Farmers’ Distress Index: An Approach for an Action Plan to Reduce Vulnerability in the Drylands of India

Reddy, A Amarender A.; Bhattacharya, A.; Reddy, S. Venku; Ricart, Sandra

doi:10.3390/land10111236

Cited by 18 publications

(11 citation statements)

References 67 publications

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“…This shows that the vulnerabilities play a significant role in the sustainable development of agriculture and land management (A. A. Reddy et al, 2021). Therefore, the development schemes have to factor in local variation in terms of infrastructure and socio‐ecologies.…”

Section: Resultsmentioning

confidence: 99%

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Land degradation and its impact on agricultural productivity: The case of India

Gorain,

Kuriachen,

Kumar

et al. 2023

Land Degrad Dev

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Land degradation has emerged as one of the pivotal concerns for Indian agriculture in the 21st century. With rapid modernization and intensification of agricultural operations, land degradation has also increased simultaneously. This study estimates the losses accruing to agriculture from land degradation. On an average, land degradation results in losses in agriculture productivity amounting to INR 3654 per hectare annually (at 2011–12 prices). Further, a reduction in land degradation by 10% would reduce direct economic losses accruing from land degradation to INR 3145 per hectare to INR 3654 per hectare. Examination of state‐level cross section reveals that annual losses accruing from land degradation vary considerably across states. A vulnerability matrix is formulated using four parameters to place the states (sub‐national agricultural units) in the order of vulnerability to land degradation. Further, we estimate that an increase in land degradation by 1% could lead to loss of agricultural productivity by INR 104 per hectare on average (2004–05 prices). The findings of the study indicate that the adoption of land and water conservation measures stands to increase the gross value added to agriculture by reducing economic losses accruing from land.

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Section: Resultsmentioning

confidence: 99%

“…A. Reddy et al, 2021). Therefore, the development schemes have to factor in local variation in terms of infrastructure and socio-ecologies.…”

Section: Effect Of Land Degradation On Agricultural Productivitymentioning

confidence: 99%

Land degradation and its impact on agricultural productivity: The case of India

Gorain,

Kuriachen,

Kumar

et al. 2023

Land Degrad Dev

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“…Hence, inhabitants of these areas encounter severe water crises in terms of both drinking water and irrigation facilities. This affects not only agriculture returns but also sustainable agriculture, thus necessitating an immediate solution (Reddy et al, 2021; Samuel et al, 2021). Groundwater management and rainwater conservation via watershed 1 management programmes have been proven to be important for sustainability in dryland agriculture.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Analysis of Watershed Management and Sustainable Agriculture in Dryland Regions: A Case Study of Purulia District, West Bengal

Ghosh,

Gupta

2023

Review of Development and Change

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Watershed management deals with managing groundwater and drinking water in dryland areas. In this study, a dynamic optimisation model for sustainable agriculture and watershed management is developed, which can help farmers in dryland regions maximise their profit from agricultural production. The steady-state values of water stock, profit and allocation of land between highly water-intensive and less water-intensive crops are determined. This study also carries out sensitivity analysis by perturbing various parameters such as technologies used in crop production, discount rate and annual recharge of groundwater stock. The results show that as the technology used for less water-intensive crops improves, groundwater stock and profit increase. This study captures how upstream and downstream farmers can optimise their net benefit from agriculture when there is water conflict between them. It also demonstrates how their water extraction patterns and benefits can change in the presence and absence of a social planner.

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“… 18 , 24 , 25 ). have tended to incorporate human and ecosystem dimensions in their vulnerability assessment framework with respect to the impacts of coastal environmental variability and hazards on populated coastal regions The socio-economic factors involve social status (income, wealth, and education), cultural aspects, risk perception, political conditions, and institutions for assessing the efficiency of disaster responses, sustainable livelihood options, and post-disaster recovery plans 26 . The demographic characteristics (race, gender, ethnicity) and health care systems that can provide more information about community resilience facing natural disasters 19 .…”

Section: Introductionmentioning

confidence: 99%

Integrated socio-environmental vulnerability assessment of coastal hazards using data-driven and multi-criteria analysis approaches

Tanim

Goharian

Moradkhani

2022

Sci Rep

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Coastal hazard vulnerability assessment has been centered around the multi-variate analysis of geo-physical and hydroclimate data. The representation of coupled socio-environmental factors has often been ignored in vulnerability assessment. This study develops an integrated socio-environmental Coastal Vulnerability Index (CVI), which simultaneously combines information from five vulnerability groups: biophysical, hydroclimate, socio-economic, ecological, and shoreline. Using the Multi-Criteria Decision Making (MCDM) approach, two CVI (CVI-50 and CVI-90) have been developed based on average and extreme conditions of the factors. Each CVI is then compared to a data-driven CVI, which is formed based on Probabilistic Principal Component Analysis (PPCA). Both MCDM and PPCA have been tied into geospatial analysis to assess the natural hazard vulnerability of six coastal counties in South Carolina. Despite traditional MCDM-based vulnerability assessments, where the final index is estimated based on subjective weighting methods or equal weights, this study employs an entropy weighting technique to reduce the individuals’ biases in weight assignment. Considering the multivariate nature of the coastal vulnerability, the validation results show both CVI-90 and PPCA preserve the vulnerability results from biophysical and socio-economic factors reasonably, while the CVI-50 methods underestimate the biophysical vulnerability of coastal hazards. Sensitivity analysis of CVIs shows that Charleston County is more sensitive to socio-economic factors, whereas in Horry County the physical factors contribute to a higher degree of vulnerability. Findings from this study suggest that the PPCA technique facilitates the high-dimensional vulnerability assessment, while the MCDM approach accounts more for decision-makers' opinions.

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Farmers’ Distress Index: An Approach for an Action Plan to Reduce Vulnerability in the Drylands of India

Cited by 18 publications

References 67 publications

Land degradation and its impact on agricultural productivity: The case of India

Land degradation and its impact on agricultural productivity: The case of India

Dynamic Analysis of Watershed Management and Sustainable Agriculture in Dryland Regions: A Case Study of Purulia District, West Bengal

Integrated socio-environmental vulnerability assessment of coastal hazards using data-driven and multi-criteria analysis approaches

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