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20202
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Subject: Soil Science and Agriculture Chemistry × Author: Neha, Unni × End date: 2020 × Start date: 2020 × Type: Thesis ×
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    ThesisItemOpen Access
    Assessment of soil quality in the post floods scenario of AEU 5 and AEU 9 of Ernakulam district of Kerala and Mapping using GIS Techniques
    (Department of Soil Science and Agricultural Chemistry, College of Horticulture, Vellanikkara, 2020) Neha, Unni; KAU; Sreelatha, A K
    Kerala state witnessed large scale devastating flood in 2018 due to excess rainfall, causing significant damage to agricultural sector and human life. One of the most affected districts was Ernakulam, especially AEU 5 and AEU 9. The AEU 5 - Pokkali lands, represent the lowlands, often below sea level, in coastal areas of Ernakulam district and extending to parts of Thrissur and Alappuzha districts. The soils are hydromorphic, often underlain by potential acid-sulphate sediments with unique hydrological conditions. Seawater inundation is not controlled and hence soils are acid-saline. The AEU 9 - south central laterites represent midland laterite terrain with typical laterite soils. The study aimed at the assessment of soil quality in the post flood scenario of AEU 5 and AEU 9 in Ernakulam district and to develop maps on soil characters and quality using GIS techniques and to workout soil quality index (SQI). For this purpose 100 geo-referenced soil samples were collected from different panchayats of AEU 5 and AEU 9 in Ernakulam district and were characterized for physical, chemical and biological properties. The Pokkali soils recorded low bulk density whereas porosity, water holding capacity and soil moisture were found high. Available N content was medium to high, available phosphorus and potassium was high in the soil. Among the secondary nutrients, available Ca and S were found sufficient for majority of the samples, while a deficiency of available Mg was noticed in Pokkali soils. In AEU 9, the soil pH varied from 5.01 to 7.69 and all the soils had an electrical conductivity less than 1.0 dS m-1. Organic carbon was noticed low to medium in the soils. Available N content was medium for 87 per cent of the samples, whereas all the samples were high in available P content. Available K was recorded low to medium values in AEU 9. Soil quality index was calculated using principal component analysis (PCA). There are three main steps involved in the soil quality index method which includes (i) selection of a minimum data set (MDS) of indicators (ii) formation of the MDS indicators and scoring of each indicators (iii) computation of index of soil quality. For developing minimum data set, principal component analysis (PCA) was performed for 23 soil attributes and resulted in 7 PCs. The indicators with high loading factors in each PCs were selected to develop minimum data set (MDS). MDS constituted 8 attributes for AEU 5 and 9 attributes for AEU 9 respectively. After the development of MDS, the soil indicators were converted to unit-less scores ranging from 0 to 1 using non-linear scoring function methods. Three types of scoring curves were used: i) more is better, ii) less is better, iii) optimum curve. Soil quality index ranged from 0.42 in Nayarambalam to 0.76 in Vadakkekkara in AEU 5, and 0.39 in Edathala to 0.92 in Aluva in AEU 9. The highest RSQI value was recorded in Aluva (69.7%) and the lowest in Edathala (29.55%) under AEU 9. In AEU 5 the highest RSQI was obtained in Vadakkekkara (71.58%) and the lowest in Nayarambalam (37.06%). Nutrient indices of flood affected areas in AEU 9 were low with respect to organic carbon and available potassium, medium with respect to available nitrogen and high with respect to available phosphorus. Nutrient index was high for nitrogen, phosphorus, potassium and organic carbon in AEU 5. Significant positive correlations were observed between organic carbon and available nitrogen, organic carbon and soil moisture content. Negative correlation existed between bulk density and porosity, organic carbon and bulk density in both AEUs. The present study revealed that soil fertility and productivity have been disturbed after the floods. In AEU 9 available potassium was found decreased after the flood. Prior to flood Kottuvally, Elamkunnapuzha, Edavanakkad and Kuzhuppilly panchayats in AEU 5 were medium in relative soil quality index (Joseph, 2014) and post flood assessment showed that these panchayats shifted to poor relative soil quality index.
  • Thumbnail Image
    ThesisItemOpen Access
    Assessment of soil quality in the post floods scenario of AEU 5 and AEU 9 of Ernakulam district of Kerala and Mapping using GIS Techniques
    (Department of Soil Science and Agricultural Chemistry, College of Horticulture, Vellanikkara, 2020) Neha, Unni; KAU; Sreelatha, A K
    Kerala state witnessed large scale devastating flood in 2018 due to excess rainfall, causing significant damage to agricultural sector and human life. One of the most affected districts was Ernakulam, especially AEU 5 and AEU 9. The AEU 5 - Pokkali lands, represent the lowlands, often below sea level, in coastal areas of Ernakulam district and extending to parts of Thrissur and Alappuzha districts. The soils are hydromorphic, often underlain by potential acid-sulphate sediments with unique hydrological conditions. Seawater inundation is not controlled and hence soils are acid-saline. The AEU 9 - south central laterites represent midland laterite terrain with typical laterite soils. The study aimed at the assessment of soil quality in the post flood scenario of AEU 5 and AEU 9 in Ernakulam district and to develop maps on soil characters and quality using GIS techniques and to workout soil quality index (SQI). For this purpose 100 geo-referenced soil samples were collected from different panchayats of AEU 5 and AEU 9 in Ernakulam district and were characterized for physical, chemical and biological properties. The Pokkali soils recorded low bulk density whereas porosity, water holding capacity and soil moisture were found high. Available N content was medium to high, available phosphorus and potassium was high in the soil. Among the secondary nutrients, available Ca and S were found sufficient for majority of the samples, while a deficiency of available Mg was noticed in Pokkali soils. In AEU 9, the soil pH varied from 5.01 to 7.69 and all the soils had an electrical conductivity less than 1.0 dS m-1. Organic carbon was noticed low to medium in the soils. Available N content was medium for 87 per cent of the samples, whereas all the samples were high in available P content. Available K was recorded low to medium values in AEU 9. Soil quality index was calculated using principal component analysis (PCA). There are three main steps involved in the soil quality index method which includes (i) selection of a minimum data set (MDS) of indicators (ii) formation of the MDS indicators and scoring of each indicators (iii) computation of index of soil quality. For developing minimum data set, principal component analysis (PCA) was performed for 23 soil attributes and resulted in 7 PCs. The indicators with high loading factors in each PCs were selected to develop minimum data set (MDS). MDS constituted 8 attributes for AEU 5 and 9 attributes for AEU 9 respectively. After the development of MDS, the soil indicators were converted to unit-less scores ranging from 0 to 1 using non-linear scoring function methods. Three types of scoring curves were used: i) more is better, ii) less is better, iii) optimum curve. Soil quality index ranged from 0.42 in Nayarambalam to 0.76 in Vadakkekkara in AEU 5, and 0.39 in Edathala to 0.92 in Aluva in AEU 9. The highest RSQI value was recorded in Aluva (69.7%) and the lowest in Edathala (29.55%) under AEU 9. In AEU 5 the highest RSQI was obtained in Vadakkekkara (71.58%) and the lowest in Nayarambalam (37.06%). Nutrient indices of flood affected areas in AEU 9 were low with respect to organic carbon and available potassium, medium with respect to available nitrogen and high with respect to available phosphorus. Nutrient index was high for nitrogen, phosphorus, potassium and organic carbon in AEU 5. Significant positive correlations were observed between organic carbon and available nitrogen, organic carbon and soil moisture content. Negative correlation existed between bulk density and porosity, organic carbon and bulk density in both AEUs. The present study revealed that soil fertility and productivity have been disturbed after the floods. In AEU 9 available potassium was found decreased after the flood. Prior to flood Kottuvally, Elamkunnapuzha, Edavanakkad and Kuzhuppilly panchayats in AEU 5 were medium in relative soil quality index (Joseph, 2014) and post flood assessment showed that these panchayats shifted to poor relative soil quality index.