Evaporation control from the water surface using silica nanostructure material (Case study: Karkheh Dam Lake)

Document Type : Research Article


1 MSc. In Echohydrology, College of Interdisciplinary Science and Technology, University of Tehran, Iran

2 College of Interdisciplinary Science and Technology, University of Tehran, Iran



Due to global warming and the increase in the population of the planet, maintaining and protecting available water resources is very important. One of the factors that has caused the reduction of water resources today is the increase in the rate of evaporation from the level of water stored in water resources. In this study, using the experimental results obtained from the work of Sina Bashir et al., the evaporation rate of the lake behind the Karkheh Dam has been modeled. This modeling has been done using the neural-adaptive fuzzy inference system. The approach of this system is considered the Mamdani approach in this modeling because this approach has a very good performance in modeling dynamic and natural processes such as evaporation. According to the laboratory results, in the presence of silica nanostructured material at 28, 32 and 40 degrees Celsius and wind conditions of 4 meters per second (similar to the prevailing wind around the Karkheh dam), the evaporation rate decreases by 33, 32 and 30%, respectively. In this modeling, the rate of reduction of evaporation is entered into the modeling as a coefficient according to the laboratory results, and as a result, the rate of evaporation obtained is the result of the decrease in the presence of nanostructured material. In this modeling, considering the creation of a nanostructured thermal insulation cover for only 20% of the lake surface, 2 million cubic meters of water can be saved and saved.


Main Subjects

[1].          PILGRIM D. H., CHAPMAN T. G., and DORAN D. G., ‘Problems of rainfall-runoff modelling in arid and semiarid regions’, Hydrological Sciences Journal, vol. 33, no. 4, 1988, doi: 10.1080/02626668809491261.
[2].          ‘(No Title)’. http://cwc.gov.in/sites/default/files/evaporation-control-in-reservoirs.pdf (accessed Jun. 12, 2021).
[3].          Gallego-Elvira B., Baille A., Martín-Gorriz B., Maestre-Valero J. F., and Martínez-Alvarez V., ‘Evaluation of evaporation estimation methods for a covered reservoir in a semi-arid climate (south-eastern Spain)’, J Hydrol (Amst), vol. 458–459, pp. 59–67, Aug. 2012, doi: 10.1016/j.jhydrol.2012.06.035.
[4].          Assouline S., Narkis K., and Or D., ‘Evaporation suppression from water reservoirs: Efficiency considerations of partial covers’, Water Resour Res, vol. 47, no. 7, 2011, doi: 10.1029/2010WR009889.
[5].          Moghiman M. and Aslani B., ‘Influence of nanoparticles on reducing and enhancing evaporation mass transfer and its efficiency’, Int J Heat Mass Transf, vol. 61, no. 1, pp. 114–118, Jun. 2013, doi: 10.1016/j.ijheatmasstransfer.2013.01.057.
[6]. Ahmadian MM. Reduce evaporation of water resources using nanomaterials. Sea Regional Conference, Development and Water Resources of the Persian Gulf. 2014; https://sid.ir/paper/842555/en (in persian)
[7].          Omolbani M. R. P., Zarindast N., Mir N., and Dehghani A. A., ‘Using fe magnetic nanoparticles for reducing evaporation from water surface in small scale’, Desalination Water Treat, vol. 71, pp. 380–387, Apr. 2017, doi: 10.5004/dwt.2017.20178.
[8]. Nejatian AA, Iraji Zad A, Tajrishi M, Dolabi M. Investigating the Impact of Nanometric Coatings on the Evaporation of Lake Chitgar. 6th Regional Climate Change Conference, Tehran. 2019; https://civilica.com/doc /1002676 ( in persian)
[9].          Ghahramani Jajin R., Feizi A., and Ghorbanpour M., ‘Reduction of Water Evaporation from Dam Reservoirs Using Hydrophobic Silverā€Doped Titanium Dioxide Nanoparticles Coating’, Water Resour Res, vol. 57, no. 5, p. e2020WR029231, May 2021, doi: 10.1029/2020wr029231.
[10]. J. Shiri, W. Dierickx, A. Pour-Ali Baba, S. Neamati, and M. A. Ghorbani, “Estimating daily pan evaporation from climatic data of the State of Illinois, USA using adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN),” Hydrology Research, vol. 42, no. 6, pp. 491–502, 2011, doi: 10.2166/nh.2011.020.
[11]. Allawi M. F. and El-Shafie A., “Utilizing RBF-NN and ANFIS Methods for Multi-Lead ahead Prediction Model of Evaporation from Reservoir,” Water Resources Management, vol. 30, no. 13, pp. 4773–4788, Oct. 2016, doi: 10.1007/s11269-016-1452-1.
[12]. Demirci M., Unes F., Kaya Y. Z., Tasar B., and Varcin H., “MODELING OF DAM RESERVOIR VOLUME USING ADAPTIVE NEURO FUZZY METHOD.” [Online]. Available: https://waterdata.usgs.gov/nwis/dv/?referred_module=qw        
[13]. Malik A.et al., “Daily pan-evaporation estimation in different agro-climatic zones using novel hybrid support vector regression optimized by Salp swarm algorithm in conjunction with gamma test,” Engineering Applications of Computational Fluid Mechanics, vol. 15, no. 1, pp. 1075–1094, 2021, doi: 10.1080/19942060.2021.1942990.
[14].        Ghumman A. R. et al., ‘Simulation of pan-evaporation using penman and hamon equations and artificial intelligence techniques’, Water (Switzerland), vol. 13, no. 6, Mar. 2021, doi: 10.3390/w13060793.
[15].        Shahi S., Mousavi S. F., and Hosseini K., ‘Simulation of pan evaporation rate by ANN artificial intelligence model in Damghan region’, Journal of Soft Computing in Civil Engineering, vol. 5, no. 3, pp. 75–87, 2021, doi: 10.22115/SCCE.2021.286933.1321.
[16].        Ashraf Vaghefi S., Mousavi S. J., Abbaspour K. C., Srinivasan R., and Yang H., ‘Analyses of the impact of climate change on water resources components, drought and wheat yield in semiarid regions: Karkheh River Basin in Iran’, Hydrol Process, vol. 28, no. 4, 2014, doi: 10.1002/hyp.9747.
[17].        Deepika S., Osman M., Kumar M., anoranjan & Sandeep H., ‘Suppressing Evaporation from Surface Water Reservoirs: A Review’. Journal of Agricultural Engineering. (2021). 57. 259-273. ‘(PDF) Suppressing Evaporation from Surface Water Reservoirs: A Review’. https://www.researchgate.net/publication/350431860_Suppressing_Evaporation_from_Surface_Water_Reservoirs_A_Review (accessed Jun. 13, 2021).
[18] Bashir S, Seifullah SAD, Rostamian SH. Investigating the Effect of Silica Nano Fluids on Reducing Water Evaporation. Third National Conference on Applied Mechanical Engineering. ; https://civilica.com/doc/1158052/certificate/print/ (in persian)
[19]         Jang J.-S. R., ‘ANFIS: adaptive-network-based fuzzy inference system’, IEEE Trans Syst Man Cybern, vol. 23, no. 3, pp. 665–685, 1993, doi: 10.1109/21.256541.
[20]         Abd-Elhamid H. F., Ahmed A., Zelenakova M., Vranayova Z., and Fathy I., ‘Reservoir management by reducing evaporation using floating photovoltaic system: A case study of lake Nasser, Egypt’, Water (Switzerland), vol. 13, no. 6, p. 769, Mar. 2021, doi: 10.3390/w13060769.