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Laurie Boithias
Geosciences Environnement Toulouse, Université de Toulouse, CNRS, IRD, UPS, 31400 Toulouse, France

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Journal article
Published: 29 July 2021 in Water
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Surface water contamination by pathogen bacteria remains a threat to public health in the rural areas of developing countries. Fecal indicator bacteria (FIB) like Escherichia coli (E. coli) are widely used to assess water contamination, but their behavior in tropical ecosystems is poorly documented. Our study focused on headwater wetlands which are likely to play a key role in stream water purification of fecal pollutants. Our main objectives were to: (i) evaluate decay rates (k) of the total, particle-attached and free-living E. coli; (ii) quantify the relative importance of solar radiation exposition and suspended particles deposition on k; and (iii) investigate E. coli survival in the deposited sediment. We installed and monitored 12 mesocosms, 4500 mL each, across the main headwater wetland of the Houay Pano catchment, northern Lao People’s Democratic Republic (Lao PDR), for 8 days. The four treatments with triplicates were: sediment deposition-light (DL); sediment deposition-dark (DD); sediment resuspension-light (RL); and sediment resuspension-dark (RD). Particle-attached bacteria predominated in all mesocosms (97 ± 6%). Decay rates ranged from 1.43 ± 0.15 to 1.17 ± 0.13 day−1 for DL and DD treatments, and from 0.50 ± 0.15 to −0.14 ± 0.37 day−1 for RL and RD treatments. Deposition processes accounted for an average of 92% of E. coli stock reduction, while solar radiation accounted for around 2% over the experiment duration. The sampling of E. coli by temporary resuspension of the deposited sediment showed k values close to zero, suggesting potential survival or even growth of bacteria in the sediment. The present findings may help parameterizing hydrological and water quality models in a tropical context.

ACS Style

Paty Nakhle; Laurie Boithias; Anne Pando-Bahuon; Chanthamousone Thammahacksa; Nicolas Gallion; Phabvilay Sounyafong; Norbert Silvera; Keooudone Latsachack; Bounsamay Soulileuth; Emma Rochelle-Newall; Yoan Marcangeli; Alain Pierret; Olivier Ribolzi. Decay Rate of Escherichia coli in a Mountainous Tropical Headwater Wetland. Water 2021, 13, 2068 .

AMA Style

Paty Nakhle, Laurie Boithias, Anne Pando-Bahuon, Chanthamousone Thammahacksa, Nicolas Gallion, Phabvilay Sounyafong, Norbert Silvera, Keooudone Latsachack, Bounsamay Soulileuth, Emma Rochelle-Newall, Yoan Marcangeli, Alain Pierret, Olivier Ribolzi. Decay Rate of Escherichia coli in a Mountainous Tropical Headwater Wetland. Water. 2021; 13 (15):2068.

Chicago/Turabian Style

Paty Nakhle; Laurie Boithias; Anne Pando-Bahuon; Chanthamousone Thammahacksa; Nicolas Gallion; Phabvilay Sounyafong; Norbert Silvera; Keooudone Latsachack; Bounsamay Soulileuth; Emma Rochelle-Newall; Yoan Marcangeli; Alain Pierret; Olivier Ribolzi. 2021. "Decay Rate of Escherichia coli in a Mountainous Tropical Headwater Wetland." Water 13, no. 15: 2068.

Preprint content
Published: 17 June 2021
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ACS Style

Ather Abbas; Laurie Boithias; Yakov Pachepsky; Kyunghyun Kim; Jong Ahn Chun; Kyung Hwa Cho. Supplementary material to "AI4Water v1.0: An open source python package for modeling hydrological time series using data-driven methods". 2021, 1 .

AMA Style

Ather Abbas, Laurie Boithias, Yakov Pachepsky, Kyunghyun Kim, Jong Ahn Chun, Kyung Hwa Cho. Supplementary material to "AI4Water v1.0: An open source python package for modeling hydrological time series using data-driven methods". . 2021; ():1.

Chicago/Turabian Style

Ather Abbas; Laurie Boithias; Yakov Pachepsky; Kyunghyun Kim; Jong Ahn Chun; Kyung Hwa Cho. 2021. "Supplementary material to "AI4Water v1.0: An open source python package for modeling hydrological time series using data-driven methods"." , no. : 1.

Preprint content
Published: 17 June 2021
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Machine learning has shown great promise for simulating hydrological phenomena. However, the development of machine learning-based hydrological models requires advanced skills from diverse fields, such as programming and hydrological modeling. Additionally, data pre-processing and post-processing when training and testing machine learning models is a time-intensive process. In this study, we developed a python-based framework that simplifies the process of building and training machine learning-based hydrological models and automates the process of pre-processing of hydrological data and post-processing of model results. Pre-processing utilities assist in incorporating domain knowledge of hydrology in the machine learning model, such as the distribution of weather data into hydrologic response units (HRUs) based on different HRU discretization definitions. The post-processing utilities help in interpreting the model’s results from a hydrological point of view. This framework will help increase the application of machine learning-based modeling approaches in hydrological sciences.

ACS Style

Ather Abbas; Laurie Boithias; Yakov Pachepsky; Kyunghyun Kim; Jong Ahn Chun; Kyung Hwa Cho. AI4Water v1.0: An open source python package for modeling hydrological time series using data-driven methods. 2021, 2021, 1 -29.

AMA Style

Ather Abbas, Laurie Boithias, Yakov Pachepsky, Kyunghyun Kim, Jong Ahn Chun, Kyung Hwa Cho. AI4Water v1.0: An open source python package for modeling hydrological time series using data-driven methods. . 2021; 2021 ():1-29.

Chicago/Turabian Style

Ather Abbas; Laurie Boithias; Yakov Pachepsky; Kyunghyun Kim; Jong Ahn Chun; Kyung Hwa Cho. 2021. "AI4Water v1.0: An open source python package for modeling hydrological time series using data-driven methods." 2021, no. : 1-29.

Overview
Published: 04 May 2021 in WIREs Water
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Intermittent rivers and ephemeral streams (IRES) are now recognized to support specific freshwater biodiversity and ecosystem services and represent approximately half of the global river network, a fraction that is likely to increase in the context of global changes. Despite large research efforts on IRES during the past few decades, there is a need for developing a systemic approach to IRES that considers their hydrological, hydrogeological, hydraulic, ecological, and biogeochemical properties and processes, as well as their interactions with human societies. Thus, we assert that the interdisciplinary approach to ecosystem research promoted by critical zone sciences and socio‐ecology is relevant. These approaches rely on infrastructure—Critical Zone Observatories (CZO) and Long‐Term Socio‐Ecological Research (LTSER) platforms—that are representative of the diversity of IRES (e.g., among climates or types of geology. We illustrate this within the French CZO and LTSER, including their diversity as socio‐ecosystems, and detail human interactions with IRES. These networks are also specialized in the long‐term observations required to detect and measure ecosystem responses of IRES to climate and human forcings despite the delay and buffering effects within ecosystems. The CZO and LTSER platforms also support development of innovative techniques and data analysis methods that can improve characterization of IRES, in particular for monitoring flow regimes, groundwater‐surface water flow, or water biogeochemistry during rewetting. We provide scientific and methodological perspectives for which this interdisciplinary approach and its associated infrastructure would provide relevant and original insights that would help fill knowledge gaps about IRES. This article is categorized under: Water and Life > Conservation, Management, and Awareness

ACS Style

Ophelie Fovet; Axel Belemtougri; Laurie Boithias; Isabelle Braud; Jean‐Baptiste Charlier; Marylise Cottet; Kevin Daudin; Guillaume Dramais; Agnès Ducharne; Nathalie Folton; Manuela Grippa; Basile Hector; Sylvain Kuppel; Jérôme Le Coz; Luc Legal; Philippe Martin; Florentina Moatar; Jérôme Molénat; Anne Probst; Jean Riotte; Jean‐Philippe Vidal; Fabrice Vinatier; Thibault Datry. Intermittent rivers and ephemeral streams: Perspectives for critical zone science and research on socio‐ecosystems. WIREs Water 2021, e1523 .

AMA Style

Ophelie Fovet, Axel Belemtougri, Laurie Boithias, Isabelle Braud, Jean‐Baptiste Charlier, Marylise Cottet, Kevin Daudin, Guillaume Dramais, Agnès Ducharne, Nathalie Folton, Manuela Grippa, Basile Hector, Sylvain Kuppel, Jérôme Le Coz, Luc Legal, Philippe Martin, Florentina Moatar, Jérôme Molénat, Anne Probst, Jean Riotte, Jean‐Philippe Vidal, Fabrice Vinatier, Thibault Datry. Intermittent rivers and ephemeral streams: Perspectives for critical zone science and research on socio‐ecosystems. WIREs Water. 2021; ():e1523.

Chicago/Turabian Style

Ophelie Fovet; Axel Belemtougri; Laurie Boithias; Isabelle Braud; Jean‐Baptiste Charlier; Marylise Cottet; Kevin Daudin; Guillaume Dramais; Agnès Ducharne; Nathalie Folton; Manuela Grippa; Basile Hector; Sylvain Kuppel; Jérôme Le Coz; Luc Legal; Philippe Martin; Florentina Moatar; Jérôme Molénat; Anne Probst; Jean Riotte; Jean‐Philippe Vidal; Fabrice Vinatier; Thibault Datry. 2021. "Intermittent rivers and ephemeral streams: Perspectives for critical zone science and research on socio‐ecosystems." WIREs Water , no. : e1523.

Special issue paper
Published: 02 May 2021 in Hydrological Processes
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Despite the importance of tropical ecosystems for climate regulation, biodiversity, water and nutrient cycles, only a few Critical Zone Observatories (CZOs) are located in the tropics. Among these, most are in humid climates, while very few data exist for semi‐arid and sub‐humid climates, due to the difficulty of estimating hydro‐geochemical balances in catchments with ephemeral streams. We contribute to fill this gap by presenting a meteorological and hydro‐geochemical dataset acquired at the Mule Hole catchment (4.1 km2), a pristine dry deciduous forest located in a biosphere reserve in south India. The dataset consists of time series of variables related to i) meteorology, including rainfall, air temperature, relative humidity, wind speed and direction, and global radiation, ii) hydrology, including water level and discharge at the catchment outlet, iii) hydrogeology, including manual (monthly) and/or automated (from 15 minutes to hourly) groundwater levels in 9 piezometers, and iv) geochemistry, including suspended sediment content in the stream and chemical composition of rainfall (event based), groundwater (monthly sampling) and stream water (storm events, 15 minutes to hourly frequency with an automatic sampler). The time series extend from 2003 to 2019. Measurement errors are minimized by frequent calibration of sensors and quality checks, both in the field and in the laboratory. Despite these precautions, several data gaps exist, due to occasional access restriction to the site and instrument destruction by wildlife. Results show that large seasonal and interannual variations of climatic conditions were reflected in the large variations of stream flow and groundwater recharge, as well as in water chemical composition. Notably, they reveal a long‐term evolution of groundwater storage, suggesting hydrogeological cycles on a decadal scale. This dataset, alone or in combination with other data, has already allowed to better understand water and element cycling in tropical dry forests, and the role of forest diversity on biogeochemical cycles. As tropical ecosystems are underrepresented by Critical Zone Observatories, we expect this data note to be valuable for the global scientific community.

ACS Style

Jean Riotte; Laurent Ruiz; Stéphane Audry; Benjamin Baud; Jean‐Pierre Bedimo Bedimo; Laurie Boithias; Jean‐Jacques Braun; Bernard Dupré; Jean‐Louis Duprey; Mikael Faucheux; Christelle Lagane; Jean‐Christophe Marechal; Hemanth Moger; Mandalagiri Subbarayappa Mohan Kumar; Harshad Parate; Olivier Ribolzi; Emma Rochelle‐Newall; Buvaneshwari Sriramulu; Murari R. R. Varma; Muddu Sekhar. The Multiscale TROPIcal CatchmentS critical zone observatory M‐TROPICS dataset III : Hydro‐geochemical monitoring of the Mule Hole catchment, south India. Hydrological Processes 2021, 35, e14196 .

AMA Style

Jean Riotte, Laurent Ruiz, Stéphane Audry, Benjamin Baud, Jean‐Pierre Bedimo Bedimo, Laurie Boithias, Jean‐Jacques Braun, Bernard Dupré, Jean‐Louis Duprey, Mikael Faucheux, Christelle Lagane, Jean‐Christophe Marechal, Hemanth Moger, Mandalagiri Subbarayappa Mohan Kumar, Harshad Parate, Olivier Ribolzi, Emma Rochelle‐Newall, Buvaneshwari Sriramulu, Murari R. R. Varma, Muddu Sekhar. The Multiscale TROPIcal CatchmentS critical zone observatory M‐TROPICS dataset III : Hydro‐geochemical monitoring of the Mule Hole catchment, south India. Hydrological Processes. 2021; 35 (5):e14196.

Chicago/Turabian Style

Jean Riotte; Laurent Ruiz; Stéphane Audry; Benjamin Baud; Jean‐Pierre Bedimo Bedimo; Laurie Boithias; Jean‐Jacques Braun; Bernard Dupré; Jean‐Louis Duprey; Mikael Faucheux; Christelle Lagane; Jean‐Christophe Marechal; Hemanth Moger; Mandalagiri Subbarayappa Mohan Kumar; Harshad Parate; Olivier Ribolzi; Emma Rochelle‐Newall; Buvaneshwari Sriramulu; Murari R. R. Varma; Muddu Sekhar. 2021. "The Multiscale TROPIcal CatchmentS critical zone observatory M‐TROPICS dataset III : Hydro‐geochemical monitoring of the Mule Hole catchment, south India." Hydrological Processes 35, no. 5: e14196.

Preprint content
Published: 08 April 2021
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ACS Style

Ather Abbas; Sangsoo Baek; Norbert Silvera; Bounsamay Soulileuth; Yakov Pachepsky; Olivier Ribolzi; Laurie Boithias; Kyung Hwa Cho. Supplementary material to "In-stream Escherichia Coli Modeling Using high-temporal-resolution data with deep learning and process-based models". 2021, 1 .

AMA Style

Ather Abbas, Sangsoo Baek, Norbert Silvera, Bounsamay Soulileuth, Yakov Pachepsky, Olivier Ribolzi, Laurie Boithias, Kyung Hwa Cho. Supplementary material to "In-stream Escherichia Coli Modeling Using high-temporal-resolution data with deep learning and process-based models". . 2021; ():1.

Chicago/Turabian Style

Ather Abbas; Sangsoo Baek; Norbert Silvera; Bounsamay Soulileuth; Yakov Pachepsky; Olivier Ribolzi; Laurie Boithias; Kyung Hwa Cho. 2021. "Supplementary material to "In-stream Escherichia Coli Modeling Using high-temporal-resolution data with deep learning and process-based models"." , no. : 1.

Preprint content
Published: 08 April 2021
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Contamination of surface waters through microbiological pollutants is a major concern to public health. Although long-term and high-frequency E. coli monitoring can help prevent diseases from fecal pathogenic microorganisms, this monitoring is time consuming and expensive. Process-driven models are an alternative method for determining fecal pathogenic microorganisms. However, process-based modeling still has limitations in improving the model accuracy because of the complex mechanistic relationships among hydrological and environmental variables. On the other hand, with the rise in data availability and computation power, the use of data-driven models is increasing. Therefore, in this study, we simulated the transport of Escherichia coli (E. coli) in a 0.6 km² tropical headwater catchment located in Lao PDR using a deep learning model and a process-based model. The deep learning model was built using the long short-term memory (LSTM) technique, whereas the process-based model was constructed using the Hydrological Simulation Program–FORTRAN (HSPF). First, we calibrated both models for surface as well as for subsurface flow. Then, we simulated the E. coli transport with 6 min time steps with both the HSPF and LSTM models. The LSTM provided accurate results for surface and subsurface flow, by showing 0.51 and 0.64 of Nash–Sutcliffe Efficiency (NSE), respectively, whereas the NSE values yielded by the HSPF were −0.7 and 0.59 for surface and subsurface flow. The simulated E. coli concentration from LSTM also improved, yielding an NSE of 0.35, whereas the HSPF showed an unacceptable performance, with an NSE value of −3.01. This is because of the limitation of HSPF in capturing the dynamics of E. coli with land-use change. The simulated E. coli concentration showed rise and drop patterns corresponding to annual changes in land use. This study shows the application of deep learning-based models as an efficient alternative to process-based models for E. coil fate and transport simulation at the catchment scale.

ACS Style

Ather Abbas; Sangsoo Baek; Norbert Silvera; Bounsamay Soulileuth; Yakov Pachepsky; Olivier Ribolzi; Laurie Boithias; Kyung Hwa Cho. In-stream Escherichia Coli Modeling Using high-temporal-resolution data with deep learning and process-based models. 2021, 2021, 1 -55.

AMA Style

Ather Abbas, Sangsoo Baek, Norbert Silvera, Bounsamay Soulileuth, Yakov Pachepsky, Olivier Ribolzi, Laurie Boithias, Kyung Hwa Cho. In-stream Escherichia Coli Modeling Using high-temporal-resolution data with deep learning and process-based models. . 2021; 2021 ():1-55.

Chicago/Turabian Style

Ather Abbas; Sangsoo Baek; Norbert Silvera; Bounsamay Soulileuth; Yakov Pachepsky; Olivier Ribolzi; Laurie Boithias; Kyung Hwa Cho. 2021. "In-stream Escherichia Coli Modeling Using high-temporal-resolution data with deep learning and process-based models." 2021, no. : 1-55.

Special issue paper
Published: 26 March 2021 in Hydrological Processes
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Simultaneously acquiring time series of climate, hydrology and hydrochemical data over decades on river systems is pivotal to understand the complex interactions involving rock, soil water, air and biota in the Critical Zone, to build integrated modeling and to propose predictive scenarios. Among the Critical Zone Observatories (CZOs) implemented in the past 25 years, only a few are located in the humid Tropics despite the importance of these regions in terms of population density, fast‐changing land use, biodiversity hotspots, biomass stock on continents, size of river systems, etc. Since 1994, weathering and erosion processes and fluxes have been investigated at both local (experimental watershed) and regional scales in the Nyong River Basin (Cameroon) which belongs to the Critical Zone Observatories network named Multiscale TROPIcal CatchmentS (M‐TROPICS). The data shared by M‐TROPICS in Cameroon are: (1) rainfall; (2) air temperature, air relative humidity, wind speed and direction, and global radiation; (3) stream and river water level; (4) pH, electrical conductivity, water temperature and suspended particulate matter (SPM) concentration; (5) major ion, alkalinity and dissolved organic carbon (DOC) concentrations. The dataset already contributed to describe the water partitioning in these tropical humid watersheds, to better understand the factors controlling chemical weathering and physical erosion in tropical ecosystems, particularly the role of organic matter. The dataset also contributed to calculate elemental weathering fluxes and saprolite production rate and to propose denudation rates on tropical cratonic landscapes. Hydrological modelling allowed quantification of the geographical water sources contributing to streamflow. DOC data were used to determine greenhouse‐gas emissions and carbon budgets from African inland waters. However, long‐term solute concentrations at the outlet of a small tributary of the Nyong River exhibit non‐stationary behavior over the last 26 years. The processes governing those fluctuations are not yet fully understood and might be related to changes in the hydrological regime, land‐cover and land‐use. The latter highlights the need for longer time‐series and continued support for CZOs particularly in the humid tropics.

ACS Style

Stéphane Audry; Henriette Ateba Bessa; Jean‐Pierre Bedimo Bedimo; Jean‐Loup Boeglin; Laurie Boithias; Jean‐Jacques Braun; Bernard Dupré; Mikael Faucheux; Christelle Lagane; Jean‐Christophe Maréchal; Jules Remy Ndam‐Ngoupayou; Bernadette Nka Nnomo; Justin Nlozoa; Jean‐Claude Ntonga; Olivier Ribolzi; Jean Riotte; Emma Rochelle‐Newall; Laurent Ruiz. The Multiscale TROPIcal CatchmentS critical zone observatory M‐TROPICS dataset I: The Nyong River Basin, Cameroon. Hydrological Processes 2021, 35, e14138 .

AMA Style

Stéphane Audry, Henriette Ateba Bessa, Jean‐Pierre Bedimo Bedimo, Jean‐Loup Boeglin, Laurie Boithias, Jean‐Jacques Braun, Bernard Dupré, Mikael Faucheux, Christelle Lagane, Jean‐Christophe Maréchal, Jules Remy Ndam‐Ngoupayou, Bernadette Nka Nnomo, Justin Nlozoa, Jean‐Claude Ntonga, Olivier Ribolzi, Jean Riotte, Emma Rochelle‐Newall, Laurent Ruiz. The Multiscale TROPIcal CatchmentS critical zone observatory M‐TROPICS dataset I: The Nyong River Basin, Cameroon. Hydrological Processes. 2021; 35 (5):e14138.

Chicago/Turabian Style

Stéphane Audry; Henriette Ateba Bessa; Jean‐Pierre Bedimo Bedimo; Jean‐Loup Boeglin; Laurie Boithias; Jean‐Jacques Braun; Bernard Dupré; Mikael Faucheux; Christelle Lagane; Jean‐Christophe Maréchal; Jules Remy Ndam‐Ngoupayou; Bernadette Nka Nnomo; Justin Nlozoa; Jean‐Claude Ntonga; Olivier Ribolzi; Jean Riotte; Emma Rochelle‐Newall; Laurent Ruiz. 2021. "The Multiscale TROPIcal CatchmentS critical zone observatory M‐TROPICS dataset I: The Nyong River Basin, Cameroon." Hydrological Processes 35, no. 5: e14138.

Special issue paper
Published: 15 March 2021 in Hydrological Processes
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Mountain regions of the humid tropics are characterized by steep slopes and heavy rains. These regions are thus prone to both high surface runoff and soil erosion. In Southeast Asia, uplands are also subject to rapid land‐use change, predominantly as a result of increased population pressure and market forces. Since 1998, the Houay Pano site, located in northern Lao PDR (19.85°N 102.17°E) within the Mekong basin, aims at assessing the long‐term impact of the conversion of traditional slash‐and‐burn cultivation systems to commercial perennial monocultures such as teak tree plantations, on the catchment hydrological response and sediment yield. The instrumented site monitors hydro‐meteorological and soil loss parameters at both microplot (1 m2) and small catchment (0.6 km2) scales. The monitored catchment is part of the network of critical zone observatories named Multiscale TROPIcal CatchmentS (M‐TROPICS). The data shared by M‐TROPICS in Houay Pano are (1) rainfall, (2) air temperature, air relative humidity, wind speed, and global radiation, (3) catchment land use, (4) stream water level, suspended particulate matter, bed particulate matter and stones, (5) soil surface features, and (6) soil surface runoff and soil detachment. The dataset has already been used to interpret suspended particulate matter and bed particulate matter sources and dynamics, to assess the impact of land‐use change on catchment hydrology, soil erosion, and sediment yields, to understand bacteria fate and weed seed transport across the catchment, and to build catchment‐scale models focused on hydrology and water quality issues. The dataset may be further used to e.g. assess the role of headwater catchments in large tropical river basin hydrology, support the interpretation of new variables measured in the catchment (e.g. contaminants other than fecal bacteria), and assess the relative impacts of both climate and land‐use change on the catchment.

ACS Style

Laurie Boithias; Yves Auda; Stéphane Audry; Jean‐Pierre Bricquet; Alounsavath Chanhphengxay; Vincent Chaplot; Anneke de Rouw; Thierry Henry Des Tureaux; Sylvain Huon; Jean‐Louis Janeau; Keooudone Latsachack; Yann Le Troquer; Guillaume Lestrelin; Jean‐Luc Maeght; Pierre Marchand; Pierre Moreau; Andrew Noble; Anne Pando‐Bahuon; Kongkeo Phachomphon; Khambai Phanthavong; Alain Pierret; Olivier Ribolzi; Jean Riotte; Henri Robain; Emma Rochelle‐Newall; Saysongkham Sayavong; Oloth Sengtaheuanghoung; Norbert Silvera; Nivong Sipaseuth; Bounsamay Soulileuth; Xaysatith Souliyavongsa; Phapvilay Sounyaphong; Sengkeo Tasaketh; Chanthamousone Thammahacksa; Jean‐Pierre Thiebaux; Christian Valentin; Olga Vigiak; Marion Viguier; Khampaseuth Xayyathip. The Multiscale TROPIcal CatchmentS critical zone observatory M‐TROPICS dataset II : Land use, hydrology and sediment production monitoring in Houay Pano, northern Lao PDR. Hydrological Processes 2021, 35, e14126 .

AMA Style

Laurie Boithias, Yves Auda, Stéphane Audry, Jean‐Pierre Bricquet, Alounsavath Chanhphengxay, Vincent Chaplot, Anneke de Rouw, Thierry Henry Des Tureaux, Sylvain Huon, Jean‐Louis Janeau, Keooudone Latsachack, Yann Le Troquer, Guillaume Lestrelin, Jean‐Luc Maeght, Pierre Marchand, Pierre Moreau, Andrew Noble, Anne Pando‐Bahuon, Kongkeo Phachomphon, Khambai Phanthavong, Alain Pierret, Olivier Ribolzi, Jean Riotte, Henri Robain, Emma Rochelle‐Newall, Saysongkham Sayavong, Oloth Sengtaheuanghoung, Norbert Silvera, Nivong Sipaseuth, Bounsamay Soulileuth, Xaysatith Souliyavongsa, Phapvilay Sounyaphong, Sengkeo Tasaketh, Chanthamousone Thammahacksa, Jean‐Pierre Thiebaux, Christian Valentin, Olga Vigiak, Marion Viguier, Khampaseuth Xayyathip. The Multiscale TROPIcal CatchmentS critical zone observatory M‐TROPICS dataset II : Land use, hydrology and sediment production monitoring in Houay Pano, northern Lao PDR. Hydrological Processes. 2021; 35 (5):e14126.

Chicago/Turabian Style

Laurie Boithias; Yves Auda; Stéphane Audry; Jean‐Pierre Bricquet; Alounsavath Chanhphengxay; Vincent Chaplot; Anneke de Rouw; Thierry Henry Des Tureaux; Sylvain Huon; Jean‐Louis Janeau; Keooudone Latsachack; Yann Le Troquer; Guillaume Lestrelin; Jean‐Luc Maeght; Pierre Marchand; Pierre Moreau; Andrew Noble; Anne Pando‐Bahuon; Kongkeo Phachomphon; Khambai Phanthavong; Alain Pierret; Olivier Ribolzi; Jean Riotte; Henri Robain; Emma Rochelle‐Newall; Saysongkham Sayavong; Oloth Sengtaheuanghoung; Norbert Silvera; Nivong Sipaseuth; Bounsamay Soulileuth; Xaysatith Souliyavongsa; Phapvilay Sounyaphong; Sengkeo Tasaketh; Chanthamousone Thammahacksa; Jean‐Pierre Thiebaux; Christian Valentin; Olga Vigiak; Marion Viguier; Khampaseuth Xayyathip. 2021. "The Multiscale TROPIcal CatchmentS critical zone observatory M‐TROPICS dataset II : Land use, hydrology and sediment production monitoring in Houay Pano, northern Lao PDR." Hydrological Processes 35, no. 5: e14126.

Journal article
Published: 10 February 2021 in Scientific Reports
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In the basin of Mekong, over 70 million people rely on unimproved surface water for their domestic requirements. Surface water is often contaminated with fecal matter and yet little information exists on the underlying mechanisms of fecal contamination in tropical conditions at large watershed scales. Our objectives were to (1) investigate the seasonality of fecal contamination using Escherichia coli as fecal indicator bacteria (FIB), and (2) establish links between the fecal contamination in stream water and its controlling factors (hydrology and land use). We present the results of (1) a sampling campaign at the outlet of 19 catchments across Lao PDR, in both the dry and the rainy seasons of 2016, and (2) a 10-day interval monitoring conducted in 2017 and 2018 at three point locations of three rivers (Nam Ou, Nam Suang, and Mekong) in northern Lao PDR. Our results show the presence of fecal contamination at most of the sampled sites, with a seasonality characterized by higher and extreme E. coli concentrations occurring during the rainy season. The highest E. coli concentrations, strongly correlated with total suspended sediment concentrations, were measured in catchments dominated by unstocked forest areas, especially in mountainous northern Lao PDR and in Vientiane province.

ACS Style

Paty Nakhle; Olivier Ribolzi; Laurie Boithias; Sayaphet Rattanavong; Yves Auda; Saysongkham Sayavong; Rosalie Zimmermann; Bounsamay Soulileuth; Anne Pando; Chanthamousone Thammahacksa; Emma J. Rochelle-Newall; William Santini; Jean-Michel Martinez; Nicolas Gratiot; Alain Pierret. Effects of hydrological regime and land use on in-stream Escherichia coli concentration in the Mekong basin, Lao PDR. Scientific Reports 2021, 11, 1 -17.

AMA Style

Paty Nakhle, Olivier Ribolzi, Laurie Boithias, Sayaphet Rattanavong, Yves Auda, Saysongkham Sayavong, Rosalie Zimmermann, Bounsamay Soulileuth, Anne Pando, Chanthamousone Thammahacksa, Emma J. Rochelle-Newall, William Santini, Jean-Michel Martinez, Nicolas Gratiot, Alain Pierret. Effects of hydrological regime and land use on in-stream Escherichia coli concentration in the Mekong basin, Lao PDR. Scientific Reports. 2021; 11 (1):1-17.

Chicago/Turabian Style

Paty Nakhle; Olivier Ribolzi; Laurie Boithias; Sayaphet Rattanavong; Yves Auda; Saysongkham Sayavong; Rosalie Zimmermann; Bounsamay Soulileuth; Anne Pando; Chanthamousone Thammahacksa; Emma J. Rochelle-Newall; William Santini; Jean-Michel Martinez; Nicolas Gratiot; Alain Pierret. 2021. "Effects of hydrological regime and land use on in-stream Escherichia coli concentration in the Mekong basin, Lao PDR." Scientific Reports 11, no. 1: 1-17.

Journal article
Published: 29 December 2020 in Journal of Hydrology
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Bacterial pathogens in surface waters threaten human health. The health risk is especially high in developing countries where sanitation systems are often lacking or deficient. Considering twelve flash-flood events sampled from 2011 to 2015 at the outlet of a 60-ha tropical montane headwater catchment in Northern Lao PDR, and using Escherichia coli as a fecal indicator bacteria, our objective was to quantify the contributions of both surface runoff and sub-surface flow to the in-stream concentration of E. coli during flood events, by (1) investigating E. coli dynamics during flood events and among flood events and (2) designing and comparing simple statistical and mixing models to predict E. coli concentration in stream flow during flood events. We found that in-stream E. coli concentration is high regardless of the contributions of both surface runoff and sub-surface flow to the flood event. However, we measured the highest concentration of E. coli during the flood events that are predominantly driven by surface runoff. This indicates that surface runoff, and causatively soil surface erosion, are the primary drivers of in-stream E. coli contamination. This was further confirmed by the step-wise regression applied to instantaneous E. coli concentration measured in individual water samples collected during the flood events, and by the three models applied to each flood event (linear model, partial least square model, and mixing model). The three models showed that the percentage of surface runoff in stream flow was the best predictor of the flood event mean E. coli concentration. The mixing model yielded a Nash-Sutcliffe efficiency of 0.65 and showed that on average, 89% of the in-stream concentration of E. coli resulted from surface runoff, while the overall contribution of surface runoff to the stream flow was 41%. We also showed that stream flow turbidity and E. coli concentration were positively correlated, but that turbidity was not a strong predictor of E. coli concentration during flood events. These findings will help building adequate catchment-scale models to predict E. coli fate and transport, and mapping the related risk of fecal contamination in a global changing context.

ACS Style

Laurie Boithias; Olivier Ribolzi; Guillaume Lacombe; Chanthamousone Thammahacksa; Norbert Silvera; Keooudone Latsachack; Bounsamay Soulileuth; Marion Viguier; Yves Auda; Elodie Robert; Olivier Evrard; Sylvain Huon; Thomas Pommier; Cyril Zouiten; Oloth Sengtaheuanghoung; Emma Rochelle-Newall. Quantifying the effect of overland flow on Escherichia coli pulses during floods: Use of a tracer-based approach in an erosion-prone tropical catchment. Journal of Hydrology 2020, 594, 125935 .

AMA Style

Laurie Boithias, Olivier Ribolzi, Guillaume Lacombe, Chanthamousone Thammahacksa, Norbert Silvera, Keooudone Latsachack, Bounsamay Soulileuth, Marion Viguier, Yves Auda, Elodie Robert, Olivier Evrard, Sylvain Huon, Thomas Pommier, Cyril Zouiten, Oloth Sengtaheuanghoung, Emma Rochelle-Newall. Quantifying the effect of overland flow on Escherichia coli pulses during floods: Use of a tracer-based approach in an erosion-prone tropical catchment. Journal of Hydrology. 2020; 594 ():125935.

Chicago/Turabian Style

Laurie Boithias; Olivier Ribolzi; Guillaume Lacombe; Chanthamousone Thammahacksa; Norbert Silvera; Keooudone Latsachack; Bounsamay Soulileuth; Marion Viguier; Yves Auda; Elodie Robert; Olivier Evrard; Sylvain Huon; Thomas Pommier; Cyril Zouiten; Oloth Sengtaheuanghoung; Emma Rochelle-Newall. 2020. "Quantifying the effect of overland flow on Escherichia coli pulses during floods: Use of a tracer-based approach in an erosion-prone tropical catchment." Journal of Hydrology 594, no. : 125935.

Journal article
Published: 19 August 2020 in Water
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Many mountainous regions of the humid tropics experience serious soil erosion following rapid changes in land use. In northern Lao People’s Democratic Republic (PDR), the replacement of traditional crops by tree plantations, such as teak trees, has led to a dramatic increase in floods and soil loss and to the degradation of basic soil ecosystem services such as water filtration by soil, fertility maintenance, etc. In this study, we hypothesized that conserving understory under teak trees would protect soil, limit surface runoff, and help reduce soil erosion. Using 1 m2 microplots installed in four teak tree plantations in northern Lao PDR over the rainy season of 2017, this study aimed to: (1) assess the effects on surface runoff and soil loss of four understory management practices, namely teak with no understory (TNU; control treatment), teak with low density of understory (TLU), teak with high density of understory (THU), and teak with broom grass, Thysanolaena latifolia (TBG); (2) suggest soil erosion mitigation management practices; and (3) identify a field visual indicator allowing a rapid appraisal of soil erosion intensity. We monitored surface runoff and soil loss, and measured teak tree and understory characteristics (height and percentage of cover) and soil surface features. We estimated the relationships among these variables through statistics and regression analyses. THU and TBG had the smallest runoff coefficient (23% for both) and soil loss (465 and 381 g·m−2, respectively). The runoff coefficient and soil loss in TLU were 35% and 1115 g·m−2, respectively. TNU had the highest runoff coefficient and soil loss (60%, 5455 g·m−2) associated to the highest crusting rate (82%). Hence, the soil loss in TBG was 14-times less than in TNU and teak tree plantation owners could divide soil loss by 14 by keeping understory, such as broom grass, within teak tree plantations. Indeed, a high runoff coefficient and soil loss in TNU was explained by the kinetic energy of rain drops falling from the broad leaves of the tall teak trees down to bare soil, devoid of plant residues, thus leading to severe soil surface crusting and soil detachment. The areal percentage of pedestal features was a reliable indicator of soil erosion intensity. Overall, promoting understory, such as broom grass, in teak tree plantations would: (1) limit surface runoff and improve soil infiltrability, thus increase soil water stock available for both root absorption and groundwater recharge; and (2) mitigate soil loss while favoring soil fertility conservation.

ACS Style

Layheang Song; Laurie Boithias; Oloth Sengtaheuanghoung; Chantha Oeurng; Christian Valentin; Bounthan Souksavath; Phabvilay Sounyafong; Anneke De Rouw; Bounsamay Soulileuth; Norbert Silvera; Bounchanh Lattanavongkot; Alain Pierret; Olivier Ribolzi. Understory Limits Surface Runoff and Soil Loss in Teak Tree Plantations of Northern Lao PDR. Water 2020, 12, 2327 .

AMA Style

Layheang Song, Laurie Boithias, Oloth Sengtaheuanghoung, Chantha Oeurng, Christian Valentin, Bounthan Souksavath, Phabvilay Sounyafong, Anneke De Rouw, Bounsamay Soulileuth, Norbert Silvera, Bounchanh Lattanavongkot, Alain Pierret, Olivier Ribolzi. Understory Limits Surface Runoff and Soil Loss in Teak Tree Plantations of Northern Lao PDR. Water. 2020; 12 (9):2327.

Chicago/Turabian Style

Layheang Song; Laurie Boithias; Oloth Sengtaheuanghoung; Chantha Oeurng; Christian Valentin; Bounthan Souksavath; Phabvilay Sounyafong; Anneke De Rouw; Bounsamay Soulileuth; Norbert Silvera; Bounchanh Lattanavongkot; Alain Pierret; Olivier Ribolzi. 2020. "Understory Limits Surface Runoff and Soil Loss in Teak Tree Plantations of Northern Lao PDR." Water 12, no. 9: 2327.

Journal article
Published: 02 August 2020 in Journal of Hydrology
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Recent intensification in climate change have resulted in the rise of hydrological extreme events. This demands modeling of hydrological processes at high temporal resolution to better understand flow patterns in catchments. To model surface and sub-surface flows in a catchment we utilized a physically based model called Hydrological Simulated Program-FORTRAN and two deep learning-based models. One deep learning model consisted of only one long short-term memory (simple LSTM), whereas the other model simulated processes in each hydrological response unit (HRU) by defining one separate LSTM for each HRU (HRU-based LSTM). The models use environmental time-series data and two-dimensional spatial data to predict surface and sub-surface flows at 6-minute time step simultaneously. We tested our models in a tropical humid headwater catchment in northern Lao PDR and compared their performances. Our results showed that the simple LSTM model outperformed the other models on surface runoff prediction with the lowest MSE (7.4e−5 m3 s−1), whereas HRU-based LSTM model better predicted patterns and slopes in sub-surface flow in comparison with the other models by having the smallest MSE value (3.2e−4 m3 s−1). This study demonstrated the performance of a deep learning model when simulating hydrological cycle with high temporal resolution.

ACS Style

Ather Abbas; Sangsoo Baek; Minjeong Kim; Mayzonee Ligaray; Olivier Ribolzi; Norbert Silvera; Joong-Hyuk Min; Laurie Boithias; Kyung Hwa Cho. Surface and sub-surface flow estimation at high temporal resolution using deep neural networks. Journal of Hydrology 2020, 590, 125370 .

AMA Style

Ather Abbas, Sangsoo Baek, Minjeong Kim, Mayzonee Ligaray, Olivier Ribolzi, Norbert Silvera, Joong-Hyuk Min, Laurie Boithias, Kyung Hwa Cho. Surface and sub-surface flow estimation at high temporal resolution using deep neural networks. Journal of Hydrology. 2020; 590 ():125370.

Chicago/Turabian Style

Ather Abbas; Sangsoo Baek; Minjeong Kim; Mayzonee Ligaray; Olivier Ribolzi; Norbert Silvera; Joong-Hyuk Min; Laurie Boithias; Kyung Hwa Cho. 2020. "Surface and sub-surface flow estimation at high temporal resolution using deep neural networks." Journal of Hydrology 590, no. : 125370.

Article
Published: 12 July 2020 in Environmental Monitoring and Assessment
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An elevated nitrogen concentration in water is one of the main problems affecting water quality in Mediterranean rivers. The objectives of this study were (1) to evaluate the contribution of the Tafna catchment to the nitrate load entering the Mediterranean Sea, (2) to quantify the impact of agriculture on the nitrate concentration in water bodies, (3) to evaluate nitrate loads entering groundwater, and (4) to quantify the role of reservoirs in nitrate retention. A SWAT model was applied during the period 2003 to 2011. The discharge calibration was based on a previous study by Zettam et al. (2017). NSE efficiencies ranged from 0.421 to 0.75, R2 ranged from 0.25 to 0.84, and PBIAS ranged from 3.68 to 39.42. The simulations of monthly nitrate loads were satisfactory in the upstream sampling stations, with NSE between 0.48 and 0.65 and R2 between 0.63 and 0.68. The PBIAS was satisfactory in all the sampling stations (− 36.30 to 10.42). In the downstream sampling stations, the calibration of the monthly nitrate loads was unsatisfactory (NSE ranged from − 0.26 to 0.21 and R2 ranged from 0.02 to 0.25). Fertilisation was the main N input in the catchment, while the main N output was plant uptake. The Tafna River carried an annual average of 37 to 85.5 t N year−1 into the Mediterranean Sea. The simulation also showed that reservoirs in the Tafna basin contain a large quantity of nitrates, i.e. 62% on average of the total amount of nitrates transported annually by the Tafna River.

ACS Style

Amin Zettam; Amina Taleb; Sabine Sauvage; Laurie Boithias; Nouria Belaidi; José Miguel Sanchez-Perez. Applications of a SWAT model to evaluate the contribution of the Tafna catchment (north-west Africa) to the nitrate load entering the Mediterranean Sea. Environmental Monitoring and Assessment 2020, 192, 1 -17.

AMA Style

Amin Zettam, Amina Taleb, Sabine Sauvage, Laurie Boithias, Nouria Belaidi, José Miguel Sanchez-Perez. Applications of a SWAT model to evaluate the contribution of the Tafna catchment (north-west Africa) to the nitrate load entering the Mediterranean Sea. Environmental Monitoring and Assessment. 2020; 192 (8):1-17.

Chicago/Turabian Style

Amin Zettam; Amina Taleb; Sabine Sauvage; Laurie Boithias; Nouria Belaidi; José Miguel Sanchez-Perez. 2020. "Applications of a SWAT model to evaluate the contribution of the Tafna catchment (north-west Africa) to the nitrate load entering the Mediterranean Sea." Environmental Monitoring and Assessment 192, no. 8: 1-17.

Preprint content
Published: 23 March 2020
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Despite being a basic human right, limited access to clean water is still a major concern in developing countries lacking adequate sanitary infrastructure. A significant proportion of the global population directly depends on surface water resources which are often contaminated with fecal matter. The presence of fecal contamination in waterbodies is often detected using fecal indicator bacteria like Escherichia coli. According to 2016 UNEP report, about one third to one half of Asian rivers are estimated to be severely polluted, with monthly in-stream concentrations of fecal coliform bacteria exceeding 1000 cfu.100 mL-1. Although various studies on small tropical catchments have improved our understanding of E. coli behavior in a tropical context, little information exists on the underlying mechanisms at large watershed scales during dry and wet seasons. Our study focuses on Mekong River and its main tributaries in Laos, an area that has witnessed rapid changes in land use and deterioration of water quality over the last three decades. We aim (1) to examine the seasonality of E. coli concentrations in stream waters, and (2) to identify the main factors controlling E. coli in-stream concentration, such as land use, hydrometeorology, and suspended sediment concentrations, through field monitoring of a range of catchments across Laos. To this end, we used two different sets of field data monitoring at multiple temporal and spatial scales. First, a total of 18 catchment outlets located between 15°N and 20°N, were sampled twice in 2016, during both dry and rainy seasons, covering a broad range of catchment sizes (240 - 25946 km²), as well as geographical and topographical features. Second, three northern rivers, Nam Ou, Nam Suang, and Mekong River, have been sampled every 10 days since July 2017. Our results shed the light on contamination over the year in all three catchments (100-100000 MPN.100 mL-1), with higher E. coli concentrations during the rainy season, associated with higher water levels, and higher concentrations of total suspended sediment (TSS) in streams. Partial Least Square (PLS) regression showed a strong positive correlation between E. coli concentrations and the percentage of unstocked forests area. Unstocked forests are exposed to erosion processes resulting in high concentrations of suspended sediment and particle-attached E. coli in-stream concentrations. In contrast, catchments with larger protected and naturally regenerated forest and grassland areas were associated with lower E. coli and TSS concentrations. These analyses highlight the importance of adequate land management in tropical context to reduce soil loss and water quality degradation. Furthermore, our results reveal the importance of improving our understanding of fate and transport of fecal contamination through field monitoring at various spatial and temporal scales, in order to assess the risk to public health, and the impact on ecosystem services, such as contaminant retention.

ACS Style

Paty Nakhle; Olivier Ribolzi; Laurie Boithias; Sayaphet Rattanavong; Yves Auda; Saysongkham Sayavong; Rosalie Zimmermann; Bounsamay Soulileuth; Anne Pando-Bahuon; Chanthamousone Thammahacksa; Emma J. Rochelle-Newall; William Santini; Jean-Michel Martinez; Nicolas Gratiot; Alain Pierret. Effects of seasonal hydrology and land use on in-stream Escherichia coli concentration in the lower Mekong basin, Laos. 2020, 1 .

AMA Style

Paty Nakhle, Olivier Ribolzi, Laurie Boithias, Sayaphet Rattanavong, Yves Auda, Saysongkham Sayavong, Rosalie Zimmermann, Bounsamay Soulileuth, Anne Pando-Bahuon, Chanthamousone Thammahacksa, Emma J. Rochelle-Newall, William Santini, Jean-Michel Martinez, Nicolas Gratiot, Alain Pierret. Effects of seasonal hydrology and land use on in-stream Escherichia coli concentration in the lower Mekong basin, Laos. . 2020; ():1.

Chicago/Turabian Style

Paty Nakhle; Olivier Ribolzi; Laurie Boithias; Sayaphet Rattanavong; Yves Auda; Saysongkham Sayavong; Rosalie Zimmermann; Bounsamay Soulileuth; Anne Pando-Bahuon; Chanthamousone Thammahacksa; Emma J. Rochelle-Newall; William Santini; Jean-Michel Martinez; Nicolas Gratiot; Alain Pierret. 2020. "Effects of seasonal hydrology and land use on in-stream Escherichia coli concentration in the lower Mekong basin, Laos." , no. : 1.

Preprint content
Published: 23 March 2020
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Recent increase in climate change has resulted in rise of hydrologic extreme events, which demands better understanding of flow patterns in catchment. Modeling surface and sub-surface flow at high temporal resolution helps to understand catchment dynamics. In this study, we simulated surface and sub-surface flow in a Laotian catchment at 6-minute resolution. We used one physically based model called Hydrological Simulated Program-FORTRAN (HSPF) and developed two deep learning-based models. One deep learning model consisted of only one long short-term memory (LSTM), whereas the other model simulated processes in each hydrologic response unit (HRU) by defining one separate LSTM for each HRU. The models consider environmental data as well as changing landuse in catchment and predict surface and sub-surface flows. Our results show that simple LSTM model outperformed other models for surface runoff prediction, whereas the HRU-based LSTM model better predicted patterns and slopes in sub-surface flow in comparison with other models.

ACS Style

Ather Abbas; Sangsoo Baek; Minjeong Kim; Mayzonee Ligaray; Olivier Ribolzi; Norbert Silvera; Joong-Hyuk Min; Laurie Boithias; Kyung Hwa Cho. Application of deep recurrent neural networks for modeling surface and sub-surface flow at high temporal resolution. 2020, 1 .

AMA Style

Ather Abbas, Sangsoo Baek, Minjeong Kim, Mayzonee Ligaray, Olivier Ribolzi, Norbert Silvera, Joong-Hyuk Min, Laurie Boithias, Kyung Hwa Cho. Application of deep recurrent neural networks for modeling surface and sub-surface flow at high temporal resolution. . 2020; ():1.

Chicago/Turabian Style

Ather Abbas; Sangsoo Baek; Minjeong Kim; Mayzonee Ligaray; Olivier Ribolzi; Norbert Silvera; Joong-Hyuk Min; Laurie Boithias; Kyung Hwa Cho. 2020. "Application of deep recurrent neural networks for modeling surface and sub-surface flow at high temporal resolution." , no. : 1.

Journal article
Published: 29 November 2018 in Vadose Zone Journal
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The French critical zone initiative, called OZCAR (Observatoires de la Zone Critique–Application et Recherche or Critical Zone Observatories–Application and Research) is a National Research Infrastructure (RI). OZCAR-RI is a network of instrumented sites, bringing together 21 pre-existing research observatories monitoring different compartments of the zone situated between “the rock and the sky,” the Earth’s skin or critical zone (CZ), over the long term. These observatories are regionally based and have specific initial scientific questions, monitoring strategies, databases, and modeling activities. The diversity of OZCAR-RI observatories and sites is well representative of the heterogeneity of the CZ and of the scientific communities studying it. Despite this diversity, all OZCAR-RI sites share a main overarching mandate, which is to monitor, understand, and predict (“earthcast”) the fluxes of water and matter of the Earth’s near surface and how they will change in response to the “new climatic regime.” The vision for OZCAR strategic development aims at designing an open infrastructure, building a national CZ community able to share a systemic representation of the CZ , and educating a new generation of scientists more apt to tackle the wicked problem of the Anthropocene. OZCAR articulates around: (i) a set of common scientific questions and cross-cutting scientific activities using the wealth of OZCAR-RI observatories, (ii) an ambitious instrumental development program, and (iii) a better interaction between data and models to integrate the different time and spatial scales. Internationally, OZCAR-RI aims at strengthening the CZ community by providing a model of organization for pre-existing observatories and by offering CZ instrumented sites. OZCAR is one of two French mirrors of the European Strategy Forum on Research Infrastructure (eLTER-ESFRI) project. Copyright © 2018. . Copyright © by the Soil Science Society of America, Inc.

ACS Style

J. Gaillardet; I. Braud; F. Hankard; Sandrine Anquetin; O. Bour; N. Dorfliger; J.R. De Dreuzy; Sylvie Galle; C. Galy; Sébastien Gogo; Laurence Gourcy; F. Habets; F. Laggoun; L. Longuevergne; T. Le Borgne; F. Naaim-Bouvet; Guillaume NORD; Vincent Simonneaux; D. Six; T. Tallec; C. Valentin; G. Abril; P. Allemand; A. Arènes; Bruno Arfib; Luc Arnaud; N. Arnaud; P. Arnaud; S. Audry; V. Bailly Comte; C. Batiot; A. Battais; H. Bellot; Eric Bernard; C. Bertrand; Hélène Bessiere; S. Binet; J. Bodin; X. Bodin; Laurie Boithias; J. Bouchez; B. Boudevillain; I. Bouzou Moussa; F. Branger; J. J. Braun; P. Brunet; B. Caceres; D. Calmels; B. Cappelaere; H. Celle-Jeanton; F. Chabaux; Konstantinos Chalikakis; Cédric Champollion; Y. Copard; C. Cotel; P. Davy; P. Deline; G. Delrieu; Jerome Demarty; C. Dessert; M. Dumont; C. Emblanch; J. Ezzahar; M. Estèves; Vincent Favier; M. Faucheux; N. Filizola; P. Flammarion; P. Floury; O. Fovet; Matthieu Fournier; A. J. Francez; L. Gandois; C. Gascuel; E. Gayer; C. Genthon; M. F. Gérard; D. Gilbert; I. Gouttevin; M. Grippa; G. Gruau; A. Jardani; L. Jeanneau; J. L. Join; Hervé Jourde; Fatima Karbou; D. Labat; Y. Lagadeuc; E. Lajeunesse; R. Lastennet; W. Lavado; E. Lawin; T. Lebel; C. Le Bouteiller; C. Legout; Y. Lejeune; E. Le Meur; Nicolas Le Moigne; J. Lions; Antoine Lucas; J. P. Malet; C. Marais-Sicre; J. C. Maréchal; C. Marlin; P. Martin; Jean Martins; Jean-Michel Martinez; N. Massei; A. Mauclerc; Naomi Mazzilli; J. Molénat; P. Moreira-Turcq; E. Mougin; S. Morin; J. Ndam Ngoupayou; G. Panthou; Christophe Peugeot; G. Picard; M. C. Pierret; G. Porel; A. Probst; J. L. Probst; Antoine Rabatel; D. Raclot; L. Ravanel; Fayçal Rejiba; P. René; O. Ribolzi; J. Riotte; Agnès Rivière; Henri Robain; Laurent Ruiz; J. M. Sanchez-Perez; W. Santini; S. Sauvage; P. Schoeneich; J. L. Seidel; M. Sekhar; O. Sengtaheuanghoung; N. Silvera; M. Steinmann; A. Soruco; G. Tallec; Emmanuel Thibert; D. Valdes Lao; C. Vincent; D. Viville; P. Wagnon; R. Zitouna. OZCAR: The French Network of Critical Zone Observatories. Vadose Zone Journal 2018, 17, 180067 .

AMA Style

J. Gaillardet, I. Braud, F. Hankard, Sandrine Anquetin, O. Bour, N. Dorfliger, J.R. De Dreuzy, Sylvie Galle, C. Galy, Sébastien Gogo, Laurence Gourcy, F. Habets, F. Laggoun, L. Longuevergne, T. Le Borgne, F. Naaim-Bouvet, Guillaume NORD, Vincent Simonneaux, D. Six, T. Tallec, C. Valentin, G. Abril, P. Allemand, A. Arènes, Bruno Arfib, Luc Arnaud, N. Arnaud, P. Arnaud, S. Audry, V. Bailly Comte, C. Batiot, A. Battais, H. Bellot, Eric Bernard, C. Bertrand, Hélène Bessiere, S. Binet, J. Bodin, X. Bodin, Laurie Boithias, J. Bouchez, B. Boudevillain, I. Bouzou Moussa, F. Branger, J. J. Braun, P. Brunet, B. Caceres, D. Calmels, B. Cappelaere, H. Celle-Jeanton, F. Chabaux, Konstantinos Chalikakis, Cédric Champollion, Y. Copard, C. Cotel, P. Davy, P. Deline, G. Delrieu, Jerome Demarty, C. Dessert, M. Dumont, C. Emblanch, J. Ezzahar, M. Estèves, Vincent Favier, M. Faucheux, N. Filizola, P. Flammarion, P. Floury, O. Fovet, Matthieu Fournier, A. J. Francez, L. Gandois, C. Gascuel, E. Gayer, C. Genthon, M. F. Gérard, D. Gilbert, I. Gouttevin, M. Grippa, G. Gruau, A. Jardani, L. Jeanneau, J. L. Join, Hervé Jourde, Fatima Karbou, D. Labat, Y. Lagadeuc, E. Lajeunesse, R. Lastennet, W. Lavado, E. Lawin, T. Lebel, C. Le Bouteiller, C. Legout, Y. Lejeune, E. Le Meur, Nicolas Le Moigne, J. Lions, Antoine Lucas, J. P. Malet, C. Marais-Sicre, J. C. Maréchal, C. Marlin, P. Martin, Jean Martins, Jean-Michel Martinez, N. Massei, A. Mauclerc, Naomi Mazzilli, J. Molénat, P. Moreira-Turcq, E. Mougin, S. Morin, J. Ndam Ngoupayou, G. Panthou, Christophe Peugeot, G. Picard, M. C. Pierret, G. Porel, A. Probst, J. L. Probst, Antoine Rabatel, D. Raclot, L. Ravanel, Fayçal Rejiba, P. René, O. Ribolzi, J. Riotte, Agnès Rivière, Henri Robain, Laurent Ruiz, J. M. Sanchez-Perez, W. Santini, S. Sauvage, P. Schoeneich, J. L. Seidel, M. Sekhar, O. Sengtaheuanghoung, N. Silvera, M. Steinmann, A. Soruco, G. Tallec, Emmanuel Thibert, D. Valdes Lao, C. Vincent, D. Viville, P. Wagnon, R. Zitouna. OZCAR: The French Network of Critical Zone Observatories. Vadose Zone Journal. 2018; 17 (1):180067.

Chicago/Turabian Style

J. Gaillardet; I. Braud; F. Hankard; Sandrine Anquetin; O. Bour; N. Dorfliger; J.R. De Dreuzy; Sylvie Galle; C. Galy; Sébastien Gogo; Laurence Gourcy; F. Habets; F. Laggoun; L. Longuevergne; T. Le Borgne; F. Naaim-Bouvet; Guillaume NORD; Vincent Simonneaux; D. Six; T. Tallec; C. Valentin; G. Abril; P. Allemand; A. Arènes; Bruno Arfib; Luc Arnaud; N. Arnaud; P. Arnaud; S. Audry; V. Bailly Comte; C. Batiot; A. Battais; H. Bellot; Eric Bernard; C. Bertrand; Hélène Bessiere; S. Binet; J. Bodin; X. Bodin; Laurie Boithias; J. Bouchez; B. Boudevillain; I. Bouzou Moussa; F. Branger; J. J. Braun; P. Brunet; B. Caceres; D. Calmels; B. Cappelaere; H. Celle-Jeanton; F. Chabaux; Konstantinos Chalikakis; Cédric Champollion; Y. Copard; C. Cotel; P. Davy; P. Deline; G. Delrieu; Jerome Demarty; C. Dessert; M. Dumont; C. Emblanch; J. Ezzahar; M. Estèves; Vincent Favier; M. Faucheux; N. Filizola; P. Flammarion; P. Floury; O. Fovet; Matthieu Fournier; A. J. Francez; L. Gandois; C. Gascuel; E. Gayer; C. Genthon; M. F. Gérard; D. Gilbert; I. Gouttevin; M. Grippa; G. Gruau; A. Jardani; L. Jeanneau; J. L. Join; Hervé Jourde; Fatima Karbou; D. Labat; Y. Lagadeuc; E. Lajeunesse; R. Lastennet; W. Lavado; E. Lawin; T. Lebel; C. Le Bouteiller; C. Legout; Y. Lejeune; E. Le Meur; Nicolas Le Moigne; J. Lions; Antoine Lucas; J. P. Malet; C. Marais-Sicre; J. C. Maréchal; C. Marlin; P. Martin; Jean Martins; Jean-Michel Martinez; N. Massei; A. Mauclerc; Naomi Mazzilli; J. Molénat; P. Moreira-Turcq; E. Mougin; S. Morin; J. Ndam Ngoupayou; G. Panthou; Christophe Peugeot; G. Picard; M. C. Pierret; G. Porel; A. Probst; J. L. Probst; Antoine Rabatel; D. Raclot; L. Ravanel; Fayçal Rejiba; P. René; O. Ribolzi; J. Riotte; Agnès Rivière; Henri Robain; Laurent Ruiz; J. M. Sanchez-Perez; W. Santini; S. Sauvage; P. Schoeneich; J. L. Seidel; M. Sekhar; O. Sengtaheuanghoung; N. Silvera; M. Steinmann; A. Soruco; G. Tallec; Emmanuel Thibert; D. Valdes Lao; C. Vincent; D. Viville; P. Wagnon; R. Zitouna. 2018. "OZCAR: The French Network of Critical Zone Observatories." Vadose Zone Journal 17, no. 1: 180067.

Journal article
Published: 23 November 2018 in Ecological Modelling
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Growth is a fundamental ecological process of stream-dwelling salmonids which is strongly interrelated to critical life history events (emergence, mortality, sexual maturity, smolting, spawning). The ability to accurately model growth becomes critical when making population predictions over large temporal (multi-decadal) and spatial (meso) scales, e.g., investigating the effect of global change. Body length collection by removal sampling is a widely-used practice for monitoring fish populations over such large scales. Such data can be efficiently integrated into a Hierarchical Bayesian Model (HBM) and lead to interesting findings on fish dynamics. We illustrate this approach by presenting an integrated HBM of brown trout (Salmo trutta) growth, population dynamics, and removal sampling data collection processes using large temporal and spatial scales data (20 years; 48 sites placed along a 100 km latitudinal gradient). Growth and population dynamics are modelled by ordinary differential equations with parameters bound together in a hierarchical structure. The observation process is modelled with a combination of a Poisson error, a binomial error, and a mixture of Gaussian distributions. Absolute fit is measured using posterior predictive checks, those results indicate that our model fits the data well. Results indicate that growth rate is positively correlated to catchment area. This result corroborates those of other studies (laboratory, exploratory) that identified factors besides water temperature that are related to daily ration and have a significant effect on stream-dwelling salmonid growth at a large scale. Our study also illustrates the value of integrated HBM and electrofishing removal sampling data to study in situ fish populations over large scales.

ACS Style

Christophe Laplanche; Pedro M. Leunda; Laurie Boithias; José Ardaíz; Francis Juanes. Advantages and insights from a hierarchical Bayesian growth and dynamics model based on salmonid electrofishing removal data. Ecological Modelling 2018, 392, 8 -21.

AMA Style

Christophe Laplanche, Pedro M. Leunda, Laurie Boithias, José Ardaíz, Francis Juanes. Advantages and insights from a hierarchical Bayesian growth and dynamics model based on salmonid electrofishing removal data. Ecological Modelling. 2018; 392 ():8-21.

Chicago/Turabian Style

Christophe Laplanche; Pedro M. Leunda; Laurie Boithias; José Ardaíz; Francis Juanes. 2018. "Advantages and insights from a hierarchical Bayesian growth and dynamics model based on salmonid electrofishing removal data." Ecological Modelling 392, no. : 8-21.

Journal article
Published: 01 September 2018 in Journal of Environmental Quality
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Land use change from annual crops to commercial tree plantations can modify flow and transport processes at the watershed scale, including the fate and transport of fecal indicator bacteria (FIB), such as Escherichia coli. The Soil and Water Assessment Tool (SWAT) is a useful means for integrating watershed characteristics and simulating water and contaminants. The objective of this study was to provide a comprehensive assessment of the impact of land use change on microbial transfer from soils to streams using the SWAT model. This study was conducted for the Houay Pano watershed located in northern Lao People’s Democratic Republic. Under the observed weather conditions, the SWAT model predicted a decrease from 2011 to 2012 and an increase from 2012 to 2013 in surface runoff, suspended solids, and E. coli transferred from the soil surface to streams. The amount of precipitation was important in simulating surface runoff, and it subsequently affected the fate and transport of suspended solids and bacteria. In simulations of identical weather conditions and different land uses, E. coli fate and transport was more sensitive to the initial number of E. coli than to its drivers (i.e., surface runoff and suspended solids), and leaf area index was a significant factor influencing the determination of the initial number of E. coli on the soil surface. On the basis of these findings, this study identifies several limitations of the SWAT fertilizer and bacteria modules and suggests measures to improve our understanding of the impacts of land use change on FIB in tropical watersheds. Copyright © 2018. . Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

ACS Style

Minjeong Kim; Laurie Boithias; Kyung Hwa Cho; Oloth Sengtaheuanghoung; Olivier Ribolzi. Modeling the Impact of Land Use Change on Basin‐scale Transfer of Fecal Indicator Bacteria: SWAT Model Performance. Journal of Environmental Quality 2018, 47, 1115 -1122.

AMA Style

Minjeong Kim, Laurie Boithias, Kyung Hwa Cho, Oloth Sengtaheuanghoung, Olivier Ribolzi. Modeling the Impact of Land Use Change on Basin‐scale Transfer of Fecal Indicator Bacteria: SWAT Model Performance. Journal of Environmental Quality. 2018; 47 (5):1115-1122.

Chicago/Turabian Style

Minjeong Kim; Laurie Boithias; Kyung Hwa Cho; Oloth Sengtaheuanghoung; Olivier Ribolzi. 2018. "Modeling the Impact of Land Use Change on Basin‐scale Transfer of Fecal Indicator Bacteria: SWAT Model Performance." Journal of Environmental Quality 47, no. 5: 1115-1122.

Journal article
Published: 01 September 2018 in Journal of Environmental Quality
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Microbial water quality lies in the nexus of human, animal, and environmental health. Multidisciplinary efforts are under way to understand how microbial water quality can be monitored, predicted, and managed. This special collection of papers in the Journal of Environmental Quality was inspired by the idea of creating a special section containing the panoramic view of advances and challenges in the arena of microbial water quality research. It addresses various facets of health-related microorganism release, transport, and survival in the environment. The papers analyze the spatiotemporal variability of microbial water quality, selection of predictors of the spatiotemporal variations, the role of bottom sediments and biofilms, correlations between concentrations of indicator and pathogenic organisms and the role for risk assessment techniques, use of molecular markers, subsurface microbial transport as related to microbial water quality, antibiotic resistance, real-time monitoring and nowcasting, watershed scale modeling, and monitoring design. Both authors and editors represent international experience in the field. The findings underscore the challenges of observing and understanding microbial water quality; they also suggest promising research directions for improving the knowledge base needed to protect and improve our water sources. Copyright © 2018. . Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

ACS Style

Y. A. Pachepsky; A. Allende; L. Boithias; K. Cho; R. Jamieson; N. Hofstra; M. Molina. Microbial Water Quality: Monitoring and Modeling. Journal of Environmental Quality 2018, 47, 931 -938.

AMA Style

Y. A. Pachepsky, A. Allende, L. Boithias, K. Cho, R. Jamieson, N. Hofstra, M. Molina. Microbial Water Quality: Monitoring and Modeling. Journal of Environmental Quality. 2018; 47 (5):931-938.

Chicago/Turabian Style

Y. A. Pachepsky; A. Allende; L. Boithias; K. Cho; R. Jamieson; N. Hofstra; M. Molina. 2018. "Microbial Water Quality: Monitoring and Modeling." Journal of Environmental Quality 47, no. 5: 931-938.