Simulation de l’effet de changements de pratiques agricoles sur la qualité des eaux avec le modèle SWAT

La lutte contre la pollution des eaux par l’agriculture nécessite des changements de pratiques agricoles. Les actions proposées par les gestionnaires des territoires ont des effets variables sur la qualité des eaux selon la nature du milieu et des activités agricoles existantes. La modélisation agro-hydrologique constitue une voie pour évaluer les impacts de pratiques agricoles sur la qualité des eaux à l’échelle de bassins versants. Elle offre ainsi un support d’aide à la décision face à une multiplicité d’actions alternatives et permet de rationaliser les choix en termes d’efficacité environnementale.Dans cet article, nous présentons la mise en oeuvre et les résultats d’une simulation d’un changement de pratiques agricoles sur un bassin versant de 385 km2 dans l’ouest de la France. Ce projet a été réalisé en partenariat avec les gestionnaires locaux afin d’évaluer les évolutions possibles de la qualité des eaux à moyen terme. Les données mobilisées sont des chroniques quotidiennes de précipitations et de température, un modèle numérique de terrain, une carte des sols, une carte des successions culturales sur deux ans résultant d’un traitement d’images satellitaires et des pratiques agricoles issues d’enquêtes.Le modèle offre une calibration hydrologique satisfaisante avec un indice de Nash de 0,81 obtenu sur la période 2000‑2001; la dynamique des transferts de nitrates et de phosphore est également reproduite, mais les résultats sont à nuancer par la fréquence insuffisante des données de validation. Après le calage du modèle, l’efficacité relative de deux changements de pratiques agricoles est estimée : a) à l’implantation d’une culture intermédiaire piège à nitrates (moutarde) et b) au passage au semis direct sous couvert végétal. Finalement, la technique du semis direct apparaît comme la pratique la plus efficace pour réduire les transferts de phosphore qui représentent la pollution principale sur l’espace étudié.Reducing the negative impact of agriculture on water quality requires changes in agricultural practices. The actions proposed by local stakeholders have variable effects on water quality depending on the kind of environment and existing agricultural activities. In this context, agro-hydrological modelling constitutes an approach for assessing the impacts of agricultural practices on water quality at the watershed level, offering valuable decision-making support regarding a range of policy alternatives. More specifically, modelling provides a means for evaluating policy choices in terms of environmental efficiency.In this article, we present the implementation and results of a simulation involving new agricultural practices on a 385 km2 watershed in western France. This project involved a partnership with local planners in order to evaluate possible changes of water quality over the mid-term. The data used are a daily series of precipitation and temperature measurements, a Digital Elevation Model, a soil map, a crop rotation map for two successive years resulting from satellite imagery, and information concerning agricultural practices based on field surveys.For the 2000-2001 calibration period, the model provided good hydrological results with a 0.81 Nash index between simulated and observed flows. The dynamics of nitrogen and phosphorus fluxes in the river were also well represented by the model, although the insufficient frequency of validation data should be kept in mind when interpreting these results. After the retrospective calibration of the model, the efficiency of two changes in agricultural practices was evaluated: i) the introduction of a winter crop cover (mustard); and ii) no tillage. The no-tillage method appeared to be the most effective in reducing phosphorus fluxes, which represent the major source of pollution in the study area

Мессояха – газогидратная залежь, роль и значение

Описаны геология и технологии эксплуатации Мессояхского газогидратного месторождения. Опыт его разработки показывает: газогидратные залежи (ГГЗ) следует активно вводить в разработку; каждая ГГЗ требует “персональной” технологии разработки; необходимо глубоко, на молекулярном уровне изучать свойства гидратонасыщенных пород и флюида, который в них содержится; необходимы принципиально новые технологии разработки ГГЗ и транспорта гидратного газа.Охарактеризовано геологічну будову й технологію розробки Мессояхського газогідратного родовища. Досвід його розробки засвідчив: газогідратні поклади (ГГП) слід активно вводити у розробку; кожна ГГП вимагає індивідуальних технологій розробки; необхідно глибоко, на молекулярному рівні вивчати властивості гідратонасичених порід та флюїда, що в них міститься; потрібно створювати принципово нові технології розробки ГГП та транспорту гідратного газу.Geology and technology of Messoyakhska field developing are discribed. Experience clearly shows: development of gas hydrate fields should be actively promoted; each gas hydrates field requires a specific development technology; it is necessary to research at the molecular level the properties of hydrate saturated rocks and is required; develop a fundamentally new technologies of hydrated gas production is vital

До 85-річчя Ісаака Бенціоновича Клеймана

У 2006 р. виповнилося 85 років одному з найшановніших археологів Одеси, відомому досліднику стародавньої Тіри Ісааку Бенціоновичу Клейману

Une approche de modélisation nivo-hydrologique inverse pour déduire les gradients d'élévation de la température de l'air et des précipitations dans les bassins de montagne

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Should altitudinal gradients of temperature and precipitation inputs be inferred from key parameters in snow-hydrological models?

International audienceThis paper evaluates whether snow-covered area and streamflow measurements can help assess altitudinal gradients of temperature and precipitation in data-scarce mountainous areas more efficiently than using the usual interpolation procedures. A dataset covering 20 Alpine catchments is used to investigate this issue. Elevation dependency in the meteorological fields is accounted for using two approaches: (i) by estimating the local and time-varying altitudinal gradients from the available gauge network based on deterministic and geostatistical interpolation methods with an external drift; and (ii) by calibrating the local gradients using an inverse snow-hydrological modelling framework. For the second approach, a simple two-parameter model is proposed to target the temperature/precipitation-elevation relationship and to regionalize air temperature and precipitation from the sparse meteorological network. The coherence of the two approaches is evaluated by benchmarking several hydrological variables (snow-covered area, streamflow) computed with snow-hydrological models fed with the interpolated datasets and checked against available measurements. Results show that accounting for elevation dependency from scattered observations when interpolating air temperature and precipitation cannot provide sufficiently accurate inputs for models. The lack of high-elevation stations seriously limits correct estimation of lapse rates of temperature and precipitation, which, in turn, affects the performance of the snowhydrological simulations due to imprecise estimates of temperature and precipitation volumes. Instead, retrieving the local altitudinal gradients using an inverse approach enables increased accuracy in the simulation of snow cover and discharge dynamics while limiting problems of over-calibration and equifinality

Potential of snow data to improve the consistency and robustness of a semi-distributed hydrological model using the SAFRAN input dataset

International audienceThis paper compares different calibration strategies for using snow data combined with streamflow records to constrain model optimisation in mountain catchments. In particular, it assesses to what extent the use of snow observations makes it possible to improve the consistency, identifiability and robustness of the calibrated parameters. To answer this question, a semi-distributed snow and ice model was used on top of a rainfall-runoff model using the SAFRAN meteorological reanalysis as input dataset on several catchments in the Alps and Pyrenees. Model calibration and control were based on streamflow observations, remotely-sensed snow-covered areas and in-situ snow water equivalent (SWE) measurements. The snow and rainfall-runoff parameters were calibrated sequentially and simultaneously against objective functions integrating different combinations of runoff, snow cover and SWE criteria. Statistical assessment of model performances in independent evaluation periods showed that sequential calibration of the snow parameters gives too much weight to snow compared to runoff. Instead, incorporating snow data in the simultaneous calibration of the parameters improves snow simulations without impairing runoff performance. This can be achieved by limiting the weight of the snow criteria to 25% in the objective function. Although local SWE measurements were found to be more useful than satellite observations for identifying more consistent parameters, it is advisable to include both in the calibration process through a compromise objective function. However, the improved model consistency was not accompanied by a significant reduction in equifinality and optimisation times. On the other hand, improving internal consistency made it possible to reduce the interdependence between the parameters of the snow model and those of the rainfall-runoff model. This also made it possible to identify the least sensitive snow parameters in order to fix them at general values without impairing model performance while reducing equifinality with a more parsimonious model. Finally, there was no evidence that using snow observations in the calibration process improves model robustness with respect to climate variability

Une approche de modélisation nivo-hydrologique inverse pour déduire les gradients d'élévation de la température de l'air et des précipitations dans les bassins de montagne

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Development of the snow- and ice-accounting routine (SIAR)

This article investigates the degrees of liberty and complexity warranted in temperature-index models to jointly simulate local snow measurements, remotely-sensed snow cover and runoff in mountainous areas. To address this issue, the snow- and ice-accounting routine (SIAR) on top of the GR4J model was developed on a dataset covering 17 mountainous catchments (45 to 3 580 km²) in the French Alps and Pyrenees. Model calibration and control were based on streamflow series, fractional snow cover (FSC) computed from MODIS snow products and at least one chronicle of local measurements of snow water equivalent (SWE) acquired in each catchment for the period 2004−2016. SIAR was applied according to a flexible number of equal-area elevation zones and different parametrizations ranging from 11 free parameters (precipitation orographic correction, temperature lapse rate, variation in the temperature lapse rate, correction for snowfall gauge under-catch, rainfall lapse rate, thermal inertia of the snow pack, constant and variable part of the degree-day snow melt factor, degree-day ice melt factor, 2-parameter hysteresis between SWE and FSC), to only fixed parameters. Results showed that the one-free-parameter SIAR is as efficient as more flexible structures in simulating both local and distributed snow dynamics as well as runoff. Interestingly, using SIAR without any free parameters by fixing the snowfall gauge under-catch correction to a median value of 160% only led to slight deterioration of local SWE dynamics. SIAR was then compared with alternative versions to justify internal processes (glacier-component, sublimation, energy balance, snowpack cold-content, variable melt factor) and modes of distribution that were retained in the final version. Finally, SIAR was compared with the Cemaneige snow routine, which showed its modeling performance was better. These findings suggest that it is possible, and even advisable, to limit the number of free parameters in temperature-index models in order to reduce problems of over-parameterization and equifinality

Projet GICC REMedHE (2012‒2016) : durabilité des usages de l’eau au sein des hydrosystèmes Hérault et Ebre sous changements climatiques et anthropiques.

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