Amina Abdelkadir Mohammedshum, Ben H. P. Maathuis, Chris M. Mannaerts, Daniel Teka
This study uses a triple-sensor collocation approach to evaluate the performance of small-holder irrigation schemes in the Zamra catchment of Northern Ethiopia. Crop water productivity (CWP), as an integrator of biomass production and water use, was used to compare the overall efficiencies of three types of irrigation systems: traditional and modern diversions, and dam-based irrigation water supply. Farmer-reported data often rely on observations, which can introduce human estimation and measurement errors. As a result, the evaluation of irrigation scheme performance has frequently been insufficient to fully explain crop water productivity. To overcome the challenges of using one single estimation method, we used a triple-sensor collocation approach to evaluate the efficiency of three small-scale irrigation schemes, using water productivity as an indicator. It employed three independent methods: remotely sensed data, a model-based approach, and farmer in-situ estimates to assess crop yields and water consumption. To implement the triple collocation appraisal, we first applied three independent evaluation methods, i.e., remotely sensed, model-based, and farmer in-situ estimates of crop yields and water consumption, to assess the crop water productivities of the systems. Triple-sensor collocation allows for the appraisal and comparison of estimation errors of measurement sensor systems, and enables the ranking of the estimators by their quality to represent the de-facto unknown true value, in our case: crop yields, water use, and its ratio CWP, in small-holder irrigated agriculture. The study entailed four main components: (1) collecting in-situ information and data from small-holder farmers on crop yields and water use; (2) derivation of remote sensing-based CWP from the FAO WaPOR open database and time series; (3) evaluation of biomass, crop yields and water use (evapotranspiration) using the AquaCrop model, integrating climate, soil data, and irrigation management practices; (4) performing and analysis of a categorical triple collocation analysis of the independent estimator data and performance ranking of the three sensing and small-holder irrigation systems. Maize and vegetables were used as main crops during three consecutive irrigation seasons (2017/18, 2018/19, 2019/20). Civil war prevented further field surveying, in-situ research, and data collection. The results indicate that remote sensing products are performed best in the modern and dam irrigation schemes for maize. For vegetables, AquaCrop performed best in the dam irrigation scheme.
{"title":"Using a Triple Sensor Collocation Approach to Evaluate Small-Holder Irrigation Scheme Performances in Northern Ethiopia","authors":"Amina Abdelkadir Mohammedshum, Ben H. P. Maathuis, Chris M. Mannaerts, Daniel Teka","doi":"10.3390/w16182638","DOIUrl":"https://doi.org/10.3390/w16182638","url":null,"abstract":"This study uses a triple-sensor collocation approach to evaluate the performance of small-holder irrigation schemes in the Zamra catchment of Northern Ethiopia. Crop water productivity (CWP), as an integrator of biomass production and water use, was used to compare the overall efficiencies of three types of irrigation systems: traditional and modern diversions, and dam-based irrigation water supply. Farmer-reported data often rely on observations, which can introduce human estimation and measurement errors. As a result, the evaluation of irrigation scheme performance has frequently been insufficient to fully explain crop water productivity. To overcome the challenges of using one single estimation method, we used a triple-sensor collocation approach to evaluate the efficiency of three small-scale irrigation schemes, using water productivity as an indicator. It employed three independent methods: remotely sensed data, a model-based approach, and farmer in-situ estimates to assess crop yields and water consumption. To implement the triple collocation appraisal, we first applied three independent evaluation methods, i.e., remotely sensed, model-based, and farmer in-situ estimates of crop yields and water consumption, to assess the crop water productivities of the systems. Triple-sensor collocation allows for the appraisal and comparison of estimation errors of measurement sensor systems, and enables the ranking of the estimators by their quality to represent the de-facto unknown true value, in our case: crop yields, water use, and its ratio CWP, in small-holder irrigated agriculture. The study entailed four main components: (1) collecting in-situ information and data from small-holder farmers on crop yields and water use; (2) derivation of remote sensing-based CWP from the FAO WaPOR open database and time series; (3) evaluation of biomass, crop yields and water use (evapotranspiration) using the AquaCrop model, integrating climate, soil data, and irrigation management practices; (4) performing and analysis of a categorical triple collocation analysis of the independent estimator data and performance ranking of the three sensing and small-holder irrigation systems. Maize and vegetables were used as main crops during three consecutive irrigation seasons (2017/18, 2018/19, 2019/20). Civil war prevented further field surveying, in-situ research, and data collection. The results indicate that remote sensing products are performed best in the modern and dam irrigation schemes for maize. For vegetables, AquaCrop performed best in the dam irrigation scheme.","PeriodicalId":23788,"journal":{"name":"Water","volume":"69 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Due to being lightweight, fine-grained sediments easily flow with water and thus amplify the destructive effect of debris flow hazards. In such hazards, water content and shear strength are key inter-controlled factors relating to the stability of fine-grained sediments and thus control the density, scale, and danger of debris flow hazards. Although the correlation between water content and sediment stability has been studied, there are still some issues to be solved: what is the changing trend of shear strength with increasing water content? What is the water content spatial distribution pattern of fine-grained sediments in debris flow? What is the role/impact of this pattern on debris flow hazards prevention? Therefore, the objective of this research is to show the spatial distribution pattern of water content and establish a correlation between the water content and the shear strength of fine-grained sediments to provide a scientific basis for debris flow hazard prevention. Taking the Beichuan debris flow for our study, with a length of 37.6 km, and a 341 km2 study area, the results show that (1) the average water content shows an increasing trend, from 9.9% in the upstream of the river (SP01–SP05) to 21.7% in the downstream of the river (SP13–SP15). (2) When unsaturated, the correlation between the water content and shear strength is determined by combining the cohesion, normal stress, and internal friction angle; when saturated, the water content is negatively correlated with shear strength. (3) Water content and shear strength are the key inter-controlled factors relating to the stability of fine-grained sediments, and the water content distribution pattern of this research indicates the key locations that require attention: locations with high water content in the downstream river or with high curvature, which is of some significance for debris flow hazard prevention.
{"title":"Research on Water Content Spatial Distribution Pattern of Fine—Grained Sediments in Debris Flow—Taking Beichuan Debris Flow as a Case","authors":"Qinjun Wang, Jingjing Xie, Jingyi Yang, Peng Liu, Wentao Xu, Boqi Yuan, Chaokang He","doi":"10.3390/w16182640","DOIUrl":"https://doi.org/10.3390/w16182640","url":null,"abstract":"Due to being lightweight, fine-grained sediments easily flow with water and thus amplify the destructive effect of debris flow hazards. In such hazards, water content and shear strength are key inter-controlled factors relating to the stability of fine-grained sediments and thus control the density, scale, and danger of debris flow hazards. Although the correlation between water content and sediment stability has been studied, there are still some issues to be solved: what is the changing trend of shear strength with increasing water content? What is the water content spatial distribution pattern of fine-grained sediments in debris flow? What is the role/impact of this pattern on debris flow hazards prevention? Therefore, the objective of this research is to show the spatial distribution pattern of water content and establish a correlation between the water content and the shear strength of fine-grained sediments to provide a scientific basis for debris flow hazard prevention. Taking the Beichuan debris flow for our study, with a length of 37.6 km, and a 341 km2 study area, the results show that (1) the average water content shows an increasing trend, from 9.9% in the upstream of the river (SP01–SP05) to 21.7% in the downstream of the river (SP13–SP15). (2) When unsaturated, the correlation between the water content and shear strength is determined by combining the cohesion, normal stress, and internal friction angle; when saturated, the water content is negatively correlated with shear strength. (3) Water content and shear strength are the key inter-controlled factors relating to the stability of fine-grained sediments, and the water content distribution pattern of this research indicates the key locations that require attention: locations with high water content in the downstream river or with high curvature, which is of some significance for debris flow hazard prevention.","PeriodicalId":23788,"journal":{"name":"Water","volume":"201 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Our research project specifically focuses on evaluating groundwater quality in six West Texas counties. We aim to determine whether environmental changes have any impact on the levels of Total Dissolved Solids (TDS) in the water supplied to the public. To achieve this goal, we will be utilizing advanced machine learning algorithms to analyze TDS levels and create geospatial maps for each year between the 1990s and 2010s. To ensure the accuracy of our data, we have gathered information from two trusted sources: the Texas Water Development Board (TWDB) and the Groundwater Database (GWDB). We have analyzed the TDS and other elemental analyses from TWDB–GWDB lab reports and compared them with the quality cutoff set by the World Health Organization (WHO). Our approach involves a thorough examination of the data to identify any emerging patterns. The machine learning algorithm has been successfully trained and tested, producing highly accurate results that effectively predict water quality. Our results have been validated through extensive testing, highlighting the potential of machine learning approaches in the fields of environmental research. Overall, our findings will contribute to the development of more effective policies and regulations in predicting groundwater quality and improving water resource management in Texas. Therefore, this research provides important information for groundwater protection and the development of plans for water resource use in the future.
{"title":"Machine Learning Algorithms for Water Quality Management Using Total Dissolved Solids (TDS) Data Analysis","authors":"Julio Garcia, Joonghyeok Heo, Cheolhong Kim","doi":"10.3390/w16182639","DOIUrl":"https://doi.org/10.3390/w16182639","url":null,"abstract":"Our research project specifically focuses on evaluating groundwater quality in six West Texas counties. We aim to determine whether environmental changes have any impact on the levels of Total Dissolved Solids (TDS) in the water supplied to the public. To achieve this goal, we will be utilizing advanced machine learning algorithms to analyze TDS levels and create geospatial maps for each year between the 1990s and 2010s. To ensure the accuracy of our data, we have gathered information from two trusted sources: the Texas Water Development Board (TWDB) and the Groundwater Database (GWDB). We have analyzed the TDS and other elemental analyses from TWDB–GWDB lab reports and compared them with the quality cutoff set by the World Health Organization (WHO). Our approach involves a thorough examination of the data to identify any emerging patterns. The machine learning algorithm has been successfully trained and tested, producing highly accurate results that effectively predict water quality. Our results have been validated through extensive testing, highlighting the potential of machine learning approaches in the fields of environmental research. Overall, our findings will contribute to the development of more effective policies and regulations in predicting groundwater quality and improving water resource management in Texas. Therefore, this research provides important information for groundwater protection and the development of plans for water resource use in the future.","PeriodicalId":23788,"journal":{"name":"Water","volume":"15 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Luigi Rosati, Federica Carraturo, Fiore Capozzi, Teresa Chianese, Alessandra La Pietra, Michela Salamone, Valeria Spagnuolo, Ida Ferrandino, Simonetta Giordano
Microplastics (MPs) persist for long periods in the environment, causing adverse effects on aquatic and terrestrial ecosystems. The accumulation of MPs in various trophic levels mostly depends on weathering phenomena, their reduced dimensions and the improved bioavailability; this ultimately causes their ingestion by organisms living in different niches. The modern concern about MPs toxicity collides with the current unavailability of standardized and reliable methodologies to assess the risks associated with the exposure of organisms from different habitats. Hence, the identification and selection of appropriate biomonitors for MPs pollution risk assessment should focus on the identification of easy-to-implement assays, rapidly interpretable results (e.g., based on the MPs bioaccumulation capabilities in their tissues) and standardizable methodologies. The present review analyzed some emerging biomonitors exploited for MPs evaluation, selected and examined according to their potential use as specific biological indicators for diverse environments. The research was focused on plants, as biological models for airborne microfibers toxicity evaluation; mussels, as key organisms for the establishment of MPs accumulation in marine environments; land snails, representing emerging organisms selected for studies of MPs’ impact on soil. Furthermore, recent findings evidenced the influence of microplastics on the composition of environmental microbiota, enhancing pathogenic biofilms formation, leading to increased water, soil, food, crops and waste contamination. Disposing of harmonized and validated methods to study MPs’ impact on the environment, integrated with promising machine learning tools, might sensibly support the risk management strategies protecting human and animal health.
{"title":"Microplastics’ Impact on the Environment and the Challenging Selection of Reliable Key Biomonitors","authors":"Luigi Rosati, Federica Carraturo, Fiore Capozzi, Teresa Chianese, Alessandra La Pietra, Michela Salamone, Valeria Spagnuolo, Ida Ferrandino, Simonetta Giordano","doi":"10.3390/w16182637","DOIUrl":"https://doi.org/10.3390/w16182637","url":null,"abstract":"Microplastics (MPs) persist for long periods in the environment, causing adverse effects on aquatic and terrestrial ecosystems. The accumulation of MPs in various trophic levels mostly depends on weathering phenomena, their reduced dimensions and the improved bioavailability; this ultimately causes their ingestion by organisms living in different niches. The modern concern about MPs toxicity collides with the current unavailability of standardized and reliable methodologies to assess the risks associated with the exposure of organisms from different habitats. Hence, the identification and selection of appropriate biomonitors for MPs pollution risk assessment should focus on the identification of easy-to-implement assays, rapidly interpretable results (e.g., based on the MPs bioaccumulation capabilities in their tissues) and standardizable methodologies. The present review analyzed some emerging biomonitors exploited for MPs evaluation, selected and examined according to their potential use as specific biological indicators for diverse environments. The research was focused on plants, as biological models for airborne microfibers toxicity evaluation; mussels, as key organisms for the establishment of MPs accumulation in marine environments; land snails, representing emerging organisms selected for studies of MPs’ impact on soil. Furthermore, recent findings evidenced the influence of microplastics on the composition of environmental microbiota, enhancing pathogenic biofilms formation, leading to increased water, soil, food, crops and waste contamination. Disposing of harmonized and validated methods to study MPs’ impact on the environment, integrated with promising machine learning tools, might sensibly support the risk management strategies protecting human and animal health.","PeriodicalId":23788,"journal":{"name":"Water","volume":"16 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Martín Alfredo Legarreta-González, César A. Meza-Herrera, Rafael Rodríguez-Martínez, Carlos Servando Chávez-Tiznado, Francisco Gerardo Véliz-Deras
Water is a vital resource for sustaining life and for numerous processes within the transformation industry. It is a finite resource, albeit one that can be renewed, and thus sustainable management is imperative. To achieve this objective, it is necessary to have the appropriate tools to assist with the planning policies for its management. This paper presents a time series analysis approach to measure and predict the pattern of water consumption by humans throughout subsectors (domestic, commercial, public sector, education, industry, and raw water) and total water consumption in Meoqui, Chihuahua, Mexico with data from 2011 to 2023, applying calibration model techniques to measure uncertainty in the forecasting. The municipality of Meoqui encompasses an area of 342 km2. The climate is semi-arid, with an average annual rainfall of 272 mm and average temperatures of 26.4 °C in summer and 9.7 °C in winter. The municipal seat, which has a population of 23,140, is supplied with water from ten wells, with an average consumption of 20 ± 579 m3 per user. The consumption of the general population indicates the existence of a seasonal autoregressive integrated moving average (SARIMA) (0,1,2)(0,0,2)12 model. (Sen’s Slope = 682.7, p < 0.001). The domestic sector exhibited the highest overall consumption, with a total volume of 17,169,009 m3 (13 ± 93). A SARIMA (2,1,0)(2,0,0)12 model was estimated, with a Sen’s slope of 221.65 and a p-value of less than 0.001. The second-largest consumer of total water was the “raw water” sector, which consumed 5,124,795 (30,146 ± 35,841) m3 and exhibited an SARIMA (0,1,1)(2,0,0)12 model with no statistically significant trend. The resulting models will facilitate the company’s ability to define water resource management strategies in a sustainable manner, in alignment with projected consumption trends.
{"title":"Time Series Analysis to Estimate the Volume of Drinking Water Consumption in the City of Meoqui, Chihuahua, Mexico","authors":"Martín Alfredo Legarreta-González, César A. Meza-Herrera, Rafael Rodríguez-Martínez, Carlos Servando Chávez-Tiznado, Francisco Gerardo Véliz-Deras","doi":"10.3390/w16182634","DOIUrl":"https://doi.org/10.3390/w16182634","url":null,"abstract":"Water is a vital resource for sustaining life and for numerous processes within the transformation industry. It is a finite resource, albeit one that can be renewed, and thus sustainable management is imperative. To achieve this objective, it is necessary to have the appropriate tools to assist with the planning policies for its management. This paper presents a time series analysis approach to measure and predict the pattern of water consumption by humans throughout subsectors (domestic, commercial, public sector, education, industry, and raw water) and total water consumption in Meoqui, Chihuahua, Mexico with data from 2011 to 2023, applying calibration model techniques to measure uncertainty in the forecasting. The municipality of Meoqui encompasses an area of 342 km2. The climate is semi-arid, with an average annual rainfall of 272 mm and average temperatures of 26.4 °C in summer and 9.7 °C in winter. The municipal seat, which has a population of 23,140, is supplied with water from ten wells, with an average consumption of 20 ± 579 m3 per user. The consumption of the general population indicates the existence of a seasonal autoregressive integrated moving average (SARIMA) (0,1,2)(0,0,2)12 model. (Sen’s Slope = 682.7, p < 0.001). The domestic sector exhibited the highest overall consumption, with a total volume of 17,169,009 m3 (13 ± 93). A SARIMA (2,1,0)(2,0,0)12 model was estimated, with a Sen’s slope of 221.65 and a p-value of less than 0.001. The second-largest consumer of total water was the “raw water” sector, which consumed 5,124,795 (30,146 ± 35,841) m3 and exhibited an SARIMA (0,1,1)(2,0,0)12 model with no statistically significant trend. The resulting models will facilitate the company’s ability to define water resource management strategies in a sustainable manner, in alignment with projected consumption trends.","PeriodicalId":23788,"journal":{"name":"Water","volume":"21 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study investigates the long-term trends (1992–2022) of nitrogen and phosphorus loadings exported by the River Po to the Adriatic Sea, to better analyse how changes in hydrology are affecting the timing and magnitude of river nutrient loads. We used 30 years of monitoring data in order to (a) identify the main temporal patterns and their interactions at a decadal, annual and seasonal scale, (b) estimate precipitation effects on load formation and evaluate whether and to which extent the hydrological regime affects nutrient export across the years and (c) analyse the nutrient export regime at a monthly scale and the main transport dynamic of N and P chemical species (hydrological vs. biogeochemical control). The long-term analysis shows a general decrease of both P and N loadings, but the trends are different between the elements and their chemical species, as well as undergoing different seasonal variations. We found a statistically significant relationships between precipitation and loads, which demonstrates that precipitation patterns drive the exported load at the intra- and interannual time scales considered in this study. Precipitation-induced load trends trigger seasonal changes in nutrient deliveries to the sea, peaking in spring and autumn. The nitrogen decrease is mainly concentrated in the summer dry period, while total phosphorus diminishes mainly in spring and autumn. This mismatch of N and P results in variable molar N:P ratios within the year. The effects of extreme drought and flood events, along with the progressive decrease in the snowmelt contribution to water fluxes, are expected to exacerbate the variability in the N and P loadings, which in turn is expected to perturbate the biodiversity, food webs and trophic state of the Northern Adriatic Sea.
{"title":"Seasonal Variability and Hydrological Patterns Influence the Long-Term Trends of Nutrient Loads in the River Po","authors":"Edoardo Cavallini, Pierluigi Viaroli, Mariachiara Naldi, Mattia Saccò, Alessandro Scibona, Elena Barbieri, Silvia Franceschini, Daniele Nizzoli","doi":"10.3390/w16182628","DOIUrl":"https://doi.org/10.3390/w16182628","url":null,"abstract":"This study investigates the long-term trends (1992–2022) of nitrogen and phosphorus loadings exported by the River Po to the Adriatic Sea, to better analyse how changes in hydrology are affecting the timing and magnitude of river nutrient loads. We used 30 years of monitoring data in order to (a) identify the main temporal patterns and their interactions at a decadal, annual and seasonal scale, (b) estimate precipitation effects on load formation and evaluate whether and to which extent the hydrological regime affects nutrient export across the years and (c) analyse the nutrient export regime at a monthly scale and the main transport dynamic of N and P chemical species (hydrological vs. biogeochemical control). The long-term analysis shows a general decrease of both P and N loadings, but the trends are different between the elements and their chemical species, as well as undergoing different seasonal variations. We found a statistically significant relationships between precipitation and loads, which demonstrates that precipitation patterns drive the exported load at the intra- and interannual time scales considered in this study. Precipitation-induced load trends trigger seasonal changes in nutrient deliveries to the sea, peaking in spring and autumn. The nitrogen decrease is mainly concentrated in the summer dry period, while total phosphorus diminishes mainly in spring and autumn. This mismatch of N and P results in variable molar N:P ratios within the year. The effects of extreme drought and flood events, along with the progressive decrease in the snowmelt contribution to water fluxes, are expected to exacerbate the variability in the N and P loadings, which in turn is expected to perturbate the biodiversity, food webs and trophic state of the Northern Adriatic Sea.","PeriodicalId":23788,"journal":{"name":"Water","volume":"5 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The acceleration of urbanization has disrupted natural water cycles, resulting in increased impervious urban surfaces and non-point source pollution from stormwater runoff. Addressing urban stormwater recharge has become crucial. This study introduces a novel silica sand-based permeable filtration material, investigating its surface characteristics, pore structure, permeability, and pollutant interception capabilities. The results demonstrate that hydrophilic binder coating modification of the permeable surface sand aggregate, combined with hydrophilic inorganic additives, having a porous structure with an average pore size of less than 50 μm and a porosity between 15% and 35%, significantly enhances surface hydrophilicity, achieving a permeation rate of up to 6.8 mL/(min·cm²). Moreover, it shows exceptional filtration and anti-clogging properties, achieving over 98% suspended solids interception and strong resistance to fouling. Dynamic biofilm formation experiments using simulated rain and domestic wastewater explore biofilm morphology and function on silica sand filtration well surfaces. Mature biofilms sustain COD removal efficiency exceeding 70%, with levels consistently below 50 mg/L, NH4+ decreasing to 2 mg N/L, and total nitrogen maintained below 10 mg N/L. The system features anoxic, anoxic, and aerobic zones, fostering synergistic organic matter and nitrogen removal by diverse microorganisms, enhancing pollutant mitigation. Silica sand-based permeable filtration material effectively mitigates urban stormwater runoff pollutants—suspended solids, organic matter, and nitrogen—offering an innovative solution for sponge city development and rainwater resource management.
{"title":"Characterization of Silica Sand-Based Pervious Bricks and Their Performance under Stormwater Treatment","authors":"Meijuan Chen, Weiying Li, Zhiqiang Dong, Dawei Zhang","doi":"10.3390/w16182625","DOIUrl":"https://doi.org/10.3390/w16182625","url":null,"abstract":"The acceleration of urbanization has disrupted natural water cycles, resulting in increased impervious urban surfaces and non-point source pollution from stormwater runoff. Addressing urban stormwater recharge has become crucial. This study introduces a novel silica sand-based permeable filtration material, investigating its surface characteristics, pore structure, permeability, and pollutant interception capabilities. The results demonstrate that hydrophilic binder coating modification of the permeable surface sand aggregate, combined with hydrophilic inorganic additives, having a porous structure with an average pore size of less than 50 μm and a porosity between 15% and 35%, significantly enhances surface hydrophilicity, achieving a permeation rate of up to 6.8 mL/(min·cm²). Moreover, it shows exceptional filtration and anti-clogging properties, achieving over 98% suspended solids interception and strong resistance to fouling. Dynamic biofilm formation experiments using simulated rain and domestic wastewater explore biofilm morphology and function on silica sand filtration well surfaces. Mature biofilms sustain COD removal efficiency exceeding 70%, with levels consistently below 50 mg/L, NH4+ decreasing to 2 mg N/L, and total nitrogen maintained below 10 mg N/L. The system features anoxic, anoxic, and aerobic zones, fostering synergistic organic matter and nitrogen removal by diverse microorganisms, enhancing pollutant mitigation. Silica sand-based permeable filtration material effectively mitigates urban stormwater runoff pollutants—suspended solids, organic matter, and nitrogen—offering an innovative solution for sponge city development and rainwater resource management.","PeriodicalId":23788,"journal":{"name":"Water","volume":"3 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study focuses on the comparative analysis and research of the raindrop size distribution (DSD) in the outer rainband and inner rainband of Typhoon “Noru” in 2022, using the OTT-Parsivel raindrop spectrometer deployed on Yongxing Island, Sansha City. The results indicate that precipitation intensity is lower when composed mainly of small and medium raindrops and increases with the presence of larger raindrops. Stronger precipitation is associated with a higher number of large raindrops. Due to the interaction of cold and warm air masses, the raindrop concentration is higher, and the raindrop diameters are larger compared to Typhoons “LEKIMA” and “RUMBIA”. The entire process predominantly consists of numerous small- to medium-sized raindrops, characteristic of a tropical typhoon. The precipitation in the inner and outer rainbands exhibits consistent types, characterized by a unimodal raindrop size distribution with a narrow spectral width, typical of stratiform-mixed cloud precipitation, where stratiform precipitation constitutes a significant portion. Strong echo reflectivity factors are often associated with higher raindrop number concentrations and larger particle sizes. The Z-R relationship of the precipitation shows a smaller coefficient but a consistent exponent compared to the standard. The calculated shape parameter slope relationship is Λ=0.02μ2+0.696μ+1.539, providing a reference for localizing the Z-R relationship in the South China Sea.
{"title":"Raindrop Size Distribution Characteristics of the Precipitation Process of 2216 Typhoon “Noru” in the Xisha Region","authors":"Guozhang Wang, Lei Li, Chaoying Huang, Lili Zhang","doi":"10.3390/w16182630","DOIUrl":"https://doi.org/10.3390/w16182630","url":null,"abstract":"This study focuses on the comparative analysis and research of the raindrop size distribution (DSD) in the outer rainband and inner rainband of Typhoon “Noru” in 2022, using the OTT-Parsivel raindrop spectrometer deployed on Yongxing Island, Sansha City. The results indicate that precipitation intensity is lower when composed mainly of small and medium raindrops and increases with the presence of larger raindrops. Stronger precipitation is associated with a higher number of large raindrops. Due to the interaction of cold and warm air masses, the raindrop concentration is higher, and the raindrop diameters are larger compared to Typhoons “LEKIMA” and “RUMBIA”. The entire process predominantly consists of numerous small- to medium-sized raindrops, characteristic of a tropical typhoon. The precipitation in the inner and outer rainbands exhibits consistent types, characterized by a unimodal raindrop size distribution with a narrow spectral width, typical of stratiform-mixed cloud precipitation, where stratiform precipitation constitutes a significant portion. Strong echo reflectivity factors are often associated with higher raindrop number concentrations and larger particle sizes. The Z-R relationship of the precipitation shows a smaller coefficient but a consistent exponent compared to the standard. The calculated shape parameter slope relationship is Λ=0.02μ2+0.696μ+1.539, providing a reference for localizing the Z-R relationship in the South China Sea.","PeriodicalId":23788,"journal":{"name":"Water","volume":"15 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Elena Vialkova, Elena Korshikova, Anastasiya Fugaeva
Turning to green technologies in wastewater treatment is a well-known global trend. The use of natural sorbents of plant origin or phytosorbents in order to purify water from various types of pollutants is becoming more and more popular. This solves several important problems at once: the use of harmless natural materials, reducing the cost of processing, and waste disposal. Moreover, there is a global increase in waste in the agricultural, food, woodworking, and other industries. This review presents data on the modern use of natural materials, mainly vegetable waste, as sorbents in wastewater treatment technologies. Natural materials remove ion metals, dyes, crude oil and petroleum products, and other organic and non-organic contaminants. The techniques of obtaining phytosorbents from plant raw materials are considered. The methods for activation and modification of the various phytosorbents, which provide greater sorption efficiency, are presented. The adsorption mechanisms for various water contaminants are examined, and model descriptions are shown. It has been revealed that the effectiveness of sorption interaction mainly depends on the presence of functional groups. Studies over the past twenty years have shown good prospects for the use of such materials and technologies in practice.
{"title":"Phytosorbents in Wastewater Treatment Technologies: Review","authors":"Elena Vialkova, Elena Korshikova, Anastasiya Fugaeva","doi":"10.3390/w16182626","DOIUrl":"https://doi.org/10.3390/w16182626","url":null,"abstract":"Turning to green technologies in wastewater treatment is a well-known global trend. The use of natural sorbents of plant origin or phytosorbents in order to purify water from various types of pollutants is becoming more and more popular. This solves several important problems at once: the use of harmless natural materials, reducing the cost of processing, and waste disposal. Moreover, there is a global increase in waste in the agricultural, food, woodworking, and other industries. This review presents data on the modern use of natural materials, mainly vegetable waste, as sorbents in wastewater treatment technologies. Natural materials remove ion metals, dyes, crude oil and petroleum products, and other organic and non-organic contaminants. The techniques of obtaining phytosorbents from plant raw materials are considered. The methods for activation and modification of the various phytosorbents, which provide greater sorption efficiency, are presented. The adsorption mechanisms for various water contaminants are examined, and model descriptions are shown. It has been revealed that the effectiveness of sorption interaction mainly depends on the presence of functional groups. Studies over the past twenty years have shown good prospects for the use of such materials and technologies in practice.","PeriodicalId":23788,"journal":{"name":"Water","volume":"15 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Marcelo Rocha dos Santos, Jucilene Silva Araújo, Sérgio Luiz Rodrigues Donato, José Alberto Alves de Souza, Elder Cunha de Lira, Ignacio Aspiazú
The reuse of wastewater from domestic sewage can contribute to forage production in regions with limited water availability. The aim was to study the agronomic performance of Gigante, Miúda, and Orelha de Elefante Mexicana cactus pear cultivars irrigated with treated sewage water; contents of macro- and micronutrients in plant tissues; export of nutrients and productivity. The study was conducted in an area near the domestic sewage treatment plant in the municipality of Guanambi, Bahia, Brazil. The experimental design was completely randomized blocks, with six replications. A drip irrigation system was used, with a flow rate of 1.6 L h−1 and a watering interval of three days, applying 33% of the reference evapotranspiration. The physical/chemical characteristics of the soil, dry matter content, nutritional content of the forage cactus pear, productivity, and soil quality were evaluated. Without soil correction or application of mineral or organic fertilizers, only with the application of wastewater, the forage cactus pear plants developed within expected standards. The ‘Orelha de Elefante Mexicana’ and the ‘Gigante’ show greater green mass productivity and irrigation water productivity for green mass when compared to the ‘Miúda’. The highest dry matter productivity is expressed by the Orelha de Elefante Mexicana cultivar. The decreasing order of macronutrient export by the forage cactus pear is K, Ca, N, Mg, S, and P, and Mn, Fe, Zn, B, and Cu for micronutrients. Irrigation with treated wastewater, using 33% of the reference evapotranspiration, maintains K contents within a sufficient range; however, for the other nutrients, it is insufficient for the forage cactus pear plants.
在水源有限的地区，生活污水的再利用有助于饲草生产。目的是研究用处理过的污水灌溉 Gigante、Miúda 和 Orelha de Elefante Mexicana 仙人掌梨栽培品种的农艺表现、植物组织中宏量和微量营养元素的含量、营养元素的输出和产量。研究在巴西巴伊亚州瓜南比市生活污水处理厂附近的一个地区进行。实验设计为完全随机区组，六次重复。采用滴灌系统，流量为 1.6 升/小时，浇水间隔为三天，浇水量为参考蒸散量的 33%。对土壤的物理/化学特性、干物质含量、仙人掌果的营养成分、生产力和土壤质量进行了评估。在没有进行土壤改良、施用矿物肥料或有机肥料的情况下，只有在施用废水后，仙人掌果植株的生长发育才符合预期标准。与 "Miúda "相比，"Orelha de Elefante Mexicana "和 "Gigante "显示出更高的绿色质量生产率和绿色质量灌溉水生产率。Orelha de Elefante Mexicana 的干物质生产率最高。仙人掌梨牧草输出的宏量营养元素依次为 K、Ca、N、Mg、S 和 P，微量营养元素依次为 Mn、Fe、Zn、B 和 Cu。用经过处理的废水进行灌溉，相当于参考蒸发量的 33%，可使钾的含量保持在足够的范围内；但对于其他养分而言，则不足以满足仙人掌果植株的需要。
{"title":"Forage Cactus Pear Cultivars Irrigated with Wastewater in a Semi-Arid Region","authors":"Marcelo Rocha dos Santos, Jucilene Silva Araújo, Sérgio Luiz Rodrigues Donato, José Alberto Alves de Souza, Elder Cunha de Lira, Ignacio Aspiazú","doi":"10.3390/w16182632","DOIUrl":"https://doi.org/10.3390/w16182632","url":null,"abstract":"The reuse of wastewater from domestic sewage can contribute to forage production in regions with limited water availability. The aim was to study the agronomic performance of Gigante, Miúda, and Orelha de Elefante Mexicana cactus pear cultivars irrigated with treated sewage water; contents of macro- and micronutrients in plant tissues; export of nutrients and productivity. The study was conducted in an area near the domestic sewage treatment plant in the municipality of Guanambi, Bahia, Brazil. The experimental design was completely randomized blocks, with six replications. A drip irrigation system was used, with a flow rate of 1.6 L h−1 and a watering interval of three days, applying 33% of the reference evapotranspiration. The physical/chemical characteristics of the soil, dry matter content, nutritional content of the forage cactus pear, productivity, and soil quality were evaluated. Without soil correction or application of mineral or organic fertilizers, only with the application of wastewater, the forage cactus pear plants developed within expected standards. The ‘Orelha de Elefante Mexicana’ and the ‘Gigante’ show greater green mass productivity and irrigation water productivity for green mass when compared to the ‘Miúda’. The highest dry matter productivity is expressed by the Orelha de Elefante Mexicana cultivar. The decreasing order of macronutrient export by the forage cactus pear is K, Ca, N, Mg, S, and P, and Mn, Fe, Zn, B, and Cu for micronutrients. Irrigation with treated wastewater, using 33% of the reference evapotranspiration, maintains K contents within a sufficient range; however, for the other nutrients, it is insufficient for the forage cactus pear plants.","PeriodicalId":23788,"journal":{"name":"Water","volume":"11 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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