Assessment of soil quality and productivity in different phases of soil erosion with the focus on land degradation neutrality in tropical humid region of India

Mandal, Debashis; Chandrakala, M.; Alam, N. M.; Roy, Trisha; Mandal, Uday

doi:10.1016/j.catena.2021.105440

Cited by 36 publications

(21 citation statements)

References 31 publications

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“…The land use for the 50 m buffer zone of Mahi ravine shows that the maximum area is under Prosophis, followed by agriculture, gullied land, land with scrub and land without scrub, forest, and fallow land. It was found that the soil organic carbon available in the soil of Mahi ravines was impacted by the land use vegetation, also reported by Mandal et al (2021). The intensive cultivation practices, sparse vegetation cover, and the absence of soil and water conservation measures with proper drainage outlets in the marginal agricultural lands of the 50 m buffer zone of Mahi ravine are increasing the vulnerability of ravine ingress into these lands (Singh et al, 2020).…”

Section: Cover Factor and Its Role In Ravine Vulnerability Indexmentioning

confidence: 77%

Novel hybrid ravine vulnerability index‐based identification of potential reclamation zones for Western India

Singh,

Dinesh,

Moharana

et al. 2023

Land Degrad Dev

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The ravine is often regarded as the worst instance of how water erosion is causing land deterioration. The farmers' livelihoods are often threatened by the ravine's expansion into the surrounding 50 m buffer zone, leaving them with no choice except to work as landless workers. Due to the high expense of ravine restoration, it is not economically possible to begin the process of reclamation in all of the ravine lands at once. As a result, it is necessary to recognize the prospective regions to bring in reclamation activities. In this work, the ravine vulnerability index for the Mahi ravine in Western India was developed using a cutting‐edge hybrid methodology. For the development of the ravine vulnerability index, it was determined that the sand, silt, clay, organic carbon, soil erodibility factor, slope, stream power index, topographic wetness index, sediment transport index, and cover factor were crucial components. Weights were applied to various parameters based on the perceived significance of each parameter in relation to another in the decision matrix of the analytical hierarchical process. The number of iterations made to reach a consistency ratio of under 10% to determine the final priority weights for each parameter. The sediment transport index had the lowest priority weight (1.4), whereas the sand had the highest priority weight (28.5). For reclamation purposes, the prospective active zones inside the designated ravine's 50‐m buffer zone, which covered an area of 63,031 acres, were determined. According to the ground truth‐validated ravine vulnerability index, possible reclamation zones were found in the 16,703 ha (26.50%) region of Mahi ravine, which was given extremely high priority. As per the Mahi ravine's land capacity classification, 20,275 ha (32.16%) of it is arable land, and 18,687 ha (29.65%) of it is non‐arable land that is ideal for soil and water conservation treatments.

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Section: Cover Factor and Its Role In Ravine Vulnerability Indexmentioning

confidence: 77%

Novel hybrid ravine vulnerability index‐based identification of potential reclamation zones for Western India

Singh,

Dinesh,

Moharana

et al. 2023

Land Degrad Dev

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“…With the development of human society and the economy, limited resources cannot meet the needs of the growing population [4]. Under the influence of multiple factors (e.g., nature and social economy), productivity had declined, land degradation, soil erosion, and other problems have continuously emerged, and mankind is facing very severe challenges [5,6]. Soil nutrients, such as organic matter (OM), phosphorus (P), and potassium (K), play an important role in the process of crop growth [7,8].…”

Section: A Background and Motivationmentioning

confidence: 99%

Application of Hyperspectral Technology Combined With Bat Algorithm-AdaBoost Model in Field Soil Nutrient Prediction

et al. 2022

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This paper proposes a hyperspectral soil nutrient estimation method based on the bat algorithm (BA)-AdaBoost model. The spectral reflectance, the first derivative of the reflectance, and the reciprocal logarithm of the reflectance are analyzed based on the 800 field soil samples and their hyperspectral data collected. The first derivative of the reciprocal logarithm of the reflectance and the sensitive band was extracted using the correlation coefficient method, and the correlation of the content of soil organic matter, phosphorus, and potassium was solved. The BA is used to optimize the two core parameters of the AdaBoost model (i.e., the maximum number of iterations (n) and the weight reduction coefficient (v) of the weak learner), the classification and regression trees(CART) decision tree is selected as the weak regression learner of the model, and the coefficient of determination is used as parameter optimization. Based on the objective function value, a BA-AdaBoost model was constructed to estimate soil organic matter and phosphorus and potassium contents. The results show that the BA-AdaBoost combined model can better search for globally optimal parameters. The AdaBoost model optimized by BA significantly improved accuracy and reliability. Among the three elements, soil organic matter estimation accuracy is the highest, and the coefficient of determination and the root mean square error are 0.867 and 0.151g • kg -1 , respectively. Compared with the model before optimization, the model accuracy and reliability improved by 29.0% and 24.1%, respectively. The results indicate that hyperspectral technology combined with the BA-AdaBoost model has certain application prospects in field soil nutrient estimation.

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“…A similar study was conducted on land suitability evaluation in the Elamdesam block, Idukki district, Kerala, with a focus on specific crops. Utilizing soil site suitability criteria, the study revealed that paddy, coconut, arecanut, black pepper, banana, pineapple, tapioca and teak were major crops in the region 11 . The results showed varying degrees of suitability for each crop, providing valuable insights for agricultural planning in the tropical humid region of Kerala.…”

Section: Introductionmentioning

confidence: 98%

Land suitability analysis for turmeric crop for humid tropical Kerala, India, under current and future climate scenarios using advanced geospatial techniques

Banu,

Krishnamurthy,

Srinivasan

et al. 2024

J Sci Food Agric

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BACKGROUNDTurmeric cultivation primarily thrives in India, followed by Bangladesh, Cambodia, Thailand, China, Malaysia, Indonesia and the Philippines. India leads globally in both area and production of turmeric. Despite this, there is a recognized gap in research regarding the impact of climate change on site suitability of turmeric. The primary objective of the present study was to evaluate both the present and future suitability of turmeric cultivation within the humid tropical region of Kerala, India, by employing advanced geospatial techniques. The research utilized meteorological data from the Indian Meteorological Department for the period of 1986–2020 as historical data and projected future data from the Coupled Model Intercomparison Project Phase 6 (CMIP6). Four climatic scenarios of shared socioeconomic pathway (SSP) from the Intergovernmental Panel on Climate Change AR6 model of MIROC6 for the year 2050 (SSP 1–2.6, SSP 2–4.5, SSP 3–7.0 and SSP 5–8.5) were used.RESULTSThe results showed that suitable area for turmeric cultivation is declining in future scenario and this decline can be primarily attributed to fluctuations in temperature and an anticipated increase in rainfall in the year 2050. Notable changes in the spatial distribution of suitable areas over time were observed through the application of geographic information system (GIS) techniques. Importantly, as per the suitability criteria provided by ICAR‐National Bureau of Soil Survey and Land Use Planning (ICAR‐NBSS & LUP), all the districts in Kerala exhibited moderately suitable conditions for turmeric cultivation. With the GIS tools, the study identified highly suitable, moderately suitable, marginally suitable and not suitable areas of turmeric cultivation in Kerala. Presently 28% of area falls under highly suitable, 41% of area falls under moderately suitable and 11% falls under not suitable for turmeric cultivation. However, considering the projected scenarios for 2050 under the SSP framework, there will be a significant decrease in highly suitable area by 19% under SSP 5–8.5. This reduction in area will have an impact on the productivity of the crop as a result of changes in temperature and rainfall patterns.CONCLUSIONThe outcome of the present research suggests that the state of Kerala needs to implement suitable climate change adaptation and management strategies for sustaining the turmeric cultivation. Additionally, the present study includes a discussion on potential management strategies to address the challenges posed by changing climatic conditions for optimizing turmeric production in the region. © 2024 Society of Chemical Industry.

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Assessment of soil quality and productivity in different phases of soil erosion with the focus on land degradation neutrality in tropical humid region of India

Cited by 36 publications

References 31 publications

Novel hybrid ravine vulnerability index‐based identification of potential reclamation zones for Western India

Novel hybrid ravine vulnerability index‐based identification of potential reclamation zones for Western India

Application of Hyperspectral Technology Combined With Bat Algorithm-AdaBoost Model in Field Soil Nutrient Prediction

Land suitability analysis for turmeric crop for humid tropical Kerala, India, under current and future climate scenarios using advanced geospatial techniques

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