scholarly journals Remote Sensing for Determining Evapotranspiration and Irrigation Demand for Annual Crops

10.5772/39305 ◽  
2013 ◽  
Author(s):  
Diofantos G. ◽  
Giorgos Papadavi
Keyword(s):  
Remote Sensing ◽  
Irrigation Demand ◽  
Annual Crops

Local sensitivity analysis of Satellite Monitoring of Irrigation software (SAMIR) over Semi-Arid climate of Morocco

2021 ◽  
Author(s):  
Aicha Moumni ◽  
Alhousseine Diarra ◽  
Abderrahman Lahrouni
Keyword(s):  
Remote Sensing ◽  
Sensitivity Analysis ◽  
Water Resources ◽  
Land Cover ◽  
Remote Sensing Data ◽  
Soil Parameters ◽  
Sensing Data ◽  
Annual Crops ◽  
Irrigated Area ◽  
Semi Arid

<p>Nowadays, the assessment of agricultural management is based mainly on the good management of water resources (i.e., to estimate the crops water consumption and provide their irrigation requirements). In this context, several agro-environmental models, (i.e., STICS, AQUACROP, TSEB, …) have been developed to assess the agricultural needs such as grain yield and/or irrigation demand prediction. These models are mainly based on the remote sensing data which contribute highly to the knowledge of some key-variables of crop models, in particular their time and space variations. The study area is the Haouz plain located in central Morocco. The climate of the plain is semi-arid continental type characterized by strong spatiotemporal irregular rains (mean annual precipitation up to 250 mm).The region relies mainly on the agricultural activities. Therefore, about 85% of available water is used for irrigated crops within the plain. The irrigated area is covered by 25% tree plantations and 75% annual crops. However, the annual crops extent depends strongly on the water availability during the season. Hence, for sustainable monitoring and optimal use of water resources (using physical modeling, satellite images and ground data), SAMIR software is developed in order to spatialize the irrigation water budget over Haouz plain. SAMIR (Simonneaux et al., 2009; Saadi et al., 2015; Tazekrit et al., 2018) is a tool for irrigation management based mainly on the use of remote sensing data. It estimates the crop evapotranspiration (ET) based on the FAO-56 model. This model requires three types of data: climatic variables for calculation of reference Evapotranspiration (ET0), land cover for computing crop coefficient Kc, and periodical phonological information for adjusting the Kc. SAMIR offers the possibility to calculate the ET of a large agricultural areas, with different land use/ land cover types, and subsequently deduce the necessary water irrigation for these areas. This model has been calibrated and validated over R3 perimeter (Diarra et al., 2017). In the present work, we studied the sensitivity (local sensibility analysis) of SAMIR software to the variations of each input parameter (i.e., ET0, precipitations, soil parameters, and irrigation configuration “real or automatic”). The simulations were made using the ground truth observations and irrigation dataset of the agricultural season of 2011/2012 over an irrigated area of Haouz plain. For the climatic variables, the obtained results showed that the effect of the ET0 is more significant compared to the effect of precipitations. It led to large shifts of the actual ET simulated by SAMIR compared to all tested parameters. For soil parameters, the sensitivity analysis illustrates that the effect is almost linear for all parameters. But the proportion of total available water, P, is the high sensitive parameter (Lenhart, et al., 2002). Finally, the comparison between the simulation of real evapotranspiration using automatic irrigation or real irrigation configuration offers an interesting result. The obtained ET values are similar for both configurations. Thus, this result offers the possibility of using only automatic irrigation configuration, in case of non-availability of the real irrigation.</p>

Estimating irrigation demand using satellite remote sensing: a case study of Paphos District area in Cyprus

2008 ◽  
Author(s):  
Diofantos G. Hadjimitsis ◽  
Giorgos Papadavid ◽  
Kyriacos Themistokleous ◽  
Anastasis Kounoudes ◽  
Leonidas Toulios
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Irrigation Demand

scholarly journals <i>Brief communication</i> "The integration of remote sensing and meteorological data for monitoring irrigation demand in Cyprus"

2009 ◽  
Vol 9 (6) ◽  
pp. 2009-2014 ◽  
Author(s):  
G. C. Papadavid ◽  
A. Agapiou ◽  
S. Michaelides ◽  
D. G. Hadjimitsis
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Satellite Images ◽  
Meteorological Data ◽  
Crop Water ◽  
Irrigation Demand ◽  
In Situ Techniques ◽  
Modeling Techniques ◽  
Agricultural Areas

Abstract. This paper examines and evaluates the integrated use of satellite remote sensing and meteorological data for estimating crop water requirements over agricultural areas of Cyprus. Intended purpose of this project is to estimate evapotranspiration using modeling techniques, satellite and meteorological data for monitoring irrigation demand. ETc was calculated with the FAO Penman-Monteith method by using satellite images acquired from July to December 2008. ETc estimates obtained in this project were compared to previous empirical data found by using in-situ techniques. ETc values have been correlated with the meteorological data to crosscheck the significance of the meteorological inputs.

Phased Arrays for Radio Astronomy, Remote Sensing, and Satellite Communications

2018 ◽  
Author(s):  
Karl F. Warnick ◽  
Rob Maaskant ◽  
Marianna V. Ivashina ◽  
David B. Davidson ◽  
Brian D. Jeffs
Keyword(s):  
Remote Sensing ◽  
Radio Astronomy ◽  
Phased Arrays ◽  
Satellite Communications

Hyperspectral Imaging Remote Sensing

2016 ◽  
Author(s):  
Dimitris Manolakis ◽  
Ronald Lockwood ◽  
Thomas Cooley
Keyword(s):  
Remote Sensing ◽  
Hyperspectral Imaging
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