Characterization and prediction of ephemeral gully erosion in Wallonia

Ephemeral gully erosion is responsible for large soil losses in agricultural settings. It contributes to a loss of agronomic value of the soil and causes severe damage to crops. It also induces an increased workload for farmers. By increasing the connectivity in the landscape, the development of ephemeral gullies also enhances sediment delivery to downstream sites. This aggravates off-site effects such as muddy floods and pollution of watercourses by sediment and associated contaminants. In Belgium most studies on ephemeral gully erosion have been performed in the loess belt of Flanders and little information are available for Wallonia. The aim of the thesis was to characterize and predict the occurrence of ephemeral gully erosion in Wallonia in order to improve our understanding of the phenomenon and to suggest relevant mitigation techniques. Gully identification based on interpretation of aerial photographs was shown to be operator-dependent and to affect gully characterization. The number, total length, dominant type as well as topographic conditions leading to gullying were found to vary greatly across Wallonia. A new, more robust method was proposed to characterize the topographic contexts prone to ephemeral gully initiation. The main factors controlling ephemeral gully ending and their spatial variability were also identified. This information may prove useful to manage gully erosion in watersheds sensitive to gullying. The occurrence of ephemeral gully erosion was predicted using a set of topographic or hydraulic indicators. However, their performances were moderate at best. This may be improved in the future by using high resolution DEMs and by ameliorating the hydrological production and transfer functions used. It may also be necessary to integrate information on linear landscape elements and tillage direction.(AGRO - Sciences agronomiques et ingénierie biologique) -- UCL, 201

Integrating environmental information in gully initiation topographic thresholds: application to three regions in Wallonia (Belgium)

Gully erosion is responsible for 20% to 80% of the total soil erosion by water in Belgium and causes serious damages. In order to explain and predict the initiation of gully erosion, many studies have focused on topographic thresholds which depend on the contributing area and slope at the gully head. However, this approach does not integrate specific environmental information such as soil type and land use. Furthermore, several methods exist to determine the threshold. This study proposes a simple methodology to integrate soil and land use information in the topographic thresholds and compares the two main approaches used for drawing gully initiation thresholds. This methodology is applied to 3 agro-pedological regions of Wallonia (Belgium). For each region, a gully database was created by digitizing gullies on the basis of aerial photographs. Slopes and contributing areas at the gully heads as well as land use and soil type in the contributing areas were extracted. Using this information, runoff volumes were calculated using the SCS Curve Number method. Gully initiation thresholds defined using slope and runoff volume are compared with thresholds based on slope and contributing area. The former approach is better able to discriminate among contributing areas that have heterogeneous land uses and soil types. We found that regional differences in topographic and environmental conditions lead to differences in the thresholds. These differences are dependent on the type of thresholding method used. . The observed differences are sensitive to the method used for drawing the threshold

Herbe, diguettes, pesticides et pomme de terre

peer reviewe

Convention de recherche relative au développement d'outils de gestion intégrée du ruissellement, de l'érosion et des transferts de polluants associés pour les bassins versants du Grand-Duché du Luxembourg. Application au bassin-versant de la Haute-Sûre

Le présent rapport présente les résultats obtenus dans le cadre de la convention de recherche relative au développement d’outils de gestion intégrée du ruissellement, de l’érosion et des transferts de polluants associés pour les bassins versants du Grand-Duché de Luxembourg (GDL). Cette convention conclue entre l’Administration des Services Techniques de l’Agriculture et l’Earth and Life Institute s’inscrit dans la continuité de la convention PESTEAUX (novembre 2015 – juillet 2017, Centre wallon de Recherches Agronomiques) visant à mettre au point un outil d’aide à la décision, basé sur un Système d’Information Géographique, pour l’évaluation du risque de pollution diffuse des eaux de surface et souterraines par l’utilisation de produits phytopharmaceutiques, à l’échelle de la parcelle agricole, au GDL. La convention PESTEAUX a mis en évidence les potentialités du modèle SWAT dans le cadre de la gestion de la qualité des eaux de surface. Ce modèle permet aussi de quantifier les débits à l’échelle de sous-bassins versants, constituant ainsi un outil particulièrement pertinent pour la gestion des écoulements superficiels à l’échelle du bassin versant. Il intègre notamment de nombreuses fonctionnalités permettant une prise en compte détaillée de l’occupation du sol et de la gestion des cultures (TCS,…). Il permet aussi de simuler l’effet de l’implantation d’aménagements hydrauliques tels que des bandes enherbées, des chenaux enherbés ou bien des zones d’immersion temporaires sur les débits liquides et solides. SWAT peut donc constituer, à l’échelle du GDL, un outil de gestion intégrée des bassins versants particulièrement pertinent dans une optique de gestion de la qualité des eaux de surface, notamment dans le contexte du barrage d’Esch-sur-Sûre qui représente un tiers de la production d’eau potable au GDL. La mise au point d’un tel outil nécessite de pouvoir le calibrer et valider le modèle de manière fiable. La première étape correspondant à la présente convention était donc de pouvoir reproduire de manière fiable au moyen du modèle les différents débits liquides mesurés sur la Sûre et ses affluents. L’objectif principale de la convention était donc de calibrer et de valider le modèle SWAT pour les débits liquides des affluents de la Sûre en amont du barrage et disposant de données mesurées

Assessing the regional and temporal variability of the topographic threshold for ephemeral gully initiation using quantile regression in Wallonia (Belgium)

Ephemeral gully erosion is responsible for large losses of soil on cropland and causes serious off-site damages. Understanding and predicting the occurrence of ephemeral gully erosion are therefore major concerns for land users, decision makers or alike. In order to explain and predict the initiation of gully erosion, numerous studies have focused on the concept of topographic threshold which relies on the slope and contributing area at the gully head. Different approaches have been used so far for defining this threshold. However, these approaches may be questioned because they are partly subjective, not always statistically-based or based on the statistical weight of all data points rather than on the data points at the threshold. To copewith these deficiencies, quantile regression is proposed as an alternative for determining the threshold line. It is applied to assess the regional and temporal variability of gully initiation inWallonia (Belgium) and compared to previous thresholding approaches. A database of gullies was created from aerial photographs for three agro-pedological areas. The areas differed considerably in terms of number (102–282), mean length (84–151 m) and type of gullies. Most gullies were located on land with summer crops and more than 70% were restricted to a single plot. Significant différences in the topographical threshold were observed across areas, but these regional differences were not consistent across the various thresholding methods. Only 12–18% of gullies were recurrent over time, yet the topographic threshold determined by quantile regression seemed to be stable in spite of annual differences in land use and climate. The results reveal the need for greater standardization of thresholding methods. Quantile regression should be preferred over other previous approaches as it is more consistent with the concept of threshold and appears more robust

Survey of Hyperspectral Earth Observation Applications from Space in the Sentinel-2 Context

In the last few decades, researchers have developed a plethora of hyperspectral Earth Observation (EO) remote sensing techniques, analysis and applications. While hyperspectral exploratory sensors are demonstrating their potential, Sentinel-2 multispectral satellite remote sensing is now providing free, open, global and systematic high resolution visible and infrared imagery at a short revisit time. Its recent launch suggests potential synergies between multi- and hyper-spectral data. This study, therefore, reviews 20 years of research and applications in satellite hyperspectral remote sensing through the analysis of Earth observation hyperspectral sensors’ publications that cover the Sentinel-2 spectrum range: Hyperion, TianGong-1, PRISMA, HISUI, EnMAP, Shalom, HyspIRI and HypXIM. More specifically, this study (i) brings face to face past and future hyperspectral sensors’ applications with Sentinel-2’s and (ii) analyzes the applications’ requirements in terms of spatial and temporal resolutions. Eight main application topics were analyzed including vegetation, agriculture, soil, geology, urban, land use, water resources and disaster. Medium spatial resolution, long revisit time and low signal-to-noise ratio in the short-wave infrared of some hyperspectral sensors were highlighted as major limitations for some applications compared to the Sentinel-2 system. However, these constraints mainly concerned past hyperspectral sensors, while they will probably be overcome by forthcoming instruments. Therefore, this study is putting forward the compatibility of hyperspectral sensors and Sentinel-2 systems for resolution enhancement techniques in order to increase the panel of hyperspectral uses

Which measurement strategies to improve spatial erosion and deposition patterns modelling?

peer reviewedValidation of the erosion models requires field data. To date, many authors continue to highlight the paucity of accurate field observations and long-term enough studies. The fields observations are often put aside because these measures are difficult to obtain: weighty experimental devices, climatic dependence, . . . Hence the models are evolving and propose refined calculation procedures including for instance the calculation of landscape evolution. The need of field data therefore increases and new measuring strategies should arise. In the centre of Belgium we choose an agricultural watershed quite representative of the local context. It covers 124 ha of loamy soil with more than 90% of arable land and a weak proportion of forest and artificial lands. The slope ranges between 0 and 9%. Instrumentation on the watershed includes meteorological observations and discharge measurement coupled with water sampling at different outlets. The weather data (radiation, temperature, wind velocity, relative humidity and rainfall) and discharge measurement (comparison between Doppler and pressure sensors) will allow us to model the hydrological behaviour of the catchment. Rainfall readings (tipping buckets) are completed with erosivity readings (disdrometer). Erosivity, together with soil data, land use and agricultural practices observations on field, will be used as entry in the Landsoil model. The sediment samplings at 3 points in the catchment will give an insight of the sediment delivery of 3 subcatchments. The Landsoil model calculates the evolution of the DTM through time. This cannot be compared to measurements at the outlet and requires further data collection. Older elevation data and/or archaeological data are a possible source of information even if their precision remains scarce in our context. 1950’s soil surveys are on the contrary really informative since they detail the horizons depth in a spatial way and can be compared to new observation across the watershed. Coupled with unmanned aerial system, they should allow us to test the model performances and improve our knowledge of the spatial patterns of erosion and deposition

Artificial surfaces characteristics and sediment connectivity explain muddy flood hazard in Wallonia

Over the last decades, the off-site damages caused by muddy floods have been of growing concern throughout much of Western Europe, and particularly in Wallonia (Belgium). A reliable identification of locations with a high muddy flood hazard is thus a key issue in this context. The main objective of this study was therefore to build and evaluate a muddy flood hazard prediction model in order to assess the probability of occurrence of muddy floods at any specific location. A logistic regression approach was used to explain muddy flood occurrence using a database of 442 muddy flood-affected sites and an equal number of homologous non-flooded sites. Explanatory variables were related to geomorphology, land use, sediment production and sediment connectivity in the contributing area. The prediction quality of the model was then validated using an independent dataset composed of 48 pairs of flooded and non-flooded sites. The best muddy flood hazard assessment model required a total of 5 explanatory variables as inputs: the mean slope, a sediment connectivity index, as well as the proportion, spatial aggregation and proximity to the outlet of artificial surfaces. The model resulted in a prediction quality of 76% (calibration dataset) and 81% (validation dataset). Including the characteristics of artificial surfaces substantially improved the model quality (p-values from 10−11 to 10−5). All three variables related to artificial surfaces showed negative correlations with the muddy flood hazard. The proportion of cropland was not included in the final model, but this variable was strongly inversely correlated to the proportion of artificial surfaces. Besides the characteristics of artificial surfaces, sediment connectivity also showed significant explanatory power (p-value of 10−12). A positive correlation between sediment connectivity and muddy flood hazard was found. Future muddy flood hazard models should therefore include both artificial surfaces characteristics and sediment connectivity-related information. Given the good prediction quality, the developed statistical model could be used as a reliable tool to prioritize sites at risk of muddy floods in order to install mitigation measures