Abstract
The appropriate management of water resources in the world is a policy that can be used in the line of optimum water consumption. One of these management instructions is optimum designing of canal sections for transferring water in irrigation networks. Since water losses in an irrigation network include seepage and evaporation losses, and regarding that the seepage losses depends on the geometry of canal and evaporation losses depends on the free water level, the designing of canal section will be done with the minimum water loss which include minimizing the seepage and evaporation from the canal under uniform flow. Until now, the optimum designing has been done based on relations some of which have high errors in exact estimation of seepage value, so it is necessary to apply a more exact method in optimization process for estimating the seepage value in canal. In this study, the canal seepage value for different states have been modeled by using SEEP/W software package, then the most appropriate soft model have been extracted between the input data (the geometry of canal and the technical characteristics of the bed soil) and output data (seepage). The extracted soft model had been compared to other experimental relations of seepage estimation, and beside confirming its high exactness in estimating seepage compared to other methods, it also have been used as a more efficient method for estimating seepage in optimization process with the aim of minimizing water losses in canals. In the proposed structure, Manning equation has been introduced as the major constraint, allowed minimum velocity, and Froude number as the minor constraint of the problem. The results of this study have been presented in form of dimensionless diagrams that made it possible to design the canal’s dimensions simply. Investigating the results of present study and previously conduced researches indicate the significant changes of canal’s optimum dimension in the present study compared to other researches due to using the proposed method for estimating the seepage.
Similar content being viewed by others
Notes
Acoustic Doppler Current Profilers
References
Adarsh S, Sahana AS (2013) Minimum cost design of irrigation canals using probabilistic global search Lausanne. Arab J Sci Eng 38(10):2631–2637
Bahramlou R (2011) Evaluation of seepage losses in irrigation stone-lined canals in cold regions and its effect on water resources (Case study in Hamedan Province). Iranian Water Res J 5(9):141–150 (In persion)
Bahramlou R (2012) Effect of Concrete Lining on seepage losses from irrigation canals of Hamedan Province. Iranian Water Res J 6(11):75–83 (In persion)
Chahar B (2007a) Optimal design of a special class of curvilinear bottomed canal section. J Hydraul Eng ASCE 133(5):571–576
Chahar BR (2007b) Analysis of seepage from polygon channels. J Hydraul Eng ASCE 133(4):451–460
Ghazaw Y (2011) Design and analysis of a canal section for minimum water loss. Alexandria Eng J 50(4):337–344
Ghobadian R, Khalaj M (2012) Numerical estimating of earth canal seepage in Nzloo area of Uromye Province and correction of empirical relation constant coefficient. J Water Soil 26(1):193–202 (In persion)
Goh ATC, Goh SH (2007) Support vector machines: their use in geotechnical engineering as illustrated using seismic liquefaction data. Comput Geotech 34(5):410–421
Heidarizadeh M (2008) Compare the results of usage the empirical and theory equations to estimate seepage from canals of Roudasht of Esfahan, the first conference on comprehensive management of zayandehrod watershed, Esfahan, (In persion)
Jang JSR (1993) ANFIS: adaptive-network based fuzzy inference systems. IEEE trans. On systems. Management Cybernetics 23(3):665–685
Kinzli KD, Martinez M, Oad R, Prior A, Gensler D (2010) Using an ADCP determine canal seepage loss in an irrigation district. Agric Water Manage 97:801–810
Kraatz DB (1977) Irrigation Canal lining. FAO Land and Water Development Series, No. 1, Rome, p 199
Mohammad Rezapour Tabari M, Eilbeigi M (2014) Auto-calibration of aquifer parameters using aquifer distributed mathematical models and direct searching algorithm. J Water Wastewater 25(91):98–109 (In persion)
Mohammad Rezapour Tabari M, Ebadi T, Maknoon R (2010) Development of a smart model for groundwater level prediction based on aquifer dynamic conditions. J Water Wastewater 21(76):70–80 (In persion)
Mohammad Rezapour Tabari M, Tavakoli S, Mazak Mari M (2014) Optimal design of concrete canal section for minimizing costs of water loss, lining and earthworks. Water Resources Management, Springer 28(10):3019–3034
Nouri Mohammadiyeh M, Sohrabi T, Rahimi H (2010) Modification of empirical equation of seepage in Erath Canals (Case Study: Ghazvin Plain). Iranian Water Res J 4(7):125–128 (In persion)
Pognant D, Canone D, Previati M, Ferraris S (2013) Using EM equipment to verify the presence of seepage losses in irrigation canals. Procedia Environ Sci 19:836–845
Rostamian R, Abedi Koupai J (2012) To estimate seepage from earth canals (case study: irrigation network of downstream Zayandehrud). Water Soil Sci (J Sci Technol Agric Natural Resources) 15(58):13–22
Salemi HR, Sepaskhah AR (2006) Modification of empirical equation of water seepage from Canal in Rodasht of Esfahan Zone. J Sci Technol Agric Natural Resources 10(1):29–42, In persion
Senthil Kumar AR, Goyal MK, Ojha CSP, Singh RD, Swamee PK, Nema RK (2013) Application of ANN, fuzzy logic and decision tree algorithms for the development of reservoir operating rules. Water Resour Manag 27(3):911–925
Sohrabi TM, Rahimi H, Salamat AR (2005) Performance evaluation of conveyance and distribution canals in Gilan and Foumanat irrigation network. J Agric Natural Resource 12(1):71–81 (In persion)
Swamee PK, Kashyap D (2001) Design of minimum seepage loss non-polygonal canal sections. J Irrigation Drainage Eng, ASCE 127(2):113–117
Swamee P, Mishra G, Chahar B (2000) Design of minimum seepage loss canal sections. J Irrig Drain Eng 126(1):28–32
Swamee P, Mishra G, Chahar B (2002) Design of minimum water-loss canal sections. J Hydraul Res 40(2):215–220
Tayfur G, Nadiri AA, Moghaddam AA (2014) Supervised intelligent committee machine method for hydraulic conductivity estimation. Water Resour Manag 28(4):1173–1184
Vapnik VN (1998) Statistical learning theory. John Wiley, New York
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Mohammad Rezapour Tabari, M., Mazak Mari, M. The Integrated Approach of Simulation and Optimization in Determining the Optimum Dimensions of Canal for Seepage Control. Water Resour Manage 30, 1271–1292 (2016). https://doi.org/10.1007/s11269-016-1225-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11269-016-1225-x