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Traditional grab sampling (GS) used widely in the study of water quality has been found lacking in spatial and temporal resolution for pesticide residue monitoring in stream water. The objectives of this article are to present a hydrograph-based sampling approach and compare it with traditional GS according to sensitivity at temporal and spatial scales and maximum concentrations of pesticide residues detected in-stream. Data collected from streams receiving water from three nested watersheds located in northwestern New Brunswick, Canada, were used in this study. The results showed that the hydrograph-based sampling method detected 20 to 30 % more pesticide cases than GS for rainfall events causing runoff. Grab sampling significantly underestimated average concentrations of pesticide residues by 50 % and maximum concentrations by 1 to 3 orders of magnitude. Using a modified sampler design, the spatial and temporal variability of pesticide residues was more accurately captured by hydrograph-based sampling, and therefore its use in monitoring programs is recommended.

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Model prediction of soil drainage classes based on digital elevation model parameters and soil attributes from coarse resolution soil maps. Can. J. Soil Sci. 88: 787Á799. High-resolution soil drainage maps are important for crop production planning, forest management, and environmental assessment. Existing soil classification maps tend to only have information about the dominant soil drainage conditions and they are inadequate for precision forestry and agriculture planning purposes. The objective of this research was to develop an artificial neural network (ANN) model for producing soil drainage classification maps at high resolution. Soil profile data extracted from coarse resolution soil maps (1:1 000 000 scale) and topographic and hydrological variables derived from digital elevation model (DEM) data (1:35 000 scale) were considered as candidates for inputs. A high-resolution soil drainage map (1:10 000) of the Black Brook Watershed (BBW) in northwestern New Brunswick (NB), Canada, was used to train and validate the ANN model. Results indicated that the best ANN model included average soil drainage classes, average soil sand content, vertical slope position (VSP), sediment delivery ratio (SDR) and slope steepness as inputs. It was found that 52% of model-predicted drainage classes were exactly the same as field assessment observations and 94% of model-predicted drainage classes were within91 class. In comparison, only 12% of maps indicated drainage classes were the same as field assessment observations based on coarse resolution soil maps and only 55% of points were within 91 class of field assessed drainage classes. Results indicated that the model could be used to produce high-resolution soil drainage maps at relatively low cost.Key words: Soil drainage, artificial neural network model, ANN model, high-resolution soil maps, DEM, hydrology model Zhao, Z., Chow, T. L., Yang, Q., Rees, H. W., Benoy, B., Xing, Z. et Meng, F. R. 2008. Mode`le pre´visionnel des classes de drainage du sol d'apre`s les parame`tres du MAN et les attributs des cartes pe´dologiques a`faible re´solution. Can. J. Soil Sci. 88: 787Á799. Les cartes de drainage du sol a`haute re´solution reveˆtent une grande importance pour la planification des cultures, la gestion des foreˆts et l'e´valuation de l'environnement. Les cartes de classification des sols actuelles ont tendance a`ne fournir de renseignements que sur les principales conditions de drainage et ne conviennent pas a`la planification de la foresterie et de l'agriculture de pre´cision. L'e´tude devait cre´er un mode`le a`re´seau neuronal artificiel (RNA) permettant une classification a`haute re´solution du drainage du sol. Les auteurs ont examine´si on pouvait utiliser a`cette fin les donne´es sur le profil du sol tire´es des cartes a`faible re´solution (e´chelle 1:1 000 000) ainsi que les variables topographiques et hydrologiques du mode`le altime´trique nume´rique (MAN) (e´chelle 1:35 000). Ils ont ensuite utilise´la carte a`haute re´solution de drainage du sol (1:10 000) du bassin...

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