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Along with the development of citizen science, more and more citizen science initiatives on soils are emerging. Soils are key components of ecosystems and from where 95% of our food originates. Because soils integrate multiple impacts of human activities, they are increasingly taken into account in public policies (agroecology, biodiversity, food, climate). This presentation will share the results of an online survey on agricultural soil citizen science across Europe. Most reported citizen science projects were at the national level (56%, n=40), limited in time (64.9%, n=40) because of funding (82.6%, n=23), with a budget less than 50.000 € (41.7%, n=36) and funded by a national research funding agency (47.2%, n=36). Regarding agricultural soil systems, half of citizen science projects studied urban or urban-countering gardening and 39% studied cropping systems, 29% fruit-vegetables and grassland systems, 18% arboriculture and vineyards. Over 57% of the reported projects have generated soil biodiversity data, 46% and 35% vegetation cover and soil organic carbon data, respectively. According to citizen science coordinators (n=33), the benefits for the scientists taking part in citizen science were ranging from publication of research outputs (69.7%) and learning opportunities (63.6%) to the potential to influence policy (45.5%). The reported benefits for the citizen scientists (n=33) ranged from learning opportunities (81.8%) and satisfaction through contributing to scientific evidence (72.7%) to publication of research outputs (24.2%). ‘Project very time consuming’ and ‘funding temporary’ were identified as the main research challenges for citizen science projects (n=31). ‘More staff resources’ was reported as the most important prerequisites for citizen science work followed by ‘more financial resources’ and ‘more recognition from academia for citizen science’ (n=28). This synthesis shows the state of the art in agricultural soil citizen science, but also the main lockers for citizen science development on soils.

The effects of climate change on the quality of freshwaters remains poorly investigated while these effects are likely to be ambiguous. Indeed, such effects are partly direct such as temperature control on reaction rates, and partly indirect such as decrease of dilution processes with drier low flows. How the fate of a given pollutant responds to climate change can differ depending on its sources, reactivity and mobilization processes. Therefore, investigating the hydrochemical response of streams to climate change requires considering several elements that differ in their sources and pathways, and in their sensitivity to local and global forcings.A cross-analysis of hydro-climatic variables and the dynamics of three solutes - carbon (C), nitrogen (N) and phosphorus (P) - was conducted at multiple temporal scales using the long-term data sets from a Critical Zone Observatory in Western France (AgrHyS). We identified trends on climatic variables (air temperature increased, winters became wetter and summers drier) and stream concentrations (NO3 concentrations decreased, DOC concentrations increased). However, no effect of air temperature and radiation was observed on stream-water concentrations for the three solutes and there was no clear response of seasonal water-quality signals to increased contrast among hydrological seasons. Therefore, despite observed inter and intra-annual effects of climate on water quality, long-term changes of stream-water concentrations seemed to be more related to agricultural changes than to climate variations. In such a temperate and humid region, the seasonal amplitude of climatic variables is higher than the magnitude of their long-term changes. In addition, agricultural catchments of Western Europe have received high inputs of nutrients since the 1960s that led to create legacy storages in particular N and P in the soil, the vadose zone and/or the groundwater. The damped response of water quality may then be related to legacy storage, leading to lower sensitivity to climatic than to agricultural drivers. Disentangling the respective effects of climate and human activities on stream water quality is particularly challenging, even more in such contexts dealing with legacy storages. As a perspective, we show how using ratios of elements with contrasted properties or origin can help addressing this challenge.

A profound transformation of agricultural production methods has become unavoidable due to the increase in the world’s population, and environmental and climatic challenges. Agroecology is now recognized as a challenging model for agricultural systems, promoting their diversification and adaptation to environmental and socio-economic contexts, with consequences for the entire agri-food system and the development of rural and urban areas. Through a prospective exercise performed at a large interdisciplinary institute, INRAE, a research agenda for agroecology was built that filled a gap through its ambition and interdisciplinarity. It concerned six topics. For genetics, there is a need to study genetic aspects of complex systems (e.g., mixtures of genotypes) and to develop breeding methods for them. For landscapes, challenges lie in effects of heterogeneity at multiple scales, in multifunctionality and in the design of agroecological landscapes. Agricultural equipment and digital technologies show high potential for monitoring dynamics of agroecosystems. For modeling, challenges include approaches to complexity, consideration of spatial and temporal dimensions and representation of the cascade from cropping practices to ecosystem services. The agroecological transition of farms calls for modeling and observational approaches as well as for creating new design methods. Integration of agroecology into food systems raises the issues of product specificity, consumer behavior and organization of markets, standards and public policies. In addition, transversal priorities were identified: (i) generating sets of biological data, through research and participatory mechanisms, that are appropriate for designing agroecological systems and (ii) collecting and using coherent sets of data to enable assessment of vulnerability, resilience and risk in order to evaluate the performance of agroecological systems and to contribute to scaling up. The main lessons learned from this collective exercise can be useful for the entire scientific community engaged in research into agroecology.

Agriculture disturbs the biogeochemical cycles of major elements, which alters the elemental stoichiometry of surface stream waters, with potential impacts on their ecosystems. However, models of catchment hydrology and water quality remain relatively disconnected, even though the observation that dissolved organic carbon (DOC) and nitrate (NO3−) have opposite spatial and temporal patterns seems relevant for improving our representation of hydrological transport pathways within catchments. We tested the ability of a parsimonious model to simultaneously reproduce intra-annual dynamics of stream flow, DOC and NO3− concentrations using 15 years of daily data from a small headwater agricultural catchment (AgrHyS observatory). The model consists of an unsaturated reservoir, a slow reservoir representing the groundwater and a fast reservoir representing the riparian zone and preferential flow paths. The sources of DOC and NO3− are assumed to behave as infinite pools with a fixed concentration in each reservoir that contributes to the stream. Stream concentrations thus result from simple mixing of slow and fast reservoir contributions. The model simultaneously reproduced annual and storm-event dynamics of discharge, DOC and NO3− concentrations in the stream, with calibration KGE scores of 0.77, 0.64 and 0.58 respectively, and validation KGE scores of 0.72, 0.58 and 0.43 respectively. These results suggest that the dynamics of these concentrations can be explained by hydrological transport processes and thus by temporally variable contributions from slow (NO3− rich and DOC poor) and fast reservoirs (DOC rich and NO3− poor), with a poor representation of the biogeochemical transformations. Unexpectedly, using the concentration time series to calibrate the model increased uncertainty in the parameters that control hydrological fluxes of the model. The legacy storage of NO3− resulting from agricultural history in the studied catchment supports the assumption that the main DOC and NO3− sources behave as infinite pools at the scale of several years. Nevertheless, reproducing the long-term trends in solute concentration would require additional information about DOC and NO3− trends within the reservoirs.

International audience; Agriculture affects the biogeochemical cycles of carbon, nitrogen, and phosphorus, leading to a deterioration of surface water quality. The increasing magnitude of climate change raises questions about potential additional or mitigating effects of climate change on this deterioration. One way to understand these potential effects is to cross-analyze the dynamics of nutrient concentrations and hydroclimatic variables at multiple time scales. Here, we used a 16-year data set, from a 5 km 2 agricultural watershed in France with a temperate oceanic climate, that contains a daily record of nutrient concentrations and hydroclimatic variables from 2002-2017. We calculated Mann-Kendall and Theil-Sen tests, Fourier transforms, and daily hydroclimatic distributions associated with extreme stream concentrations to investigate long-term trends, seasonal dynamics and their interannual variations, and the daily time scale, respectively. Dynamics of dissolved organic carbon (DOC) and nitrate (NO 3) concentrations displayed opposite patterns at the three temporal scales, while soluble reactive phosphorus concentrations showed decoupled dynamics, related more to extreme hydrological events. Climate and past agricultural changes seem to have a synergetic effect that leads to long-term NO 3 decrease and DOC increase. Precipitation and, to a greater extent, watershed wetness controlled seasonal and event-driven dynamics.

As a critical interface in the environment, soils can provide a wide range of ecosystem services (ES). However, while there is growing demand to assess soil ES from agricultural systems, considering them in land management strategies remains a challenge. Indeed, because of the difficulty in relating soil properties to ES, soil ES are still not fully considered in the territorial planning decision process. Through a comprehensive approach based on soil processes, an assessment framework is proposed to make soil ES understandable and usable by actors of territorial planning. This assessment framework is based on a conceptual model that is then developed into an operational framework. The conceptual model, which is supported by a literature review, relates agricultural soil ES to common socio-economic development challenges. The operational framework is based on the development of soil ES modelling and enables comparison of soil management options, which provides information to help choose among planning scenarios. This soil ES assessment framework, relating soil science to territorial governance, should improve integration of soil ES into decision making in a territorial planning context and support sustainable socio-economic development.

Hillslope, groundwater, near- and in-stream interactions are key processes to understand in order to reduce the impact of agriculture on natural ecosystem. Indeed, hydrologic connectivity controls the fate of the nutrients within a catchment. The dynamics of nutrients (Nitrates NO3 and Phosphates PO4) and dissolved organic carbon (DOC) at the outlet are the product of past agricultural practices and local climate conditions. DOC, NO3 and PO4 are usually studied and modelled separately and originate from wetlands, groundwater and surface flows respectively. The simultaneous modelling of these elements is an opportunity to better understand the hydrologic connectivity because of their specific spatial origin, reactivity and mobilization processes. We developed a parsimonious rainfall-runoff model coupled with solutes reactivity and transport module in an agricultural research catchment (Kervidy-Naizin, 5km²). We used a three boxes lumped model (soil, groundwater and wetland) and StorAge-Selection function (SAS-function), agricultural surplus and daily climatic variables (precipitations, temperature, evapotranspiration) in order to simulate the daily discharge and stream concentrations at the outlet. Model tests confirmed that adding constraints such as solutes concentrations to a hydrological model helped to avoid unlikely sets of parameters. Simulations also showed that air temperature and agricultural practices are the major drivers of the supply of elements available within the catchment by controlling their biogeochemical reactivity; and that water table levels and precipitations are the major drivers of the variability of the concentrations in the stream by controlling the hydrological connectivity and the mixing between sources areas.

In the last few decades, the degradation of water quality and resulting regulations, such as the European Water Framework Directive, the United States Clean Water Act, and the New Zealand Resource Management Act 1991 have promoted water quality monitoring in terms of parameter richness, spatial density and high temporal resolution. Long-term catchment observatories have been strengthened to gain insight into hydrological and biogeochemical processes. New technologies have been developed and deployed to collect more in situ water quality data at higher frequencies. Thus, water quality monitoring around the world has produced a large amount of data from research catchments but also from national monitoring networks. Despite these efforts, water quality data are highly heterogeneous in terms of targeted parameters, measurement methods, sampling frequencies. Also, accessibility to water samples differ from each hydrological compartment (stream, groundwater, soil water and precipitation). Among water quality time-series, higher sampling frequencies are available for stream water where monitoring is relatively easy to carry out generating a high amount of data. However, groundwater data are rare since monitoring and access is relatively difficult. Also, the aim of monitoring network evolved with time. In fact, networks are usually established for a specific purpose which is changing with time and the questions the network is trying to answer? This raise the issue of spatial and temporal flexibility- multi purpose network and the use of network to support model development which could be seen as a “theoretical” monitoring network.The objective of this talk is to present a review of methods used for analysing temporal water quality signals and models outputs, based on a panel of examples from few but densely monitored environmental research observatories. Such infrastructures also give an insight into critical zone (CZ) research that help to build a transdisciplinary community to identify the main knowledge gaps in CZ processes and behaviour.

International audience; The AgrHyS is a long-term agro-hydrological observatory dedicated to studying the processes controlling hydro-chemical fluxes in headwater catchments in response to the effects of agricultural. AgrHyS is composed of instrumented catchments located in western France in a temperate oceanic climate that are characterized by shallow groundwater (

Management of agricultural diffuse pollution to water remains a challenge and is influenced by the complex interactions of rainfall-runoff pathways, soil and nutrient management, agricultural landscape heterogeneity and biogeochemical cycling in receiving water bodies. Amplified cycles of weather can also influence nutrient loss to water although they are less considered in policy reviews. Here, we present the development of climate-chemical indicators of diffuse pollution in highly monitored catchments in Western Europe. Specifically, we investigated the influences and relationships between weather processes amplified by the North Atlantic Oscillation during a sharp upward trend (2010–2016) and the patterns of diffuse nitrate and phosphorus pollution in rivers. On an annual scale, we found correlations between local catchment-scale nutrient concentrations in rivers and the influence of larger, oceanic-scale climate patterns defined by the intensity of the North Atlantic Oscillation. These influences were catchment-specific showing positive, negative or no correlation according to a typology. Upward trends in these decadal oscillations may override positive benefits of local management in some years or indicate greater benefits in other years. Developing integrated climate-chemical indicators into catchment monitoring indicators will provide a new and important contribution to water quality management objectives.

We tested an empirical modelling approach using relatively low-cost continuous records of turbidity and discharge as proxies to estimate phosphorus (P) concentrations at a sub-hourly time step for estimating loads. The method takes into account non-linearity and hysteresis effects during storm events, and hydrological conditions variability. High-frequency records of total P and reactive P originating from four contrasting European agricultural catchments in terms of P loads were used to test the method. The models were calibrated on weekly grab sampling data combined with 10 storms surveyed sub-hourly per year (weekly+ survey) and then used to reconstruct P concentrations during all storm events for computing annual loads. For total P, results showed that this modelling approach allowed the estimation of annual loads with limited uncertainties (≈ -10% ± 15%), more reliable than estimations based on simple linear regressions using turbidity, based on interpolated weekly+ data without storm event reconstruction, or on discharge weighted calculations from weekly series or monthly series. For reactive P, load uncertainties based on the non-linear model were similar to uncertainties based on storm event reconstruction using simple linear regression (≈ 20% ± 30%), and remained lower than uncertainties obtained without storm reconstruction on weekly or monthly series, but larger than uncertainties based on interpolated weekly+ data (≈ -15% ± 20%). These empirical models showed we could estimate reliable P exports from non-continuous P time series when using continuous proxies, and this could potentially be very useful for completing time-series datasets in high-frequency surveys, even over extended periods.

Summary High-resolution mapping of soil phosphorus (P) concentration is necessary to identify critical source areas reliably where a large risk of transport coincides with a large potential source of P in agricultural landscapes. However, dense soil P data are not usually available to produce such maps and to obtain them is expensive. In this study, we modelled and mapped soil extractable P (ExtP) and total P (TP) concentrations in an intensively farmed 12-km2 catchment in Brittany (NW France) with two different datasets to test the suitability of readily available regional or national databases for high-resolution mapping. We used a machine learning tool (Cubist) to develop rule-based predictive models from a calibration dataset. Covariates included pedological, geological, agricultural, terrain and geophysical-related attributes obtained specifically in the study area (SURVEY) or derived from readily available regional or national databases (DATABASE). Even though better predictions were obtained with the SURVEY data (RMSE = 0.018 g kg−1 for ExtP and RMSE = 0.219 g kg−1 for TP), the DATABASE data produced acceptable predictions (RMSE = 0.024 g kg−1 for ExtP and RMSE = 0.253 g kg−1 for TP). The machine learning tool helped to identify key covariates that would improve the prediction of soil P when detailed data are not available. Readily available data about crop rotations could increase the accuracy of existing ExtP maps. These maps, combined with additional soil analysis for extractable Al, would improve the mapping of TP and the identification of areas with a large potential source of P. Highlights Modelling and mapping of soil phosphorus with the machine learning algorithm Cubist. Comparison of regional or national databases and detailed survey data for prediction. Models with regional and national data performed well, but some areas with large concentrations of P were not identified. Information about crop rotation and soil extractable Al improved model performance.

ISI Document Delivery No.: GA0JN Times Cited: 0 Cited Reference Count: 45 Gu, S. Gruau, G. Malique, F. Dupas, R. Petitjean, P. Gascuel-Odoux, C. China Scholarship Council; Agence de l'Eau Loire-Bretagne [14038840]; EC2CO INSU-CNRS programme via the Trans-P project [AO2015-882574]; EC2CO INSU-CNRS programme via the PHOSNAP project [AO2015-882574] Sen Gu benefited from a Ph.D. grant from the China Scholarship Council. The study was funded by the Agence de l'Eau Loire-Bretagne (14038840) and the EC2CO INSU-CNRS programme (AO2015-882574) via the Trans-P and PHOSNAP projects. We would like to thank Martine Bouhnik-Le Coz for the ICP-MS analysis. We thank Anne Bergeret for her help in determining soil properties and soil P speciation. We thank Cornelia Rumpel and Alexandra Creme for the Hedley P fractionation analysis. Michelle Corson and Michael Corson post-edited the English style and grammar. Elsevier science bv Amsterdam; International audience; Drying and rewetting (DRW) events in soils cause the release of molybdate-unreactive dissolved phosphorus (MUP) into soil solutions, which has been historically considered biologically-derived phosphorus (P) from microbial cell lysis. This unreactive P, however, could also represent P bound to soil colloids/nanoparticles, whose releases are also known to be physically stimulated during DRW events. To explore this possibility, two riparian wetland soils (A and B) with contrasting soil P speciation were subjected to three successive DRW cycles in soil columns. Leachates were successively filtrated/ultrafiltrated with 0.45 μm, 30 kDa and 5 kDa pore size membranes to separate the different colloidal/nanoparticulate fractions, in which molybdate-reactive P (MRP), total P (TP), MUP (defined as TP minus MRP), Fe, Al and dissolved organic carbon (DOC) concentrations were measured. For both soils, TP concentrations peaked at the beginning of each rewetting event then decreased rapidly upon leaching. MUP concentrations appeared similar variations as TP, but MRP concentrations remained relatively constant during leaching. Soil B showed larger TP release peaks than soil A and contained different P forms (more MUP and MRP, respectively). In both soils, colloidal/nanoparticulate P was an important fraction (up to 70%) of TP (

ISI Document Delivery No.: GE0KF Times Cited: 1 Cited Reference Count: 58 Fovet, O. Humbert, G. Dupas, R. Gascuel-Odoux, C. Gruau, G. Jaffrezic, A. Thelusma, G. Faucheux, M. Gilliet, N. Hamon, Y. Grimaldi, C. Agence Nationale de Ia Recherche via the MOSAIC project; INRA This work was funded by the Agence Nationale de Ia Recherche via the MOSAIC project and by INRA for the monitoring in the Kervidy-Naizin catchment - ERO AgrHyS. Data are available via http://geowww.agrocampus-ouest.fr/portails/?portail = vidae. The authors also thank all those who helped with the lab work: Beatrice Trinkler, Laurence Carteaux, Yannick Fauvel, Patrice Petit jean, and Armelle Racape. Elsevier science bv Amsterdam; International audience; The response of stream chemistry to storm is of major interest for understanding the export of dissolved and particulate species from catchments. The related challenge is the identification of active hydrological flow paths during these events and of the sources of chemical elements for which these events are hot moments of exports. An original four-year data set that combines high frequency records of stream flow, turbidity, nitrate and dissolved organic carbon concentrations, and piezometric levels was used to characterize storm responses in a headwater agricultural catchment. The data set was used to test to which extend the shallow groundwater was impacting the variability of storm responses. A total of 177 events were described using a set of quantitative and functional descriptors related to precipitation, stream and groundwater pre-event status and event dynamics, and to the relative dynamics between water quality parameters and flow via hysteresis indices. This approach led to identify different types of response for each water quality parameter which occurrence can be quantified and related to the seasonal functioning of the catchment. This study demonstrates that high-frequency records of water quality are precious tools to study/unique in their ability to emphasize the variability of catchment storm responses.

ISI Document Delivery No.: GK8RITimes Cited: 0Cited Reference Count: 53Piazza, Gustavo Antonio Dupas, Remi Gascuel-Odoux, Chantal Grimaldi, Catherine Pinheiro, Adilson Kaufmann, VanderCNPq [403739/2013-6, 309980/2017-8]; FAPESC [2016TR2525]; CAPES [PDSE - 88881.134429/2016-01]Long-term monitoring in the Concordia catchment is supported by CNPq (Process 403739/2013-6 and 309980/2017-8) and FAPESC (Process 2016TR2525). The first author acknowledges CAPES for the scholarship (process PDSE - 88881.134429/2016-01). The authors would like to thank all those who helped with the field and lab work.Elsevier science bvAmsterdam; Despite global efforts to monitor water quality in catchments worldwide, tropical and subtropical zones still lack data to study the influence of human activities and climate variations on solute dynamics. In this study, we monitored ten solutes every two weeks for six years (2010-2015) in three nested catchments (2 to 30 km(2)), which contained heterogeneous landscapes composed of forests and agricultural land, and one small neighboring forested catchment (0.4 km(2)). Data analysis revealed that i) rainfall, discharge and solute concentrations displayed no clear seasonal patterns, unlike many catchments of the temperate zone; ii) solute concentrations in the agricultural area were higher than those in the forested area, but both areas displayed similar temporal patterns due to a common hydroclimatic driver; iii) all four catchments displayed a chemostatic export regime for most of the solutes, similar to catchments of the temperate zone; and iv) a positive correlation was observed between anion concentrations and ENSO (El Nino-Southern Oscillation) index. ENSO appeared to influence both hydroclimatic and anion dynamics in these subtropical catchments. (C) 2018 Elsevier B.V. All rights reserved.

ISI Document Delivery No.: GL8ZN Times Cited: 1 Cited Reference Count: 48 Gascuel-Odoux, C. Fovet, O. Gruau, G. Ruiz, L. Merot, P. Univ rioja, serv publicaciones La rioja; International audience; Catchment studies on water quality started in the 1960s, when scientists identified long-term environmental impacts and realized the complexity involved in environmental degradation and recovery. Since scientists need to understand biogeochemical and hydrological processes in detail, long-term observatories have been established over time, particularly in the field of catchment hydrology and biochemistry. The AgrHyS (for “AgroHydroSystem”) observatory comprises two small catchments in Brittany (France) and this article unfolds the evolution over 50 years of the scientific questions and related observations and studies in one of them, the Kervidy-Naizin catchment. While a well-defined set of variables was monitored since the beginning (the “basic observatory basket”), the research topics and additional monitored variables were much broader. The first 25 years focused on hydrological and biogeochemical processes, while the next 25 years focused on more integrated issues related to soil ecology and landscape biogeochemical cycles. The AgrHyS observatory has succeeded in fostering interdisciplinary research. The current challenge is the engagement of the observatory in international networks to enable inter-comparison of hydro-systems response to gradients of different land use and environmental conditions.

ISI Document Delivery No.: GH6XMTimes Cited: 0Cited Reference Count: 46Vongvixay, Amphone Grimaldi, Catherine Dupas, Remi Fovet, Ophelie Birgand, Francois Gilliet, Nicolas Gascuel-Odoux, ChantalWileyHoboken; The study aimed to identify hydrological and landscape factors that influence sediment transport in 2 agricultural catchments in north-western FranceMoulinet and Kervidy-Naizinwith the same climate, size, and bedrock but with contrasting suspended sediment (SS) fluxes. Discharge and SS concentrations were continuously monitored at the catchment outlets for 9 hydrological years. Data were examined at annual, seasonal, and individual storm-flow event scales. Storm events were classified into 3 typessingle small, successive, and major eventswhose effect on sediment transport was studied. At the annual scale, SS yields were higher in Moulinet (16-63x10(3)kgkm(-2)) than in Kervidy-Naizin (3-22x10(3)kgkm(-2)) despite similar water fluxes. However, Kervidy-Naizin had higher potential for hillslope erosion because of more frequent occurrence of saturation excess runoff, more frequent bare soil in cultivated area, and fewer hedgerows. Major storm events were also stronger in this catchment. Although high SS concentrations and fluxes occurred only during a few major events in Kervidy-Naizin, SS export was always substantial throughout the year in Moulinet. We hypothesised that bank degradation due to cattle trampling generated the higher SS export in the Moulinet catchment. This hypothesis was confirmed by the large decrease in SS fluxes following construction of watering troughs in the middle of the study period. In the Kervidy-Naizin catchment, natural woody vegetation or grass buffer strips along the stream effectively protect the stream from bank erosion or a possible influx of hillslope erosion particles, except during some major events in winter.

Human activities have substantially altered riverine exports of carbon, nitrogen and phosphorus in the Anthropocene, causing major alterations of freshwater and marine ecosystems worldwide. Documenting anthropogenic alterations of carbon and nutrient cycles in aquatic ecosystems is a challenge as industrialization in western countries began in the 18th century and the green revolution in the mid-20th century, while river monitoring became widespread only since the 1990’s. Brittany - France, is one of the few noticeable exceptions of a region with multi-decadal datasets of nitrate (NO3-), soluble reactive phosphorus (SRP), total phosphorus (TP) and dissolved organic carbon (DOC) in meso-scale (< 5000 km2) rural catchments. Here we analyze these multi-decadal and multi-parameter time series with the objectives to investigate: i) long term trajectory of C, N, P concentrations in relation to the history of diffuse and point source pressures in seven catchments since the 1970’s, ii) medium term variations in relation to inter-annual climate variability (during 5-year wet-dry cycles) and iii) seasonal variations (and their long term evolution) in relation to catchments properties and history. Statistical analyses include a seasonal-trend decomposition procedure based on Loess (STL) and long term input-output hysteresis plots. Results show that long term NO3- concentration is controlled by the agricultural N surplus with a hysteresis effect, indicating a time lag of approximately 10 years between decrease in N inputs and decrease in NO3- loads. Long term SRP and TP concentrations are mainly controlled by point source emissions that have decreased continuously since the 1980’s. Long term DOC concentration shows little variation contrary to many catchments of the northern hemisphere. Medium term inter-annual NO3- concentration is controlled by discharge, with an increase in concentrations during wet years and a hysteresis effect indicating the flushing of a pool of nitrate stored in the catchments during antecedent drier years. Medium term SRP concentration is also controlled by discharge, with a dilution during wet years supporting the hypothesis of point-source dominated emissions. Medium term variations in TP and DOC concentrations are less clear, possibly because of opposite flushing and dilution effects during wet years. Seasonal variations exhibited winter maxima for NO3- and summer maxima for SRP, TP and DOC, confirming the dominant diffuse nature of NO3- emissions, the point-source dominated P emissions and possibly autochthonous DOC production during the summer period. Despite the study catchments being of relatively small size (median 800 km2), they were large enough to comprise a variety of point and diffuse sources which were not monitored individually, and the effect of hillslope processes could often not be disentangled from in stream processes. Therefore, future work will focus on combining monitoring in smaller headwater catchments, where few sources are present and in stream processes minimal, and in downstream stations representing the integrated signal discharging into the sea

Agricultural intensification has greatly decreased grassland surface area in some regions, thus changing grassland management and modifying environmental and socio-economic systems. Therefore, knowledge about grassland management practices in farming systems is needed for sustainable agriculture. In this context, the PaturMata model simulates grassland management at the farm scale. The PaturMata model simulates grassland dynamics and several factors such as farming practices, grass consumption, and fertilization. The model takes into account environmental and farming system parameters such as climate, field number, size, and location; livestock units; and conventional or organic agriculture. Here, we first ran the model under climatic conditions favorable to grass growth for four farms on an experimental site located in western France. Biophysical variables extracted from remote-sensing images were used to initialize PaturMata, whose predictions were compared to on-site surveys. We generated forecasting scenarios of the same farms under different climatic conditions. Results show that PaturMata predicts a 70 % decrease in grass consumption, a 50 % decrease in the number of annual grazing periods, and a 60 % increase in the amount of conserved forage consumed, when conditions are unfavorable to grass growth. We conclude that the PaturMata model can help design farms and management strategies capable of coping with a wide range of conditions.

International audience; Excessive nutrient delivery into freshwater bodies results in increased eutrophication risk worldwide. Because high-frequency monitoring cannot be generalised to all rivers, methods are needed to assess eutrophication risk in contexts with scarce data. To this end, we present an assessment framework which includes: (i) a mass-balance model to estimate diffuse N and P transfer/retention in unmonitored catchments and (ii) a set of indicators based on N:P:Si molar ratios to assess the risk of eutrophication in freshwaters. The model, called Nutting, integrates variables that describe both agricultural pressures and physical attributes of catchments (climate, topography, soil). Nutting refines previous mass-balance models by describing nutrient pressures with soil N surplus and soil P content instead of N and P inputs, and by considering physical attributes not only as lumped variables over the entire area but also within river corridors. The model was calibrated on a set of 160 independent catchments across France and applied to all headwater catchments. We found that apparent N and P retention represented 53 +/- 24% and 95 +/- 29% of soil N and P surplus, respectively, and was mainly controlled by the climate and a hydrology-related connectivity index. The spatial organisation of the landscape was of secondary importance compared to the refined description of agricultural pressures. Estimated eutrophication risk was highly sensitive to assumptions about P bioavailability, hence the potential range of headwaters at risk of eutrophication spanned 26-63% of the catchments, depending on assumptions. This framework provides a generic method to assess the relative contribution of agriculture to nutrient loads and the subsequent risk of eutrophication. (V) 2014 Elsevier Ltd. All rights reserved.

Spatially distributed agro-hydrological models allow researchers and stakeholders to represent, understand and formulate hypotheses about the functioning of agro-environmental systems and to predict their evolution. These models have guided agricultural management by simulating effects of landscape structure, farming system changes and their spatial arrangement on stream water quality. Such models generate many intermediate results that should be managed, analyzed and transformed into usable information. We describe a data warehouse (N-Catch) built to store and analyze simulation data from the spatially distributed agro-hydrological model TNT2. We present scientific challenges to and tools for building data warehouses and describe the three dimensions of N-Catch: space, time and an original hierarchical description of cropping systems. We show how to use OLAP to explore and extract all kinds of useful high-level information by aggregating the data along these three dimensions and how to facilitate exploration of the spatial dimension by coupling N-Catch with GIS. Such tool constitutes an efficient interface between science and society, simulation remaining a research activity, exploration of the results becoming an easy task accessible for a large audience. A data warehouse (DW) as a tool to explore simulated agro-environmental data.N-Catch as an example of a DW for analyzing N emissions across a catchment.DWs for catchment N management.

International audience; In agricultural landscapes, establishment of vegetated buffer zones in riparian wetlands (RWs) is promoted to decrease phosphorus (P) emissions because RWs can trap particulate P from upslope fields. However, long-term accumulation of P risks the release of dissolved P, since the unstable hydrological conditions in these zones may mobilize accumulated particulate P by transforming it into a mobile dissolved P species. This study evaluates how hydroclimate variability, topography and soil properties interact and influence this mobilization, using a three-year dataset of molybdate-reactive dissolved P (MRDP) and total dissolved P (TDP) concentrations in soil water from two RWs located in an agricultural catchment in western France (Kervidy-Naizin), along with stream P concentrations. Two main drivers of seasonal dissolved P release were identified: i) soil rewetting during water-table rise after dry periods and ii) reductive dissolution of soil Fe (hydr)oxides during prolonged water saturation periods. These mechanisms were shown to vary greatly in space (according to topography) and time (according to intra- and interannual hydroclimate variability). The concentration and speciation of the released dissolved P also varied spatially depending on soil chemistry and local topography. Comparison of sites revealed a similar correlation between soil P speciation (percentage of organic P ranging from 35–70%) and the concentration and speciation of the released P (MRDP from < 0.10 to 0.40 mg l− 1; percentage of MRDP in TDP from 25–70%). These differences propagated to stream water, suggesting that the two RWs investigated were the main sources of dissolved P to streams. RWs can be critical areas due to their ability to biogeochemically transform the accumulated P in these zones into highly mobile and highly bioavailable dissolved P forms. Hydroclimate variability, local topography and soil chemistry must be considered to decrease the risk of remobilizing legacy soil P when establishing riparian buffer zones in agricultural landscapes.

International audience; Diffuse transfer of nitrogen (N) and phosphorus (P) in agricultural catchments is controlled by the mobilisation of sources and their delivery to receiving waters. While plot scale experiments have focused on mobilisation processes, many catchment scale studies have hitherto concentrated on the controls of dominant flow pathways on nutrient delivery. To place mobilisation and delivery at a catchment scale, this study investigated their relative influence on contrasting nitrate-N and soluble P concentrations and N:P ratios in two shallow groundwater fed catchments with different land use (grassland and arable) on the Atlantic seaboard of Europe. Detailed datasets of N and P inputs, concentrations in shallow groundwater and concentrations in receiving streams were analysed over a five year period (October 2010-September 2015). Results showed that nitrate-N and soluble P concentrations in shallow groundwater give a good indication of stream concentrations, which suggests a dominant control of mobilisation processes on stream exports. Near-stream attenuation of nitrate-N (−30%), likely through denitrification and"dilution, and enrichment in soluble P (+100%), through soil-groundwater interactions, were similar in both catchments. The soil, climate and land use controls on mobilisation were also investigated. Results showed that grassland tended to limit nitrate-N leaching as compared to arable land, but grassland could also contribute to increased P solubilisation. In the context of land use change in these groundwater fed systems, the risk of pollution swapping between N and P must be carefully considered, particularly for interactions of land use with soil chemistry and climate.

The EU Water Framework Directive (WFD) obliges Member States to improve the quality of surface water and groundwater. The measures implemented to date have reduced the contribution of point sources of pollution, and hence diffuse pollution from agriculture has become more important. In many catchments the water quality remains poor. COST Action 869 was an EU initiative to improve surface water quality that ran from 2006 to 2011, in which 30 countries participated. Its main aim was a scientific evaluation of the suitability and cost-effectiveness of options for reducing nutrient loss from rural areas to surface waters at catchment scale, including the feasibility of the options under different climatic and geographical conditions. This paper gives an overview of various categories of mitigation options in relation to phosphorus (P). The individual measures are described in terms of their mode of action, applicability, effectiveness, time frame, environmental side-effects (N cycling) and cost. In total, 83 measures were evaluated in COST Action 869.

[Departement_IRSTEA]Eaux [ADD1_IRSTEA]Hydrosystèmes et risques naturels [ADD2_IRSTEA]Dynamique et fonctionnement des écosystèmes [ADD2_IRSTEA]Systèmes aquatiques soumis à des pressions multiples; International audience; The analysis of concentration-discharge (C-Q) relationships provides useful information on the processes controlling the mobilization and delivery of chemical elements into streams as well as biogeochemical transformations in river networks. Previous metrics developed to characterize export regimes seldom considered the possibility for the C response to Q dynamics to differ between short-term Q variations during storm events and seasonal Q variations during baseflow periods. Here, we present the “C-Qquick-slow” model, which considers the possibility for C-Q relationships to vary across temporal scales. This model was applied in 219 French catchments with various sizes (11–2500 km2), land use and hydrological contexts. We evidenced contrasting export regimes for nitrate (NO3 −), total phosphorus (TP) and soluble reactive phosphorus (SRP), and surprisingly consistent C-Q patterns at the seasonal scale for each parameter. For instance, NO3 −-Q relationships were positive at the seasonal scale in 75% cases and relationships during storms showed either a dilution pattern (24% cases), a non-significant pattern (50%), or a mobilization pattern (12%). TP and SRP relationships with Q at the seasonal scale were almostsystematically negative (95%), and patterns during storm events were in most cases mobilization for TP (77%) or non-significant for SRP (69%). We linked the different C-Q relationships with catchment descriptors and found that indicators of diffuse source loading determined NO3 − seasonal amplitudes, and hydrological drivers could explain the behavior during storms. By contrast, point sources determined P seasonal amplitudes, and diffuse sources controlled P dynamics during storms. The C-Qquick-slow model has the potential to improve nutrient loadestimations because of the good predictability of appropriate C-Q archetypes and the possibility to interpolate low frequency concentration data to a daily frequency

To improve hydro-chemical modeling and forecasting, there is a need to better understand flood-induced variability in water chemistry and the processes controlling it in watersheds. In the literature, assumptions are often made, for instance, that stream chemistry reacts differently to rainfall events depending on the season; however, methods to verify such assumptions are not well developed. Often, few floods are studied at a time and chemicals are used as tracers. Grouping similar events from large multivariate datasets using principal component analysis and clustering methods helps to explain hydrological processes; however, these methods currently have some limits (definition of flood descriptors, linear assumption, for instance). Most clustering methods have been used in the context of regionalization, focusing more on mapping results than on understanding processes. In this study, we extracted flood patterns using the probabilistic Latent Dirichlet Allocation (LDA) model, its first use in hydrology, to our knowledge. The LDA method allows multivariate temporal datasets to be considered without having to define explanatory factors beforehand or select representative floods. We analyzed a multivariate dataset from a long-term observatory (Kervidy-Naizin, western France) containing data for four solutes monitored daily for 12 years: nitrate, chloride, dissolved organic carbon, and sulfate. The LDA method extracted four different patterns that were distributed by season. Each pattern can be explained by seasonal hydrological processes. Hydro-meteorological parameters help explain the processes leading to these patterns, which increases understanding of flood-induced variability in water quality. Thus, the LDA method appears useful for analyzing long-term datasets.

Hydrol. Earth Syst. Sci.ISI Document Delivery No.: EF6IITimes Cited: 0Cited Reference Count: 77Dupas, Remi Salmon-Monviola, Jordy Beven, Keith J. Durand, Patrick Haygarth, Philip M. Hollaway, Michael J. Gascuel-Odoux, ChantalAgence de l'Eau Loire Bretagne via the "Trans-P project"; ORE AgrHySThis work was funded by the "Agence de l'Eau Loire Bretagne" via the "Trans-P project". Long-term monitoring in the Kervidy-Naizin catchment is supported by "ORE AgrHyS".Copernicus gesellschaft mbhGottingen; We developed a parsimonious topography-based hydrologic model coupled with a soil biogeochemistry sub-model in order to improve understanding and prediction of soluble reactive phosphorus (SRP) transfer in agricultural headwater catchments. The model structure aims to capture the dominant hydrological and biogeochemical processes identified from multiscale observations in a research catchment (Kervidy-Naizin, 5 km(2)). Groundwater fluctuations, responsible for the connection of soil SRP production zones to the stream, were simulated with a fully distributed hydrologic model at 20m resolution. The spatial variability of the soil phosphorus content and the temporal variability of soil moisture and temperature, which had previously been identified as key controlling factors of SRP solubilization in soils, were included as part of an empirical soil biogeochemistry sub-model. The modelling approach included an analysis of the information contained in the calibration data and propagation of uncertainty in model predictions using a generalized likelihood uncertainty estimation (GLUE) "limits of acceptability" framework. Overall, the model appeared to perform well given the uncertainty in the observational data, with a Nash-Sutcliffe efficiency on daily SRP loads between 0.1 and 0.8 for acceptable models. The role of hydrological connectivity via groundwater fluctuation and the role of increased SRP solubilization following dry/hot periods were captured well. We conclude that in the absence of near-continuous monitoring, the amount of information contained in the data is limited; hence, parsimonious models are more relevant than highly parameterized models. An analysis of uncertainty in the data is recommended for model calibration in order to provide reliable predictions.

Several controls are known to affect water quality of stream networks during flow recession periods, such as solute leaching processes, surface water–groundwater interactions as well as biogeochemical in-stream turnover processes. Throughout the stream network, combinations of specific water and solute export rates and local in-stream conditions overlay the biogeochemical signals from upstream sections. Therefore, upstream sections can be considered functional units which could be distinguished and ordered regarding their relative contribution to nutrient dynamics at the catchment outlet. Based on snapshot sampling of flow and nitrate concentrations along the stream in an agricultural headwater during the summer flow recession period, we determined spatial and temporal patterns of water quality for the whole stream. A data-driven, in-stream-mixing-and-removal model was developed and applied for analysing the spatio-temporal in-stream retention processes and their effect on the spatio-temporal fluxes of nitrate from subcatchments. Thereby, we have been able to distinguish quantitatively between nitrate sinks, sources per stream reaches, and subcatchments, and thus we could disentangle the overlay of nitrate sink and source signals. For nitrate sources, we determined their permanent and temporal impact on stream water quality and for nitrate sinks, we found increasing nitrate removal efficiencies from upstream to downstream. Our results highlight the importance of distinct nitrate source locations within the watershed for in-stream concentrations and in-stream removal processes, respectively. Thus, our findings contribute to the development of a more dynamic perception of water quality in streams and rivers concerning ecological and sustainable water resource management.

La salinisation des sols constitue un risque majeur du développement de l’irrigation dans le monde. Dans le Delta du Fleuve Sénégal, l’existence d’une nappe phréatique salée et proche de la surface du sol accentue ce risque. Une modélisation des transferts hydriques a été réalisée pour mieux évaluer ce risque. Elle a été faite à partir du code Hydrus sur l’ensemble du cycle cultural et a pris en compte deux types de sol et deux modes de culture de cette région : la simple et la double culture. Elle a permis d’estimer les flux hydriques descendants pendant la phase d’irrigation par submersion, et les flux hydriques et salins ascendants pendant la phase d’irrigation et de non-irrigation. Cette modélisation indique que : i) le toit de la nappe salée remonte d’environ 50 cm pendant la phase d’irrigation; ii) une zone non saturée de faible épaisseur subsiste entre la surface inondée et la nappe; iii) l’infiltration cumulée est deux fois plus forte en double qu’en simple culture; et iv) la forte évaporation durant la phase de non-irrigation peut faire remonter entre 5,5 à 6 t de sels par ha et par an, selon les sols et les conditions de culture. Cette modélisation, qui s’appuie sur des mesures in situ des paramètres hydrodynamiques, devra être confrontée à des observations in situ de flux. Elle devra intégrer des processus non pris à ce stade tel que le piégeage d’air. Les relevés piézométriques depuis dix ans montrent, par ailleurs, un léger relèvement du niveau de la nappe salée. L’ensemble de ces résultats est suffisamment préoccupant pour préconiser, dans le cas d’une irrigation par submersion, la mise en place d’un drainage superficiel pour éviter le relèvement de la nappe et assurer l’évacuation des sels hors de la nappe et, par là, la pérennisation de l’agriculture dans cette région du Delta du fleuve Sénégal, Soil salinisation is a major hazard of the extension of irrigation in the world. In the Delta of the Senegal River Valley, a highly saline groundwater close to the soil surface increases this hazard. A water and salt modeling by means of the Hydrus code has been performed to evaluate this hazard. Two soil types and two crop systems, a single and a double one, have been considered. The calculations have been performed on the complete agricultural cycle to determine water flows going down during the irrigation phase, and water and salt flows ascending to the soil surface during the irrigation and non irrigation phases. The modeling shows that: 1) the recharge due to the irrigation period induces an elevation of the water table of about 50 cm; 2) an unsaturated zone persists between the flooded surface and the water table; 3) the cumulative infiltration is two times higher in the double crop rice system than in the single crop system; 4) the high evaporation during the dry phase causes an ascension of from 5.5 to 6 t of salts per ha and per year according to the soil type and the crop system. This modeling, which was based on field measurements of hydrodynamic properties, has to be validated by field observations of the fluxes. Some processes such as air trapping should be tested. Piezometer monitoring over the past 10 years indicates a slight rise in the saline water table. All these results demonstrate the relevance of setting up a surficial drainage system for the flooded irrigation fields, to avoid an elevation of the water table and to evacuate salts from the soil surface, in order to perpetuate agriculture in the Delta of the Senegal River Valley.

While most hydrological models reproduce the general flow dynamics, they frequently fail to adequately mimic system-internal processes. In particular, the relationship between storage and discharge, which often follows annual hysteretic patterns in shallow hard-rock aquifers, is rarely considered in modelling studies. One main reason is that catchment storage is difficult to measure, and another one is that objective functions are usually based on individual variables time series (e.g. the discharge). This reduces the ability of classical procedures to assess the relevance of the conceptual hypotheses associated with models. We analysed the annual hysteric patterns observed between stream flow and water storage both in the saturated and unsaturated zones of the hillslope and the riparian zone of a headwater catchment in French Brittany (Environmental Research Observatory ERO AgrHys (ORE AgrHys)). The saturated-zone storage was estimated using distributed shallow groundwater levels and the unsaturated-zone storage using several moisture profiles. All hysteretic loops were characterized by a hysteresis index. Four conceptual models, previously calibrated and evaluated for the same catchment, were assessed with respect to their ability to reproduce the hysteretic patterns. The observed relationship between stream flow and saturated, and unsaturated storages led us to identify four hydrological periods and emphasized a clearly distinct behaviour between riparian and hillslope groundwaters. Although all the tested models were able to produce an annual hysteresis loop between discharge and both saturated and unsaturated storage, the integration of a riparian component led to overall improved hysteretic signatures, even if some misrepresentation remained. Such a system-like approach is likely to improve model selection.

International audience; Phosphorus (P) transfer during storm events represents a significant part of annual P loads in streams and contributes to eutrophication in downstream water bodies. To improve understanding of P storm dynamics, automated or semiautomated methods are needed to extract meaningful information from ever-growing water quality measurement data sets. In this paper, seasonal patterns of P storm dynamics are identified in two contrasting watersheds (arable and grassland) through Dynamic Time Warping (DTW) combined with k-means clustering. DTW was used to align discharge time series of different lengths and with differences in phase, which allowed robust application of a k-means clustering algorithm on rescaled P time series. In the arable watershed, the main storm pattern identified from autumn to winter displayed distinct export dynamics for particulate and dissolved P, which suggests independent transport mechanisms for both P forms. Conversely, the main storm pattern identified in spring displayed synchronized export of particulate and dissolved P. In the grassland watershed, the occurrence of synchronized export of dissolved and particulate P forms was not related to the season, but rather to the amplitude of storm events. Differences between the seasonal distributions of the patterns identified for the two watersheds were interpreted in terms of P sources and transport pathways. The DTW-based clustering algorithm used in this study proved useful for identifying common patterns in water quality time series and for isolating unusual events. It will open new possibilities for interpreting the high-frequency and multiparameter water quality time series that are currently acquired worldwide.

SUMMARYQuantitative assessment of mitigation measures for nitrogen (N) pollution requires adequate models, good knowledge of catchment functioning and a thorough understanding of agricultural systems and stakeholder constraints. The current paper analyses a set of results from simulations, with two models, of agricultural changes in two catchments in different contexts with different constraints. The results show that reducing N inputs and increasing grassland areas are the most efficient measures, not only because they reduce N fluxes in streams but also because they enhance N use by agriculture and the whole catchment system. Introducing catch crops, hedgerows and riparian buffers are interesting complementary measures but of limited impact when implemented alone. These results are sensitive to the way mitigation measures are translated into model inputs, and their operational implications are discussed.

Total phosphorus (TP) build-up in agricultural soils represents both a threat to aquatic ecosystems and a valuable resource for future crop production, given the context of increasing food demand combined with the rapid depletion of the world's phosphate reserves. Therefore, it is crucially important (i) to identify the main factors controlling topsoil TP and (ii) to develop methods for mapping its spatial distribution. Multiple linear regression models were used with two distinct approaches to calculate TP and covariates linked to the P cycle. Firstly, covariates were selected from the Réseau de Mesures de la Qualité des Sols database, the French soil monitoring network, which consists of soil samples collected from 2158 sites on a 16-km regular grid. Secondly, covariates were selected to map TP from spatially exhaustive datasets in France. The first approach explains 80% of variability in topsoil TP. The variables selected are linked to the autochthonous origin of P (parent material), to allochthonous origin (organic carbon and nitrogen contents) and to the retention capacity of soil (Al, Fe, Ca and clay contents). The predicted map obtained from the second approach provides a mean TP of 0.76 g/kg. This study demonstrates that creating national scale maps of TP, based on detailed soil sampling and many variables, is feasible and can be used to model the P cycle and P transfer processes. Such maps can be used in P erosion and transfer models over river basins, and therefore to predict P exports to surface waters.

The need for better conciliation between food production and environmental protection calls for new conceptual approaches in agronomy. Ecological intensification (EI) is one of the most encouraging and successful conceptual frameworks for designing more sustainable agricultural systems, though relying upon semantic ambivalences and epistemic tensions. This article discusses abilities and limits of the EI framework in the context of strong social and environmental pressure for agricultural transition. The purpose is thus to put EI at stake in the light of the results of an interdisciplinary and participatory research project that explicitly adopted EI goals in livestock semi-industrialized farming systems. Is it possible to maintain livestock production systems that are simultaneously productive, sustainable, and viable and have low nitrate emissions in vulnerable coastal areas? If so, how do local stakeholders use these approaches? The main steps of the innovation process are described. The effects of political and social dynamics on the continuity of the transition process are analyzed, with a reflexive approach. This experiment invites one to consider that making EI operational in a context of socio-technical transition toward agroecology represents system innovation, requiring on-going dialogue, reflexivity, and long-term involvement by researchers.

The estimation of water and solute transit times in catchments is crucial for predicting the response of hydrosystems to external forcings (climatic or anthropogenic). The hydrogeochemical signatures of tracers (either natural or anthropogenic) in streams have been widely used to estimate transit times in catchments as they integrate the various processes at stake. However, most of these tracers are well suited for catchments with mean transit times lower than about 4-5 years. Since the second half of the 20th century, the intensification of agriculture led to a general increase of the nitrogen load in rivers. As nitrate is mainly transported by groundwater in agricultural catchments, this signal can be used to estimate transit times greater than several years, even if nitrate is not a conservative tracer. Conceptual hydrological models can be used to estimate catchment transit times provided their consistency is demonstrated, based on their ability to simulate the stream chemical signatures at various time scales and catchment internal processes such as N storage in groundwater. The objective of this study was to assess if a conceptual lumped model was able to simulate the observed patterns of nitrogen concentration, at various time scales, from seasonal to pluriannual and thus if it was relevant to estimate the nitrogen transit times in headwater catchments. A conceptual lumped model, representing shallow groundwater flow as two parallel linear stores with double porosity, and riparian processes by a constant nitrogen removal function, was applied on two paired agricultural catchments which belong to the Research Observatory ORE AgrHys. The Global Likelihood Uncertainty Estimation (GLUE) approach was used to estimate parameter values and uncertainties. The model performance was assessed on (i) its ability to simulate the contrasted patterns of stream flow and stream nitrate concentrations at seasonal and inter-annual time scales, (ii) its ability to simulate the patterns observed in groundwater at the same temporal scales, and (iii) the consistency of long-term simulations using the calibrated model and the general pattern of the nitrate concentration increase in the region since the beginning of the intensification of agriculture in the 1960s. The simulated nitrate transit times were found more sensitive to climate variability than to parameter uncertainty, and average values were found to be consistent with results from others studies in the same region involving modeling and groundwater dating. This study shows that a simple model can be used to simulate the main dynamics of nitrogen in an intensively polluted catchment and then be used to estimate the transit times of these pollutants in the system which is crucial to guide mitigation plans design and assessment. (C) 2015 Elsevier B.V. All rights reserved.

The aim of this work is threefold: (1) to identify the main characteristics of water-table variations from observations in the Kervidy-Naizin catchment, a small catchment located in western France; (2) to confront these characteristics with the assumptions of the Topmodel concepts; and (3) to analyse how relaxation of the assumptions could improve the simulation of distributed water-table depth. A network of piezometers was installed in the Kervidy-Naizin catchment and the water-table depth was recorded every 15 min in each piezometer from 1997 to 2000. From these observations, the Kervidy-Naizin groundwater appears to be characteristic of shallow groundwaters of catchments underlain by crystalline bedrock, in view of the strong relation between water distribution and topography in the bottom land of the hillslopes. However, from midslope to summit, the water table can attain a depth of many metres, it does not parallel the topographic surface and it remains very responsive to rainfall. In particular, hydraulic gradients vary with time and are not equivalent to the soil surface slope. These characteristics call into question some assumptions that are used to model shallow lateral subsurface flow in saturated conditions. We investigate the performance of three models (Topmodel, a kinematic model and a diffusive model) in simulating the hourly distributed water-table depths along one of the hillslope transects, as well as the hourly stream discharge. For each model, two sets of parameters are identified following a Monte Carlo procedure applied to a simulation period of 2649 h. The performance of each model with each of the two parameter sets is evaluated over a test period of 2158 h. All three models, and hence their underlying assumptions, appear to reproduce adequately the stream discharge variations and water-table depths in bottom lands at the foot of the hillslope. To simulate the groundwater depth distribution over the whole hillslope, the steady-state assumption (Topmodel) is quite constraining and leads to unacceptable water-table depths in midslope and summit areas. Once this assumption is relaxed (kinematic model), the water-table simulation is improved. A subsequent relaxation of the hydraulic gradient (diffusive model) further improves water-table simulations in the summit area, while still yielding realistic water-table depths in the bottom land.

Nitrate concentrations in streamwater of agricultural catchments often exhibit interannual variations, which are supposed to result from land-use changes, as well as seasonal variations mainly explained by the effect of hydrological and biogeochemical cycles. In catchments on impervious bedrock, seasonal variations of nitrate concentrations in streamwater are usually characterized by higher nitrate concentrations in winter than in summer. However, intermediate or inverse cycles with higher concentrations in summer are sometimes observed. An experimental study was carried out to assess the mechanisms that determine the seasonal cycles of streamwater nitrate concentrations in intensive agricultural catchments. Temporal and spatial patterns of groundwater concentrations were investigated in two adjacent catchments located in south-western Brittany (France), characterized by different seasonal variations of streamwater nitrate concentrations. Wells were drilled across the hillslope at depths ranging from 1·5 to 20 m. Dynamics of the water table were monitored and the groundwater nitrate and chloride concentrations were measured weekly over 2 years. Results highlighted that groundwater was partitioned into downslope domains, where denitrification induced lower nitrate concentrations than into mid-slope and upslope domains. For one catchment, high subsurface flow with high nitrate concentrations during high water periods and active denitrification during low water periods explained the higher streamwater nitrate concentrations in winter than in summer. For the other catchment, the high contribution of groundwater with high nitrate concentrations smoothed or inverted this trend. Increasing bromide/chloride ratio and nitrate concentrations with depth argued for an effect of past agricultural pressure on this catchment. The relative contribution of flows in time and correlatively the spatial origin of waters, function of the depth and the location on the hillslope, and their chemical characteristics control seasonal cycles of streamwater nitrate concentrations and can influence their interannual trends. Copyright © 2004 John Wiley & Sons, Ltd.

Cet article, destine surtout aux non hydrologues, presente les problemes poses par la parametrisation des modeles hydrologiques et les reponses apportees. Les principales approches de modelisation hydrologique sont decrites, essentiellement sous l'angle du nombre de parametres consideres et de leur sens physique. Les modeles semi-distribues, bases sur une simplification des lois physiques et des schemas de spatialisation du bassin versant, pour restreindre le jeu de parametres, sont utilises pour illustrer le probleme de la parametrisation des modeles en hydrologie, a partir des travaux menes sur le bassin versant de recherche de Naizin (Morbihan, France). Nous montrons ainsi: (1) l'incidence de la resolution spatiale et temporelle sur la valeur des parametres et leur sens physique; (2) la non-unicite du jeu de parametres permettant une prediction acceptable des debits; (3) l'interet de l'approche bayesienne pour mieux contraindre les jeux de parametres et formaliser la pluralite des jeux de parametres possibles. D'autres approches de modelisation s'affranchissant partiellement du probleme de parametrisation sont esquissees, basees sur: (1) une architecture plus modulaire des modeles, permettant une identification des parametres decouplee du modele; (2) une approche qualitative de la modelisation, raisonnant l'accessibilite des parametres, l'usage et la transparence du modele.

Overland-flow triggering on rough surfaces was investigated using an understanding-oriented model. The model was based on conditioned-walker technique and developed to simulate and analyse the evolution of puddle connection on numerically generated rough surfaces. The percolation theory gave a theoretical framework to formalize model outputs and to study overland-flow scaling. Overland-flow triggering appeared consistent with a percolation process. A scale-change exponent was suggested. New insights based on the concept of transfer distance of water were emphasized. Transfer distance enabled us to analyse the water redistribution inside a field and helped to define rainfall efficiency when infiltration occurred. Copyright © 2002 John Wiley & Sons, Ltd.

A two-dimensional model representing flow and nitrate transport in groundwater was developed and applied to a hillslope of the Kervidy catchment. The objective of the modelling was: (1) to characterize better the flow and nitrate transport in the groundwater and to determine the characteristic times of the system; (2) to explore the consequences of changes in nitrate leaching to groundwater on nitrate concentration in stream water. The finite-difference code MODFLOW was used to simulate the distribution of hydraulic head within the groundwater. Nitrate transport was described by the convection equation solved using MT3D. MODPATH was also used to analyse flow paths and travel times in the groundwater. Four units were considered in the model: (i) the plough layer, (ii) the soil, (iii) the weathered shale and (iv) the fissured shale. Autotrophic denitrification in the shale and partly in the weathered shale was represented, as well as heterotrophic denitrification in the upper horizon of bottom land. A steady-state average flow was assumed with a spatially uniform groundwater recharge of 2 mm day -1 , corresponding to the winter mean daily recharge observed in the Kervidy catchment. Nitrate recharge rate was fixed at 100 mg l -1 , which is equivalent to a nitrogen flux of 165 kg ha -1 year -1 , Six scenarios of nitrate leaching changes were analysed with the model. The first two correspond to spatially uniform decreases of the nitrate recharge rate to 80 and 60 mg l -1 , respectively. In the other four scenarios, nitrate recharge rate was spatially distributed along the hillslope so that the average nitrogen flux remained equal to 165 kg ha -1 year -1 . Simulated hydraulic heads were similar to observed values along the hillslope, except for the summit. The transport model reproduced the spatial pattern of nitrate concentrations observed in the weathered shale groundwater, a deviation appearing only in the nearest piezometer to the stream. Travel times within the groundwater appeared to be highly variable, from a few days up to 3 years. Scenario analysis showed that a significant decrease of stream nitrate concentration can be expected following a global decrease in nitrate leaching along the hillslope. However, the fall could be very gradual in time.

Overland-flow generation is affected by surface roughness. This study analysed effects of surface roughness on overland-flow by means of a model simulating depression filling, flow pathways and runoff generation. It examined the relevant characteristics of surface roughness using numerically generated surfaces. At first, horizontal surfaces with random roughness of different correlation distances were considered. This showed that overland-flow is sensitive to the random-roughness correlation only if the correlation distance is similar to the surface size. Because this correlation distance is limited in natural soil surfaces, correlation properties are unlikely to modify overland-flow triggering. This allowed simplification of the description of random roughness. Then a general slope was added and different amplitude ratios between general slope and random roughness were simulated. Slope modified the development of overland-flow. While runoff was only sensitive to steep slopes, water transfer by overland-flow inside the surface was affected by low slopes too. The ratio between general slope and random roughness is a major parameter that controls transfers both inside the surface and to the outlet. Copyright © 2002 John Wiley & Sons, Ltd.

During rainfall events, surface roughness affects runoff generation by providing water surface storage in the depressions and altering the flow direction on the surface. The process of runoff initiation, or triggering, involves the gradual filling of individual depressions and the connection of those overflowing depressions toward the outflow boundary. Although studies have been conducted to relate surface roughness to total depression storage, little work has been done in quantifying the roughness effects on runoff initiation. This study examines the role of surface roughness on overland flow triggering in interrill areas. Laboratory experiments were conducted on a 2.4-m×2.4-m soil box exposed to a sequence of four rainfall events with treatments including two levels of initial roughness and two slope gradients. Surface microtopography was digitised by a laser scanner before and after each rainfall event. Soil roughness was analysed by the variogram method and its role in runoff triggering was evaluated using a numerical model that gradually fills depressions with a conditioned-walker method. Experimental variograms showed a gradual lowering of semivariances in a homothetic way after each additional rainfall, indicating that all roughness scales are affected similarly. All variograms showed a distinct topographic correlation length that can be related to depressional storage capacity. The linear relationship between these two variables also has a threshold roughness term below which the storage capacity tends to zero. Analyses of the runoff triggering showed that a small modification of micro-topographic structure had a major effect on runoff initiation. Even if the storage capacity is an important parameter of the runoff characteristics, large differences are observed between the initial stages of each experiment and final stages. We attributed these differences to the creation of preferential connections between topography depressions due to the material redistribution. Since the variogram analysis may not be sensitive toward the development of preferential flow path in a local scale, additional methodologies, such as the conditioned-walker analysis used in this study, need to be incorporated in quantifying the role of surface microtopography on the dynamics of runoff generation.