Geospatial assessment of soil and land properties for mango suitability in Mustariwadi micro-watershed using geo-spatial techniques (AHP & Wao)

Introduction

Soil and land resources are declining both in quantitative and qualitative terms at a rapid rate worldwide primarily due to anthropogenic activities and secondly because of depletion of natural reasons. The pressure of producing more and more food on these limited resources to satisfy the demands of increasing world population has further aggravated the situation at alarming speed. Impact of climate change has also imposed unpredictable conditions in soil and land for cultivation of crop. Interventions like suitable soil and water conservation methods, nutrient management practices and adoption of crops based on soil and land properties can bring major positive change in productive potential of land. Each parcel of land has got its own potentials and limitations with respect to their physical, chemical and biological properties to support crop growth. Therefore to strengthen the decision support system of sustainable enhancement of productivity, site specific crop suitability is an important pre-requisite. Intensive data on inherent properties of site specific of soil, land and crop,which influence on each other's potential and capabilities (Greenland et al., 1998; Richardson et al., 2023) in playing vital role in evaluating land suitability for different crops there by becomes critical inputs in making strategies for increasing productivity (Pramanik 2016) and making agriculture sustainable (El Baroudy 2016; Falascaet al., 2012) [10,16,15,6,7,13] .

Mustariwadi micro watershed, covering an area of 555.5 ha, was identified as study area where, mango is one among the commonly cultivated fruit crop. With an objective to bring out site specific crop suitability plan for mango, a detailed Land Resource Inventory (LRI) was carried out to characterise surface and subsurface properties of soil and land. The outcomes of LRI were processed through AHP to develop site specific mango suitability map using GIS.

Highlights

 To characterize soil and land properties  To identify potential and limiting factors of soil and land for mango cultivation  To find out extent and distribution of mango suitable area

Materials and methods 2.1 Study Area:

Mustariwadi micro-watershed is located between 18°9'10" to 18°10' 0" N latitude and 77°17'30" to 77°20'0" E longitude in Humnabad taluk of Bidar district, covering an area about 555.5 ha. (Figure 1). The microwatersheds coming under north-eastern transition zone with average annual rainfall of 847 mm. Soils of Micro-watershed are lateritic with undulating physiographic.

Criteria selection

Criteria considered for assessment of mango suitability in the study area was done by referring to manual on soil site suitability criteria for major crops (Naidu et al., 2006, FAO 2015). The site specific physical and chemical properties like soil texture, depth, slope, pH, EC, and OC were recorded and used for assessing the land suitable for mango cultivation. The raster datasets developed using LRI and Lab studies along with the spatial data were processed on GIS Platform for selection of criteria as per the objectives of the study. (Table 1). Land suitability analysis for mango

Standardization of criteria layers

All the criteria considered for cropland suitability analysis were standardized based on the soil classification and characterization guide for agricultural suitability by FAO and other guidelines defining natural and artificial constraints for agriculture suitability (Naidu et al., 2006).The crop requirements were matched with the soil and land characteristics to arrive at the crop suitability. The land suitability classification for different crops, viz., two orders were recognized, order S-Suitable and order N-Not suitable. Further, the orders have classes, subclasses and units. Order-S has three classes, Class S1-Highly Suitable, Class S2-Moderately Suitable and Class S3-Marginally Suitable, N-Not suitable. There are no sub-classes within the class S1 as they will have very minor or no limitations for crop growth. Geostatistical interpolation technique kriging was applied to obtain the spatial layers of soil chemical properties. All these layers were classified and thematic maps were prepared as per the standards given by National Bureau of Soil Survey and Land Use Planning. These criteria maps are as shown in figure 3 and4.

Analytical Hierarchy Process (AHP)

The relative importance values were determined following Storie index (O'geen, 2008), where a Saaty`s scale score of 1 to 9 of the respective importance were obtained. A pair wise ) [17] . Consistency Index (CI) as deviation or degree of consistency was derived using the following below equation,

Where λmax is the largest Eigen value of the pair-wise comparison matrix and n is the number of classes (Alonso et al., 2006) Consistency Ratio (CR) is a measure of consistency of pair wise comparison matrix and is given by equation,CR=CI/RI Where, RIis the ratio Index. The value of RI for different n values is given in. When CR value is less than 0.10, the matrix indicates a reasonable consistency. The calculated results of weight would be accepted when the consistency ratio was satisfactory (Saaty 1980; 2003).

Weighted Overlay Analysis

Thematic layers of different surface and sub-surface characters with their respective ratings were analysed through AHP (Agarwalet al., 2013) [1] method to get their weightages.The analytical hierarchy process is a multi-attribute land evaluation technique which allows to determine the weights of these multiple and heterogeneous criteria indicating relative importance. Different thematic layers identified in the study with their respective weightages were further integrated with each other in ArcGIS 10.6.1 software as per weighted overlay technique using the spatial analyst tool (Table 3).

Results and Discussion

Physical and chemical properties of soil of an area are the important attributes which enable to asses the land suitable for different crops. To find out the site specific suitability for mango, soil and land properties criteria like soil depth, texture, slope, organic carbon, electrical conductivity (EC) and pH was processed through AHP and Weighted Overlay Analysis (Table 2 to 6). The results indicate that soil organic carbon with a weightage value above 25% is the most important factor in making land suitable for mango out of the six criteria (Bandyopadhyay et al., 2009) [4] . On the status of the remaining criteria of Soil depth and slope with weightage value of 21% each were found to be second most important factors in deciding mango crop suitability in the study area. Whereas remaining properties like pH, Texture & EC with their weightage value of 16%,,11%, 6% respectively were found to be least influential on crop suitability as compare to soil organic carbon and depth, slope have proved their hierarchy in deciding mango suitability of the study area. As soil and land properties co-exist & highly interdependent in creating favorable or unfavorable conditions for crop growth, Status of soil and land characters have clearly proved their ability to become suitable or not suitable for mango crop (Sulankeet al., 2023) [19] . Thus, based on the outcomes of the weighted overlay evaluation, the study area of 555.5 ha falling under four different mango suitability categories were identified as mentioned in table 7. The reasons for land parcels belonging to Highly suitable (S1) category which has spread across 61 ha(10.93%) are found strongly associated with deep to very deep soil depth where it allowes the mango crop to have deeper and wider tap root system which enables to extract nutrient and moisture from deeper horizons. As these soils are belonging to very gently sloping lands, they become less prone to soil, nutrient and moisture loss. Therefore higher status of organic carbon is matching to the others conditions like neutral pH, Sandy clay loam texture. properties such as; clay soil texture influences the soil potential with its role in the retention of more SOC, faster decomposition and transformation process (Gami et al., 2009) [9] . In addition to that clay isknown imparts good water holding capacity, reduced leaching loss, high nutrient retention, adsorption and exchange abilities due to its high surface area reflecting as higher fertility (Borchers et al., 1992; Kome et al., 2019). Moreover, land parcels on which very deep (>150 cm) soil have been identified, are existing in lowland and midland physiographic position which will have a positive influence on soil development through deposition as well as through in-situ process (Karaca et al., 2018). Deeper rooting depth makes these soils harbor and nurture many annual and perennial crops with tap root system (Yüksek et al., 2009) [4,19,9,5,12,11,20,22] . On the contrary lands identified as not suitable (N) category which are extended upto 133 ha (24.02%)can be confirmed by existence of severe limitation like very shallow to shallow depth and existence of lithic contact layer which blocks the root penetration. As most of the soils belongs to 3-5% slope and making them susceptible for erosion, runoff losses, resulting in low organic carbon, moderately alkaline pH, and dominance of weathered parent material which leads to increase in severity of limiting factors of mango crop [21] .

Conclusions: By applying weighted overlay analysis, LRI data can be used to crop specific and site specific suitability assessment. Such information can be an important input for developing decision support system model for judging crop suitability in a micro-watershed. Findings ofsuch studies can be extrapolated and used in crop specific land-use planning for large area with similar land and soil characters.

Authors contribution

References

1. Agarwal E, Agarwal R, Garg RD, Garg PK. Delineation of groundwater potential zone: An AHP/ANP approach. J Earth Syst Sci. 2013;122(3):887-898. DOI:10.1007/s12040013-0309-8.
2. Alexandratos N, Bruinsma J. World agriculture towards 2030/2050: The 2012 revision. Rome: Food and Agriculture Organization of the United Nations; 2012.
3. Alonso JA, Lamata MT. Consistency in the analytic hierarchy process: A new approach. Int J Uncertain Fuzziness Knowl Based Syst. 2006;14(4):445-459. DOI:10.1142/S0218488506004114.
4. Bandyopadhyay S, Jaiswal RK, Hegde VS, Jayaraman V. Assessment of land suitability potentials for agriculture using a remote sensing and GIS based approach. Int J Remote Sens. 2009;30(4):879-895. DOI:10.1080/01431160802395235.
5. Borchers JG, Perry DA. The influence of soil texture and aggregation on carbon and nitrogen dynamics in southwest Oregon forests and clearcuts. Can J For Res. 1992;22(3):298-305. DOI:10.1139/x92-039.
6. El Baroudy AA. Mapping and evaluating land suitability using a GIS-based model. Catena. 2016;140:96-104.
7. Falasca SL, Ulberich AC, Ulberich E. Developing an agroclimatic zoning model to determine potential production areas for castor bean (Ricinus communis L.). Ind Crops Prod. 2012;40:185-191.
8. Gami SK, Lauren JG, Duxbury JM. Influence of soil texture and cultivation on carbon and nitrogen levels in soils of the eastern Indo-Gangetic Plains. Geoderma. 2009;153(34):304-311. DOI:10.1016/j.geoderma.2009.08.003.
9. Greenland DJ, Gregory PJ, Nye PH, editors. Introduction and conclusions for a discussion entitled Land resources: On the edge of the Malthusian precipice? Philos Trans R Soc Lond B Biol Sci. 1997;352(1356):861-867.
10. Karaca S, Gülser F, Selçuk R. Relationships between soil properties, topography and land use in the Van Lake Basin, Turkey. Eurasian J Soil Sci. 2018;7(2):115-120.
11. Kome GK, Enang RK, Tabi FO, Yerima BPK. Influence of clay minerals on some soil fertility attributes: A review. Open J Soil Sci. 2019;9(9):155-188.
12. Naidu LGK, Ramamurthy V, Challa O, Hegde R, Krishnan P. Manual soil-site suitability criteria for major crops. NBSS Publication No. 129. Nagpur: National Bureau of Soil Survey and Land Use Planning; 2006. p. 1-3.
13. O'Geen AT. A revised Storie Index for use with digital soils information. Oakland (CA): University of California Agriculture and Natural Resources; 2008.
14. Pramanik MK. Site suitability analysis for agricultural land use of Darjeeling district using AHP and GIS techniques. Model Earth Syst Environ. 2016;2:1-22.
15. Richardson GS, Ruark MD, Radatz T, Radatz A, Cooley E, Silva EM, et al. The influence of inherent soil factors and agricultural management on soil organic matter. Ecosphere. 2023;14(3):e4459.
16. Saaty TL. Fundamentals of the analytic network process multiple networks with benefits, costs, opportunities and risks. J Syst Sci Syst Eng. 2004;13(3):348-379.
17. Saaty TL. Decision making with the analytic hierarchy process. Int J Serv Sci. 2008;1(1):83-98.
18. Salunkhe S, Nandgude S, Tiwari M, Bhange H, Chavan SB. Land suitability planning for sustainable mango production in vulnerable region using geospatial multi-criteria decision model. Sustainability. 2023;15:2619. DOI:10.3390/su15032619.
19. Yüksek T, Göl C, Yüksek F, Erdoğan Yüksel E. The effects of land-use changes on soil properties: The conversion of alder coppice to tea plantations in the humid Northern Black Sea region. Afr J Agric Res. 2009;4(7):665-674.
20. Liu K, Bandara M, Hamel C, Knight JD, Gan Y. Intensifying crop rotations with pulse crops enhances system productivity and soil organic carbon in semi-arid environments. Field Crops Res. 2020;248:107657.
21. Ayehu GT, Besufekad SA. Land suitability analysis for rice production: A GIS-based multi-criteria decision approach. Am J Geogr Inf Syst. 2015;4(3):95-104.