Simulating the effects of low impact development approaches on urban flooding: a case study from Tehran, Iran.

Low impact development (LID) methods have been shown to be efficient in reducing the peak flow and total volume of urban stormwater, which is a top priority for effective urban stormwater management in many municipalities. However, decision-makers need information on the effects of LIDs and their associated costs before allocating limited resources. In this study, the Storm Water Management Model (SWMM) was used to investigate the effects of five different LID scenarios on urban flooding in a district in Tehran, Iran. The LID scenarios included rain barrel (RB) at two sizes, bio-retention cell (BRC), and combinations of the two structures. The results showed that significant node flooding and overflow volume would occur in the study area under the existing conditions, especially for rainfall events with longer return periods. BRC and combinations of BRC and RBs were the most effective options in reducing flooding, while the smaller-size RB was the cheapest alternative. However, normalized cost, obtained through dividing the total cost by the percent reduction in node flooding and/or overflow volume, was smallest for BRC. The results of this study demonstrate how hydraulic modeling can be combined with economic analysis to identify the most efficient and affordable LID practices for urban areas.

Performance Assessment of Five Different Soil Moisture Sensors under Irrigated Field Conditions in Oklahoma.

Meeting the ever-increasing global food, feed, and fiber demands while conserving the quantity and quality of limited agricultural water resources and maintaining the sustainability of irrigated agriculture requires optimizing irrigation management using advanced technologies such as soil moisture sensors. In this study, the performance of five different soil moisture sensors was evaluated for their accuracy in two irrigated cropping systems, one each in central and southwest Oklahoma, with variable levels of soil salinity and clay content. With factory calibrations, three of the sensors had sufficient accuracies at the site with lower levels of salinity and clay, while none of them performed satisfactorily at the site with higher levels of salinity and clay. The study also investigated the performance of different approaches (laboratory, sensor-based, and the Rosetta model) to determine soil moisture thresholds required for irrigation scheduling, i.e., field capacity (FC) and wilting point (WP). The estimated FC and WP by the Rosetta model were closest to the laboratory-measured data using undisturbed soil cores, regardless of the type and number of input parameters used in the Rosetta model. The sensor-based method of ranking the readings resulted in overestimation of FC and WP. Finally, soil moisture depletion, a critical parameter in effective irrigation scheduling, was calculated by combining sensor readings and FC estimates. Ranking-based FC resulted in overestimation of soil moisture depletion, even for accurate sensors at the site with lower levels of salinity and clay.