Deficit irrigation under water stress and salinity conditions: The MOPECO-Salt Model

The AquaCrop model was used to simulate maize growth and soil water content under full and deficit irrigation managements as 1.2, 1, 0.8, and 0.6 of the potential crop water requirement. Generally, the RMSEs in simulating soil water content in calibration and validation were 0.01-0.039 and 0.012-0.037 m 3 m −3 , respectively, that overall corresponds to 3-14 % error. For the in-season biomass development, the RMSEs in calibration varied between 2.16 and 2.73 Mg ha −1 , while they varied between 1.97 and 5.19 Mg ha −1 in validation for the four irrigation managements. The model showed poor performance for simulating biomass late in the season under deficit irrigation managements. The RMSEs of final grain yield simulation were 0.71 and 1.77 Mg ha −1 that corresponded to 7 and 18 % error in calibration and validation, respectively. Likewise, the RMSEs for simulating the final biomass in calibration and validation were 1.29 and 2.21 Mg ha −1 that equals to 6 and 10 % error, respectively. Results demonstrated that AquaCrop is a useful decision-making tool for investigating deficit irrigations and maize growth in the region. However, in agreement with the findings in earlier studies on AquaCrop, the model showed insufficient accuracy in simulating final grain yield and biomass under moderate to severe water stresses. It is suggested that AquaCrop would benefit of including some calibrating parameters about the root distribution pattern in the soil because it is a water-driven model and highly depends on the accurately simulated water uptake from the soil profile.

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“…1 Introduction (Domínguez et al 2011), soybean (Khoshravesh et al 2013), cabbage (Wellens et al 2013), and tef .…”

mentioning

confidence: 99%

Modeling Maize Yield and Soil Water Content with AquaCrop Under Full and Deficit Irrigation Managements

Ahmadi

Mosallaeepour

Kamgar-Haghighi

et al. 2015

Water Resour Manage

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“…In this function, TW N = net irrigation (I N ) + effective rainfall (P e ). To obtain Y vs. TW N , the model simulates a range of deficit irrigation schedules using the optimized regulated deficit irrigation (ORDI) methodology, considering the effects of irrigation uniformity (López-Mata et al, 2010) and electrical conductivity of water (Domínguez et al, 2011) on yield. The Y vs. TW N function is translated into "Yield vs. Total Gross Water" (Y vs. TW G ), where TW G = gross irrigation (I G ) + P e , to include the application efficiency of the irrigation system.…”

Section: Mopeco Descriptionmentioning

confidence: 99%

“…3) were determined in the area for a Granero cultivar by using a weighting lysimeter (López-Urrea et al, 2009a), the initial soil moisture content was assumed as 0.95 of total available water, the texture was sandy-clay-loam, and the effective root depth was 40 cm. The daily soil water balance was calculated as the difference between inputs (rainfall and irrigation) and outputs (ET a and deep percolation) (Domínguez et al, 2011).…”

Section: Mopeco Descriptionmentioning

confidence: 99%

“…The MOPECO (economic optimization model for irrigation water management) model was conceived for optimizing the gross margin (GM) of farms through a better use of irrigation water (de Juan et al, 1996). MOPECO has been calibrated in several irrigable lands of the world: Bekaa Valley in Lebanon (Domínguez et al, 2011); Fortaleza and Rio de Janeiro in Brazil (Leite et al, 2014;Carvalhoa et al, 2014); and San Luis in Argentina (Garbero et al, 2014). In Castilla-La Mancha (CLM) region (Spain), this model has been calibrated for several crops such as maize (Zea Mays L.) (Domínguez et al, 2012a), garlic (Allium sativum L.) (Domínguez et al, 2013), melon (Cucumis melo L.) (Leite et al, 2014), and onion (Allium cepa L.) (Domínguez et al, 2012b).…”

Section: Introductionmentioning

confidence: 99%

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Distribution of limited irrigation water based on optimized regulated deficit irrigation and typical metheorological year concepts

Leite

Martínez-Romero

Tarjuelo

et al. 2015

Agricultural Water Management

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“…La ET m diaria se calcula multiplicando el Kc diario por la evapotranspiración de referencia (ET o ) diaria (Allen et al, 1998). ET a diaria requiere un balance diario del contenido de agua en el suelo para su estimación, el balance de agua en el suelo diario se calcula como la diferencia entre las entradas (precipitaciones y riego) y salidas (ET a y percolación profunda) (Domínguez et al, 2011). Para la simulación de la cebada también se necesita la duración de las etapas de Kc y Ky en grados día acumulados (GDD).…”

Section: 1-calibración Del Modelo Mopeco Establecimiento De Las Neunclassified

Distribución Optimizada De Volúmenes Limitados De Agua De Riego Y Su Efecto Sobre El Rendimiento Y La Calidad De La Cebada Cervecera

Pardo¹,

Lellis²,

Romero³

et al. 2016

XXXIV Congreso Nacional De Riegos

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ResumenEn Castilla-La Mancha (C-LM), la cebada es un cultivo con bajas necesidades de agua de riego (lámina neta, In=2.500 m 3 ha -1 ) y con una gran diferencia de rendimiento entre secano y regadío. Sin embargo, por la escasez de recursos hídricos, las dotaciones limitadas de agua, y el alto coste de la energía, los agricultores se están planteando aplicar riego deficitario a este cultivo. El objetivo de este trabajo es determinar, para las condiciones de C-LM, las estrategias de riego deficitario controlado que, con volúmenes limitados de agua de riego, maximizan el rendimiento de la cebada cervecera sin que la calidad del producto se vea afectada. Se han desarrollado ensayos de campo considerado 5 volúmenes de agua disponible (Ilimitada, 1 In, 0.9 In, 0.8 In, y 0.7 In), optimizando los calendarios de riegos combinando las metodologías "año meteorológico típico" (Tipical Meteorological Year,TMY) y "riego deficitario optimizado por etapas" (Optimized Regulated Deficit Irrigation, ORDI) con el modelo MOPECO. Se ha conseguido una buena distribución del agua disponible a lo largo de la campaña, sin alcanzar un estrés severo global en ninguna de las etapas de desarrollo, logrando un alto rendimiento sin decremento de la calidad, pese a desconocer las condiciones climáticas en las que se iba a desarrollar el cultivo. Los rendimientos obtenidos fueron similares a los estimados al inicio de la campaña y los parámetros de calidad medidos, excelentes en todos los tratamientos.

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Deficit irrigation under water stress and salinity conditions: The MOPECO-Salt Model

Cited by 66 publications

References 36 publications

Modeling Maize Yield and Soil Water Content with AquaCrop Under Full and Deficit Irrigation Managements

Modeling Maize Yield and Soil Water Content with AquaCrop Under Full and Deficit Irrigation Managements

Distribution of limited irrigation water based on optimized regulated deficit irrigation and typical metheorological year concepts

Distribución Optimizada De Volúmenes Limitados De Agua De Riego Y Su Efecto Sobre El Rendimiento Y La Calidad De La Cebada Cervecera

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