A Model to Estimate the Laying Curve of White Leghorn Hens in the Last Three Years in the Province of Ciego de Avila, Cuba

A number of 15 976 egg production records from three hen batches in Ciego de Avila (2016) were used. The laying curve was characterized in similar conditions to IIA (2013), Republic of Cuba. The estimation of the laying curves made of mean productions from three stages in a year was presented. Four mathematical models were applied for curve adjustment: McNally, Wood, quadratic logarithmic, and linear hyperbolic. Different statistical criteria were used for validation: determination coefficient (R2), (R2A), residual analysis, and others. The means, standard deviation (SD), standard error (SE), and variation coefficient (VC) were made for each period. Egg production accounted for 84.35 and 60.61% of total laying, the best year was 2016. The highest values of SE and VC were observed at the end of production, as expected. Adjustment and discrimination showed a high adjustment criterion in the four models, but the best values were observed with McNally (1971), in R2 (99.60%), and adjusted R2 (99.42%). McNally reached the highest adjustment values: YM=-2233.62-18583.8*(MONTH/426)-029.0*(MONTH/426**2+780.241*log (426/MONTH)-68.1269*(log(426/MONTH))*2, and it described the best production of White Leghorn (L33) hens in Ciego de Avila

Potencial Incubatorio de diferentes tipos de huevos procedentes de reproductoras ligeras White Legornh clasificados como defectuosos por su forma y/o peso

The productive potential of defective eggs for the incubation of light breeders by their weight and / or shape was evaluated. A 3 x 2 factorial design was used, in which the factors were: Weight: from 45 g to 51.5 g (small) of 52 to 65 g (normal) and 65 g to 80 g. (large) and Shape: from 66.5 to 75.4% (ovoids) and from 75.5 to 85.5% (rounded). A when performing the KMO test on the arcosenos, correlations were found between the variables, so it was necessary to use multivariate techniques specifically main components. The experimental unit was each tray in each type of egg; In 4 incubations and the Variable responses: indicators of the biological controls, Final results of the incubation, the results were analyzed using the SPSS program (version 11.0 of 2001). Among the main results we can point out that no significant differences were found for the interactions of the shapes and weights, so they were treated as independent factors. Regarding the forms, only significant differences were found for the Efficiency component for total embryonic mortality adjusted with means of 36.14 and 49.22 for the ovoid and non-ovoid forms studied respectively, being the most efficient rounded form. In the same way there were only differences in this component with means for the small, normal and large ones of 50.44; 49.98 and 27.63 respectively, indicating that large eggs are the least efficient in the first days of incubation. In relation to the second matrix, all the components were not significant and, as in the first, the independent variables had the same result. Therefore, it is concluded that: It was demonstrated that the eggs of White Leghorn breeders classified as unfit (except for large ovoids or not) are likely to be used in artificial incubation and that animals that could produce with similar efficiency are obtained from them to those from normal ovoid eggs, so they may be a possibility for egg production. The forms studied did not show significant differences, so they can be used to obtain eggs for incubation.Se evalúo el potencial productivo de huevos defectuosos para la incubación de reproductoras ligeras por su peso y/o forma, Se utilizó un diseño factorial 3 x 2, en que los factores fueron: Peso: de 45 g a 51,5 g (pequeños) de 52 a 65 g (normales) y de 65 g a 80 g. (grandes) y Forma: de 66,5 a 75,4 % (ovoides) y de 75,5 a 85,5 % (redondeados). A al realizar la prueba KMO a los arcosenos se encontraron correlaciones entre las variables por lo que fue necesario utilizar técnicas multivariadas específicamente componentes principales. La unidad experimental fue cada bandeja en cada tipo de huevo; en 4 incubaciones y las Variables respuestas: indicadores de los controles biológicos, Resultados finales de la incubación, los resultados fueron analizados mediante el programa SPSS (versión 11.0 del 2001). Ente los principales resultados podemos señalar que no se encontraron diferencias significativas para las interacciones de las formas y los pesos por lo que fueron tratadas como factores independientes. En relación a las formas sólo se encontró diferencias significativas para la componente Eficiencia para la mortalidad embrionaria total ajustada con medias de 36.14 y 49.22 para las formas ovoides y no ovoides estudiadas respectivamente, siendo la forma redondeada más eficiente. En los pesos de igual manera sólo existió diferencias en esta componente con medias para los pequeños, normales y grandes de 50.44; 49.98 y 27.63 respectivamente, indicando que los huevos grandes son los menos eficientes en los primeros días de incubación. En relación con la segunda matriz todas las componentes fueron no significativas y al igual que en la primera las variables independientes tuvieron igual resultado. Por lo que se concluye que: Se demostró que los huevos de reproductoras White Leghorn clasificados como no aptos (exceptuando los grandes ovoides o no) tienen posibilidades de ser utilizados en la incubación artificial y que se obtienen de ellos animales que pudieran producen con similar eficiencia a los provenientes de huevos ovoides normales, por lo que pueden ser una posibilidad para la producción de huevos. Las formas estudiada no presentaron diferencias significativas por lo que pueden ser utilizadas para obtener huevos para la incubación

Diseño de mortero de baja resistencia para relleno en tuberías en el Centro Comercial Box Park, Surco, 2019

La tesis de investigación titulada: Diseño de mortero de baja Resistencia y su influencia en el relleno de tuberías en el centro comercial Box Park Surco, 2019, tiene como objetivo determinar el efecto de la aplicación del diseño de mortero de baja resistencia utilizando material propio, obtenido en obra durante la actividad de la excavación, para reemplazar el relleno convencional y ver cómo este mortero influye y aporta en el relleno en redes de tuberías del centro comercial Box Park, surco 2019 La finalidad de la investigación es mejorar el relleno compactado convencional, creando un diseño de mortero de baja resistencia, que permitirá dar solución al problema de hundimientos, mejorando la capacidad portante, disminuyendo el asentamiento y mejorando la productividad en el proceso constructivo. La investigación es experimental, y cuantitativa. La población estuvo constituida por la cantidad de pruebas en laboratorio hasta encontrar un diseño de mezclas, el cual una de sus características es que sea un suelo de capacidad portante entre 5 a 10 kg/cm2, que viene hacer un suelo bueno y sea excavable para futuros trabajos de desarrollo de infraestructura, la técnica que se empleo fue la observación, teniendo como instrumento la ficha técnica. Los resultados estadísticos T de Studen indican que existe una diferencia significativa entre ambas variables, el diseño de mortero elaborado con material propio influye en las propiedades del relleno compactado, mejorando su capacidad portante, haciéndola productiva y disminuyendo el problema del hundimiento. En cuanto al relleno compactado convencional se hizo el ensayo de corte directo para obtener la resistencia y compararlo con la resistencia del mortero de baja resistencia

Modeling actual water use under different irrigation regimes at district scale: Application to the FAO-56 dual crop coefficient method

The modeling of irrigation in land surface models are generally based on two soil moisture parameters SMthreshold and SMtarget at which irrigation automatically starts and stops, respectively. Typically, both parameters are usually set to optimal values allowing to fill the soil water reservoir with just the estimated right amount and to avoid crop water excess at all times. The point is that agricultural practices greatly vary according to many factors (climatological, crop, soil, technical, human, etc.). To fill the gap, we propose a new calibration method of SMthreshold and SMtarget to represent the irrigation water use in any (optimal, deficit or even over) irrigation regime. The approach is tested using the dual-crop coefficient FAO-56 model implemented at the field scale over an 8100 ha irrigation district in northeastern Spain where the irrigation water use is precisely monitored at the district scale. Both irrigation parameters are first retrieved at monthly scale from the irrigation observations of year 2019. The irrigation simulated by the FAO-56 model is then evaluated against observations at district and weekly scale over 5 years (2017–2021) separately. The performance of the newly calibrated irrigation module is also assessed by comparing it against three other modules with varying configurations including default estimates for SMthreshold and SMtarget. The proposed irrigation module obtains systematically the best performance for each of the 5 years with an overall correlation coefficient of 0.95 ± 0.02 and root-mean square error of 0.27 ± 0.07 hm3/week (0.64 ± 0.17 mm/day). Unlike the three irrigation modules used as benchmark, the new irrigation module is able to reproduce the farmers’ practices throughout the year, and especially, to simulate the actual water use in the deficit and excess irrigation regimes occurring in the study area in spring and summer, respectively.This study was supported by the IDEWA project ( ANR-19-P026-003 ) of the Partnership for research and innovation in the Mediterranean area ( PRIMA ) program and by the Horizon 2020 ACCWA project (grant agreement # 823965 ) in the context of Marie Sklodowska-Curie Research and Innovation Staff Exchange (RISE) program. The authors wish to acknowledge the "Comunitat de Regants Canal Algerri Balaguer" and the Ebro Hydrographic Confederation (SAIH Ebro) for providing the observation irrigation data used in this study

Modelación de curvas de puesta de los tres últimos años en gallinas White Leghorn en la provincia Ciego de Ávila.

Se utilizaron 15 976 registros de producción de huevos, correspondientes a tres crianzas del 2016 en la provincia Ciego de Ávila. Se caracterizó la curva de puesta en condiciones similares a las propuestas por IIA (2013) en la República de Cuba.  Se muestra la estimación de las curvas de puesta realizadas con  las producciones medias corres-pondientes a tres etapas de 12 meses. Se aplicaron cuatro modelos matemáticos para el ajuste a dicha curva: Mc N a-lly, Wood, Cuadrática logarítmica y lineal hiperbólica. Para la validación se tomaron diferentes criterios estadí sticos: coeficiente de determinación (R2), (R2 A), además del análisis de los residuos entre otros. Para cada período se o b-tuvo la media, desviación estándar DE, error estándar (EE) y coeficiente de variación (CV). La producción de huevos alcanzó valores entre 84,35 y 60,61 % de puesta y el mejor año fue el 2016, mientras que los valores más altos de EE y CV correspondieron al final del periodo de producción, como era de esperar. La bondad de ajuste y discriminación entre los modelos utilizados demostraron un alto criterio de ajuste en los cuatro modelos, pero el mejor fue  Mc Nally (1971) con R2 de 99,60 %, los R2 ajustados con 99,42 %. La expresión Mc Nally, alcanzó los valores más altos de ajuste YM=-2233,62-18583,8*(MES/426)-029,0*(MES/426**2+780,241*log(426/MES)-68,1269*(log(426/MES))*2 y describe mejor la producción huevo de gallinas White Leghorn L33 en las condiciones de Ciego de Ávila.Laying Curve Model of White Leghorn Hens in the Last Three Years in the Province of Ciego de Avila, Cuba.ABSTRACTA number of 15 976 egg production records from three hen batches in Ciego de Avila (2016) were used. The laying curve was characterized in similar conditions to IIA (2013), Republic of Cuba. E stimation of the laying curves made to mean productions from three stages in a year, was presented. Four mathematical models were applied for curve adjustment: McNally, Wood, quadratic logarithmic, and linear hyperbolic. Different statistical criteria were used for validation: determination coefficient (R2), (R2A), as well as residue analysis and others. Mean, standard deviation (SD), standard error (SE), and variation coefficient (VC) were achieved for each period. Egg production accounted for 84.35 and 60.61% of total laying, 2016 was the best year. The highest values of SE and VC were observed at the end of production, as expected. Adjustment and discrimination showed a high adjustment criterion in the four models, but the best values were observed with McNally (1971), in R2 (99.60%), and adjusted R2 (99.42%). McNally reached the highest adjustment values: YM=-2233.62-18583.8* (MONTH/426)-029.0*(MONTH/426**2+780.241*log (426/MONTH)-68.1269*(log  (426/MONTH))*2, and it described the best production of White Leghorn L33 hens in Ciego de Avil

Suivi des ressources en eau des cultures irriguées par télédétection multi-spectrales optique/thermique

Irrigated agriculture is an important pressure on water resources, consuming more than 70% of the mobilized freshwater resources at global scale. However, the information on irrigation, which is crucial for the sustainability of water resources in agricultural regions, is often unavailable. Therefore, monitoring and quantifying the crop water budget over extended areas is critical. This PhD thesis aims to integrate optical/thermal remote sensing data into a simplified crop water balance model for monitoring the water budget of irrigated agricultural areas. For this purpose, an innovative and stepwise approach is developed to estimate simultaneously the irrigation, the evapotranspiration (ET) and the root-zone soil moisture (RZSM) at crop field scale (100 m resolution) on a daily basis. In a first step, a feasibility study is carried out using in situ optical/thermal measurements collected over a winter wheat field of the Haouz plain, Morocco. A crop water stress coefficient (Ks) derived from the land surface temperature (LST) and vegetation index (NDVI) is first translated into RZSM diagnostic estimates, which is then used to estimate irrigation amounts and dates along the season. Next, the retrieved irrigations allow forcing the dual crop coefficient FAO-56 model (FAO- 2Kc) to re-analyze the daily ET and RZSM. The re-analyzed RZSM is significantly improved with respect to RZSM diagnostic estimates, reaching the same accuracy as that obtained by using actual irrigations (RMSE = 0.03 m3m-3 and R2 = 0.7). However, the approach needs to be tested using satellite data in order to demonstrate its real applicability. The next step consists in adapting the previous approach to spatially integrated but temporally sparse Landsat NDVI/LST data. For this purpose, a contextual method is first used to derive Landsat-derived estimates (crop coefficients and RZSM), which are used to re-initialize a FAO-based model and propagate this information daily throughout the season. Then, the retrieved pixel-scale irrigations are aggregated to the crop field-scale. The approach is applied to three agricultural areas (12 km by 12 km) in the semi-arid region of Haouz Plain, and validated over five winter wheat fields with different irrigation techniques (drip-, flood- and no-irrigation). The results show that the seasonal irrigation amounts over all the sites and seasons is accurately estimated (RMSE = 44 mm and R = 0.95), regardless of the irrigation techniques. Acceptable errors (RMSE = 27 mm and R = 0.52) are obtained for irrigations cumulated over 15 days, but poor agreements at daily to weekly scales are found in terms of irrigation. However, the daily RZSM and ET are accurately estimated using the retrieved irrigation and are very close to those estimated using actual irrigations (overall RMSE equal to 0.04 m3m-3 and 0.83 mm.d-1 for RZSM and ET, respectively). In a final step, an operational LST disaggregation method based on NDVI/LST and Landsat/MODIS relationships is implemented for enhancing the spatio-temporal resolution of LST as input to the irrigation retrieval approach. The disaggregation method is tested over an arid region of Chile and our study area in the Haouz Plain. Combining both disaggregated LST and Landsat LST data sets, thanks to the increase in the temporal frequency of LST data, results in a better detection of irrigation events and amounts. The overall RMSE of cumulated irrigation at different time scales is decreased from 46 to 34 mm, while the R is increased from 0.50 to 0.64. Consistently, the RZSM estimated using the disaggregated LST in addition to Landsat LST as input is improved by 26% and 14% in terms of RMSE and R, respectively.L'agriculture est une pression importante sur les ressources en eau, consommant plus de 70% de l'eau douce mobilisée à l'échelle mondiale. Cependant, les informations sur l'irrigation, pourtant cruciales pour assurer une durabilité de la ressource, sont souvent indisponibles. Par conséquent, il est essentiel d'estimer les différents termes du bilan d'eau des cultures à grande échelle. Cette thèse vise à intégrer les données de télédétection optique/thermique dans un modèle simplifié de bilan d'eau des cultures pour le suivi du bilan d'eau des zones agricoles irriguées. Une approche innovante est développée pour estimer simultanément l'irrigation, l'évapotranspiration (ET) et l'humidité en zone racinaire (RZSM) journalières à l'échelle de parcelle (ou à 100 m de résolution). Dans une première partie, une étude de faisabilité est réalisée à l'aide de mesures optiques/thermiques in situ collectées sur une parcelle de blé d'hiver dans la plaine du Haouz, au Maroc. En pratique, un coefficient de stress hydrique (Ks) dérivé de la température de surface (LST) et d'un indice de végétation (NDVI) est d'abord traduit en une première approximation de RZSM, qui est utilisée pour estimer les quantités et les dates d'irrigation au cours de la saison. Les irrigations obtenues permettent ensuite de forcer le modèle FAO-56 à coefficient cultural double (FAO-2Kc) et de fournir des ré-analyses ET et RZSM journalières. La RZSM ré-analysée est significativement améliorée par rapport aux premières estimations de RZSM, atteignant la même précision que celle obtenue en utilisant les irrigations réelles (RMSE=0,03 m3m-3 et R2=0,7). Toutefois, l'approche doit encore être testée avec des données satellitaires afin de démontrer son applicabilité dans le cas réel. La deuxième partie consiste à adapter l'approche précédente aux données optiques/thermiques Landsat à faible fréquence temporelle. Une méthode contextuelle est utilisée pour obtenir des estimations dérivées de Landsat (coefficients de culture et RZSM), qui sont utilisées pour réinitialiser un modèle basé sur le FAO-2Kc et propager ces informations à l'échelle journalière tout au long de la saison. Ensuite, les irrigations obtenues à l'échelle des pixels sont agrégées à la parcelle pour ré-analyser l'ET et la RZSM journalières. L'approche est appliquée sur trois zones agricoles (12 km x 12 km) de la région semi-aride de la plaine du Haouz et validée sur cinq parcelles de blé d'hiver avec différentes techniques d'irrigation (goutte à goutte, gravitaire et sans irrigation). Les résultats montrent que l'irrigation saisonnière sur l'ensemble des sites et des saisons est estimée avec une bonne précision (RMSE=44 mm et R=0,95), et ce quelque soit la technique d'irrigation. Des erreurs acceptables (RMSE=27 mm et R=0,52) sont obtenues pour des irrigations cumulées sur 15 jours, mais les erreurs sont beaucoup plus importants à l'échelle journalière et hebdomadaire. Cependant, les RZSM et ET journalières sont estimées avec précision à l'aide de des irrigations inversées et sont même très proches de celles estimées à l'aide des irrigations réelles (RMSE=0,04 m3m-3 pour RZSM et RSME=0,83 mm.d-1 pour ET). Dans la troisième partie, une méthode opérationnelle de désagrégation des données de LST basée sur les relations NDVI/LST et Landsat/MODIS est mise en œuvre pour améliorer la résolution spatio-temporelle de la LST utilisée en entrée de l'approche d'estimation de l'irrigation. La méthode de désagrégation est testée sur une région aride du Chili et sur notre zone d'étude dans la plaine du Haouz. La combinaison des données deLST Landsat et des données de LST désagrégées permet, grâce au gain en résolution temporelle, une meilleure détection des événements et des quantités d'irrigation. Le RMSE global de l'irrigation cumulée à différentes échelles de temps est réduite de 46 à 34 mm, tandis que le R passe de 0,50 à 0,64

Identifying relationships between biophysical variables of the rainfed coastal landscape of maule region and the surface energy balance components, by using remote sensing

Memoria para optar al título profesional de: Ingeniero en Recursos Naturales RenovablesPara la planificación y gestión de los recursos hídricos se requiere conocer no sólo la cantidad de agua que llega a la superficie terrestre, sino también el agua que sale de la superficie como evapotranspiración (ET). Esta variable es el factor más importante en el intercambio de energía y agua entre la superficie de la tierra y la atmósfera, la cual puede estimarse a través del balance energético superficial (BES). De esta manera, la estimación de los flujos energéticos superficiales permite avanzar en el conocimiento del paisaje de un territorio para su posterior planificación. En este estudio se estimó la distribución espacial de los flujos energéticos superficiales en un sector caracterizado por limitaciones hídricas, el secano costero de la Región del Maule, con el objetivo de identificar relaciones entre las variables biofísicas del paisaje y los componentes del BES. Para esto se calibró el modelo S-SEBI en el área de estudio y estimaron los componentes del BES a través de dos imágenes satelitales del sensor ASTER y datos de temperaturas máximas y mínimas diarias. Luego, para analizar los patrones espaciales en el paisaje, los componentes del BES se compararon con las variables biofísicas del paisaje asociadas a: índice de vegetación NDVI obtenido de las imágenes ASTER; cobertura de uso de suelo, clases de textura y profundidad del suelo, obtenidos a partir de estudios cartográficos de la Región del Maule; y variables topográficas de altitud, pendiente y exposición obtenidas de un Modelo Digital de Elevación (DEM). Las comparaciones fueron realizadas en base a diagramas de cajas entre las clases del material cartográfico para cada componente del BES, para lo cual se aplicaron pruebas de contrastes entre clases con el test estadístico Kruskal-Wallis y posteriormente con el test Mann-Whitney. Las variables topográficas fueron comparadas en base a las distribuciones de frecuencias para cada variable y componente. A partir de esta metodología se obtuvieron los componentes del BES en ambas escenas, donde se encontraron que la mayoría de las clases mostraron diferencias significativas. Mientras que las coberturas boscosas tienen las mayores tasas de ET, los terrenos agrícolas se sitúan muy por debajo con tasas similares a las praderas y matorrales. En cuanto al NDVI se encontró una alta correlación lineal con la ET, explicando en más del 75% las tasas encontradas para ambas escenas. Finalmente, se pudo concluir que el modelo S-SEBI permite estimar los componentes del BES con un mínimo de datos meteorológicos, y sus patrones espaciales observados en ambas escenas pueden ser explicados por las variables biofísicas estudiadas.The planning and management of water resources requires not only to know the amount of water that reaches Earth's surface, but also the amount of water that leaves the surface in the evapotranspiration process (ET). This variable is the most important factor in the energy and water exchange between Earth's surface and the atmosphere and it can be estimated with the Surface Energy Balance Model (SEB). The estimation of surface's energy fluxes spatial distribution improves the knowledge of an area's landscape thus, allowing a better planning and management of such area. The purpose of this study was to estimate the spatial distribution of surface energy fluxes in a sector with limited water resources, the rained coastal of Region del Maule, Chile, in order to identify the relationships between the biophysical variables present it the landscape and the the SEB model components. To achieve this, the S-SEBI model was calibrated to estimate the components of the SEB model by using data (2 scenes) from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and data of the maximum and minimum daily temperatures. Then, to analyze the spatial patterns present in the landscape, SEB components were compared with landscape biophysical variables associated to: NDVI index obtained from the ASTER images; land use, soil texture and soil depth classes (obtained from Region del Maule's Geographic Information System (GIS); and the elevation, slope and aspect obtained from a Digital Elevation Model. Comparisons were made based on the analysis of box-plots between GIS classes of each component of the SEB model, applying contrast test between the classes with the Kruskal-Wallis and Mann-Whitney statistical tests. The topographic variables were compared based on the frequency distributions of each variable and component. Then, the SEB model components were obtained for both of the ASTER scenes showing that the majority of the classes showed significant differences. While the forest cover had the highest ET rates, agricultural land rates are similar of those of the grassland and shrubland classes. A high linear correlation was found between the ET and NDVI, explaining more than the 75% found for both of the scene. Finally, it was concluded that S-SEBI model can estimate the components of the SEB model using minimal meteorological data and that the spatial patterns observed in both scenes are in fact explained by the studied biophysical variables

Monitoring the water budget of irrigated crops from multi-spectral optical/thermal remote sensing data

L'agriculture est une pression importante sur les ressources en eau, consommant plus de 70% de l'eau douce mobilisée à l'échelle mondiale. Cependant, les informations sur l'irrigation, pourtant cruciales pour assurer une durabilité de la ressource, sont souvent indisponibles. Par conséquent, il est essentiel d'estimer les différents termes du bilan d'eau des cultures à grande échelle. Cette thèse vise à intégrer les données de télédétection optique/thermique dans un modèle simplifié de bilan d'eau des cultures pour le suivi du bilan d'eau des zones agricoles irriguées. Une approche innovante est développée pour estimer simultanément l'irrigation, l'évapotranspiration (ET) et l'humidité en zone racinaire (RZSM) journalières à l'échelle de parcelle (ou à 100 m de résolution). Dans une première partie, une étude de faisabilité est réalisée à l'aide de mesures optiques/thermiques in situ collectées sur une parcelle de blé d'hiver dans la plaine du Haouz, au Maroc. En pratique, un coefficient de stress hydrique (Ks) dérivé de la température de surface (LST) et d'un indice de végétation (NDVI) est d'abord traduit en une première approximation de RZSM, qui est utilisée pour estimer les quantités et les dates d'irrigation au cours de la saison. Les irrigations obtenues permettent ensuite de forcer le modèle FAO-56 à coefficient cultural double (FAO-2Kc) et de fournir des ré-analyses ET et RZSM journalières. La RZSM ré-analysée est significativement améliorée par rapport aux premières estimations de RZSM, atteignant la même précision que celle obtenue en utilisant les irrigations réelles (RMSE=0,03 m3m-3 et R2=0,7). Toutefois, l'approche doit encore être testée avec des données satellitaires afin de démontrer son applicabilité dans le cas réel. La deuxième partie consiste à adapter l'approche précédente aux données optiques/thermiques Landsat à faible fréquence temporelle. Une méthode contextuelle est utilisée pour obtenir des estimations dérivées de Landsat (coefficients de culture et RZSM), qui sont utilisées pour réinitialiser un modèle basé sur le FAO-2Kc et propager ces informations à l'échelle journalière tout au long de la saison. Ensuite, les irrigations obtenues à l'échelle des pixels sont agrégées à la parcelle pour ré-analyser l'ET et la RZSM journalières. L'approche est appliquée sur trois zones agricoles (12 km x 12 km) de la région semi-aride de la plaine du Haouz et validée sur cinq parcelles de blé d'hiver avec différentes techniques d'irrigation (goutte à goutte, gravitaire et sans irrigation). Les résultats montrent que l'irrigation saisonnière sur l'ensemble des sites et des saisons est estimée avec une bonne précision (RMSE=44 mm et R=0,95), et ce quelque soit la technique d'irrigation. Des erreurs acceptables (RMSE=27 mm et R=0,52) sont obtenues pour des irrigations cumulées sur 15 jours, mais les erreurs sont beaucoup plus importants à l'échelle journalière et hebdomadaire. Cependant, les RZSM et ET journalières sont estimées avec précision à l'aide de des irrigations inversées et sont même très proches de celles estimées à l'aide des irrigations réelles (RMSE=0,04 m3m-3 pour RZSM et RSME=0,83 mm.d-1 pour ET). Dans la troisième partie, une méthode opérationnelle de désagrégation des données de LST basée sur les relations NDVI/LST et Landsat/MODIS est mise en œuvre pour améliorer la résolution spatio-temporelle de la LST utilisée en entrée de l'approche d'estimation de l'irrigation. La méthode de désagrégation est testée sur une région aride du Chili et sur notre zone d'étude dans la plaine du Haouz. La combinaison des données deLST Landsat et des données de LST désagrégées permet, grâce au gain en résolution temporelle, une meilleure détection des événements et des quantités d'irrigation. Le RMSE global de l'irrigation cumulée à différentes échelles de temps est réduite de 46 à 34 mm, tandis que le R passe de 0,50 à 0,64.Irrigated agriculture is an important pressure on water resources, consuming more than 70% of the mobilized freshwater resources at global scale. However, the information on irrigation, which is crucial for the sustainability of water resources in agricultural regions, is often unavailable. Therefore, monitoring and quantifying the crop water budget over extended areas is critical. This PhD thesis aims to integrate optical/thermal remote sensing data into a simplified crop water balance model for monitoring the water budget of irrigated agricultural areas. For this purpose, an innovative and stepwise approach is developed to estimate simultaneously the irrigation, the evapotranspiration (ET) and the root-zone soil moisture (RZSM) at crop field scale (100 m resolution) on a daily basis. In a first step, a feasibility study is carried out using in situ optical/thermal measurements collected over a winter wheat field of the Haouz plain, Morocco. A crop water stress coefficient (Ks) derived from the land surface temperature (LST) and vegetation index (NDVI) is first translated into RZSM diagnostic estimates, which is then used to estimate irrigation amounts and dates along the season. Next, the retrieved irrigations allow forcing the dual crop coefficient FAO-56 model (FAO- 2Kc) to re-analyze the daily ET and RZSM. The re-analyzed RZSM is significantly improved with respect to RZSM diagnostic estimates, reaching the same accuracy as that obtained by using actual irrigations (RMSE = 0.03 m3m-3 and R2 = 0.7). However, the approach needs to be tested using satellite data in order to demonstrate its real applicability. The next step consists in adapting the previous approach to spatially integrated but temporally sparse Landsat NDVI/LST data. For this purpose, a contextual method is first used to derive Landsat-derived estimates (crop coefficients and RZSM), which are used to re-initialize a FAO-based model and propagate this information daily throughout the season. Then, the retrieved pixel-scale irrigations are aggregated to the crop field-scale. The approach is applied to three agricultural areas (12 km by 12 km) in the semi-arid region of Haouz Plain, and validated over five winter wheat fields with different irrigation techniques (drip-, flood- and no-irrigation). The results show that the seasonal irrigation amounts over all the sites and seasons is accurately estimated (RMSE = 44 mm and R = 0.95), regardless of the irrigation techniques. Acceptable errors (RMSE = 27 mm and R = 0.52) are obtained for irrigations cumulated over 15 days, but poor agreements at daily to weekly scales are found in terms of irrigation. However, the daily RZSM and ET are accurately estimated using the retrieved irrigation and are very close to those estimated using actual irrigations (overall RMSE equal to 0.04 m3m-3 and 0.83 mm.d-1 for RZSM and ET, respectively). In a final step, an operational LST disaggregation method based on NDVI/LST and Landsat/MODIS relationships is implemented for enhancing the spatio-temporal resolution of LST as input to the irrigation retrieval approach. The disaggregation method is tested over an arid region of Chile and our study area in the Haouz Plain. Combining both disaggregated LST and Landsat LST data sets, thanks to the increase in the temporal frequency of LST data, results in a better detection of irrigation events and amounts. The overall RMSE of cumulated irrigation at different time scales is decreased from 46 to 34 mm, while the R is increased from 0.50 to 0.64. Consistently, the RZSM estimated using the disaggregated LST in addition to Landsat LST as input is improved by 26% and 14% in terms of RMSE and R, respectively

Irrigation retrieval from Landsat optical/thermal data integrated into a crop water balance model: A case study over winter wheat fields in a semi-arid region

International audienceMonitoring irrigation is essential for an efficient management of water resources in arid and semi-arid regions. We propose to estimate the timing and the amount of irrigation throughout the agricultural season using optical and thermal Landsat-7/8 data. The approach is implemented in four steps: i) partitioning the Landsat land surface temperature (LST) to derive the crop water stress coefficient (Ks), ii) estimating the daily root zone soil moisture (RZSM) from the integration of Landsat-derived Ks into a crop water balance model, iii) retrieving irrigation at the Landsat pixel scale and iv) aggregating pixel-scale irrigation estimates at the crop field scale. The new irrigation retrieval method is tested over three agricultural areas during four seasons and is evaluated over five winter wheat fields under different irrigation techniques (drip, flood and no-irrigation). The model is very accurate for the seasonal accumulated amounts (R ~ 0.95 and RMSE ~ 44 mm). However, lower agreements with observed irrigations are obtained at the daily scale. To assess the performance of the irrigation retrieval method over a range of time periods, the daily predicted and observed 2 irrigations are cumulated from 1 to 90 days. Generally, acceptable errors (R = 0.52 and RMSE = 27 mm) are obtained for irrigations cumulated over 15 days and the performance gradually improves by increasing the accumulation period, depicting a strong link to the frequency of Landsat overpasses (16 days or 8 days by combining Landsat-7 and-8). Despite the uncertainties in retrieved irrigations at daily to weekly scales, the daily RZSM and evapotranspiration simulated from the retrieved daily irrigations are estimated accurately and are very close to those estimated from actual irrigations. This research demonstrates the utility of high spatial resolution optical and thermal data for estimating irrigation and consequently for better closing the water budget over agricultural areas. We also show that significant improvements can be expected at daily to weekly time scales by reducing the revisit time of high-spatial resolution thermal data, as included in the TRISHNA future mission requirements