Abstract: Urban flooding in Chittagong City usually occurs during the monsoon season and a rainwater harvesting (RWH) system can be used as a remedial measure. This study examines the feasibility of rain barrel RWH system at a distributed scale within an urbanized area located in the northwestern part of Chittagong City that experiences flash flooding on a regular basis. For flood modeling, the storm water management model (SWMM) was employed with rain barrel low-impact development (LID) as a flood reduction measure. The Hydrologic Engineering Center’s River Analysis System (HEC-RAS) inundation model was coupled with SWMM to observe the detailed and spatial extent of flood reduction. Compared to SWMM simulated floods, the simulated inundation depth using remote sensing data and the HEC-RAS showed a reasonable match, i.e., the correlation coefficients were found to be 0.70 and 0.98, respectively. Finally, using LID, i.e., RWH, a reduction of 28.66% could be achieved for reducing flood extent. Moreover, the study showed that 10%–60% imperviousness of the subcatchment area can yield a monthly RWH potential of 0.04–0.45 m3 from a square meter of rooftop area. The model can be used for necessary decision making for flood reduction and to establish a distributed RWH system in the study area.

Abstract: Quantifying evapotranspiration and drainage losses is essential for improving irrigation efficiency. The FAO-56 is the most popular method for computing crop evapotranspiration. There is, however, a need for locally derived crop coefficients (Kc) with a high temporal resolution to reduce errors in the water balance. The aim of this paper is to introduce a dynamic Kc approach, based on Leaf Area Index (LAI) observations, for improving water balance computations. Soil moisture and meteorological data were collected in a terraced nectarine (Prunus persica var. nucipersica) orchard in Cyprus, from 22 March 2019 to 18 November 2021. The Kc was derived as a function of the canopy cover fraction (c), from biweekly in situ LAI measurements. The use of a dynamic Kc resulted in Kc estimates with a bias of 17 mm and a mean absolute error of 0.8 mm. Evapotranspiration (ET) ranged from 41% of the rainfall (P) and irrigation (I) in the wet year (2019) to 57% of P + I in the dry year (2021). Drainage losses from irrigation (DR_I) were 44% of the total irrigation. The irrigation efficiency in the nectarine field could be improved by reducing irrigation amounts and increasing the irrigation frequency. Future studies should focus on improving the dynamic Kc approach by linking LAI field observations with remote sensing observations and by adding ground cover observations.

Abstract: Quantifying evapotranspiration and drainage losses is essential for improving irrigation efficiency. The FAO-56 is the most popular method for computing crop evapotranspiration. There is, however, a need for locally derived crop coefficients (Kc) with a high temporal resolution to reduce errors in the water balance. The aim of this paper is to introduce a dynamic Kc approach, based on Leaf Area Index (LAI) observations, for improving water balance computations. Soil moisture and meteorological data were collected in a terraced nectarine (Prunus persica var. nucipersica) orchard in Cyprus, from 22 March 2019 to 18 November 2021. The Kc was derived as a function of the canopy cover fraction (c), from biweekly in situ LAI measurements. The use of a dynamic Kc resulted in Kc estimates with a bias of 17 mm and a mean absolute error of 0.8 mm. Evapotranspiration (ET) ranged from 41% of the rainfall (P) and irrigation (I) in the wet year (2019) to 57% of P + I in the dry year (2021). Drainage losses from irrigation (DR_I) were 44% of the total irrigation. The irrigation efficiency in the nectarine field could be improved by reducing irrigation amounts and increasing the irrigation frequency. Future studies should focus on improving the dynamic Kc approach by linking LAI field observations with remote sensing observations and by adding ground cover observations.