Skip to main content

Advertisement

SpringerLink
Log in

Land capability assessment of Sali watershed for agricultural suitability using a multi-criteria-based decision-making approach

  • Research
  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

The assessment of land’s agricultural potential, through a land capability evaluation, delves into its innate limitations, crop suitability, and responses to soil management. In regions where agriculture reigns supreme, socio-economic development is inexorably linked to the agricultural sector, making the optimal utilization of land resources an imperative pursuit. The pursuit of this objective is underpinned by the selection of new agricultural areas and the determination of which crops thrive in specific locations, for which the multi-criteria decision-making (MCDM) method emerges as an ideal choice. This comprehensive research endeavour revolves around the intricate interplay of climatic, edaphic, fertility, topographical, and socioeconomic determinants. Within this intricate web, a total of 15 determinants play a pivotal role, including precipitation, potential evapotranspiration (PET), soil texture, drainage, soil organic-carbon, nitrogen content, pH, clay content, river proximity, land use/land cover (LULC), slope, temperature, social suitability, irrigation density, and elevation. To weigh these determinants, the Analytical Hierarchy Process (AHP) comes into play, ultimately revealing that the dominant influences on land capability stem from the realms of climate and soil. The watershed’s terrain analysis revealed a distinct suitability contrast: 168 km2 highly suitable, 181.3 km2 moderate, and 429 km2 low. The eastern and northeastern sectors were notably promising. Rigorous validation, using the ROC curve, confirmed the reliability and precision. The process yielded an impressive 83.2% AUC, unequivocally confirming the assessment’s remarkable accuracy and dependability.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request.

References

  • Abd-Elmabod, S. K., Jordán, A., Fleskens, L., Phillips, J. D., Muñoz-Rojas, M., van der Ploeg, M., & de la Rosa, D. (2017). Modelling agricultural suitability along soil transects under current conditions and improved scenario of soil factors. In Soil mapping and process modelling for sustainable land use management (pp. 193–219). Elsevier. https://doi.org/10.1016/B978-0-12-805200-6.00007-4

    Chapter  Google Scholar 

  • Abdulazeez, A. (2017). Effects of soil texture on vegetative and root growth of Senna obtusifolia seedlings indigenous to Bichi, Sudan savannah of Northern Nigeria, in green house conditions. IOSR Journal of Agriculture and Veterinary Science (IOSR-JAVS), 10, 70–74.

    Article  Google Scholar 

  • Abdul-Baki, A. A., & Stommel, J. R. (1995). Pollen viability and fruit set of tomato genotypes under optimum and high-temperature regimes. HortScience, 30(1), 115–117.

    Article  Google Scholar 

  • Abou EL-Magd, I., & Tanton, T. W. (2003). Improvements in land use mapping for irrigated agriculture from satellite sensor data using a multi-stage maximum likelihood classification. International Journal of Remote Sensing, 24(21), 4197–4206.

    Article  ADS  Google Scholar 

  • Adriyanshah, N. F., Khalid, N. H. N., Usman, F., Izhar, A. S. M., Jawas, J. A., & Jalal, W. N. W. (2022, March). Development of corrosion hazard map in peninsular Malaysia using inverse distance weighting (IDW) interpolation. In: Advances in civil engineering materials: Selected articles from the International Conference On Architecture And Civil Engineering (ICACE2021) (pp. 225–233). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-16-8667-2_24

  • Akıncı, H., Özalp, A. Y., & Turgut, B. (2013). Agricultural land use suitability analysis using GIS and AHP technique. Computers and Electronics in Agriculture, 97, 71–82.

    Article  Google Scholar 

  • Aldababseh, A., Temimi, M., Maghelal, P., Branch, O., & Wulfmeyer, V. (2018). Multi-criteria evaluation of irrigated agriculture suitability to achieve food security in an arid environment. Sustainability, 10(3), 803.

    Article  Google Scholar 

  • Al-Hasani, A. A. J., & Shahid, S. (2022). Spatial distribution of the trends in potential evapotranspiration and its influencing climatic factors in Iraq. Theoretical and Applied Climatology, 150(1–2), 677–696.

    Article  ADS  Google Scholar 

  • Allen, R. G., Pereira, L. S., Raes, D., & Smith, M. (1998). Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. Fao, Rome, 300(9), D05109.

    Google Scholar 

  • Alloway, B. J. (2008). Micronutrients and Crop Production: An Introduction. In B. J. Alloway (Ed.), Micronutrient Deficiencies in Global Crop Production. Dordrecht: Springer. https://doi.org/10.1007/978-1-4020-6860-7_1

    Chapter  Google Scholar 

  • Aloni, B., Peet, M., Pharr, M., & Karni, L. (2001). The effect of high temperature and high atmospheric CO2 on carbohydrate changes in bell pepper (Capsicum annuum) pollen in relation to its germination. Physiologia Plantarum, 112(4), 505–512.

    Article  PubMed  CAS  Google Scholar 

  • Anusha, B. N., Babu, K. R., Kumar, B. P., Sree, P. P., Veeraswamy, G., Swarnapriya, C., & Rajasekhar, M. (2023). Integrated studies for land suitability analysis towards sustainable agricultural development in semi-arid regions of AP. India. Geosystems and Geoenvironment, 2(2), 100131.

    Article  Google Scholar 

  • Arabameri, A., Rezaei, K., Cerdà, A., Conoscenti, C., & Kalantari, Z. (2019). A comparison of statistical methods and multi-criteria decision making to map flood hazard susceptibility in Northern Iran. Science of the Total Environment, 660, 443–458. https://doi.org/10.1016/j.scitotenv.2019.01.021

    Article  PubMed  ADS  CAS  Google Scholar 

  • Arabameri, A., Tiefenbacher, J. P., Blaschke, T., Pradhan, B., & Tien Bui, D. (2020). Morphometric analysis for soil erosion susceptibility mapping using novel gis-based ensemble model. Remote Sensing, 12(5), 874. https://doi.org/10.3390/rs12050874

    Article  ADS  Google Scholar 

  • Atalay, I. (2006). Toprak Olusumu, Sınıflandırılması ve Cografyası. Meta Basım Matbaacılık, Izmir (in Turkish). Çevre ve Orman Bakanlığı.

  • Baker, J. T., & Allen, L. H. (1993). Contrasting crop species responses to CO2 and temperature: Rice, soybean and citrus. Vegetation, 104, 239–260.

    Article  Google Scholar 

  • Bera, A. (2017). Assessment of soil loss by universal soil loss equation (USLE) model using GIS techniques: A case study of Gumti River Basin, Tripura, India. Modeling Earth Systems and Environment, 3(1), 29. https://doi.org/10.1007/s40808-017-0289-9

    Article  Google Scholar 

  • Bera, A., Mukhopadhyay, B. P., & Das, D. (2019). Landslide hazard zonation mapping using multi-criteria analysis with the help of GIS techniques: A case study from Eastern Himalayas, Namchi, South Sikkim. Natural Hazards, 96(2), 935–959. https://doi.org/10.1007/s11069-019-03580-w

    Article  Google Scholar 

  • Bera, A., & Mukhopadhyay, B. P. (2023). Identification of suitable sites for surface rainwater harvesting in the drought prone Kumari River basin, India in the context of irrigation water management. Journal of Hydrology, 129655(1–17) https://doi.org/10.1016/j.jhydrol.2023.129655

  • Brady, N. C., & Weil, R. R. (1999). The nature and properties of soils Prentice-Hall Inc. New Jersey: Upper Saddle River.

    Google Scholar 

  • Brady, N. C., Weil, R. R., & Weil, R. R. (2008). The nature and properties of soils (Vol. 13, pp. 662–710). Upper Saddle River, NJ: Prentice Hall.

    Google Scholar 

  • Branca, G., Lipper, L., McCarthy, N., & Jolejole, M. C. (2013). Food security, climate change, and sustainable land management A Review. Agronomy for Sustainable Development, 33, 635–650.

    Article  Google Scholar 

  • Brosens, L., Campforts, B., Robinet, J., Vanacker, V., Opfergelt, S., Ameijeiras-Mariño, Y., & Govers, G. (2020). Slope gradient controls soil thickness and chemical weathering in subtropical Brazil: Understanding rates and timescales of regional soilscape evolution through a combination of field data and modelling. Journal of Geophysical Research: Earth Surface, 125(6), e2019JF005321.

    Article  ADS  Google Scholar 

  • Cialella, A. T., Dubayah, R., Lawrence, W., & Levine, E. (1997). Predicting soil drainage class using remotely sensed and digital elevation data. Photogrammetric Engineering and Remote Sensing, 63(2), 171–177.

    Google Scholar 

  • Curtin, D., Campbell, C. A., & Jalil, A. (1998). Effects of acidity on mineralization: PH-dependence of organic matter mineralization in weakly acidic soils. Soil Biology and Biochemistry, 30(1), 57–64.

    Article  CAS  Google Scholar 

  • Dai, Y., Xin, Q., Wei, N., Zhang, Y., Shangguan, W., Yuan, H., & Lu, X. (2019). A global high-resolution data set of soil hydraulic and thermal properties for land surface modeling. Journal of Advances in Modeling Earth Systems, 11(9), 2996–3023.

    Article  ADS  Google Scholar 

  • Darwinkel, A. (1980). Grain production of winter wheat in relation to nitrogen and diseases. 1. Relationship between nitrogen dressing and yellow rust infection. Zeitschrift fur Acker-und Pflanzenbau, 149(4), 299–308.

    Google Scholar 

  • Das, S., & Gupta, K. (2019). Soil survey to support land use/land cover planning in BPS and BPM region in Gangajalghati block, West Bengal, India. Spatial Information Research, 27(5), 573–586. https://doi.org/10.1007/s41324-019-00257-1

    Article  MathSciNet  Google Scholar 

  • De Montis, A., De Toro, P., Droste-Franke, B., Omann, I., & Stagl, S. (2000, May). Criteria for quality assessment of MCDA methods. In 3rd Biennial Conference of the European Society for Ecological Economics, Vienna (pp. 3–6).

  • Elsheikh, R., Shariff, A. R. B. M., Amiri, F., Ahmad, N. B., Balasundram, S. K., & Soom, M. A. M. (2013). Agriculture Land Suitability Evaluator (ALSE): A decision and planning support tool for tropical and subtropical crops. Computers and Electronics in Agriculture, 93, 98–110.

    Article  Google Scholar 

  • Fathizad, H., Pakbaz, N., Sodaiezadeh, H., & Shojaei, S. (2017). Exploring canola planting area using AHP associated with GIS in Meymeh-Zarinabad of Iran. Spatial Information Research, 25, 371–379. https://doi.org/10.1007/s41324-016-0064-4

    Article  Google Scholar 

  • Giger, M., Liniger, H., Sauter, C., & Schwilch, G. (2018). Economic benefits and costs of sustainable land management technologies: An analysis of WOCAT’s global data. Land Degradation & Development, 29(4), 962–974. https://doi.org/10.1002/ldr.2429

    Article  Google Scholar 

  • Giller, K. E., Witter, E., Corbeels, M., & Tittonell, P. (2009). Conservation agriculture and smallholder farming in Africa: The heretics’ view. Field Crops Research, 114(1), 23–34.

    Article  Google Scholar 

  • Goovaerts, P. (1998). Geostatistical tools for characterizing the spatial variability of microbiological and physico-chemical soil properties. Biology and Fertility of Soils, 27, 315–334.

    Article  CAS  Google Scholar 

  • Gregorich, E. G., Lapen, D. R., Ma, B. L., McLaughlin, N. B., & VandenBygaart, A. J. (2011). Soil and crop response to varying levels of compaction, nitrogen fertilization, and clay content. Soil Science Society of America Journal, 75(4), 1483–1492.

    Article  ADS  CAS  Google Scholar 

  • Hamidy, N., Alipur, H., Nasab, S. N. H., Yazdani, A., & Shojaei, S. (2016). Spatial evaluation of appropriate areas to collect runoff using Analytic Hierarchy Process (AHP) and Geographical Information System (GIS) (case study: The catchment “Kasef” in Bardaskan. Modeling Earth Systems and Environment, 2, 1–11. https://doi.org/10.1007/s40808-016-0230-7

    Article  Google Scholar 

  • Hassan, I., Javed, M. A., Asif, M., Luqman, M., Ahmad, S. R., Ahmad, A., & Hussain, B. (2020). Weighted overlay based land suitability analysis of agriculture land in Azad Jammu and Kashmir using GIS and AHP. Pakistan Journal of Agricultural Sciences, 57(6), 1509–1519. https://doi.org/10.21162/PAKJAS/20.9507

    Article  Google Scholar 

  • Hengl, T., Heuvelink, G. B., Kempen, B., Leenaars, J. G., Walsh, M. G., Shepherd, K. D., & Tondoh, J. E. (2015). Mapping soil properties of Africa at 250 m resolution: Random forests significantly improve current predictions. PLoS ONE, 10(6), e0125814.

    Article  PubMed  PubMed Central  Google Scholar 

  • Hengl, T., Leenaars, J. G., Shepherd, K. D., Walsh, M. G., Heuvelink, G. B., Mamo, T., & Kwabena, N. A. (2017a). Soil nutrient maps of Sub-Saharan Africa: Assessment of soil nutrient content at 250 m spatial resolution using machine learning. Nutrient Cycling in Agroecosystems, 109, 77–102.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Hengl, T., Mendes de Jesus, J., Heuvelink, G. B., Ruiperez Gonzalez, M., Kilibarda, M., Blagotić, A., & Kempen, B. (2017b). SoilGrids250m: Global gridded soil information based on machine learning. PLoS ONE, 12(2), e0169748.

    Article  PubMed  PubMed Central  Google Scholar 

  • Horn, R., Simota, C., Fleige, H., Dexter, A., Rajkai, K., & Rosa, D. D. L. (2002). Prediction of soil strength of arable soils and stress dependent changes in ecological properties based on soil maps. Journal of Plant Nutrition and Soil Science, 165(2), 235–239.

    Article  CAS  Google Scholar 

  • Howell, T. A. (2001). Enhancing water use efficiency in irrigated agriculture. Agronomy Journal, 93(2), 281–289.

    Article  Google Scholar 

  • Iftikar, W., Chattopadhyay, G. N., Majumdar, K., & Sulewski, G. D. (2009). Use of village-level soil fertility maps as a fertilizer decision support tool in the red and lateritic soil zone of India. Better Crops, 94(3), 10–12.

    Google Scholar 

  • Kakani, V. G., Prasad, P. V. V., Craufurd, P. Q., & Wheeler, T. R. (2002). Response of in vitro pollen germination and pollen tube growth of groundnut (Arachis hypogaea L.) genotypes to temperature. Plant, Cell & Environment, 25(12), 1651–1661.

    Article  Google Scholar 

  • Kidd, D., Webb, M., Malone, B., Minasny, B., & McBratney, A. (2015). Digital soil assessment of agricultural suitability, versatility and capital in Tasmania, Australia. Geoderma Regional, 6, 7–21.

    Article  Google Scholar 

  • Koubouris, G. C., Metzidakis, I. T., & Vasilakakis, M. D. (2009). Impact of temperature on olive (Olea europaea L.) pollen performance in relation to relative humidity and genotype. Environmental and Experimental Botany, 67(1), 209–214.

    Article  Google Scholar 

  • Koulouri, M., & Giourga, C. (2007). Land abandonment and slope gradient as key factors of soil erosion in Mediterranean terraced lands. CATENA, 69(3), 274–281.

    Article  Google Scholar 

  • Kumar, S., Srivastava, P. K., & Snehmani. (2017). GIS-based MCDA–AHP modelling for avalanche susceptibility mapping of Nubra valley region, Indian Himalaya. Geocarto International, 32(11), 1254–1312. https://doi.org/10.1080/10106049.2016.1206626

    Article  ADS  Google Scholar 

  • Kumar, A., Pramanik, M., Chaudhary, S., & Negi, M. S. (2021). Land evaluation for sustainable development of Himalayan agriculture using RS-GIS in conjunction with analytic hierarchy process and frequency ratio. Journal of the Saudi Society of Agricultural Sciences, 20(1), 1–17. https://doi.org/10.1016/j.jssas.2020.10.001

    Article  Google Scholar 

  • Kurt, I., Ture, M., & Kurum, A. T. (2008). Comparing performances of logistic regression, classification and regression tree, and neural networks for predicting coronary artery disease. Expert Systems with Applications, 34(1), 366–374. https://doi.org/10.1016/j.eswa.2006.09.004

    Article  Google Scholar 

  • Lal, R. (2013). Climate-strategic agriculture and the water-soil-waste nexus. Journal of Plant Nutrition and Soil Science, 176(4), 479–493.

    Article  MathSciNet  CAS  Google Scholar 

  • Levine, E. R., Knox, R. G., & Lawrence, W. T. (1994). Relationships between soil properties and vegetation at the Northern Experimental Forest, Howland. Maine. Remote Sensing of Environment, 47(2), 231–241.

    Article  ADS  Google Scholar 

  • Li, S., Wang, G., Sun, S., Hagan, D. F. T., Chen, T., Dolman, H., & Liu, Y. (2021). Long-term changes in evapotranspiration over China and attribution to climatic drivers during 1980–2010. Journal of Hydrology, 595, 126037.

    Article  Google Scholar 

  • Loupassaki, M., Vasilakakis, M., & Androulakis, I. (1997). Effect of pre-incubation humidity and temperature treatment on the in vitro germination of avocado pollen grains. Euphytica, 94, 247–251.

    Article  Google Scholar 

  • Lu, H., Zheng, D., Yang, K., & Yang, F. (2020). Last-decade progress in understanding and modelling the land surface processes on the Tibetan Plateau. Hydrology and Earth System Sciences, 24(12), 5745–5758.

    Article  ADS  Google Scholar 

  • Martins, A. A. A., Madeira, M. V., & Refega, A. A. G. (1995). Influence of rainfall on properties of soils developed on granite in Portugal. Arid Land Research and Management, 9(3), 353–366.

    Google Scholar 

  • Matinfar, H. R., Sarmadian, F., & Alavipanah, S. K. (2011). Use of DEM and ASTER sensor data for soil and agricultural characterizing. International Agrophysics, 25(1), 37–46.

    Google Scholar 

  • McCauley, A., Jones, C., & Jacobsen, J. (2009). Soil pH and organic matter. Nutrient Management Module, 8(2), 1–12.

    Google Scholar 

  • McLauchlan, K. K. (2006). Effects of soil texture on soil carbon and nitrogen dynamics after cessation of agriculture. Geoderma, 136(1–2), 289–299.

    Article  ADS  CAS  Google Scholar 

  • Merasha, E. (1999). Annual Rainfall and potential evapotranspiration in Ethiopia. Ethiopian Journal of Natural Resources, 1, 137–154.

    Google Scholar 

  • Mesgaran, M. B., Madani, K., Hashemi, H., & Azadi, P. (2017). Iran’s land suitability for agriculture. Scientific Reports, 7(1), 1–12.

    Article  CAS  Google Scholar 

  • Millet, I., & Saaty, T. L. (2000). On the relativity of relative measures–accommodating both rank preservation and rank reversals in the AHP. European Journal of Operational Research, 121(1), 205–212. https://doi.org/10.1016/S0377-2217(99)00040-5

    Article  Google Scholar 

  • Minasny, B., Hong, S. Y., Hartemink, A. E., Kim, Y. H., & Kang, S. S. (2016). Soil pH increase under paddy in South Korea between 2000 and 2012. Agriculture, Ecosystems & Environment, 221, 205–213.

    Article  Google Scholar 

  • Mistri, P., & Sengupta, S. (2020). Multi-criteria decision-making approaches to agricultural land suitability classification of Malda District, Eastern India. Natural Resources Research, 29(3), 2237–2256.

    Article  CAS  Google Scholar 

  • Mitchell, R. A. C., Mitchell, V. J., Driscoll, S. P., Franklin, J., & Lawlor, D. W. (1993). Effects of increased CO2 concentration and temperature on growth and yield of winter wheat at two levels of nitrogen application. Plant, Cell & Environment, 16(5), 521–529.

    Article  CAS  Google Scholar 

  • Mukherjee, I., & Singh, U. K. (2020). Delineation of groundwater potential zones in a drought-prone semi-arid region of east India using GIS and analytical hierarchical process techniques. Catena, 194, 104681(1-18). https://doi.org/10.1016/j.catena.2020.104681

  • Navidi, M. N., Seyedmohammadi, J., & McDowell, R. W. (2022). A proposed new approach to identify limiting factors in assessing land suitability for sustainable land management. Communications in Soil Science and Plant Analysis, 53(19), 2558–2573. https://doi.org/10.1080/00103624.2022.2072511

    Article  CAS  Google Scholar 

  • Neina, D. (2019). The role of soil pH in plant nutrition and soil remediation. Applied and Environmental Soil Science, 2019, 1–9. https://doi.org/10.1155/2019/5794869

    Article  CAS  Google Scholar 

  • Noor, I. M. M., Prasetyowati, S. S., & Sibaroni, Y. (2022). Prediction map of rainfall classification using random forest and inverse distance weighted (IDW). Building of Informatics, Technology and Science (BITS), 4(2), 723–731.

    Article  Google Scholar 

  • Novoa, R., & Loomis, R. S. (1981). Nitrogen and plant production. Plant and Soil, 58, 177–204.

    Article  CAS  Google Scholar 

  • Nusret, D., & Dug, S. (2012). Applying the inverse distance weighting and kriging methods of the spatial interpolation on the mapping the annual precipitation in Bosnia and Herzegovina.

  • Olson, K. R., & Lang, J. M. (2000). Bulletin 811: Optimum crop productivity ratings for Illinois soils.

  • Olson, K. R., & Morton, L. W. (2012). The impacts of 2011 induced levee breaches on agricultural lands of Mississippi River Valley. Journal of Soil and Water Conservation, 67(1), 5A-10A.

    Article  Google Scholar 

  • Pai, D. S., Rajeevan, M., Sreejith, O. P., Mukhopadhyay, B., & Satbha, N. S. (2014). Development of a new high spatial resolution (02.5× 02.5) long period (1901–2010) daily gridded rainfall data set over India and its comparison with existing data sets over the region. Mausam, 65(1), 1–18.

    Article  Google Scholar 

  • Parajuli, K., Jones, S. B., Tarboton, D. G., Flerchinger, G. N., Hipps, L. E., Allen, L. N., & Seyfried, M. S. (2019). Estimating actual evapotranspiration from stony-soils in montane ecosystems. Agricultural and Forest Meteorology, 265, 183–194.

    Article  ADS  Google Scholar 

  • Paustian, K., Lehmann, J., Ogle, S., Reay, D., Robertson, G. P., & Smith, P. (2016). Climate-smart soils. Nature, 532(7597), 49–57.

    Article  PubMed  ADS  CAS  Google Scholar 

  • Peet, M. M., & Bartholemew, M. (1996). Effect of night temperature on pollen characteristics, growth, and fruit set in tomato. Journal of the American Society for Horticultural Science, 121(3), 514–519.

    Article  Google Scholar 

  • Piri, I., Moosavi, M., Taheri, A. Z., Alipur, H., Shojaei, S., & Mousavi, S. A. (2019). The spatial assessment of suitable areas for medicinal species of Astragalus (Astragalus hypsogeton Bunge) using the Analytic Hierarchy Process (AHP) and Geographic Information System (GIS). The Egyptian Journal of Remote Sensing and Space Science, 22(2), 193–201. https://doi.org/10.1016/j.ejrs.2018.02.003

    Article  Google Scholar 

  • Poggio, L., De Sousa, L. M., Batjes, N. H., Heuvelink, G., Kempen, B., Ribeiro, E., & Rossiter, D. (2021). SoilGrids 2.0: Producing soil information for the globe with quantified spatial uncertainty. Soil, 7(1), 217–240.

    Article  ADS  CAS  Google Scholar 

  • Pour, S. H., Abd Wahab, A. K., Shahid, S., & Ismail, Z. B. (2020). Changes in reference evapotranspiration and its driving factors in peninsular Malaysia. Atmospheric Research, 246, 105096.

    Article  Google Scholar 

  • Raza, A., Al-Ansari, N., Hu, Y., Acharki, S., Vishwakarma, D. K., Aghelpour, P., & Elbeltagi, A. (2022). Misconceptions of reference and potential evapotranspiration: A PRISMA-guided comprehensive review. Hydrology, 9(9), 153.

    Article  Google Scholar 

  • Rossel, R. V., & McBratney, A. B. (1998). Laboratory evaluation of a proximal sensing technique for simultaneous measurement of soil clay and water content. Geoderma, 85(1), 19–39.

    Article  ADS  Google Scholar 

  • Saaty, T. L. (1994). Fundamentals of decision making and priority theory with the analytic hierarchy process. RWS publications.

    Google Scholar 

  • Saaty, T. (1980). Fundamentals of decision making and priority theory with analytical hierarchical process. the AHP Series, Vol. VI, RWS Publications, The University of Pittsburgh, Pittsburgh.

  • Saaty, T. L., & Vargas, L. G. (2013). The logic of priorities: applications of business, energy, health and transportation. International Series in Management Science Operations Research (pp. 1–299). Springer Science & Business Media. 

  • Schoengold, K., & Zilberman, D. (2014). Water and development: The importance of irrigation in developing countries. January 2004.

  • Sen, P., Majumdar, K., & Sulewski, G. (2008). Importance of spatial nutrient variability mapping to facilitate SSNM in small land holding systems. Indian J. Fert, 4(11), 43–50.

    CAS  Google Scholar 

  • Seyedmohammadi, J., & Navidi, M. N. (2022). Applying fuzzy inference system and analytic network process based on GIS to determine land suitability potential for agricultural. Environmental Monitoring and Assessment, 194(10), 712. https://doi.org/10.1007/s10661-022-10327-x

    Article  PubMed  CAS  Google Scholar 

  • Seyedmohammadi, J., Sarmadian, F., Jafarzadeh, A. A., Ghorbani, M. A., & Shahbazi, F. (2018). Application of SAW, TOPSIS and fuzzy TOPSIS models in cultivation priority planning for maize, rapeseed and soybean crops. Geoderma, 310, 178–190. https://doi.org/10.1016/j.geoderma.2017.09.012

    Article  ADS  Google Scholar 

  • Seyedmohammadi, J., Sarmadian, F., Jafarzadeh, A. A., & McDowell, R. W. (2019a). Integration of ANP and fuzzy set techniques for land suitability assessment based on remote sensing and GIS for irrigated maize cultivation. Archives of Agronomy and Soil Science, 65(8), 1063–1079. https://doi.org/10.1080/03650340.2018.1549363

    Article  CAS  Google Scholar 

  • Seyedmohammadi, J., Sarmadian, F., Jafarzadeh, A. A., & McDowell, R. W. (2019b). Development of a model using matter element, AHP and GIS techniques to assess the suitability of land for agriculture. Geoderma, 352, 80–95. https://doi.org/10.1016/j.geoderma.2019.05.046

    Article  ADS  CAS  Google Scholar 

  • Seyedmohammadi, J., Zeinadini, A., Navidi, M. N., & McDowell, R. W. (2023). A new robust hybrid model based on support vector machine and firefly meta-heuristic algorithm to predict pistachio yields and select effective soil variables. Ecological Informatics, 74, 102002. https://doi.org/10.1016/j.ecoinf.2023.102002

    Article  Google Scholar 

  • Shah, F., Huang, J., Cui, K., Nie, L., Shah, T., Chen, C., & Wang, K. (2011). Impact of high-temperature stress on rice plant and its traits related to tolerance. The Journal of Agricultural Science, 149(5), 545–556.

    Article  CAS  Google Scholar 

  • Shojaei, S., Alipur, H., Ardakani, A. H. H., Nasab, S. N. H., & Khosravi, H. (2018). Locating Astragalus hypsogeton Bunge appropriate site using AHP and GIS. Spatial Information Research, 26, 223–231. https://doi.org/10.1007/s41324-018-0166-2

    Article  Google Scholar 

  • Shrestha, D. P., & Zinck, A. (2001). Land use of image knowledge classification in mountainous areas: Integration processing, digital elevation data and field (application to Nepal). JAG, 3(1), 249–261.

    Google Scholar 

  • Smith, C. W., Johnston, M. A., & Lorentz, S. (1997). Assessing the compaction susceptibility of South African forestry soils. II. Soil properties affecting compatibility and compressibility. Soil and Tillage Research, 43(3–4), 335–354.

    Article  Google Scholar 

  • Smith, P., Martino, D., Cai, Z., Gwary, D., Janzen, H., Kumar, P., & Smith, J. (2008). Greenhouse gas mitigation in agriculture. Philosophical Transactions of the Royal Society b: Biological Sciences, 363(1492), 789–813.

    Article  CAS  Google Scholar 

  • Sonneveld, B. G. J. S. (2003). Formalizing expert judgements in land degradation assessment: A case study for Ethiopia. Land Degradation & Development, 14(4), 347–361.

    Article  Google Scholar 

  • Spiertz, J. H. J., & De Vos, N. M. (1983). Agronomical and physiological aspects of the role of nitrogen in yield formation of cereals. Plant and Soil, 75, 379–391.

    Article  CAS  Google Scholar 

  • De Steiguer, J. E., Duberstein, J., & Lopes, V. (2003). The analytic hierarchy process as a means for integrated watershed management. In First interagency conference on research on the watersheds (pp. 736–740). Agricultural Research Service, US Department of Agriculture, Agricultural Research Service, Benson, Ariz.

  • Thornthwaite, C. W. (1948). An approach toward a rational classification of climate. Geographical Review, 38(1), 55–94.

    Article  ADS  Google Scholar 

  • Trangmar, B. B., Yost, R. S., & Uehara, G. (1986). Application of geostatistics to spatial studies of soil properties. Advances in Agronomy, 38, 45–94.

    Article  Google Scholar 

  • Tuan, N. T., Qiu, J. J., Verdoodt, A., Hu, L. I., & Van Ranst, E. (2011). Temperature and precipitation suitability evaluation for the winter wheat and summer maize cropping system in the Huang-Huai-Hai Plain of China. Agricultural Sciences in China, 10(2), 275–288.

    Article  Google Scholar 

  • Vanacker, V., Vanderschaeghe, M., Govers, G., Willems, E., Poesen, J., Deckers, J., & De Bievre, B. (2003). Linking hydrological, infinite slope stability and land-use change models through GIS for assessing the impact of deforestation on slope stability in high Andean watersheds. Geomorphology, 52(3–4), 299–315. https://doi.org/10.1016/S0169-555X(02)00263-5

    Article  ADS  Google Scholar 

  • Van Groenigen, J. W., Van Kessel, C., Hungate, B. A., Oenema, O., Powlson, D. S., & Van Groenigen, K. J. (2017). Sequestering soil organic carbon: a nitrogen dilemma. Environmental Science and Technology, 51, 4738–4739. https://doi.org/10.1021/acs.est.7b01427

    Article  PubMed  ADS  CAS  Google Scholar 

  • Vilasan, R. T., & Kapse, V. S. (2022). Evaluation of the prediction capability of AHP and F-AHP methods in flood susceptibility mapping of Ernakulam district (India). Natural Hazards, 1–27. https://doi.org/10.1007/s11069-022-05248-4

  • Walworth, J. L. (1998). Potatoes-field crop fertilizer recommendations for Alaska. Crop Production and Soil Management Series. FGV-00246A. Accessed Febuary 17, 2003. [Available online] http://www.uaf.Edu/coop-ext/

  • Warszawski, L., Frieler, K., Huber, V., Piontek, F., Serdeczny, O., Zhang, X., & Ge, Q. (2017). Center for International Earth Science Information Network—CIESIN—Columbia University. (2016). Gridded population of the World, Version 4 (GPWv4): Population density. Palisades. NY: NASA Socioeconomic Data and Applications Center (SEDAC). Atlas of Environmental Risks Facing China under Climate Change, p. 228. https://doi.org/10.7927/H4NP22DQ

  • Xu, H., Ye, M., & Li, J. (2008). The water transfer effects on agricultural development in the lower Tarim River, Xinjiang of China. Agricultural Water Management, 95(1), 59–68.

    Article  Google Scholar 

  • Zabihi, H., Ahmad, A., Vogeler, I., Said, M. N., Golmohammadi, M., Golein, B., & Nilashi, M. (2015). Land suitability procedure for sustainable citrus planning using the application of the analytical network process approach and GIS. Computers and Electronics in Agriculture, 117, 114–126.

    Article  Google Scholar 

  • Zebarth, B. J., Forge, T. A., Goyer, C., & Brin, L. D. (2015). Effect of soil acidification on nitrification in soil. Canadian Journal of Soil Science, 95(4), 359–363.

    Article  CAS  Google Scholar 

  • Zhang, H., & Wang, L. (2021). Analysis of the variation in potential evapotranspiration and surface wet conditions in the Hancang River Basin, China. Scientific Reports, 11(1), 1–10.

    Google Scholar 

  • Zhao, C., Jia, X., & Zhang, X. (2020). Using pedo-transfer functions to estimate dry soil layers along an 860-km long transect on China’s Loess Plateau. Geoderma, 369, 114320.

    Article  ADS  Google Scholar 

  • Živanović-Miljković, J., Crnčević, T., & Marić, I. (2012). Land use planning for sustainable development of peri-urban zones. Spatium, 28, 15–22.

    Article  Google Scholar 

  • Zomer, R. J., Bossio, D. A., Sommer, R., & Verchot, L. V. (2017). Global sequestration potential of increased organic carbon in cropland soils. Scientific Reports, 7(1), 1–8.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The authors express gratitude to several institutions and individuals for their valuable contributions to this research. These include the ICAR-National Bureau of Soil Survey and Land Use Planning in Kolkata, Gram Panchayat offices of Bankura District, Bankura Agriculture Office, and the Tribal Development Department of the Government of West Bengal for providing essential secondary information. They also appreciate the cooperation of local residents in various Gram Panchayats during primary data collection. Special thanks go to Dr. Amit Bera for his valuable suggestions and advice, as well as anonymous reviewers whose feedback significantly improved this work.

Author information

Authors and Affiliations

  1. Department of Earth Sciences and Remote Sensing, JIS University, Kolkata, 700109, West Bengal, India

    Arkadeep Dutta, Manua Banerjee & Ratnadeep Ray

Authors
  1. Arkadeep Dutta
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Manua Banerjee
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ratnadeep Ray
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization: Arkadeep Dutta, Ratnadeep Ray, Manua Banerjee; data curation: Arkadeep Dutta; formal analysis and investigation; Arkadeep Dutta, Ratnadeep Ray; writing—original draft preparation: Arkadeep Dutta; writing, review, and editing: Arkadeep Dutta, Ratnadeep Ray; supervision: Ratnadeep Ray, Manua Banerjee. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Arkadeep Dutta.

Ethics declarations

Ethics approval

The submitted work is original and has not been published elsewhere in any form or language (partially or in full). All sources used are properly disclosed with proper references. All authors have been personally and actively involved in substantial work leading to the paper, and will take public responsibility for its content. All authors have read, understood, and have complied as applicable with the statement on “Ethical responsibilities of Authors” as found in the Instructions for Authors.

Consent to participate

Not applicable.

Consent for publication

The participant has consented to the submission of the case report to the journal.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dutta, A., Banerjee, M. & Ray, R. Land capability assessment of Sali watershed for agricultural suitability using a multi-criteria-based decision-making approach. Environ Monit Assess 196, 237 (2024). https://doi.org/10.1007/s10661-024-12393-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10661-024-12393-9

Keywords

Search

Navigation