Research Article
BibTex RIS Cite
Year 2023, Volume: 12 Issue: 3, 267 - 276, 02.07.2023
https://doi.org/10.18393/ejss.1277096

Abstract

References

  • Averianov, S.F., 1982. Filtration from canals and its influence on groundwater regime. Kolos, Moscow, USSR. 238p. [in Russian].
  • Bohaienko, V., Romashchenko, M., Sardak, A., Gladky, A., 2022. Mathematical modelling technique to mitigate soil moisture measurement inaccuracies under the conditions of drip irrigation. Irrigation Science (in Press)
  • Cannata, M., 2006. GIS embedded approach for Free & Open Source Hydrological Modelling. PhD thesis, Department of Geodesy and Geomatics, Polytechnic of Milan, Italy.
  • Choudhury, B.J., Idso, S.B., Reginato, R.J., 1987. Analysis of an empirical model for soil heat flux under a growing wheat crop for estimating evaporation by an infraredtemperature based energy balance equation. Agricultural and Forest Meteorology 39 (4): 283–297.
  • Deardorff, J.W., 1978. Efficient prediction of ground surface temperature and moisture, with inclusion of a layer of vegetation. Journal of Geophysical Research 83: 1889-1903.
  • Ding, R., Kang, Sh., Li, F., Zhang, Y., Tong, L., 2013. Evapotranspiration measurement and estimation using modified Priestley–Taylor model in an irrigated maize field with mulching. Agricultural and Forest Meteorology 168:140-148.
  • Elbeltagi, A., Srivastava, A., Al-Saeedi, A.H., Raza, A., Abd-Elaty, I., El-Rawy, M., 2023. Forecasting long-series daily reference evapotranspiration based on best subset regression and machine learning in Egypt. Water 15(6): 1149.
  • Ershadi, A., McCabe, M., Evans, J.P., Chaney, N.W., Wood, E.F., 2014. Multi-site evaluation of terrestrial evaporation models using FLUXNET data. Agricultural and Forest Meteorology 187: 46–61.
  • Faybishenko, B., 2007. Climatic forecasting of net ınfiltration at Yucca Mountain using analogue meteorological data. Vadose Zone Journal 6: 77–92.
  • Gharsallah, O., Facchi, A., Gandolfi, C., 2013. Comparison of six evapotranspiration models for a surface irrigated maize agro-ecosystem in Northern Italy. Agricultural Water Management 130: 119–130.
  • Gigante, V., Iacobellis, V., Manfreda, S., Milella, P., Portoghese, I., 2009. Influences of Leaf Area Index estimations on water balance modeling in a Mediterranean semi-arid basin. Natural Hazards and Earth System Sciences 9: 979–991.
  • Gong, X., Qiu, R., Ge, J., Bo, G., Ping, Y., Xin, Q., Wang, Sh. 2021. Evapotranspiration partitioning of greenhouse grown tomato using a modified Priestley–Taylor model. Agricultural Water Management 247: 106709.
  • Kovalchuk, P.I., Matiash, T.V., 2006. Optimization of yearly water use planning in the conditions of resources deficit. Melioratsija i vodne hospodarstvo 93-94: 210-218. [in Ukrainian].
  • Kustas, W.P., Zhan, X., Schmugge, T.J., 1998. Combining optical and microwave remote sensing for mapping energy fluxes in a semiarid watershed. Remote Sensing of Environment 64(2): 116–131.
  • Molz, F. J., Remson, I., 1970. Extraction term models of soil moisture use by transpiring plants. Water Resources Research 6(5): 1346-1356.
  • Monteith, J.L., 1965. Evaporation and environment. In: The State and Movement of Water in Living Organisms. 19th Symposium of the Society for Experimental Biology. Fogg, G.E. (Ed.). 8–12 September 1964, Swansea. The Company of Biologists: Cambridge. pp.205–234.
  • Overgaard, J., Rosbjerg, D., Butts, M.B., 2006. Land-surface modelling in hydrological perspective – a review. Biogeosciences 3(2): 229–241.
  • Podlubny, I., 1999. Fractional differential equations: An introduction to fractional derivatives, fractional differential equations, to methods of their solution and some of their applications. Academic Press, USA. 340p.
  • Priestley, C.H.B., Taylor, R.J., 1972. On the assessment of surface heat flux and evaporation using large-scale parameters. Monthly Weather Review 100: 81–92.
  • Qiu, R.J., Liu, C.W., Cui, N.B., Wu, Y.J., Wang, Z.C., Li, G., 2019. Evapotranspiration estimation using a modified Priestley-Taylor model in a rice-wheat rotation system. Agricultural Water Management 224: 105755.
  • Rodriguez-Iturbe, I., 2000. Ecohydrology: A hydrologic perspective of climate-soil-vegetation dynamies. Water Resources Research 36(1): 3–9.
  • Romashchenko, M.I., Bohaienko, V.O., Matiash, T.V., Kovalchuk, V.P., Danylenko, I.I., 2020. Influence of evapotranspiration assessment on the accuracy of moisture transport modeling under the conditions of sprinkling irrigation in the south of Ukraine. Archives of Agronomy and Soil Science 66(10): 1424-1435.
  • Romashchenko, M.I., Bohaienko, V.O., Matiash, T.V., Kovalchuk, V.P., Krucheniuk, A.V., 2021. Numerical simulation of irrigation scheduling using fractional Richards equation. Irrigation Science 39(3): 385-396.
  • Samarskii, A.A., 2001. The Theory of Difference Schemes. CRC Press, USA. 786p.
  • Savenije, H.H.G., 2004. The importance of interception and why we should delete the term evapotranspiration from our vocabulary. Hydrological Processes 18(8): 1507–1511.
  • Sellers, P.J., Heiser, M.D., Hall, F.G., 1992. Relations between surface conductance and spectral vegetation indices at intermediate (100 m2 to 15 km2) length scales. Journal of Geophysical Research 97(D17): 19033–19059.
  • Shao, M., Liu, H., Yang, L., 2022. Estimating tomato transpiration cultivated in a sunken solar greenhouse with the penman-monteith, shuttleworth-wallace and priestley-taylor models in the North China Plain. Agronomy 12: 2382.
  • Shao, W., Su, Y., Langhammer, J., 2017. Simulations of coupled non-isothermal soil moisture transport and evaporation fluxes in a forest area. Journal of Hydrology and Hydromechanics 65: 410–425.
  • Shuttleworth, W.J., Wallace, J.S., 1985. Evaporation from sparse crops—an energy combination theory. Quarterly Journal of the Royal Meteorological Society 111: 839–855.
  • UIPVE, 2019. Ukrainian Institute of Plant Varieties Expertize. Protection of plant variety rights: Bulletin. Issue 1. 1088 p.
  • van Dam, J.C., Feddes, R.A., 2000. Numerical simulation of infiltration, evaporation and shallow groundwater levels with the Richards equation. Journal of Hydrology 233(1-4): 72-85.
  • van Genuchten, M.T., 1980. A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Science Society of America Journal 44(5): 892-898.
  • Venturini, V., Islam, S., Rodriguez, L., 2008. Estimation of evaporative fraction and evapotranspiration from MODIS products using a complementary based model. Remote Sensing of Environment 112: 132–141.
  • Wanniarachchi, S., Sarukkalige, R., 2022. A Review on evapotranspiration estimation in agricultural water management: Past, Present, and Future. Hydrology 9(7):123.
  • Zhang, Y.A., Wang, Sh.H., Ji, G.L., 2015. Comprehensive survey on particle swarm optimization algorithm and its applications. Mathematical Problems in Engineering Article ID: 931256.

Simulation of irrigation in southern Ukraine incorporating soil moisture state in evapotranspiration assessments

Year 2023, Volume: 12 Issue: 3, 267 - 276, 02.07.2023
https://doi.org/10.18393/ejss.1277096

Abstract

The paper studies the accuracy of modeling moisture transport under the conditions of sprinkler irrigation using evapotranspiration assessment methods that take into account the soil moisture conditions. Appropriate modifications of the Penman-Monteith and the Priestley-Taylor models are considered. Moisture transport modeling is performed using the Richards equation in its integer- and fractional-order forms. Parameters identification is performed by the particle swarm optimization algorithm based on the readings of suction pressure sensors. Results for the two periods of 11 and 50 days demonstrate the possibility of up to ~20% increase in the simulation accuracy by using a modified Priestley-Taylor model when the maintained range of moisture content in the root layer is 70%-100% of field capacity. When irrigation maintained the range of 80%-100% of field capacity, moisture content consideration within evapotranspiration assessment models did not enhance simulation accuracy. This confirms the independence of evapotranspiration from soil moisture content at its levels above 80% of field capacity as in this case actual evapotranspiration reaches a level close to the potential one. Scenario modeling of the entire growing season with the subsequent estimation of crop (maize) yield showed that irrigation regimes generated using evapotranspiration models, which take into account soil moisture data, potentially provide higher yields at lower water supply.

References

  • Averianov, S.F., 1982. Filtration from canals and its influence on groundwater regime. Kolos, Moscow, USSR. 238p. [in Russian].
  • Bohaienko, V., Romashchenko, M., Sardak, A., Gladky, A., 2022. Mathematical modelling technique to mitigate soil moisture measurement inaccuracies under the conditions of drip irrigation. Irrigation Science (in Press)
  • Cannata, M., 2006. GIS embedded approach for Free & Open Source Hydrological Modelling. PhD thesis, Department of Geodesy and Geomatics, Polytechnic of Milan, Italy.
  • Choudhury, B.J., Idso, S.B., Reginato, R.J., 1987. Analysis of an empirical model for soil heat flux under a growing wheat crop for estimating evaporation by an infraredtemperature based energy balance equation. Agricultural and Forest Meteorology 39 (4): 283–297.
  • Deardorff, J.W., 1978. Efficient prediction of ground surface temperature and moisture, with inclusion of a layer of vegetation. Journal of Geophysical Research 83: 1889-1903.
  • Ding, R., Kang, Sh., Li, F., Zhang, Y., Tong, L., 2013. Evapotranspiration measurement and estimation using modified Priestley–Taylor model in an irrigated maize field with mulching. Agricultural and Forest Meteorology 168:140-148.
  • Elbeltagi, A., Srivastava, A., Al-Saeedi, A.H., Raza, A., Abd-Elaty, I., El-Rawy, M., 2023. Forecasting long-series daily reference evapotranspiration based on best subset regression and machine learning in Egypt. Water 15(6): 1149.
  • Ershadi, A., McCabe, M., Evans, J.P., Chaney, N.W., Wood, E.F., 2014. Multi-site evaluation of terrestrial evaporation models using FLUXNET data. Agricultural and Forest Meteorology 187: 46–61.
  • Faybishenko, B., 2007. Climatic forecasting of net ınfiltration at Yucca Mountain using analogue meteorological data. Vadose Zone Journal 6: 77–92.
  • Gharsallah, O., Facchi, A., Gandolfi, C., 2013. Comparison of six evapotranspiration models for a surface irrigated maize agro-ecosystem in Northern Italy. Agricultural Water Management 130: 119–130.
  • Gigante, V., Iacobellis, V., Manfreda, S., Milella, P., Portoghese, I., 2009. Influences of Leaf Area Index estimations on water balance modeling in a Mediterranean semi-arid basin. Natural Hazards and Earth System Sciences 9: 979–991.
  • Gong, X., Qiu, R., Ge, J., Bo, G., Ping, Y., Xin, Q., Wang, Sh. 2021. Evapotranspiration partitioning of greenhouse grown tomato using a modified Priestley–Taylor model. Agricultural Water Management 247: 106709.
  • Kovalchuk, P.I., Matiash, T.V., 2006. Optimization of yearly water use planning in the conditions of resources deficit. Melioratsija i vodne hospodarstvo 93-94: 210-218. [in Ukrainian].
  • Kustas, W.P., Zhan, X., Schmugge, T.J., 1998. Combining optical and microwave remote sensing for mapping energy fluxes in a semiarid watershed. Remote Sensing of Environment 64(2): 116–131.
  • Molz, F. J., Remson, I., 1970. Extraction term models of soil moisture use by transpiring plants. Water Resources Research 6(5): 1346-1356.
  • Monteith, J.L., 1965. Evaporation and environment. In: The State and Movement of Water in Living Organisms. 19th Symposium of the Society for Experimental Biology. Fogg, G.E. (Ed.). 8–12 September 1964, Swansea. The Company of Biologists: Cambridge. pp.205–234.
  • Overgaard, J., Rosbjerg, D., Butts, M.B., 2006. Land-surface modelling in hydrological perspective – a review. Biogeosciences 3(2): 229–241.
  • Podlubny, I., 1999. Fractional differential equations: An introduction to fractional derivatives, fractional differential equations, to methods of their solution and some of their applications. Academic Press, USA. 340p.
  • Priestley, C.H.B., Taylor, R.J., 1972. On the assessment of surface heat flux and evaporation using large-scale parameters. Monthly Weather Review 100: 81–92.
  • Qiu, R.J., Liu, C.W., Cui, N.B., Wu, Y.J., Wang, Z.C., Li, G., 2019. Evapotranspiration estimation using a modified Priestley-Taylor model in a rice-wheat rotation system. Agricultural Water Management 224: 105755.
  • Rodriguez-Iturbe, I., 2000. Ecohydrology: A hydrologic perspective of climate-soil-vegetation dynamies. Water Resources Research 36(1): 3–9.
  • Romashchenko, M.I., Bohaienko, V.O., Matiash, T.V., Kovalchuk, V.P., Danylenko, I.I., 2020. Influence of evapotranspiration assessment on the accuracy of moisture transport modeling under the conditions of sprinkling irrigation in the south of Ukraine. Archives of Agronomy and Soil Science 66(10): 1424-1435.
  • Romashchenko, M.I., Bohaienko, V.O., Matiash, T.V., Kovalchuk, V.P., Krucheniuk, A.V., 2021. Numerical simulation of irrigation scheduling using fractional Richards equation. Irrigation Science 39(3): 385-396.
  • Samarskii, A.A., 2001. The Theory of Difference Schemes. CRC Press, USA. 786p.
  • Savenije, H.H.G., 2004. The importance of interception and why we should delete the term evapotranspiration from our vocabulary. Hydrological Processes 18(8): 1507–1511.
  • Sellers, P.J., Heiser, M.D., Hall, F.G., 1992. Relations between surface conductance and spectral vegetation indices at intermediate (100 m2 to 15 km2) length scales. Journal of Geophysical Research 97(D17): 19033–19059.
  • Shao, M., Liu, H., Yang, L., 2022. Estimating tomato transpiration cultivated in a sunken solar greenhouse with the penman-monteith, shuttleworth-wallace and priestley-taylor models in the North China Plain. Agronomy 12: 2382.
  • Shao, W., Su, Y., Langhammer, J., 2017. Simulations of coupled non-isothermal soil moisture transport and evaporation fluxes in a forest area. Journal of Hydrology and Hydromechanics 65: 410–425.
  • Shuttleworth, W.J., Wallace, J.S., 1985. Evaporation from sparse crops—an energy combination theory. Quarterly Journal of the Royal Meteorological Society 111: 839–855.
  • UIPVE, 2019. Ukrainian Institute of Plant Varieties Expertize. Protection of plant variety rights: Bulletin. Issue 1. 1088 p.
  • van Dam, J.C., Feddes, R.A., 2000. Numerical simulation of infiltration, evaporation and shallow groundwater levels with the Richards equation. Journal of Hydrology 233(1-4): 72-85.
  • van Genuchten, M.T., 1980. A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Science Society of America Journal 44(5): 892-898.
  • Venturini, V., Islam, S., Rodriguez, L., 2008. Estimation of evaporative fraction and evapotranspiration from MODIS products using a complementary based model. Remote Sensing of Environment 112: 132–141.
  • Wanniarachchi, S., Sarukkalige, R., 2022. A Review on evapotranspiration estimation in agricultural water management: Past, Present, and Future. Hydrology 9(7):123.
  • Zhang, Y.A., Wang, Sh.H., Ji, G.L., 2015. Comprehensive survey on particle swarm optimization algorithm and its applications. Mathematical Problems in Engineering Article ID: 931256.
There are 35 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Vsevolod Bohaienko This is me 0000-0002-3317-9022

Tetiana Matiash This is me 0000-0003-1225-086X

Mykhailo Romashchenko This is me 0000-0002-9997-1346

Publication Date July 2, 2023
Published in Issue Year 2023 Volume: 12 Issue: 3

Cite

APA Bohaienko, V., Matiash, T., & Romashchenko, M. (2023). Simulation of irrigation in southern Ukraine incorporating soil moisture state in evapotranspiration assessments. Eurasian Journal of Soil Science, 12(3), 267-276. https://doi.org/10.18393/ejss.1277096