Editor’s Choice Articles

Accurate rainfall forecasting in watersheds is of indispensable importance for predicting streamflow and flash floods. This paper investigates the accuracy of several forecasting technologies based on Wavelet Packet Decomposition (WPD) in monthly rainfall forecasting. First, WPD decomposes the observed monthly rainfall data into several subcomponents. Then, three data-based models, namely Back-propagation Neural Network (BPNN) model, group method of data handing (GMDH) model, and autoregressive integrated moving average (ARIMA) model, are utilized to complete the prediction of the decomposed monthly rainfall series, respectively. Finally, the ensemble prediction result of the model is formulated by summing the outputs of all submodules. Meanwhile, these six models are employed for benchmark comparison to study the prediction performance of these conjunction methods, which are BPNN, WPD-BPNN, GMDH, WPD-GMDH, ARIMA, and WPD-ARIMA models. The paper takes monthly data from Luoning and Zuoyu stations in Luoyang city of China as the case study. The performance of these conjunction methods is tested by four quantitative indexes. Results show that WPD can efficiently improve the forecasting accuracy and the proposed WPD-BPNN model can achieve better prediction results. It is concluded that the hybrid forecast model is a very efficient tool to improve the accuracy of mid- and long-term rainfall forecasting. Full article

In this study, an inland reservoir water quality parameters’ inversion model was developed using a back propagation (BP) neural network to conduct reservoir eutrophication evaluation, according to multi-temporal remote sensing images and field observations. The inversion model based on the BP neural network (the BP inversion model) was applied to a large inland reservoir in Jiangmen city, South China, according to the field observations of five water quality parameters, namely, Chlorophyl-a (Chl-a), Secchi Depth (SD), total phosphorus (TP), total nitrogen (TN), and Permanganate of Chemical Oxygen Demand (CODMn), and twelve periods of Landsat8 satellite remote sensing images. The reservoir eutrophication was evaluated. The accuracy of the BP inversion model for each water parameter was compared with that of the linear inversion model, and the BP inversion models of two parameters (i.e., Chl-a and CODMn) with larger fluctuation range were superior to the two multiple linear inversion models due to the ability of improving the generalization of the BP neural network. The Dashahe Reservoir was basically in the state of mesotrophication and light eutrophication. The area of light eutrophication accounted for larger proportions in spring and autumn, and the reservoir inflow was the main source of nutrient salts. Full article

The mineralization of tetracycline by electrochemical advanced oxidation processes (EAOPs) as well as the study of the toxicity of its intermediates and degradation products are presented. Electro-Fenton (EF), anodic oxidation (AO), and electro-Fenton coupled with anodic oxidation (EF/AO) were used to degrade tetracycline on carbon felt (cathode) and a sub-stoichiometric titanium oxide (Ti₄O₇) layer deposited on Ti (anode). As compared to EF and AO, the coupled EF/AO system resulted in the highest pollutant removal efficiencies: total organic carbon removal was 69 ± 1% and 68 ± 1%, at 20 ppm and 50 ppm of initial concentration of tetracycline, respectively. The effect of electrolysis current on removal efficiency, mineralization current efficiency, energy consumption, and solution toxicity of tetracycline mineralization were investigated for 20 ppm and 50 ppm tetracycline. The EF/AO process using a Ti₄O₇ anode and CF cathode provides low energy and high removal efficiency of tetracycline caused by the production of hydroxyl radicals both at the surface of the non-active Ti₄O₇ electrode and in solution by the electro-Fenton process at the cathodic carbon felt. Complete removal of tetracycline was observed from HPLC data after 30 min at optimized conditions of 120 mA and 210 mA for 20 ppm and 50 ppm tetracycline concentrations. Degradation products were elucidated, and the toxicity of the products were measured with luminescence using Microtox^® bacteria toxicity test. Full article

In 2021, heavy precipitation events in Germany have confirmed once again that pluvial flooding can cause catastrophic damage in large, medium, and small cities. However, despite several hazard-oriented strategies already in place, to date there is still a lack of integrated approaches to actually preventing negative consequences induced by heavy rainfall events. Furthermore, municipalities across the world are still learning from recent episodes and there is a general need to explore new techniques and guidelines that could help to reduce vulnerability, and enhance the resilience, adaptive capacity, and sustainability of urban environments, considering the already predicted future challenges associated with climate variability. To address this gap, this paper presents the outcomes of the research project “Heavy Rainfall Checklist for Sewer Operation” which was conducted by IKT Institute for Underground Infrastructure, to involve all the stakeholders affected by pluvial flooding within cities, and implement a series of documents that can be adopted by municipalities across the world to support organizations and their operational staff in preventing problems caused by heavy rainfall incidents. More in detail, three different rainfall scenarios have been deeply analysed, and for each of them a list of specific tasks and suggestions has been provided for aiding decision-making. Full article

The unprecedented pressure posed by a growing population on water resources generates a significant shortage between the available resources and water demand, which together with water scarcity, floods, and droughts, can affect the world population and various other consumers. On the other hand, soil resources, which represent an essential and complex environmental ecosystem, as a support for the biological cycle, source of nutrients, and water for cultivated and wild plants, forestry, etc., are a provider of raw materials, and are increasingly degrading due to unsustainable use. Since both soil and water are vital resources and support for growth and life of plants, their preservation and sustainable management have become an urgent issue for policy makers, governmental factors, academia, and stakeholders. An important question to be answered is what the disturbing factors of soil–plants–water cycles are and how their negative influence can be reduced, since they affect the quality of life and human health. This work proposes an overview on new research into the links between soil and water, and the interactions among soil, water, and plants in a changing and threatened environment, which can determine human welfare. The analysis addresses the global context of water and soil resources, factors that affect their equilibrium and dynamics, especially toxic pollutants such as heavy metals and others, and their mutual relationship with plant growth. Full article

Under-water sensing and image processing play major roles in oceanic scientific studies. One of the related challenges is that the absorption and scattering of light in underwater settings degrades the quality of the imaging. The major drawbacks of underwater imaging are color distortion, low contrast, and loss of detail (especially edge information). The paper proposes a method to address these issues by de-noising and increasing the resolution of the image using a model network trained on similar data. The network extracts frames from a video and filters them with a trigonometric–Gaussian filter to eliminate the noise in the image. It then applies contrast limited adaptive histogram equalization (CLAHE) to improvise the image contrast, and finally enhances the image resolution. Experimental results show that the proposed method could effectively produce enhanced images from degraded underwater images. Full article

Twelve beaches located in Ceuta (Spain) were studied from February to April 2019 to assess litter amounts (expressed as number of items), categories and temporal distribution. At each beach, three surveys were conducted, i.e., one per month (i.e., 36 in total). Selected beaches covered urban (7), rural (2) and remote (3) bathing areas. Plastic represented the dominant material, i.e., 35.2% of all debris, followed by glass (18.2%), pottery/ceramics (14.6%), wood (11.4%), metal (11.4%), paper/cardboard (4.8%), cloth (3.5%), rubber (0.7%), organic (0.3%) and other materials (0.1%). The Clean Coast Index was calculated to classify beaches in five categories for evaluating the cleanliness level of the coast observed at each survey: “Very Clean” (7 surveys), “Clean” (10), “Moderately Dirty” (8), “Dirty” (2) and “Extremely Dirty” (9). Litter occurrence was assessed by the Litter Grade methodology, which allowed to classify beaches in four grades: “A”: very good (0); “B”: good (4); “C”: fair (7); and “D”: poor (25). In a few surveys, some beaches were considered “good”, but their management should not be ignored because in other surveys those beaches reached fair and poor scores. Several potentially harmful litter items were related to beach users. Severe eastern storms removed litter at many of the beaches investigated and favored accumulation at others. Data analysis shows significant differences in litter abundance with respect to site, beach typology and the presence of cleaning operations but no important differences between the studied months. Rural beaches recorded the most litter, followed by urban and remote beaches. All beaches require immediate and more appropriate management actions to improve their environmental status. Full article

Poor groundwater quality in household wells is hypothesized as being a potential contributor to chronic kidney disease of unknown etiology (CKDu) in Sri Lanka. However, the influencing factors of groundwater quality in Sri Lanka are rarely investigated at a national scale. Here, the spatial characteristics of groundwater geochemistry in Sri Lanka were described. The relationships of groundwater quality parameters with environmental factors, including lithology, land use, and climatic conditions, were further examined to identify the natural and anthropogenic controlling factors of groundwater quality in Sri Lanka. The results showed that groundwater geochemistry in Sri Lanka exhibited significant spatial heterogeneity. The high concentrations of NO₃⁻ were found in the districts that have a higher percentage of agricultural lands, especially in the regions in the coastal zone. Higher hardness and fluoride in groundwater were mainly observed in the dry zone. The concentrations of trace elements such as Cd, Pb, Cu, and Cr of all the samples were lower than the World Health Organization guideline values, while some the samples had higher As and Al concentrations above the guideline values. Principal component analysis identified four components that explained 73.2% of the total data variance, and the first component with high loadings of NO₃⁻, hardness, As, and Cr suggested the effects of agricultural activities, while other components were primarily attributed to natural sources and processes. Further analyses found that water hardness, fluoride and As concentration had positive correlations with precipitation and negative correlations with air temperature. The concentration of NO₃⁻ and water hardness were positively correlated with agricultural lands, while As concentration was positively correlated with unconsolidated sediments. The environmental factors can account for 58% of the spatial variation in the overall groundwater geochemistry indicated by the results of redundancy analysis. The groundwater quality data in this study cannot identify whether groundwater quality is related to the occurrence of CKDu. However, these findings identify the coupled controls of lithology, land use, and climate on groundwater quality in Sri Lanka. Future research should be effectively designed to clarify the synergistic effect of different chemical constituents on CKDu. Full article

Microplastic disposal into riverine ecosystems is an emergent ecological hazard that mainly originated from land-based sources. This paper presents a comprehensive review on physical processes involved in microplastics transport in riverine ecosystems. Microplastic transport is governed by physical characteristics (e.g., plastic particle density, shape, and size) and hydrodynamics (e.g., laminar and turbulent flow conditions). High-density microplastics are likely to prevail near riverbeds, whereas low-density particles float over river surfaces. Microplastic transport occurs either due to gravity-driven (vertical transport) or settling (horizontal transport) in river ecosystems. Microplastics are subjected to various natural phenomena such as suspension, deposition, detachment, resuspension, and translocation during transport processes. Limited information is available on settling and rising velocities for various polymeric plastic particles. Therefore, this paper highlights how appropriately empirical transport models explain vertical and horizontal distribution of microplastic in riverine ecosystems. Microplastics interact, and thus feedback loops within the environment govern their fate, particularly as these ecosystems are under increasing biodiversity loss and climate change threat. This review provides outlines for fate and transport of microplastics in riverine ecosystems, which will help scientists, policymakers, and stakeholders in better monitoring and mitigating microplastics pollution. Full article

Water scarcity is becoming a global concern for many reasons as its consumption increases. This research aimed to analyze sustainability inequalities in the water consumption of EU countries. Descriptive statistics using data for four AQUASTAT periods (2002, 2007, 2012, and 2017), and quotients for the AQUASTAT 2017 period, were calculated using a proposed econometric model. The main results were that countries with high GPD and population showed high water stress and total water withdrawal. Countries with lower industry-value-added-to-GDP quotients were among those with higher industrial water use efficiency, while low water-services-use-efficiency quotients were associated with high services value added to GDP. Suggestions for policymakers are provided and formula application guidelines for regional-level comparisons are described. Full article

Vegetation cover is an important factor controlling erosion and sediment yield. Therefore, its effect is accounted for in both experimental and modelling studies of erosion and sediment yield. Numerous studies have been conducted to account for the effects of vegetation cover on erosion across spatial scales; however, little has been conducted across temporal scales. This study investigates changes in vegetation cover across multiple temporal scales in Eastern Cape, South Africa and how this affects erosion and sediment yield modelling in the Tsitsa River catchment. Earth observation analysis and sediment yield modelling are integrated within this study. Landsat 8 imagery was processed, and Normalised Difference Vegetation Index (NDVI) values were extracted and applied to parameterise the Modified Universal Soil Loss Equation (MUSLE) vegetation (C) factor. Imagery data from 2013–2018 were analysed for an inter-annual trend based on reference summer (March) images, while monthly imagery for the years 2016–2017 was analysed for intra-annual trends. The results indicate that the C exhibits more variation across the monthly timescale than the yearly timescale. Therefore, using a single month to represent the annual C factor increases uncertainty. The modelling shows that accounting for temporal variations in vegetation cover reduces cumulative simulated sediment by up to 85% across the inter-annual and 30% for the intra-annual scale. Validation with observed data confirmed that accounting for temporal variations brought cumulative sediment outputs closer to observations. Over-simulations are high in late autumn and early summer, when estimated C values are high. Accordingly, uncertainties are high in winter when low NDVI leads to high C, whereas dry organic matter provides some protection from erosion. The results of this study highlight the need to account for temporal variations in vegetation cover in sediment yield estimation but indicate the uncertainties associated with using NDVI to estimate C factor. Full article

The fate of microplastics (MP) in seawater is heavily influenced by the biota: the density of MP particles can be changed due to biofouling, which affects sinking, or MP can be digested by zooplankton and transferred into fecal pellets with increased sinking rate. We hypothesize that seasonal production and degradation of organic matter, and corresponding changes in the plankton ecosystem affect the MP capacity for transportation and burying in sediments in different seasons. This is simulated with a coupled hydrodynamical-biogeochemical model that provides a baseline scenario of the seasonal changes in the planktonic ecosystem and changes in the availability of particulate and dissolved organic matter. In this work, we use a biogeochemical model OxyDep that simulates seasonal changes of phytoplankton (PHY), zooplankton (HET), dissolved organic matter (DOM) and detritus (POM). A specifically designed MP module considers MP particles as free particles ($M{P}_{free}$), particles with biofouling ($M{P}_{biof}$), particles consumed by zooplankton ($M{P}_{het}$) and particles in detritus, including fecal pellets ($M{P}_{det}).$ A 2D coupled benthic-pelagic vertical transport model 2DBP was applied to study the effect of seasonality on lateral transport of MP and its burying in the sediments. OxyDep and MP modules were coupled with 2DBP using Framework for Aquatic Biogeochemical Modelling (FABM). A depletion of MP from the surface water and acceleration of MP burying in summer period compared to the winter was simulated numerically. The calculations confirm the observations that the “biological pump” can be one of the important drivers controlling the quantity and the distribution of MP in the water column. Full article

Natural occurrence and anthropogenic practices contribute to the release of pollutants, specifically heavy metals, in water over the years. Therefore, this leads to a demand of proper water treatment to minimize the harmful effects of the toxic heavy metals in water, so that a supply of clean water can be distributed into the environment or household. This review highlights several water treatment methods that can be used in removing heavy metal from water. Among various treatment methods, the adsorption process is considered as one of the highly effective treatments of heavy metals and the functionalization of adsorbents can fully enhance the adsorption process. Therefore, four classes of adsorbent sources are highlighted: polymeric, natural mineral, industrial by-product, and carbon nanomaterial adsorbent. The major purpose of this review is to gather up-to-date information on research and development on various adsorbents in the treatment of heavy metal from water by emphasizing the adsorption capability, effect of pH, isotherm and kinetic model, removal efficiency and the contact of time of every adsorbent. Full article

Recognition of sustainability issues around water resource consumption is gaining traction under global warming and land utilization complexities. These concerns increase the challenge of gaining an appropriate comprehension of the anthropogenic activities and natural processes, as well as how they influence the quality of surface water and groundwater systems. The characteristics of water resources cause difficulties in the comprehensive assessment regarding the source types, pathways, and pollutants behaviors. As the behavior and prediction of widely known contaminants in the water resources remain challenging, some new issues have developed regarding heavy metal pollutants. The main aim of this review is to focus on certain essential pollutants’ discharge from anthropogenic activities categorized based on land-use sectors such as industrial applications (solid/liquid wastes, chemical compounds, mining activities, spills, and leaks), urban development (municipal wastes, land use practices, and others), and agricultural practices (pesticides and fertilizers). Further, important pollutants released from natural processes classified based on climate change, natural disasters, geological factors, soil/matrix, and hyporheic exchange in the aquatic environment, are also discussed. Moreover, this study addresses the major inorganic substances (nitrogen, fluoride, and heavy metals concentrations). This study also emphasizes the necessity of transdisciplinary research and cross-border communication to achieve sustainable water quality using sound science, adaptable legislation, and management systems. Full article

Water is the most important resource; it is utilized largely in agricultural production and is fundamental to ensuring global food security. This study aims to assess sustainable water management interventions and their impact on the farm economy. To increase water productivity, the most important adaptations that have been proposed are high-efficiency irrigation systems, drought-resistant varieties, the substitution of water-intensive crops with less water-demanding crops, the mulching of soil, zero tillage, and all on-farm operations that can save water, especially ground water. The recent analysis utilized farm survey data from 469 representative farmers along with secondary statistics. The data were collected via a multi-stage sampling technique to ensure the availability of representative farm populations based on a comprehensive site selection criterion. The TOA-MD model estimates the adoption rate of a proposed adaptation based on net farm returns. The impact of high-efficiency irrigation systems and the substitution of high delta crops for low delta crops had a positive impact on net farm returns and per capita income, and a negative impact on farm poverty in the study area. It is recommended that policymakers consult farmer representatives about agricultural and water-related issues so that all the policies can be implemented properly. Full article

Polycyclic aromatic hydrocarbons (PAHs) were detected in different types of PAH-containing samples collected in Lake Baikal during wildfires in the adjacent areas. The set of studied samples included the following: (i) water from the upper layer (5 m); (ii) water from the surface microlayer; (iii) water from the lake tributaries; (iv) water from deep layers (400 m); and (v) aerosol from the near-water layer. Ten PAHs were detected in the water samples: naphthalene, 1-methylnaphthalene, 2-methylnaphthalene acenaphthylene, acenaphthene, fluorene, phenanthrene, fluoranthene, pyrene, and chrysene. The total PAH concentrations (ƩPAHs) were detected in a wide range from 9.3 to 160 ng/L, characterizing by seasonal, intersessional, and spatial variability. In September 2016, the ƩPAH concentration in the southern basin of the lake reached 610 ng/L in the upper water layer due to an increase in fluorene, phenanthrene, fluoranthene, and pyrene in the composition of the PAHs. In June 2019, ƩPAHs in the water from the northern basin of the lake reached 290 ng/L, with the naphthalene and phenanthrene concentrations up to 170 ng/L and 92 ng/L, respectively. The calculation of back trajectories of the atmospheric transport near Lake Baikal, satellite images, and ƩPAH concentrations in the surface water microlayer of 150 to 960 ng/L confirm the impact of wildfires on Lake Baikal, with which the seasonal increase in the ƩPAH concentrations was associated in 2016 and 2019. The toxicity of PAHs detected in the water of the lake in extreme situations was characterized by the total value of the toxic equivalent for PAHs ranging from 0.17 to 0.22 ng/L, and a possible ecological risk of the impact on biota was assessed as moderate. Full article

The present work aims to build a unique hybrid model by combining six fuzzy operator feature selection-based techniques with logistic regression (LR) for producing groundwater potential models (GPMs) utilising high resolution DEM-derived parameters in Saudi Arabia’s Bisha area. The current work focuses exclusively on the influence of DEM-derived parameters on GPMs modelling, without considering other variables. AND, OR, GAMMA 0.75, GAMMA 0.8, GAMMA 0.85, and GAMMA 0.9 are six hybrid models based on fuzzy feature selection. The GPMs were validated by using empirical and binormal receiver operating characteristic curves (ROC). An RF-based sensitivity analysis was performed in order to examine the influence of GPM settings. Six hybrid algorithms and one unique hybrid model have predicted 1835–2149 km² as very high and 3235–4585 km² as high groundwater potential regions. The AND model (ROCe-AUC: 0.81; ROCb-AUC: 0.804) outperformed the other models based on ROC’s area under curve (AUC). A novel hybrid model was constructed by combining six GPMs (considering as variables) with the LR model. The AUC of ROCe and ROCb revealed that the novel hybrid model outperformed existing fuzzy-based GPMs (ROCe: 0.866; ROCb: 0.892). With DEM-derived parameters, the present work will help to improve the effectiveness of GPMs for developing sustainable groundwater management plans. Full article

This paper presents reliability, water demand and economic analysis of rainwater harvesting (RWH) systems for eight Australian capital cities (Adelaide, Brisbane, Canberra, Darwin, Hobart, Melbourne, Perth and Sydney). A Python-based tool is developed based on a daily water balance modelling approach, which uses input data such as daily rainfall, roof area, overflow losses, daily water demand and first flush. Ten different tank volumes are considered (1, 3, 5, 10, 15, 20, 30, 50, 75 and 100 m³). It is found that for a large roof area and tank size, the reliability of RWH systems for toilet and laundry use is high, in the range of 80–100%. However, the reliability for irrigation use is highly variable across all the locations. For combined use, Adelaide shows the smallest reliability (38–49%), while Hobart demonstrates the highest reliability (61–77%). Furthermore, economic analysis demonstrates that in a few cases, benefit–cost ratio values greater than one can be achieved for the RWH systems. The findings of this study will help the Australian Federal Government to enhance RWH policy, programs and subsidy levels considering climate-sensitive inputs in the respective cities. Full article

Green roofs (GRs) and vertical greenery systems (VGSs) can contribute certain pollutants to stormwater runoff, affecting the quality of the receiving waters. The objective of this review paper is to discuss the potential impact of these systems on the quality of urban runoff. In the green building systems section, a series of materials used in greenery systems and their specific application are presented and environmentally relevant substances that could be leached out from these materials are identified as potential pollutants. After the identification of environmentally relevant pollutants that have already been measured in urban runoff and originate from these systems, an assessment of their pathways, fate, and impact in the aquatic environment is performed. Since GRs and VGSs are already considered to be solutions for stormwater quantity and quality management in urban areas, recommendations for mitigating their environmental impact through runoff are needed. It can be concluded that special focus should be placed on measures that target the pollution source, such as optimizing GR and VGS construction practices and materials used, as well as establishing appropriate decentralized stormwater treatment measures. Both of these approaches will help to reduce or even entirely avoid the emission of relevant pollutants into the aquatic environment. Full article

River vegetation radically modifies the flow field and turbulence characteristics. To analyze the vegetation effects on the flow, most scientific studies are based on laboratory tests or numerical simulations with vegetation stems on smooth beds. Nevertheless, in this manner, the effects of bed sediments are neglected. The aim of this paper is to experimentally investigate the effects of bed sediments in a vegetated channel and, in consideration of that, comparative experiments of velocity measures, performed with an Acoustic Doppler Velocimeter (ADV) profiler, were carried out in a laboratory flume with different uniform bed sediment sizes and the same pattern of randomly arranged emergent rigid vegetation. To better comprehend the time-averaged flow conditions, the time-averaged velocity was explored. Subsequently, the analysis was focused on the energetic characteristics of the flow field with the determination of the Turbulent Kinetic Energy (TKE) and its components, as well as of the energy spectra of the velocity components immediately downstream of a vegetation element. The results show that both the vegetation and bed roughness surface deeply affect the turbulence characteristics. Furthermore, it was revealed that the roughness influence becomes predominant as the grain size becomes larger. Full article

Urban agriculture (UA) plays a key role in the circular metabolism of cities, as it can use water resources, nutrients, and other materials recovered from streams that currently leave the city as solid waste or as wastewater to produce new food and biomass. The ecosystem services of urban green spaces and infrastructures and the productivity of specific urban agricultural technologies have been discussed in literature. However, the understanding of input and output (I/O) streams of different nature-based solutions (NBS) is not yet sufficient to identify the challenges and opportunities they offer for strengthening circularity in UA. We propose a series of agriculture NBS, which, implemented in cities, would address circularity challenges in different urban spaces. To identify the challenges, gaps, and opportunities related to the enhancement of resources management of agriculture NBS, we evaluated NBS units, interventions, and supporting units, and analyzed I/O streams as links of urban circularity. A broader understanding of the food-related urban streams is important to recover resources and adapt the distribution system accordingly. As a result, we pinpointed the gaps that hinder the development of UA as a potential opportunity within the framework of the Circular City. Full article

The ecological features of invasive alien species are crucial for their effective management. However, they are often lacking in newly invaded ecosystems. This is the case of the European catfish Silurus glanis L. in Lake Maggiore, where the species is present since 1990, but no scientific information is available on its ecology. To start filling this knowledge gap, 236 catfish (67 cm to 150 cm of total length) were collected, measured, and dissected for stomach content analyses from three localities and in two habitats (littoral vs. pelagic) in late autumn/early winter. The NPUE and BPUE (individuals (N) and biomass (B, in grams) per unit effort (m²), respectively) of catfish were generally higher in littoral (NPUE > 0.01; BPUE > 96) than in pelagic habitats (NPUE < 0.009; BPUE < 114), but the catfish had, on average, larger sizes in pelagic habitats. Overall, 581 individual prey items were recorded, belonging to 12 taxa. Pelagic catfish specialized their diet exclusively on three prey fish (coregonids, shad, and roach), whilst the diet of littoral catfish was more variable and dominated by crayfish, perch, and roach. These results highlighted for the first time the interaction of larger catfish with the lake’s pelagic food web, and thus possible consequences are discussed, including the potential contrasting role S. glanis may have for the lake’s fishery. Full article

In arid and semi-arid regions, it is essential to monitor the spatiotemporal variability and dynamics of vegetation. Among other provinces of Pakistan, Punjab has produced a significant number of crops. Recently, Punjab, Pakistan, has been described as a global hotspot for extremes of climate change. In this study, the soil adjusted vegetation index (SAVI), normalized vegetation difference index (NDVI), and enhanced vegetation index (EVI) were comprehensively evaluated to monitor vegetation change in Punjab, Pakistan. The time-series MODIS (Moderate Resolution Imaging Spectroradiometer) data of different periods were used. The mean annual variability of the above vegetation indices (VIs) from 2000 to 2019 was evaluated and analyzed. For each type of vegetation, two phenological metrics (i.e., for the start of the season and end of the season) were calculated and compared. The spatio-temporal image analysis of the mean annual vegetation indices revealed similar patterns and varying vegetation conditions. In the forests and vegetation areas with sparse vegetation, the EVI showed high uncertainty. The phenological metrics of all vegetation indices were consistent for most types of vegetation. However, the NDVI result had the greatest variance between the start and end of season. The lowest annual VI variability was mainly observed in the southern part of the study area (less than 10% of the study area) based on the statistical analysis of spatial variability. The mean annual spatial variability of NDVI was <20%, SAVI was 30%, and EVI ranged between 10–20%. More than 40% of the variability was observed in the NDVI and SAVI vegetation indices. Full article

There is little knowledge regarding the environmental sustainability of domestic on-site or decentralised wastewater treatment systems (DWWTS). This study evaluated six unique life cycle environmental impacts for different DWTTS configurations of five conventional septic tank systems, four packaged treatment units, and a willow evapotranspiration system. Similar freshwater eutrophication (FE), dissipated water (DW), and mineral and metal (MM), burdens were noted between the packaged and conventional system configurations, with the packaged systems demonstrating significantly higher impacts of between 18% and 56% for climate change (CC), marine eutrophication (ME), and fossils (F). At a system level, higher impacts were observed in systems requiring (i) three vs. two engineered treatment stages, (ii) a larger soil percolation trench area, and (iii) pumping of effluent. The evapotranspiration system presented the smallest total environmental impacts (3.0–10.8 lower), with net benefits for FE, ME, and MM identified due to the biomass (wood) production offsetting these burdens. Further analysis highlighted the sensitivity of results to biomass yield, operational demands (desludging or pumping energy demands), and embodied materials, with less significant impacts for replacing mechanical components, i.e., pumps. The findings highlighted the variation in environmental performance of different DWTTS configurations and indicated opportunities for design improvements to reduce their life cycle impacts. Full article

Due to numerous droughts in recent years, the amount of surface water in arid and semi-arid regions has decreased significantly, so reliance on groundwater to meet local and regional demands has increased. The Kabgian watershed is a karst watershed in southwestern Iran that provides a significant proportion of drinking and agriculture water supplies in the area. This study identified areas with karst groundwater potential using a combination of machine learning and statistical models, including entropy-SVM-LN, entropy-SVM-SG, and entropy-SVM-RBF. To do this, 384 karst springs were identified and mapped. Sixteen factors that are related to karst potential were identified from a review of the literature, and these were compiled for the study area. The 384 locations were randomly separated into two categories for training (269 location) and validation (115 location) datasets to be used in the modeling process. The ROC curve was used to evaluate the modeling results. The models used, in general, were good at determining the location of karst groundwater potential. The evaluation showed that the E-SVM-RBF model had an area under the curve of 0.92, indicating that it was most accurate estimator of groundwater potential among the ensemble models. Evaluation of the relative importance of each of the 16 factors revealed that land use, a vector ruggedness measure, curvature, and topography roughness index were the most important explainers of the presence of karst groundwater in the study area. It was also found that the factors affecting the presence of karst springs are significantly different from non-karst springs. Full article

During the breakup of river ice covers, a greater potential for erosion occurs due to rising discharge and moving ice and the highly dynamic waves that form upon ice-jam release. Consequently, suspended-sediment concentrations can increase sharply and peak before the arrival of the peak flow. Large spikes in sediment concentrations occasionally occur during the passage of sharp waves resulting from releases of upstream ice jams and the ensuing ice runs. This is important, as river form and function (both geomorphologic and ecological) depend upon sediment erosion and deposition. Yet, sediment monitoring programs often overlook the higher suspended-sediment concentrations and loads that occur during the breakup period owing to data-collection difficulties in the presence of moving ice and ice jams. In this review paper, we introduce basics of river sediment erosion and transport and of relevant phenomena that occur during the breakup of river ice. Datasets of varying volume and detail on measured and inferred suspended-sediment concentrations during the breakup period on different rivers are reviewed and compared. Possible effects of river characteristics on seasonal sediment supply are discussed, and the implications of increased sediment supply are reviewed based on seasonal comparisons. The paper also reviews the environmental significance of increased sediment supply both on water quality and ecosystem functionality. Full article

Detailed knowledge of energy and mass fluxes between land and the atmosphere are necessary to monitor the climate of the land and effectively exploit it in growing agricultural commodities. One of the important surface land fluxes is evapotranspiration, which combines the process of evaporation from the soil and that of transpiration from plants, describing the movement of water vapour from the land to the atmosphere. Accurately estimating evapotranspiration in agricultural systems is of high importance for efficient use of water resources and precise irrigation scheduling operations that will lead to improved water use efficiency. This paper reviews the major mechanistic and empirical models for estimating evapotranspiration including the Penman–Monteith, Stanghellini, Priestly–Taylor, and Hargreaves and Samani models. Moreover, the major differences between the models and their underlined assumptions are discussed. The application of these models is also reviewed for both open and closed field mediums and limitations of each model are highlighted. The main parameters affecting evapotranspiration rates in greenhouse settings including aerodynamic resistance, stomatal resistance and intercepted radiation are thoroughly discussed for accurate measurement and consideration in evapotranspiration models. Moreover, this review discusses direct evapotranspiration measurements systems such as eddy covariance and gas exchange systems. Other direct measurements appertaining to specific parameters such as leaf area index and surface leaf temperature and indirect measurements such as remote sensing are also presented, which can be integrated into evapotranspiration models for adaptation depending on climate and physiological characteristics of the growing medium. This review offers important directions for the estimation of evapotranspiration rates depending on the agricultural setting and the available climatological and physiological data, in addition to experimentally based adaptation processes for ET models. It also discusses how accurate evapotranspiration measurements can optimise the energy, water and food nexus. Full article

The emergence of SARS-CoV-2 variants of concern (VOCs) and variants of interest (VOIs) poses an increased risk to global public health and underlines the need to prioritise monitoring and research to better respond to the COVID-19 pandemic. Wastewater monitoring can be used to monitor SARS-CoV-2 spread and to track SARS-CoV-2 variants. A long read amplicon sequencing approach based on the Oxford Nanopore technology, targeting the spike protein, was applied to detect SARS-CoV-2 variants in sewage samples collected in central Italy on April 2021. Next-generation sequencing was performed on three pooled samples. For variant identification, two approaches–clustering (unsupervised) and classification (supervised)–were implemented, resulting in the detection of two VOCs and one VOI. Key mutations of the Alpha variant (B.1.1.7) were detected in all of the pools, accounting for the vast majority of NGS reads. In two different pools, mutations of the Gamma (P.1) and Eta (B.1.525) variants were also detected, accounting for 22.4%, and 1.3% of total NGS reads of the sample, respectively. Results were in agreement with data on variant circulation in Italy at the time of wastewater sample collection. For each variant, in addition to the signature key spike mutations, other less common mutations were detected, including the amino acid substitutions S98F and E484K in the Alpha cluster (alone and combined), and S151I in the Eta cluster. Results of the present study show that the long-read sequencing nanopore technology can be successfully used to explore SARS-CoV-2 diversity in sewage samples, where multiple variants can be present, and that the approach is sensitive enough to detect variants present at low abundance in wastewater samples. In conclusion, wastewater monitoring can help one discover the spread of variants in a community and early detect the emerging of clinically relevant mutations or variants. Full article

Climate change is threatening water security in water-scarce regions across the world, challenging water management policy in terms of how best to adapt. Transformative new approaches have been proposed, but management policies remain largely the same in many instances, and there are claims that good current management practice is well adapted. This paper takes the case of the Murray–Darling Basin, Australia, where management policies are highly sophisticated and have been through a recent transformation in order to critically review how well adapted the basin’s management is to climate change. This paper synthesizes published data, recent literature, and water plans in order to evaluate the outcomes of water management policy. It identifies several limitations and inequities that could emerge in the context of climate change and, through synthesis of the broader climate adaptation literature, proposes solutions that can be implemented when basin management is formally reviewed in 2026. Full article

The presence of impermeable surfaces in urban areas hinders natural drainage and directs the surface runoff to storm drainage systems with finite capacity, which makes these areas prone to pluvial flooding. The occurrence of pluvial flooding depends on the existence of minimal areas for surface runoff generation and concentration. Detailed hydrologic and hydrodynamic simulations are computationally expensive and require intensive resources. This study compared and evaluated the performance of two simplified methods to identify urban pluvial flood-prone areas, namely the fill–spill–merge (FSM) method and the topographic wetness index (TWI) method and used the TELEMAC-2D hydrodynamic numerical model for benchmarking and validation. The FSM method uses common GIS operations to identify flood-prone depressions from a high-resolution digital elevation model (DEM). The TWI method employs the maximum likelihood method (MLE) to probabilistically calibrate a TWI threshold ($\tau$) based on the inundation maps from a 2D hydrodynamic model for a given spatial window (W) within the urban area. We found that the FSM method clearly outperforms the TWI method both conceptually and effectively in terms of model performance. Full article

The SIMDualKc model was applied to evaluate the crop water use and the crop coefficient (K_c) of an irrigated olive grove (Olea europaea L.) located in Sicily, Italy, using experimental data collected from two crop seasons. The model applies the FAO56 dual K_c approach to compute the actual crop evapotranspiration (ET_{c act}) and its components, i.e., the actual tree transpiration (T_{c act}), obtained through the basal crop coefficient (K_cb), and soil evaporation according to an evaporation coefficient (K_e). Model calibration was performed by minimizing the difference between the predicted T_{c act} and the observed daily tree transpiration measured with sap flow instrumentation (T_{SF field}) acquired in 2009. The validation was performed using the independent data set of sap flow measurements from 2011. The calibrated K_cb was equal to 0.30 for the initial and non-growing season stages, 0.42 for the mid-season, and 0.37 for the end season. For both seasons, the goodness-of-fit indicators relative to comparing T_{SF field} with the simulated T_{c act} resulted in root mean square errors (RMSE) lower than 0.27 mm d⁻¹ and a slope of the linear regression close to 1.0 (0.94 ≤ b₀ ≤ 1.00). The olive grove water balance simulated with SIMDualKc produced a ratio between soil evaporation (E_s) and ET_{c act} that averaged 39%. The ratio between actual (ET_{c act}) and potential crop evapotranspiration (ET_c) varied from 84% to about 99% in the mid-season, indicating that the values of ET_{c act} are close to ET_c, i.e., the adopted deficit irrigation led to limited water stress. The results confirm the suitability of the SIMDualKc model to apply the FAO56 dual K_c approach to tree crops, thus assessing the water use of olives and supporting the development of appropriate irrigation management tools that are usable by farmers. A different way to estimate K_cb is based on the approach suggested in 2009 by Allen and Pereira (A&P), which involves the measured fraction of ground covered (shaded) by the crop and the height of the trees. Its application to the studied grove produced the mid-season K_cb values ranging from 0.40–0.45 and end-season K_cb values ranging from 0.35–0.40. The comparison between the A&P-computed T_{c act A&P} and T_{SF field} shows RMSE values ranging from 0.27 to 0.43 mm d⁻¹, which demonstrates the adequacy of the latter approach for parameterizing water balance models and for irrigation scheduling decision making. Full article

Groundwater is a precious freshwater resource heavily relied upon by agricultural activities in many parts of the world, and especially by countries with limited water resources located in arid regions. Groundwater resources are under severe pressures due to population increase, urbanisation and socio-economic development, with potential for causing long-term threats to human life and natural ecosystems. This study attempts to investigate the impacts of local and regional climatic trends, and establish key forcing functions that have changed local groundwater resources. The main questions answered through this study include: Are these changes beneficial or detrimental? If they are detrimental, what is the future outlook for impacts on the ecosystem? What are the corrective actions needed to avert the long-term risks in arid environments? In view of this, the methodology developed in this study focuses on a joint time-series statistical analysis using ground data as well as Gravity Recovery and Climate Experiment (GRACE) satellite data. Results show a substantial depletion in the groundwater thickness (0.24 ± 0.20 cm/year) during the period of observation (2002–2020). Long-term temperature data indicates that the annual mean temperature increased significantly by 1.02 °C between 1987 and 2016, while total rainfall exhibited a slight decreasing trend. In addition to groundwater extraction, fluctuations in monthly rainfall, soil moisture, evapotranspiration and relative humidity support the groundwater thickness reduction of GRACE datasets. The use of desalinated water and wastewater reuse in the agriculture sector may reduce the pressure on groundwater resources. Optimization, adaptation and mitigation in the EWF nexus will further improve the sustainability of the EWF resources. Full article

Concern is widely being published that the occurrence of toxic cyanobacteria is increasing in consequence of climate change and eutrophication, substantially threatening human health. Here, we review evidence and pertinent publications to explore in which types of waterbodies climate change is likely to exacerbate cyanobacterial blooms; whether controlling blooms and toxin concentrations requires a balanced approach of reducing not only the concentrations of phosphorus (P) but also those of nitrogen (N); how trophic and climatic changes affect health risks caused by toxic cyanobacteria. We propose the following for further discussion: (i) Climate change is likely to promote blooms in some waterbodies—not in those with low concentrations of P or N stringently limiting biomass, and more so in shallow than in stratified waterbodies. Particularly in the latter, it can work both ways—rendering conditions for cyanobacterial proliferation more favourable or less favourable. (ii) While N emissions to the environment need to be reduced for a number of reasons, controlling blooms can definitely be successful by reducing only P, provided concentrations of P can be brought down to levels sufficiently low to stringently limit biomass. Not the N:P ratio, but the absolute concentration of the limiting nutrient determines the maximum possible biomass of phytoplankton and thus of cyanobacteria. The absolute concentrations of N or P show which of the two nutrients is currently limiting biomass. N can be the nutrient of choice to reduce if achieving sufficiently low concentrations has chances of success. (iii) Where trophic and climate change cause longer, stronger and more frequent blooms, they increase risks of exposure, and health risks depend on the amount by which concentrations exceed those of current WHO cyanotoxin guideline values for the respective exposure situation. Where trophic change reduces phytoplankton biomass in the epilimnion, thus increasing transparency, cyanobacterial species composition may shift to those that reside on benthic surfaces or in the metalimnion, changing risks of exposure. We conclude that studying how environmental changes affect the genotype composition of cyanobacterial populations is a relatively new and exciting research field, holding promises for understanding the biological function of the wide range of metabolites found in cyanobacteria, of which only a small fraction is toxic to humans. Overall, management needs case-by-case assessments focusing on the impacts of environmental change on the respective waterbody, rather than generalisations. Full article

In this work, the recent trends in the application of the sulfate radical-based advanced oxidation processes (SR-AOPs) for the treatment of wastewater polluted with emerging contaminants (ECs) and pathogenic load were systematically studied due to the high oxidizing power ascribed to these technologies. Additionally, because of the economic benefits and the synergies presented in terms of efficiency in ECs degradation and pathogen inactivation, the combination of the referred to AOPs and conventional treatments, including biological processes, was covered. Finally, the barriers and limitations related to the implementation of SR-AOPs were described, highlighting the still scarce full-scale implementation and the high operating-costs associated, especially when solar energy cannot be used in the oxidation systems. Full article

The Soyang Dam, the largest multipurpose dam in Korea, faces water resource management challenges due to global warming. Global warming increases the duration and frequency of days with high temperatures and extreme precipitation events. Therefore, it is crucial to accurately predict the inflow rate for water resource management because it helps plan for flood, drought, and power generation in the Seoul metropolitan area. However, the lack of hydrological data for the Soyang River Dam causes a physical-based model to predict the inflow rate inaccurately. This study uses nearly 15 years of meteorological, dam, and weather warning data to overcome the lack of hydrological data and predict the inflow rate over two days. In addition, a sequence-to-sequence (Seq2Seq) mechanism combined with a bidirectional long short-term memory (LSTM) is developed to predict the inflow rate. The proposed model exhibits state-of-the-art prediction accuracy with root mean square error (RMSE) of 44.17 m³/s and 58.59 m³/s, mean absolute error (MAE) of 14.94 m³/s and 17.11 m³/s, and Nash–Sutcliffe efficiency (NSE) of 0.96 and 0.94, for forecasting first and second day, respectively. Full article

The objective of the presented study was to develop a high-temporal-resolution stochastic rainwater harvesting (RWH) model for assessing the dual benefits of RWH: potable water savings and runoff reduction. Model inputs of rainfall and water demand are used in a stochastic manner, maintaining their natural pattern, while generating realistic noise and temporal variability. The dynamic model solves a mass-balance equation for the rainwater tank, while logging all inflows and outflows from it for post-simulation analysis. The developed model can simulate various building sizes, roof areas, rainwater tank volumes, controlled release policies, and time periods, providing a platform for assessing short- and long-term benefits. Standard passive rainwater harvesting operation and real-time control policies (controlled release) are demonstrated for a 40-apartment building with rainfall data typical for a Mediterranean climate, showing the system’s ability to supply water for non-potable uses, while reducing runoff volumes and flows, with the latter significantly improved when water is intentionally released from the tank prior to an expected overflow. The model could be used to further investigate the effects of rainwater harvesting on the urban water cycle, by coupling it with an urban drainage model and simulating the operation of a distributed network of micro-reservoirs that supply water and mitigate floods. Full article

Land use land cover (LULC) change is the crucial driving force that affects the hydrological processes of a watershed. The changes of LULC have an important influence and are the main factor for monitoring the water balances. The assessment of LULC change is indispensable for sustainable development of land and water resources. Understanding the watershed responses to environmental changes and impacts of LULC classes on hydrological components is vigorous for planning water resources, land resource utilization, and hydrological balance sustaining. In this study, LULC effects on hydrological parameters of the Nashe watershed, Blue Nile River Basin are investigated. For this, historical and future LULC change scenarios in the Nashe watershed are implemented into a calibrated Soil and Water Assessment Tool (SWAT) model. Five LULC scenarios have been developed that represent baseline, current, and future periods corresponding to the map of 1990, 2005, 2019, 2035, and 2050. The predicted increase of agricultural and urban land by decreasing mainly forest land will lead till 2035 to an increase of 2.33% in surface runoff and a decline in ground water flow, lateral flow, and evapotranspiration. Between 2035 and 2050, a gradual increase of grass land and range land could mitigate the undesired tendency. The applied combination of LULC prognosis with process-based hydrologic modeling provide valuable data about the current and future understanding of variation in hydrological parameters and assist concerned bodies to improve land and water management in formulating approaches to minimize the conceivable increment of surface runoff. Full article

Rapid urbanization, aging infrastructure, and changes in rainfall patterns linked to climate change have brought considerable challenges to water managers around the world. Impacts from such drivers are likely to increase even further unless the appropriate actions are put in place. Floods, landslides, droughts and water pollution are just a few examples of such impacts and their corresponding consequences are in many cases devastating. At the same time, it has become a well-accepted fact that traditional (i.e., grey infrastructure) measures are no longer effective in responding to such challenges. Nature-based solutions (NBS) have emerged as a new response towards hydro-meteorological risk reduction and the results obtained to date are encouraging. However, their application has been mainly in the area of water quantity management with few studies that report on their efficiency to deal with water quality aspects. These solutions are based on replicating natural phenomena and processes to solve such problems. The present paper addresses the question of three NBS systems, namely, bio-retention cells, vegetative swales and porous pavements, for the removal of total suspended solids (TSS), total nitrogen (TN) and total phosphorus (TP) when applied in different configurations (single or networked). The results presented in this paper aim to advance the understanding of their performances during varying rainfall patterns and configurations and their potential application conditions. Full article

This paper presents an analysis of projected precipitation extremes over the East African region. The study employs six indices defined by the Expert Team on Climate Change Detection Indices to evaluate extreme precipitation. Observed datasets and Coupled Model Intercomparison Project Phase six (CMIP6) simulations are employed to assess the changes during the two main rainfall seasons: March to May (MAM) and October to December (OND). The results show an increase in consecutive dry days (CDD) and decrease in consecutive wet days (CWD) towards the end of the 21st century (2081–2100) relative to the baseline period (1995–2014) in both seasons. Moreover, simple daily intensity (SDII), very wet days (R95 p), very heavy precipitation >20 mm (R20 mm), and total wet-day precipitation (PRCPTOT) demonstrate significant changes during OND compared to the MAM season. The spatial variation for extreme incidences shows likely intensification over Uganda and most parts of Kenya, while a reduction is observed over the Tanzania region. The increase in projected extremes may pose a serious threat to the sustainability of societal infrastructure and ecosystem wellbeing. The results from these analyses present an opportunity to understand the emergence of extreme events and the capability of model outputs from CMIP6 in estimating the projected changes. More studies are recommended to examine the underlying physical features modulating the occurrence of extreme incidences projected for relevant policies. Full article

Water pollution is a worldwide problem. Water consumption increases at a faster rate than population and this leads to a higher pollution rate. Sustainable Development Goals (SDG) include proposals aimed at ensuring the availability of clean water and its sustainable management (Goal 6), as well as the conservation and sustainable use of oceans and seas. The current trend consists in trying to reconcile economic growth with sustainability, avoiding the negative externalities for the environment generated by human activity. More specifically, the objective of this article is to present the evolution of the research regarding the removal of polluting pharmaceuticals that are discharged into wastewater. To do that, a bibliometric analysis of 2938 articles comprising the period 1979–2020 has been carried out. This analysis includes productivity indicators in the scientific field: journals, authors, research institutions and countries. In addition, keyword analysis allows the identification of four main axes of the research regarding the removal of pharmaceutical residues found in wastewater. The first group of articles is aimed at identifying the pharmaceuticals present in polluting effluents. The second and third groups of articles focus on presenting the procedures that enable the treatment of emerging contaminants, either from a biological point of view (second group) or a physicochemical point of view (third group). The fourth group refers to water quality and its possibilities to be reused. Finally, there is a growing trend of worldwide scientific publications, which justifies the importance of polluting residues management, especially those of pharmaceutical origin, in order to achieve a more sustainable society. Full article

Flood disaster has gained global attention due to the huge impact it has on human lives, economies, and sustainable environments. Flood disaster preparedness, which can significantly be influenced by disaster risk perception, has been highlighted as an effective way to manage flood disaster risk, as many other means have proved futile, yet no study has attempted using multiple dimensions to analyze this relationship in Ghana. Therefore, this study, using a survey of 369 households in the most flood-prone region, Accra Metropolis, analyzed the influence of flood disaster risk perception on urban households’ flood disaster preparedness. Based on the Protective Action Decision Model, the empirical models were constructed and estimated using the Tobit and binary logistic regression models. The results show that the majority of households (60.16%) were unprepared for flood disasters, and the perception of flood disaster risk and the sustainability risk posed by floods significantly affect flood disaster preparedness behaviours of households in a positive direction. The total number of flood disaster preparedness behaviours adopted was significantly related to probability, the threat to lives, sense of worry, and sustainability risk perceptions. Finally, income, education, and house ownership, among other household and individual characteristics, had significant positive effects on preparations for flood disasters. These findings suggest that effective policies to mitigate flood disasters must incorporate risk communication to boost households’ flood disaster preparedness. Full article

Fine-grained cohesive sediment is the primary vector for nutrient and contaminant redistribution through aquatic systems and is a critical indicator of land disturbance. A critical limitation of most existing sediment transport models is that they assume that the transport characteristics of fine sediment can be described using the same approaches that are used for coarse-grained non-cohesive sediment, thereby ignoring the tendency of fine sediment to flocculate. Here, a modelling framework to simulate flow and fine sediment transport in the Crowsnest River, the Castle River, the Oldman River and the Oldman Reservoir after the 2003 Lost Creek wildfire in Alberta, Canada was developed and validated. It is the first to include explicit description of fine sediment deposition/erosion processes as a function of bed shear stress and the flocculation process. This framework integrates four existing numerical models: MOBED, RIVFLOC, RMA2 and RMA4 using river geometry, flow, fine suspended sediment characteristics and bathymetry data. Sediment concentration and particle size distributions computed by RIVFLOC were used as the upstream boundary condition for the reservoir dispersion model RMA4. The predicted particle size distributions and mass of fine river sediment deposited within various sections of the reservoir indicate that most of the fine sediment generated by the upstream disturbance deposits in the reservoir. Deposition patterns of sediment from wildfire-impacted landscapes were different than those from unburned landscapes because of differences in settling behaviour. These differences may lead to zones of relatively increased internal loading of phosphorus to reservoir water columns, thereby increasing the potential for algae proliferation. In light of the growing threats to water resources globally from wildfire, the generic framework described herein can be used to model propagation of fine river sediment and associated nutrients or contaminants to reservoirs under different flow conditions and land use scenarios. The framework is thereby a valuable tool to support decision making for water resources management and catchment planning. Full article

Natural landscapes have changed significantly through anthropogenic activities, particularly in areas that are severely impacted by climate change and population expansion, such as countries in Southeast Asia. It is essential for sustainable development, particularly efficient water management practices, to know about the impact of land use and land cover (LULC) changes. Geographic information systems (GIS) and remote sensing were used for monitoring land use changes, whereas artificial neural network cellular automata (ANN-CA) modeling using quantum geographic information systems (QGIS) was performed for prediction of LULC changes. This study investigated the changes in LULC in the Perak River basin for the years 2000, 2010, and 2020. The study also provides predictions of future changes for the years 2030, 2040, and 2050. Landsat satellite images were utilized to monitor the land use changes. For the classification of Landsat images, maximum-likelihood supervised classification was implemented. The broad classification defines four main classes in the study area, including (i) waterbodies, (ii) agricultural lands, (iii) barren and urban lands, and (iv) dense forests. The outcomes revealed a considerable reduction in dense forests from the year 2000 to 2020, whereas a substantial increase in barren lands (up to 547.39 km²) had occurred by the year 2020, while urban land use has seen a rapid rise. The kappa coefficient was used to assess the validity of classified images, with an overall kappa coefficient of 0.86, 0.88, and 0.91 for the years 2000, 2010, and 2020, respectively. In addition, ANN-CA simulation results predicted that barren and urban lands will expand in the future at the expense of other classes in the years 2030, 2040, and 2050. However, a considerable decrease will occur in the area of dense forests in the simulated years. The study successfully presents LULC changes and future predictions highlighting significant pattern of land use change in the Perak River basin. This information could be helpful for land use administration and future planning in the region. Full article

The anthropogenic pressures of the twentieth century have seriously endangered the Mediterranean coastal zone; as a consequence, marine seagrass habitats have strongly retreated, mostly those of Posidonia oceanica. For this reason, over time, restoration programs have been put in place through transplantation activities, with different success. These actions have also been conducted with other Mediterranean marine seagrasses. The results of numerous transplanting operations conducted in the Northern Adriatic Sea and lagoons with Cymodocea nodosa, Zostera marina and Z. noltei and in the Central and Southern Adriatic Sea with P. oceanica (only within the project Interreg SASPAS), are herein presented and compared, taking also into account the presence of extensive meadows of C. nodosa, Z. marina and Z. noltei, along the North Adriatic coasts and lagoons. Full article

Submarine debris flows and their generated waves are common disasters in Nature that may destroy offshore infrastructure and cause fatalities. As the propagation of submarine debris flows is complex, involving granular material sliding and wave generation, it is difficult to simulate the process using conventional numerical models. In this study, a numerical model based on the smoothed particle hydrodynamics (SPH) algorithm is proposed to simulate the propagation of submarine debris flow and predict its generated waves. This model contains the Bingham fluid model for granular material, the Newtonian fluid model for the ambient water, and a multiphase granular flow algorithm. Moreover, a boundary treatment technique is applied to consider the repulsive force from the solid boundary. Underwater rigid block slide and underwater sand flow were simulated as numerical examples to verify the proposed SPH model. The computed wave profiles were compared with the observed results recorded in references. The good agreement between the numerical results and experimental data indicates the stability and accuracy of the proposed SPH model. Full article

Frequent droughts, seasonal precipitation, and growing agricultural water demand in the Yakima River Basin (YRB), located in Washington State, increase the challenges of optimizing water provision for agricultural producers. Increasing water storage through managed aquifer recharge (MAR) can potentially relief water stress from single and multi-year droughts. In this study, we developed an aggregated water resources management tool using a System Dynamics (SD) framework for the YRB and evaluated the MAR implementation strategy and the effectiveness of MAR in alleviating drought impacts on irrigation reliability. The SD model allocates available water resources to meet instream target flows, hydropower demands, and irrigation demand, based on system operation rules, irrigation scheduling, water rights, and MAR adoption. Our findings suggest that the adopted infiltration area for MAR is one of the main factors that determines the amount of water withdrawn and infiltrated to the groundwater system. The implementation time frame is also critical in accumulating MAR entitlements for single-year and multi-year droughts mitigation. In addition, adoption behaviors drive a positive feedback that MAR effectiveness on drought mitigation will encourage more MAR adoptions in the long run. MAR serves as a promising option for water storage management and a long-term strategy for MAR implementation can improve system resilience to unexpected droughts. Full article

Sea-level rise (SLR) is known as a central part of the Earth’s response to human-induced global warming and is projected to continue to rise over the twenty-first century and beyond. The importance of coastal areas for both human and natural systems has led researchers to conduct extensive studies on coastal vulnerability to SLR impacts and develop adaptation options to cope with rising sea level. Investigations to date have focused mostly on developed and highly populated coasts, as well as diverse ecosystems including tidal salt marshes and mangroves. As a result, there is less information on vulnerability and adaptation of less-developed and developing coasts to sea-level rise and its associated impacts. Hence, this research aimed at outlining an appropriate coastal management framework to adapt to SLR on the coasts that are in the early stage of development. A coastal area with a low level of development, located in southern Iran along the Gulf of Oman, was selected as a case study. The types of lands exposed to the high-end estimates of SLR by 2100 were identified and used as the primary criteria in determining the practical adaptation approaches for developing coasts. The result of coastal exposure assessment showed that, of five exposed land cover types, bare land, which is potentially considered for development, has the highest percentage of exposure to future sea-level rise. In order to protect the exposed coastal lands from future development and increase adaptive capacity of coastal systems, we developed a Spatial Integrated SLR Adaptive Management Plan Framework (SISAMP) based on an exposure reduction approach. Spatial land management tools and coastal exposure assessment models along with three other key components were integrated into the proposed conceptual framework to reduce coastal vulnerability through minimizing exposure of coastal communities to SLR-induced impacts. This adaptation plan provides a comprehensive approach for sustainable coastal management in a changing climate, particularly on developing coasts. Full article

The drinking and irrigation water scarcity is a major global issue, particularly in arid and semi-arid zones. In rural areas, groundwater could be used as an alternative and additional water supply source in order to reduce human suffering in terms of water scarcity. In this context, the purpose of the present study is to facilitate groundwater potentiality mapping via spatial-modelling techniques, individual and ensemble machine-learning models. Random forest (RF), logistic regression (LR), decision tree (DT) and artificial neural networks (ANNs) are the main algorithms used in this study. The preparation of groundwater potentiality maps was assembled into 11 ensembles of models. Overall, about 374 groundwater springs was identified and inventoried in the mountain area. The spring inventory data was randomly divided into training (75%) and testing (25%) datasets. Twenty-four groundwater influencing factors (GIFs) were selected based on a multicollinearity test and the information gain calculation. The results of the groundwater potentiality mapping were validated using statistical measures and the receiver operating characteristic curve (ROC) method. Finally, a ranking of the 15 models was achieved with the prioritization rank method using the compound factor (CF) method. The ensembles of models are the most stable and suitable for groundwater potentiality mapping in mountainous aquifers compared to individual models based on success and prediction rate. The most efficient model using the area under the curve validation method is the RF-LR-DT-ANN ensemble of models. Moreover, the results of the prioritization rank indicate that the best models are the RF-DT and RF-LR-DT ensembles of models. Full article

Water quality has deteriorated in recent years as a result of rising population and unplanned development, impacting ecosystem health. The water quality parameters of Qaroun Lake are contaminated to varying degrees, particularly for aquatic life consumption. For that, the objective of this work is to improve the assessments of surface water quality and to determine the different geo-environmental parameters affecting the lake environmental system in Qaroun Lake utilizing the weighted arithmetic water quality index (WAWQI) and four pollution indices (heavy metal pollution index (HPI), metal index (MI), contamination index (C_d), and pollution index (PI), that are enhanced by multivariate analyses as cluster analysis (CA), principal component analysis (PCA), and support vector machine regression (SVMR). Surface water samples were collected at 16 different locations from the lake during years 2018 and 2019. Thirteen physiochemical parameters were measured and used to calculate water quality indices (WQIs). The WQIs of Qaroun Lake such WAWQI, HPI, MI, C_d, PI revealed a different degree of contamination, with respect to aquatic life utilization. The WQIs result revealed that surface water in the lake is unsuitable, high polluted, and seriously affected by pollution for an aquatic environment. The PI findings revealed that surface water samples of Qaroun Lake were significantly impacted by Al, moderately affected by Cd and Cu, and while slightly affected by Zn due to uncontrolled releases of domestic and industrial wastewater. Furthermore, increasing salinity accelerates the deterioration of the lake aquatic environment. Therefore, sewage and drainage wastewater should be treated before discharging into the lake. The SVMR models based on physiochemical parameters presented the highest performance as an alternative method to predict the WQIs. For example, the calibration (Val.) and the validation (Val.) models performed best in assessing the WQIs with R² (0.99) and with R² (0.97–0.99), respectively. Finally, a combination of WQIs, CA, PCA, and SVMR approaches could be employed to assess surface water quality in Qaroun Lake. Full article

The quantitative prediction of hydrological components through hydrological models could serve as a basis for developing better land and water management policies. This study provides a comprehensive step by step modelling approach for a small agricultural watershed using the SWAT model. The watershed is situated in Petzenkirchen in the western part of Lower Austria and has total area of 66 hectares. At present, 87% of the catchment area is arable land, 5% is used as pasture, 6% is forested and 2% is paved. The calibration approach involves a sequential calibration of the model starting from surface runoff, and groundwater flow, followed by crop yields and then soil moisture, and finally total streamflow and sediment yields. Calibration and validation are carried out using the r-package SWATplusR. The impact of each calibration step on sediment yields and total streamflow is evaluated. The results of this approach are compared with those of the conventional model calibration approach, where all the parameters governing various hydrological processes are calibrated simultaneously. Results showed that the model was capable of successfully predicting surface runoff, groundwater flow, soil profile water content, total streamflow and sediment yields with Nash-Sutcliffe efficiency (NSE) of greater than 0.75. Crop yields were also well simulated with a percent bias (PBIAS) ranging from −17% to 14%. Surface runoff calibration had the highest impact on streamflow output, improving NSE from 0.39 to 0.77. The step-wise calibration approach performed better for streamflow prediction than the simultaneous calibration approach. The results of this study show that the step-wise calibration approach is more accurate, and provides a better representation of different hydrological components and processes than the simultaneous calibration approach. Full article