Optimal use of Agricultural Land in an Arid Region from Using GIS and Linear Algorithm: Al-Hasaka-SYRIA

Year 2019, , 268 - 276, 08.12.2019

Rukea Al-hasn Younes Idriss Othman Hammal

https://doi.org/10.30897/ijegeo.619478

Abstract

 

This research aims to evaluate the lands of Wadi
Khirbet al-Malihah area in Al-hasaka province (2016-2018) and
determine the optimal land use. A geo-pedological soil survey was initiated,
and 10 soil profiles representing the physiographic in the study area were
collected for some chemical and physical properties analysis. The land evaluation
was achieved using LAMIS (Land Management Information System) program under the
GIS platform. The evaluation was done applying map-algebra on both crops'
requirements with parametric conditions of lands and climate characteristics.
The resulting evaluation showed according to the suggested scenario (limited
irrigation water), crops with the lowest water requirements were selected:
moderate suitable S2 by 41.52%, limit suitable S3 by 28.27% of the study area.
Linear programming was used to produce the final optimal land use map according
to three criteria: costs, gross margin and water requirements. The results show
that there are diversity advantage and the land area of study that suit to be
area cropping commodities are tested with an area of 41895 ha. Land use in the Wadi
Khirbet al-Malihah achieving profitability with the optimal combination of
cropping wheat (29.579%), the lentils (22.257%) and Kinua (9.283%).

Keywords

: Optimal; land use, land evaluation, Geographic information system, Linear programming

References

• Agriculture statistical group.(2016).Syrian Ministry of Agriculture and Agrarian Reform, Division of Agricultural Statistics Computer Centre: Damascus, Syria.Ali, M.(2010). Years of Drought: A Report on the Effects of Drought on the Syrian. Peninsula, Heinrich-Böll-Stiftung - Middle East Office.Alsheikh, M., Ahmed, M. (2002). Development of Mixed Farming System in a Newly Reclaimed Area in Egypt. Session No. LMP3.12. Abstract No. 107Andrew, J. (2007).Mason "Solving linear programs using Microsoft Excel SOLVER" University of Auckland. Balazs, O., Opara, N., Beesea, F. (2005). A simple method for measuring the carbonate content of soil. Soil Sci. Soc. Am. J., 69, 1066–1068.Ball, J. (2002). Towards a methodology for mapping ‘regions for sustainability’using PPGIS. Progress in Planning, 58(2), 81-140.Bani, N., Jamal, R.H.,Farshad, A.(2003). land evaluation for land use planning with especial attention to sustainable fodder production in Rouzeh Chi catchment of Orumiyeh area –Iran international Institute for geo- information science and Earth observation Enschede,The Netherlands .Master Thesis.Bojorquez-Tapia, L. A., Diaz-Mondragon, S., & Ezcurra, E. (2001). GIS-based approach for participatory decision making and land suitability assessment. International Journal of Geographical Information Science, 15(2), 129-151.Burton, Carrol., Wall .(1999). Quantitative Methods for Business & Economics,Longman, NY.Climate Atlas of Syria.(1977). Ministry of Defence. Meteorological Department. Climate Division Service of military geography, pp150.Conyers, M., Davey, B.(1988). Observations on some routine methods for soil pH determination. Soil Science, 145: 29-36.Edrich, M. (2005). Strategies and Policies for Sustainable and Integrated Planning in Nablus City, Unpublished Master Thesis, College of Graduate Studies, An-Najah National University, p 30.(in Arabic)Hoobler, B. M., Vance, G. F., Hamerlinck, J. D., Munn, L. C., & Hayward, J. A. (2003). Applications of land evaluation and site assessment (LESA) and a geographic information system (GIS) in East Park County, Wyoming. Journal of Soil and Water Conservation, 58(2), 105-112.Idriss, Y. (2011)"2". Land Management Information System (LAMIS). first edition. General organization for Remote Sensing. Damascus. 25 p. (in Arabic) Ministry of Agriculture and Agrarian Reform. (2016). Annual Agricultural Statistical Abstract. Damascus. (in Arabic)Rhoades,D.(1990). Determining soil salinity from measurements of electrical conductivity. Commun. Soil Sci. Plant Anal. 21: 1887-1926.Richards, L.A. (1954). Diagnosis and improvement of saline and alkali soils. USDA Agric. Handbook 60. Washington, D. CSankri, N. (1987). Environment, vegetation and grazing areas of the dry and highly drought areas of Syria, Publications of the Faculty of Agriculture, University of Aleppo. Aleppo, Syria, 793 p. (in Arabic).Sarker, R., Talukdar, S., Anwarul, H. (1997). “Determination of optimal crop mix for crop cultivation in Bangladesh.” Appl. Math. Sciences,21(10):621-632.Scarpari, S., Beaclair, F.(2010). “Optimized agricultural planning of Sugarcane using linear programming” Revistainvestigacionoperacional, vol. 31,no 2, pp.126-132.Syria Climate Atlas.(1977). Syrian Arab Republic, Ministry of Defense, Directorate General of Meteorology, Directorate of Climate, this Atlas was prepared and printed under the supervision of the Directorate General of Meteorology. (in Arabic)Taei, D., Obeidi, M., Abdel Hamid, A., Omar, N .(2009). Applications and Analysis of Quantitative Business System WinQSB. (Memory library). Baghdad, Iraq. Number of pages 220. (in Arabic)Trung, N. H., Tri, L. Q., Van Mensvoort, M. E. F., & Bregt, A. K. (2006). 14 Comparing Land-use Planning Approaches in the Coastal Mekong Delta of Vietnam. Environment and livelihoods in tropical coastal zones, 177.USDA .(2006). “Keys to Soil Taxonomy” United State Department of Agriculture, Natural Resources Conservation Service (NRCS) tenth edition, 2006.68Vijay, G.(2002). " Financial analysis using Excel “، VJ books Inc, Canada.p227.Walkley, A., Black, I.A. (1934). An examination of the Degtjareff method for determination soil organic matter, and a proposed modification of the chromic acid titration method. Soil, Sci.34:29-38.