Modélisation des transferts de pesticides à l'échelle des bassins versants en période de crue

Les concentrations élevées en pesticides dans les eaux de surface drainant des bassins versants agricoles sont devenues une préoccupation majeure en Europe depuis une cinquantaine d'années. Les pesticides sont transférés dans l'environnement par différentes voies (le ruissellement de surface et de sub-surface, le flux de nappe), soit en solution soit adsorbés aux particules de sol en suspension dans l'eau. Les eaux de ruissellement et de percolation entraînent avec elles des charges de contaminants dont les concentrations en solution peuvent s'avérer toxiques pour la faune et la flore aquatique et rendre l'eau impropre à la consommation humaine si le réseau de drainage est une source de captage pour l'alimentation en eau potable. Les crues constituent donc des événements hydrologiques de première importance dans la contamination des eaux continentales par les pesticides. Les objectifs de cette thèse ont été de (1) caractériser, à l'aide d'un modèle agro-hydrologique, la dynamique des transferts de pesticides à l'échelle du bassin versant dans une région agricole, notamment en période de crue ; (2) identifier les facteurs de contrôle du transfert de pesticides et (3) améliorer, le cas échéant, les équations formalisées dans le modèle. Deux approches ont été menées de front afin de répondre aux questions posées : l'analyse de données mesurées et modélisées sur le bassin versant agricole de la Save (sud-ouest de la France). Une étude de faisabilité réalisée en préliminaire a montré que le modèle Soil and Water Assessment Tool (SWAT - Arnold et al., 1998) était adapté à la modélisation du transfert de pesticides, dans les phases dissoute et particulaire, à l'échelle du bassin versant. L'hydrologie et les concentrations à l'exutoire des phases dissoute et particulaire (respectivement les nitrates et les matières en suspension) ont été calibrées. Les voies privilégiées de transfert des pesticides en fonction des conditions hydrologiques ont été identifiées. La modélisation a ensuite été mise en œuvre avec des itinéraires techniques plus détaillés en entrée du modèle et des mesures sub-journalières de pesticides en crue. Les différentes voies de transfert des pesticides dans les deux phases, ainsi que leurs facteurs de contrôle environnementaux, ont été étudiés. Deux facteurs de contrôle, respectivement dépendant des pratiques agricoles (la date d'application des pesticides, qui est un facteur anthropique) et intrinsèque aux molécules de pesticides (le coefficient Kd de partition entre phases dissoute et particulaire, qui est un facteur physico-chimique) ont été abordés plus en détail. Le rôle de la typologie du bassin versant sur les transferts est discuté. Des cartes de risque de contamination des eaux de surface par les pesticides sont présentées pour le bassin de la Save. Dans la perspective d'améliorer le formalisme des modèles de transfert des pesticides, une équation qui relie le coefficient Kd au coefficient de distribution octanol/eau Kow et à la concentration en matières en suspension a été proposée. ABSTRACT : Rising pesticide levels in streams draining intensively managed agricultural land has become a widespread problem throughout Europe in recent decades. Pesticides are transferred into the environment through various pathways (surface and sub-surface runoff, groundwater return flow), either in solution or sorbed onto particles. Runoff and percolating water carry contaminants loads which concentrations in solution may be harmful to terrestrial and aquatic ecosystems rendering water unfit to human consumption if the draining network is a source for drinking water. Floods are hydrological events of major importance in continental waters contamination by pesticides. The objectives of this PhD thesis were (1) to characterise pesticides transfer dynamics at catchment scale in an agricultural area during floods; (2) to identify the factors controlling pesticides transfer and (3) to improve modelling by changing formalism with more suitable equations. Two approaches were set up: analysing both measured and simulated data sets, stemming from the River Save catchment (south-western France). A preliminary feasibility study showed that the Soil and Water Assessment Tool (SWAT - Arnold et al., 1998) was adapted for pesticides transfer modelling in both dissolved and sorbed phases, at catchment scale. Water discharge, dissolved and sorbed phases (respectively nitrate and suspended sediments) were calibrated. Pesticides transfer preferred pathways depending on hydrological conditions were identified. Modelling was then carried on more detailed management practices as input and on sub-daily pesticides concentration measurements during flood events. The various transfer pathways in both phases together with the environmental controlling factors were assessed. At last, two controlling factors, respectively depending on management practices (application date, an anthropogenic factor) and on an intrinsic pesticide molecule property (the partition coefficient Kd which is a physico-chemical factor) were studied. The role of catchment typology was discussed. Surface water contamination risk maps were drawn on Save catchment. In order to improve the formalism of pesticide transfer models, an equation was proposed that relates Kd to the octanol/water partition coefficient Kow and to suspended matter concentration

Occurrence of metolachlor and trifluralin losses in the Save river agricultural catchment during floods

Rising pesticide levels in streams draining intensively managed agricultural land have a detrimental effect on aquatic ecosystems and render water unfit for human consumption. The Soil and Water Assessment Tool (SWAT) was applied to simulate daily pesticide transfer at the outlet from an agriculturally intensive catchment of 1110 km2 (Save river, south-western France). SWAT reliably simulated both dissolved and sorbed metolachlor and trifluralin loads and concentrations at the catchment outlet from 1998 to 2009. On average, 17 kg of metolachlor and 1 kg of trifluralin were exported at outlet each year, with annual rainfall variations considered. Surface runoff was identified as the preferred pathway for pesticide transfer, related to the good correlation between suspended sediment exportation and pesticide, in both soluble and sorbed phases. Pesticide exportation rates at catchment outlet were less than 0.1% of the applied amount. At outlet, SWAT hindcasted that (i) 61% of metolachlor and 52% of trifluralin were exported during high flows and (ii) metolachlor and trifluralin concentrations exceeded European drinking water standards of 0.1 µg L−1 for individual pesticides during 149 (3.6%) and 17 (0.4%) days of the 1998–2009 period respectively. SWAT was shown to be a promising tool for assessing large catchment river network pesticide contamination in the event of floods but further useful developments of pesticide transfers and partition coefficient processes would need to be investigated

Modelling river discharge at sub-daily time-step: comparison of the performances of the conceptual SWAT model and the process-oriented MARINE model

Due to global change, the frequency of intense rainfall events and consequent flash floods are expected to increase in the next decades across the Mediterranean coastal basins. To date, few distributed models are able to simulate hydrological processes at basin-scale at a reasonable time scale to describe these flash events with accurate details. The MARINE model is one of them: it is a process-oriented fully distributed model operating dynamically at the rainfall event time-scale. Both infiltration and saturation excess are represented along with subsurface, overland and channel flows. It does not describe ground-water processes since the model's purpose is to simulate individual flood events during which ground-water processes are considered negligible. The SWAT model is a conceptual semi-distributed model assuming several simplifications in equations that dynamically simulates above- and below-ground processes. It has been recently upgraded to sub-daily time-step calculations. Considering the 1400 km² Têt Mediterranean river basin (southwestern France) as a case-study, the objective of this study was to assess and compare the performances of these two models when simulating the discharge at sub-daily time-step. We first calibrated the two models based on the same input dataset (topography, land-use, soil classes, and meteorological stations’ grid). We then compared the performances of the two models on a number of selected flood events. This ongoing work will contribute to assess the ability of the SWAT model to simulate discharge at sub-daily time-step

Modelling river discharge and sediments fluxes at sub-daily time-step: Insight into the CRUE-SIM project devoted to Mediterranean coastal flash floods

The CRUE-SIM project (2014-2017) is an interdisciplinary project that brings together atmosphere physicists, hydrologists and oceanographers to study and model flash floods across the Mediterranean region : it integrates water and sediment transport as a consequence of intense rainfall, from the catchment to the sea. The objectives of the project are (1) the coupling between atmosphere, ocean and sea with continental hydrological and hydrodynamic models and (2) the integration of the feedbacks and the forcing continuity from one compartment to the other along the brief but intense events that will be studied. Considering the 1400 km² Têt Mediterranean river basin (southwestern France) as a case-study, two hydrological models will be used at different time and spatial scales: the low resolution SWAT model outputs will be used as the inputs of the high resolution MARINE model, both using rainfall forcing from the Meso-NH atmospheric model. The feedback of the storm surge on the downstream part of the basin will be considered thanks to the SYMPHONIE ocean model. We will quantify the fluxes, at a sub-daily time-step, of water and of suspended particulate matter transported during floods from the soil to the river and from the river to the sea. The CRUE-SIM project is one of the research lines of the SEDILION project funded by RTRA-STAE focused on the transport of dissolved and sorbed matter during flash floods

New insight into pesticide partition coefficient Kd for modelling pesticide fluvial transport: Application to an agricultural catchment in south-western France

Pesticides applied on crops are leached with rainfall to groundwater and surface water. They threat the aquatic environment and may render water unfit for human consumption. Pesticide partitioning is one of the pesticide fate processes in the environment that should be properly formalised in pesticide fate models. Based on the analysis of 7 pesticide molecules (alachlor, atrazine, atrazine’s transformation product deethylatrazine or DEA, isoproturon, tebuconazole and trifluralin) sampled from July 2009 to October 2010 at the outlet of the river Save (south-western France), the objectives of this study were (1) to check which of the environmental factors (discharge, pH, concentrations of total suspended matter (TSM), dissolved organic carbon (DOC) and particulate organic carbon (POC) could control the pesticide sorption dynamic, and (2) to establish a relationship between environmental factors, the partition coefficient Kd and the octanol/water distribution coefficient Kow. The comparison of physico-chemical parameters values during low flow and high flow shows that discharge, TSM and POC are the factors most likely controlling the pesticide sorption processes in the Save river network, especially for lower values of TSM (below 13 mg L-1). We therefore express Kd depending on the widely literature-related variable Kow and on the commonly simulated variable TSM concentration. The equation can be implemented in any model describing the fluvial transport and fate of pesticides in both dissolved and sorbed phases, thus, Kd becomes a variable in time and space. The Kd calculation method can be applied to a wide range of catchments and organic contaminants

Analysis of the uncertainty in the monetary valuation of ecosystem services - a case study at the river basin scale

Ecosystem services provide multiple benefits to human wellbeing and are increasingly considered by 18 policy-makers in environmental management. However, the uncertainty related with the monetary 19 valuation of these benefits is not yet adequately defined or integrated by policy-makers. Given this 20 background, our aim was to quantify different sources of uncertainty when performing monetary 21 valuation of ecosystem services, in order to provide a series of guidelines to reduce them. With an 22 example of 4 ecosystem services (i.e., water provisioning, waste treatment, erosion protection, and 23 habitat for species) provided at the river basin scale, we quantified the uncertainty associated with 24 the following sources: (1) the number of services considered, (2) the number of benefits considered 25 for each service, (3) the valuation metrics (i.e. valuation methods) used to value benefits, and (4) the 26 uncertainty of the parameters included in the valuation metrics. Results indicate that the highest 27 uncertainty was caused by the number of services considered, as well as by the number of benefits 28 considered for each service, whereas the parametric uncertainty was similar to the one related to the 29 selection of valuation metric, thus suggesting that the parametric uncertainty, which is the only 30 uncertainty type commonly considered, was less critical than the structural uncertainty, which is in 31 turn mainly dependent on the decision-making context. Given the uncertainty associated to the 32 valuation structure, special attention should be given to the selection of services, benefits and 33 metrics according to a given context

Advantages and insights from a hierarchical Bayesian growth and dynamics model based on salmonid electrofishing removal data

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

Modeling the Fate and Transport of Malathion in the Pagsanjan-Lumban Basin, Philippines

Exposure to highly toxic pesticides could potentially cause cancer and disrupt the development of vital systems. Monitoring activities were performed to assess the level of contamination; however, these were costly, laborious, and short-term leading to insufficient monitoring data. However, the performance of the existing Soil and Water Assessment Tool (SWAT model) can be restricted by its two-phase partitioning approach, which is inadequate when it comes to simulating pesticides with limited dataset. This study developed a modified SWAT pesticide model to address these challenges. The modified model considered the three-phase partitioning model that classifies the pesticide into three forms: dissolved, particle-bound, and dissolved organic carbon (DOC)-associated pesticide. The addition of DOC-associated pesticide particles increases the scope of the pesticide model by also considering the adherence of pesticides to the organic carbon in the soil. The modified SWAT and original SWAT pesticide model was applied to the Pagsanjan-Lumban (PL) basin, a highly agricultural region. Malathion was chosen as the target pesticide since it is commonly used in the basin. The pesticide models simulated the fate and transport of malathion in the PL basin and showed the temporal pattern of selected subbasins. The sensitivity analyses revealed that application efficiency and settling velocity were the most sensitive parameters for the original and modified SWAT model, respectively. Degradation of particulate-phase malathion were also significant to both models. The rate of determination (R2) and Nash-Sutcliffe efficiency (NSE) values showed that the modified model (R2 = 0.52; NSE = 0.36) gave a slightly better performance compared to the original (R2 = 0.39; NSE = 0.18). Results from this study will be able to aid the government and private agriculture sectors to have an in-depth understanding in managing pesticide usage in agricultural watersheds

In-stream Escherichia coli modeling using high-temporal-resolution data with deep learning and process-based models

Contamination of surface waters with microbiological pollutants is a major concern to public health. Although long-term and high-frequency Escherichia coli (E. coli) monitoring can help prevent diseases from fecal pathogenic microorganisms, such monitoring is time-consuming and expensive. Process-driven models are an alternative means for estimating concentrations of fecal pathogens. However, process-based modeling still has limitations in improving the model accuracy because of the complexity of relationships among hydrological and environmental variables. With the rise of data availability and computation power, the use of data-driven models is increasing. In this study, we simulated fate and transport of E. coli in a 0.6 km(2) tropical headwater catchment located in the Lao People's Democratic Republic (Lao PDR) using a deep-learning model and a process-based model. The deep learning model was built using the long short-term memory (LSTM) methodology, whereas the process-based model was constructed using the Hydrological Simulation Program-FORTRAN (HSPF). First, we calibrated both models for surface as well as for subsurface flow. Then, we simulated the E. coli transport with 6 min time steps with both the HSPF and LSTM models. The LSTM provided accurate results for surface and subsurface flow with 0.51 and 0.64 of the Nash-Sutcliffe efficiency (NSE) values, respectively. In contrast, the NSE values yielded by the HSPF were -0.7 and 0.59 for surface and subsurface flow. The simulated E. coli concentrations from LSTM provided the NSE of 0.35, whereas the HSPF gave an unacceptable performance with an NSE value of -3.01 due to the limitations of HSPF in capturing the dynamics of E. coli with land-use change. The simulated E. coli concentration showed the rise and drop patterns corresponding to annual changes in land use. This study showcases the application of deep-learning-based models as an efficient alternative to process-based models for E. coli fate and transport simulation at the catchment scale

Modelling the impacts of agricultural management practices on river water quality in Eastern England

Agricultural diffuse water pollution remains a notable global pressure on water quality, posing risks to aquatic ecosystems, human health and water resources and as a result legislation has been introduced in many parts of the world to protect water bodies. Due to their efficiency and cost-effectiveness, water quality models have been increasingly applied to catchments as Decision Support Tools (DSTs) to identify mitigation options that can be introduced to reduce agricultural diffuse water pollution and improve water quality. In this study, the Soil and Water Assessment Tool (SWAT) was applied to the River Wensum catchment in eastern England with the aim of quantifying the long-term impacts of potential changes to agricultural management practices on river water quality. Calibration and validation were successfully performed at a daily time-step against observations of discharge, nitrate and total phosphorus obtained from high-frequency water quality monitoring within the Blackwater sub-catchment, covering an area of 19.6 km2. A variety of mitigation options were identified and modelled, both singly and in combination, and their long-term effects on nitrate and total phosphorus losses were quantified together with the 95% uncertainty range of model predictions. Results showed that introducing a red clover cover crop to the crop rotation scheme applied within the catchment reduced nitrate losses by 19.6%. Buffer strips of 2 m and 6 m width represented the most effective options to reduce total phosphorus losses, achieving reductions of 12.2% and 16.9%, respectively. This is one of the first studies to quantify the impacts of agricultural mitigation options on long-term water quality for nitrate and total phosphorus at a daily resolution, in addition to providing an estimate of the uncertainties of those impacts. The results highlighted the need to consider multiple pollutants, the degree of uncertainty associated with model predictions and the risk of unintended pollutant impacts when evaluating the effectiveness of mitigation options, and showed that high-frequency water quality datasets can be applied to robustly calibrate water quality models, creating DSTs that are more effective and reliable