| publications-2061 |
Peer reviewed articles |
2021 |
Datry, T., D. Allen, R. Argelich, J. Barquin, N. Bonada, A. Boulton, F. Branger, Y. Cai, M. Cañedo-Argüelles, N. Cid, Z. Csabai, M. Dallimer, J. C. de Araújo, S. Declerck, T. Dekker, P. Döll, A. Encalada, M. Forcellini, A. Foulquier, J. Heino, F. Jabot, P. Keszler, L. Kopperoinen, S. Kralisch, A. Künne, N. Lamouroux, C. Lauvernet, V. Lehtoranta, B. Loskotová, R. Marcé, J. M. Ortega, C. Mata |
Securing biodiversity, functional integrity, and ecosystem services in drying river networks (DRYvER) |
Research Ideas and Outcomes |
10.3897/rio.7.e77750 |
Data Management & Analytics |
River Basins |
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River networks are among Earth’s most threatened hot-spots of biodiversity and provide key ecosystem services (e.g., supply drinking water and food, climate regulation) essential to sustaining human well-being. Climate change and increased human water use are causing more rivers and streams to dry, with devastating impacts on biodiversity and ecosystem services. Currently, more than a half of the global river networks consist of drying channels, and these are expanding dramatically. However, drying river networks (DRNs) have received little attention from scientists and policy makers, and the public is unaware of their importance. Consequently, there is no effective integrated biodiversity conservation or ecosystem management strategy of DRNs. A multidisciplinary team of 25 experts from 11 countries in Europe, South America, China and the USA will build on EU efforts to assess the cascading effects of climate change on biodiversity, ecosystem functions and ecosystem services of DRNs through changes in flow regimes and water use. DRYvER (DRYing riVER networks) will gather and upscale empirical and modelling data from nine focal DRNs (case studies) in Europe (EU) and Community of Latin American and Caribbean States (CELAC) to develop a meta-system framework applicable to Europe and worldwide. It will also generate crucial knowledge-based strategies, tools and guidelines for economically-efficient adaptive management of DRNs. Working closely with stakeholders and end-users, DRYvER will co-develop strategies to mitigate and adapt to climate change impacts in DRNs, integrating hydrological, ecological (including nature-based solutions), socio-economic and policy perspectives. The end results of DRYvER will contribute to reaching the objectives of the Paris Agreement and placing Europe at the forefront of research on climate change. |
869226 |
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| publications-2062 |
Peer reviewed articles |
2021 |
Julie Crabot, Sylvain Dolédec, Maxence Forcellini, Thibault Datry, |
Efficiency of invertebrate-based bioassessment for evaluating the ecological status of streams along a gradient of flow intermittence |
Ecological Indicators |
10.1016/j.ecolind.2021.108440 |
Data Management & Analytics |
River Basins |
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No abstract available |
869226 |
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| publications-2063 |
Peer reviewed articles |
2022 |
B-Béres V, Kókai Z, VárbÃró G, Mustazhapova G, Csabai Z, Pernecker B, Borics G, Bácsi I, Boda P |
Flow Intermittence Drives the Benthic Algal Composition, Biodiversity and Diatom-Based Quality of Small Hilly Streams in the Pannonian Ecoregion, Hungary |
Frontiers in Ecology and Evolution |
10.3389/fevo.2022.834548 |
Data Management & Analytics |
River Basins |
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Climate change is putting increasing pressure on flowing waters. Drastic water level fluctuations in rivers or drying up of small and medium-sized streams all contribute to the biodiversity crisis threatening freshwater ecosystems. Benthic diatoms are important elements of biofilm in small streams. However, knowledge on the relationship between benthic diatoms and flow intermittence is incomplete, especially in regions recently impacted by recurrent drying. Thus, we investigated benthic diatom flora of small intermittent, hilly streams in the warm temperate region of Europe (the Pannonian Ecoregion). Our hypotheses were addressed to compositional changes, biodiversity loss and diatom-based ecological assessment. The results revealed clear flow intermittence-induced differences in taxa and trait composition of diatoms. Altogether six species for the dry phase and three species in the aquatic phase were identified as indicative ones by using indicator value analyses. In contrast to water regime induced changes in assemblages, there was a seasonal overlap in taxa and trait composition. During the study period, the drying up of streams did not result in significant biodiversity loss either at taxa or trait levels. Functional dispersion, however, reduced significantly by summer. Overall, neither the hydrological regime nor seasonal changes had a significant effect on diatom-based quality indices, except for the Rott trophic index (TID index). The TID index values were significantly lower in dry phases than in aquatic ones. These results suggested that the drying up of streams has a very complex influence on benthic diatoms. It seems that taxonomical and functional redundancy can reduce the negative impact of short-time flow intermittence on assemblages. As a practical benefit, the results are the first to support the use of diatom-based quality indices in the assessment of flow intermittence in the temperate region. |
869226 |
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| publications-2064 |
Peer reviewed articles |
2024 |
Jamal Ezzahar, Abdelghani Chehbouni, Nadia Ouaadi, Mohammed Madiafi, Khabba Said, Salah Er-Raki, Ahmed Laamrani, Adnane Chakir, Zohra Lili Chabaane, Mehrez Zribi |
Sentinel-1 Backscatter and Interferometric Coherence for Soil Moisture Retrieval in Winter Wheat Fields Within a Semiarid South-Mediterranean Climate: Machine Learning Versus Semiempirical Models |
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
10.1109/jstars.2023.3339616 |
AI & Machine Learning |
Uncategorized |
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No abstract available |
823965 |
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| publications-2065 |
Peer reviewed articles |
2023 |
Houda Nassah, Fakir Younes, Erraki Salah, Khabba Said, Bernard Mougenot |
Mapping Soil Clay Content and Hydraulic Properties over an Agricultural Semiarid Plain Using Remote Sensing and Interpolation Techniques |
Ecological Engineering & Environmental Technology |
10.12912/27197050/174738 |
AI & Machine Learning |
Uncategorized |
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No abstract available |
823965 |
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| publications-2066 |
Peer reviewed articles |
2024 |
Pierre Laluet, Luis Olivera-Guerra, VÃctor Altés, Vincent Rivalland, Alexis Jeantet, Julien Tournebize, Omar Cenobio-Cruz, Anaïs Barella-Ortiz, Pere Quintana-SeguÃ, Josep Maria Villar, Olivier Merlin |
Drainage assessment of irrigation districts: on the precision and accuracy of four parsimonious models |
Hydrology and Earth System Sciences |
10.5194/hess-28-3695-2024 |
Simulation & Modeling |
Irrigation Systems |
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Abstract. In semi-arid irrigated environments, agricultural drainage is at the heart of three agro-environmental issues: it is an indicator of water productivity, it is the main control to prevent soil salinization and waterlogging problems, and it is related to the health of downstream ecosystems. Crop water balance models combined with subsurface models can estimate drainage quantities and dynamics at various spatial scales. However, such models' precision (capacity of a model to fit the observed drainage using site-specific calibration) and accuracy (capacity of a model to approximate observed drainage using default input parameters) have not yet been assessed in irrigated areas. To fill the gap, this study evaluates four parsimonious drainage models based on the combination of two surface models (RU and SAMIR) and two subsurface models (Reservoir and SIDRA) with varying complexity levels: RU-Reservoir, RU-SIDRA, SAMIR-Reservoir, and SAMIR-SIDRA. All models were applied over two sub-basins of the Algerri–Balaguer irrigation district, northeastern Spain, equipped with surface and subsurface drains driving the drained water to general outlets where the discharge is continuously monitored. Results show that RU-Reservoir is the most precise (average KGE (Q0.5) of 0.87), followed by SAMIR-Reservoir (average KGE (Q0.5) of 0.79). However, SAMIR-Reservoir is the most accurate model for providing rough drainage estimates using the default input parameters provided in the literature. |
823965 |
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| publications-2067 |
Peer reviewed articles |
2023 |
Salah Er-Raki, Abdelghani Chehbouni |
Remote Sensing in Irrigated Crop Water Stress Assessment |
Remote Sensing |
10.3390/rs15040911 |
Data Management & Analytics |
Irrigation Systems |
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Optimizing water management in agriculture is of crucial importance, especially in arid and semi-arid regions where the existing water shortage is exacerbated by human activities and climate change [...] |
823965 |
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| publications-2068 |
Peer reviewed articles |
2024 |
Salah Er-Raki, Elhoussaine Bouras, Julio Cesar Rodriguez, Fidencio CruzBautista, Chriss Watts, Carlos Lizarraga-Celaya, Abdelghani Chehbouni |
Using AquaCrop for Irrigation and water productivity assessment of Table grapes in arid region of Mexico |
E3S Web of Conferences |
10.1051/e3sconf/202448904011 |
Simulation & Modeling |
Irrigation Systems |
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The aim of this work is to use the AquaCrop model for irrigation and water productivity assessment of Table grapes in arid region of Mexico during 2005 and 2006 cropping seasons. The irrigation efficiency was investigated by comparing the irrigation scheduling design used by the farmer to the AquaCrop model recommendations. Data analysis showed that the farmer irrigates almost every day, which results in the water content in the root zone always exceeding the soil moisture at field capacity (FC). This generates substantial losses of water through deep percolation. By using the AquaCrop model, the optimization of irrigation water scheduling in order to avoid both water stress and deep percolation was about 547 mm and 510 mm, which it is about half of what was applied by the farmer (1006 mm and 930 mm) during 2005 and 2006, respectively. This large difference, lost through deep percolation, reduces the water productivity (WP) by about 45%. |
823965 |
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| publications-2069 |
Peer reviewed articles |
2021 |
Ilaria Cesana, Mariano Bresciani, Sergio Cogliati, Claudia Giardino, Remika Gupana, Dario Manca, Stefano Santabarbara, Monica Pinardi, Martina Austoni, Andrea Lami, Roberto Colombo |
Preliminary Investigation on Phytoplankton Dynamics and Primary Production Models in an Oligotrophic Lake from Remote Sensing Measurements |
Sensors |
10.3390/s21155072 |
Data Management & Analytics |
Natural Water Bodies |
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The aim of this study is to test a series of methods relying on hyperspectral measurements to characterize phytoplankton in clear lake waters. The phytoplankton temporal evolutions were analyzed exploiting remote sensed indices and metrics linked to the amount of light reaching the target (EPAR), the chlorophyll-a concentration ([Chl-a]OC4) and the fluorescence emission proxy. The latter one evaluated by an adapted version of the Fluorescence Line Height algorithm (FFLH). A peculiar trend was observed around the solar noon during the clear sky days. It is characterized by a drop of the FFLH metric and the [Chl-a]OC4 index. In addition to remote sensed parameters, water samples were also collected and analyzed to characterize the water body and to evaluate the in-situ fluorescence (FF) and absorbed light (FA). The relations between the remote sensed quantities and the in-situ values were employed to develop and test several phytoplankton primary production (PP) models. Promising results were achieved replacing the FA by the EPAR or FFLH in the equation evaluating a PP proxy (R2 > 0.65). This study represents a preliminary outcome supporting the PP monitoring in inland waters by means of remote sensing-based indices and fluorescence metrics. |
101004186 |
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| publications-2070 |
Peer reviewed articles |
2021 |
Monica Pinardi, Gary Free, Beatrice Lotto, Nicola Ghirardi, Marco Bartoli, Mariano Bresciani |
Exploiting high frequency monitoring and satellite imagery for assessing chlorophyll-a dynamics in a shallow eutrophic lake |
The Journal of Limnology |
10.4081/jlimnol.2021.2033 |
Data Management & Analytics |
Natural Water Bodies |
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Freshwater ecosystems are challenged by cultural eutrophication across the globe, and it is a priority for water managers to implement water quality monitoring at different spatio-temporal scales to control and mitigate the eutrophication process. Phytoplankton abundance is a key indicator of the trophic and water quality status of lakes. Phytoplankton dynamics are characterized by high spatio-temporal variation, driven by physical, chemical and biological factors, that challenge the capacity of routine monitoring with conventional sampling techniques (i.e., boat based sampling) to characterise these complex relationships. In this study, high frequency in situ measurements and multispectral satellite data were used in a synergistic way to explore temporal (diurnal and seasonal) dynamics and spatial distribution of Chlorophyll-a (Chl-a) concentration, a proxy of phytoplankton abundance, together with physico-chemical water parameters in a shallow fluvial-lake system (Mantua Lakes). A good agreement was found between Chl-a retrieved by remote sensing data and Chl-a fluorescence data recorded by multi-parameters probes (R2 = 0.94). The Chl-a maps allowed a seasonal classification of the Mantua Lakes system as eutrophic or hypertrophic. Along the Mantua lakes system an increasing gradient in Chl-a concentration was recorded following the transition from a fluvial to lacustrine system. There was significant seasonal heterogeneity among the sub-basins, probably due to different hydrodynamics, influenced also by macrophyte stands. High-frequency data revealed the importance of rainfall events in the timing and growth dynamics of phytoplankton, particularly for spring and late summer blooms. Combining temporal and spatial data at high resolution improves the understanding of complex fluvial-lake systems. This technique can allow managers to target blooms in near-real time as they move through a system and guide them to localized hot spots enabling timely management action in ecosystems of high conservation and recreational value. |
101004186 |
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