Jason P. Julian, Courtney Stuhldreher, Madeline T. Wade
The classification of stream flow regimes has been a subject of study for over a half century in the fields of hydrology, geomorphology, ecology, and water resources management. But with the most recent Supreme Court decision on jurisdictional Waters of the United States (WOTUS) and the 2023 Conforming Rule, the answer to the question of which waters are relatively permanent has increased in importance and urgency. One state where this question is salient is Arizona, where approximately 95% of its streams are nonperennial. In this study, we use long-term (> 30 years) daily discharge records from Arizona to assess semi-natural flow regimes of arid streams within the context of the 2023 Conforming Rule. Using flow percentile distributions, we distinguished flow permanency—ephemeral vs. intermittent vs. perennial—for 70 stream reaches distributed throughout the state. Ephemeral streams had a median flow of 0 cms and a 75th percentile flow permanence less than 25% (i.e., less than 3 months of flow for every 7.5 out of 10 years). On the other end of the spectrum, perennial streams had a 90th percentile flow permanence of 100%. In the middle, intermittent streams had a 75th percentile flow permanence greater than 25% and a 90th percentile flow permanence less than 100%. We also assessed the effect of the recent megadrought (since 1994) on flow permanency. As a result of the megadrought, four perennial streams transitioned to intermittent, four intermittent streams transitioned to ephemeral, and one perennial stream became ephemeral. The flow classification we present here is specific to Arizona streams but could be useful to other arid regions seeking to answer the question of which streams are relatively permanent in a typical year.
{"title":"What Is Relatively Permanent? Flow Regimes of Arizona Streams within the Context of the 2023 Conforming Rule on the Revised Definition of “Waters of the United States”","authors":"Jason P. Julian, Courtney Stuhldreher, Madeline T. Wade","doi":"10.3390/w16182641","DOIUrl":"https://doi.org/10.3390/w16182641","url":null,"abstract":"The classification of stream flow regimes has been a subject of study for over a half century in the fields of hydrology, geomorphology, ecology, and water resources management. But with the most recent Supreme Court decision on jurisdictional Waters of the United States (WOTUS) and the 2023 Conforming Rule, the answer to the question of which waters are relatively permanent has increased in importance and urgency. One state where this question is salient is Arizona, where approximately 95% of its streams are nonperennial. In this study, we use long-term (> 30 years) daily discharge records from Arizona to assess semi-natural flow regimes of arid streams within the context of the 2023 Conforming Rule. Using flow percentile distributions, we distinguished flow permanency—ephemeral vs. intermittent vs. perennial—for 70 stream reaches distributed throughout the state. Ephemeral streams had a median flow of 0 cms and a 75th percentile flow permanence less than 25% (i.e., less than 3 months of flow for every 7.5 out of 10 years). On the other end of the spectrum, perennial streams had a 90th percentile flow permanence of 100%. In the middle, intermittent streams had a 75th percentile flow permanence greater than 25% and a 90th percentile flow permanence less than 100%. We also assessed the effect of the recent megadrought (since 1994) on flow permanency. As a result of the megadrought, four perennial streams transitioned to intermittent, four intermittent streams transitioned to ephemeral, and one perennial stream became ephemeral. The flow classification we present here is specific to Arizona streams but could be useful to other arid regions seeking to answer the question of which streams are relatively permanent in a typical year.","PeriodicalId":23788,"journal":{"name":"Water","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254659","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 paper develops a method integrating Geographic Information Systems (GIS) and the Decision-Making Trials and Evaluation Laboratory (DEMATEL) for the analysis of factors influencing urban flood risk and the identification of flood-prone areas. The method is based on nine selected factors: land use/land cover (LULC: the ratio of built-up areas, the ratio of greenery areas), elevation, slope, population density, distance from the river, soil, Topographic Wetness Index (TWI), and Normalized Difference Vegetation Index (NDVI). The DEMATEL method is used to determine the cause–effect relationship between selected factors, allowing for key criteria and their weights to be determined. LULC and population density were identified as the most important risk factors for urban floods. The method was applied to a case study—the Serafa River watershed (Poland), an urbanized catchment covering housing estates of cities of Kraków and Wieliczka frequently affected by flooding. GIS analysis based on publicly available data using QGIS with weights obtained from DEMATEL identified the vulnerable areas. 45% of the total catchment area was classified as areas with a very high or high level of flood risk. The results match the actual data on inundation incidents that occurred in recent years in this area. The study shows the potential and possibility of using the DEMATEL-GIS method to determine the significance of factors and to designate flood-prone areas.
{"title":"Urban Flood Risk Assessment and Mapping Using GIS-DEMATEL Method: Case of the Serafa River Watershed, Poland","authors":"Wiktoria Natkaniec, Izabela Godyń","doi":"10.3390/w16182636","DOIUrl":"https://doi.org/10.3390/w16182636","url":null,"abstract":"This paper develops a method integrating Geographic Information Systems (GIS) and the Decision-Making Trials and Evaluation Laboratory (DEMATEL) for the analysis of factors influencing urban flood risk and the identification of flood-prone areas. The method is based on nine selected factors: land use/land cover (LULC: the ratio of built-up areas, the ratio of greenery areas), elevation, slope, population density, distance from the river, soil, Topographic Wetness Index (TWI), and Normalized Difference Vegetation Index (NDVI). The DEMATEL method is used to determine the cause–effect relationship between selected factors, allowing for key criteria and their weights to be determined. LULC and population density were identified as the most important risk factors for urban floods. The method was applied to a case study—the Serafa River watershed (Poland), an urbanized catchment covering housing estates of cities of Kraków and Wieliczka frequently affected by flooding. GIS analysis based on publicly available data using QGIS with weights obtained from DEMATEL identified the vulnerable areas. 45% of the total catchment area was classified as areas with a very high or high level of flood risk. The results match the actual data on inundation incidents that occurred in recent years in this area. The study shows the potential and possibility of using the DEMATEL-GIS method to determine the significance of factors and to designate flood-prone areas.","PeriodicalId":23788,"journal":{"name":"Water","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254655","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}
Elisa Benà, Pierluigi Giacò, Sara Demaria, Roberta Marchesini, Michele Melis, Giulia Zanotti, Costanza Baldisserotto, Simonetta Pancaldi
The global population increase during the last century has significantly amplified freshwater demand, leading to higher wastewater (WW) production. European regulations necessitate treating WW before environmental. Microalgae have gained attention for wastewater treatment (WWT) due to their efficiency in remediating nutrients and pollutants, alongside producing valuable biomass. This study investigates the phycoremediation potential of a Chlorella-like strain isolated from urban WW in a 600L-scale system under winter conditions. Experiments in December 2021 and February 2022 tested the strain’s adaptability to varying environmental conditions, particularly temperatures (min-max temperature range: from −3.69 to 10.61 °C in December and −3.96 to 17.61 °C in February), and its ability to meet legal discharge limits. In December, low temperatures algal growth. Nitrates showed an RE of about 92%, while ammonia slightly decreased (RE, about 32%), and phosphorous remained unchanged. In February, mild temperatures increased algal density (33.3 × 106 cell mL−1) and, at the end of experiment, all nutrients were below legal limits with very high RE % (NH4+, 91.43; PO43− 97.32). Both trials showed an E. coli RE, % = 99%. The study highlights the potential of microalgae for WWT and the importance of considering seasonal variations when implementing these systems.
{"title":"Winter Season Outdoor Cultivation of an Autochthonous Chlorella-Strain in a Pilot-Scale Prototype for Urban Wastewater Treatment","authors":"Elisa Benà, Pierluigi Giacò, Sara Demaria, Roberta Marchesini, Michele Melis, Giulia Zanotti, Costanza Baldisserotto, Simonetta Pancaldi","doi":"10.3390/w16182635","DOIUrl":"https://doi.org/10.3390/w16182635","url":null,"abstract":"The global population increase during the last century has significantly amplified freshwater demand, leading to higher wastewater (WW) production. European regulations necessitate treating WW before environmental. Microalgae have gained attention for wastewater treatment (WWT) due to their efficiency in remediating nutrients and pollutants, alongside producing valuable biomass. This study investigates the phycoremediation potential of a Chlorella-like strain isolated from urban WW in a 600L-scale system under winter conditions. Experiments in December 2021 and February 2022 tested the strain’s adaptability to varying environmental conditions, particularly temperatures (min-max temperature range: from −3.69 to 10.61 °C in December and −3.96 to 17.61 °C in February), and its ability to meet legal discharge limits. In December, low temperatures algal growth. Nitrates showed an RE of about 92%, while ammonia slightly decreased (RE, about 32%), and phosphorous remained unchanged. In February, mild temperatures increased algal density (33.3 × 106 cell mL−1) and, at the end of experiment, all nutrients were below legal limits with very high RE % (NH4+, 91.43; PO43− 97.32). Both trials showed an E. coli RE, % = 99%. The study highlights the potential of microalgae for WWT and the importance of considering seasonal variations when implementing these systems.","PeriodicalId":23788,"journal":{"name":"Water","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254653","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":null,"pages":null},"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}
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":null,"pages":null},"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}
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":null,"pages":null},"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}
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":null,"pages":null},"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}
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":null,"pages":null},"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}
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":null,"pages":null},"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}
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":null,"pages":null},"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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：