Effect of Rainfall Variability on Rice Yield in North Eastern Hills of India: A Case Study

Dkhar, Deotrephy K.; Feroze, S.M.; Singh, Ram Kumar; Ray, Lala I.P.

doi:10.1007/s40003-017-0276-4

Cited by 11 publications

(5 citation statements)

References 7 publications

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“…Both inter‐annual and long‐run climate variability affect food production in India (Guiteras, 2009; Pre & Revadekar, 2013). The relationship between weather and crop yields has been studied in India, among others, by Auff et al (2012); Barnwal and Kotani (2013); Birth et al (2014); Birthal et al (2014, 2015); Pat and Kumar (2014); Dkhar et al (2017); and Mishra et al (2017). Weather variables significantly drive the yield/production distribution and feature considerable nonlinearity.…”

Section: Context and Datamentioning

confidence: 99%

Weather shocks, traders' expectations, and food prices

Letta

Montalbano

Pierre

2021

American J Agri Economics

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The empirical literature on the impacts of weather shocks on agricultural prices typically explores post-harvest price dynamics rather than pre-harvest ones. Inspired by the intra-annual competitive storage theory, we empirically investigate the role of weather news in traders' anticipations on pre-harvest price fluctuations in India's local markets. Using a panel of district-level monthly wholesale food prices from 2004 to 2017, we leverage the time lag between a weather anomaly and the corresponding supply shock to isolate price reactions caused by changes in expectations. We find that drought conditions significantly increase food prices during the growing period, that is before any harvest failure has materialized. These results suggest that markets respond immediately to expected supply shortfalls by updating their beliefs and adapting accordingly and that the expectation channel accounts for a substantial share of supply-side food price shocks. A direct comparison with the effects of the same weather anomalies on the prices of the first harvest month reveals that expectations anticipate more than 80% of the total price impact.

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Section: Context and Datamentioning

confidence: 99%

Weather shocks, traders' expectations, and food prices

Letta

Montalbano

Pierre

2021

American J Agri Economics

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“…In the same vein, Lertamphainont and Sparrow (2016) noted that crop income fell sharply due to rainfall extremes from either flood or droughts in Thailand, while Levine and Yang (2014) showed that higher rainfall led to increased rice production using a panel of Indonesian districts. Rainfall, typically, had a positive impact on production yield (Dkhar, Feroze, Singh, & Ray, 2017;Isik & Devadoss, 2006). For instance, rainfall positively affected cassava yield in northeastern areas of Thailand which is a poor region (Phatcharopaswatanagul, 2018) consistent with Dell et al (2012) who found that precipitation positively affected agricultural output in poor countries.…”

Section: Literature Reviewmentioning

confidence: 94%

Impact of Rainfall on Agricultural Growth in Thailand: Evidence in Farming and Fishing Activities

2019

JESD

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Rainfall is related to economic growth. This is especially true for the agricultural sector which is a key food source. Rainfall has beneficial impacts in both arid and poor regions. Thailand, as an upper middle-income country according to the World Bank, has a tropical climate although rainfall varies between each region. Precipitation in the northern and northeastern regions is low while the southern region, as a narrow strip of land running northsouth bordering the Andaman Sea to the West and the Gulf of Thailand to the East, has the highest rainfall. Agricultural product characteristics differ between regions. In arid areas, agrarian products are largely from farming while fisheries predominate in the southern region. The effect of rainfall on GDP growth was explored on a region-by-region basis using panel data from 2004 to 2015 at provincial level. The FGLS (Feasible Generalized Least Square) estimator was used in the regression models. Results showed that in northeastern and northern regions, rainfall stimulated economic growth in all dimensions of the agricultural sector and agricultural subsectors. The economic impact of rainfall played a major role in the fishing subsectors compared to the farming subsector. Overall, results identified the regions and agricultural subsectors that were economically profitable as a result of increased rainfall.

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“…In addition, the Station-Year method used in section 3.3.2 above was also applied in this section. The statistical or empirical method used in this research was tested to be the best method in crop-climate analysis and was used by many authors in their respective studies (Adebayo, 2000;Adebayo & Adebayo, 1997;Dkhar, Feroze, Singh, & Ray, 2017;Govinda, 2013;Mahmood, Ahmad, Hassan, & Bakhsh, 2012;Tiamiyu, Eze, Yusuf, Maji, & Bakare, 2015).…”

Section: Methods Of Data Analysismentioning

confidence: 99%

Application of Analytical Hierarchical Process (AHP) in Development of Suitability Model for Rice Production in Taraba State

Ezra

Adeyinka

Saeed

2020

International Journal of Sustainable Agricultural Research

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This research was aim at applying Multi-Criteria Decision Making (MCDM) in Agro-Climatic Zoning of Taraba State for rice Production. Climatic variables, Rice Yield, Digital Elevation Model (DEM), Land Sat 8 (OLI) and Soil Texture map were the data used. Climatic data of the state were analyzed over time and Space using trend and spatial analysis tools in excel and Arc GIS respectively, while correlation and stepwise regression analysis between rice yield and the climatic variables were analyzed in SPSS. Mean temperature, August and September rainfalls were identified to be the critical Climatic factors affecting the growth and yield of rice in the State. The highly suitable cover places such as; Lisasam, Takum, Donga, Wukari, Mutum Biyu and Bali while the suitable area occupy places like Serti, Lau, Sunkani, Jalingo and Lankaviri. Suitability map produced with NDVI showed that the highly suitable area for Rice cultivation reduced from 31.93% to 28.76%. In regards to this findings, cultivation of rice should be encourage in Highly Suitable and Suitable zones of the State while cultivation of alternative crops other than rice in not suitable area is very important in reducing the risk of crop failure. In addition, application of Multi Criteria Decision Making (MCDM) a Remote Sensing and GIS tool and NDVI plays a significant role in Agro-climatic suitability zoning, as such, the tools are recommended in Agro-climatic research. Contribution/Originality: This study contributes to the Agricultural planning by determining the suitable area for cultivation of rice in Taraba State. Similarly, this paper contributes the first logical analysis that incorporates Agro-climatic statistical method and MCDM (AHP) method in designing a model for Agro-climatic suitability analysis.

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Effect of Rainfall Variability on Rice Yield in North Eastern Hills of India: A Case Study

Cited by 11 publications

References 7 publications

Weather shocks, traders' expectations, and food prices

Weather shocks, traders' expectations, and food prices

Impact of Rainfall on Agricultural Growth in Thailand: Evidence in Farming and Fishing Activities

Application of Analytical Hierarchical Process (AHP) in Development of Suitability Model for Rice Production in Taraba State

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