Water, Volume 14, Issue 13 (July-1 2022) – 163 articles

Sediment is the main carrier of pollutants in river channels. This study analyzed the distribution characteristics of precipitation, runoff, and sediment and their response characteristics in the Daning River basin. Based on daily precipitation (1979–2017), runoff (1989–2017), and sediment (1997–2017) time series, the Gini concentration index, precipitation concentration index (PCI), precipitation concentration degree (PCD), and precipitation concentration period were applied to assess the concentration characteristics of precipitation, runoff, and sediment on the daily, monthly, and seasonal scales. At each intensity level, precipitation was negatively correlated to the PCI and PCD. The normalized difference vegetation index (NDVI) values had strong negative correlations with rainy days with light precipitation (0.1–9.9 mm). The degrees of concentration were in the same order for the multiscale analysis: runoff < precipitation < sediment. Although the amount of daily precipitation of more than 25 mm displayed a significant increasing trend, suggesting an increased risk of flood and soil erosion, the significantly improved vegetation cover reduced the sediment-carrying capacity of the surface runoff, with significant decreases in the total amount and multiscale concentration degrees of sediment being observed. The results of the study provide a reference for the improvement of the potable water safety and ecological environment in the Three Gorges Reservoir region. Full article

Water rights trading is an important way to solve the problem of water shortage by market mechanism. The allocation of water rights among ecological water, energy water, and grain planting water are the basis of the regional water rights trade. In this paper, the concept of coordinated development of water–ecology–energy–food is proposed. We build a water rights allocation model with fairness, efficiency, and coordinated development as the goal, to achieve water security for various industries. Taking Yinchuan city as an example, the results showed that compared with the current water rights the water rights of life increased by 1.07%, the water rights of ecology increased by 1.85%, the water rights of energy industry decreased by 1.09%, the water rights of food planting decreased by 3.27%, the water rights of other agriculture increased by 0.83%, and the water rights of the general industry increased by 0.65%. After the allocation of water rights, the cooperativity of water–ecology–energy–food increased by 7.56%, and the total value of water resources in various industries increased by 2.31 × 10⁸ CNY. A new water rights allocation model is developed in this paper, which can provide a reference for the allocation of water rights among regional industries. Full article

Among the well-known approaches for controlling seawater intrusion during extensive freshwater abstraction from coastal aquifers is the construction of subsurface dams. In the current research, the SEAWAT code is being implemented to examine the impact of groundwater extraction on the effectiveness of a damaged subsurface dam for controlling saltwater intrusion. Simulations were performed numerically to check impact of the subsurface dam height, dam location, well height, well location, abstraction rate, fracture aperture, fracture location, seawater density and fracture dimension on the effectiveness of subsurface dam as a countermeasure to prevent saltwater intrusion in coastal aquifers. Increasing the abstraction rate from 1 × 10⁻⁶ to 5 × 10⁻⁶ m³/s caused the seawater to advance more into the freshwater, and the loss of effectiveness increased. The minimum and maximum value of loss of subsurface dam effectiveness was recorded to be 34.6% to 93%, respectively, for the abstraction rates from the well equal 1 × 10⁻⁶ and 5 × 10⁻⁶ m³/s, consequentially. When the dimensionless value of well height location L_w/L_d is increased from 1.0 to 2.0, the effectiveness of the subsurface dam is reduced by around 20%. The findings demonstrate that the well location, well depth, abstraction rate, location of the dam, fracture aperture, and density of saltwater all affect the effectiveness impairment of the fractured subsurface dam for controlling saltwater intrusion. Decision makers could use findings of this research to better manage groundwater resources in coastal aquifers. Full article

Groundwater occurrence in semi-arid regions is variable in space and time due to climate patterns, terrain features, and aquifer properties. Thus, accurate delineation of Groundwater Potential Zones (GWPZs) is essential for sustainable water resources management in these environments. The present research aims to delineate and assess GWPZs in a semi-arid basin of San Luis Potosi (SLP), Mexico, through the integration of Remote Sensing (RS), Geographic Information System (GIS), and Analytic Hierarchy Process (AHP). Seven thematic layers (geology, lineament density, land use and land cover, topographic wetness index (TWI), rainfall, drainage density, and slope) were generated in raster format. After the AHP procedure and rank assignment, the thematic layers were integrated using the raster calculator to obtain the GWPZs map. The results indicated that 68.21% of the area is classified as low groundwater potential, whereas 26.30% is classified as moderate. Validation was done by assessing the water residence time data from 15 wells distributed in the study area. Furthermore, the Receiver Operating Characteristics (ROC) curve was obtained, indicating a satisfactory accuracy prediction (AUC = 0.677). This study provides valuable information for decision-makers regarding the conservation and sustainable management of groundwater resources. Full article

Fecal indicator bacteria (FIB), such as E. coli and Enterococci, are used to indicate the potential of fecal contamination in waterways. One known source of FIB in urbanized areas is the occurrence of combined sewer overflows (CSOs). To explore the impact of CSOs on local water quality and FIB presence, sampling was conducted during the summers of 2017–2019 of two cities, one with CSOs and one without, on the Mohawk River in upstate New York, USA. Sampling included in situ physiochemical parameters of pH, temperature, and dissolved oxygen and laboratory tests for E. coli, Enterococci, nitrates, and total organic carbon (TOC). Correlations between parameters were explored using the Wilcoxon rank sum test and Spearman’s Rank correlation with and without considerations of site and city location. Overall, positive correlations between FIB and rainfall were identified in one city but were less significant in the other, suggesting a buffering of FIB concentrations likely due to inflow contributions from a reservoir. Samples collected downstream from an active CSO reached the detection limit of the FIB tests, demonstrating a 2-log or greater increase in FIB concentrations from dry weather conditions. The city with CSOs demonstrated greater FIB concentrations, which are likely a combination of greater urban runoff, CSOs, and the potential resuspension of sediment during high flow events. Due to the widespread presence of FIB in the region, future research includes utilizing microbial source tracking to identify the sources of contamination in the region. Full article

An apparent proliferation of filamentous algal blooms (FABs) in pristine lakes around the world is a source of concern. However, little is known about the predominant drivers and effects of such FABs on lake ecosystems. We observed FABs in a large clear-water lake (Bear Lake, UT/ID, USA) and analyzed long-term lake monitoring data and algal stable isotopes for changes in climate, food webs and anthropogenic nutrient loading, respectively, as potential local drivers of FAB formation. Furthermore, we quantified in situ metabolism rates on rocks with and without FABs at two locations. Long-term monitoring data revealed increasing summer water temperatures (2009 to 2020) and decreasing winter ice cover (1923 to 2021). The FABs had δ¹⁵N values that were higher than 0 ‰, indicating a potential nutrient influx to Bear Lake from livestock or human waste. Climate change and anthropogenic nutrients may thus have facilitated FAB occurrence. Contrary to expectation, the FABs exhibited significantly lower gross primary production rates compared to low-biomass periphyton communities, indicating potentially negative effects of FAB proliferations on lake food webs. Our results highlight the need for expanding lake monitoring programs to include littoral zones to detect and mitigate changes occurring in lakes. Full article

The threat of anthropogenic eutrophication and harmful algal blooms in lakes requires the development of innovative stormwater best management practices (BMPs) to reduce the external loading of phosphorus (P). This paper presents the findings of a 5-year study of a full-scale P removal structure constructed in Minnesota, USA with spent lime drinking water treatment residual (DWTR), a by-product of water softening at a local water treatment plant. Influent and effluent water samples were collected by auto-samplers during 43 storm events during the growing season. Samples were analyzed for P constituents, heavy metals, total suspended solids (TSS), and pH. Toxicity of the effluent was assessed using Ceriodaphnia dubia. Flow-weighted removal effectiveness was calculated for each storm event. Overall, the spent lime DWTR reduced total P loading by 70.9%, dissolved reactive P by 78.5%, dissolved P by 74.7%, and TSS by 58.5%. A significant reduction in heavy metals was also observed. Toxicity tests indicated the aquatic toxicity of the effluent treated with spent lime DWTR was not different from untreated stormwater. This study provided long-term real-world data that demonstrated that a full-scale P removal structure with spent lime DWTR significantly reduced P and other pollutants in stormwater discharging to an urban lake. Therefore, spent lime DWTR, which is currently treated as a waste product, is a promising filter material for stormwater treatment. Full article

To investigate the monitoring history and long-term change trends in surface water quality in China since the reform and opening up, the history of surface water environment monitoring is summarized, including monitoring scope, monitoring methods, and technical requirements. Temporal and spatial patterns of surface water quality in China were analyzed based on the monitoring results. In the past 40 years, the monitoring targets for surface water quality have been continuously improved, the frequency of monitoring has become more science-based, and the monitoring indicators are now comprehensive. Overall, the temporal change trend in surface water quality has followed a “fluctuating changes stage—rapid deterioration stage—fluctuations stalemate stage—rapid improvement stage” pattern. However, the current regional surface water quality is still in a polluted status, and there is a gap between surface water quality status and the goal of building a well-off society. At present, China’s surface water pollution is prone to high numbers of incidents and the treatment of surface water pollution has entered a crucial stage. The potential for the continuous reduction of major pollutant discharges has become more challenging, and the marginal cost for pollution control has increased. It is very difficult to comprehensively solve the outstanding water environment problems. In addition to strengthening the existing work on surface water quality control, it is also necessary to strengthen the work of risk identification, early warning, and regulation implementation of the surface water environment. During the 14th year plan period (2021–2025), the overall planning on water resources, water ecology, and water quality will be implemented, and beautiful rivers and lakes will be created. Full article

Drought has had an increasingly serious impact on humans with global climate change. The drought index is an important indicator used to understand and assess different types of droughts. At present, many drought indexes do not sufficiently consider human activity factors. This study presents a modified drought index and the standardized precipitation evapotranspiration irrigation index (SPEII), considering the human activity of irrigation that is based on the theory of the standardized precipitation evapotranspiration index (SPEI). This study aims to compare the modified drought index (SPEII) and ·SPEI and self-calibrating Palmer drought severity index (scPDSI) in the major crop-producing areas and use SPEII to evaluate the possible future drought characteristics based on CMIP5 Model. The Pearson correlation coefficient was used to assess the relevance between drought indexes (SPEII, SPEI, and scPDSI) and vegetation dynamics. The normalized difference vegetation index (NDVI) was used to represent the vegetation dynamics change. The results showed that SPEII had better performance than the SPEI and scPDSI in monitoring cropland vegetation drought, especially in cropland areas with high irrigation. The winter wheat growth period of the SPEII had better performance than that of summer maize in croplands with higher irrigation levels on the North China Plain (NCP) and Loess Plateau (LP). In general, future drought on the NCP and LP showed small changes compared with the base period (2001–2007). The drought intensity of the winter wheat growth period showed an increasing and steady trend in 2020–2080 under the representative concentration pathway (RCP) 4.5 scenario on the NCP and LP; additionally, the severe drought frequency in the central LP showed an increasing trend between 2020 and 2059. Therefore, the SPEII can be more suitable for analyzing and evaluating drought conditions in a large area of irrigated cropland and to assess the impacts of climate change on vegetation. Full article

The excess loading of nutrients generated by agricultural activities is a leading cause of water quality impairment across the globe. Various management practices have been developed and widely implemented as conservation management strategies to combat water pollution originating from agricultural activities. In the last ten years, there has also been a widespread recognition of the need for nutrient harvesting from wastewaters and resource recovery. In Europe’s Northern Periphery and Arctic (NPA) areas, the expertise in water and runoff management is sporadic and needs to be improved. Therefore, the objective of this research was to perform a comprehensive review of the state of the art of Good Agricultural Practices (GAPs) for the NPA region. A set of questionnaires was distributed to project partners combined with a comprehensive literature review of GAPs focusing on those relevant and/or implemented in the NPA region. Twenty-four GAPs were included in the inventory. This review reveals that there is a large level of uncertainty, inconsistency, and a gap in the knowledge regarding the effectiveness of GAPs in nutrient reduction (NRE), their potential for nutrient recycling and recovery (NRR), and their operation and maintenance requirements (OMR) and costs. Although the contribution of GAPs to water quality improvement could not be quantified, this inventory provides a comprehensive and first-of-its-kind guide on available measures and practices to assist regional and local authorities and communities in the NAP region. A recommendation for incorporating and retrofitting phosphorus retaining media (PRMs) in some of the GAPs, and/or the implementation of passive filtration systems and trenches filled with PRMs to intercept surface and subsurface farm flows, would result in the enhancement of both NRE and NRR. Full article

Because of the ongoing climate change, the frequency of extreme rainfall events at the global scale is expected to increase, resulting in higher social and economic impacts. Thus, improving the forecast accuracy and the risk communication is a fundamental goal to limit social and economic damages. Both Numerical Weather Prediction (NWP) and radar-based nowcasting systems still have open issues, mainly in terms of precipitation correct time/space localization predictability and rapid forecast accuracy decay, respectively. Trying to overcome these issues, this work aims to present a nowcasting system combining an NWP model (WRF), using a 3 h rapid update cycling 3DVAR assimilation of radar reflectivity data, with the radar-based nowcasting system PhaSt through a blending technique. Moreover, an innovative post-processing algorithm named SWING (Score-Weighted Improved NowcastinG) has been developed in order to take into account the timely and spatial uncertainty in the convective field simulation. The overarching goal is to pave the way for an easy and automatic communication of the heavy rainfall warning derived by the nowcasting procedure. The results obtained applying the SWING algorithm over a case study of 22 days in the fall 2019 season suggest that the algorithm could improve the predictive capability of a traditional deterministic nowcasting forecast system, keeping a useful forecast timing and thus integrating the current forecast procedures. Eventually, the main advantage of the SWING algorithm is also its very high versatility, since it could be used with any meteorological model also in a multi-model forecast approach. Full article

The characteristics of nitrogen contamination of shallow groundwater were evaluated through current status analysis and trend detection of ammonium–N and nitrate–N concentrations under various cropping patterns to assess the effectiveness of rational fertilization in the Choushui River alluvial fan, central Western Taiwan. The influence of cropping patterns on both ammonium–N and nitrate–N contamination associated with redox conditions/dissolved oxygen (DO) in shallow groundwater was also discussed in this study. The analysis revealed that shallow groundwater beneath double rice cropping and rotational cropping regions is still characterized by high ammonium–N concentration despite rational fertilization promotion. However, very few monitoring wells showed an upward trend of ammonium–N/nitrate–N concentrations, indicating that shallow groundwater is not further deteriorated by nitrogen pollution in most parts of the study area. Therefore, the remediation of nitrogen contaminated groundwater will be a long-term process and more effort must be invested. Moreover, the strict redox conditions defined by a single DO threshold value may not account for groundwater nitrogen pollution in the study area. It is difficult to determine the redox conditions and predominant nitrogen pollution patterns of shallow groundwater purely from cropping patterns. Instead, contamination may have resulted from an integrated process governed by several other factors. Tracing the potential sources of nitrogen pollution and establishing a more integral monitoring network should be implemented to formulate a more comprehensive nitrogen pollution control strategy in this area. Full article

Algicidal bacteria combined with the ability of aerobic denitrification is considered to be a promising way to control harmful cyanobacterial bloom and remove nitrogen. However, the effect of these bacteria on the vertical distribution of colonial cyanobacteria and nutrients remained unknown. In this study, two algicidal and denitrifying bacteria were respectively co-cultured with the colonial Microcystis aeruginosa to construct the microcosm systems, and then the cyanobacteria number, the ratio of bacterial to cyanobacterial abundance, the content of dissolved nitrogen, phosphorus and organic carbon in different water layers were investigated. The results showed that the distribution difference of Microcystis among the vertical water layers was further enlarged due to the short-term influence of algicidal bacteria Brevundimonas diminuta and Pseudomonas stutzeri. The number of Microcystis in the lower layer was further reduced by the inhibitory effect of the algicidal bacteria. However, there was a dramatic increase in the number of Microcystis in the upper layer, even when the ratio of algicidal bacteria to cyanobacteria increased significantly. B. diminuta and P. stutzeri both greatly promoted the removal of dissolved total nitrogen in the upper and middle layers of cyanobacteria blooming water, but they also boosted the release of dissolved phosphorus in all layers. These results enable us to better understand the possible limitations of algicidal bacteria in their application to control cyanobacteria blooms. Full article

Europium recovery from wastewater is determined by its high significance for industry and toxicity for living organisms. The capacity of cyanobacteria Arthospira platensis (Spirulina) to remove Eu(III) through biosorption and bioaccumulation was evaluated. In biosorption experiments, the effects of four variables pH, metal concentration, time, and temperature on metal removal were studied. In bioaccumulation experiments, the effect of Eu(III) concentrations on biomass bioaccumulation capacity and biochemical composition was assessed. The efficiency of Eu(III) uptake in both experiments was determined using ICP-AES techniques. Maximum biosorption of Eu(III) was achieved at pH 3.0. Equilibrium data fitted well with the Langmuir and Freundlich models, with maximum adsorption capacity of 89.5 mg/g. The pseudo-first-, pseudo-second-order, and Elovich models were found to correlate well with the experimental data. According to thermodynamic studies the sorption was feasible, spontaneous, and endothermic in nature. At addition of Eu(III) ions in the cultivation medium in concentrations of 10–30 mg/L, its accumulation in biomass was 9.8–29.8 mg/g (removal efficiency constituting 98–99%). Eu(III) did not affect productivity and content of carbohydrates and pigments in biomass but led to the decrease of the content of protein and an increase in the amount of MDA. The high Eu(III) biosorption and bioaccumulation efficiency of Arthrospira platensis may constitute an effective and eco-friendly strategy to recover it from contaminated environment. Full article

Knowledge of how the isotopic composition (i.e., δ²H, δ¹⁸O and ³H) of precipitation changes within an individual catchment allows the origins of surface and groundwater to be differentiated and the dynamic characteristics of water within individual water bodies to be traced. This paper presents the Slovenian Network of Isotopes in Precipitation (SLONIP), a research platform that has been operating since April 2020. The SLONIP platform currently contains 2572 isotope data points of monthly composite precipitation from eight locations obtained from various investigations performed since 1981. It also provides information about a sample’s location, analysis, and links to the relevant scientific papers. It also presents the data in numerical and graphical form, including monthly, seasonal, and annual means and local meteoric water lines, all calculated using a Python code made freely available on GitHub. The platform provides essential information for geographically, climatologically, and geologically diverse regions like Slovenia and can help improve our understanding of the water cycle on a local and regional scale. Full article

Toppling is a common deformation and failure phenomenon in the reservoir bank slopes of hydropower projects. This paper studies the genesis and evolution of different toppling bodies during water impoundment at the Miaowei Hydropower Station Reservoir on the Lancang River in southwest China. Toppling properties were determined and second failure characteristics analyzed in different reservoir impoundment stages. Different degrees of toppling deformation were primarily affected by the transverse bending stress, while the regional tectonic stress has been shown to have a significant effect on the transverse bending of the rock layers. Combined with the on-site investigation and monitoring results, the failure mechanisms of the different toppling deformation bodies were analyzed. The second failure of the toppling rock mass caused by the reservoir impoundment process is mainly the hydrodynamic splitting along fractures, wave impaction and softening on the slope foot. The transverse bending effect of gravity is transmitted upward through joint misalignment, rotation and slip, accelerating the speed of secondary toppling failure and forming a compression-shear failure along the toppling tension crack. A model to predict the scope and time of failure in the toppling deformation banks under the action of reservoir hydrodynamics was proposed. Full article

To realise the ecological protection and high-quality development of the Yellow River Basin and transition from extensive utilisation to intensive conservation of agricultural water, a multi-objective crop planting structure optimisation model was established. The model enabled highly efficient crop planting in terms of net income with high yield and low consumption of water. Thereafter, the game algorithm was used to balance different requirements of each objective function under each constraint, both competitively and cooperatively, to obtain an optimal crop planting structure. Finally, the proposed model and analysis method were demonstrated and verified using the Xiaolangdi south bank irrigation area as an example. The results indicated that using the competitive game algorithm produced a superior crop planting structure in terms of high net income, high yield, and low water usage, suggesting that the relationships between game players and objective functions should be considered in designing the optimisation model. Thus, the proposed approach provides a theoretical basis for the sustainable development of the agricultural industry by realising the intensive utilisation of water resources in a particular irrigation area. Full article

Water-soluble organic pollutants, such as phenolic compounds, have been exposed to environments globally. They have a significant impact on groundwater and surface water quality. In this work, different Mn₃O₄ catalysts were prepared for metal oxide activation of peroxymonosulfate (PMS) to remove the phenolic compound from the water environment. The as-prepared catalysts were characterized using thermogravimetric-differential thermal analysis (TG-DTA), powder X-ray diffraction (XRD), scanning electron microscopy (SEM), and Brunauer-Emmett-Teller (BET) surface area analysis. Furthermore, the effect of temperature and reusability of the as-prepared Mn₃O₄ catalysts is also investigated. The Mn₃O₄ nanoparticles (NPs) catalyst reveals an excellent performance for activating PMS to remove phenol compounds. Mn₃O₄ NPs exhibits 96.057% efficiency in removing 25 ppm within 60 min. The kinetic analysis shows that Mn₃O₄ NPs fitted into pseudo-first order kinetic model and exhibited relatively low energy activation of 42.6 kJ/mol. The reusability test of Mn₃O₄ NPs displays exceptional stability with 84.29% efficiency after three-sequential cycles. The as-prepared Mn₃O₄ NPs is proven suitable for phenolic remediation in aqueous solutions. Full article

In this study, a stochastic rainfall generator was developed to create continuous rainfall time series with a high temporal resolution of 10 min. The rainfall-generation process involved Monte Carlo simulation for stochastically generating rainfall parameters such as rainfall quantity, duration, inter-event time, and type. A bivariate copula was used to preserve the correlation between rainfall quantity and rainfall duration in the generated rainfall series. A modified Huff curve method was used to overcome the drawbacks of rainfall type classification by using the conventional Huff curve method. The number of discarded rainfall events was lower in the modified Huff curve method than in the conventional Huff curve method. Moreover, the modified method includes a new rainfall type that better represents rainfall events with a relatively uniform temporal pattern. The developed rainfall generator was used to reproduce rainfall series for the Yilan River Basin in Taiwan. The statistical indices of the generated rainfall series were close to those of the observed rainfall series. The results obtained for rainfall type classification indicated the necessity and suitability of the proposed new rainfall type. Overall, the developed stochastic rainfall generator can suitably reproduce continuous rainfall time series with a resolution of 10 min. Full article

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