Water

The Croatian economy performs unfavorably in terms of the impact of production on wastewater discharges, which is particularly pronounced in the industrial sectors. Each unit of gross industrial value added produced in Croatia generates significantly more wastewater discharges than in most European countries with a similar level of economic development. Moreover, in 2020, only 26.9% of the total industrial wastewater discharges of the Croatian economy were treated, while 76.2% of the total industrial wastewater discharges were directly discharged into the environment. Since most of the industrial production in the Croatian economy is destined to meet the intermediate needs of other sectors, policy makers in Croatia must take into account that the level of industrial wastewater discharges is also influenced by the production level of sectors that depend on the intermediate products of wastewater-intensive industries. For this reason, we developed a wastewater extended input–output model of the Croatian economy to determine and analyze the impact of intersectoral linkages in Croatian production systems on the amount of untreated wastewater discharges. The results of the study show that wastewater flows in the Croatian economy are largely generated by the processes of production and consumption of intermediate products from the chemical and petroleum refining sectors, which also account for the largest share of the calculated wastewater footprint of total Croatian production. In light of the emerging empirical evidence, it can be concluded that targeting market-based and regulation-based measures at wastewater-intensive producers is not sufficient to reduce the relatively high level of untreated wastewater discharges in the Croatian economy. There is also a need for appropriate integrated policy measures in sectors that have a large wastewater footprint due to their established supply chains. Full article

The variability of the rainfall stable isotopic values (δ²H_p, δ¹⁸O_p) in the Ecuadorian Amazon to the Andes presents a marked local “altitude” effect. At the same time, this complex orography creates diverse precipitation regimes (unimodal, bimodal, and three-modal) that make it difficult to establish a relationship with the local amount. Nevertheless, stations along these regions show a similar intra-annual isotopic variability, with lower values during MAM and ON. In contrast, higher values are found during DJF and JAS in a w-shaped pattern, suggesting a common regional controller. A monthly δ²H_p and δ¹⁸O_p collection campaign was established in Central Ecuador (n = 30) to complement stations biased towards the northern and southern parts. Based on back trajectory analysis, the results demonstrated that moisture arrives from two primary sources: the Tropical North Atlantic (DJFM) and the Amazon Basin (JAS). Nevertheless, their convergence (AMJ and ON) is the crucial factor modulating the lowest isotopic values. Precisely, this convergence is stronger at the V-Index region (5° S–5° N, 65°–75° W), where the wind seasonality and reversal at low levels are enhanced, allowing the inter-hemispheric moisture flux transport (cross-equatorial flow). We propose that the amount of rainfall located at the V-Index region is a more robust approach for explaining the δ²H_p and δ¹⁸O_p variability rather than the local amount. Full article

Climate change and the development of urban centers within flood-prone areas have significantly increased flood-related disasters worldwide. However, most flood risk categorization and prediction efforts have been focused on the hydrologic features of flood hazards, often not considering subsequent long-term losses and recovery trajectories (i.e., community’s flood resilience). In this study, a two-stage Machine Learning (ML)-based framework is developed to accurately categorize and predict communities’ flood resilience and their response to future flood hazards. This framework is a step towards developing comprehensive, proactive flood disaster management planning to further ensure functioning urban centers and mitigate the risk of future catastrophic flood events. In this framework, resilience indices are synthesized considering resilience goals (i.e., robustness and rapidity) using unsupervised ML, coupled with climate information, to develop a supervised ML prediction algorithm. To showcase the utility of the framework, it was applied on historical flood disaster records collected by the US National Weather Services. These disaster records were subsequently used to develop the resilience indices, which were then coupled with the associated historical climate data, resulting in high-accuracy predictions and, thus, utility in flood resilience management studies. To further demonstrate the utilization of the framework, a spatial analysis was developed to quantify communities’ flood resilience and vulnerability across the selected spatial domain. The framework presented in this study is employable in climate studies and patio-temporal vulnerability identification. Such a framework can also empower decision makers to develop effective data-driven climate resilience strategies. Full article

Being one of the most important sources of water in the Jilin Province in China, the Yinma River Basin (YRB) is facing problems of water scarcity in low economic areas and low utilization in richer areas mainly caused by the irrational allocation of water, excessive pursuit of economic benefits, and neglect of environmental problems. Restricting watershed development involves potential decision-making risks. Some scholars have used the interval two-stage stochastic planning method to adjust water resource allocation in the Drinking Horse River Basin, but the method uses historical statistics for projection and does not take into account the ambiguity and uncertainty in real planning situations. Therefore, this study addresses the problems prevalent in the allocation of water resources in the YRB through optimization using stochastic programming methods, interval and two-stage, and introduces the fuzzy mathematical programming method, with the aim of coordinating the water balance of various water-consuming sectors in the YRB, so as to reconfigure the water allocation. The goal is to solve the existing problems of irrational water allocation, reduce system risks posed by excessive economic development, mitigate water shortages in the water-consuming sectors, and alleviate potential decision-making risks and vague uncertainties associated with the allocation of water resources. Additionally, optimization of the pollution-holding capacity improvement project was carried out. The interval fuzzy two-stage model simulation developed in this study shows that the distribution of water across the different administrative regions can be reduced by up to 30% compared with the original model, effectively reducing the problem of water wastage. Post-optimization, the impact of water shortage in the water resources allocation scheme is alleviated to a significant degree, and there is no water shortage in some areas. At the same time, the eco-environmental sector has gradually taken the leading role in the distribution of water reuse among the different water-consuming sectors. The pollution-holding capacity has been enhanced, and the discharge and river entry chemical oxygen demand (COD) and ammonia nitrogen, two typical pollutants, have been reduced. The membership interval in the interval fuzzy two-stage model reflects the relationship between the possible level of the target value and the risk level. This study provides a guideline for decision makers for balancing the relationship between benefits and risks and proposes a planning scheme that is more conducive to the development of the river basin. Full article

An approach of reporting long-term trends in groundwater extraction and baseflow impacts in the Murray-Darling Basin (MDB) in south-eastern Australia was developed and tested. The principal aim of the framework was to provide early warning of any potential adverse impacts from groundwater extraction on environmental releases of surface water for baseflow, support adaptive management of these impacts, and highlight those areas which may benefit from conjunctive water management. The analysis showed that there is no current decadal trend in the annual aggregate groundwater extraction volumes or stream impact across the non-Victorian MDB, with much of the interannual variability being related to rainfall. Despite this, increasing volumes of environmental releases of water for baseflows in some river valleys are being required to replace the stream depletion caused by historical patterns of groundwater extraction established before 2003. Two valleys were identified for which there may be insufficient surface water storage to release water to substitute stream losses to groundwater and still support ecosystems during dry periods. The increasing trend in extraction since 2003 in one of the units has significantly increased the risk in that valley. The reporting framework was shown to be effective for alluvial groundwater systems connected to regulated rivers. Full article

Water quality assessment and its monitoring are necessary for areas of mining activities. In Malaysia, the mining industry is the backbone of the manufacturing and construction sectors. This study used spatio-temporal water quality modeling along a reach with mining activities during high and low discharges at Sungai (river) Lebir and Sungai Aring, situated in Gua Musang, Kelantan, Peninsular Malaysia. The objective was to assess the spatio-temporal environmental impact of mining activities during the wet and dry seasons. Data were collected at different locations along the reach. Point and non-point sources were near the mining site. Overland flow calculation at the mining site was found with the widely used SCS (Soil Conservation Service) curve number method. Several scenarios were analyzed, such as baseline, worst-case, and with-mitigation. The study revealed that baseline values of all parameters were either in a natural condition or slightly polluted, except for aluminum. All parameters were estimated at a high concentration from the mining site to downstream during the worst case of the wet season. Whereas, during the worst case of the dry season, no significant differences were observed compared to baseline values. In the with-mitigation scenario, parameter concentrations were improved and similar to baseline values. Overall, the scenario selection was helpful in the environmental impact assessment. Furthermore, this study will be significant in pre- and post-mining assessment and environmental clearance. Full article

(1) An approach with great potential for fast and cost-effective profiling and identification of diatoms in lake ecosystems is presented herein. This approach takes advantage of Raman spectroscopy. (2) The study was based on the analysis of 790 Raman spectra from 29 species, belonging to 15 genera, 12 families, 9 orders and 4 subclasses, which were analysed using chemometric methods. The Raman data were first analysed by a partial least squares regression discriminant analysis (PLS-DA) to characterise the diatom species. Furthermore, a method was developed to streamline the integrated interpretation of PLS-DA when a high number of significant components is extracted. Subsequently, an artificial neural network (ANN) was used for taxa identification from Raman data. (3) The PLS interpretation produced a Raman profile for each species reflecting its biochemical composition. The ANN models were useful to identify various taxa with high accuracy. (4) Compared to studies in the literature, involving huge datasets one to four orders of magnitude larger than ours, high sensitivity was found for the identification of Achnanthidium exiguum (67%), Fragilaria pararumpens (67%), Amphora pediculus (71%), Achnanthidium minutissimum (80%) and Melosira varians (82%). Full article

In this study, the suitability of four earthen, seawater ponds located in the Thatta district of Sindh province (Pakistan) was evaluated for the purpose of semi-intensive mariculture, which remains to be a severely underdeveloped branch of the agricultural industry of this populous Asian country. Initial pond soil probes were promising, as they showed a high clay and silt content. Monthly water samples were obtained in the year 2019 (from January to December), which allowed for the monitoring of water parameters, as well as the identification and relative quantification of planktic populations. As a result, the monthly variations of basic water parameters were found within optimal ranges for planktic growth (water temperature, salinity, pH, transparency, and dissolved oxygen). Bacillariophyta was the largest phytoplanktic group, with the most dominant species being Sundstroemia setigera, followed by the cyanobacteria Oscillatoria limosa. Copepoda was the most numerous group of identified zooplankton, followed by tintinnids and foraminiferans. Total suspended solids (TSS) calculations indicated up to nine-fold month-to-month reductions of planktic biomass, observed in the form of diminishing Bacillariophyta (December) and Copepoda (June and December). In conclusion, the studied ponds appear to be suitable for semi-intensive mariculture activity due to the abundance of diverse planktic forms (mainly Copepoda—preferable natural food for commercially important fish species), which was achieved even without the use of fertilizers. However, significant drops of planktic biomass may still occur, which implies the need for regular water monitoring procedures, which would in turn allow fish producers to implement periodical adjustments to the administered feeding rates with artificial diets. Full article

This study aimed at estimating peat adsorption properties for copper ion removal from aqueous solutions during peat modification. Two peat modifications have been studied using batch tests and quantitatively reproduced with instrumental analysis by using spectrometric, potentiometric, and thermodynamic modeling methods. The first variation—mechanical activation—was carried out in a planetary mill; for the second one—mechanochemical activation—dry sodium percarbonate (Na₂CO₃∙1.5H₂O₂) was added. The adsorption of copper ions was studied in the concentration range from 10–150 mg/L with an interaction time from 0.25–12 h. Both modifications led to significant changes in the interaction energy in the adsorption layer; thus, the acceptor properties of macromolecules were enhanced from natural peat to mechanically activated peat and mechanochemically activated peat. FTIR spectra, specific surface area characteristics, and sorption experiments show the predominantly chemical nature of copper sorption. Maximum adsorption capacity was determined to be 24.1, 42.1, and 16.0 mg/g for natural peat, mechanically activated peat, and mechanochemically activated peat, respectively. The example of peat mechanochemically oxidized with Na₂CO₃∙1.5H₂O₂ shows that the improvement in the physicochemical properties (C_BET and specific surface area) plays a smaller role in the sorption capacity in relation to copper ions than the presence of phenolic and carboxyl groups, the content of which decreases during oxidation. Full article

Landslides often cause deaths and severe economic losses. In general, forests play an important role in reducing landslide probability because of the stabilizing effect of the tree roots. Although fruit groves consist of trees, which are similar to forests, practical land management, such as the frequent trampling of fields by laborers and compression of the terrain, may cause such land to become prone to landslides compared with forests. Fruit groves are widely distributed in hilly regions, but few studies have examined their role in landslide initiation. This study aims at filling this gap evaluating the predisposing and triggering conditions for rainfall-triggering landslides in part of Uwajima City, Japan. A large number of landslides occurred due to a heavy rainfall event in July 2018, where citrus groves occupied about 50% of the study area. In this study, we combined geodata with a regression model to assess the landslide hazard of fruit groves in hilly regions. We developed maps for five conditioning factors: slope gradient, slope aspect, normalized difference vegetation index (NDVI), land use, and geology. Based on these five maps and a landslide inventory map, we found that the landslide area density in citrus groves was larger than in forests for the categories of slope gradient, slope aspect, NDVI, and geology. Ten logistic regression models along with different rainfall indices (i.e., 1-h, 3-h, 12-h, 24-h maximum rainfall and total rainfall) and different land use (forests or citrus groves) in addition to the other four conditioning factors were produced. The result revealed that “citrus grove” was a significant factor with a positive coefficient for all models, whereas “forest” was a negative coefficient. These results suggest that citrus groves have a higher probability of landslide initiation than forests in this study area. Similar studies targeting different sites with various types of fruit groves and several rainfall events are crucial to generalize the analysis of landslide hazard in fruit groves. Full article

Water is a fundamental resource for human survival but the consumption of water that is unfit for drinking leads to serious diseases. Access to high–resolution satellite imagery provides an opportunity for innovation in the techniques used for water quality monitoring. With remote sensing, water quality parameter concentrations can be estimated based on the band combinations of the satellite images. In this study, a hybrid remote sensing and deep learning approach for forecasting multi–step parameter concentrations was investigated for the advancement of the traditionally employed water quality assessment techniques. Deep learning models, including a convolutional neural network (CNN), fully connected network (FCN), recurrent neural network (RNN), multi–layer perceptron (MLP), and long short term memory (LSTM), were evaluated for multi–step estimations of an optically active parameter, i.e., electric conductivity (EC), and an inactive parameter, i.e., dissolved oxygen (DO). The estimation of EC and DO concentrations can aid in the analysis of the levels of impurities and oxygen in water. The proposed solution will provide information on the necessary changes needed in water management techniques for the betterment of society. EC and DO parameters were taken as independent variables with dependent parameters, i.e., pH, turbidity, total dissolved solids, chlorophyll–$\alpha$, Secchi disk depth, and land surface temperature, which were extracted from Landsat–8 data from the years 2014–2021 for the Rawal stream network. The bi–directional LSTM obtained better results with a root mean square error (RMSE) of 0.2 (mg/L) for DO and an RMSE of 281.741 ($\mathsf{\mu }$S/cm) for EC, respectively. The results suggest that a hybrid approach provides efficient and accurate results in feature extraction and evaluation of multi–step forecast of both optically active and inactive water quality parameters. Full article

The variation in moisture content between subsequent irrigations determines the use of infiltration equations that contain representative physical parameters of the soil when irrigation begins. This study analyzes the reliability of the hydrodynamic model to simulate the advanced phase in border irrigation. For the solution of the hydrodynamic model, a Lagrangian scheme in implicit finite differences is used, while for infiltration, the Kostiakov equation and the Green and Ampt equation are used and compared. The latter was solved using the Newton–Raphson method due to its implicit nature. The models were validated, and unknown parameters were optimized using experimental data available in the literature and the Levenberg–Marquardt method. The results show that it is necessary to use infiltration equations based on soil parameters, because in subsequent irrigations, the initial conditions change, modifying the advance curve in border irrigation. From the coupling of both equations, it is shown that the empirical Kostiakov equation is only representative for a specific irrigation event, while with the Green and Ampt equations, the subsequent irrigations can be modeled, and the advance/infiltration process can be observed in detail. Full article

The objective of this study is to produce suitability maps for potential rainwater harvesting techniques (RWHT) in the West Bank (WB), Palestine. These techniques aim to reduce water scarcity, which is a major problem for the conservation of water resources in the area. Based on literature reviews and expert recommendations, seven RWHts were selected (runoff basin system, contour ridges, cisterns, eyebrow terrace, check dam, on-farm pond, and bench terraces). Analysis methods performed in the Arc GIS environment include spatial analysis and data reclassification. Other calculations include multi-criteria analysis for assigning suitability. Five criteria (rainfall, runoff, land use, slope, and soil texture) for RWHt were analyzed to produce a suitability map for each technique. The results show that runoff basin systems in the northeast and southwest of WB are the most suitable, with about 50% of the area of WB moderately suitable for this technique, while 70% of the area of WB is very suitable for the contour ridge technique. Furthermore, this analysis shows that almost 50% of the WB is very suitable for cisterns. Sixty percent of the area is very suitable for on-farm puddling, especially in the north and southwest of WB. The areas with high suitability for the different techniques comprehensively cover the WB, as shown in the RWHt suitability maps and the integrated map. Nevertheless, this approach can help decision makers in making an initial selection of RWH techniques suitable for their region. Full article

Urban flooding is an increasingly common phenomenon around the world. The reasons are usually attributed to the insufficient capacity of the combined sewer system and its inability to adapt to the changing dynamics of rainfall. This is also the case in Warsaw (the capital of Poland), where the sewage system was designed in the 1960s. The aim of the article is to highlight possible hydrological solutions that would significantly improve Warsaw’s situation in terms of rainfall runoff. The article looks at some solutions that were previously mentioned in the literature and presents an assessment of the possible changes in land use/land cover on the hydrological processes and improvements in the general hydrological situation of Warsaw. In addition, the article points out the need to update the programme and spatial approach to the discharge of water from specific watersheds in Warsaw, as well as to establish a single manager for stormwater drainage in the city of Warsaw. An important issue is the restoration of natural retention basins in the city and the construction of artificial basins in places with frequent local flooding. The article emphasises the importance of building individual detention basins (as well as low-impact developments) for newly planned investments. Other important aspects are as follows: the construction of suitable underground or open channels, the need to disconnect Ursynów’s stormwater runoff from the catchment area of the Służewiecki Stream and to channel it along the southern bypass for Warsaw (S-2) to the dry lakes and ponds in Wilanów. Finally, the article discusses the application of Sustainable Drainage Systems (SuDS) and Real-Time Control (RTC) in urban drainage systems as a possible solution to improve wastewater management in urban areas. Full article

A bibliometric analysis using the Scopus database was performed to investigate the research documents published from 1990 to 2019 in scientific sources related to molybdenum in drinking water and determine the quantitative characteristics of the research in this period. The results from the analysis revealed that the number of publications was maintained at a regular production of around 5 papers per year until 2009, followed by a fast linear increase in the production in the period from 2010 to 2016 (29 papers in 2016), but the scientific production regarding this topic was reduced in 2017 and 2018 to recover the production obtained in 2016 once again in 2019. The total contribution of the three most productive countries (USA, China and India, respectively) accounted for around 50% of the total number of publications. Environmental Science was the most common subject (51.4% contribution), followed by Chemistry (26.7% contribution). The research efforts targeted toward the search for technical solutions for molybdenum removal from water are not as important as the ones focused on the identification of molybdenum-polluted water bodies and the analysis of the health effects of the intake of molybdenum. Nevertheless, examples of technological treatments to remove molybdenum from the aqueous solution include the use of adsorption and ion exchange; coagulation, flocculation and precipitation followed by filtration; membrane technologies and biological treatments. Full article

To analyze the structural characteristics of zooplankton functional groups (ZFGs) and their correlation with environmental physicochemical factors in the Chaohu Lake Basin, water samples were collected from October 2019 to July 2020, and the zooplankton species and ZFGs were investigated. A total of 250 species, including 88 protozoa, 115 rotifers, 28 cladocerans, and 19 copepod species, were detected and divided into 16 ZFGs. The ZFGs exhibited obvious spatiotemporal heterogeneity. ZFGs in the Chaohu Lake were notably different from those in rivers and were different between the rivers. In the ecosystem, network analysis showed that protozoan algae/protozoan bacteria (PA/PB), rotifer particle filter (RF), and rotifer small predator (RSG) were important in the spring, summer, and autumn that and small zooplankton filter (SCF) was important in spring, autumn, and winter, while the importance of other ZFGs changed with seasons. Redundancy analysis showed that the environmental factors with a strong correlation between the ZFG compositions differed in each season. Different ZFGs exhibited different correlations with environmental factors. This study showed that ZFGs were closely related to environmental factors and that functional traits can reflect responses to changes in the water environment. Full article

Topobathymetric monitoring carried out in the past 30 years revealed that the amount of sand in the active zone of the Belgian West Coast increased substantially. Correcting for sand works carried out, the rate of natural feeding of the area was estimated to be 10 mm/year, which is significantly more than the local sea level rise rate of 2 to 3 mm/year. One concludes that this coastal zone, with a length of ca. 16 km, has shown a natural resilience against sea level rise. The question remains which processes govern this behavior and where natural input of sand to the system occurs. Using available coastal monitoring data for the Belgian coast, as well as a state-of-the-art sand transport model, revealed that different processes drive a cross-shore natural feeding from offshore to the coastline. The spatial distribution of this cross-shore natural feeding is determined by the existence of a gully-sand bank system. The outcome of this research was a conceptual model for the large-scale sand exchange in the study area which is implemented in an 1D coastline model. The most important element in these models was the cross-shore natural feeding of the active zone via a shoreface connected ridge amounting to 95,000 m³/year in the period 2000–2020. Full article