Quantitative Estimation of Annual Soil Loss by Integration of Remote Sensing, GIS, and Universal Soil Loss Equation (Case Study: Tartus District, Syria)
Abstract views: 291 / PDF downloads: 35
Abstract
This paper describes the procedures employed to integrate Remote Sensing(RS) and Geographic Information System (GIS) techniques in an effort to characterize the
spatial distribution of the risk of soil erosion by water on lands of Tartus district, Syria.
The universal soil loss equation (USLE) is used to calculate the annual soil loss rates for
Tartus soils. Mainly Landsat Enhanced Thematic Mapper (ETM) dated 5/2009, thematic
maps such as land capabilities, landuse, digital elevation model (DEM) and climate data
were used to determine USLE factors. Integration of these data sets resulted in a map
of polygons with unique combinations of USLE factor values. The study showed that
water erosion mainly threatens those soils on hilly lands where vegetation is sparse or
absent and exposed to heavy rainfall. Mostly these lands extend around these towns
and villages of Tiro, Jwibat, Hrison, Shiekh Bader, HamamWasel, Dulbeh and Safasif,
where these soil loss was about 150 t h-1 y-1 which account for 0.13% of the soil loss.
These quantities of annual soil loss can be considered as a very severe amounts, and
if this water erosion persists at these high rates, the soil will be eroded and the parent
material will be exposed in these regions. The study also mentioned a package of
remedial measures so as to combat land degradation in the study area.
Key words: Water erosion, USLE, Landsat ETM, GIS, Sustainable land use, Tartus.
Downloads
References
Abed, Mohammad 2000. The Development of Latakia
GIS-Based Soil Database and Related Applied
Model, Case Study: Latakia district, Syria. Ph.
D. thesis.
ACSAD 2009. Monitoring and assessing land
degradation process, selected methods and case
studies. The Arab Center for the Studies of Arid
Zones and Dry Lands, Damascus.
Bu, Zhaohong and Li, Quanying 1995. Preliminary
study on the method of soil erodibility value
mapping. Journal of Rural Eco-Environment 11(1):
-9.
Bu, Zhaohong, Sun Jinzhuang, Zhou Fujiang, Tang,
Wanlong and Xi, Chengfan. 1997. A study on
quantitative remote sensing method of soil
erosion and its application. Journal of ACTA
Pedologica Sinica 34(3): 235-245.
Bu, Zhaohong, Tang, Wanlong, Pan and Xianzhang
Algorithm of terrain factors of GIS pixel in
monitoring soil loss by remote sensing. Journal of
ACTA Pedologica Sinica 31(3): 323-329.
Dickinson, W.T., Rudra, R.P. and Wall, G.J. 1989.
Nomographs and software for field and bank
erosion. Journal of Soil and Water Conservation.
Nov-Dec: 596-600.
Table 6. The annual soil loss, A, in Tartus district
Soil loss grade Soil loss
(t hm-2 year-1)
Area
(km2)
% of
total
Very slight 0-1 763.6122 39.95
Slight 1-5 598.3497 31.30
Low 5-10 262.2051 13.72
Moderate 10-25 218.6757 11.44
High 25-50 56.5992 2.96
Very high 50-80 9.7146 0.51
Severe 80-150 2.2320 0.12
Very severe 150-250 0.2313 0.01
6200
AL-ABED et al.
Dong, Liang 1997. Application of GIS to nonpoint
source pollution in West Lake watershed: a
case study. Master thesis. Hangzhou. Zhejiang
Agricultural University. pp. 20-24.
FAO 1965. Soil erosion by water some measures for
its control on cultivated lands. Rome. pp. 141-
GORS (General Organization of Remote Sensing,
agriculture faculty- Damascus University) 1991.
Study on lands and forests of the coastal region
using remote sensing techniques: Tartus District.
Damascus University press.
Juergens, C., Fander, M.W. 1993. Soil erosion
assessments by means of Landsat TM and
ancillary digital data in relation to water quality.
Journal of Soil Technology (6):215-223. 6(3): 215-
Kbebo Issa, Bu Issa Abdelaziz, Ibrahim Jihad 2015.
Study of soil erosion in the coastal area Latakia
& Tartus. (in cooperation with Ministry of
Environment).
Michell, J Kent and Bubenzer, Gary D. 1980. Soil
erosion. Jhon Willy & Sons Ltd. 17-62.
Wischmeier, W.H. and Smith, D.D. 1965. Predicting
rainfall-erosion losses from cropland east of the
Rocky Mountains, Agriculture Handbook No.
USDA. Washington, D.C.
Wischmeier, W.H., Johnson, C.B. and Cross, B.V.
A soil erodibility nomograph for farm
land and construction sites. Journal of Soil water
conservation 26: 189.
Wischmeier, W.H. and Smith, D.D. 1978. Predicting
rainfall erosion losses, a guide to conservation
planning. Agriculture Handbook No. 537.
USDA. Washington, D. C. 47 pp.
You Songcai and Li Wenqing 1999. Estimation of
soil erosion supported by GIS: A case study
in Guanji township, Taihe, Jiangxi. Journal of
Natural Resources 14(1): 63-68.
Downloads
Submitted
Published
Issue
Section
License