Exploring non‑conventional irrigation methods and drone‑based monitoring to enhance water use efciency: a case of rice cultivation in Colombia
Climate variability in Colombia threatens water supplies for rice and other crops, highlighting the urgent need for efficient irrigation techniques. This study was conducted over three growing seasons in the Tolima region and evaluated three irrigation techniques: cascade distribution (CD), multip...
| Autores principales: | , , , , , , |
|---|---|
| Formato: | article |
| Lenguaje: | Inglés |
| Publicado: |
Springer Science and Business Media Deutschland GmbH
2025
|
| Materias: | |
| Acceso en línea: | https://link.springer.com/article/10.1007/s00271-025-01025-w http://hdl.handle.net/20.500.12324/41153 https://doi.org/10.1007/s00271-025-01025-w |
| id |
RepoAGROSAVIA41153 |
|---|---|
| record_format |
dspace |
| institution |
Corporación Colombiana de Investigación Agropecuaria |
| collection |
Repositorio AGROSAVIA |
| language |
Inglés |
| topic |
Riego - F06 Preparación del suelo - F07 Oryza sativa Riego Cultivo Uso del agua Transitorios http://aims.fao.org/aos/agrovoc/c_5438 http://aims.fao.org/aos/agrovoc/c_3954 http://aims.fao.org/aos/agrovoc/c_1972 http://aims.fao.org/aos/agrovoc/c_16065 |
| spellingShingle |
Riego - F06 Preparación del suelo - F07 Oryza sativa Riego Cultivo Uso del agua Transitorios http://aims.fao.org/aos/agrovoc/c_5438 http://aims.fao.org/aos/agrovoc/c_3954 http://aims.fao.org/aos/agrovoc/c_1972 http://aims.fao.org/aos/agrovoc/c_16065 Martínez Vega, Ronald Ricardo Ouazaa, Sofane De Swaef, Tom Chaali, Nesrine Garré, Sarah Jaramillo Barrios, Camilo Ignacio Moreno Fonseca, Liz Patricia Exploring non‑conventional irrigation methods and drone‑based monitoring to enhance water use efciency: a case of rice cultivation in Colombia |
| description |
Climate variability in Colombia threatens water supplies for rice and other crops, highlighting the urgent need for efficient
irrigation techniques. This study was conducted over three growing seasons in the Tolima region and evaluated three
irrigation techniques: cascade distribution (CD), multiple inlet rice irrigation (MIRI), and alternate wetting and drying
combined with MIRI (AWD + MIRI). The focus was on optimizing water usage, sustaining grain yield, and leveraging
vegetation indices for irrigation monitoring. Key findings revealed that visual soil moisture monitoring in light-textured
soils enabled substantial irrigation reductions. MIRI reduced water usage by 22%–54%, while AWD + MIRI achieved
reductions of 48%–65% compared to CD, with no significant grain yield loss. CD, however, demonstrated the lowest water
productivity. Vegetation indices measured peaked during the reproductive stage, aligning with maximum biomass. Notably,
MIRI consistently exhibited superior vegetation index values, particularly in growing season 2 (GS2) and growing season
3 (GS3), whereas CD underperformed. Variability analyses highlighted Greener area (GGA) as a more sensitive index,
whereas Normalized Difference Vegetation Index (NDVI) demonstrated a lower capacity to capture crop variability for
irrigation monitoring. These findings emphasize that adopting the most water-efficient irrigation method identified in this
study, AWD + MIRI, coupled with GGA monitoring, can enhance water use efficiency without compromising yield. This
approach offers a sustainable path forward for Colombian rice cultivation under the growing pressures of climate variability. |
| format |
article |
| author |
Martínez Vega, Ronald Ricardo Ouazaa, Sofane De Swaef, Tom Chaali, Nesrine Garré, Sarah Jaramillo Barrios, Camilo Ignacio Moreno Fonseca, Liz Patricia |
| author_facet |
Martínez Vega, Ronald Ricardo Ouazaa, Sofane De Swaef, Tom Chaali, Nesrine Garré, Sarah Jaramillo Barrios, Camilo Ignacio Moreno Fonseca, Liz Patricia |
| author_sort |
Martínez Vega, Ronald Ricardo |
| title |
Exploring non‑conventional irrigation methods and drone‑based monitoring to enhance water use efciency: a case of rice cultivation in Colombia |
| title_short |
Exploring non‑conventional irrigation methods and drone‑based monitoring to enhance water use efciency: a case of rice cultivation in Colombia |
| title_full |
Exploring non‑conventional irrigation methods and drone‑based monitoring to enhance water use efciency: a case of rice cultivation in Colombia |
| title_fullStr |
Exploring non‑conventional irrigation methods and drone‑based monitoring to enhance water use efciency: a case of rice cultivation in Colombia |
| title_full_unstemmed |
Exploring non‑conventional irrigation methods and drone‑based monitoring to enhance water use efciency: a case of rice cultivation in Colombia |
| title_sort |
exploring non‑conventional irrigation methods and drone‑based monitoring to enhance water use efciency: a case of rice cultivation in colombia |
| publisher |
Springer Science and Business Media Deutschland GmbH |
| publishDate |
2025 |
| url |
https://link.springer.com/article/10.1007/s00271-025-01025-w http://hdl.handle.net/20.500.12324/41153 https://doi.org/10.1007/s00271-025-01025-w |
| work_keys_str_mv |
AT martinezvegaronaldricardo exploringnonconventionalirrigationmethodsanddronebasedmonitoringtoenhancewateruseefciencyacaseofricecultivationincolombia AT ouazaasofane exploringnonconventionalirrigationmethodsanddronebasedmonitoringtoenhancewateruseefciencyacaseofricecultivationincolombia AT deswaeftom exploringnonconventionalirrigationmethodsanddronebasedmonitoringtoenhancewateruseefciencyacaseofricecultivationincolombia AT chaalinesrine exploringnonconventionalirrigationmethodsanddronebasedmonitoringtoenhancewateruseefciencyacaseofricecultivationincolombia AT garresarah exploringnonconventionalirrigationmethodsanddronebasedmonitoringtoenhancewateruseefciencyacaseofricecultivationincolombia AT jaramillobarrioscamiloignacio exploringnonconventionalirrigationmethodsanddronebasedmonitoringtoenhancewateruseefciencyacaseofricecultivationincolombia AT morenofonsecalizpatricia exploringnonconventionalirrigationmethodsanddronebasedmonitoringtoenhancewateruseefciencyacaseofricecultivationincolombia |
| _version_ |
1842255633106075648 |
| spelling |
RepoAGROSAVIA411532025-08-30T03:00:39Z Exploring non‑conventional irrigation methods and drone‑based monitoring to enhance water use efciency: a case of rice cultivation in Colombia Exploring non‑conventional irrigation methods and drone‑based monitoring to enhance water use efciency: a case of rice cultivation in Colombia Martínez Vega, Ronald Ricardo Ouazaa, Sofane De Swaef, Tom Chaali, Nesrine Garré, Sarah Jaramillo Barrios, Camilo Ignacio Moreno Fonseca, Liz Patricia Riego - F06 Preparación del suelo - F07 Oryza sativa Riego Cultivo Uso del agua Transitorios http://aims.fao.org/aos/agrovoc/c_5438 http://aims.fao.org/aos/agrovoc/c_3954 http://aims.fao.org/aos/agrovoc/c_1972 http://aims.fao.org/aos/agrovoc/c_16065 Climate variability in Colombia threatens water supplies for rice and other crops, highlighting the urgent need for efficient irrigation techniques. This study was conducted over three growing seasons in the Tolima region and evaluated three irrigation techniques: cascade distribution (CD), multiple inlet rice irrigation (MIRI), and alternate wetting and drying combined with MIRI (AWD + MIRI). The focus was on optimizing water usage, sustaining grain yield, and leveraging vegetation indices for irrigation monitoring. Key findings revealed that visual soil moisture monitoring in light-textured soils enabled substantial irrigation reductions. MIRI reduced water usage by 22%–54%, while AWD + MIRI achieved reductions of 48%–65% compared to CD, with no significant grain yield loss. CD, however, demonstrated the lowest water productivity. Vegetation indices measured peaked during the reproductive stage, aligning with maximum biomass. Notably, MIRI consistently exhibited superior vegetation index values, particularly in growing season 2 (GS2) and growing season 3 (GS3), whereas CD underperformed. Variability analyses highlighted Greener area (GGA) as a more sensitive index, whereas Normalized Difference Vegetation Index (NDVI) demonstrated a lower capacity to capture crop variability for irrigation monitoring. These findings emphasize that adopting the most water-efficient irrigation method identified in this study, AWD + MIRI, coupled with GGA monitoring, can enhance water use efficiency without compromising yield. This approach offers a sustainable path forward for Colombian rice cultivation under the growing pressures of climate variability. Arroz-Oryza sativa 2025-08-29T17:25:02Z 2025-08-29T17:25:02Z 2025-05 2025 article Artículo científico http://purl.org/coar/resource_type/c_2df8fbb1 info:eu-repo/semantics/article https://purl.org/redcol/resource_type/ART http://purl.org/coar/version/c_970fb48d4fbd8a85 https://link.springer.com/article/10.1007/s00271-025-01025-w 0342-7188 http://hdl.handle.net/20.500.12324/41153 https://doi.org/10.1007/s00271-025-01025-w reponame:Biblioteca Digital Agropecuaria de Colombia instname:Corporación colombiana de investigación agropecuaria AGROSAVIA eng Irrigation Science 1 3 1 19 Adhikary PP, Mohanty S, Rautaray SK, Manikandan N, Mishra A (2023) Alternate wetting and drying water management can reduce phosphorus availability under lowland rice cultivation irrespective of nitrogen level. Environ Monit Assess 195:1420. https:// doi. org/ 10. 1007/ s10661- 023- 12052-5 Barnes EM, Clarke TR, Richards SE, Colaizzi PD, Haberland J, Kostrzewski M, Waller P, Choi C, Riley E, Thompson T, Lascano RJ, Li H, Moran MS (2000) Coincident detection of crop water stress, nitrogen status and canopy density using ground-based multispectral data. In: Proceedings of the fifth international conference on precision agriculture 2000. Bloomington, MN, USA Boonjung H, Fukai S (1996) Effects of soil water deficit at different growth stages on rice growth and yield under upland conditions. 2. Phenology, biomass production and yield. Field Crop Res 48:47– 55. https:// doi. org/ 10. 1016/ 0378- 4290(96) 00039-1 Bouman BAM, Peng S, Castaneda AR, Visperas RM (2005) Yield and water use of irrigated tropical aerobic rice systems. Agr Water Manage 74(2):87–105. https:// doi. org/ 10. 1016/j. agwat. 2004. 11. 007 Bwire D, Saito H, Mugisha M, Nabunya V (2022) Water productivity and harvest index response of paddy rice with alternate wetting and drying practice for adaptation to climate change. Water. https:// doi. org/ 10. 3390/ w1421 3368 Carrijo DR, Akbar N, Reis AFB, Li C, Gaudin ACM, Parikh SJ, Green PG, Linquist BA (2018) Impacts of variable soil drying in alternate wetting and drying rice systems on yields, grain arsenic concentration and soil moisture dynamics. Field Crop Res 222:101–110. https:// doi. org/ 10. 1016/j. fcr. 2018. 02. 026 Carrijo DR, Lundy ME, Linquist BA (2017) Rice yields and water use under alternate wetting and drying irrigation: a meta-analysis. Field Crop Res 203:173–180. https:// doi. org/ 10. 1016/j. fcr. 2016. 12. 002 Casadeús J, Kaya J, Bort J, Nachit MM, Araus JL, Amor S, Ferrazzano G, Maalouf F, Maccaferri M, Martos V, Ouabbou H, Villegas D (2007) Using vegetation indices derived from conventional digital cameras as selection criteria for wheat breeding in water-limited environments. Ann Appl Bio 150:227–236. https:// doi. org/ 10. 1111/j. 1744- 7348. 2007. 00116.x Chaali N, Ouazaa S, Jaramillo-Barrios CI, Garré S (2024) Enhancing irrigation management: unsupervised machine learning coupled with geophysical and multispectral data for informed decisionmaking in rice production. Smart Agr Technol 9:100635. https:// doi. org/ 10. 1016/j. atech. 2024. 100635 Chlapecka JL, Hardke JT, Roberts TL, Mann MG, Ablao A (2021) Scheduling rice irrigation using soil moisture thresholds for furrow irrigation and intermittent flooding. Agron J 113(2):1258– 1270. https:// doi. org/ 10. 1002/ agj2. 20600 Cortolima (2016) Entorno regional del complejo de páramos “Los nevados” en jurisdicción de la corporación autónoma regional del Tolima - Cortolima. Ibagué, 2016. https:// corto lima. gov. co/ images/ estud io/ param os/ ENTOR NO_ REGIO NAL_ DEL_ COMPL EJO_ DE_ PÁRAMOS_ PN. N._ LOS_ NEVAD OS_ 2016_p. pdf. Accessed 15 September 2023 Datta A, Ullah H, Ferdous Z (2017) Water management in rice. In: Chauhan BS, Jabran K, Mahajan G (eds) Rice production worldwide. Springer International Publishing, Cham, Switzerland, pp 255–277. https:// doi. org/ 10. 1007/ 978-3- 319- 47516-5_ 11 dela Torre DMG, Gao J, Macinnis-Ng C (2021) Remote sensing-based estimation of rice yields using various models: a critical review. Geo-Spat Inf Sci 24(4):580–603. https:// doi. org/ 10. 1080/ 10095 020. 2021. 19366 56 de Lima IP, Jorge RG, de Lima JLMP (2021) Remote sensing monitoring of rice fields: towards assessing water saving irrigation management practices. Front Remote Sens. https:// doi. org/ 10. 3389/ frsen. 2021. 762093 De Swaef T, Maes WH, Aper J, Baert J, Cougnon M, Reheul D, Steppe K, Roldán-Ruiz I, Lootens P (2021) Applying RGB- and thermalbased vegetation indices from UAVs for high-throughput field phenotyping of drought tolerance in forage grasses. Remote Sens- Basel 13:147. https:// doi. org/ 10. 3390/ rs130 10147 Easterday K, Kislik C, Dawson TE, Hogan S, Kelly M (2019) Remotely sensed water limitation in vegetation: insights from an experiment with unmanned aerial vehicles (UAVs). Remote Sens-Basel 11:1853. https:// doi. org/ 10. 3390/ rs111 61853 Fan L, Fang S, Fan J, Wang Y, Zhan L, He Y (2024) Rice yield estimation using machine learning and feature selection in Hilly and Mountainous Chongqing, China. Agric-Basel 14:1615. https:// doi. org/ 10. 3390/ agric ultur e1409 1615 FAO (2009) ETo Calculator version 3.1. https:// www. fao. org/ filea dmin/ user_ upload/ faowa ter/ Appli catio ns/ EToCa lcula tor64 Bit. zip. Accessed 15 May 2021 Fedearroz - FNA (2012) Guía de trabajo - Adopción masiva de tecnología. Naxos Editores Bogotá, Colombia. p 27. https:// fedea rroz- websi te. s3. amazo naws. com/ media/ docum ents/ Guia_ de_ traba jo_ baja. pdf. Accessed 15 April 2021 Feng L, Bouman BAM, Tuong TP, Cabangon RJ, Li Y, Lu G, Feng Y (2007) Exploring options to grow rice using less water in northern China using a modelling approach I. Field experiments and model evaluation. Agr Water Manage 88:1–13. https:// doi. org/ 10. 1016/j. agwat. 2006. 10. 006 Ferreira S, Sánchez JM, Gonçalves JM (2023) A remote-sensingassisted estimation of water use in rice paddy fields: a study on Lis Valley Portugal. Agron-Basel 13(5):1357. https:// doi. org/ 10. 3390/ agron omy13 051357 Garcia L (2014) Caracterización de las respuestas fisiológicas y bioquímicas en tres clones de cacao (Theobroma cacao L.) sometidos a diferentes niveles de déficit hídrico. Dissertation, Facultad de Ciencias Agrarias, Universidad Nacional de Colombia García M, Piñeros A, Bernal F, Ardila E (2012) Variabilidad climática, cambio climático y el recurso hídrico en Colombia. Revista De Ingeniería. 36:60–64. https:// doi. org/ 10. 16924/ revin ge. 36. 11 González-Betancourt M, Mayorga-Ruíz ZL (2018) Normalized difference vegetation index for rice management in el Espinal, Colombia. DYNA Colombia. 85(205):47–56. https:// doi. org/ 10. 15446/ dyna. v85n2 05. 69516 Henry C, Hardke J, Krutz J, Massey J, Reba M, Adviento-Borbe A (2017) using alternate wetting and drying (AWD) rice flood management. RICE INFORMATION. Division of Agriculture. Research & Extension. University of Arkansas System. https:// www. uaex. uada. edu/ farm- ranch/ crops- comme rcial- horti cultu re/ rice/ 2017% 20Alt ernate% 20Wet ting% 20and% 20Dry ing% 20Rice% 20Man ageme nt. pdf. Accessed 01 September 2023 Hisham NHB, Hashim N, Saraf NM, Talib N (2022) Monitoring of Rice Growth Phases Using Multi-Temporal Sentinel-2 Satellite Image. In: 8th international conference on geomatics and geospatial technology 1051:012021. https:// doi. org/ 10. 1088/ 1755- 1315/ 1051/1/ 012021 IDEAM. Características climatológicas de ciudades principales y municipios turísticos. http:// www. ideam. gov. co/ docum ents/ 21021/ 21789/ 1Siti os+ turis ticos2. pdf/ cd410 6e9- d608- 4c29- 91cc- 16bee 9151d dd. Accessed 01 September 2023 IRRI (2015) IRRI Rice Production Manual: Steps to successful rice production. International Rice Research Institute, Los Baños (Philippines). http:// knowl edgeb ank. irri. org/ images/ docs/ 12- Steps- Requi red- for- Succe ssful- Rice- Produ ction. pdf. Accessed 30 September 2023 Ishfaq M, Farooq M, Zulfiqar U, Hussain S, Akbar N, Nawaz A, Anjum SA (2020) Alternate wetting and drying: a water-saving and ecofriendly rice production system. Agr Water Manage. https:// doi. org/ 10. 1016/j. agwat. 2020. 106363 Jabran K, Ullah E, Hussain M, Farooq M, Haider N, Chauhan BS (2015) Water saving, water productivity and yield outputs of fine-grain rice cultivars under conventional and water-saving rice production systems. Exp Agric 51(4):567–581. https:// doi. org/ 10. 1017/ S0014 47971 40004 77 Jorge J, Vallbé M, Soler JA (2019) Detection of irrigation inhomogeneities in an olive grove using the NDRE vegetation index obtained from UAV images. Eur J Remote Sens 52(1):169–177. https:// doi. org/ 10. 1080/ 22797 254. 2019. 15724 59 Marti-Jerez K, Català-Forner M, Tomàs N, Murillo G, Ortiz C, Sánchez-Torres MJ, Vitali A, Lopes MS (2023) Agronomic performance and remote sensing assessment of organic and mineral fertilization in rice fields. Front Plant Sci 14:1230012. https:// doi. org/ 10. 3389/ fpls. 2023. 12300 12 Massey JH, Reba ML, Adviento-Borbe MA, Chiu YL, Payne GK (2022) Direct comparisons of four irrigation systems on a commercial rice farm: irrigation water use efficiencies and water dynamics. Agr Water Manage. https:// doi. org/ 10. 1016/j. agwat. 2022. 107606 Massey JH, Smith MC, Vieira DAN, Adviento-Borbe MA, Reba ML, Vories ED (2018) expected irrigation reductions using multipleinlet rice irrigation under rainfall conditions of the lower Mississippi river valley. J Irrig Drain Eng 144(7):04018016. https:// doi. org/ 10. 1061/ (ASCE) IR. 1943- 4774. 00013 03 Mote K, Rao VP, Ramulu V, Kumar KA, Devi MU (2022) Performance of rice (Oryza sativa (L.)) under AWD irrigation practice: a brief review. Paddy Water Environ. https:// doi. org/ 10. 1007/ s10333- 021- 00873-4 Muangprakhon R, Kaewplang S (2021) Estimation of paddy rice plant height using UAV remote sensing. Eng Access 7(2):93–97. https:// doi. org/ 10. 14456/ mijet. 2021. 14 Muff S, Nilsen EB, O’Hara RB, Nater CR (2022) Rewritting result sections in the language of evidence. Trends Ecol Evol 37(3):203– 210. https:// doi. org/ 10. 1016/j. tree. 2021. 10. 009 Nawaz A, Rehman AU, Rehman A, Ahmad S, Siddique KHM, Farooq M (2022) Increasing sustainability for rice production systems. J Cereal Sci 103:103400. https:// doi. org/ 10. 1016/j. jcs. 2021. 103400 Ouazaa S, Jaramillo-Barrios CI, Chaali N, Quevedo Amaya YM, Calderon Carvajal JE, Montenegro Ramos O (2022) Towards sitespecific management zones delineation in rotational cropping systems: Application of a multivariate spatial clustering model based on soil properties. Geoderma Reg 30:e00564. https:// doi. org/ 10. 1016/j. geodrs. 2022. e00564 Perfetti J, Bravo-Ureta B, García A, Pantoja J, Delgado M, Blanco J, Jara R, Moraga C, Paredes G, Naranjo J, González L (2019) Adecuación de tierras y el desarrollo de la agricultura colombiana: políticas e instituciones. Fedesarrollo, Bogotá. https:// www. repos itory. fedes arrol lo. org. co/ bitst ream/ handle/ 11445/ 3763/ Repor_ Abril_ 2019_ Perfe tti_ et_ al. pdf? seque nce= 4& isAll owed=y. Accessed 10 October 2025 Purcell LC, Sinclair TR, Mcnew RW (2003) Drought avoidance assessment for summer annual crops using long-term weather data. Agron J 95:1566–1576. https:// doi. org/ 10. 2134/ agron j2003. 1566 Qin J, Hu F, Zhang B, Wei Z, Li H (2006) Role of straw mulching in non-continuously flooded rice cultivation. Agr Water Manage 83:252–260. https:// doi. org/ 10. 1016/j. agwat. 2006. 01. 001 Quevedo-Amaya YM, Beltrán-Medina JI, Hoyos-Cartagena JÁ, Calderón-Carvajal JE, Barragán-Quijano E (2020) Selection of sowing date and biofertilization as alternatives to improve the yield and profitability of the F68 rice variety. Agron Colomb 38(1):73–84. https:// doi. org/ 10. 15446/ agron. colomb. v38n1. 79803 R Core Team. R: a Language and Environment for Statistical Computing. Version 4.2.1. Ribeiro AS, e Sousa JA, Simões C, Martins LL, Dias L, Mendes R, Martins C (2021) Parshall flumes flow rate uncertainty including contributions of the model parameters and correlation effects. Measur Sens. https:// doi. org/ 10. 1016/j. measen. 2021. 100108 Rondeaux G, Steven M, Baret F (1996) Optimization of soil-adjusted vegetation indices. Remote Sens Environ 55(2):95–107. https:// doi. org/ 10. 1016/ 0034- 4257(95) 00186-7 Rouse JW, Haas RH, Schell JA, Deering DW (1974) Monitoring vegetation systems in the Great Plains with ERTS. In Third ERTS Symposium Vol. 1:301–317. Paper-A20. NASA Goddard Space Flight Center. https:// ntrs. nasa. gov/ citat ions/ 19740 022614 Sancho-Adamson M, Trillas MI, Bort J, Fernandez-Gallego JA, Romanyà J (2019) Use of RGB vegetation indexes in assessing early effects of verticillium wilt of olive in asymptomatic plants in high and low fertility scenarios. Remote Sens-Basel 11:607. https:// doi. org/ 10. 3390/ rs110 60607 Sheeny JE, Mitchell PL, Ferrer AB (2004) Bi-phasic growth patterns in rice. Ann Bot-London 94:811–817. https:// doi. org/ 10. 1093/ aob/ mch208 Triana-Martinez JC, Fernandez-Gallego JA, Barrero O, Borra-Serrano I, De Swaef T, Lootens P, Roldan-Ruiz I (2022) ViCTool: an open-source tool for vegetation indices computation of aerial raster images using python GDAL. In: Proceedings of EGU General Assembly. Vienna, Austria & Online. https:// doi. org/ 10. 5194/ egusp here- egu22- 8914 Vories ED, Tacker PL, Hogan R (2005) Multiple inlet approach to reduce water requirements for rice production. Appl Eng Agric 21(4):611–616. https:// doi. org/ 10. 13031/ 2013. 18571 Wei G, Chen H, Lin E, Hu X, Xie H, Cui Y, Luo Y (2023) Identification of water layer presence in paddy fields using UAV-based visible and thermal infrared imagery. Agronomy-Basel 13:1932. https:// doi. org/ 10. 3390/ agron omy13 071932 Wichelns D (2014) Do Estimates of Water Productivity Enhance Understanding of Farm-Level Water Management? Water-Basel 6:778–795. https:// doi. org/ 10. 3390/ w6040 778 Wichelns D (2015) Water productivity and water footprints are not helpful in determining optimal water allocations or efficient management strategies. Water Int 40(7):1059–1070. https:// doi. org/ 10. 1080/ 02508 060. 2015. 10862 55 Xue J, Su B (2017) Significant remote sensing vegetation indices: a review of developments and applications. J Sensors. https:// doi. org/ 10. 1155/ 2017/ 13536 91 Yuan Z, Cao Q, Zhang K, Ata-Ul-Karim ST, Tan Y, Zhu Y, Cao W, Liu X (2016) Optimal leaf positions for SPAD meter measurement in rice. Front Plant Sci. https:// doi. org/ 10. 3389/ fpls. 2016. 00719 Zhao X, Chen M, Xie H, Luo W, Wei G, Zheng S, Wu C, Khan S, Cui Y, Luo Y (2023) Analysis of irrigation demands of rice: Irrigation decision-making needs to consider future rainfall. Agr Water Manage. https:// doi. org/ 10. 1016/j. agwat. 2023. 108196 Zoebl D (2006) Is water productivity a useful concept in Agricultural Water Management? Agr Water Manage 84:265–273. https:// doi. org/ 10. 1016/j. agwat. 2006. 03. 002 Atribución-NoComercial-CompartirIgual 4.0 Internacional http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf application/pdf Colombia Springer Science and Business Media Deutschland GmbH Irrigation Science; (2025): Irrigation Science (May.);p. 1 - 19. |