The long-term performance of Soil Aquifer Treatment (SAT) for effluent reuse

2003 ◽  
Vol 3 (4) ◽  
pp. 239-246 ◽  
Author(s):  
E. Idelovitch ◽  
N. Icekson-Tal ◽  
O. Avraham ◽  
M. Michail
Keyword(s):  
Groundwater Recharge ◽  
Large Scale ◽  
Soil Layer ◽  
Chemical Precipitation ◽  
Quality Data ◽  
Soil Aquifer Treatment ◽  
Ammonia Adsorption ◽  
Water Quality Data ◽  
Aquifer System ◽  
Effluent Reuse

An innovative scheme of groundwater recharge for wastewater effluent reuse has been practiced on a large scale in the Dan Region Project in Israel since 1977. The system, referred to as SAT (for Soil Aquifer Treatment), provides advanced treatment prior to effluent reuse for unrestricted irrigation. A major study recently carried out consisted of a comprehensive analysis of the water quality data available in the recharged effluent (before SAT), as well as in observation wells and recovery wells (after SAT). The results obtained with respect to suspended solids, organics and nutrients (nitrogen compounds and phosphorus) are presented and discussed. The main processes occurring in the soil-aquifer system, which are responsible for the removal of the above contaminants are filtration through the upper soil layer, organic matter biodegradation and adsorption, ammonia adsorption and biological nitirification-denitrification, and chemical precipitation and adsorption of phosphorus. The findings of the study have provided valuable information on the above processes and their interaction, and have demonstrated that the SAT system should be considered an attractive method for effluent reuse in areas where hydrogeological conditions are suitable for groundwater recharge via spreading basins.

Implementation of a large scale water quality data management system

1976 ◽  
Vol 10 (1) ◽  
pp. 31-36 ◽  
Author(s):  
William D. Haseman ◽  
Clyde Holsapple ◽  
Andrew B. Whinston
Keyword(s):  
Water Quality ◽  
Data Management ◽  
Management System ◽  
Large Scale ◽  
Data Management System ◽  
Quality Data ◽  
Water Quality Data

scholarly journals GRQA: Global River Water Quality Archive

2021 ◽  
Vol 13 (12) ◽  
pp. 5483-5507
Author(s):  
Holger Virro ◽  
Giuseppe Amatulli ◽  
Alexander Kmoch ◽  
Longzhu Shen ◽  
Evelyn Uuemaa
Keyword(s):  
Water Quality ◽  
Time Series ◽  
River Water ◽  
Environmental Sustainability ◽  
Large Scale ◽  
Observation Time ◽  
River Water Quality ◽  
Quality Data ◽  
Observation Data ◽  
Water Quality Data

Abstract. Large-scale hydrological studies are often limited by the lack of available observation data with a good spatiotemporal coverage. This has affected the reproducibility of previous studies and the potential improvement of existing hydrological models. In addition to the observation data themselves, insufficient or poor-quality metadata have also discouraged researchers from integrating the already-available datasets. Therefore, improving both the availability and quality of open water quality data would increase the potential to implement predictive modeling on a global scale. The Global River Water Quality Archive (GRQA) aims to contribute to improving water quality data coverage by aggregating and harmonizing five national, continental and global datasets: CESI (Canadian Environmental Sustainability Indicators program), GEMStat (Global Freshwater Quality Database), GLORICH (GLObal RIver CHemistry), Waterbase and WQP (Water Quality Portal). The GRQA compilation involved converting observation data from the five sources into a common format and harmonizing the corresponding metadata, flagging outliers, calculating time series characteristics and detecting duplicate observations from sources with a spatial overlap. The final dataset extends the spatial and temporal coverage of previously available water quality data and contains 42 parameters and over 17 million measurements around the globe covering the 1898–2020 time period. Metadata in the form of statistical tables, maps and figures are provided along with observation time series. The GRQA dataset, supplementary metadata and figures are available for download on the DataCite- and OpenAIRE-enabled Zenodo repository at https://doi.org/10.5281/zenodo.5097436 (Virro et al., 2021).

scholarly journals The Evolution of Pollutant Concentrations in a River Severely Affected by Acid Mine Drainage: Río Tinto (SW Spain)

Minerals ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 598 ◽  
Author(s):  
Manuel Olías ◽  
Carlos R. Cánovas ◽  
Francisco Macías ◽  
María Dolores Basallote ◽  
José Miguel Nieto
Keyword(s):  
Acid Mine Drainage ◽  
Large Scale ◽  
Mine Drainage ◽  
Seasonal Pattern ◽  
Quality Data ◽  
Water Quality Data ◽  
Sw Spain ◽  
Acid Mine ◽  
Rio Tinto ◽  
Río Tinto

The Río Tinto, located in the Iberian Pyrite Belt (SW Spain), constitutes an extreme case of pollution by acid mine drainage. Mining in the area dates back to the Copper Age, although large-scale mining of massive sulfide deposits did not start until the second half of the 19th century. Due to acidic mining discharges, the Río Tinto usually maintains a pH close to 2.5 and high concentrations of pollutants along its course. From a detailed sampling during the hydrological year 2017/18, it was observed that most pollutants followed a similar seasonal pattern, with maximum concentrations during autumn due to the washout of secondary soluble sulfate salts and minimum values during large flood events. Nevertheless, As and Pb showed different behavior, with delayed concentration peaks. The dissolved pollutant load throughout the monitored year reached 5000 tons of Fe, 2600 tons of Al, 680 tons of Zn, and so on. While most elements were transported almost exclusively in the dissolved phase, Fe, Pb, Cr, and, above all, As showed high values associated with particulate matter. River water quality data from 1969 to 2019 showed a sharp worsening in 2000, immediately after the mine closure. From 2001 on, an improvement was observed.

Groundwater recharge with municipal effluent: Dan Region Reclamation Project, Israel

1996 ◽  
Vol 34 (11) ◽  
pp. 227-233 ◽  
Author(s):  
A. Kanarek ◽  
M. Michail
Keyword(s):  
Groundwater Recharge ◽  
Municipal Wastewater ◽  
Reclaimed Water ◽  
Soil Aquifer Treatment ◽  
Biological Degradation ◽  
Municipal Wastewater Treatment ◽  
Water Quality Control ◽  
Wastewater Treatment Process ◽  
Recovery Method ◽  
Aquifer System

The Dan Region Project is the largest water reclamation scheme in Israel which provides for collection, treatment, groundwater recharge and reuse of municipal wastewater from Tel-Aviv metropolitan area and several other neighboring municipalities. The project serves a total population of about 1.3 million with an average municipal wastewater flow of 270,000 cu.m/d. The special recharge-recovery method developed and practiced successfully in the Dan Region Project is rather a soil aquifer treatment (SAT) which should be considered as an integral part of the municipal wastewater treatment process. SAT consists of controlled passage of effluent through the unsaturated zone and the aquifer, mainly for purification purposes, as well as for seasonal and multiannual storage. The recharge operation is carried out by means of spreading basins which are surrounding by adequately spaced recovery wells which permit separating the recharge zone from the rest of the aquifer. The major purification processes occurring in the soil aquifer system are: slow-sand filtration, chemical precipitation, adsorption, ion exchange, biological degradation, nitrification, denitrification and disinfection. Water quality control in the recharge zone is virtually complete and the very high quality of reclaimed water obtained after SAT is suitable for a variety of non potable uses especially for unrestricted agricultural irrigation. During the last five years, about 400 million cu.m of reclaimed water was supplied for unrestricted irrigation to the south of the country.

GRQA: Global River Water Quality Archive

2021 ◽  
Author(s):  
Holger Virro ◽  
Giuseppe Amatulli ◽  
Alexander Kmoch ◽  
Longzhu Shen ◽  
Evelyn Uuemaa
Keyword(s):  
Water Quality ◽  
River Water ◽  
Large Scale ◽  
Hydrological Modeling ◽  
Water Quality Modeling ◽  
River Water Quality ◽  
Quality Data ◽  
Observation Data ◽  
Water Quality Data ◽  
Physically Based

<p>Recent advances in implementing machine learning (ML) methods in hydrology have given rise to a new, data-driven approach to hydrological modeling. Comparison of physically based and ML approaches has shown that ML methods can achieve a similar accuracy to the physically based ones and outperform them when describing nonlinear relationships. Global ML models have been already successfully applied for modeling hydrological phenomena such as discharge.</p><p>However, a major problem related to large-scale  water quality modeling has been the lack of available observation data with a good spatiotemporal coverage. This has affected the reproducibility of previous studies and the potential improvement of existing models. In addition to the observation data itself, insufficient or poor quality metadata has also discouraged researchers to integrate the already available datasets. Therefore, improving both, the availability, and quality of open water quality data would increase the potential to implement predictive modeling on a global scale.</p><p>We aim to address the aforementioned issues by presenting the new Global River Water Quality Archive (GRQA) by integrating data from five existing global and regional sources:</p><ul><li>Canadian Environmental Sustainability Indicators program (CESI)</li> <li>Global Freshwater Quality Database (GEMStat)</li> <li>GLObal RIver Chemistry database (GLORICH)</li> <li>European Environment Agency (Waterbase)</li> <li>USGS Water Quality Portal (WQP)</li> </ul><p>The resulting dataset contains a total of over 14 million observations for 41 different forms of some of the most important water quality parameters, focusing on nutrients, carbon, oxygen and sediments. Supplementary metadata and statistics are provided with the observation time series to improve the usability of the dataset. We report on developing a harmonized schema and reproducible workflow that can be adapted to integrate and harmonize further data sources. We conclude our study with a call for action to extend this dataset and hope that the provided reproducible method of data integration and metadata provenance shall lead as an example.</p>

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