Geostatistical Approach to Determining the Pressure Head Spatial Distribution along the Center-Pivot Lateral Line
Publication: Journal of Irrigation and Drainage Engineering
Volume 150, Issue 6
Abstract
Irrigation is important for the growth of world agriculture, as it enables greater security in agricultural production. The use of center-pivot for irrigation is very common in Brazil. However, there are some information gaps, mainly related to spatial variability in the water application in variable topography. Thus, the present study aimed to apply the geostatistical approach to characterize and evaluate the magnitude of the pressure head (PH) spatial variability in center-pivot lateral lines operating in plots with variable topography. For this analysis, six different points were installed along the lateral line and measured with PH transducers in 18 lateral line angular positions in the study area. Universal kriging (UK) was used to estimate PH across the whole field. The semivariogram was adjusted by the hole effect theoretical model, indicating a strong spatial dependence on PH. A decision support system tool was developed to assist in the analysis of the PH spatial distribution along the center-pivot lateral line using a geostatistical approach (kriging). The proposed tool can be useful for managers of irrigable areas and to identify zones with high energy use (wasted PH) along lateral lines of center-pivot systems. The estimation of PH distribution using geostatistical and UK techniques was satisfactory, allowing the creation of a thematic map. Precision irrigation and monitoring using a thematic map of PH distribution from kriging can help monitor the operating conditions of a center-pivot, as well as improve the decision-making regarding proper management of the whole irrigation system.
Practical Applications
Center-pivot irrigation systems are very common in agricultural production areas around the world. Due to the large area irrigated by center-pivots, it is very important to study the reduction in water and energy use in these equipment. Thus, an important point to be studied is the PH distribution along the center-pivot lateral line in areas with undulating topography, where there is a significant PH variation. In this study, we present an analysis of the PH distribution along the lateral line using a geostatistical approach (kriging) to obtain PH values in the entire irrigated area. For this, PH data collected at six different points along the lateral line were used in a decision support system tool, developed to estimate PH in the entire irrigated area using the geostatistical approach. This estimate was satisfactory, allowing the creation of a thematic map. The proposed tool proved to be useful for easily identifying zones with high energy use (wasted PH). In this way, the use of precision irrigation and the analysis of the equipment through thematic mapping can help irrigators in monitoring the operating conditions of a center-pivot.
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Data Availability Statement
All data, models, and code generated or used during this study appear in the published article.
Acknowledgments
The authors would like to thank the Itograss Agrícola Ltda. for granting the equipment for the study, the Foundation for Supporting Research of the State of Minas Gerais (FAPEMIG) for the author’s scholarship, the National Council for Scientific and Technological Development (CNPq) for the financing of equipment, and the Coordination for the Improvement of Higher Education Personnel (Capes) for the granting of scholarships. The many useful comments made by three anonymous reviewers are gratefully acknowledged.
References
Alves, E. D. S., L. M. Araújo, J. S. D. D. Alves, J. É. D. O. Santos, and C. R. L. Zimback. 2015. “Geostatistics applied to the uniformity of water application in a used and new drip irrigation system.” Rev. Bras. Agri. Irrig. 9 (3): 127. https://doi.org/10.7127/rbai.v9n300298.
Baptista, V. B. S., A. Colombo, B. D. Barbosa, L. A. Alvarenga, and A. V. Diotto. 2020. “Pressure distribution on center-pivot lateral lines: analytical models compared to EPANET 2.0.” J. Irrig. Drain. Eng. 146 (8): 04020025. https://doi.org/10.1061/(ASCE)IR.1943-4774.0001488.
Baptista, V. B. S., J. I. Córcoles, A. Colombo, and M. Á. Moreno. 2019. “Feasibility of the use of variable speed drives in center-pivot systems installed in plots with variable topography.” Water 11 (10): 2192. https://doi.org/10.3390/w11102192.
Barbosa, B. D., A. Colombo, J. G. de Souza, V. B. D. S. Baptista, and A. Araújo. 2018. “Energy efficiency of a center pivot irrigation system.” Eng. Agric. 38: 284–292. https://doi.org/10.1590/1809-4430-Eng.Agric.v38n2p284-292/2018.
Barker, J. B., T. E. Franz, D. M. Heeren, C. M. Neale, and J. D. Luck. 2017. “Soil water content monitoring for irrigation management: A geostatistical analysis.” Agric. Water Manage. 188 (Mar): 36–49. https://doi.org/10.1016/j.agwat.2017.03.024.
Bottega, E. L., D. M. Queiroz, F. D. A. Carvalho Pinto, and C. M. A. Souza. 2013. “Spatial variability of soil attributes in a no-tillage system with crop rotation in the Brazilian savannah.” Rev. Ciênc. Agron. 44 (1): 1–9. https://doi.org/10.1590/S1806-66902013000100001.
Brar, D., W. L. Kranz, T. H. Lo, S. Irmak, and D. L. Martin. 2017. “Energy conservation using variable-frequency drives for center-pivot irrigation: Standard systems.” Trans. ASABE 60 (1): 95–106. https://doi.org/10.13031/trans.11683.
Burgess, T. M., and R. Webster. 1980. “Optimal interpolation and isarithmic mapping of soil properties.” Eur. J. Soil Sci. 31 (2): 315–331. https://doi.org/10.1111/j.1365-2389.1980.tb02084.x.
Cambardella, C. A., T. B. Moorman, J. M. Novak, T. B. Parkin, D. L. Karlen, R. F. Turco, and A. E. Konopka. 1994. “Field-scale variability of soil properties in central Iowa soils.” Soil Sci. Soc. Am. J. 58 (5): 1501–1511. https://doi.org/10.2136/sssaj1994.03615995005800050033x.
Charles, T. S., T. R. Lopes, S. N. Duarte, J. G. Nascimento, H. de Carvalho Ricardo, and A. B. Pacheco. 2022. “Estimating average annual rainfall by ordinary kriging and TRMM precipitation products in midwestern Brazil.” J. South Am. Earth Sci. 118 (Apr): 103937. https://doi.org/10.1016/j.jsames.2022.103937.
Da Silva Ribeiro, L., I. R. Oliveira, J. S. Dantas, C. V. Silva, G. B. Silva, and J. R. Azevedo. 2016. “Spatial variability of physical attributes of cohesive soil under conventional and no tillage systems.” Pesqui. Agropecu. Bras. 51 (9): 1699–1702. https://doi.org/10.1590/s0100-204x2016000900071.
De Paz, J. M., C. Albert, F. Visconti, M. G. Jiménez, F. Ingelmo, and M. J. Molina. 2015. “A new methodology to assess the maximum irrigation rates at catchment scale using geostatistics and GIS.” Precis. Agric. 16 (5): 505–531. https://doi.org/10.1007/s11119-015-9392-y.
ESRI (Environmental Systems Research Institute). 2009. Using ArcGIS geostatistical analyst, 300. Redlands, CA: ESRI.
Evans, R. G., and B. A. King. 2010. “Site-specific sprinkler irrigation in a water limited future.” In Proc., 5th National Decennial Irrigation Conf. Proc. St Joseph, MI: American Society of Agricultural and Biological Engineers.
Evans, R. G., J. LaRue, K. C. Stone, and B. A. King. 2013. “Adoption of site-specific variable rate sprinkler irrigation systems.” Irrig. Sci. 31 (4): 871–887. https://doi.org/10.1007/s00271-012-0365-x.
FAO (Food and Agriculture Organization). 2022. “The role of water in agricultural development.” Accessed November 7, 2022. https://www.fao.org/4/y5582e/y5582e04.htm#bm04.
Fu, Q., W. Liu, S. Cui, T. Li, and D. Liu. 2017. “Geostatistical analysis of factors affecting irrigation water use efficiency on the Sanjiang plain.” Trans. ASABE 60 (2): 431–438. https://doi.org/10.13031/trans.11984.
Haghverdi, A., B. G. Leib, R. A. Washington-Allen, M. J. Buschermohle, and P. D. Ayers. 2016. “Studying uniform and variable rate center-pivot irrigation strategies with the aid of site-specific water production functions.” Comput. Electron. Agric. 123 (May): 327–340. https://doi.org/10.1016/j.compag.2016.03.010.
Hedley, C. B., and I. J. Yule. 2009. “Soil water status mapping and two variable-rate irrigation scenarios.” Precis. Agric. 10 (4): 342–355. https://doi.org/10.1007/s11119-009-9119-z.
Heermann, D. 1990. “Center-pivot design and evaluation.” Visions of the Future. Accessed March 15, 2020. https://www.ksre.k-state.edu/irrigate/oow/p03/Heermann_CenterPivotDesign-Eval.pdf.
Hodam, S., S. Sarkar, A. G. Marak, A. Bandyopadhyay, and A. Bhadra. 2017. “Spatial interpolation of reference evapotranspiration in India: Comparison of IDW and Kriging methods.” J. Inst. Eng. India Ser. A 98 (4): 511–524. https://doi.org/10.1007/s40030-017-0241-z.
Hyndman, R. J., and A. B. Koehler. 2006. “Another look at measures of forecast accuracy.” Int. J. Forecasting 22 (4): 679–688. https://doi.org/10.1016/j.ijforecast.2006.03.001.
Isaaks, E. H., and R. M. Srivastava. 1989. An introduction to applied geostatistics. New York: Oxford University Press.
Jiménez-Bello, M. Á., F. M. Alzamora, J. R. Castel, and D. S. Intrigliolo. 2011. “Validation of a methodology for grouping intakes of pressurized irrigation networks into sectors to minimize energy consumption.” Agric. Water Manage. 102 (1): 46–53. https://doi.org/10.1016/j.agwat.2011.10.005.
Journel, A. G., and C. J. Huijbregts. 1978. Vol. 600 of Mining geostatistics. London: Academic Press.
Kerry, R., and M. A. Oliver. 2008. “Determining nugget: Sill ratios of standardized variograms from aerial photographs to krige sparse soil data.” Precis. Agric. 9 (1–2): 33–56. https://doi.org/10.1007/s11119-008-9058-0.
King, B. A., and R. W. Wall. 2000. “Distributed instrumentation for optimum control of variable speed electric pumping plants with center-pivots.” Appl. Eng. Agric. 16 (1): 45. https://doi.org/10.13031/2013.4993.
Knox, J. W., M. G. Kay, and E. K. Weatherhead. 2012. “Water regulation, crop production, and agricultural water management—Understanding farmer perspectives on irrigation efficiency.” Agric. Water Manage. 108 (Jun): 3–8. https://doi.org/10.1016/j.agwat.2011.06.007.
Kumar, A., S. Maroju, and A. Bhat. 2007. “Application of ArcGIS geostatistical analyst for interpolating environmental data from observations.” Environ. Prog. 26 (Jun): 220–225. https://doi.org/10.1002/ep.10223.
Li, J., H. Wan, and S. Shang. 2020. “Comparison of interpolation methods for mapping layered soil particle-size fractions and texture in an arid oasis.” Catena 190 (May): 104514. https://doi.org/10.1016/j.catena.2020.104514.
Mcbratney, A. B., and R. Webster. 1986. “Choosing functions for semi-variograms of soil properties and fitting them to sampling estimates.” J. Soil Sci. 37 (4): 617–639. https://doi.org/10.1111/j.1365-2389.1986.tb00392.x.
Mendoza, C. J. C., and J. A. Frizzone. 2013. “Energy savings in center-pivot irrigation due to improved uniformity of water distribution.” Rev. Bras. Agri. Irrig. 6 (3): 184–197. https://doi.org/10.7127/rbai.v6n300083.
Miller, K. A., J. D. Luck, D. M. Heeren, T. Lo, D. L. Martin, and J. B. Barker. 2017. “A geospatial variable rate irrigation control scenario evaluation methodology based on mining root zone available water capacity.” Precis. Agric. 19 (Mar): 666–683. https://doi.org/10.1007/s11119-017-9548-z.
Moharana, P. C., R. K. Jena, and U. K. Pradhan. 2020. “Geostatistical and fuzzy clustering approach for delineation of site-specific management zones and yield-limiting factors in irrigated hot arid environment of India.” Precis. Agric. 21 (Mar): 426–448. https://doi.org/10.1007/s11119-019-09671-9.
Nguyen, A. T., A. L. Thompson, K. Sudduh, and E. Vories. 2015. “Automating variable rate irrigation management prescription for center-pivots from field data maps.” In Proc., 2015 ASABE/IA Irrigation Symp.: Emerging Technologies for Sustainable Irrigation-A Tribute to the Career of Terry Howell, Sr. Conf. Proc., 1–14. St Joseph, MI: American Society of Agricultural and Biological Engineers.
Oliver, M. A., and R. Webster. 2014. “A tutorial guide to geostatistics: Computing and modelling variograms and kriging.” Catena 113 (Mar): 56–69. https://doi.org/10.1016/j.catena.2013.09.006.
Perea, R. G., A. Daccache, J. R. Díaz, E. C. Poyato, and J. W. Knox. 2018. “Modelling impacts of precision irrigation on crop yield and in-field water management.” Precis. Agric. 19 (3): 497–512. https://doi.org/10.1007/s11119-017-9535-4.
Phasinam, K., T. Kassanuk, P. P. Shinde, C. M. Thakar, D. K. Sharma, M. K. Mohiddin, and A. W. Rahmani. 2022. “Application of IoT and cloud computing in automation of agriculture irrigation.” J. Food Qual. 2022 (Mar): 1–8. https://doi.org/10.1155/2022/8285969.
Pyrcz, M. J., and C. V. Deutsch. 2003. “The whole story on the hole effect.” Geostatistical Assoc. Australas. Newsl. 18 (May): 3–5.
QGIS Development Team. 2018. “QGIS geographic information system.” Open Source Geospatial Foundation Project. Accessed July 10, 2019. http://www.qgis.org.
Sandri, D., and D. D. A. Cortez. 2009. “Performance parameters of sixteen center-pivot irrigation equipment.” Cienc. Agrotecnol. 33 (1): 271–278. https://doi.org/10.1590/S1413-70542009000100037.
Santos, B. P., R. A. G. Siqueira, J. A. de Aragão Villar, and M. A. V. Freitas. 2022. “Agricultura e Irrigação no Brasil no cenário das Mudanças Climáticas.” Rev. Tecnol. Gestão Sustentável 1 (2). https://doi.org/10.17271/rtgs.v1i2.3158.
Scaloppi, E. J., and R. G. Allen. 1993. “Hydraulics of irrigation laterals: Comparative analysis.” J. Irrig. Drain. Eng. 119 (1): 91–115. https://doi.org/10.1061/(ASCE)0733-9437(1993)119:1(91).
Sukkuea, A., and A. Heednacram. 2022. “Prediction on spatial elevation using improved kriging algorithms: An application in environmental management.” Expert Syst. Appl. 207 (May): 117971. https://doi.org/10.1016/j.eswa.2022.117971.
Tabuada, M. A. 2011. “Hydraulics of Center-pivot laterals: Complete analysis of friction head loss.” J. Irrig. Drain. Eng. 137 (8): 513–523. https://doi.org/10.1061/(ASCE)IR.1943-4774.0000314.
Tarjuelo, J. M., J. A. Rodriguez-Diaz, R. Abadía, E. Camacho, C. Rocamora, and M. A. Moreno. 2015. “Efficient water and energy use in irrigation modernization: Lessons from Spanish case studies.” Agric. Water Manage. 162 (Mar): 67–77. https://doi.org/10.1016/j.agwat.2015.08.009.
Webster, R., and M. A. Oliver. 1992. “Sample adequately to estimate variograms of soil properties.” J. Soil Sci. 43 (1): 177–192. https://doi.org/10.1111/j.1365-2389.1992.tb00128.x.
Webster, R., and M. A. Oliver. 2007. Geostatistics for environmental scientists. New York: Wiley.
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Published In
Journal of Irrigation and Drainage Engineering
Volume 150 • Issue 6 • December 2024
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© 2024 American Society of Civil Engineers.
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Received: May 3, 2023
Accepted: Jun 10, 2024
Published online: Aug 21, 2024
Published in print: Dec 1, 2024
Discussion open until: Jan 21, 2025
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