Use of autonomous transmission line-type electromagnetic sensors for classification of dry and wet periods at sub-hourly time intervals.

Accurate identification of wet and dry weather periods at sub-hourly time intervals is important for the description and control of processes directly influenced by rainfall, such as infiltration into urban drainage systems, purification processes in wastewater treatment plants, or effective irrigation systems. It is also necessary for monitoring and modeling rainfall itself. Traditional instrumentation used to measure rainfall (rain gauges and radars) often fails to detect the transition between dry and wet weather at sufficient spatial and temporal resolution. Opportunistic sensing has become a promising approach in hydrology to overcome these deficits without drastically increasing the cost of measuring campaigns. In this study, we identify dry and wet weather periods using autonomous and inexpensive transmission line-type electromagnetic sensors, primarily intended for soil water content measurement.Four transmission line-type electromagnetic sensors, a tipping bucket rain gauge, and a laser precipitation monitor were installed in an urban catchment for an experimental period of 3 months during the summer. An algorithm for the reliable detection of the onset and end of precipitation episodes was developed for use with the sensors. Our analysis demonstrates that transmission line-type electromagnetic sensors provide results with accuracy similar to, and with five times greater sensitivity than a tipping bucket rain gauge. However, the sensors produced false-negative results more than 1.6% of the time (i.e., 25% of the received rain). Nevertheless, the low specificity of the sensors is not critical when they are used in combination with rain gauges or other sensors that are less prone to falsely detect wet periods.

Assessing the performance of blue-green solutions through a fine-scale water balance model for an urban area.

Blue and Green Infrastructures (BGIs) are natural or semi-natural systems that are considered an efficient solution to enhance stormwater management. To assess the performance of BGIs in mitigating floods and droughts in an urban area, a water balance model was developed in this study to simulate runoff formation and propagation. The developed model features fine spatial and temporal resolutions and flexibly integrates BGIs. Combining the conceptual single reservoir approach and the empirical continuous Soil Conservation Service Curve Number (SCS-CN) method, the model achieves computational efficiency, enabling long-term simulations that capture both short-term extreme events and long-term water balance. Its high transferability allows for easy incorporation of local datasets, making it adaptable to various urban contexts. Applied on a university campus located in Belgium, the model was used to simulate the water balance components of feasible BGIs for the study area, which were green roofs, permeable surfaces and rainwater tanks. Scenario analysis of both single BGI and combined BGI implementations was conducted, and all BGI scenarios were evaluated based on peak flow and runoff volume reduction and water balance analysis. Results demonstrate that the implementation of a combination of several BGIs with different functions is an effective solution for both flood control and drought mitigation, as these solutions can significantly reduce runoff flows, increase infiltration and provide considerable rainwater reuse.

Transport of bromide and pesticides through an undisturbed soil column: a modeling study with global optimization analysis.

The fate of pesticides in tropical soils is still not understood as well as it is for soils in temperate regions. In this study, water flow and transport of bromide tracer and five pesticides (atrazine, imazaquin, sulfometuron methyl, S-metolachlor, and imidacloprid) through an undisturbed soil column of tropical Oxisol were analyzed using a one-dimensional numerical model. The numerical model is based on Richards' equation for solving water flow, and the advection-dispersion equation for solving solute transport. Data from a laboratory column leaching experiment were used in the uncertainty analysis using a global optimization methodology to evaluate the model's sensitivity to transport parameters. All pesticides were found to be relatively mobile (sorption distribution coefficients lower than 2 cm(3) g(-1)). Experimental data indicated significant non-conservative behavior of bromide tracer. All pesticides, with the exception of imidacloprid, were found less persistent (degradation half-lives smaller than 45 days). Three of the five pesticides (atrazine, sulfometuron methyl, and S-metolachlor) were better described by the linear kinetic sorption model, while the breakthrough curves of imazaquin and imidacloprid were more appropriately approximated using nonlinear instantaneous sorption. Sensitivity analysis suggested that the model is most sensitive to sorption distribution coefficient. The prediction limits contained most of the measured points of the experimental breakthrough curves, indicating adequate model concept and model structure for the description of transport processes in the soil column under study. Uncertainty analysis using a physically-based Monte Carlo modeling of pesticide fate and transport provides useful information for the evaluation of chemical leaching in Hawaii soils.

Field leaching of pesticides at five test sites in Hawaii: modeling flow and transport.

BACKGROUND: Physically based tier-II models may serve as possible alternatives to expensive field and laboratory leaching experiments required for pesticide approval and registration. The objective of this study was to predict pesticide fate and transport at five different sites in Hawaii using data from an earlier field leaching experiment and a one-dimensional tier-II model. As the predicted concentration profiles of pesticides did not provide close agreement with data, inverse modeling was used to obtain adequate reactive transport parameters. The estimated transport parameters of pesticides were also utilized in a tier-I model, which is currently used by the state authorities to evaluate the relative leaching potential. RESULTS: Water flow in soil profiles was simulated by the tier-II model with acceptable accuracy at all experimental sites. The observed concentration profiles and center of mass depths predicted by the tier-II simulations based on optimized transport parameters provided better agreements than did the non-optimized parameters. With optimized parameters, the tier-I model also delivered results consistent with observed pesticide center of mass depths. CONCLUSION: Tier-II numerical modeling helped to identify relevant transport processes in field leaching of pesticides. The process-based modeling of water flow and pesticide transport, coupled with the inverse procedure, can contribute significantly to the evaluation of chemical leaching in Hawaii soils.