Simulating the effect of spatial wind changes on evaporation with CE-QUAL-W2 integrated model and Bowen ratio

Document Type : Complete scientific research article

Authors

1 Ph.D. Student, Dept. of Hydrology and Water Resources, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.

2 . Corresponding Author, Associate Prof., Dept. of Hydrology and Water Resources, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.

3 Assistant Prof., Dept. of Civil Engineering, Jundi-Shapur University of Technology, Dezful, Iran.

Abstract

Background and objectives: The wind, as one of the most effective factors on evaporation from the surface of water sources, such as reservoirs of dams, plays a significant role in estimating the volume of losses due to evaporation and thus protecting water resources. However, in most evaporation estimation methods, such as experimental relationships, evaporation pans, and even new methods such as the use of satellite images, wind is considered as a constant parameter. The wind parameter has a spatial distribution under the influence of the elevations overlooking the lake and water levels. On the other hand, simulating the spatial changes of the wind and investigating its effect on evaporation, as one of the factors affecting the water cycle, is time-consuming and difficult due to the complexity of the calculations. Failure to apply wind location changes will reduce the accuracy of the calculated evaporation and as a result, it will be difficult to access the exact amount of evaporation losses.
Materials and methods: In this study, to calculate the effect of spatial changes of wind on evaporation losses from the Dez Dam reservoir located in Khuzestan province and the southwest of Iran, the combination of the CE-QUAL-W2 model and Bowen Ratio Energy Budget (BREB) method was used. The wind shelter coefficient (WSC) as one of the input parameters to the CE-QUAL-W2 model, makes it possible for the model to consider the wind shelter condition in different segments of water bodies differently. However, due to the lack of access to a suitable criterion to show the wind shelter condition in different segments, before this research, the value of WSC was considered constant in all or large parts of the water body. In this study, CE-QUAL-W2 model capability was used for reservoir segmentation, and wind shelter condition was determined in each segment, using the wind shelter index (Sx). Therefore, it was possible to assign different WSC values in each segment. In this way, the thermal profiles in each of these segments, under the influence of two conditions of constant and variable wind (constant and variable WSC), were extracted and entered into the BREB method to calculate evaporation.
Results: The results showed that the application of spatial wind changes compared to constant wind conditions, improved the performance of the CE-QUAL-W2 model by 45% in the temperature calibration stage. Also, the monthly evaporation from the lake increased by 13%.
Conclusion: This study, introduced a standardized method for simulating the effect of spatial wind changes on evaporation from water surfaces. So that, it was possible to quantify the effect of wind on evaporation and as a result water losses from the lake, by comparing two conditions of variable and constant wind, in different segments of the studied lake.

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References

1.Hashemi Monfared, A., Rezapour, M., Rezapour, H., & Azhdary Moghaddam, M. (2019). Determination of the Optimum Angle of the Floating Solar Panels to Reduce Evaporation and Energy Production by the Ansys Fluent Model (Case Study: Chahnimeh No. 4 Sistan). Iranian Journal of Eco Hydrology, 5 (4), 1297-1307. [In Persian]2.He, W., Lian, J., Yao, Y., Wu, M., & Ma, Ch. (2017). Modeling the effect of temperature-control curtain on the thermal structure in a deep stratified reservoir. Journal of Environmental Management, 202 (1), 106-116. doi: 10.1016/j.jenvman.2017.07.006. 3.Hojjati, E., Mahtabi, G., Taran, F., & Kisi, O. (2021). Estimating evaporation from reservoirs using energy budget and empirical methods: Alavian dam reservoir, NW Iran. Italian Journal of Agrometeorology, 2, 19-34. doi: 10. 13128/ijam-1033.4.Jhajharia, D., Shrivastava, S. K., Sarkar, D., & Sarkar, S. (2019). Temporal characteristics of pan evaporation trends under the humid conditions of northeast India. Journal of Agricultural and Forest Meteorology, 149 (5), 763-770. doi: 10.1016/j.agrformet.2008.10.024.5.Li, Z., Wang, S., & Li, J. (2020). Spatial variations and long‑term trends of potential evaporation in Canada. Journal of Scientific Reports, 22089, 1-13. doi: 10.1038/s41598-020-78994-9. 6.Burn, D. H., & Hesch, N. M. (2007). Trends in evaporation for the Canadian Prairies. Journal of Hydrology, 336 (1-2), 61-73. doi: 10.1016/j.jhydrol. 2006.12.011.7.Chinyepe, A. (2010). Satellite Remote Sensing of Surface water evaporation over Lake Mutirikwi, Zimbabwe. M.Sc. Thesis, Faculty of Engineering, Zimbabwe University, Zimbabwe, 212.8.El-Magd, I. H. A., & Elham, M. A. (2011). Estimation of the evaporative losses from Lake Nasser, Egypt using optical satellite imagery. International Journal of Digital Earth, 5 (2), 133-146. doi: 10.1080/17538947.2011.586442. 9.Hassan, H., Ismail, Sh. S., Elmoustafa, A., & Khalaf, Sh. (2018). Evaluating evaporation rate from high Aswan Dam Reservoir using RS and GIS techniques. The Egyptian Journal of Remote Sensing and Space Science, 21 (3), 285-293. doi: 10.1016/j.ejrs.2017.10.001.10.Imam Dost, Sh., Shahanzari, A., & Taghavi, J. (2019). Determination of Evaporation from Free Surface Water in Mazandaran Plain (Dazmirkandeh Abbandan) and Compared with Seven Experimental Methods. Journal of Watershed Management Research, 9 (18), 241-249. [In Persian]11.Najafvand Darikvandi, M., & Eslami, H. (2016). Empirical methods Comparison of estimation evaporation From Free Water Surface (Case Study: Dez Regulatory Dam). Journal of Water Engineering, 4 (2), 65-73.12.Rahimpour, M., & Rahimzadegan, M. (2021). Assessment of surface energy balance algorithm for land and operational simplified surface energy balance algorithm over freshwater and saline water bodies in Urmia Lake Basin. Journal of Theoretical and Applied Climatology, 143 (3-4), 1457-1472.
doi: 10.1007/s00704-020-03472-1. 13.Zamani, S., & Rahimzadegan, M. (2018). Evaluation of SEBS, SEBAL, and METRIC models in estimation of the evaporation from the freshwater lakes (Case study: Amirkabir dam, Iran). Journal of Hydrology, 561, 523-531. doi: 10.1016/j.jhydrol.2018.04.025. 14.Ziaie, R., Mohammadnezhad, B., Taheriyoun, M., Karimi, A., & Amiri, S. (2019). Evaluation of Thermal Stratification and Eutrophication in Zayandeh Roud Dam Reservoir Using Two-Dimensional CE-QUAL-W2 Model. Journal of Environmental Engineering, 145 (6), 1-13. doi: 10.1061/ (ASCE) EE.1943-7870.0001529. 15.Abd-Elhamid, F., Ahmad, A., Zelenakova, M., Vranayova, Z., & Fathy, I. (2021). Reservoir Management by Reducing Evaporation Using Floating Photovoltaic System: A Case Study of Lake Nasser, Egypt. Journal
of Water, 13 (6), 769. doi: 10.3390/ w13060769. 16.Ebaid, H., & Ismail, S. (2010). Lake Nasser evaporation reduction study. Journal of Advanced Research, 1 (4), 315–322. doi: 10.1016/j.jare. 2010.09.002. 17.Xu, C., Gong, L., Jiang, T., Chen, D., & Singh, V. P. (2006). Analysis of spatial distribution and temporal trend of reference evapotranspiration and pan evaporation in Changjiang (Yangtze River) catchment. Journal of Hydrology, 327, 81-93. doi: 10.1016/j.jhydrol. 2005.11.029. 18.Sharifi, M. R., & Shahi, Z. (2020). Assessment of wind shelter conditions of an open water storage reservoir using wind shelter index. Journal of Lake and Reservoir Management, 37 (3), 1-13. doi: 10.1018/10402381.2020.1836094.19.Seemann, S. W., Li, J., Menzel, W. P., & Gumley, L. E. (2003). Operational Retrieval of Atmospheric Temperature, Moisture, and Ozone from MODIS Infrared Radiances. Journal of Applied Meteorology and Climatology, 42 (8), 1072-1091. doi: 10.1175/1520-0450(2003)042<1072:OROATM>2.0.CO; 2.20.Afshar, A., Kazemi, H., & Saadatpour, M. (2011). Particle swarm optimization for automatic calibration of large scale water quality model (CEQUAL- W2): application to Karkheh reservoir, Iran. Journal of Water Resource Management, 25 (10), 2613-2632. doi: 10.1007/s11269-011-9829-7.21.Feizi, F., Afshar, A., Saadatpour, M., & Faraji, E. (2015). Modifying the
CE-QUAL-W2 Model to Simulate Volatile Organic Compounds in River-Reservoir Systems. Journal of Water and Wastewater, 26 (5), 35-47. [In Persian]22.Khajepour, M. E., Eghbalzadeh, A., Shiasi Arani, M., Eftekhari, M., & Javan, M. (2014). Comparison of CE-QUAL-W2 and Dyresm Models in Simulating Heat Distribution Within 15 Khordad Reservoir. Journal of Water and Soil (Agricultural Sciences and Technology), 28 (2), 343-352. [In Persian]23.Kim, Y., & Kim, B. (2006). Application of a 2-Dimensional Water Quality Model (CE-QUAL-W2) to the Turbidity Interflow in a Deep Reservoir (Lake Soyang, Korea). Journal of Lake and Reservoir Management, 22 (3), 213-222. doi: 10.1080/07438140609353898.24.Saadatpour, M. (2020). An Adaptive Surrogate Assisted CE-QUAL-W2 Model Embedded in Hybrid NSGA-II_ AMOSA Algorithm for Reservoir Water Quality and Quantity Management. Journal of Water Resources Management, 34 (2), 1437-1451. doi: 10.1007/s11269-020-02510-x.25.Saadatpour, M., & Afshar, A. (2005). Temperature calibration in reservoirs with genetic algorithm. In: 2th national water resources management conference, Iran, Isfahan, 23-24 January. [In Persian]26.Saeidi, P., Mehrdadi, N., Ardestani, M., & Baghvand, A. (2014). Simulation of thermal stratification and dissolved oxygen concentrations using CE-QUAl-W2 model (Case study: Shahid Rajaei Dam). Journal of Environmental Studies, 39 (4), 171-180. doi: 10.22059/jes.2014.36470. [In Persian]27.Esmaeilzadeh Hanjani, A., Sarai Tabrizi, M., & Babazadeh, H. (2023). Numerical Modelling of Thermal Stratification in Dam Reservoir Using CE-QUAL-W2 Model (Case study: Yamchi Dam). Journal of Water Resources Engineering, 16 (58), 101-114. doi: 10.30495/WEJ.2023.30480.2358. [In Persian]28.Esmaeilzadeh Hanjani, A., Sarai Tabrizi, M., & Babazadeh, H. (2023). Dissolved oxygen concentration and eutrophication evaluation in Yamchi dam reservoir, Ardabil, Iran. Journal of Applied Water Science, 13 (518), 2-12. doi: 10.1007/s13201-022-01786-1.29.Khodabandeh, F., Dehghani Darmian, M., Azhdary Moghaddam, M., & Hashemi Monfared, S. A. (2021). Reservoir quality management with CE-QUAL-W2/ANN surrogate model and PSO algorithm (case study: Pishin Dam, Iran). Arabian Journal of Geosciences, 14 (5), 401. doi: 10.1007/s12517-021-06735-x.30.Lindenschmidt, K. E., Carr, M. K., Sadeghian, A., & Morales-Marin, L. (2019). CE-QUAL-W2 model of dam outflow elevation impact on temperature, dissolved oxygen and nutrients in a reservoir. Journal of Scientific Data, 6 (312), 1-6. doi: 10.1038/s41597-019-0316-y.31.Salehi, M., Khani Temeliyeh, Z., Parchami, N., & Ahmadpour, Z. (2019). Numerical Modeling of Thermal Stratification and Water Quality in Reservoir By CE-QUAL-W2 Model. Journal of Water and Soil conservation, 26 (4), 53-73. doi: 10.22069/ JWSC. 2019.14971.3010. [In Persian]32.Shabani, A., Zhang, X., Chu, X., & Zheng, H. (2021). Automatic Calibration for CE-QUAL-W2 Model Using Improved Global-Best Harmony Search Algorithm. Journal of Water, 13 (16), 2-15. doi: 10.3390/w13162308.33.Terry, J., & Lindenschmidt, K. E. (2023). Water quality and flow management scenarios in the qu’Appelle river–reservoir system using loosely coupled WASP and CE-QUAL-W2 models. Journal of Water, 15 (11), 2005.  doi: 10.3390/w15112005.34.Tavera-Quiroz, H., Rosso-Pinto, M., Hernandez, G., Pinto, S., & Canales, F. A. (2023). Water quality Analysis of a tropical reservoir based on temperature and dissolved oxygen modeling by CE-QUAL-W2. Journal of Water, 15 (6), 1-18. doi: 10.3390/w15061013.35.Vanda, S., Nikoo, M. R., Taravatrooy, N., Al-Rawas, G. A., Sadr, S., Memon, F., & Nematollahi, B. (2023). A novel compromise approach for risk-based selective water withdrawal from reservoirs considering qualitative-quantitative aspects. Journal of Water Resources Management, 37 (12), 4861-4879. doi: 10.1007/s11269-023-03584-z. 36.dos Reis, R., & Dias, N. (1998). Multi-season lake evaporation: energy budget estimates and CRLE model assessment with limited meteorological observations. Journal of Hydrology, 208 (3-4), 135-147. doi: 10.1016/S0022-1694(98)00160-7.37.Sacks, L., Lee, T., & Radell, M. (1994). Comparison of energy budget evaporation losses from two morphometrically different Florida seepage lakes. Journal of Hydrology, 156 (1-4), 311-334. doi: 10.1016/0022-1694(94)90083-3.38.Sturrock, A., Winter, T., & Rosenberry, D. (1992). Energy budget evaporation from Williams Lake: a closed lake in north central Minnesota. Journal of Water Resources Research, 28 (6), 1605-1617. doi: 10.1029/92WR00553.39.Winter, T. C., Buso, D. C., Rosenberry, D. O., Likens, G. E., Sturrock, A. M. J., & Mau, D. P. (2003). Evaporation determined by the energy budget method for Mirror Lake, New Hampshire. Limnology and Oceanography. 48 (3), 995-1009. doi: 10.4319/lo.2003. 48.3.0995.40.Acharya, B., & Sharma, V. (2021). Comparison of Satellite Driven Surface Energy Balance Models in Estimating Crop Evapotranspiration in Semi-Arid to Arid Inter-Mountain Region. Journal of Remote Sensing, 13 (9), 1822. doi: 10.3390/rs13091822.41.Bozorgi, A., Bozorg-Haddad, O., Sima, S., & Loaiciga, H. A. (2020). Comparison of methods to calculate evaporation from reservoirs. International Journal of River Basin Management, 18 (1), 1-12. doi: 10. 1080/15715124.2018.1546729.42.Gorjizade, A., Akhond-Ali, A. M., Zarei, H., & Seyyed Kaboli, H. (2014). Evaluation of Eight Evaporation Estimation Methods in a Semi-Arid Region (Dez reservoir, Iran). International Journal of Advanced Biological and Biomedical Research, 2 (5), 1823-1836. doi: 10.13140/RG.2. 1.4700.1122.43.Hussain, M. M. A. (2017). Evaporation and Evaluation of Seven Estimation Methods: Results from Brullus Lake, North of Nile Delta, Egypt. Journal of Atmospheric and Oceanic Sciences, 2 (3), 66-74. doi: 10.11648/j.hyd. 20170504.12.44.Lenters, J., Kratz, T., & Bowser, C. (2005). Effects of climate variability on lake evaporation: results from a long-term energy budget study of Sparkling Lake, northern Wisconsin (USA). Journal of Hydrology, 30 (1-4), 168-195. doi: 10.1016/j.jhydrol.2004.10.028.45.Majidi, M., Alizadeh, A., Farid, A., & Vazifedoust, M. (2015). Estimating Evaporation from Lakes and Reservoirs under Limited Data Condition in a Semi-Arid Region. Journal of
Water Resources Management, 29 (10), 3711-3733. doi: 10.1007/ s11269-015-1025-8.46.Omar, M. H., & El-Bakry, M. M. (1981). Estimation of Evaporation from The Lake of the Aswan High Dam (Lake Nasser) Based on Measurements Over the Lake. Journal of Agricultural Meteorology, 23, 293-308. doi: 10.1016/ 0002-1571(81)90115-1. 47.Rosenberry, D. O., Stannard, D. I., Winter, T. C., & Martinez, M. L. (2004). Comparison of 13 equations for determining evapotranspiration from a prairie wetland, Cottonwood Lake area, North Dakota, USA, Wetlands. 24 (3), 483-497. doi: 10.1672/0277-5212 (2004)024[0483:COEFDE]2.0.CO;2.48.En-nkhili, H., Nizar, I., Igouzal, M., Touazit, A., Youness, N., & Etebaai, I. (2023). Artificial neural network and energy budget method to predict daily evaporation of Boudaroua reservoir (northern Morocco). Journal Water and Land Development, 57, 107-115. doi: 10.24425/jwld.2023.145341. 49.Cole, T. M., & Wells, S. A. (2015). CE-QUAL-W2: A two-dimensional, laterally averaged, hydrodynamic and water quality model, version 3.72. Depart of Civil and Environ Eng, Portland State University, Portland, OR, 1-680.50.Kazemi Alamooti, H., Afshar, A., & Saadatpour, M. (2012). Automatic Thermal Calibration of Two Dimensional CE-QUAL-W2 Model in Karkheh Reservoir Applying Particle Swarm Optimization Algorithm. Journal of Water and Wastewater, 23 (4), 2-12. [In Persian]51.Khodadadi, N., & Zakermoshfeqh, M. (2018). Two-dimensional modeling of thermal stratification and water quality of Karkheh reservoir. Conference on Civil Engineering, Architecture and Urban Planning of the Islamic World. https:// civilica.com/ doc/775314/.[In Persian]52.Winstral, A., Elder, K., & Davis, R. E. (2002). Spatial snow modeling of wind-redistributed snow using terrain based parameters. Journal of Hydrometeorology, 3 (5), 524-538. doi: 10.1175/1525-7541(2002)003< 0524: SSMOWR>2.0.CO;2. 53.Shahi, Z., & Sharifi, M. R. (2018). An Algorithm for Selecting the Effective Distance of the Wind Shelter to Verify the Wind Shelter Status at the Lake Level of Dams (Case Study: Lake of Dez Reservoir Dam). Journal of Irrigation Sciences and Engineering, 41 (1), 211-223. doi: 10.22055/ JISE. 2018.23774.1697. [In Persian]54.Antonopoulos, V. Z., Gianniou, S. K., & Antonopoulos, A. V. (2016). Artificial neural networks and empirical equations to estimate daily evaporation: application to lake Vegoritis, Greece. Hydrological Sciences Journal, 61 (14), 1-27. doi: 10.1080/ 02626667. 2016.1142667.55.Gianniou, S. K., & Antonopoulos, V. Z. (2007). Evaporation and energy budget in Lake Vegoritis, Greece. Journal of Hydrology, 351 (3), 212-223. doi: 10.1016/j.jhydrol.2007.08.007.
Journal of Water and Soil Conservation
Volume 31, Issue 1
April 2024
Pages 133-152

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