Introducing affordable and accessible physical covers to reduce evaporation from agricultural water reservoirs and pools (field study, statistics, and intelligent methods)
Abstract:Nowadays, a major part of the stored surface water resources is wasted by evaporation. By implementing low-cost methods to prevent water evaporation, it is possible to return this part of water to the agricultural, industrial, and drinking cycles. The present study aimed to evaluate the effect of polystyrene (compressed foam), pieces of wood, and synthetic beeswax cover with different surface coverage of 60%, 70%, and 80% in the standard Colorado Sunken evaporation pan on the evaporation rate. The materials us… Show more
“…Figure 10 compares the changes of the parameters received from Semnan meteorological station including minimum temperature (Celsius), maximum temperature (Celsius), maximum humidity (percentage), minimum humidity (percentage), sunlight hours, pressure (hectopascal) and wind speed (meters per second) on test days; it also shows the rate of evaporation from the CASEP and CSSEP (mm) (Ghazvinian et al, 2021). From the obtained results, it can be deduced that wind speed and temperature are at their lowest correlation with the ER.…”
Section: Casep Cssepmentioning
confidence: 99%
“…The results showed that the ER from the MDF-containing pan was 91% lower than that of the CSSEP. Ghazvinian et al (2021) went on to place various coatings such as polystyrene, wood, and synthetic honey wax on the CSSEP, where they measured the evaporation and compared the ER from the control pan with the pan containing the coatings. The results showed that the rate of evaporation in the pan containing polystyrene was less than the evaporation in other pans and the control pan.…”
One method of estimating the evaporation rate (ER) is to use a variety of evaporation pans, such as the Class A standard evaporation pan (CASEP) and the Colorado Sanken standard evaporation pan (CSSEP). In this study, the rate of evaporation of CASEP and CSSEP have been investigated and compared with each other. This study was conducted in Semnan, Iran. CSSEP was used as a test pan, which was performed in an open space around the Faculty of Civil Engineering, Semnan University. Evaporation was recorded daily for 123 days. The evaporation of the CASEP pan was obtained from the synoptic station of Semnan, which is located at a distance of 2.39 km from the test site. Meteorological data were also obtained from the synoptic station of Semnan and compared with experimental evaporation data. The results of this study showed that the daily ER from CASEP and CSSEP in the tested time periods were not significantly different. Based on the Klomogorov-Sminrov method, the best statistical distributions for CASEP and CSSEP were calculated as Error and Gamma, respectively. The coefficient of determination (R 2 ) between the two pans was estimated to be about 93%. Also, by examining the ER with other meteorological data, it was observed that the ER has the highest correlation with the average daily air temperature.
“…Figure 10 compares the changes of the parameters received from Semnan meteorological station including minimum temperature (Celsius), maximum temperature (Celsius), maximum humidity (percentage), minimum humidity (percentage), sunlight hours, pressure (hectopascal) and wind speed (meters per second) on test days; it also shows the rate of evaporation from the CASEP and CSSEP (mm) (Ghazvinian et al, 2021). From the obtained results, it can be deduced that wind speed and temperature are at their lowest correlation with the ER.…”
Section: Casep Cssepmentioning
confidence: 99%
“…The results showed that the ER from the MDF-containing pan was 91% lower than that of the CSSEP. Ghazvinian et al (2021) went on to place various coatings such as polystyrene, wood, and synthetic honey wax on the CSSEP, where they measured the evaporation and compared the ER from the control pan with the pan containing the coatings. The results showed that the rate of evaporation in the pan containing polystyrene was less than the evaporation in other pans and the control pan.…”
One method of estimating the evaporation rate (ER) is to use a variety of evaporation pans, such as the Class A standard evaporation pan (CASEP) and the Colorado Sanken standard evaporation pan (CSSEP). In this study, the rate of evaporation of CASEP and CSSEP have been investigated and compared with each other. This study was conducted in Semnan, Iran. CSSEP was used as a test pan, which was performed in an open space around the Faculty of Civil Engineering, Semnan University. Evaporation was recorded daily for 123 days. The evaporation of the CASEP pan was obtained from the synoptic station of Semnan, which is located at a distance of 2.39 km from the test site. Meteorological data were also obtained from the synoptic station of Semnan and compared with experimental evaporation data. The results of this study showed that the daily ER from CASEP and CSSEP in the tested time periods were not significantly different. Based on the Klomogorov-Sminrov method, the best statistical distributions for CASEP and CSSEP were calculated as Error and Gamma, respectively. The coefficient of determination (R 2 ) between the two pans was estimated to be about 93%. Also, by examining the ER with other meteorological data, it was observed that the ER has the highest correlation with the average daily air temperature.
Wheat plays a vital role in the food security of society, and early estimation of its yield will be a great help to macro-decisions. For this purpose, wheat yield and water productivity (WP) by considering soil data, irrigation, fertilizer, climate, and crop characteristics and using a novel hybrid approach called hazelnut tree search algorithm (HTS) and extreme machine learning method (ELM) was examined under the drip (tape) irrigation. A dataset including 125 wheat yield data, irrigation and meteorological data of Mahabad plain located southeast of Lake Urmia, Iran, was used as input parameters for crop year 2020–2021. Eighty percentage of the data were used for training, and the remaining 20% for model testing. Nine different input scenarios were presented to estimate yield and WP. The efficiency of the proposed model was calculated with the statistical indices coefficient of determination (R2), root-mean-square error (RMSE), normalized root-mean-square error, and efficiency criterion. Sensitivity analysis result showed that the parameters of irrigation, rainfall, soil moisture, and crop variety provide better results for modeling. There was good agreement between the practical values (field management data) and the estimated values with the HTS–ELM model. The results also showed that the HTS–ELM method is very efficient in selecting the best input combination with R2 = 0.985 and RMSE = 0.005. In general, intelligent hybrid methods can enable optimal and economical use of water and soil resources.
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