S. Er-Raki

An integrated modelling and remote sensing approach for hydrological study in arid and semi-arid regions: the SUDMED Programme

Recent efforts have been concentrated in the development of models to understand and predict the impact of environmental changes on hydrological cycle and water resources in arid and semi‐arid regions. In this context, remote sensing data have been widely used to initialize, to force, or to control the simulations of these models. However, for several reasons, including the difficulty in establishing relationships between observational and model variables, the potential offered by satellite data has not been fully used. As a matter of fact, a few hydrological studies that use remote sensing data emanating from different sources (sensors, platforms) have been performed. In this context, the SUDMED programme has been designed in 2002 to address the issue of improving our understanding about the hydrological functioning of the Tensift basin, which is a semi‐arid basin situated in central Morocco. The first goal is model development and/or refinement, for investigating the hydrological responses to future scenario about climate change and human pressure. The second aim is the effective use of remote sensing observations in conjunction with process models, to provide operational prognostics for improving water‐resource management. The objective of this paper is to present the SUDMED programme, its objectives, and its thrust areas, and to provide an overview of the results obtained in the first phase of the programme (2002–2006). Finally, the lessons learned, future objectives, and unsolved issues are presented.

Citrus orchard evapotranspiration : comparison between eddy covariance measurements and the FAO-56 approach estimates

Abstract The aim of this study was to use the FAO-56 single and dual crop coefficient approaches to estimate actual evapotranspiration (ETa) over an irrigated citrus orchard under drip and flood irrigations in Marrakech, Morocco. The results showed that, by using crop coefficients suggested in the FAO-56 paper, the performance of both approaches was poor for two irrigation treatments. The Root Mean Squared Error (RMSE) between measured and simulated ETa values over the citrus orchard under drip irrigation was about 1.43 and 1.27 mm/day for the single and dual approaches, respectively, while the corresponding statistics for the orchard irrigated by the flooding technique was 1.87 and 2.48 mm/day. After determination of the appropriate values of the crop coefficient (Kc) based on eddy covariance measurements of ETa, the performance of both approaches greatly improved. The obtained Kc values were lower than the FAO-56 values by about 20%. The low Kc values obtained reflect the practice of drip irrigation for one field and the low value of cover fraction for the other field. Additionally, the efficiency of the irrigation practices was investigated by comparing the measured Kc for two fields. The results showed that a considerable amount of water was lost by direct soil evaporation from the citrus orchard irrigated by flooding technique.

Monitoring of irrigated wheat in a semi‐arid climate using crop modelling and remote sensing data: Impact of satellite revisit time frequency

The rationale of this research is to investigate approaches based on modelling and remote sensing data for estimating the spatial distribution of yield and irrigation of wheat in semi‐arid areas. The specific objective is to compare the performances of two approaches to test the STICS crop model using remotely sensed estimates of leaf area index (LAI). An experimental study of phenology, yield and water balance of irrigated wheat was made in the Marrakech‐Haouz plain during year 2003. Experimental data was allowed to run STICS using two approaches: (1) Calibration of the parameters that control the time course of LAI; (2) driving from LAI time series interpolated with a simple model. The results show the accuracy of STICS to simulate actual evapotranspiration and yield for both approaches. Finally, the two approaches were compared using remotely sensed estimates of LAI upon four scenarios of satellite time revisit frequency. The simulations we obtained always show acceptable results. However, differences appear between the variables, between the approaches and between the frequencies.

Agrometerological study of semi-arid areas: an experiment for analysing the potential of time series of FORMOSAT-2 images (Tensift-Marrakech plain)

Earth Observing Systems designed to provide both high spatial resolution (10 m) and high capacity of time revisit (a few days) offer strong opportunities for the management of agricultural water resources. The FORMOSAT‐2 satellite is the first and only satellite with the ability to provide daily high‐resolution images over a particular area with constant viewing angles. As part of the SudMed project, one of the first time series of FORMOSAT‐2 images has been acquired over the semi‐arid Tensift‐Marrakech plain. Along with these acquisitions, an experimental data set has been collected to monitor land‐cover/land‐use, soil characteristics, vegetation dynamics and surface fluxes. This paper presents a first analysis of the potential of these data for agrometerological study of semi‐arid areas.

Consistency between In Situ, Model-Derived and High-Resolution-Image-Based Soil Temperature Endmembers: Towards a Robust Data-Based Model for Multi-Resolution Monitoring of Crop Evapotranspiration

Due to their image-based nature, “contextual” approaches are very attractive to estimate evapotranspiration (ET) from remotely-sensed land surface temperature (LST) data. Their application is however limited to highly heterogeneous areas where the soil and vegetation temperature endmembers (Tends) can be observed at the thermal sensor resolution. This paper aims to develop a simple theoretical approach to estimate Tends independently from LST images. Soil Tends are simulated by a soil energy balance model forced by meteorological data. Vegetation Tends are obtained from soil Tends and air temperature. Model-derived soil Tends are first evaluated with in situ measurements made over an irrigated area in Morocco. The root mean square difference (RMSD) between modeled and ground-based soil Tends is estimated as 2.4 oC. Model-derived soil Tends are next compared with the soil Tends retrieved from 90-m resolution ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) data collected over two irrigated areas in Mexico and Spain. Such a comparison reveals a strong consistency between model-derived and high-resolution image-based soil Tends. A recent contextual ET model (SEB-1S) is then applied to 90-m resolution and to 1-km resolution (aggregated) ASTER data using the model-derived or image-based Tends as the input. The RMSD between 90-m resolution SEB-1S and in situ ET is estimated as 65 and 82 W·m-2, and the RMSD between 1-km resolution SEB-1S and aggregated SEB-1S ET is estimated as 78 and 56 W·m-2, for the image-based and model-derived Tends, respectively. In light of the above results, Tends should be estimated a priori when contextual models are applied to low resolution images. Moreover, the consistency over highly heterogeneous areas between model-derived and high-resolution image-based Tends provides a meaningful basis for developing mixed modeling observational approaches.

Using an unsupervised approach of Probabilistic Neural Network (PNN) for land use classification from multitemporal satellite images

Using of Probabilistic Neural Network (PNN) to multichannel image classification.Automatic process to transform the supervised PNN classification to unsupervised.Combination of PNN, hierarchical clustering and cluster validity Index.Land use classification gives a precision with about 3.44% of error.Can be used to large surfaces where the information on soil and crops is limited. The aim of this work is to develop an unsupervised approach based on Probabilistic Neural Network (PNN) for land use classification. A time series of high spatial resolution acquired by LANDSAT and SPOT images has been used to firstly generate the profiles of Normalized Difference Vegetation Index (NDVI) and then used for the classification procedure.The proposed method allows the implementation of cluster validity technique in PNN using Wards method to get clusters. This procedure is completely automatic with no parameter adjusting and instantaneous training, has high ability in producing a good cluster number estimates and provides a new point of view to use PNN as unsupervised classifier. The obtained results showed that this approach gives an accurate classification with about 3.44% of error through a comparison with the real land use and provides a better performance when comparing to usual unsupervised classification methods (fuzzy c-means (FCM) and K-means).

Combining a large aperture scintillometer and estimates of available energy to derive evapotranspiration over several agricultural fields in a semi-arid region

Abstract The objective of the present study was to investigate the potential of a large aperture scintillometer (LAS) combined with a simple available energy model to estimate area-averaged latent heat flux in difficult environmental conditions. The difficulties are related to the sparseness of the vegetation, the heterogeneity of the soil characteristics, and, most importantly, the heterogeneity in terms of soil moisture induced by the “flood irrigation” method. In this context, three sites (Agdal, R3 and Sâada) in the Tensift Al Haouz plain (region of Marrakech city, central Morocco) have been equipped with a LAS and eddy covariance (EC) system (local scale measurements). Agdal and R3 are a flood-irrigated olive yard and wheat field, respectively. Sâada is a drip-irrigated orange orchard. Due to the irrigation method applied, the Agdal and R3 sites shifted from being almost homogeneous between two irrigations (dry conditions) and completely heterogeneous during the irrigation events (large variability of soil moisture along the site), while Sâada was always heterogeneous, at least at the scintillometer footprint scale. Consequently, the comparison between the sensible heat fluxes derived from both LAS and EC showed a large scatter during the irrigation events, while a good correspondence was found in between two irrigations. It was also found that combining LAS and an estimate of the available energy (using a simple model) can provide reasonable large-scale evapotransipration estimates, which are of prime interest for irrigation management.

A Life-Size and Near Real-Time Test of Irrigation Scheduling with a Sentinel-2 Like Time Series (SPOT4-Take5) in Morocco

This paper describes the setting and results of a real-time experiment of irrigation scheduling by a time series of optical satellite images under real conditions, which was carried out on durum wheat in the Haouz plain (Marrakech, Morocco), during the 2012/13 agricultural season. For the purpose of this experiment, the irrigation of a reference plot was driven by the farmer according to, mainly empirical, irrigation scheduling while test plot irrigations were being managed following the FAO-56 method, driven by remote sensing. Images were issued from the SPOT4 (Take5) data set, which aimed at delivering image time series at a decametric resolution with less than five-day satellite overpass similar to the time

Assessment of Equity and Adequacy of Water Delivery in Irrigation Systems Using Remote Sensing-Based Indicators in Semi-Arid Region, Morocco

The irrigation performance criteria of equity and adequacy are of primary concern for irrigation managers. The input data required at various scales to assess irrigation performance, often not available, need costly intensive field campaigns. Remote sensing techniques, used to directly estimate crop evapotranspiration (ETc), became recently an attractive option to assess irrigation performance from individual fields to irrigation scheme or river basin scale. In this study, ETc maps were obtained by combining the FAO-56 dual approach with relationships between crop biophysical variables and NDVI (Normalized Difference Vegetation Index), using high spatial resolution time series of SPOT and Landsat images. This approach was applied for 2002/2003 growing season in Haouz plain, Morocco. Remote sensing-based indicators, reflecting equity and adequacy of the irrigation water delivery were estimated. Adequacy was determined according to Relative Irrigation supply (RIS), Depleted Fraction (DF) and Relative Evapotranspiration (RET) and equity according to the coefficient of variation of ETc. The analysis of these indicators exhibits a great variability among fields. Variability in irrigation performance at all levels, associated factors and possible improvements are discussed. This study demonstrates how remote sensing-based estimates of water consumption provide better estimates of irrigation performance at different scales than the traditional field survey methods.

Estimating cereal evapotranspiration using a simple model driven by satellite data

The SUD-MED project aims at monitoring water resources over Mediterranean regions. As part of the project, this paper presents a method we developed for estimating cereal water requirement. The method consists in driving the simple model developed by the FAO with remotely-sensed data. It was tested on an little area cultivated with wheat in the semi-arid Marrakech plain (Morocco). We use a time series of high spatial resolution images acquired by SPOT-4/HRVIR during the 2001/2002 agricultural season. The method outlines the spatio-temporal patterns of crop cycles. The associated maps of phenological variables and seasonal evapotranspiration appear consistent with regional rainfall and irrigation features. Perspectives of improvement are finally discussed.