A kinetic modeling study of phosphate adsorption onto Phoenix dactylifera L. date palm fibers in batch mode

AbstractThe removal of phosphates from aqueous solutions by adsorption onto date palm fibers (DPF) has been studied in batch mode. The aim of this study was to understand the mechanisms that govern phosphate sorption and find an appropriate model for the kinetics of removal. In order to investigate the mechanism of sorption and potential rate controlling steps, pseudo first-order, pseudo second-order, intra-particle diffusion and the Elovich equations have been used to test experimental data. Kinetic analysis of the four models has been carried out for initial phosphate concentration in the range of 30–110mg/L. The rate constants for the four models have been determined and the correlation coefficients have been calculated in order to assess which model provides the best fit predicted data with experimental results. Seven statistical functions were used to estimate the error deviations between experimental and theoretically predicted kinetic adsorption values, including the average relative error deviation (ARED), Marquardt’s percent standard error deviation (MPSED), the hybrid fractional error function (HYBRID), the sum of the squares of the errors (SSE) and three alternative statistical functions, including the Chi-square test, the F-test and Student’s T-test. The results showed that, both Elovich equation and pseudo second-order equation provide the best fit to experimental data for different initial phosphate concentrations

COMPARISON BETWEEN MULTITEMPORAL GRAPH BASED CLASSICAL LEARNING AND LSTM MODEL CLASSIFICATIONS FOR SITS ANALYSIS

International audienceVery High Resolution (VHR) multispectral Satellite Image Time Series (SITS) enables the production of temporal land cover maps, thanks to high spatial, temporal and spectral resolution of modern earth observation programs. Besides, statistical learning methods applied to SITS monitoring and analysis have created relatively efficient semi-automatic classification techniques. It would therefore be natural to think that the use of deep learning methods on SITS would lead to advances comparable to those known in the field of computer vision. However, when applied to concrete cases, the results are not as convincing. This paper proposes a comparison between a SOTAG (Spatial-Object Temporal Adjacency Graphs) SVM based spatio-temporal classification approach and the Recurrent Neuronal Network (RNN), LSTM (Long Short-Term Memory) model which is trained by historical SITS. The trained LSTM networks are then used to predict new time series data. Both methods perform a spatio-temporal map indicating the temporal profiles of cartographic regions. The proposed approaches will be applied on real and simulated SITS data. We will demonstrate that both results are comparable despite computational times and algorithms complexity

Mapping and monitoring of Large-Sfax wetlands (center-east of Tunisia) using radiometric indexes and GIS tools

Wetlands are characterized by temporary alterations in their structure and composition, and by multifunctionality. Therefore, identifying the boundaries of these zones is essential for appropriate characterization. In this context, this applied research work focuses on the wetlands of Large Sfax in the eastern center of Tunisia. The adopted methodology is based on a combined approach based on multivariate analysis and multi-dates analysis for the identification and the spatial delimitation of wetlands in the study area. The radiometric indexes of humidity NDWI, vegetation NDVI and brightness IB were calculated for the years 2003 and 2015 by using satellite imagery coming from Landsat ETM+7 and Landsat OLI 8. The classification maps of the calculated indexes enabled the identification and spectral delimitation of the wetlands of the study area. The multi-dates analysis was based on the visual interpretation of the panchromatic aerial photographs and the Google Earth snippets for the update of the results. This allowed the spatial delineation and the monitoring of marine, inland, and artificial wetlands in the study area. The importance of using the combined approach is that it allows a better characterization of wetlands. &nbsp

Mapping and monitoring of Large-Sfax wetlands (center-east of Tunisia) using radiometric indexes and GIS tools

Wetlands are characterized by temporary alterations in their structure and composition, and by multifunctionality. Therefore, identifying the boundaries of these zones is essential for appropriate characterization. In this context, this applied research work focuses on the wetlands of Large Sfax in the eastern center of Tunisia. The adopted methodology is based on a combined approach based on multivariate analysis and multi-dates analysis for the identification and the spatial delimitation of wetlands in the study area. The radiometric indexes of humidity NDWI, vegetation NDVI and brightness IB were calculated for the years 2003 and 2015 by using satellite imagery coming from Landsat ETM+7 and Landsat OLI 8. The classification maps of the calculated indexes enabled the identification and spectral delimitation of the wetlands of the study area. The multi-dates analysis was based on the visual interpretation of the panchromatic aerial photographs and the Google Earth snippets for the update of the results. This allowed the spatial delineation and the monitoring of marine, inland, and artificial wetlands in the study area. The importance of using the combined approach is that it allows a better characterization of wetlands

Assessment of Citizen's Measurements Using Test Strips for Water Quality in Medjerda Watershed (Northern Tunisia)

Water resources in Africa are subjected to many pressures related to urban growth and agricultural expansions which will be exarcebated by climate change. These pressures jeopardise achieving the UN-Sustainable Development Goal 6 (SDG6). Water resources in Africa are subjected to many pressures related to urban growth, agricultural expansion, and climate change (Bahri et al., 2016). These pressures jeopardise reaching the UN-Sustainable Development Goal 6 (SDG6). Efficient monitoring of water systems is pivotal for designing efficient water management strategies that alleviates aforementioned pressures (Mutambara et al., 2016). Yet, the water monitoring capacity in Africa is often very poor, in particular for Water Quality Monitoring (WQM). Citizen Science (CS) based WQM is nowadays proposed as an innovative approach to strengthen the WQM capacity (Fehri et al., 2020; Njue et al., 2019; Jollymore et al., 2017). The concept of CS is based on the potential social benefits of engaging, collaborating and actively involving citizens in data collection and knowledge generation. Yet, the quality of CS-based WQM is different as compared to reference WQM. CS-based WQM programmes need therefore to be thoroughly validated. The main objective of this study is to assess the quality of a CSbased WQM program for the Medjerda river in Tunisia

Assessing the Performance of a Citizen Science Based Water Quality Monitoring Program for Nitrates Using Test Strips Implemented in the Medjerda Hydrosystem in Northern Tunisia

Recent technological progress in water management of hydrosystems has been made to deploy efficient and effective water quality monitoring systems (WQMS). Among these, a citizen science (CS)-based water quality monitoring (WQM) program using test strips is considered as a smart tool that may aid in the production of reliable, continuous, and comprehensive data on the water quality resources of hydrosystems over a broad range of spatial and temporal scales. In this case study, the objective is to evaluate the performance of a CS-based WQM for nitrates assessment using test water quality strips for the Medjerda watershed in Northern Tunisia. Overall, 137 samples were collected from 24 sampling sites and were analyzed by 33 participants. Citizens involved in the program were regrouped in five citizen types according to their socio-economic characteristics. Statistical tests, analysis of variance (ANOVA) and multiple correspondence analyses (MCA) were achieved to survey the goodness of fit of CS as a contribution to data collection in terms of the socio-economic profile of the participant. The results show that this tool could be reliable for obtaining the levels of nitrate in water samples. Water quality test trips can conveniently be used by citizens for WQM of nitrates when they are rigorously following the manufacturer’s instructions. Additional efforts in communication and training could help to improve the performance of this CS-WQM program for nitrate in the Medjerda watershed

VHR satellite image time series analysis for illegal building monitoring using multi-dimensional histogram earth mover's distance

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Involvement of Citizens in the Measurements of Water Salinity Using Test Kits in the Medjerda Watershed (Northern Tunisia)

Citizen science-based (CS) water quality monitoring (WQM) is considered as an innovative approach to enhance the hydrosystems’ monitoring. The main objective of this study is to assess the salinity monitoring adopting CS-based WQM for Medjerda watershed, the main hydrosystem of Tunisia, using test kits. The study focused on total dissolved solids (TDS) and electrical conductivity (EC) of water. 96 samples were collected to assess water salinity, from 12 sampling sites located in the Medjerda river or its main tributaries. Water salinity monitoring tests, for wet (January–March 2020) and dry (June–July 2020) periods, were performed by test kits. Regression analysis, determination coefficient (R2), F test, and Cronbach’s alpha (αC) test were performed to statistically assess the difference between the citizens’ dataset and the standard values. Results show that TDS and EC-sensitive test kits were reliable for measuring a wide range of concentrations of 207–6073 ppm and 415–9999 µS/cm, respectively. There was also a good agreement between the citizen-based outcomes and the analytical methods. Nevertheless, the reliability depends on the citizen and the parameter to be tested. Finally, the rapid and simple measurements using the test kits appear suitable to be used as CS-WQM for Medjerda hydrosystem if instructions are strictly followed, and test kits are correctly used. With more consistent training, the test kits should allow for reliable, sensitive, and precise monitoring of water quality

VHR satellite image time series analysis for illegal building monitoring using multi-dimensional histogram earth mover's distance

International audienc