Herb W. Rees

Using artificial neural network models to produce soil organic carbon content distribution maps across landscapes.

Soil organic carbon (SOC) content is an important soil quality indicator that plays an important role in regulating physical, chemical and biological properties of soil. Field assessment of SOC is time consuming and expensive. It is difficult to obtain high-resolution SOC distribution maps that are needed for landscape analysis of large areas. An artificial neural network (ANN) model was developed to predict SOC based on parameters derived from digital elevation model (DEM) together with soil properties extracted from widely available coarse resolution soil maps (1:1 000 000 scale). Field estimated SOC content data extracted from high-resolution soil maps (1:10 000 scale) in Black Brook Watershed in northwestern New Brunswick, Canada, were used to calibrate and validate the model. We found that vertical slope position (VSP) was the most important variable that determines distributions of SOC across the landscape. Other variables such as slope steepness, and potential solar radiation (PSR) also had signifi...

Influences of Sampling Methodologies on Pesticide-Residue Detection in Stream Water

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.

Seasonal distribution of runoff and soil loss under four tillage treatments in the upper St. John River valley New Brunswick, Canada

The effect of four different tillage treatments on surface runoff and soil loss, their seasonal distribution and temporal variation in soil erodibility were examined using runoff-erosion plots (10 m wide × 30 m long), on a Holmesville gravelly loam soil, a major soil type used for potato production in New Brunswick. Fall moldboard plowing, fall chisel plowing, spring moldboard plowing and subsoiling followed by fall moldboard plowing were evaluated under barley and fallow conditions on 8 and 11% slopes between 1989 and 1993. With exception of one year, annual precipitation was lower than normal. However, due to higher rainfall during the cropping season, the calculated erosivities were higher than those typically used for conservation planning in this region. Runoff data revealed that fall moldboard plowing generated the highest runoff. Either performing subsoiling prior to fall moldboard plowing or delaying moldboard plowing until the next spring, reduced runoff by approximately 10%. Chisel plowing, whic...

Model prediction of soil drainage classes based on digital elevation model parameters and soil attributes from coarse resolution soil maps

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), sedi...

Field Performance of Nine Soil Water Content Sensors on a Sandy Loam Soil in New Brunswick, Maritime Region, Canada

An in situ field test on nine commonly-used soil water sensors was carried out in a sandy loam soil located in the Potato Research Center, Fredericton, NB (Canada) using the gravimetric method as a reference. The results showed that among the tested sensors, regardless of installation depths and soil water regimes, CS615, Trase, and Troxler performed the best with the factory calibrations, with a relative root mean square error (RRMSE) of 15.78, 16.93, and 17.65%, and a r2 of 0.75, 0.77, and 0.65, respectively. TRIME, Moisture Point (MP917), and Gopher performed slightly worse with the factory calibrations, with a RRMSE of 45.76, 26.57, and 20.41%, and a r2 of 0.65, 0.72, and 0.78, respectively, while the Gypsum, WaterMark, and Netafim showed a frequent need for calibration in the application in this region.

A Watershed-scale Assessment of Cost-Effectiveness of Sediment Abatement with Flow Diversion Terraces

Soil conservation beneficial management practices (BMPs) are effective at controlling soil loss from farmlands and minimizing water pollution in agricultural watersheds. However, costs associated with implementing and maintaining these practices are high and often deter farmers from using them. Consequently, it is necessary to conduct cost-benefit analysis of BMP implementation to assist decision-makers with planning to provide the greatest level of environmental protection with limited resources and funding. The Soil and Water Assessment Tool (SWAT) was used to evaluate the efficacy of flow diversion terraces (FDT) in abating sediment yield at the outlet of Black Brook Watershed (BBW), northwestern New Brunswick. Different FDT-implementation scenarios were expressed as the ratio of land area protected by FDT to the total cultivated area. From this analysis, we found that average annual sediment yield decreased exponentially with increased FDT protection. When the proportion of FDT-protected areas was low, sediment reductions caused by FDT increased sharply with increasing use of FDT. Similarly, marginal sediment yield abatement costs (dollar per tonne of sediment reduction) increased exponentially with increasing proportion of FDT-protected area. The results indicated that increasing land protection with FDT from 6 to 50% would result in a reduction of about 2.1 tonne ha(-1) yr(-1) and costs of sediment reduction increased from

Effects of pulp fibre on soil physical properties and soil erosion under simulated rainfall

7 to

Effects of coarse fragment content on soil physical properties, soil erosion and potato production

12 per tonne. Increasing FDT-protected cropland from 50 to 100%, a reduction of about 0.9 tonne of sediment ha(-1) yr(-1) would occur and the costs would increase from

Effects of Hay Mulch on Soil Properties and Potato Tuber Yield under Irrigation and Nonirrigation in New Brunswick, Canada

12 to

Predict soil texture distributions using an artificial neural network model

53 per tonne of sediment yield reduction.