Geospatial and common methods for the assessment of land suitability for wheat production in Iran
DOI:
https://doi.org/10.12775/EQ.2024.052Keywords
Cropland suitability, geospatial index, Inceptisols, Mollisols, EntisolsAbstract
Wheat is considered the most important crop in Iran; however, not all of the land in Iran is equally suitable for growing wheat. This study aimed to apply a spatial model for land suitability assessment integrated with geographic information system (GIS) techniques for the wheat crop. Climate and Soil parameters were recognized as factors affecting land suitability for wheat crop in the study area. Three indices were used in assessing land suitability, soil fertility, chemical and physical quality indices. The results of the proposed model (LSI) were compared with the square root and Storie methods. The results showed that most of the units fall within the Moderate suitable class (S2) and the Marginally suitable class (S3) which together represent 88.66% of the total area. About 7.08% of the study area was High suitable and About 2.37% of the study area was unsuitable for wheat crops and those areas correspond to the adverse physical and chemical properties of the soil. The comparison of the results of the three approaches used showed that the present model has a Moderate level of agreement with the square root method (0.516) and showed that the present model has a low level of agreement with the Storie method (0.243). Comparing the results showed that the story model has a high agreement with the square root method (0.884). In the current model, the use of different indicators allows for obtaining results that seem to be more consistent with the current conditions of the region.
References
Ashraf S., Munokyan R., Normohammadan B. & Babaei, A., 2010, Qualitative land suitability evaluation for growth of wheat in the northeast of Iran. Research Journal of Biology Science 5: 548–552.
Akpoti K., Kabo-Bah A.T. & Zwart S.J. 2019, Agricultural land suitability analysis: State-of-the-art and outlooks for integration of climate change analysis. Agric. Syst. 173: 172–208.
AGRA, 2013, Africa Agriculture Status Report: Focus on Stable crops. AGRA. Alliance for a Green Revolution of Africa.
Andrews S.S., Karlen D.L. & Mitchell J.P., 2002, A comparison of soil quality indexing methods for vegetable production systems in northern California. Agric. Ecosyst. Environ. 90: 25–45.
Aparicio V. & Costa J.L., 2007, Soil quality indicators under continuous cropping systems in the Argentinean Pampas. Soil Till. Res. 96: 155–165.
Ball A. & De la Rosa D., 2006, Modeling possibilities for the assessment of soil systems, [in:] A. Uphoff, D.A. Davidson, S.P. Theocharopoulos, R.J. Bloksma (eds), A land evaluation project in Greece using Systems 8(4): 369–384.
Banaei M.H., 1998, Soil Moisture and Temperature Regimes Map of Iran. Soil and Water Institute, Tehran, Iran.
Bodaghabadi M.B., Casasnovas J.A.M., Khakili P., Masihabadi M.H. & Gandomkar A., 2015, Assessment of the FAO traditional land evaluation methods, A case study: Iranian Land Classification method. Soil Use Manag. 31: 384–396.
Booty W.G., Lam D.C.L., Wong I.W.S. & Siconolfi P., 2001, Design and implementation of an environmental decision support system. Environ. Model. Softw. 16: 453–458.
Chen J., 2014, GIS-based multi-criteria analysis for land use suitability assessment in the City of Regina. Environmental Systems Research 3: 1–10.
Cohen J., 1960, A coefficient of agreement for nominal scales. Educational and Psychological Measurement 20 (1): 37–46
Danvi A., Jütten T., Giertz S., Zwart S.J. & Diekkrüger B., 2016, A spatially explicit approach to assess the suitability for rice cultivation in an inland valley in central Benin. Agric. Water Manag. 177: 95–106.
Darwish K.M., Wahba M.M. & Awad F., 2006, Agricultural soil suitability of haplo-soils for some crops in newly reclaimed areas of Egypt. J. Appl. Sci. Res. 2: 1235–1243.
De la Rosa D. & Van Diepen C., 2002, Qualitative and Quantitative Land Evaluation, [in:] W. Verheye (ed.), 1.5 Land Use and Land Cover, Encyclopedia of Life Support System (EOLSS-UNESCO). Eolss Publisher, Oxford (http://www.eolss.net).
De Zorzi P., Barbizzi S., Belli M., Fajgelj A., Jacimovic R., Jeran Z., Sansone U. & van der Perk M., 2008, Soil Sampling Reference Site: The Challenge in Defining Reference Material for Sampling. Appl. Radiat. Isotopes 66: 1588–1591.
Doran J.W. & Jones A.J. (eds), 1996, Methods for Assessing Soil Quality. Soil Science Society of America Special Publication, vol. 49. Soil Science Society of America, Madison, Wisconsin.
Dumanski J. & Pieri C., 2000, Land quality indicators: Research Plan. Agriculture, Ecosystems and Environment 81: 93–102.
El Baroudy A.A., 2011, Land evaluation by integrating remote sensing and GIS for cropping system analysis in Siwa Oasis, Western Desert of Egypt. Egypt. J. Soil Sci. 51: 211–222.
El Baroudy A.A., 2016, Mapping and Evaluating Land Suitability Using a GIS-Based Mode. Catena 140: 96–104.
Esmail B.A. & Geneletti D., 2018, Multi-criteria decision analysis for nature conservation: A review of 20 years of applications. Methods Ecol. Evol. 9: 42–53.
Estes L., Bradley B.A., Beukes H., Hole D.G., Lau M., Oppenheimer M.G., Schulze R., Tadross M. & Turner W.R., 2013, Comparing mechanistic and empirical model projections of crop suitability and productivity: Implications for ecological forecasting. Glob. Ecol. Biogeogr. 22: 1007–1018.
FAO, 1976, A Framework for Land Evaluation. Food and Agriculture Organization of the United Nations, Soils Bulletin No.32. FAO, Rome.
FAO, 1985, Guidelines: Land Evaluation for Irrigated Agriculture. Soil Bulletin No.55. FAO, Rome.
FAO, 2017, The Future of Food and Agriculture–Trends and Challenges. FAO: Rome, Italy, p. 1–180.
FAO, 2020, Food and agriculture organization of the United Nations. https://www.fao.org/faostat/en/#data/QC
Fayyaz H., Yaghmaeian N., Sabouri A. & Shirinfekr A., 2021, Assessing soil fertility index using Fuzzy AHP and parametric methods for tea cultivation with different productivities. Journal of Agricultural Engineering Soil Science and Agricultural Mechanization, (Scientific Journal of Agriculture), 44(3): 275–294.
Gee G.N. & Bauder J.W., 1986, Particle Size Distribution, [in:] A. Klute (ed.), Methods of Soil Analysis Part 1. Physical and Mineralogical Methods, 2nd edition. Agronomy Society of America/Soil Science Society of America, Madison, Wisconsin, p. 383–411.
Ghanbarie E., Jafarzadeh A.A., Shahbazi F. & Servati M., 2016, Comparing Parametric Methods (the Square Root and the Storie) with the Fuzzy Set Theory for Land Evaluation of Khaje Region for Wheat. Int. J. Adv. Biotechnol. Res. 7: 343–351.
Ghansah B., Forkuo E.K., Osei E.F., Appoh R.K., Asare M.Y. & Klutse N.A.B., 2018, Mapping the spatial distribution of small reservoirs in the White Volta Sub-basin of Ghana. Remote Sens. Appl. Soc. Environ. 9: 107–115.
Govaerts B., Sayre K.D. & Deckers J., 2006, A Minimum Data Set for Soil Quality Assessment of Wheat and Maize Cropping in the Highlands of Mexico. Soil Til. Res. 87: 163–174.
Greene R., Devillers R., Luther J.E. & Eddy B.G., 2011, GIS-Based Multiple-Criteria Decision Analysis. Geogr. Compass. 5: 412–432.
Halder J.C., 2013, Land suitability assessment for crop cultivation by using remote sensing and GIS. J. Geogr. Geol. 5: 65–74.
Hamzeh S., Mokarram M. & Alavipanah S.K., 2014, Combination of fuzzy and AHP methods to assess land suitability for barley: a case study of semi-arid lands in the southwest of Iran. Desert 19: 173–181.
Hassan I., Javed M.A., Asif M., Luqman M., Ahmad S.R., Ahmad A., Akhtar S. & Hussain B., 2020, Weighted overlay-based land suitability analysis of agriculture land in Azad Jammu and Kashmir using GIS and AHP. Pakistan J. Agric. Sci. 57: 1509–1519.
He L., Wang S., Peng C. & Tan Q., 2018, Optimization of Water Consumption Distribution Based on Crop Suitability in the Middle Reaches of Heihe River. Sustainability 10, 2119.
Hengl T., Rossiter D.G. & Stein A., 2003, Soil sampling strategies for spatial prediction by correlation with auxiliary maps. Geoderma 120: 75–93.
Herrick J.E., Brown J.R., Tugel A.J., Shaver P.L. & Havstad K.M., 2002, Application of soil quality to monitoring and management: paradigms from rangeland ecology. Agronomy Journal 94: 3–11.
Hoseini Y. & Kamrani M., 2018, Using a fuzzy logic decision system to optimize the land suitability evaluation for a sprinkler irrigation method. Outlook Agric. 47: 298–307.
IIASA, FAO., 2012, Global Agro-Ecological Zones–Model Documentation (GAEZ v. 3.0). International Institute of Applied Systems Analysis: Laxenburg, Austria; Food and Agricultural Organization: Rome, Italy.
Jackson M.L., 1967, Soil Chemical Analysis. Prentice Hall Inc. Engle-wood Cliffs, N. S. Constable & Co. Ltd., London.
Jackson M.L., 1973, Soil Chemical Analysis. Constable and Co. Ltd. Prentice Hall of India Pvt. Ltd., New Delhi.
Jain R., Chand P., Rao S. & Agarwal P., 2020, Crop and Soil Suitability Analysis Using Multi-Criteria Decision Making in Drought-ProneSemi-Arid Tropics in India. J. Soil Water Conserv. 19: 271–283.
Kaim A., Cord A.F. & Volk M., 2018, A review of multi-criteria optimization techniques for agricultural land use allocation. Environ. Model. Softw. 105: 79–93.
Karlen DL., Gardner JC. & Rosek MJ., 1998, A soil quality framework for evaluating the impact of CRP. J. Prod. Agricul. 11: 56–60.
Karthikeyan K., Vasu D., Tiwary P., Cunliffe A.M., Chandran P., Mariappan S. & Singh S.K., 2019, Comparison of Methods for Evaluating the Suitability of Vertisols for Gossypium hirsutum (Bt Cotton) in Two Contrasting Agro-Ecological Regions. Arch. Agron. Soil Sci. 65: 968–979.
Khan, Mohammad Shah Nawaz & Khan, Mohammad Mazhar Ali, 2014, Land Suitability Analysis for Sustainable Agricultural Land Use Planning in Bulandshahar District of Uttar Pradesh. Int. J. Scientific Res. Publications 4(3): 1–11. https://www.researchgate.net/publication/288808164_Land_Suitability_Analysis_for_Sustainable_Agricultural_Land_Use_Planning_in_Bulandshahr_District_of_Uttar_Pradesh
Khiddir S.M., 1986, A Statistical Approach in the Use of Parametric Systems Applied to FAO Framework for Land Evaluation (Dissertation). State University of Ghent, Belgium.
Kidd D., Malone B., McBratney A., Minasny B. & Webb M., 2015, Operational sampling challenges to digital soil mapping in Tasmania, Australia. Geoderma Regional 4: 1–10. Doi:10.1016/j.geodrs.2014.11.002
Kishore C.A., 2016, Land suitability evaluation criteria for agricultural crop selection. Agricultural Research Communication Centre, India.
Klute A. & Dirksen C., 1986, Hydraulic conductivity and diffusivity: laboratory methods, [in:] A. Klute (ed.), Methods of Soil Analysis, Part 1, Physical and Mineralogical Methods, second ed. American Society of Agronomy, Madison, WI, p. 687–734.
Kurukulasuriya P. & Mendelsohn R., 2008, How Will Climate Change Shift Agro-Ecological Zones and Impact African Agriculture? The World Bank: Washington, DC, USA.
Lavkulich L.M., 1981, Methods Manual, Pedology Laboratory. Department of Soil Science, University of British Columbia, Vancouver, British Columbia, Canada.
Leroux L., Castets M., Baron C., Escorihuela M.J., Bégué A. & Seen D.L., 2019, Maize yield estimation in West Africa from crop process-induced combinations of multi-domain remote sensing indices. Eur. J. Agron. 108: 11–26.
Liebig J., 1857, Ueber die Darstellungdes Wasserglases auf nassemWege. Eur. J. Org. Chem. 102: 101–104.
Lindsay W.L. & Norvell W.A., 1978, Development of DTPA soil test for zink, iron, manganese, and copper. Soil Science Society American Journal 43: 966–972.
Malczewski J., 2006, GIS-based multicriteria decision analysis: A survey of the literature. Int. J. Geogr. Inf. Sci. 20: 703–726.
Maleki P., Landi A., Sayyad G.H., Baninemeh J. & Zareian G.H., 2010, Application of fuzzy logic to land suitability for irrigated wheat, [in:] Proceeding of the 19th World Congress of Soil Science, Soil Solutions for a Changing World. Brisbane, Australia.
Mandal U.K., 2016, Soil physical and chemical properties in relation to conservation of natural resources.
Manna P., Basile A., National I., Bonfante A., National I. & Terribile F., 2009, Comparative approaches from empirical to mechanistic simulation modeling in Land Evaluation studies. EGU General Assembly Conference, Abstracts, 2009, p. 7475. Available online: https://ui.adsabs.harvard.edu/abs/2009EGUGA..11.7475M/abstract [Accessed on 26 January 2021].
Manna M., Achary V., Islam M.M., Agrawal T. & Reddy M.K., 2016, The development of a phosphite mediated fertilization and weed control system for rice. Sci. Rep. 6, 24941.
Mansoori M.H., 1992, Guidelines for the classification of multi-purpose lands, Technical Publication No. 832 (212). Soil and Water Research Institute, 87 pp.
Mendoza G. & Martins H., 2006, Multi-criteria decision analysis in natural resource management: A critical review of methods and new modelling paradigms. For. Ecol. Manag. 230: 1–22.
Minasny B. & McBratney A.B., 2006, A conditioned Latin hypercube method for sampling in the presence of ancillary information. Computers and Geosciences 32(9): 1378–1388.
Minasny B. & McBratney A.B., 2007, Spatial prediction of soil properties using EBLUP with the Matérn covariance function. Geoderma 140(4): 324–336.
Mohammadrezaei N., Pazira E., Sokoti R. & Ahmadi A., 2014, Land suitability evaluation for wheat cultivation by Fuzzy-AHP, Fuzzy-Simul Theory approach as compared with the parametric method in the southern plain of Urmia. Bull. Environ. Pharmacol. Life Sci. 3: 112–117.
Mokarram M., Rangzan K., Moezzi A. & Baninemehc J., 2010, Land suitability evaluation for wheat cultivation by fuzzy theory approach as compared with the parametric method. Proceedings of the international archives of the photogrammetry. Remote Sens. Spat. Inf. Sci. 38: 140–145.
Munene P., Chabala L.M. & Mweetwa A.M., 2017, Land Suitability Assessment for Soybean (Glycine max (L.) Merr.) Production in Kabwe District, Central Zambia. J. Agric. Sci. 9, 74.
Mustafa A.A., Singh M., Sahoo R.N., Ahmed N., Khanna M., Sarangi A. & Mishra A.K., 2011, Land suitability analysis for different crops: a multi-criteria decision-making approach using remote sensing and GIS. Researcher 3: 61–84.
Nelson D.W. & Sommers L.E., 1982, Total carbon, organic carbon, and organic matter, [in:] A.L. Page, R.H. Miller, D.R. Keeney (eds), Methods of Soil Analysis. Part 2 Chemical and Microbiological Properties. 2nd edition. ASA-SSSA; Madison, WI, p. 579–595.
Nelson R.E., 1982, Carbonate and gypsum, [in:] A.L. Page (ed.), Methods of soil analysis. Part 2. 2nd ed. Agronomy. Monograph, vol. 9. ASA and SSSA, Madison, WI, p. 181–197.
Nordgren R., 2016, Introduction to Scientific Programming and Simulation Using R, 2nd edition. J. Stat. Softw. 78: 1–4.
Phillips S.J., Dudík M., Elith J., Graham C.H., Lehmann A., Leathwick J. & Ferrier S., 2009, Sample selection bias and presence-only distribution models: Implications for background and pseudo-absence data. Ecol. Appl. 19: 181–197.
Rey D., Holman I., Daccache A., Morris J., Weatherhead E. & Knox J., 2016, Modeling and mapping the economic value of supplemental irrigation in a humid climate. Agric. Water Manag. 173: 13–22.
Rezaei S.A., Gilkes R.J., Andrews S.S. & Arzani H., 2006, Soil quality assessment in semiarid rangeland in Iran. Soil Use Management 21: 402–409.
Rhodes J.D., 1982, Cation exchange capacity, [in:] A.L. Page, R.H. Miller, D.R. Keeney (eds), Methods of Soil Analysis. Part 2. Chemical and Microbiological Properties. American Society of Agronomy, Inc. Soil Science Society of America. Inc. Madison, WI, p. 149–157.
Shahbazi F., Jafarzadeh A., Sarmadian F., Neyshaboury M.R., Oustan S., Anaya-Romero M., Lojo M. & De la Rosa D., 2009, Climate change impact on land capability using MicroLEIS DSS. Int. Agrophysics 23: 277–286.
Shahriar N. & Ghashghaei Sh., 2018, Forecasting Global Wheat Prices and Influences on Currency Reserve in Iran. J. Financ. Econ. (Financial Economics and Development), 11(41): 225–241.
Shewry P.R. & Hey S.J., 2015, The Contribution of Wheat to Human Diet and Health. Food Energy Secur. 4(3): 178–202.
Shields P.G., Smith C.D. & McDonald W.S., 1996, Agricultural Land Evaluation in Australia- A Review. ACLEP (Australian Collaborative Land Evaluation Program), Canberra.
Silva-Gallegos J.J., Aguirre-Salado C., Miranda-Aragón L., Sánchez-Díaz G., Valdez-Lazalde J.R., Pedroza Carneiro J.W. & Flores-Cano J.A., 2017, Locating Potential Zones for Cultivating Stevia rebaudiana in Mexico: Weighted Linear Combination Approach. Sugar Tech. 19: 206–218.
Singh D.P. & Rathore M.S., 2017, Land Characterization and Soil-Site Suitability for Major Crops of Pratapgarh District, Rajasthan. J. Indian Soc. Soil Sci. 65: 10–15.
Soil Survey Staff., 2014, Keys to Soil Taxonomy, 12th edition. USDA Natural Resources Conservation Service.
Storie R., 1978, Storie Index Rating. University of California Division of Agricultural Sciences Special Publication 3203, Oakland.
Sys C., Van Ranst E. & Debaveye J., 1991, Land Evaluation, Part I. Principles in Land Evaluation and Crop Production Calculations. General Administration for development cooperation, Brussels, p. 40–80.
Sys C., Van Ranst E., Debaveye J. & Beernaert F., 1993, Land Evaluation. Part III. Crop Requirements. Agr. Publication No. 7. ITC, Ghent.
Van Wart, J., van Bussel L.G.J., Wolf J., Licker R., Grassini P., Nelson A., Boogaard H., Gerber J., Mueller N.D., Claessens L., et al., 2013, Use of Agro-climatic Zones to Upscale Simulated Crop Yield Potential. Field Crops Res. 143: 44–55.
Van de Graaff R.H.M., 1988, Land Evaluation, [in:] R.H. Gunn, J.A. Beattie, R.E. Reid, R.H.M. van de Graaff (eds), Australian Soil and Land Survey Handbook: Guidelines for Conducting Surveys. Inkata Press, Sydney, p. 258–281.
Vasu D., Srivastava R., Patil N.G., Tiwary P., Chandran P. & Kumar Singh S., 2018, A Comparative Assessment of Land Suitability Evaluation Methods for Agricultural Land Use Planning at Village Level. Land Use Policy 79: 146–163.
Vázquez-Quintero G., Prieto-Amparán J.A., Pinedo-Alvarez A., Valles-Aragón M.C., Morales-Nieto C.R. & Villarreal-Guerrero F., 2020, GIS-Based Multicriteria Evaluation of Land Suitability for Grasslands Conservation in Chihuahua, Mexico. Sustainability 12, 185.
Waltman D., 2012, Newhall Simulation Model V 1.6.0 (JAVA Core Model).
Yu Y., Shi L., Huai H. & Li C., 2014, Study on the Application of Information Technologies on Suitability Evaluation Analysis in Agriculture. New Trends Nonlinear Control 420: 165–176.
Zadeh L.A., 1965, Fuzzy sets. Information and Control 8: 338–353.
Zahirnia A. & Matinfar H., 2016, Estimation of yield of irrigated wheat fields based on data from Landsat 8 satellite in southwestern region of Khuzestan province, [in:] Proceeding of the First National Conference on Remote Sensing and Geographic Information Systems in Earth Sciences. Shiraz, Iran.
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Copyright (c) 2024 Maria Kohani; Hamid Reza Matinfar, Mahmood Rostaminia, Seyed Omid Reza Shobairi, Sun Lingxiao, Zhang Haiyan, Li Chunlan, He Jing; Behnam Asghari Beirami; Qirghizbek Ayombekov
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