Advertisement

Irrigation Scheduling for Cotton Cultivation

  • Sajjad Hussain
  • Ashfaq Ahmad
  • Aftab Wajid
  • Tasneem Khaliq
  • Nazim Hussain
  • Muhammad MubeenEmail author
  • Hafiz Umar Farid
  • Muhammad Imran
  • Hafiz Mohkum Hammad
  • Muhammad Awais
  • Amjed Ali
  • Muhammad Aslam
  • Asad Amin
  • Rida Akram
  • Khizer Amanet
  • Wajid Nasim
Chapter
  • 43 Downloads

Abstract

Crops need water for evaporation (E) and transpiration (T), known as evapotranspiration (ET). However, too much water is not good for various crops. Crop water need depends on growth stage, climate, and crop type. Approximately 40% cotton is produced under irrigated conditions. Water for irrigation is becoming limited in many cotton-growing regions and competition for water is increasing speedily in areas normally having plentiful water resources. So, many cotton producers and the associations representing cotton producers are interested in the scheduling of irrigation strategies that increase water use efficiency (WUE). Responses of cotton under water stress depend on stage of growth, duration, time, and extent of stress. Cotton is a drought-tolerant crop; however, it performs better under optimum water conditions. The water requirement of cotton is 27–51 acre inches depending upon growing duration and prevailing climatic conditions. However, it is essential to apply uniform and accurate amount of water at proper time for maximum cotton yield. Normally, cotton uses less water from sowing to emergence. However, pre-sowing irrigation is mandatory to ensure good cotton seed germination. After germination, crop water demand increases from 0.2 to 0.44 in. per day. Lack of water can reduce plant growth, the number of fruiting sites because of shedding of young bolls, and boll size, consequently resulting in loss of yield potential. There are various irrigation scheduling tools, the main purpose of which is to supply water according to the need of the plant. Water balance method, estimating crop water use, and sensor-based scheduling are a few important tools to maintain irrigation scheduling in cotton.

Keywords

Water use efficiency Evapotranspiration Irrigation methods Irrigation techniques 

Abbreviations

CO2

Carbon dioxide

CT

Canopy temperature

ET

Evapotranspiration

FDR

Frequency domain reflectometry

GMS

Granular matrix sensors

MIST

Mississippi irrigation scheduling tool

SDI

Subsurface drip irrigation

TDR

Time domain reflectometry

VMC

Volumetric moisture content

WUE

Water use efficiency

References

  1. Abbas Q, Ahmad S (2018) Effect of different sowing times and cultivars on cotton fiber quality under stable cotton-wheat cropping system in southern Punjab, Pakistan. Pak J Life Soc Sci 16:77–84Google Scholar
  2. Ahmad S, Abbas Q, Abbas G, Fatima Z, Atique-ur-Rehman NS, Younis H, Khan RJ, Nasim W, Habib ur Rehman M, Ahmad A, Rasul G, Khan MA, Hasanuzzaman M (2017) Quantification of climate warming and crop management impacts on cotton phenology. Plan Theory 6(7):1–16Google Scholar
  3. Ahmad S, Iqbal M, Muhammad T, Mehmood A, Ahmad S, Hasanuzzaman M (2018) Cotton productivity enhanced through transplanting and early sowing. Acta Sci Biol Sci 40:e34610CrossRefGoogle Scholar
  4. Ahmad S, Raza I (2014) Optimization of management practices to improve cotton fiber quality under irrigated arid environment. J Food Agric Environ 2(2):609–613Google Scholar
  5. Ahmad S, Raza I, Ali H, Shahzad AN, Atiq-ur-Rehman, Sarwar N (2014) Response of cotton crop to exogenous application of glycinebetaine under sufficient and scarce water conditions. Braz J Bot 37(4):407–415Google Scholar
  6. Ali H, Abid SA, Ahmad S, Sarwar N, Arooj M, Mahmood A, Shahzad AN (2013a) Integrated weed management in cotton cultivated in the alternate-furrow planting system. J Food Agric Environ 11(3&4):1664–1669Google Scholar
  7. Ali H, Abid SA, Ahmad S, Sarwar N, Arooj M, Mahmood A, Shahzad AN (2013b) Impact of integrated weed management on flat-sown cotton (Gossypium hirsutum L.). J Anim Plant Sci 23(4):1185–1192Google Scholar
  8. Ali H, Afzal MN, Ahmad F, Ahmad S, Akhtar M, Atif R (2011) Effect of sowing dates, plant spacing and nitrogen application on growth and productivity on cotton crop. Int J Sci Eng Res 2(9):1–6Google Scholar
  9. Ali H, Hameed RA, Ahmad S, Shahzad AN, Sarwar N (2014a) Efficacy of different techniques of nitrogen application on American cotton under semi-arid conditions. J Food Agric Environ 12(1):157–160Google Scholar
  10. Ali H, Hussain GS, Hussain S, Shahzad AN, Ahmad S, Javeed HMR, Sarwar N (2014b) Early sowing reduces cotton leaf curl virus occurrence and improves cotton productivity. Cercetări Agronomice în Moldova XLVII(4):71–81Google Scholar
  11. Amin A, Nasim W, Mubeen M, Ahmad A, Nadeem M, Urich P, Fahad S, Ahmad S, Wajid A, Tabassum F, Hammad HM, Sultana SR, Anwar S, Baloch SK, Wahid A, Wilkerson CJ, Hoogenboom G (2018) Simulated CSM-CROPGRO-cotton yield under projected future climate by SimCLIM for southern Punjab, Pakistan. Agric Syst 167:213–222CrossRefGoogle Scholar
  12. Amin A, Nasim W, Mubeen M, Nadeem M, Ali L, Hammad HM, Sultana SR, Jabran K, Habib urRehman M, Ahmad S, Awais M, Rasool A, Fahad S, Saud S, Shah AN, Ihsan Z, Ali S, Bajwa AA, Hakeem KR, Ameen A, Amanullah, Rehman HU, Alghabar F, Jatoi GH, Akram M, Khan A, Islam F, Ata-Ul-Karim ST, Rehmani MIA, Hussain S, Razaq M, Fathi A (2017) Optimizing the phosphorus use in cotton by using CSM-CROPGRO-cotton model for semi-arid climate of Vehari-Punjab, Pakistan. Environ Sci Pollut Res 24(6):5811–5823CrossRefGoogle Scholar
  13. Aqeel-Ur-Rehman, Abbasi AZ, Islam N, Shaikh ZA (2014) A review of wireless sensors and networks applications in agriculture. Comput Stand Inter 36:263–270CrossRefGoogle Scholar
  14. Bhattarai SP, McHugh AD, Lotz G, Midmore DJ (2006) The response of cotton to subsurface drip and furrow irrigation in a vertisol. Exp Agr 42(1):29–49CrossRefGoogle Scholar
  15. Bhatti GH, Patel HM (2012) Estimation of evapotranspiration for four major crops using dual crop coeffcient method in SardarSarovar command area. Hydro–2012, Conference on Hydraulics, Water Resources, Coastal and Environmental Engineering. Mumbai: Indian Institute of TechnologyGoogle Scholar
  16. DeJonge KC, Ascough JC, Andales AA, Hansen NC, Garcia LA, Arabi M (2012) Improving evapotranspiration simulations in the CERES-maize model under limited irrigation. Agric Water Manag 115:92–103CrossRefGoogle Scholar
  17. DeJonge KC, Thorp KR (2017) Standardized reference evapotranspiration and dual crop coefficient approach in the DSSAT cropping system model. Trans ASABE 60(6):1965–1981CrossRefGoogle Scholar
  18. Duchemin B, Hadria R, Erraki S, Boulet G, Maisongrande P, Chehbouni A, Escadafal R, Ezzahar J, Hoedjes JCB, Kharrou MH, Khabba S, Mougenot B, Olioso A, Rodriguez JC, Simonneaus V (2006) Monitoring wheat phenology and irrigation in Central Morocco: on the use of relationships between evapotranspiration, crops coefficients, leaf area index and remotely sensed vegetation indices. Agric Water Manag 79:1–27CrossRefGoogle Scholar
  19. Dursun M, Özden S (2014) An efficient improved photovoltaic irrigation system with artificial neural network based modeling of soil moisture distribution - a case study in Turkey. Comput Electron Agric 102:120–126CrossRefGoogle Scholar
  20. Evett SR, Howell STA, Schneider AD, Copeland KS, Dusek DA, Brauer DK, Gowda PH (2016) The Bushland weighing lysimeters: a quarter century of crop ET investigations to advance sustainable irrigation. Trans ASABE 59(1):163–179CrossRefGoogle Scholar
  21. Fortes PS, Platonov AE, Pereira LS (2005) GISAREG—A GIS based irrigation scheduling simulation model to support improved water use. Agric Water Manag 77:159–179CrossRefGoogle Scholar
  22. Grismer ME (2002) Regional cotton lint yield, ETc and water value in Arizona and California. Agric Water Manag 54:227–242CrossRefGoogle Scholar
  23. Howell TA, Evett SR, Tolk JA, Schneider AD (2004) Evapotranspiration of full-, deficit-irrigated, and dryland cotton on the northern Texas High Plains. J Irrig Drain Eng 130(4):277–285CrossRefGoogle Scholar
  24. Hunsaker DJ, Barnes EM, Clarke TR, Fitzgerald GJ, Pinter JPJ (2005) Cotton irrigation scheduling using remotely sensed and FAO-56 basal crop coefficients. Trans ASAE 48(4):1395–1407CrossRefGoogle Scholar
  25. Hunsaker DJ, Elshikha DM (2017) Surface irrigation management for guayule rubber production in the U.S. desert southwest. Agric Water Manag 185:43–57CrossRefGoogle Scholar
  26. Khan MB, Khaliq A, Ahmad S (2004) Performance of mashbean intercropped in cotton planted in different planting patterns. J Res (Sci) 15(2):191–197Google Scholar
  27. Leib BG, Jabro JD, Matthews GR (2003) Field evaluation and performance comparison of soil moisture sensors. Soil Sci 168(6):396–408Google Scholar
  28. Modala NR, Ale S, Rajan N, Munster CL, DeLaune PB, Thorp KR, Barnes EM (2015) Evaluation of the CSM-CROPGRO-cotton model for the Texas Rolling Plains region and simulation of deficit irrigation strategies for increasing water use efficiency. Trans ASABE 58(3):685–696Google Scholar
  29. Nehra IPL, Nehra KC (2004) Effect of FIRB (Furrow Irrigated Raised Bed) system on productivity of cotton–wheat cropping system. In: Proceeding of International Symposium on Strategies for Sustainable Cotton Production- A global vision, 23–25th November 2004Google Scholar
  30. Pereira LS, Gonc¸alves JM, Dong B, Mao Z, Fang SX (2007) Assessing basin irrigation and scheduling strategies for saving irrigation water and controlling salinity in the upper Yellow River Basin, China. Agric Water Manag 93(3):109–122CrossRefGoogle Scholar
  31. Phene CJ, Detar WR, Clark DA (1992) Real-time irrigation scheduling of cotton with an automated pan evaporation system. Am Soc Agric Eng 8(6):787–793CrossRefGoogle Scholar
  32. Rahman MH, Ahmad A, Wang X, Wajid A, Nasim W, Hussain M, Ahmad B, Ahmad I, Ali Z, Ishaque W, Awais M, Shelia V, Ahmad S, Fahad S, Alam M, Ullah H, Hoogenboom G (2018) Multi-model projections of future climate and climate change impacts uncertainty assessment for cotton production in Pakistan. Agric For Meteorol 253-254:94–113CrossRefGoogle Scholar
  33. Shah NG, Das I (2012) Precision irrigation sensor network based irrigation, problems, perspectives and challenges of agricultural water management, IIT Bombay, India, pp 217–232Google Scholar
  34. Tariq M, Afzal MN, Muhammad D, Ahmad S, Shahzad AN, Kiran A, Wakeel A (2018) Relationship of tissue potassium content with yield and fiber quality components of Bt cotton as influenced by potassium application methods. Field Crop Res 229:37–43CrossRefGoogle Scholar
  35. Tariq M, Yasmeen A, Ahmad S, Hussain N, Afzal MN, Hasanuzzaman M (2017) Shedding of fruiting structures in cotton: factors, compensation and prevention. Trop Subtrop Agroecosyst 20(2):251–262Google Scholar
  36. Thorp KR, Ale S, Bange MP, Barnes EM, Hoogenboom G, Lascano RJ, White JW (2014) Development and application of process-based simulation models for cotton production: a review of past, present, and future directions. J Cotton Sci 18(1):10–47Google Scholar
  37. Usman M, Ahmad A, Ahmad S, Irshad M, Khaliq T, Wajid A, Hussain K, Nasim W, Chattha TM, Trethowan R, Hoogenboom G (2009) Development and application of crop water stress index for scheduling irrigation in cotton (Gossypium hirsutum L.) under semiarid environment. J Food Agric Environ 7(3&4):386–391Google Scholar
  38. Vories ED, Greene JK, Teague TG, Stewart JH, Phipps BJ, Pringle HC, Clawson EL, Hogan RJ, O’Leary PF, Griffin TW (2011) Determining the optimum timing for the final furrow irrigation on mid-south cotton. Trans ASABE 27(5):737–745Google Scholar
  39. Vories ED, Hogan R, Tacker PL, Glover RE, Lancaster SW (2007) Estimating the impact of delaying irrigation for midsouth cotton on clay soil. Trans ASABE 50(3):929–937CrossRefGoogle Scholar
  40. Wang J, Wang H, He J, Li L, Shen M, Tan X, Min H, Zheng L (2015) Wireless sensor network for real-time perishable food supply chain management. Comput Electron Agric 110:196–207CrossRefGoogle Scholar
  41. Yang Y, Yang Y, Moiwo JP, Hu Y (2010) Estimation of irrigation requirement for sustainable water resources reallocation in North China. Agric Water Manag 97(11):1711–1721CrossRefGoogle Scholar
  42. Yazar A, Sezen SM, Sesveren S (2002) LEPA and trickle irrigation of cotton in the Southeast Anatolia project (GAP) area in Turkey. Agric Water Manag 54:189–203CrossRefGoogle Scholar
  43. Zwart SJ, Bastiaanssen WGM (2004) Review of measured crop water productivity values for irrigated wheat, rice, cotton, and maize. Agric Water Manag 69:115–133CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Sajjad Hussain
    • 1
  • Ashfaq Ahmad
    • 2
  • Aftab Wajid
    • 3
  • Tasneem Khaliq
    • 3
  • Nazim Hussain
    • 4
  • Muhammad Mubeen
    • 1
    Email author
  • Hafiz Umar Farid
    • 5
  • Muhammad Imran
    • 1
  • Hafiz Mohkum Hammad
    • 1
  • Muhammad Awais
    • 6
  • Amjed Ali
    • 7
  • Muhammad Aslam
    • 8
  • Asad Amin
    • 1
    • 9
  • Rida Akram
    • 1
  • Khizer Amanet
    • 1
  • Wajid Nasim
    • 10
  1. 1.Department of Environmental SciencesCOMSATS Institute of Information TechnologyVehariPakistan
  2. 2.Program Chair, Climate Change, US.-Pakistan Centre for Advanced Studies in Agriculture and Food SecurityUniversity of Agriculture FaisalabadFaisalabadPakistan
  3. 3.Agro-Climatology Lab, Department of AgronomyUniversity of Agriculture FaisalabadFaisalabadPakistan
  4. 4.Department of AgronomyBahauddin Zakariya UniversityMultanPakistan
  5. 5.Department of Agricultural EngineeringBahauddin Zakariya UniversityMultanPakistan
  6. 6.Department of AgronomyUniversity College of Agriculture and Environmental Sciences, The Islamia University of Bahawalpur (IUB)BahawalpurPakistan
  7. 7.University College of Agriculture, University of SargodhaSargodhaPakistan
  8. 8.Department of Agriculture (Extension Wing)Government of PunjabLahorePakistan
  9. 9.Queensland Alliance for Agriculture and Food Innovation (QAAFI)The University of QueenslandBrisbaneAustralia
  10. 10.Department of Agronomy, University College of Agriculture and Environmental SciencesIslamia University of BahawalpurBahawalpurPakistan

Personalised recommendations