Introduction
⌅In Ecuador, Manabí has the largest percentage of agricultural land (1,894,000 ha), followed by Guayas, Loja, Los Ríos, and Esmeraldas, being of vital importance to the Manabí economy (Instituto Nacional de Estadística y Censos, 2021INEC (INSTITUTO NACIONAL DE ESTADÍSTICA Y CENSOS): Encuesta de Superficie y Producción Agropecuaria Continua 2020. Contenido, INEC. Buenas cifras mejores vidas. Ecuador. 2021. Disponible en: https://www.ecuadorencifras.gob.ec/documentos/web-inec/Estadisticas_agropecuarias/espac/espac-2020/Presentacion .). Moreover, the climate has become unpredictable, causing changes in humidity, fog, temperatures, and rainfall, where constant variations in the amount, intensity, and temporal pattern of precipitation are observed (Su et al., 2023SU, Y.; WANG, J.; LI, J.; WANG, L.; WANG, K.; LI, A. GAO, L. Y WANG, Z.: “Cambios espaciotemporales y factores impulsores de la evapotranspiración de referencia y la evapotranspiración del cultivo para la producción de algodón en China desde 1960 hasta 2019” Frente. Reinar. Sci., 11, 11, 2023. ). Therefore, the accuracy of rainfall information is crucial for agronomy, hydrology, and meteorology (Ara, Lewis y Ostendorf, 2018ARA, I.; LEWIS, M. Y OSTENDORF, B.: “Análisis espacio-temporal del impacto del clima, la intensidad de los cultivos y los medios de riego: una evaluación de los determinantes del rendimiento del arroz.” Agricultura y seguridad alimentaria, 5(1),12, 2018. DOI: https://doi.org/10.1186/s40066-016-0061-9 .).
The distribution of water in irrigation systems requires technical and equitable planning, so that water resources are utilized efficiently and timely, and do not result in losses in agricultural production and quality (Zeleke et al., 2023ZELEKE, A.; TESFAYE, K.; TADESSE, T.; ALEM, T; ADEME, D. Y ENYEW, A.: “Análisis espaciotemporal de la variabilidad y tendencias de las precipitaciones y la temperatura para un sistema agrícola de maíz resiliente al clima en las principales zonas agroecológicas del noroeste de Etiopía,” Revista Internacional de Sostenibilidad Agrícola, 21(1), 11, 2023. DOI: https://doi.org/10.1080/14735903.2023.2255450 .). The analysis of precipitation behavior and its spatial and temporal variability constitutes an essential aspect for understanding current and future climatic processes (Liu et al., 2022LIU, Z.; JING, D.; HAN, Y. YU, J.; LU, T. Y ZHANGZHONG, L.: “Características de distribución espaciotemporal y análisis de factores que influyen en la evapotranspiración de referencia en la región de Beijing-Tianjin-Hebei de 1990 a 2019 bajo el cambio climático,” Sostenibilidad, 14(10), 1-12, 2022. DOI: https://doi.org/10.3390/su14106277 .).
It is worth mentioning that climate change has altered weather patterns worldwide, directly affecting agricultural production Variations in temperature, rainfall, and water availability affect crop yields, while the increase in temperatures accelerates soil evaporation, which in the long term causes more frequent and longer-lasting droughts each year (Yin et al., 2023YIN, D. W.; XIAO, N. C.; MING, Z. X.; GUO, H. ; ZHANG, Y. Y ZHANG, Y.: “Análisis espaciotemporal de la variabilidad de la humedad del suelo y su factor determinante.” Sensores Remotos, 15(24), 13, 2023. DOI: https://doi.org/10.3390/rs15245768 .), Additionally, climate variability and water management in agricultural areas require modern techniques that allow for a better understanding of the spatial distribution of precipitation and evapotranspiration, which is essential for irrigation planning (Ashraf et al., 2023ASHRAF, H.; QAMAR, S.; 2 , RIAZ, N.; SHAMSHIRI, R.R.; SULTAN, M.; KHALID, B.; IBRAHIM, S.M.; IMRAN, M. Y KHAN, M.U.: “Estimación espaciotemporal de la evapotranspiración de referencia para Aplicaciones agrícolas en Punjab, Pakistán” Agricultura, 13, 13, 2023. ; Barros de Sousa et al., 2023BARROS DE SOUSA, L.; DE ASSUNCAO M., A.A.; DA SILVA, M.V.; BRITO. A.T.A.; DE CARVALHO, A.A.; DA SILVA, T.G.F. Y PEDROSO DE LIMA, J.L.M.: “Análisis espaciotemporal de las precipitaciones y las sequías en una cuenca semiárida de Brasil: dinámica de uso y cobertura del suelo,” Sensores Remotos., 15(10), 9, 2023. DOI: https://doi.org/10.3390/rs15102550 .). Under arid conditions, the correlation between evapotranspiration and precipitation increases, with evapotranspiration being a determining factor of the water balance (Chakroun et al., 2023CHAKROUN, H.; ZEMNI, N.; BENHMID, A.; DELLALY, V.; SLAMA, F.; BOUKSILA, F. Y BERNDTSSON, R.: “Evapotranspiración en clima semiárido: teledetección versus simulación de agua del suelo,” Sensores, 23(5), 9, 2023. DOI: https://doi.org/10.3390/s23052823 .).
According to Alamri et al., (2023)ALAMRI, Y.; ALRWIS, K.; GHANEM; KAMARA, S.; ALAAGIB, S. Y ALDAWDAHI, N.: “El nexo económico entre la energía, el consumo de agua y la producción de alimentos en Arabia Saudita”. Economías, 11(4), 1-14, 2023 DOI: https://doi.org/10.3390/economies11040113 ., agriculture consumes 70% of the world's freshwater, and it is estimated that by 2050, food production will need to increase by 70% due to population growth and the rise in purchasing power in developing countries. In Ecuador, 80% of the water allocated to agriculture irrigates only one-third of the crops, while the rest depends exclusively on rain (Abbas et al., 2022ABBAS, S.; YASEEN, M.; LATIF, Y.; WASEEM, M.; MUHAMMAD, S.; KEBEDE, L. M.; SHER, S.; ALI, I. M.; ADNAN, M. Y HASSAN, K. T.: “Análisis espaciotemporal de los extremos climáticos en la parte superior Cuenca del Indo, Pakistán,” Agua, 14(11), 17, 2022. DOI: https://doi.org/10.3390/w14111718 .).
In Ecuador, it is estimated that the internal renewable water resources amount to approximately 442 km³ annually, of which about 82% is allocated to agriculture, highlighting the high dependence of the productive sector on available water (Chuncho y Chuncho, 2019CHUNCHO, C. Y CHUNCHO, G. “Páramos del Ecuador, Importancia y afectaciones: Una revisión.” Bosques Latitud Cero, 9(2), 71-83, 2019. ). It is worth mentioning that a precise understanding of hydrological variables, such as effective precipitation, is essential for optimizing water management in agriculture (Wang et al., 2020WANG, T.; DU, C.; NIE, T.; YI, S. Z.; ZHU, S.; FENG, C.; DAI, C.; CHU, L.; LIU, Y. Y LIANG, Q.: “Análisis espaciotemporal de las necesidades de agua del maíz en la provincia de Heilongjiang, China, durante el período 1960-2015.” Agua, 12(9), 10, 2020. DOI: https://doi.org/10.3390/w12092472 .). In the coastal cantons such as Guayaquil, Machala, Portoviejo, Babahoyo, Santa Elena, and Esmeraldas, the influence of the sea causes an increase in rainfall between December and March, followed by a decrease Pérez y Domínguez (2019)PÉREZ, R. Y DOMÍNGUEZ, J.: “Irrigation Regime for Crops in Manabí, Ecuador: Proposal for Five Permanent Crops,” Revista Ciencias Técnicas Agropecuarias, 28(4), 63-72, 2019. . Según Villa et al., (2022)VILLA, C. A. O.; ONTIVEROS, C. R. E.; RUIZ, A. O.; GONZÁLEZ, S. A.; QUEVEDO, T. J. A. Y ORDOÑEZ, H. L. M.: “Variación espacio-temporal de la evapotranspiración de referencia a partir de métodos empíricos en Chihuahua, México,” Ingeniería agrícola y biosistemas, 13(1), 96-115, 2021. , climate change has intensified the effects on agricultural production, manifesting in rising temperatures and regional variations in precipitation, making it difficult to predict the future availability of water for irrigation.
The Sustainable Development Goal 13 highlights the need to act against climate change, due to the increase in extreme weather events, such as storms, floods, and droughts, which affect ecosystems and agricultural production (Organización de las Naciones Unidas, 2023ONU (ORGANIZACIÓN DE LAS NACIONES UNIDAS): En Manabí, Ecuador, la sostenibilidad radica en las tradiciones sagradas. 2023. Disponible en: https://unsdg.un.org/latest/stories/manabi-ecuador-sustainability-lies-sacred-traditions (Accessed: October 6, 2023).). In this context, the use of technological tools such as Geographic Information Systems (GIS) makes it possible to analyze the spatial and temporal variability of water resources, generate high-resolution climate models, and project future scenarios for climate change adaptation, contributing to sustainable water management and resilient agricultural development (Lars, 2021LARS, L. I.: Spatiotemporal Analysis of Variability in Soil Volumetric Water Content and Spatial. Statistical Methods for Management Zone Delineation for Variable Rate Irrigation. Tesis. Maestro en ciencia. Brigham Young University. EE.UU. 2021. Disponible en: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=10393&context=etd .; Koycegiz, 2024KOYCEGIZ, C.: “Análisis espaciotemporal de la variabilidad de las precipitaciones en una cuenca endorreica de Turquía con datos de experimentos regionales coordinados de reducción de escala climática regional.” Revista de ingeniería de Alejyría, 91, 368-381, 2024. DOI: https://doi.org/https://doi.org/10.1016/j.aej.2024.02.010 .).
Based on the above, the question arises: What is the spatial and temporal distribution of the variables that affect water deficit in Manabí for irrigation purposes? For this reason, this study aimed to analyze the spatial and temporal distribution of the variables that affect water deficit in Manabí for irrigation purposes.
Materials and methods
⌅The study focused on the province of Manabí, located to the north with Esmeraldas, to the south with Santa Elena and Guayas, to the east with Los Ríos and Santo Domingo de los Tsáchilas, and to the west with the Pacific Ocean (Figure 1). It has elevations of up to 500 meters above sea level and approximate coordinates of 4°40'00" S and 80°05'00" W.
In Manabí, the climate is influenced by the Pacific Ocean and ocean currents. The rainy season, from December to April, presents high temperatures and abundant precipitation typical of the humid tropical forest, while the dry season, influenced by the cold Humboldt current, is milder and with lower humidity, generating microclimates that affect agriculture and local activities. As seen in Figure 2, Manabí has 20 weather stations distributed to monitor climatic variables and support decision-making in agriculture and risk management.
There are 49 weather stations strategically distributed across various cantons, as detailed in Table 1.
| Código | Descripción | Tipo | Zona Hidro. | Latitud | Longitud | Altitud (m) | Instit. Propiet. |
|---|---|---|---|---|---|---|---|
| M0447 | 24 De mayo (Jaboncillo) | PV | 130 | 1° 16' 44" S | 80° 25' 6" W | 115 | INAMHI |
| M1234 | Yil-Unesum | CO | 120 | 1° 20' 49" S | 80° 32' 23" W | 378 | INAMHI |
| M1241 | Atascoso | PV | 0 | 1° 4' 21" S | 80° 0' 32" W | 497 | INAMHI |
| M1074 | Ayampe | PV | 120 | 1° 41' 0" S | 80° 47' 0" W | 0 | EX-C.R.M |
| M1217 | Bahía De Caráquez-Puce | CO | 100 | 0° 39' 34" S | 80° 23' 51" W | 12 | INAMHI |
| M1251 | Banchal | PV | - | 1° 38' 37" S | 80° 29' 13" W | 149 | INAMHI |
| M1077 | Bella Flor | PV | 110 | 1° 5' 0" S | 80° 7' 0" W | 0 | EX-C.R.M |
| M1088 | Botadero (Río Briceño) | PV | 90 | 0° 32' 0" S | 80° 16' 0" W | 0 | EX-C.R.M |
| M0163 | Boyacá | PV | 100 | 0° 34' 15" S | 80° 10' 41" W | 70 | INAMHI |
| M0450 | Camarones-Manabí | PV | 120 | 1° 7' 46" S | 80° 46' 38" W | 197 | INAMHI |
| M0171 | Camposano #2 | CO | 130 | 1° 35' 34" S | 80° 24' 4" W | 156 | INAMHI |
| M1233 | Cantagallo-Granja Unesum | CP | 120 | 1° 17' 13" S | 80° 43' 44" W | 64 | INAMHI |
| M0162 | Chone-U. Católica | CP | 100 | 0° 39' 51" S | 80° 2' 11" W | 36 | INAMHI |
| M0453 | Chorrillos | PV | 110 | 1° 3' 15" S | 80° 41' 20" W | 226 | INAMHI |
| M0458 | Colimes De Paján | PV | 130 | 1° 34' 42" S | 80° 30' 21" W | 200 | INAMHI |
| M1079 | Convento | PV | 90 | 0° 16' 0" S | 80° 2' 0" W | 0 | EX-C.R.M |
| M1205 | Cuaque Pedernales | PV | 60 | 0° 26' 0" N | 80° 3' 0" W | 0 | EX-C.R.M |
| M0451 | El Anegado | PV | 120 | 1° 28' 46" S | 80° 32' 19" W | 398 | INAMHI |
| M0160 | El Carmen | CO | 130 | 0° 15' 35" S | 79° 25' 37" W | 260 | INAMHI |
| M1230 | Espam-Mfl-Calceta | CP | 100 | 0° 49' 23" S | 80° 11' 1" W | 15 | INAMHI |
| M1076 | Guajabe | PV | 110 | 1° 6' 0" S | 80° 10' 0" W | 0 | EX-C.R.M |
| M0589 | Guale | PV | 130 | 1° 37' 32" S | 80° 14' 9" W | 40 | EX-CEDEGE |
| M1078 | Guale Ayampe | PV | 120 | 1° 41' 0" S | 80° 44' 0" W | 0 | EX-C.R.M |
| M0167 | Jama | CO | 90 | 0° 11' 49" S | 80° 15' 53" W | 46 | INAMHI |
| M0455 | Joa-Jipijapa | PV | 120 | 1° 21' 45" S | 80° 35' 40" W | 260 | INAMHI |
| M0169 | Julcuy | CO | 130 | 1° 28' 48" S | 80° 37' 56" W | 263 | INAMHI |
| M0462 | Junín | PV | 100 | 0° 56' 4" S | 80° 12' 30" W | 20 | INAMHI |
| M1089 | La Azucena | PV | 60 | 1° 4' 0" S | 79° 59' 0" W | 0 | EX-C.R.M |
| M1081 | La Colombia (Ayampe) | PV | 120 | 1° 40' 0" S | 80° 40' 0" W | 0 | EX-C.R.M |
| M0448 | La Laguna | PV | 110 | 1° 9' 10" S | 80° 37' 27" W | 235 | INAMHI |
| M1208 | La Teodomira | CP | 110 | 1° 9' 51" S | 80° 23' 24" W | 60 | INAMHI |
| M0047 | Manta-Inocar | CO | 120 | 0° 56' 3" S | 80° 44' 2" W | 3 | - |
| M0166 | Olmedo-Manabí | CO | 130 | 1° 23' 41" S | 80° 12' 25" W | 50 | INAMHI |
| M0623 | Palmeras Unidas (Palmar) | PV | 130 | 0° 15' 53" S | 79° 35' 48" W | 460 | EX-CEDEGE |
| M0005 | Portoviejo-Utm | AP | 110 | 1° 2' 15" S | 80° 27' 35" W | 46 | INAMHI |
| M1080 | Poza Honda | CP | 110 | 1° 7' 0" S | 80° 12' 0" W | 0 | EX-C.R.M |
| M0457 | Puerto Cayo | PV | 120 | 1° 20' 58" S | 80° 44' 11" W | 6 | INAMHI |
| M0464 | Río Chamotete-Jesús María | PV | 110 | 1° 2' 12" S | 80° 13' 58" W | 128 | INAMHI |
| M0454 | Río Chico En Alajuela | PV | 110 | 1° 3' 16" S | 80° 17' 33" W | 118 | INAMHI |
| M1091 | Río Grye (Chone) | PV | 100 | 0° 40' 0" S | 79° 59' 0" W | 0 | EX-C.R.M |
| M1105 | Río Grye Inamhi | PV | 100 | 0° 43' 52" S | 79° 56' 44" W | 124 | INAMHI |
| M1104 | Río Santo | PV | 100 | 0° 34' 7" S | 80° 0' 2" W | 75 | INAMHI |
| M0165 | Rocafuerte | CO | 110 | 0° 55' 21" S | 80° 26' 55" W | 20 | INAMHI |
| M0446 | San Isidro-Manabí | PV | 90 | 0° 22' 34" S | 80° 11' 1" W | 138 | INAMHI |
| M1090 | San Miguel | PV | 110 | 1° 2' 0" S | 80° 5' 0" W | 0 | EX-C.R.M |
| M0459 | San Pablo-Manabí | PV | 120 | 1° 34' 44" S | 80° 35' 30" W | 465 | INAMHI |
| M1092 | Sancán-Crm | PV | 120 | 1° 15' 0" S | 80° 35' 0" W | 0 | EX-C.R.M |
| M0449 | Sancán-Inamhi | PV | 110 | 1° 15' 29" S | 80° 35' 12" W | 255 | INAMHI |
| M0452 | Zapote | PV | 100 | 0° 56' 18" S | 80° 3' 20" W | 79 | INAMHI |
The precipitation data (Table 2) and evapotranspiration data (Table 3) were obtained from Pérez et al. (2018)PÉREZ, R. Y DOMÍNGUEZ, J.: “Irrigation Regime for Crops in Manabí, Ecuador: Proposal for Five Permanent Crops,” Revista Ciencias Técnicas Agropecuarias, 28(4), 63-72, 2019. and analyzed in this study, from the collection of information from all the meteorological stations in Manabí. However, only 20 of the 49 stations have sufficient statistical support for precipitation studies, and only 2 meet the minimum requirements for evapotranspiration.
| No. | Código Nuevo | Descripción | Año 75% prob. | Ene | Feb | Mar | Abr | May | Jun | Jul | Ago | Sep | Oct | Nov | Dic | Precipitación Anual (mm) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | M0005 | Portoviejo-Utm | 2011 | 63.10 | 122.40 | 20.30 | 69.40 | 0.30 | 42.50 | 4.50 | 0.00 | 0.10 | 1.30 | 0.00 | 31.30 | 355.20 |
| 2 | M0162 | Chone-U. Católica | 2005 | 119.00 | 189.80 | 105.50 | 319.00 | 4.70 | 1.40 | 0.80 | 0.20 | 1.50 | 2.50 | 1.10 | 57.40 | 802.90 |
| 3 | M0165 | Rocafuerte | 2011 | 25.80 | 112.00 | 29.50 | 73.80 | 0.00 | 6.40 | 0.50 | 0.00 | 1.00 | 0.00 | 0.00 | 5.30 | 254.30 |
| 4 | M0166 | Olmedo-Manabí | 2005 | 21.20 | 340.40 | 383.40 | 426.40 | 3.00 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | 0.00 | 37.00 | 1212.40 |
| 5 | M0167 | Jama | 1996 | 30.40 | 167.20 | 127.40 | 56.60 | 8.70 | 0.10 | 6.70 | 0.00 | 0.20 | 0.00 | 0.00 | 0.00 | 397.30 |
| 6 | M0169 | Julcuy | 2005 | 8.30 | 83.40 | 86.00 | 101.50 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 5.70 | 284.90 |
| 7 | M0171 | Camposano #2 | 2003 | 171.40 | 289.80 | 109.00 | 141.00 | 231.70 | 0.00 | 0.00 | 1.60 | 0.00 | 1.60 | 0.00 | 2.30 | 948.40 |
| 8 | M0447 | 24 de mayo (Jaboncillo) | 2004 | 87.20 | 182.50 | 263.50 | 72.70 | 111.70 | 5.80 | 7.90 | 0.20 | 4.30 | 4.00 | 0.80 | 0.00 | 740.60 |
| 9 | M0448 | La Laguna | 1990 | 63.10 | 52.40 | 24.60 | 15.00 | 0.00 | 1.50 | 8.00 | 16.80 | 2.60 | 3.70 | 8.20 | 4.90 | 200.80 |
| 10 | M0449 | Sancán-Inamhi | 2007 | 28.30 | 16.10 | 49.90 | 115.50 | 9.40 | 0.20 | 5.40 | 1.30 | 0.00 | 0.00 | 0.30 | 18.50 | 244.90 |
| 11 | M0450 | Camarones-Manabí | 2009 | 81.40 | 55.10 | 11.50 | 5.00 | 7.50 | 2.30 | 0.80 | 3.60 | 2.42 | 4.40 | 3.70 | 0.00 | 177.72 |
| 12 | M0451 | El Anegado | 1997 | 20.40 | 42.50 | 52.10 | 49.00 | 54.40 | 48.20 | 19.90 | 11.50 | 25.00 | 20.80 | 101.60 | 152.90 | 598.30 |
| 13 | M0453 | Chorrillos | 1993 | 18.70 | 166.40 | 53.20 | 13.80 | 7.30 | 5.70 | 4.70 | 4.20 | 6.10 | 5.90 | 3.90 | 2.00 | 291.90 |
| 14 | M0454 | Río Chico En Alajuela | 1991 | 136.20 | 113.70 | 144.60 | 98.40 | 50.20 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 23.50 | 566.60 |
| 15 | M0455 | Joa-Jipijapa | 2005 | 0.00 | 84.70 | 63.40 | 59.90 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 15.40 | 223.40 |
| 16 | M0457 | Puerto Cayo | 2011 | 54.40 | 71.00 | 0.00 | 28.00 | 2.40 | 8.50 | 18.20 | 12.30 | 1.00 | 8.90 | 0.00 | 17.20 | 221.90 |
| 17 | M0458 | Colimes de Paján | 1990 | 106.40 | 173.00 | 197.20 | 196.00 | 39.70 | 47.00 | 1.60 | 0.00 | 0.00 | 0.30 | 0.00 | 60.50 | 821.70 |
| 18 | M0459 | San Pablo-Manabí | 2010 | 167.70 | 179.00 | 232.20 | 182.80 | 42.00 | 5.90 | 11.00 | 2.00 | 0.80 | 0.40 | 14.80 | 101.90 | 940.50 |
| 19 | M0462 | Junín | 2000 | 127.70 | 208.70 | 158.30 | 106.28 | 39.88 | 18.30 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 26.50 | 685.66 |
| 20 | M0464 | Río Chamotete-Jesús María | 1991 | 136.60 | 141.50 | 272.50 | 130.10 | 68.70 | 31.50 | 0.00 | 2.30 | 0.90 | 0.00 | 14.40 | 21.90 | 820.40 |
| Código | Descrip. | Año 25% prob. | Este | Norte | Ene | Feb | Mar | Abr | May | Jun | Jul | Ago | Sep | Oct | Nov | Dic | Anual (mm) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| M0005 | Portoviejo-Utm | 2011 | 560110.5 | 9885319.8 | 146.8 | 125.5 | 149.5 | 149.2 | 145.7 | 127.2 | 133.7 | 145.7 | 142.0 | 146.0 | 141.9 | 139.8 | 1692.9 |
| M0162 | Chone-U. Católica | 2005 | 607223.7 | 9926579.1 | 129.4 | 117.2 | 140.7 | 133.3 | 125.3 | 110.5 | 115.2 | 120.3 | 134.8 | 129.2 | 128.7 | 126.4 | 1510.9 |
The method applied was descriptive, analytical, and deductive, using records from 20 meteorological stations with at least 13 years of observation. The necessary variables to calculate effective precipitation (Pe) and reference crop evapotranspiration (ETo) were analyzed. Using GIS, thematic maps were generated that reflect the spatial and temporal changes in Manabí, in order to support irrigation planning.
The effective precipitation (Pe) was determined using the USDA-SCS method proposed by McCuen (1982), which estimates the portion of the total precipitation (Pt) that is actually utilized by the crops. The formula applied was:
In this equation, Pe corresponds to the effective monthly precipitation in millimeters and Pt represents the total monthly precipitation. The calculations were carried out for each weather station and thirteen maps were generated, one for each month of the year and one general map, in order to visualize the spatial distribution of usable rainfall. The thresholds established by the method were applied to divide the values and thus identify areas with greater or lesser availability of effective water for crops.
The reference crop evapotranspiration (ETo) was calculated using the Hargreaves and Samani method (1985), which allows for the estimation of water loss thru evaporation and transpiration using temperature and solar radiation data. The expression used was:
In this formula, ETo represents the reference evapotranspiration in millimeters per day, Tmean the mean daily temperature, Tmax the maximum temperature, Tmin the minimum temperature, and Ra the extraterrestrial solar radiation. The calculation was performed monthly by season, applying the difference between the extreme temperatures multiplied by solar radiation, thus obtaining the water behavior in different climatic zones.
Finally, the water deficit (Dh) was determined based on the difference between the evapotranspiration of the reference crop and the effective precipitation, using the formula:
The water deficit (mm) represents the amount of water missing in the soil when evapotranspiration exceeds effective precipitation. This parameter allowed the identification of periods and areas with the highest water demand in Manabí.
For the creation of the maps, ArcGIS was used with a base map of Manabí (IGM shapefiles). The meteorological data were incorporated with their UTM coordinates and the Kriging and IDW interpolation methods were applied, which allowed for the representation of spatial variability and the definition of color scales that facilitate climatic interpretation in the province.
Results
⌅The present study presents the results of the spatial analysis of hydrological and climatological variables to determine the water deficit in Manabí, Ecuador. Effective precipitation, reference crop evapotranspiration (ETo), and water deficit were evaluated, applying georeferencing tools that allowed the generation of spatial variability maps.
These maps show how climatic conditions differ between areas, providing key information for agricultural planning, water resource management, and the reduction of climate risks in the province.
Analysis of the Thematic Maps of Effective Precipitation
⌅In Figure 3, the monthly and annual ranges of effective precipitation are shown, allowing for the observation of rainfall variations throughout the year, with the aim of analyzing its temporal distribution, as seen below.
In Figure 4, the monthly distribution of effective precipitation in Manabí is observed, where the heaviest rains are recorded between January and April in the north and center, especially at the Chone (M0162), Pichincha (M0164), Flavio Alfaro (M0160), Santa Ana (M0166), and Paján (M0448) stations, with values exceeding 100 mm/month. In Figure 5, the annual map confirms this trend, showing lower precipitation in coastal areas such as Manta (M0452), Montecristi (M0450), and Jaramijó (M0454), where the influence of the ocean reduces humidity
This table shows the spatial analysis of effective precipitation throughout the year, highlighting areas with the highest and lowest rainfall availability (Table 4).
| Periodo | Análisis |
|---|---|
| January-February | The highest precipitation was recorded in Chone, Pichincha, Bolívar, Junín, Flavio Alfaro, and Santa Ana, with values between ~72 and 120 mm/month. In contrast, coastal areas such as Manta, Montecristi, Jama, and Rocafuerte recorded the lowest values (<70 mm/month). |
| March-April | A contrasting distribution was maintained: Santa Ana, Olmedo, and Paján reached over 100 mm/month, while Manta, Montecristi, and Jaramijó recorded minimal precipitation (~5-65 mm/month). |
| May-June | A marked decrease in rainfall was evident throughout the province. Only Paján exceeded 100 mm/month, while most stations recorded values below 40 mm/month. |
| July-August | Precipitation was very low (<25 mm/month), with northern areas almost without any recorded rainfall. |
| September-October | The scarcity continued, with values below 24 mm/month, with light rains concentrated in the south. |
| November-December | An increase was observed in the south, especially in Puerto López, Paján, and 24 de mayo, reaching up to 115 mm/month. |
| Annual | The highest precipitation was concentrated in Flavio Alfaro, Chone, Pichincha, Santa Ana, and Paján; the lowest in Manta, Montecristi, and Jaramijó. |
Analysis of Thematic Maps of Reference Crop Evapotranspiration
⌅In Figure 6, the monthly and annual ranges of evapotranspiration for the reference crop are presented, showing the variations in water demand throughout the year, identifying the periods of greatest and least water loss, which are essential for the efficient management of water resources in the study area.
In Figure 7, the monthly distribution of reference crop evapotranspiration is observed, showing higher values in the south of Manabí, mainly in Portoviejo (M0005), Santa Ana (M0166), Paján (M0448), and Jipijapa (M0455), with peaks of up to 154 mm/month between May and June. In Figure 8, the annual behavior shows that the highest rates are concentrated in Montecristi (M0450), Portoviejo (M0005), and Jipijapa (M0455), while the north, represented by Chone-U. Católica (M0162) and Flavio Alfaro (M0160), maintains lower values due to its higher humidity.
Table 5 presents the spatial analysis of reference crop evapotranspiration (ETo) throughout the year, highlighting the areas with the highest and lowest irrigation demands.
| Period | Analysis |
|---|---|
| January-February | The highest rates were recorded in the southern zone (Portoviejo, Santa Ana, Paján) with up to ~146 mm/month, while the northern zone showed lower values (~119 mm/month). |
| March-April | The trend persisted with high values in the south (~149 mm/month) and lower in the north. |
| May-June | The peak was reached (~154 mm/month) in Portoviejo, Olmedo, and Jipijapa, slightly decreasing toward the north (~132 mm/month). July-August Evapotranspiration remained high in the south (127-145 mm/month) and moderate in the north. |
| July-August | Evapotranspiration remained high in the south (127-145 mm/month) and moderate in the north. |
| September-October | The values stabilized with maxima in the south (~146 mm/month) and minima in the north (~129 mm/month). |
| November-December | Rates of up to 140 mm/month were observed in the south and 126 mm/month in the north |
| Annual | The highest rates were concentrated in Montecristi, Portoviejo, and Jipijapa; the lowest in the northern area. |
Analysis of the Thematic Maps of Water Deficit
⌅In Figure 9 indicates the monthly and annual ranges of water deficit, allowing the identification of periods when the irrigation demand exceeds availability, as observed below.
In Figure 10, the monthly distribution of water deficit is observed, with higher values in the south and coastal area Montecristi (M0450), Rocafuerte (M0165), Portoviejo (M0005), and Manta (M0452), reaching up to 146 mm, especially during the dry months. In Figure 11, the annual map reflects the same pattern, showing that the north, with stations like Chone (M0162), Paján (M0448), and Flavio Alfaro (M0160), maintains a more stable water balance throughout the year.
The spatial analysis of water deficit throughout the year is observed in Table 6, highlighting areas with the greatest irrigation scarcity and those with better availability.
| Period | Analysis |
|---|---|
| January-February | The deficit was higher in the south (Montecristi, Rocafuerte, Manta), reaching up to 146 mm, while in the north (Chone, Flavio Alfaro) the values were lower (~22 mm). |
| March-April | The south recorded pronounced deficits (~144 mm), while the north showed lower values (-23 mm). |
| May-June | There was a general increase in the deficit, reaching 127 mm in most stations, except for Paján (-0.10 mm). |
| July-August | High deficits persisted in the south (~145 mm), with lower values in the north. |
| September-October | The same trend continued, with deficits of up to 146 mm in the southern zone. |
| November-December | High values continued (~139-142 mm), with Chone and Jipijapa being the stations with the least deficit. |
| Annual | The highest deficit was concentrated in the southern coastal area (Montecristi, Rocafuerte, Portoviejo), while the lowest values were observed in Chone and Paján. |
Monthly temporal trend of the variables affecting water deficit in Manabí
⌅A clear difference was observed in the distribution of rainfall, evapotranspiration, and water deficit at the Manabí stations. The central and southern areas, such as Portoviejo-UTM (M0005) and 24 de mayo (M0447), had more rain, while the coastal areas, such as Jama (M0167) and Montecristi (M0450), recorded less. In the south, Puerto Cayo (M0457) and Joa-Jipijapa (M0455) showed higher evapotranspiration, and the water deficit was stronger in Rocafuerte (M0165) and Montecristi (M0450). In contrast, the north, with Flavio Alfaro (M0160) and Junín (M0163), maintained more balanced conditions.
Figure 12 shows a comparative analysis of effective precipitation, reference crop evapotranspiration, and water deficit at the Manabí stations. It is observed that the southern and coastal areas have lower water availability due to high evapotranspiration and low precipitation, while the north maintains a more stable and favorable balance.
Discussion
⌅The results obtained for effective precipitation show that in Manabí there is a clear spatial difference in water availability, with higher values observed between January and April in the northern and central areas, where stations like Chone, Flavio Alfaro, and Santa Ana exceeded 100 mm/month, while coastal areas like Manta and Montecristi recorded values below 70 mm/month and even minimums close to 5 mm/month during the dry months. This behavior coincides with what was described by Pérez y Domínguez (2019)PÉREZ, R. Y DOMÍNGUEZ, J.: “Irrigation Regime for Crops in Manabí, Ecuador: Proposal for Five Permanent Crops,” Revista Ciencias Técnicas Agropecuarias, 28(4), 63-72, 2019. , who reported that in Manabí the annual precipitation shows strong contrasts between humid inland areas and drier coastal sectors, which conditioned the need for supplemental irrigation. Similarly, Filgueiras et al., (2019)FILGUEIRAS, R.; REIS, M.M.; LOPES, E.M.; RIBEIRO, R.B. Y RAMOS, M.C.A.: “Dinámica espacio-temporal de variables climatológicas en la ayuda a la toma de decisiones en agricultura de regadío.” Journal of Agricultural Science, 11(6), 1-9, 2019. they demonstrated that in tropical agricultural systems, the spatial variability of rainfall can generate significant productive differences within the same region. Nieto C. et al., (2018)NIETO C., C. PAZMIÑO, C. E.; ROSERO, S. Y QUISHPE, B.: “Estudio del aprovechamiento de agua de riego disponible por unidad de producción agropecuaria, con base en el requerimiento hídrico de cultivos y el área regada, en dos localidades de la Sierra ecuatoriana,” Siembra, 5(1 SE-Artículos originales. Agronomía), 51-70, 2018. DOI: https://doi.org/10.29166/siembra.v5i1.1427 . they also found in the Ecuadorian Sierra that areas with higher natural precipitation show less dependence on artificial irrigation, a situation comparable to the north of Manabí, where the water balance was more favorable. These results confirm that the irregular distribution of rainfall is one of the main factors explaining the provincial agricultural heterogeneity.
Regarding the evapotranspiration of the reference crop (ETo), the obtained values show a higher water demand in the south of Manabí, reaching peaks close to 154 mm/month between May and June in stations like Portoviejo and Jipijapa, while the north presented lower values around 119-132 mm/month. Similar results were reported by Ashraf et al., (2023)ASHRAF, H.; QAMAR, S.; 2 , RIAZ, N.; SHAMSHIRI, R.R.; SULTAN, M.; KHALID, B.; IBRAHIM, S.M.; IMRAN, M. Y KHAN, M.U.: “Estimación espaciotemporal de la evapotranspiración de referencia para Aplicaciones agrícolas en Punjab, Pakistán” Agricultura, 13, 13, 2023. in Punjab, where evapotranspiration ranged between 120 and 160 mm/month, directly associated with the increase in temperature and solar radiation. Zheng et al., (2022)ZHENG, Q.; HE, J.; QIN, M.; LUI, T. Y HUANG, X.: “Variación espaciotemporal de la evapotranspiración potencial y sus factores dominantes durante el período 1970-2020 en la región de Sichuan-Chongqing, China” Más uno, 17(6), 15, 2022. DOI: https://doi.org/10.1371/journal.pone.0268702 . they also identified comparable spatial variations, indicating that areas with lower atmospheric humidity experience greater water losses due to evapotranspiration. At the national level. Ortiz y Chile (2020)ORTIZ, R. Y CHILE, M.: “Métodos de cálculo para estimar la evapotranspiración de referencia para el Valle de Tumbaco.” Siembra, 7(1), 70-79, 2020. they estimated ETo values close to 140 mm/month in the Tumbaco valley, a range very close to those obtained in this study, which supports the consistency of the results. From a productive standpoint, Abanum, Olalekan y Aremu (2023)ABANUM, N.; OLALEKAN, I. Y AREMU, O.: “Tasas de riego y su respuesta al desarrollo del crecimiento de los genotipos del cacao (Theobroma cacao L.).” Revista internacional de ciencias de plantas y suelos, 35(13), 154-164, 2023. demonstrated that crops like cocoa increase their irrigation requirements when evapotranspiration exceeds 130 mm/month, a situation observed in much of southern Manabí. Likewise, Dhaloiya et al., (2022)DHALOIYA, A.; HOODA, R.S.; KUMAR, D.; MALIK, A. Y KUMAR, A.: Evaluación basada en geoinformática de las necesidades brutas de riego de diferentes cultivos cultivos cultivados en la región suroeste de Haryana, India in M. Zakwan et al. (eds.) Direcciones actuales en la investigación sobre la escasez de agua. Elsevier (Current Directions in Water Scarcity Research), 299-316, 2022. DOI: https://doi.org/https://doi.org/10.1016/B978-0-323-91910-4.00018-2 . they highlight that geospatial analysis allows for the identification of critical water demand areas, which aligns with the spatial patterns evidenced in the generated maps.
Regarding the water deficit, the results indicate that the most critical conditions are concentrated in the southern coastal zone, where stations like Montecristi, Rocafuerte, and Manta reached values close to 146 mm, while the north showed much lower deficits, around 22 mm, and even almost neutral balances in Paján. These values reflect a direct combination of low precipitation and high evapotranspiration. Inzunza et al., (2018)INZUNZA, M. A.; VILLA, C. M.M.; CATALÁN, V. E.A.; LÓPEZ, L. R. Y SIFUENTES, I. E.: “Maize grain yield under soil water deficit at two growing stages,” Revista Fitotecnia Mexicana, 41(3), 283-290, 2018. DOI: https://doi.org/10.35196/rfm.2018.3.283-290 . they reported that deficits exceeding 120 mm cause significant reductions in corn yield, which allows for inferring possible productive impacts in the drier areas of Manabí. Similarly, Ohikhena (2023)OHIKHENA, A.: “Efectos del riego regulado en la estación seca sobre el uso de agua de los árboles, la dinámica de la humedad de la zona de las raíces y el rendimiento del cacao.” Revista de horticultura. 10(1), 13, 2023. observed that during prolonged dry seasons, the use of regulated irrigation allowed for the compensation of similar deficits, improving the efficient use of water in tropical crops. Katerji et al., (2023)KATERJI, N.; VAN HOORN, J.W.; HAMDY, U. Y MASTRORILLI, M.: “Efecto de la salinidad sobre el desarrollo y rendimiento de los cultivos, análisis de la tolerancia a la sal según varios métodos de clasificación,” Gestión del agua para la agricultura, 62(1),. 37-66, 2003. DOI: https://doi.org/https://doi.org/10.1016/S0378-3774(03)00005-2 . they also warn that persistent water deficits can promote soil degradation processes and increased salinity, especially in coastal regions, a condition that coincides with the areas identified in this study.
This comparison with previous studies confirms that the identified spatial pattern corresponds to well-documented regional climatic processes and highlights the need for differentiated water management strategies according to local water availability.
Conclusions
⌅It was determined that the spatial and temporal analysis of the variables associated with water deficit in the province of Manabí reveals significant contrasts between the different areas of the territory. The southern region presents the lowest values of effective precipitation and the highest deficits, reflecting a high water demand, while the northern stations, such as Flavio Alfaro (M0160) and Junín (M0163), show more favorable conditions with higher precipitation and positive balances. The concentration of rainfall in the months of February and March, coupled with high and constant evapotranspiration, shows that water scarcity intensifies between June and November, with demand far exceeding natural supply.
These results confirm that the semi-arid climate of Manabí generates a structural water deficit that requires technical and sustained planning to ensure the efficient use of the resource and the stability of agricultural systems, and highlight the need to strengthen water resource management and conservation strategies in Manabí, promoting sustainable agricultural practices, efficient water use, and the implementation of adaptation measures in response to climate variability.