The computation of flood-affected zones plays a pivotal role in risk management and land use planning. These zones can be identified by applying remote sensing techniques, digital elevation models, and implementing hydrological and hydraulic models. Remote sensing can detect changes in water surface levels over time using optical and SAR images. Digital elevation models are essential for defining the topography and morphometry of water bodies. Often, these techniques are employed to determine water levels associated with recorded events, representing a need for estimating water levels associated with different return periods. Subsequently, hydraulic models must be integrated with remote sensing techniques to create reliable models for sizing engineering projects related to return periods, which can vary from 5 to 5 years depending on the cost-benefit relation of a selected hydraulic structure. This research presents a framework for utilizing technological tools to combine remote sensing techniques with hydraulic models to correlate recorded flooding events and estimate flooding for different return periods. A case study in Santa Cruz de Lorica, Colombia, is assessed to demonstrate the advantages of the combined techniques discussed in this study. The flooding in the case study is delineated using optical and SAR images from different sources. A detailed discussion about using images applied to flooding zones is presented.

The scope of this study is to evaluate the interannual spatial variability in impacts from coastal inundation due to seawater flooding over characteristic urban settings and important residential areas of Miami (South Miami-Dade County, Florida, USA). Our analyses refer to the recent 30-year period from 1994 to 2023. The aim is to identify in great detail (i.e., at the property and building scales) all the important environmental and socioeconomic implications recognized as important factors in the sustainability of coastal environments. In this work, we also validate an updated version of the CoastFLOOD model for littoral inundation and apply it in very high resolution (dx=1-2m) throughout the densely populated urban area around Biscayne Bay, including Miami Beach areas that are more exposed to the storm surges of the Atlantic Ocean. Moreover, we investigate the long-term variability in and trends of Sea Level Elevation measured by tide-gauge records. We further assess the 50- up to 1000-year return values of Total Water Level (TWL) on the coast, and finally we map the respective inundation patterns over coastal low-land areas. New metrics of exposure to flood impacts at the building and property levels are introduced and post-processed for portrayal via high-resolution GIS maps. The main motivation of this study is to contribute to a better understanding of climatic impacts along the exposed coastal areas of Miami supporting local stakeholders’ and real-estate actors’ needs for focused research on the impacts on public plot-holdings and implications for individual properties’ prices and insurance fees.

This study evaluated the impact of citric acid (CA) to increase metal uptake Cu²⁺, Ni²⁺, and/or Pb²⁺ in duckweed (Lemna minor). Duckweed was cultured in single or mixed metal solutions (Ni²⁺ 50 ppm, Cu²⁺50 ppm, and /or Pb²⁺ 10 ppm) with different levels of CA added (no CA 0 ppm, low-level 10 ppm, middle-level 50 ppm, or high-level 100 ppm CA) for 4 weeks. Then, the plants were harvested, oven dried, and acid-digested. The amounts of metals in plants were analysed by an inductively coupled plasma optical emission spectrometer. The results indicated that duckweed successfully survived and sequestered metals from all solutions. Different levels of CA had different impacts on different metal sequestration in duckweed. For duckweed cultured in single metal solutions, 10 ppm CA already significantly increased Pb²⁺accumulation in duckweed; 50 ppm CA and 100 ppm significantly enhanced Cu²⁺ and Ni ²⁺ levels in duckweed by more than 80%. For duckweed cultured in mixed metal solutions, middle and high levels of CA significantly increased the amounts of Cu²⁺ and Ni²⁺ in duckweed. However, CA did not have a significant impact on Pb uptake in duckweed from mixed metal solutions. More research is needed to further understand the impact of CA to enhance metal uptake in plants and its application to increase phytoremediation efficiency.

The United States Army Corps of Engineers (USACE) has been assessing risks at all USACE dams over the last ten years to manage its dam portfolio in a risk-informed manner. For each risk assessment, a reservoir stage–frequency curve is estimated. This critical piece of information conveys the probability of exceeding each reservoir stage within a given year and forms the foundation for estimating probabilities of failure. Within the USACE, the stage–frequency curve is usually derived using an inflow volume-based approach that makes use of historical stream gage data and potentially rainfall-runoff data when considering extreme events. For performing a rainfall-runoff analysis, areal precipitation frequency estimates are needed. The only national scale precipitation frequency product is the NOAA Atlas 14, which is limited to a precipitation frequency of 1 in 1,000 years, or an annual exceedance probability (AEP) of 0.001. Dam safety studies routinely evaluate risks with frequencies of up to 1 in 1,000,000 years (1E-6 AEP) or less. As such, project-specific studies must be conducted to obtain the necessary point and areal precipitation frequency estimates.

Current practice in precipitation frequency for dam safety uses L-moments and areal reduction factors. However, advances in the field of extreme value theory (EVT) have demonstrated the capacity to efficiently, flexibly, and credibly model spatial extremes of pointwise maxima using a max-stable process (MSP), the infinite-dimensional analog of the multivariate extreme value distribution. Applying this, one can not only compute pointwise return level maps but also model the joint distribution and carry out more complex areal-based assessments of risk while working within the theoretically justified mathematical framework provided by EVT. The MSP-based modeling approach allows for spatially varying trend surfaces for parameters and the ability to directly estimate area-based exceedances within an EVT-based framework. Importantly, the MSP modeling approach has a strong and coherent mathematical basis for model fitting, selection, extrapolation, and uncertainty quantification.

Wastewater treatment presents a pressing global challenge, emphasizing the urgent need for more sustainable solutions. In pursuit of energy and carbon neutrality, microalgal–bacterial granular sludge (MBGS) systems have emerged as a promising alternative, leveraging the symbiotic relationship between the microalgae and bacteria within the granules in terms of gas exchange. MBGS systems offer efficient treatment but also hold promise for substantial energy savings and greenhouse gas emission reductions.

The present study aimed to ascertain the dissolved oxygen threshold required for efficient pollutant removal from coastal aquaculture, aiming at water recycling in industrial settings. To accomplish this, an MBGS system was applied to the treatment of aquaculture wastewater and underwent a gradual reduction in the airflow rate from 3.0 to 1.5 L min⁻¹ over 134 days. Regardless of the airflow rate, complete ammonium removal was consistently achieved, while lower airflow rates appeared to enhance nitrite and nitrate removal. The composition of the treated effluents met the toxicity limits for fish, enabling water reuse in aquaculture facilities. However, if the airflow rate was reduced to about 1.5 L min⁻¹, outgrowth of filamentous microorganisms started to occur on the granules' surface, compromising their efficient separation from the treated water.

Aeration typically contributes significantly to the energy consumption in wastewater treatment processes. Utilizing MBGS systems can effectively reduce the aeration needs, up to a certain level, without compromising the treatment performance, thus improving the ecological footprint of the treatment process.

Acknowledgments: This work was financed by Norte 2020 through the project 3BOOST (POCI-01-0246-FEDER-181302). The authors thank the CBQF scientific collaboration under FCT project UIDB/50016/2020.

In last decades, urban population increase led to the displacement of green spaces and natural infiltration areas, with impermeable surfaces, harming the urban water cycle. Furthermore, and due to the increased frequency and intense extreme precipitation events that are happening more frequently due to global climate change effect, traditional urban drainage systems could not effectively manage precipitation-generated surface water in such intense events, straining the city's water drainage infrastructure. In this regard, Green Roofs (GR) have been considered a sustainable engineering solution that can help to minimize drainage systems stress, due to their retention and detention capacity into their multilayer system structure, and therefore decreasing the amount of drained water that runs-off to the pluvial urban drainage network. The present work developed a simulation procedure, encompassing four roofs of different areas (150 m², 300 m², 500 m² and 1000 m²) to assess the impact of the implementation of an extensive GR with expanded clay in its composition (drainage layer and substrate), on downstream drainage systems sizing process. Characteristic runoff coefficients of different types of roof structures and also a runoff coefficient from an experimental GR tested were selected, to determine the rainwater inflow rate to drainage pipes downstream, Q. Simulation results obtained showed that expanded clay extensive GR allows lowest diameters for the drainage system downstream when compared to other roof types, leading to a potential decrease in the costs associated with the drainage network installation.

Flame retardants (FRs) are widely used to reduce the flammability of commercial products. Amongst them, Tetrabromobisphenol A (TBBPA), a persistent chemical, is used extensively in textiles, plastics, electronics, and electrical equipment. TBBPA is frequently detected in aqueous (ranging from 0.14 to 130 ng L^-1) and biological samples (up to 1.15 μg L^-1 in urine samples). Studies on TBBPA and its degradation products' toxicity have shown their impact in both humans and animals, highlighting their cytotoxic, cardiotoxic, and immunotoxic effects. The conventional treatment processes have often presented limitations, and numerous organic pollutants are highly resistant to them. In recent decades, advanced oxidation processes (AOPs) have been harnessed to efficiently eliminate organic contaminants from water and wastewater.

Therefore, the aim of the present study was to effectively remove TBBPA and its characteristic degradation products using a low-cost and practical AOP combining a widely used oxidant and solar irradiation. High degradation percentages were achieved at the first stages of the treatment, with almost complete removal of TBBPA. The efficiency of the process was also evaluated using certified bioassays that are widely used for the estimation of toxic effects in various organisms of different trophic levels. Based on the results, the treated samples did not induce toxic potential, suggesting the efficiency of using AOPs to remove persistent organic pollutants from water.

The increasing frequency and severity of drought episodes in Central Europe due to climate change pose a significant threat. Slovakia is particularly vulnerable to these changes due to its complex geography and vital agricultural lowlands. This study focuses on agricultural droughts, which harm the economy and the delicate ecosystem. Monitoring soil moisture, a key indicator of drought is challenging due to the need for in situ data. However, remote sensing data provide valuable insights from the Advanced SCATterometer (ASCAT) on the Meteorological Operational (Metop) satellites. ASCAT offers soil moisture data with daily revisit times and spatial resolutions of 12.5 and 25 km². This research calculated the Soil Water Deficit Index (SWDI) using ASCAT soil moisture data for the growing season (March–November) from 2007 to 2019 in the Danubian and Eastern Slovakian lowlands. SWDI, calculated monthly, employs the 5th percentile as the wilting point and the 95th percentile and minimum of the maximum value during the growing season as estimators of field capacity. According to the research findings, the average duration of drought events is six months in the Eastern lowlands and 5.5 months in the Danubian lowlands, occurring with a frequency of 66.7% and 65.8%, respectively. The average drought magnitude is 6.93 in the Eastern lowlands and 7.2 in the Danubian lowlands. The shortest drought duration recorded is three months (2008), and the longest is eight months (2019). Peak drought magnitude (8.16) occurred in 2011, with the lowest (5.5) in 2010. Drought intensity averaged 1.23, peaking at 2.04 in 2008 and dropping to 0.80 in 2012. The Danubian lowlands recorded the highest intensity (2.6) in 2011 and 2014, and the lowest (0.99) in 2009. These findings underscore the urgent need for adaptive strategies to protect agriculture and ecosystems from climate-change-induced drought impacts.

The study of leaks in potable water networks is crucial due to rates that can exceed 30%, resulting in significant losses and impacting finances, the environment, and water availability. Water management companies grapple with effectively managing these systems, especially in reducing leaks in aging infrastructure. Innovative technologies like mathematical modeling and computational simulation enhance leak detection and management. However, these methods often disregard system inertia, omitting variations in pressure regulating valve (PRV) operations over short periods.

This article compares traditional methodologies with an alternative approach introducing an innovative rigid water column model. This model evaluates losses considering PRV adjustments over short periods, analyzing pressure variations and leakage flow patterns. By factoring in system inertia, it provides a more accurate assessment of leak volumes, improving water management efficiency, and offering a practical tool for engineers assessing leakage volumes in real networks. The importance of considering system inertia to properly simulate PRV operations in water distribution systems is emphasized.

In essence, integrating system inertia into leak management strategies is crucial for optimizing the performance of potable water networks. Leveraging advanced modeling techniques and acknowledging the dynamic nature of water systems enable stakeholders to make informed decisions, minimizing losses, preserving resources, and ensuring water supply sustainability.

Worldwide, about one out of two people depend on groundwater resources to satisfy their drinking water needs. While groundwater is typically of a higher quality than surface water, pollution and geologic conditions may necessitate treating groundwater to meet safe water quality criteria. Groundwater is present under the earth in soil spores or the fractures of rocks. The device that we are building will help us to know about the level of groundwater through various software and by adding different processes. Many devices have been made, but this one will be a successful and efficient device for everyone. Those who are facing problems with such resources can know information about their groundwater level and act accordingly. As the process is based on steps, we will explain it in terms you can readily grasp. We utilized a hydraulic pressure sensor (a water-detection sensor) in the first phase, which will link to an electronic device called an Arduino kit (or another device such as a Nano-device), a 16-bit 12C ADC (Analog to Digital Converter), and a Max 485 module. An extra HC 12 (half-duplex wireless serial communication) module will be connected to a laptop. Power will be provided directly or through batteries. The reading from the sensor is saved on a hard disc or USB flash. On our laptop, we will obtain readings continuously. Our sensor will function and provide a reading in this manner. The value you see in the software will increase depending on the length of the wire you dip the sensor in. The wire's length is completely adjustable.