chapter presents brief summaries of individual studies that are available for major water resources systems in the state, which include the Everglades, the Tampa Bay region, the St. Johns River watershed, and the Suwannee River and Apalachicola River basins. Available climate models and their downscaled versions have varying degrees of bias and lack of skill that need to be considered in impact analyses. In all regions, projected changes in rainfall, temperature, and sea level may have significant impacts on water supply, water levels in environmentally sensitive areas, flood protection, and water quality.
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Uejio, C. K., Peters, T. W., & Patz, J. A. (2012). Inland lake indicator bacteria: Long-term impervious surface and weather influences and a predictive Bayesian model. Lake and Reservoir Management, 28(3), 232–244.
Abstract: Indicator bacteria (IB) that tend to occur with human pathogens provide surveillance of waterborne disease risk. This study analyzes a long-term IB surveillance record at Geneva Lake, Wisconsin, United States. The first research objective examined the influence of urbanization on fecal coliform (FC) variability and change from 1975 to 2000. Over this period, impervious surface expansion mirrored escalating fecal coliform in 2 of the 3 urbanized subwatersheds; however, impervious surface construction in less-developed subwatersheds did not impact FC levels. Average FC levels were highest at the only municipality (Linn Hillside Road Creek) with beaches around the lake using septic systems. The second research objective developed a predictive model to forecast human health risk in periods without surveillance. A Bayesian framework communicated uncertainty surrounding beach management decisions. Existing water quality surveillance is limited by infrequent and relatively slow sample processing; thus, beach managers often do not have reliable water quality information. The predictive statistical model determined associations between biophysical conditions and E. coli levels from 2001 to 2008. More moisture (precipitation, lake discharge) increased E. coli levels at almost every sampling site. Statistical models may accurately forecast risk at some beaches and hydrologic conditions. In particular, statistical models for Lake Geneva and Williams Bay beaches exhibit high overall accuracy, good specificity, and modest sensitivity levels.
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Warner, L. A., Lamm, A. J., & Kumar Chaudhary, A. (2018). Florida residents' perceived role in protecting water quantity and quality through landscape practices. Landscape and Urban Planning, 171, 1–6.
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Yang, Y. - Y., & Lusk, M. G. (2018). Nutrients in Urban Stormwater Runoff: Current State of the Science and Potential Mitigation Options. Curr Pollution Rep, 4(2), 112–127.
Abstract: Stormwater runoff of nutrients from developed landscapes is recognized as a major threat to water quality degradation through cultural eutrophication, which can lead to ecosystem imbalances and harmful algal growth. This review summarizes the current state-of-knowledge on the occurrence, sources, and transport processes of nitrogen (N) and phosphorus (P) in urban stormwater runoff and describes strategies for nutrient management of urban stormwater runoff. Future research needs identified from this review are provided as well.
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