Reliability Analysis of Rainwater Harvesting Tanks for Irrigation Use in Greenhouse Agriculture

Abstract

Rainwater harvesting is an ancient water management practice that has been used to cover potable and non-potable water needs. In recent years, this practice is adopted as a promising alternative and sustainable source of water to meet irrigation needs in agriculture in arid and semi-arid regions. In the present study, a daily water balance model was applied to investigate the size of rainwater tanks for irrigation use in greenhouse begonia and tomato cultivation in two regions of Greece with significant greenhouse areas. For the application of the water balance model, daily rainfall depth values of a 12-year time series (2008–2020) from representative rainfall stations of the study areas were used, as well as the daily water needs of the crops. The greenhouse roof was assumed to be the water collection area of the rainwater harvesting system with values ranging from 1000 to 10,000 m2. The analysis of the results showed that in the case of the begonia crop, the covered tanks ranged from 100 to 200 m3 per 1000 m2 greenhouse area with a reliability coefficient that ranged from 65 to 72%, respectively, to meet the water needs of plants. Further increase of the reliability coefficient was carried out with disproportionately large volumes of tanks. In the case of the tomato crop, covered tank volumes ranged from 100 to 290 m3 per 1000 m2 of greenhouse area, and had a reliability coefficient of 90% to 100%, respectively, while uncovered tanks had a maximum reliability coefficient of 91% for a critical tank volume of 177 m3 per 1000 m2 of greenhouse area and decreased for any further increase of tank volume.

Effect of Rainfall Regime on Rainwater Harvesting Tank Sizing for Greenhouse Irrigation Use

“…For sizing the rainwater harvesting tanks to meet the irrigation needs of tomato crops in greenhouses, a daily water balance model reported by Londra et al [11] was applied. Specifically, the model takes into consideration the daily rainfall and evaporation data, the greenhouse rooftop (as the catchment area for rainwater) and its runoff coefficient, the tank volume, and the irrigation needs.…”

“…Specifically, the model takes into consideration the daily rainfall and evaporation data, the greenhouse rooftop (as the catchment area for rainwater) and its runoff coefficient, the tank volume, and the irrigation needs. The model is described by the following equation [11]:…”

“…In contrast, Boyaci and Kartal [10], in their study in Kırşehir province (Turkey) with low annual rainfall (i.e., 388.3 mm), presented that 61.49% and 47.74% of the tomato crop irrigation needs in heated and unheated greenhouses, respectively, could be met by tanks with capacities of 0.21 and 0.30 m 3 /m 2 , respectively. Londra et al [11] studied the reliability of rainwater tanks to meet the irrigation needs of begonia and tomato crops in two regions of Greece with low annual rainfall (419 mm and 448 mm). They found that 65 to 72% of the irrigation needs of the begonia crop during a 12-month growing season could be met by covered tanks 100 to 200 m 3 per 1000 m 2 greenhouse area, respectively.…”

“…Considering that the size of rainwater tanks is strongly influenced by the local weather conditions of the region where the tanks will be established [12][13][14][15][16], the local characteristics related to the greenhouse and rainwater tank infrastructure, and the cultivated crops and their irrigation needs, the application of an appropriate daily water balance model for determining the tank size is needed [11].…”

Is Greenhouse Rainwater Harvesting Enough to Satisfy the Water Demand of Indoor Crops? Application to the Bolivian Altiplano

“…We have included the most relevant parameters that affect the water balance, which are: precipitation, the runoff coefficient of greenhouse roofs, frequency and volume of irrigation, the maximum capacity of the water tank used as storage, and crop factors. Unlike other studies, which use monthly mean accumulated rainfall [36,50], here, we simulate the balance at daily scale, which better captures the impact of extreme rainfall episodes [51,52]. Our analysis has evaluated the influence of the above parameters in the percentage of satisfied water demand and the volume of water loss for each simulation type and greenhouse.…”