The Mapping of the Soils’ Degradation State by Adaptation the PAP/RAC Guidelines in the Watershed of Wadi Arbaa Ayacha, Western Rif, Morocco

The watershed of the Arbaa Ayacha River is an environment favorable to the development of the phenomena of water erosion as a result of its topographic features, lithological and climate. Therefore it has been the subject of evaluation of states erosive and of different causal factors of the risk of erosion by adaptation of cross-matrices based on directives PAP/RAC (Priority Actions Programme/Regional Activity Centre) [1]. This method is based on three approaches. The predictive approach provides a synthetic map of the distribution of the erosive states, with 51% of the basin subjected to high risks. The descriptive mapping of the various forms of erosion shows an enormous extension of stripping and sheet erosion (91%), superficial gullies and moderately deep gullies are growing in view of the gathering of runoffs from upstream to the downstream. The superposition of the results of both predictive and descriptive approaches gives a consolidated map PAP/RAC whose analysis shows that soils’ loss throughout the basin is proportional to the increase of the major factors of water erosion according to the level of importance: The topographical factor—soil types—slope-lithology following a positive linear relationship, while the order of the parameters that are negative linear relationship is density of vegetation cover-land cover [2]. This same map gives maximal losses corresponding mainly to friable lithologic natural areas of badlands at the center of the basin which correspond to Tensift’s terraces [3]. In the downstream basin, the combined effect of deep ravines and banks sapements promotes high risk while in the upstream, the localized solifluxions and gravity screens participate in serious losses.

Mapping forest fires by nonparametric clustering analysis

Fires have a noteworthy role to play with regards to ecological and environmental losses in Mediterranean forests. In addition to ecological impacts, fire may create economic, social as well as cultural changes. The detection of fire-scars has critical importance to help decrease losses.In the present study, forest fires recorded in Antalya, one of the most important ecological and tourist regions within the Western Mediterranean, were clustered and mapped. Since the dominant factors and devastation records derived from the cases had nominal-scaled properties, a categorical databased nonparametric clustering algorithm was performed in this evaluation. The proposed tool, k-modes algorithm,uses modes instead of means for clustering. The algorithm may be implemented quickly and does not make distributional assumptions concerning the available data. It uses a frequency-based method to update the modes of the fires.The derived modes from the maps may be useful information for local authorities to manage. In conclusion, the proposed nonparametric clustering procedure may be employed to build a decision-support system to monitor and identify fire activities and to enhance fire management efficiency.