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This study examines the hydrologic performance of conventional and low-impact development (LID) stormwater approaches when implemented as retrofit measures in a highly urbanised catchment (10.23 km2). A hydrologic-hydrodynamic model was proposed to simulate different implementation scenarios. Rainfall data and downstream water level observations between 01/2016 and 02/2019 were used to calibrate and validate (0.77 ≤ NSE ≤ 0.97) the model for the current situation. The simulation of stormwater control, as indicated in the municipal regulation, involving on-site retention tanks at a lot scale, led to peak flow reductions of 5% for a 10-year design storm event. When the number of dwelling owners subjected to comply with the control measures was increased, a peak flow reduction of 18% for the same event was reached. Modelling tools can guide policy and rule-making processes from a catchment management perspective, supporting the evaluation and improvement of strategies adopted in urban stormwater management. [ABSTRACT FROM AUTHOR]

Automated soil moisture systems are commonly used in precision agriculture. Using low-cost sensors, the spatial extension can be maximized, but the accuracy might be reduced. In this paper, we address the trade-off between cost and accuracy comparing low-cost and commercial soil moisture sensors. The analysis is based on the capacitive sensor SKU:SEN0193 tested under lab and field conditions. In addition to individual calibration, two simplified calibration techniques are proposed: universal calibration, based on all 63 sensors, and a single-point calibration using the sensor response in dry soil. During the second stage of testing, the sensors were coupled to a low-cost monitoring station and installed in the field. The sensors were capable of measuring daily and seasonal oscillations in soil moisture resulting from solar radiation and precipitation. The low-cost sensor performance was compared to commercial sensors based on five variables: (1) cost, (2) accuracy, (3) qualified labor demand, (4) sample volume, and (5) life expectancy. Commercial sensors provide single-point information with high reliability but at a high acquisition cost, while low-cost sensors can be acquired in larger numbers at a lower cost, allowing for more detailed spatial and temporal observations, but with medium accuracy. The use of SKU sensors is then indicated for short-term and limited-budget projects in which high accuracy of the collected data is not required. [ABSTRACT FROM AUTHOR]