Open Access
Subscription Access
Irrigation Scheduling Based on Canopy Temperature and Soil Moisture Status
Issues of water availability and quality are major concerns under the climatic change scenarios. For sustainable agriculture, improved irrigation techniques can play a crucial role in the conservation of water and increase crop production. This article delineates the necessity of irrigation scheduling based on sound scientific principles. To effectively manage irrigation and crop water requirements, all irrigation scheduling methods should focus on a soil-plant-atmosphere approach.
Keywords
Canopy Temperature, Irrigation Scheduling, Remote Sensing, Soil Moisture, Water Stress.
User
Font Size
Information
- https://www.worldbank.org/en/topic/water-in-agriculture (accessed on 15 March 2022).
- Jain, R., Kishore, P. and Singh, D. K., Irrigation in India: status, challenges, and options. J. Soil Water Conserv., 2019, 18(4), 354–363.
- Amarasinghe, U. A., Shah, T., Turral, H. and Anand, B. K., India’s water future to 2025–2050: business-as-usual scenario and deviations. IWMI Research Report 123, International Water Management Institute, Colombo, Sri Lanka, 2007, p. 47.
- Jones, J. W., Irrigation scheduling: advantages and pitfalls of plant-based methods. J. Exp. Bot., 2004, 55(407), 2427–2436.
- Thompson, R. G., Gallardo, M. and Fernandez, M., Continuous soil moisture monitoring for irrigation scheduling of drip-irrigated vegetables grown in the greenhouse. In Proceedings of the VII Congress of the European Society of Agronomy (eds Villalobos, F. J. and Testi, L.), 2002, pp. 415–416.
- Idso, S. B., Jackson, R. D., Pinter, P. J. and Hatfield, J. L., Normalizing the stress degree day for environmental variability. Agric. Meteorol., 1981, 24, 45–55.
- Gu, Z., Qi, Z., Burghate, R., Yuan, S., Jiao, X. and Xu, J., Irrigation scheduling approaches and applications: a review. J. Irrig. Drain. Eng., 2020, 146(6), 04020007.
- Jackson, R. D., Idso, S. B., Reginato, R. J. and Pinter, P. J., Canopy temperature as crop water stress indicator. Water Resour. Res., 1981, 17(4), 1133–1138.
- Gonita, N. K. and Tiwari, K. N., Development of crop water stress index of wheat crop for scheduling irrigation using infrared thermometry. Agric. Water Manage., 2008, 95, 1144–1152.
- Han, M., Zhang, H., Dejonge, K. C., Comas, L. and Trout, T. J., Estimating Mazie waterstress by standard deviation of canopy temperature in thermal imagery. Agric. Water Manage., 2016, 177, 400–409.
- Padhi, J., Misra, R. K. and Payero, J. O., Estimation of soil water deficit in an irrigated cotton field with infrared thermometry. Field Crops Res., 2012, 126, 45–55.
- Wanjura, D. E., Upchurch, D. R. and Mahan, J. R., Behavior of temperature-based water stress indicators in BIOTIC-controlled irrigation. Irrig. Sci., 2006, 24, 223–232.
- Clawson, K. L. and Blad, B. L., Infrared thermometry for scheduling irrigation of corn. Agron. J., 1982, 74(2), 311–316.
- Viani, F., Experimental validation of a wireless system for the irrigation management in smart farming applications. Microw. Opt. Technol. Lett., 2016, 58(9), 2186–2189.
- Hedley, C. and Yule, I., A method for spatial prediction of daily soil water status for precise irrigation scheduling. Agric. Water Manage., 2009, 96(12), 1737–1745.
- Migliaccio, K., Schaffer, W. B., Crane, J. H. and Davies, F. S., Plant response to evapotranspiration and soil water sensor irrigation scheduling methods for papaya production in South Florida. Agric. Water Manage., 2010, 97(10), 1452–1460.
- Evett, S. R., Schwartz, R. C., Mazahrih, N. T. H., Jitan, M. A. and Shaqir, I. M., Soil water sensors for irrigation scheduling: can they deliver a management allowed depletion? Acta Hortic., 2011, 888, 231–237.
- Berni, J. A., Zarco-Tejada, P. J., Suárez, L. and Fereres, E., Thermal and narrowband multispectral remote sensing for vegetation monitoring from an unmanned aerial vehicle. IEEE Trans. Geosci. Remote Sensing, 2009, 47, 722–738.
- Wang, X., Zhao, C., Guo, Ni., Li, Y., Jian, S. and Yu, K., Determining the canopy water stress for spring wheat using canopy hyperspectral reflectance data in Loess Plateau semi arid regions. Spectrosc. Lett., 2015, 48, 492–498.
- Zhao, T., Stark, B., Chen, Y., Ray, A. L. and Doll, D., A detailed field study of direct correlations between ground truth crop water stress and normalized difference vegetation index (NDVI) from small unmanned aerial system (sUAS). In IEEE International Conference on Unmanned Aircraft Systems (ICUAS), Denver Marriott Tech Centre, Denver, Colorado, USA, 2015, pp. 520–525.
- Zarco-Tejada, P. J., González-Dugo, V. and Berni, J. A., Fluorescence, temperature and narrow-band indices acquired from a UAV platform for water stress detection using a micro hyperspectral imager and a thermal camera. Remote Sensing Environ., 2012, 117, 322–337.
- Berni, J., Zarco-Tejada, P., Sepulcre-Cantó, G., Fereres, E. and Villalobos, F., Mapping canopy conductance and CWSI in olive orchards using high resolution thermal remote sensing imagery. Remote Sensing Environ., 2009, 113, 2380–2388.
- Elston, J., Why unmanned aircraft for agriculture? ASABE Resour. Mag., 2016; http://bt.e-ditionsbyfry.com/publication/?i=316822.
- Campos, I., González-Piqueras, J., Carrara, A., Villodre, J. and Calera, A., Estimation of total available water in the soil layer by integrating actual evapotranspiration data in a remote sensing-driven soil water balance. J. Hydrol., 2016, 534, 427–439.
- Filion, R. et al., Remote sensing for mapping soil moisture and drainage potential in semi-arid regions: applications to the Campidano plain of Sardinia, Italy. Sci. Total Environ. Part B, 2016, 543, 862–876.
- Gago, J. et al., UAVs challenge to assess waterstress for sustainable agriculture. Agric. Water Manage., 2015, 153, 9–19.
- Panigada, C. et al., Fluorescence, PRI and canopy temperature for water stress detection in cereal crops. Int. J. Appl. Earth Observ. Geoinf., 2014, 30, 167–178.
- Dangwal, N., Patel, N. R., Kumari, M. and Saha, S. K., Monitoring of water stress in wheat using multispectral indices derived from Landsat-TM. Geocarto Int., 2016, 31(6), 682–693.
- Pramanik, M., Garg, N. K., Tripathi, S. K., Singh, R. and Rajan, R., A new approach of canopy temperature-based irrigation scheduling of wheat in humid subtropical climate of India. Proc. Natl. Acad. Sci. India, Sect. B, 2017, 87, 1261–1269.
- Kar, G. and Kumar, A., Energy balance and crop water stress in winter maize under phenology-based irrigation scheduling. Irrig. Sci., 2010, 28, 211–220.
- Alderfasi, A. A. and Nielsen, D. C., Use of crop water stress index for monitoring water status and scheduling irrigation in wheat. Agric. Water Manage., 2000, 27, 69–75.
- Erdem, T., Erdem, Y., Orta, A. H. and Okursoy, H., Use of a crop water stress index for scheduling the irrigation of sunflower (Helianthus annuus L.). Turk. J. Agric. For., 2006, 30, 11–20.
- O’Shaughnessy, S. A., Evett, S. R., Colaizzi, P. D. and Howell, T. A., Automatic irrigation scheduling of grain sorghum using a CSWI and time threshold. In Fifth National Decennial Irrigation CD-ROM Proceedings, Phoenix, AZ, USA, 5–8 December 2010.
- Bockhold, D. L., Thompson, A. L., Sudduth, K. A. and Henggeler, J. C., Irrigation scheduling based on crop canopy temperature for humid environment. Am. Soc. Agric. Biol. Eng., 2011, 54(6), 2021–2028.
- Ünlü, M., Kanber, R., Kapur, B., Tekin, S. and Koç, D. L., The crop water stress index (CSWI) for drip-irrigated cotton in a semi-arid region of Turkey. Afr. J. Biotechnol., 2011, 10(12), 2258–2273.
- Candogan, B. N., Sincik, M., Buyukcangaz, H., Demirtas, C., Goksoy, A. T. and Yazgan, S., Yield, quality and crop water stress index relationships for deficit-irrigated soybean [Glycin max (L.) Merr.] in sub-humid climatic conditions. Agric. Water Manage., 2013, 118, 113–121.
- Ahmadi, H., Nasrolahi, A. H., Sharifipour, M. and Isvand, H. R., Determination of soybean water stress index (CSWI) for irrigation management for maximum yield and water productivity. J. Irrig. Water Eng., 2018, 8(32), 121–131.
- Khorsand, A., Rezaverdinejad, V., Asgarzadeh, H., Heris, A. M., Rahimi, A. and Besharat, S., Irrigation scheduling of black gram based on crop water stress index (CSWI) under drip irrigation. Iran. J. Soil Water Res., 2019, 50, 2125–2138.
- Irmak, S., Haman, D. Z. and Bastug, R., Determination of crop water stress index for irrigation timing and yield estimation of corn. Agron. J., 2000, 92(6), 1221–1227.
- Erdem, Y., Erdem, T., Orta, A. H. and Okursoy, H., Irrigation scheduling for watermelon with crop water stress index (CWSI). J. Central Eur. Agric., 2005, 6(4), 449–460.
- Kumar, N., Poddar, A., Shankar, V., Ojha, C. S. P. and Adeloye, A. J., Crop water stress index for scheduling irrigation of Indian mustard (Brassica juncea) based on water use efficiency considerations. J. Agron. Crop Sci., 2020, 206(1), 148–159.
- Yuan, G., Luo, Y., Sun, X. and Tang, D., Evaluation of a crop water stress index for detecting water stress in winter wheat in the North China Plain. Agric. Water Manage., 2003, 64, 29–40.
- Kang, Y., Wang, F. X., Liu, H. J. and Yuan, B. Z., Potato evapo-transpiration and yield under different drip irrigation regimes. Irrig. Sci., 2004, 23, 133–143.
- Igbadun, H. E., Salim, B. A., Tarimo, A. K. P.R. and Mahoo, H. F., Effects of deficit irrigation scheduling on yield and soil water balance of irrigated maize. Irrig. Sci., 2008, 27, 11–23.
- Laghari, K. Q., Lashari, B. K. and Menon, H. M., Water use efficiency of cotton and wheat crop at various management allowed depletion in lower Indus basin. Mehran Univ. Res. J. Eng. Technol., 2010, 29(4), 661–672.
- Jha, S. K., Gao, Y., Liu, H., Huang, Z., Wang, G., Liang, Y. and Duan, A., Root development and water uptake in winter wheat under different irrigation methods and scheduling for North China. Agric. Water Manage., 2017, 182, 139–150.
- Muktar, B. Y. and Yigezu, T. T., Determination of optimal irrigation scheduling for maize (Zea mays) at Teppi, southwest of Ethiopia. Int. J. Res. Innov. Earth Sci., 2016, 3(5), 97–100.
- Ansari, R., Cheema, M. J. S., Liaqat, M. U., Ahmed, S. and Khan, H. I. U. K., Evaluation of irrigation scheduling techniques: a case study of wheat crop sown over permanent beds under semi-arid conditions. J. Agric. Plant Sci., 2019, 17(1), 9–21.
- Tunali, S. P., Gürbüz, T., Dağdelen, N. and Akçay, S., The effects of different irrigation scheduling approaches on seed yield and water use efficiencies of cotton. Turk. J. Agric. Food Sci. Technol., 2021, 9(8), 1530–1536.
- Bijanzadeh, E. and Emam, Y., Evaluation of crop water stress index, canopy temperature, and grain yield of five Iranian wheat cultivars under late-season drought stress. J. Plant Physiol. Breed., 2012, 2(1), 23–33.
- Kashyap, P. S. and Panda, R. K., Effect of irrigation scheduling on potato crop parameters under water stressed conditions. Agric. Water Manage., 2003, 59, 49–66.
- Amatya, S., Karkee, M., Alva, A. K., Larbi, P. and Adhikari, B., Hyperspectral imaging for detecting water stress in potatoes. In ASABE Annual Meeting, Texas, USA, 2012, Paper no. 12-1345197.
- Rossini, M. et al., Assessing canopy PRI from airborne imagery to map water stress in maize. Photogramm. Remote Sensing, 2013, 46, 168–177.
- Ihuoma, S. O. and Madramootoo, C. A., Crop reflectance indices for mapping water stressin greenhouse-grown bell pepper. Agric. Water Manage., 2019, 219, 49–58.
Abstract Views: 190
PDF Views: 92