Rain Fed Rice Agriculture under Climate Variability in Southeast Asia: The Case of Thailand

Reda, Abbadi Girmay; Tripathi, Nitin Kumar

doi:10.4172/2157-7617.1000297

Cited by 6 publications

(3 citation statements)

References 10 publications

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“…In the area where fresh water is available, farmers use the traditional irrigated method to flood the rice field (Chan et al, 2012). Moreover, for places with less water, farmers can implement the rain-fed rice approach or use aerobic rice culture on their farms (Akinbile et al, 2011;Girmay Reda & Tripathi, 2016). However, with the uncertainty of climate change, water availability might be interrupted, which can cause drought, and some places may receive higher rainfall amounts than expected, leading to flooding.…”

Section: Water Regimementioning

confidence: 99%

Predictive Modelling for Rice Weeds in Climate Change: A Review

Abd Manaf,

Juraimi,

Che'Ya

et al. 2022

Adv Agric Food Res J

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Rice (Oryza sativa L.) is an important staple food not only for Asians but also for people worldwide. However, weeds in rice fields can cause yield reduction due to their tendency to compete for resources. These significant biological obstacles can potentially cause complete yield loss if inappropriately managed. In addition, future climate change can cause rice weeds to become more competitive against cultivated rice plants by providing new favourable conditions for the unwanted species to expand aggressively. As the effect of climate change on rice weeds has been studied, the abiotic parameters, including carbon dioxide concentration, atmospheric temperature, drought, and soil salinity, can be used to construct predictive modelling to forecast rice weed infestation. If the weed invasion in rice fields can be predicted accurately based on the weather information, the farmers can prepare the countermeasure early to avoid high yield loss. However, some challenges need to be faced by the researchers as the weed invasion depends not only on the climate condition alone. This review summarizes the effect of climatic variation on weed infestation in rice fields. It also discusses how predictive modelling can be developed based on the information of the environmental conditions and their challenges.

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Section: Water Regimementioning

confidence: 99%

Predictive Modelling for Rice Weeds in Climate Change: A Review

Abd Manaf,

Juraimi,

Che'Ya

et al. 2022

Adv Agric Food Res J

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“…The differences in the irrigated lowland rice and rainfed lowland rice production at national, provincial and local levels are due to farming area differentiation related to regional characteristics. Rainfed lowland rice farming can only produce rice during the rainy season (Reda et al, 2015). The arrival of the rainy season has a large effect on the activities of rainfed lowland rice farmers.…”

Section: Introductionmentioning

confidence: 99%

Determinants of Production and Income Risks of Rainfed Lowland Farming: A Case Study in Maros Regency, Indonesia

Arifin¹,

Bíba²,

Syafiuddin

2021

Caraka Tani J. Sustain. Agric.

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Rainfed lowland farming production is generally lower than irrigated lowland rice due to area differentiation regional features. Rainfed lowland rice farming can only produce rice during the rainy season because lowland rice cannot be planted in the dry season. The purposes of this study are (1) to analyze the risk of production and income of rice farming in rainfed lowland farming and (2) to investigate the factors influencing the risk of rice farming in rainfed lowland farming. Data were collected from 100 respondents of rice farmers in four sub-districts in Maros Regency using the multi-stage cluster random sampling technique. The analysis of production and income risks were performed using multiple linear regression with the heteroscedastic method. The results have shown that rice farming in rainfed lowland farming poses a risk to production and income. The variables that significantly influence the rainfed lowland rice farming are land area, the number of seeds, the amount of urea fertilizer and the amount of pesticide. Farmers are required to manage risk by prioritizing the effectiveness and efficiency production factors as needed. Similarly the government is expected to assist farmers in maintaining the level of rice selling prices.

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“…The basin borders Myanmar at the north, Salawin basin at the west, Wang, and Kok basins at the southeast and the northeast, respectively. The topography of the basin includes hilly and mountains, valleys, and lowland plains (Reda et al, 2015).…”

Section: Figure 31 Location and Elevation Of Upper Ping River Basinmentioning

confidence: 99%

Low-flow assessment for ungauged sub-basin in upper ping river basin, Thailand

Man

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Water scarcity has become one of the most remarkable problems in Thailand. An assessment of low-flow may lead to better water resources management and reduce the risk of water scarcity. The assessment of low-flow in gauged basins where the flow time series are available is straightforward. The challenge exists in ungauged or poorly-gauged basins where the flow data are unavailable or of low quality. Due to the studies of low-flow assessment in ungauged basins are of limited, this study aims to address the low-flow assessment in 25 sub-basins in the Upper Ping River basin in Thailand with available data from 1995-2014 by defining an applicable regionalization method for extrapolating beyond the limitations of observed flow data. Three regionalization methods namely regional regression method, sub-basin similarity method, and climate adjustment method are investigated for the selected sub-basins. The regional regression method is based on a stepwise regression procedure as the relationship between low-flow characteristics and basin physical characteristics. The sub-basin similarity method considered the weight of donor basins according to a combination of physical similarity and spatial proximity. The climate adjustment method considered the distance, choice of record augmentation technique, and the length of overlap period between the subject and the donor basins. Ninety-five-percentile flow (Q95), baseflow index (BFI), and the annual minimum 7-day moving average streamflow with a 10-year recurrence interval (7Q10) are selected in representing the low-flow characteristics of the sub-basins. The result indicated that the three regionalization methods are applicable to predict low-flow in the Upper Ping River basin but with a different predictive degree. However, the comparison further indicated that the climate adjustment method performs well in predicting 7Q10 and Q95 while for BFI it yields a moderate performance when there are available flow records of at least 5 years. Alternatively, applying the regional regression method with Q95 is more recommended than the sub-basin similarity method or with 7Q10 and BFI when there is no flow record available or available with a period of fewer than 5 years.

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Rain Fed Rice Agriculture under Climate Variability in Southeast Asia: The Case of Thailand

Cited by 6 publications

References 10 publications

Predictive Modelling for Rice Weeds in Climate Change: A Review

Predictive Modelling for Rice Weeds in Climate Change: A Review

Determinants of Production and Income Risks of Rainfed Lowland Farming: A Case Study in Maros Regency, Indonesia

Low-flow assessment for ungauged sub-basin in upper ping river basin, Thailand

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