الخلاصة:
Oasis  agrosystems  play  an  important  role  in  the  development  of arid  lands.  Water  is  the 
limiting  factor  for  the  improvement  of  these  areas.  However,  if  development  under  irrigation 
contributes to the increase of agricultural production, its extension is accompanied by serious threats to 
the preservation of the environment, especially the quality of the soil,  which is already weakened by 
extreme climatic conditions. In this topic, the spatial variability of the properties of irrigated soils is a 
means of knowing the state of the latter. This study aims to determine the spatial variability of organic 
carbon, salinity, PHWATER, pHKCL, total and active limestone in the soil using a geostatistical approach. 
The present study was carried out in the region of Zelfana  (Ghardaïa) located in the Algerian central 
Sahara. We opted for a random sampling method, where we carried out 15 profiles. The edaphic study 
was  done  on  three  depths  (0-30 cm,  30-60 cm,  60-120 cm). The  main  results  obtained  show  that  the 
irrigation  water  coming  from  the  Albian  aquifer  has  a  medium  to  poor  quality  (C3  S1).  The 
granulometric results show that the study area is characterised by a predominantly sandy to sandy-clay 
texture.  The  analytical  results  show  that  the  soils  studied  are  generally  very  poor  in  organic  carbon 
(CO < 1%) in all three levels. The soil is low to very saline, with EC values at 25°C ranging from 0.64 
to  3.87  dS/m  with  an  ascending  saline  profile.  The  soil  is  slightly  to  highly  calcareous,  with  total 
limestone  values  ranging from  2.08  to  30.94%  15.62%.  The  soil  is  alkaline  with  a  pH  ranging  from 
8.25 to 8.31.The results of the spatial distribution of the studied parameters show a high to very high 
variation of organic carbon, moderate to very high for limestone, and high to moderate for salinity. On 
the other hand, the spatial variability of pHWATER and pHKCL is low. The nugget effect is very low for 
all  parameters  studied.  The  results  of  the  cross-validation  led  to the  selection  of  the  most  reliable 
variogram  models,  namely the circular, spherical, gaussian  and  exponential,  which  were  used  to 
produce the spatial variability maps by ordinary kriging.