This page has only limited features, please log in for full access.
The monitoring of surface-water quality followed by water-quality modeling and analysis are essential for generating effective strategies in surface-water-resource management. However, worldwide, particularly in developing countries, water-quality studies are limited due to the lack of a complete and reliable dataset of surface-water-quality variables. In this context, several statistical and machine-learning models were assessed for imputing water-quality data at six monitoring stations located in the Santa Lucía Chico river (Uruguay), a mixed lotic and lentic river system. The challenge of this study is represented by the high percentage of missing data (between 50% and 70%) and the high temporal and spatial variability that characterizes the water-quality variables. The competing algorithms implement univariate and multivariate imputation methods (inverse distance weighting (IDW), Random Forest Regressor (RFR), Ridge (R), Bayesian Ridge (BR), AdaBoost (AB), Hubber Regressor (HR), Support Vector Regressor (SVR) and K-nearest neighbors Regressor (KNNR)). According to the results, more than 76% of the imputation outcomes are considered “satisfactory” (NSE > 0.45). The imputation performance shows better results at the monitoring stations located inside the reservoir than those positioned along the mainstream. IDW was the model with the best imputation results, followed by RFR, HR and SVR. The approach proposed in this study is expected to aid water-resource researchers and managers in augmenting water-quality datasets and overcoming the missing data issue to increase the number of future studies related to the water-quality matter.
Rafael Rodríguez; Marcos Pastorini; Lorena Etcheverry; Christian Chreties; Mónica Fossati; Alberto Castro; Angela Gorgoglione. Water-Quality Data Imputation with a High Percentage of Missing Values: A Machine Learning Approach. Sustainability 2021, 13, 6318 .
AMA StyleRafael Rodríguez, Marcos Pastorini, Lorena Etcheverry, Christian Chreties, Mónica Fossati, Alberto Castro, Angela Gorgoglione. Water-Quality Data Imputation with a High Percentage of Missing Values: A Machine Learning Approach. Sustainability. 2021; 13 (11):6318.
Chicago/Turabian StyleRafael Rodríguez; Marcos Pastorini; Lorena Etcheverry; Christian Chreties; Mónica Fossati; Alberto Castro; Angela Gorgoglione. 2021. "Water-Quality Data Imputation with a High Percentage of Missing Values: A Machine Learning Approach." Sustainability 13, no. 11: 6318.
The monitoring of surface-water quality followed by water-quality modeling and analysis is essential for generating effective strategies in water-resource management. However, worldwide, particularly in developing countries, water-quality studies are limited due to the lack of a complete and reliable dataset of surface-water-quality variables. In this context, several statistical and machine-learning models were assessed for imputing water-quality data at six monitoring stations located in the Santa Lucía Chico river (Uruguay), a mixed lotic and lentic river system. The challenge of this study is represented by the high percentage of missing data (between 50% and 70%) and the high temporal and spatial variability that characterizes the water-quality variables. The competing algorithms implemented belonged to both univariate and multivariate imputation methods (inverse distance weighting (IDW), Random Forest Regressor (RFR), Ridge (R), Bayesian Ridge (BR), AdaBoost (AB), Hubber Regressor (HR), Support Vector Regressor (SVR), and K-nearest neighbors Regressor (KNNR)). According to the results, more than 76% of the imputation outcomes are considered satisfactory (NSE > 0.45). The imputation performance shows better results at the monitoring stations located inside the reservoir than the ones positioned along the mainstream. IDW was the most chosen model for data imputation.
Rafael Rodriguez; Marcos Pastorini; Lorena Etcheverry; Christian Chreties; Mónica Fossati; Alberto Castro; Angela Gorgoglione. Water-Quality Data Imputation With High Percentage of Missing Values: A Machine Learning Approach. 2021, 1 .
AMA StyleRafael Rodriguez, Marcos Pastorini, Lorena Etcheverry, Christian Chreties, Mónica Fossati, Alberto Castro, Angela Gorgoglione. Water-Quality Data Imputation With High Percentage of Missing Values: A Machine Learning Approach. . 2021; ():1.
Chicago/Turabian StyleRafael Rodriguez; Marcos Pastorini; Lorena Etcheverry; Christian Chreties; Mónica Fossati; Alberto Castro; Angela Gorgoglione. 2021. "Water-Quality Data Imputation With High Percentage of Missing Values: A Machine Learning Approach." , no. : 1.
Urban stormwater runoff represents a significant challenge for the practical assessment of diffuse pollution sources on receiving water bodies. Given the high dimensionality of the problem, the main goal of this study was the comparison of linear and non-linear machine learning (ML) methods to characterize urban nutrient runoff from impervious surfaces. In particular, the principal component analysis (PCA) for the linear technique and the self-organizing map (SOM) for the non-linear technique were chosen and compared considering the high number of successful applications in the water quality field. To strengthen this comparison, these techniques were supported by well-known linear and non-linear methods. Those techniques were applied to a complete dataset with precipitation, flow rate, and water quality (sediments and nutrients) records of 577 events gathered for a watershed located in Southern Italy. According to the results, both linear and non-linear techniques can represent build-up and wash-off, the two main processes that characterize urban nutrient runoff. In particular, non-linear methods are able to capture and represent better the rainfall-runoff process and the transport of dissolved nutrients in urban runoff (dilution process). However, their computational time is higher than the linear technique (0.0054 s vs. 15.24 s, for linear and non-linear, respectively, in our study). The outcomes of this study provide significant insights into the application of ML methods for the water quality field.
Angela Gorgoglione; Alberto Castro; Vito Iacobellis; Andrea Gioia. A Comparison of Linear and Non-Linear Machine Learning Techniques (PCA and SOM) for Characterizing Urban Nutrient Runoff. Sustainability 2021, 13, 2054 .
AMA StyleAngela Gorgoglione, Alberto Castro, Vito Iacobellis, Andrea Gioia. A Comparison of Linear and Non-Linear Machine Learning Techniques (PCA and SOM) for Characterizing Urban Nutrient Runoff. Sustainability. 2021; 13 (4):2054.
Chicago/Turabian StyleAngela Gorgoglione; Alberto Castro; Vito Iacobellis; Andrea Gioia. 2021. "A Comparison of Linear and Non-Linear Machine Learning Techniques (PCA and SOM) for Characterizing Urban Nutrient Runoff." Sustainability 13, no. 4: 2054.
The ecological state of inland waters of the Santa Lucía watershed, the primary drinking water source of Uruguay, has raised interest since it presents the seasonal phenomenon of eutrophication. For this reason, an in-depth understanding of the behaviour in time and space of the water-quality variables that characterize this stream is essential. Therefore, this study aims to evaluate the occurrence of spatial and temporal patterns of water-quality variables (Q, turbidity, T, TN, NO3-, NO2-, NH4+, TP, DO, BOD5) in the Santa Lucía Chico watershed with the aid of multivariate statistical tools. The principal component analysis, coupled with k-means cluster analysis, helped to identify a seasonal variation (fall-winter and spring-summer). The hierarchical cluster analysis allowed us to classify the water-quality monitoring stations in three groups in the fall-winter season. The loadings values of the cluster analysis highlighted the most significant pollutants at each monitoring station. The outcomes of this work are expected to contribute valuable knowledge for determining effective management strategies to reduce stream pollution and protect the aquatic ecosystem health of the study area.
A Gorgoglione; J Alonso; C Chreties; M Fossati. Assessing temporal and spatial patterns of surface-water quality with a multivariate approach: a case study in Uruguay. IOP Conference Series: Earth and Environmental Science 2020, 612, 012002 .
AMA StyleA Gorgoglione, J Alonso, C Chreties, M Fossati. Assessing temporal and spatial patterns of surface-water quality with a multivariate approach: a case study in Uruguay. IOP Conference Series: Earth and Environmental Science. 2020; 612 (1):012002.
Chicago/Turabian StyleA Gorgoglione; J Alonso; C Chreties; M Fossati. 2020. "Assessing temporal and spatial patterns of surface-water quality with a multivariate approach: a case study in Uruguay." IOP Conference Series: Earth and Environmental Science 612, no. 1: 012002.
Land-cover mapping is critically needed in land-use planning and policy making. Compared to other techniques, Google Earth Engine (GEE) offers a free cloud of satellite information and high computation capabilities. In this context, this article examines machine learning with GEE for land-cover mapping. For this purpose, a five-phase procedure is applied: (1) imagery selection and pre-processing, (2) selection of the classes and training samples, (3) classification process, (4) post-classification, and (5) validation. The study region is located in the San Salvador basin (Uruguay), which is under agricultural intensification. As a result, the 1990 land-cover map of the San Salvador basin is produced. The new map shows good agreements with past agriculture census and reveals the transformation of grassland to cropland in the period 1990–2018.
Florencia Hastings; Ignacio Fuentes; Mario Perez-Bidegain; Rafael Navas; Angela Gorgoglione. Land-Cover Mapping of Agricultural Areas Using Machine Learning in Google Earth Engine. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 12252, 721 -736.
AMA StyleFlorencia Hastings, Ignacio Fuentes, Mario Perez-Bidegain, Rafael Navas, Angela Gorgoglione. Land-Cover Mapping of Agricultural Areas Using Machine Learning in Google Earth Engine. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; 12252 ():721-736.
Chicago/Turabian StyleFlorencia Hastings; Ignacio Fuentes; Mario Perez-Bidegain; Rafael Navas; Angela Gorgoglione. 2020. "Land-Cover Mapping of Agricultural Areas Using Machine Learning in Google Earth Engine." Transactions on Petri Nets and Other Models of Concurrency XV 12252, no. : 721-736.
Urban stormwater runoff is considered worldwide as one of the most critical diffuse pollutions since it transports contaminants that threaten the quality of receiving water bodies and represent a harm to the aquatic ecosystem. Therefore, a thorough analysis of nutrient build-up and wash-off from impervious surfaces is crucial for effective stormwater-treatment design. In this study, the self-organizing map (SOM) method was used to simplify a complex dataset that contains precipitation, flow rate, and water-quality data, and identify possible patterns among these variables that help to explain the main features that impact the processes of nutrient build-up and wash-off from urban areas. Antecedent dry weather, among the rainfall-related characteristics, and sediment transport resulted in being the most significant factors in nutrient urban runoff simulations. The outcomes of this work will contribute to facilitating informed decision making in the design of management strategies to reduce pollution impacts on receiving waters and, consequently, protect the surrounding ecological environment.
Angela Gorgoglione; Alberto Castro; Andrea Gioia; Vito Iacobellis. Application of the Self-organizing Map (SOM) to Characterize Nutrient Urban Runoff. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 12252, 680 -692.
AMA StyleAngela Gorgoglione, Alberto Castro, Andrea Gioia, Vito Iacobellis. Application of the Self-organizing Map (SOM) to Characterize Nutrient Urban Runoff. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; 12252 ():680-692.
Chicago/Turabian StyleAngela Gorgoglione; Alberto Castro; Andrea Gioia; Vito Iacobellis. 2020. "Application of the Self-organizing Map (SOM) to Characterize Nutrient Urban Runoff." Transactions on Petri Nets and Other Models of Concurrency XV 12252, no. : 680-692.
Land use/land cover is one of the critical factors that affects surface-water quality at catchment scale. Effective mitigation strategies require an in-depth understanding of the leading causes of water pollution to improve community well-being and ecosystem health. The main aim of this study is to assess the relationship between land use/land cover and biophysical and chemical water-quality parameters in the Santa Lucía catchment (Uruguay, South America). The Santa Lucía river is the primary potable source of the country and, in the last few years, has had eutrophication issues. Several multivariate statistical analyses were adopted to accomplish the specific objectives of this study. The principal component analysis (PCA), coupled with k-means cluster analysis (CA), helped to identify a seasonal variation (fall/winter and spring/summer) of the water quality. The hierarchical cluster analysis (HCA) allowed one to classify the water-quality monitoring stations in three groups in the fall/winter season. The factor analysis (FA) with a rotation of the axis (varimax) was adopted to identify the most significant water-quality variables of the system (turbidity and flow). Finally, another PCA was run to link water-quality variables to the dominant land uses of the watershed. Strong correlations between TP and agriculture-land use, TP and livestock farming, NT and urban areas arose. It was found that these multivariate exploratory tools can provide a proper overview of the water-quality behavior in space and time and the correlations between water-quality variables and land use.
Angela Gorgoglione; Javier Gregorio; Agustín Ríos; Jimena Alonso; Christian Chreties; Mónica Fossati. Influence of Land Use/Land Cover on Surface-Water Quality of Santa Lucía River, Uruguay. Sustainability 2020, 12, 4692 .
AMA StyleAngela Gorgoglione, Javier Gregorio, Agustín Ríos, Jimena Alonso, Christian Chreties, Mónica Fossati. Influence of Land Use/Land Cover on Surface-Water Quality of Santa Lucía River, Uruguay. Sustainability. 2020; 12 (11):4692.
Chicago/Turabian StyleAngela Gorgoglione; Javier Gregorio; Agustín Ríos; Jimena Alonso; Christian Chreties; Mónica Fossati. 2020. "Influence of Land Use/Land Cover on Surface-Water Quality of Santa Lucía River, Uruguay." Sustainability 12, no. 11: 4692.
Regionalization techniques have been comprehensively discussed as the solution for runoff predictions in ungauged basins (PUB). Several types of regionalization approach have been proposed during the years. Among these, the physical similarity one was demonstrated to be one of the most robust. However, this method cannot be applied in large regions characterized by highly variable climatic conditions, such as sub-tropical areas. Therefore, this study aims to develop a new regionalization approach based on an enhanced concept of physical similarity to improve the runoff prediction of ungauged basins at country scale, under highly variable-weather conditions. A clustering method assured that watersheds with different hydrologic and physical characteristics were considered. The novelty of the proposed approach is based on the relationships found between rainfall-runoff model parameters and watershed-physiographic factors. These relationships were successively exported and validated at the ungauged basins. From the overall results, it can be concluded that the runoff prediction in the ungauged basins was very satisfactory. Therefore, the proposed approach can be adopted as an alternative method for runoff prediction in ungauged basins characterized by highly variable-climatic conditions.
Santiago Narbondo; Angela Gorgoglione; Magdalena Crisci; Christian Chreties. Enhancing Physical Similarity Approach to Predict Runoff in Ungauged Watersheds in Sub-Tropical Regions. Water 2020, 12, 528 .
AMA StyleSantiago Narbondo, Angela Gorgoglione, Magdalena Crisci, Christian Chreties. Enhancing Physical Similarity Approach to Predict Runoff in Ungauged Watersheds in Sub-Tropical Regions. Water. 2020; 12 (2):528.
Chicago/Turabian StyleSantiago Narbondo; Angela Gorgoglione; Magdalena Crisci; Christian Chreties. 2020. "Enhancing Physical Similarity Approach to Predict Runoff in Ungauged Watersheds in Sub-Tropical Regions." Water 12, no. 2: 528.
The Data Scarcity problem is repeatedly encountered in environmental research. This may induce an inadequate representation of the response’s complexity in any environmental system to any input/change (natural and human-induced). In such a case, before getting engaged with new expensive studies to gather and analyze additional data, it is reasonable first to understand what enhancement in estimates of system performance would result if all the available data could be well exploited. The purpose of this Special Issue, “Overcoming Data Scarcity in Earth Science” in the Data journal, is to draw attention to the body of knowledge that leads at improving the capacity of exploiting the available data to better represent, understand, predict, and manage the behavior of environmental systems at meaningful space-time scales. This Special Issue contains six publications (three research articles, one review, and two data descriptors) covering a wide range of environmental fields: geophysics, meteorology/climatology, ecology, water quality, and hydrology.
Angela Gorgoglione; Alberto Castro; Christian Chreties; Lorena Etcheverry. Overcoming Data Scarcity in Earth Science. Data 2020, 5, 5 .
AMA StyleAngela Gorgoglione, Alberto Castro, Christian Chreties, Lorena Etcheverry. Overcoming Data Scarcity in Earth Science. Data. 2020; 5 (1):5.
Chicago/Turabian StyleAngela Gorgoglione; Alberto Castro; Christian Chreties; Lorena Etcheverry. 2020. "Overcoming Data Scarcity in Earth Science." Data 5, no. 1: 5.
Protection of surface water quality plays a crucial role for sustainable urban watershed management since the wash-off from impervious contaminated surfaces generates transport phenomena from a range of pollutants (like nutrients, such as total nitrogen (Ntot) and total phosphorus (Ptot)). This leads to the consequent reduction of water quality, and to phenomena, such as eutrophication and the presence of algae blooms. For this reason, a comprehensive understanding of nutrient build-up and wash-off is essential for efficient stormwater treatment design. However, data scarcity could represent one of the main limitations in this context. This manuscript presents a methodological framework able to tackle such limitations by an in-depth investigation of the main factors that influence the build-up and wash-off from impervious surfaces, including rainfall, watershed, and drainage-network characteristics. The outcomes highlight the key role played by the antecedent dry period, among the rainfall characteristics, and the width of the overland flow path, among the catchment/drainage characteristics. It is also confirmed as appropriate to use suspended solids as a surrogate for the investigation of the behavior of other pollutant species. Additionally, the capability of this approach in assessing modeling performance was successfully tested. The results of the present study are expected to contribute valuable knowledge for defining effective management strategies to minimize stream pollution and protect the health of aquatic ecosystems in urban watersheds characterized by data scarcity.
Angela Gorgoglione; Andrea Gioia; Vito Iacobellis. A Framework for Assessing Modeling Performance and Effects of Rainfall-Catchment-Drainage Characteristics on Nutrient Urban Runoff in Poorly Gauged Watersheds. Sustainability 2019, 11, 4933 .
AMA StyleAngela Gorgoglione, Andrea Gioia, Vito Iacobellis. A Framework for Assessing Modeling Performance and Effects of Rainfall-Catchment-Drainage Characteristics on Nutrient Urban Runoff in Poorly Gauged Watersheds. Sustainability. 2019; 11 (18):4933.
Chicago/Turabian StyleAngela Gorgoglione; Andrea Gioia; Vito Iacobellis. 2019. "A Framework for Assessing Modeling Performance and Effects of Rainfall-Catchment-Drainage Characteristics on Nutrient Urban Runoff in Poorly Gauged Watersheds." Sustainability 11, no. 18: 4933.
Land use change is an important driver of trends in streamflow. However, the effects are often difficult to disentangle from climate effects. The aim of this paper is to demonstrate that trends in streamflow can be identified by analysing residuals of rainfall-runoff simulations using a Generalized Additive Mixed Model. This assumes that the rainfall-runoff model removes the average climate forcing from streamflow. The case study involves the Santa Lucía river (Uruguay), the GR4J rainfall-runoff model, three nested catchments ranging from 690 to 4900 km 2 and 35 years of observations (1981–2016). Two exogenous variables were considered to influence the streamflow. Using satellite data, growth in forest cover was identified, while the growth in water licenses was obtained from the water authority. Depending on the catchment, effects of land use change differ, with the largest catchment most impacted by afforestation, while the middle size catchment was more influenced by the growth in water licenses.
Rafael Navas; Jimena Alonso; Angela Gorgoglione; R. Willem Vervoort. Identifying Climate and Human Impact Trends in Streamflow: A Case Study in Uruguay. Water 2019, 11, 1433 .
AMA StyleRafael Navas, Jimena Alonso, Angela Gorgoglione, R. Willem Vervoort. Identifying Climate and Human Impact Trends in Streamflow: A Case Study in Uruguay. Water. 2019; 11 (7):1433.
Chicago/Turabian StyleRafael Navas; Jimena Alonso; Angela Gorgoglione; R. Willem Vervoort. 2019. "Identifying Climate and Human Impact Trends in Streamflow: A Case Study in Uruguay." Water 11, no. 7: 1433.
One of the main causes of water conflicts in transboundary watersheds all over the world is represented by the increasing water demand due to urban, industrial, and agricultural development. In this context, water scarcity plays a critical role since, during a drought period, water supply is not sufficient to cover the demand of all water uses. In this work, we have conceptualized and developed a new scenario-based framework able to improve the sustainability and equity of water allocation among two or more riparian countries. The proposed approach is in accordance with the United Nations Watercourses Convention. It considers a hydraulic/hydrologic model, a water-management model, and combines them with multi-criteria decision analysis (MCDA) and what if scenario analysis (WISA). The suggested framework was applied to the transboundary watershed of Cuareim/Quaraí river (Uruguay/Brazil) to tackle a real water-sharing conflict. It resulted in being very flexible in exploring various policy options and test and quantifying them with different scenarios to reach an objective and impartial decision in a water-sharing issue. This framework can effectively be applied to any other transboundary watershed to resolve any possible conflict related to water-allocation/water-management matter.
Angela Gorgoglione; Magdalena Crisci; Rafael H. Kayser; Christian Chreties; Walter Collischonn. A New Scenario-Based Framework for Conflict Resolution in Water Allocation in Transboundary Watersheds. Water 2019, 11, 1174 .
AMA StyleAngela Gorgoglione, Magdalena Crisci, Rafael H. Kayser, Christian Chreties, Walter Collischonn. A New Scenario-Based Framework for Conflict Resolution in Water Allocation in Transboundary Watersheds. Water. 2019; 11 (6):1174.
Chicago/Turabian StyleAngela Gorgoglione; Magdalena Crisci; Rafael H. Kayser; Christian Chreties; Walter Collischonn. 2019. "A New Scenario-Based Framework for Conflict Resolution in Water Allocation in Transboundary Watersheds." Water 11, no. 6: 1174.
Constructed wetlands (CWs) are affordable and reliable green technologies for the treatment of various types of wastewater. Compared to conventional treatment systems, CWs offer an environmental-friendly approach, are low cost, have fewer operational and maintenance requirements, and have a high potential for being applied in developing countries; particularly in small rural communities. However, the sustainable management and successful application of these systems remain a challenge. Therefore, after briefly giving basic information on wetlands and summarizing the classification and use of current CWs, this study aims to provide sustainable solutions for the performance and applications of CWs. To accomplish this objective, design and management parameters of CWs, including macrophyte species, media types, water level, hydraulic retention time (HRT), and hydraulic loading rate (HLR), are discussed. The current study collects and presents results of more than 120 case studies from around the world. This work provides a tool for researchers and decision-makers for using CWs to treat wastewater in a particular area. This study presents an aid for informed analysis, decision-making, and communication.
Angela Gorgoglione; Vincenzo Torretta. Sustainable Management and Successful Application of Constructed Wetlands: A Critical Review. Sustainability 2018, 10, 3910 .
AMA StyleAngela Gorgoglione, Vincenzo Torretta. Sustainable Management and Successful Application of Constructed Wetlands: A Critical Review. Sustainability. 2018; 10 (11):3910.
Chicago/Turabian StyleAngela Gorgoglione; Vincenzo Torretta. 2018. "Sustainable Management and Successful Application of Constructed Wetlands: A Critical Review." Sustainability 10, no. 11: 3910.
Drainage-system management relies on results from urban stormwater models; errors in these models may have serious implications. Inaccurate field data or overly simplified models may cause the complex response of an urban basin to a rainfall event to be inadequately represented. Before undertaking expensive studies to gather and analyze additional data, it is reasonable to understand what enhancement in model performance would result if individual uncertainties could be decreased. This paper uses data collected during field monitoring campaigns to calibrate and validate a hydrologic and sediment-transport model within the Storm Water Management Model (SWMM). Solid accumulation and disappearance rates were identified as factors generating the highest model sensitivity. A generalized evaluation matrix is presented that considers both the uncertainty in input variables and the associated sensitivity in model response to inform model performance expectations and guide investments in model improvement toward actions with maximum benefit.
Angela Gorgoglione; Fabián A. Bombardelli; Bruno J.L. Pitton; Lorence R. Oki; Darren L. Haver; Thomas M. Young. Uncertainty in the parameterization of sediment build-up and wash-off processes in the simulation of sediment transport in urban areas. Environmental Modelling & Software 2018, 111, 170 -181.
AMA StyleAngela Gorgoglione, Fabián A. Bombardelli, Bruno J.L. Pitton, Lorence R. Oki, Darren L. Haver, Thomas M. Young. Uncertainty in the parameterization of sediment build-up and wash-off processes in the simulation of sediment transport in urban areas. Environmental Modelling & Software. 2018; 111 ():170-181.
Chicago/Turabian StyleAngela Gorgoglione; Fabián A. Bombardelli; Bruno J.L. Pitton; Lorence R. Oki; Darren L. Haver; Thomas M. Young. 2018. "Uncertainty in the parameterization of sediment build-up and wash-off processes in the simulation of sediment transport in urban areas." Environmental Modelling & Software 111, no. : 170-181.
Insecticides, such as pyrethroids, have frequently been detected in runoff from urban areas, and their offsite transport can cause aquatic toxicity in urban streams and estuaries. To better understand the wash-off process of pesticide residues in urban runoff, the association of pyrethroids with sediment in runoff from residential surfaces was investigated in two watersheds located in Northern California (Sacramento County). Rainfall, flow rate, and event mean concentrations/loads of sediments and pyrethroids, collected during seasonal monitoring campaigns from 2007 to 2014, were analyzed to identify relationships among stormwater quality and rainfall characteristics, primarily using Principal Component Analysis (PCA). Pyrethroid wash-off was strongly related to sediment wash-off whenever sediment loads exceeded 10 mg; this value was conveniently selected as a threshold between dissolved and particle-bound control of off-site pyrethroid transport. A new mechanistic model for predicting pyrethroid wash-off profiles from residential surfaces at basin-scale was implemented in the Storm Water Management Model (SWMM). The accuracy of the model predictions was estimated by evaluating the root mean square error (RMSE), Nash–Sutcliff efficiency (NSE), and Kling–Gupta efficiency (KGE) for each pyrethroid detected (RMSEtot = 0.13; NSEtot = 0.28; KGEtot = 0.56). The importance of particle-bound transport revealed in this work confirms previous field investigations at a smaller scale, and it should be a key consideration when developing policies to mitigate pesticide runoff from urban areas.
Angela Gorgoglione; Fabián A. Bombardelli; Bruno J. L. Pitton; Lorence R. Oki; Darren L. Haver; Thomas M. Young. Role of Sediments in Insecticide Runoff from Urban Surfaces: Analysis and Modeling. International Journal of Environmental Research and Public Health 2018, 15, 1464 .
AMA StyleAngela Gorgoglione, Fabián A. Bombardelli, Bruno J. L. Pitton, Lorence R. Oki, Darren L. Haver, Thomas M. Young. Role of Sediments in Insecticide Runoff from Urban Surfaces: Analysis and Modeling. International Journal of Environmental Research and Public Health. 2018; 15 (7):1464.
Chicago/Turabian StyleAngela Gorgoglione; Fabián A. Bombardelli; Bruno J. L. Pitton; Lorence R. Oki; Darren L. Haver; Thomas M. Young. 2018. "Role of Sediments in Insecticide Runoff from Urban Surfaces: Analysis and Modeling." International Journal of Environmental Research and Public Health 15, no. 7: 1464.
In the context of the implementation of sustainable water treatment technologies for soil pollution prevention, a methodology that try to overcome the lack of runoff quality data in Puglia (Southern Italy) is firstly tackled in this paper. It provides a tool to obtain total suspended solid (TSS) pollutographs in areas without availability of monitoring campaigns. The proposed procedure is based on the relationship between rainfall characteristics and pollutant wash-off. In particular, starting from the evaluation of the observed regional rainfall patterns by using a rainfall generator model, the storm water management model (SWMM) was applied on five case studies located in different climatic subareas. The quantity SWMM parameters were evaluated starting from the drainage network and catchments characteristics, while the quality parameters were obtained from results of a monitoring campaign conducted for quality model calibration and validation with reference to the pollutograph’s shape and the peak-time. The research yields a procedure useful to evaluate the first flush phenomenon in ungauged sites and, in particular, it provides interesting information for designing efficient and sustainable drainage systems for first flush treatment and diffuse pollution treatment.
Angela Gorgoglione; Andrea Gioia; Vito Iacobellis; Alberto Ferruccio Piccinni; Ezio Ranieri. A Rationale for Pollutograph Evaluation in Ungauged Areas, Using Daily Rainfall Patterns: Case Studies of the Apulian Region in Southern Italy. Applied and Environmental Soil Science 2016, 2016, 1 -16.
AMA StyleAngela Gorgoglione, Andrea Gioia, Vito Iacobellis, Alberto Ferruccio Piccinni, Ezio Ranieri. A Rationale for Pollutograph Evaluation in Ungauged Areas, Using Daily Rainfall Patterns: Case Studies of the Apulian Region in Southern Italy. Applied and Environmental Soil Science. 2016; 2016 ():1-16.
Chicago/Turabian StyleAngela Gorgoglione; Andrea Gioia; Vito Iacobellis; Alberto Ferruccio Piccinni; Ezio Ranieri. 2016. "A Rationale for Pollutograph Evaluation in Ungauged Areas, Using Daily Rainfall Patterns: Case Studies of the Apulian Region in Southern Italy." Applied and Environmental Soil Science 2016, no. : 1-16.
The characterization of stormwater runoff on urbanized surfaces by means of comparison between experimental data and simulations is a strict requirement for a sustainable management of urban sewer systems. A monitoring campaign was carried out within a residential area in Puglia (Southern Italy) in order to collect and evaluate quantity and quality data. A strong correlation was observed between COD (Chemical Oxygen Demand) and TSS (Total Suspended Solid) concentrations, whose values exceed water quality standards. TSS was used for calibration of Storm Water Management Model (SWMM) which was then validated with reference to the pollutograph’s shape and the peak-time. The first flush phenomenon occurrence was also investigated by looking at the distribution of pollutant mass vs. volume in stormwater discharges, using the so-called “M(V) curves”. Results show that on average the first 30% of that washed off carries 60% of TSS and provides important information for the design of efficient systems for first flush treatment.
Maria Di Modugno; Andrea Gioia; Angela Gorgoglione; Vito Iacobellis; Giovanni La Forgia; Alberto F. Piccinni; Ezio Ranieri. Build-Up/Wash-Off Monitoring and Assessment for Sustainable Management of First Flush in an Urban Area. Sustainability 2015, 7, 5050 -5070.
AMA StyleMaria Di Modugno, Andrea Gioia, Angela Gorgoglione, Vito Iacobellis, Giovanni La Forgia, Alberto F. Piccinni, Ezio Ranieri. Build-Up/Wash-Off Monitoring and Assessment for Sustainable Management of First Flush in an Urban Area. Sustainability. 2015; 7 (5):5050-5070.
Chicago/Turabian StyleMaria Di Modugno; Andrea Gioia; Angela Gorgoglione; Vito Iacobellis; Giovanni La Forgia; Alberto F. Piccinni; Ezio Ranieri. 2015. "Build-Up/Wash-Off Monitoring and Assessment for Sustainable Management of First Flush in an Urban Area." Sustainability 7, no. 5: 5050-5070.
A comparison between model and experimental pilot-scale horizontal subsurface flow constructed wetland (HSFCW) located in Lecce (Apulia, South Italy) has been reported in the paper. The experiments were carried out in three constructed wetlands each with a planted area equal to 15 m2 and with water depth of 0.6 m. Tracer tests were conducted by single-shot injection of a dissolution of KBr into the inlet tubes of the beds. The objective of the study was to compare hydraulic performances in a pilot experiences and to evaluate the suitability of two-dimensional method for describing the hydraulic behaviour of the HSFCW. At the beginning of the experience and after 24 months the results show the variation of the hydraulic conductivity and a good correlation between model and physical data by modifying input parameters as a consequence of the clogging.
Ezio Ranieri; Angela Gorgoglione; Alessandro Solimeno. A comparison between model and experimental hydraulic performances in a pilot-scale horizontal subsurface flow constructed wetland. Ecological Engineering 2013, 60, 45 -49.
AMA StyleEzio Ranieri, Angela Gorgoglione, Alessandro Solimeno. A comparison between model and experimental hydraulic performances in a pilot-scale horizontal subsurface flow constructed wetland. Ecological Engineering. 2013; 60 ():45-49.
Chicago/Turabian StyleEzio Ranieri; Angela Gorgoglione; Alessandro Solimeno. 2013. "A comparison between model and experimental hydraulic performances in a pilot-scale horizontal subsurface flow constructed wetland." Ecological Engineering 60, no. : 45-49.
Ezio Ranieri; Angela Gorgoglione; Comasia Montanaro; Antonella Iacovelli; Petros Gikas. Removal capacity of BTEX and metals of constructed wetlands under the influence of hydraulic conductivity. Desalination and Water Treatment 2012, 56, 1256 -1263.
AMA StyleEzio Ranieri, Angela Gorgoglione, Comasia Montanaro, Antonella Iacovelli, Petros Gikas. Removal capacity of BTEX and metals of constructed wetlands under the influence of hydraulic conductivity. Desalination and Water Treatment. 2012; 56 (5):1256-1263.
Chicago/Turabian StyleEzio Ranieri; Angela Gorgoglione; Comasia Montanaro; Antonella Iacovelli; Petros Gikas. 2012. "Removal capacity of BTEX and metals of constructed wetlands under the influence of hydraulic conductivity." Desalination and Water Treatment 56, no. 5: 1256-1263.