The hydrology of the Sahel is characterised by the degradation of the drainage network that induces a lack of large watersheds. In the Niamey degree, different studies have shown the importance of pools in the hydrology of the region. It was shown that different processes such as evaporation or deep infiltration depend on the level of filling of the pools. During the last years, several observations have shown different evolutions of these pools in the Niamey degree.
Our objectives in this paper are to identify the pools and their evolution. Our approach is based on high resolution optical remote sensing data, SPOT/HRV (20m) and SPOT5 (10m) images. This study uses a large data base of optical images (5 images in 1992, 1 image in 1994, 1 image in 1996 and 2 images in 2003). The identification approach is based on the NDVI coefficient calculated from Near Infrared and Red channels for each SPOT image. It is observed that the pools present the lowest values of NDVI in the studied optical images. The distribution of NDVI for pools is estimated for the different images, then a threshold is chosen to separate pools from the other types of land use.
First, we observe the evolution of pool surface and their number in the monsoon period from June to November in 1992. It is clearly shown that the maximum of pool surface corresponds to August 1992. This result is well correlated with rainfall statistics. Second, the estimation of pool surface and number from 1992 to 2003 shows an increase of the pools, particularly in the tiger bush. This behaviour could be explained particularly by the increase of the surface runoff in the region.
This paper discusses the potential of radar signal to characterize the bare surface roughness in arid or semi-arid regions. Two different scales have been considered with two microwave sensors: high resolution ERS/SAR and low resolution ERS Wind Scatterometer instruments. Ground truth measurements were acquired over different arid sites in the South of Tunisia. An empirical approach is proposed to derive the surface roughness from SAR measurements. In this approach, the surface roughness is characterized by a parameter called Zs. Then, a good correlation between SAR and WSC data is demonstrated. Using these two sensors, we are able to derive the backscattering signal versus incidence angle, in the cases of big sand dunes, rocky relief and others. An empirical model is then proposed to retrieve the sand dune percentage within the different cells of the WSC.
This paper discusses the potential of radar signal to characterise the stone cover over bare soil surfaces in arid rocky regions. A high correlation was observed between radar measurements and stone cover percentage. Numerical Moment method based on integral equations of backscattering has been used to study the influence of the stone cover on simulated radar signal. Simulations are validated with measurements acquired in two arid sites. A good agreement is demonstrated between numerical simulations and radar ERS2 measurements. An empirical model is then proposed to inverse radar measurements and retrieve stone cover percentage.
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