Determinants of climate variability adaptation strategies: A case of Itang Special District, Gambella Region, Ethiopia

Getahun, Azemir Berhanu; Ayal, Desalegn Yayeh; Ture, Kassahun; Zeleke, Tadesse Terefe

doi:10.1016/j.cliser.2021.100245

Cited by 32 publications

(24 citation statements)

References 21 publications

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“…OLS was used to find out important determinants affecting the farmer's level of adaptation to climate variability. Important determinants that affect farmers' level of adaptation were selected based on the previous studies, such as years of schooling [22], farming experience [22], income [23,24], perception of climate variability [22,25], membership organization [22,26], and extreme climate events [22,25].…”

Section: 𝑇𝐴 = 𝑆𝐴mentioning

confidence: 99%

Adaptation to climate variability of rainfed farmers in Seluma Regency, Bengkulu, Indonesia

Mulyasari

Prawito

Yuristia

2022

IOP Conf. Ser.: Earth Environ. Sci.

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Farmers are synonymous with poverty because of the great uncertainty about the impact and magnitude of climate variability. Adaptation efforts, in principle, minimize vulnerability to impacts caused by climate variability. This study aims to see the level of adaptation of farmers and the factors that influence it. A randomly selected 100 rainfed farmers survey was conducted in Seluma Regency, Bengkulu, from June to September 2020. The analysis used to measure the level of adaptation was to compare the number of adaptations adopted by farmers with the total adaptation used in this study and to analyze the factors that affect the level of adaptation using multiple regression models. The results showed that rainfed farmers have a low of adaptation to climate variability. Most farmers make adjustments to planting time, replace climate-resistant varieties, and take advantage of government assistance as a form of adaptation to climate variability. The level of adaptation of rainfed farmers to climate variability is influenced by experience, income, and farmer group membership.

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Section: 𝑇𝐴 = 𝑆𝐴mentioning

confidence: 99%

Adaptation to climate variability of rainfed farmers in Seluma Regency, Bengkulu, Indonesia

Mulyasari

Prawito

Yuristia

2022

IOP Conf. Ser.: Earth Environ. Sci.

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“…The factors influencing agricultural households' adaptation to climate change can be categorised as personal attributes, psychological factors, and socio-economic factors (Guo et al 2021). Studies have found the main determinants of adaptation to climate change to be gender (Qazlbash, 2021), farm size (Moroda et al, 2021), household size (Getahun et al, 2021), livestock holding (Khan et al, 2021;Alauddin & Sarker, 2021), and income (Sertse 2021). Table 2 shows that education is a major determinant of using different crop varieties, mixed cropping, fertilizers, and tree planting.…”

Section: Perception Of Climate Changementioning

confidence: 99%

Vulnerability and adaptation to climate change in Rajasthan

2022

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Climate change is a globally challenging phenomenon that is particularly distressing for the agricultural sector, as agricultural products and productivity depend on the climate. This study analyses agricultural households? perception of climate change and the adaption strategies undertaken to mitigate it. A purposive random sampling technique is used to collect primary data from a survey conducted in the arid and semi-arid regions of Rajasthan, India. The study employs logistic regression to identify the determinants of the perception of climate change and adaptation strategies, while a livelihood vulnerability index is constructed to indicate households? degree of vulnerability, focusing especially on adaptive capacity. Out of the total sample of 600 households analysed, 534 perceive a long-term change in the climate. Farmers? adaptation strategies include crop diversification, mixed cropping, crop rotation, and farm ponds. The major factors affecting adaptation are the educational status of the household head, farming experience, type of financial support, agricultural training, land size, access to agricultural institutions, distance between the household and farmland, and storage. The livelihood vulnerability index shows that most of the households are moderately vulnerable. The study recommends an efficient weather forecasting system and effective government policies to improve credit availability, financial support, and agricultural mechanization.

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“…Therefore, it's crucial to detect the historical seasonal and interannual variability and trend analysis of hydroclimatic variables (rainfall, temperature and stream flow) at regional and local scales to depict the response of subbasin to hydroclimatic variability and to develop more effective responsive strategies to manage climate induced risks (Mahmood et al, 2019;Anose et al, 2021) for better management and allocation of water resources for future sustainable water resource management (Daba et al, 2020;Etana et al,2020;Getahun et al, 2021;Orke and Li, 2021). Hence, different watershed based hydroclimatic parameters variability and trend analysis was conducted in Ethiopia.…”

Section: Introductionmentioning

confidence: 99%

Spatio-temporal variability and trends of hydroclimatic variables at Zarima Sub-Basin North Western Ethiopia

2022

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Globally, hydroclimatic variables have been changed due to human activities and have an impact on agricultural production and water resource management. This study investigated the spatio-temporal variability of hydroclimatic variables in Zarima subbasin using rainfall and temperature data from 1984 to 2018 and stream flow data from 1990 to 2014. The data were analyzed using the coefficient of variation, standardized anomaly index, Mann–Kendall trend and Sen’s slope estimator test. The results showed that rainfall, maximum and minimum temperatures of the Zarima subbasin varied spatially and temporally. The annual and Kiremit season rainfall and stream flow showed low to moderate variability (CV < 30%) whereas Bega and Belg season rain fall and stream flow showed high degree of variability (CV < 40%). The annual and Kiremit season rainfall showed relatively higher variability along the northern border of the subbasin. However, maximum temperature showed less degree of variability (CV < 10%) over the subbasin, whereas the annual and seasonal minimum temperatures showed less to moderate variability (CV = 2–28%). The minimum temperature showed moderate variability around the south east lower border of the subbasin on the annual time scale and the north east part of the subbasin during the Kiremit season. The Bega and Belg seasons mean minimum temperatures showed less to high degree of variability (CV = 0–40%). The south east lower part of the subbasin showed moderate to high variability during the Bega and Belg seasons. Results of a standardized anomaly index of the rainfall, temperature and stream flow confirmed that the sub basin experienced fluctuations between dry, wet, cool and warm years. The spatial representation of annual rainfall showed a statically significant increasing trend in some parts of the subbasin and an insignificant increasing trend in the majority of the subbasin up to 300 mm per decade, while the Bega and Belg seasons showed statistically insignificant increasing and decreasing trends. Kiremit season rainfall showed heterogenous results in both statistics and trend direction. The mean annual maximum showed an increasing trend from 0.35 to 0.9 °C. The Bega, Belg and Kiremit seasons' maximum temperatures increased by a range of 0.35 to 0.95 °C; 0.4 from 1.2 °C and 0.1 to 0.55 °C pre decade respectively. While the annual minimum temperature increased by 0.05 to 0.5 °C and decreasing trend by 0.1 to 0.3 °C around the south eastern part of the subbasin. The Bega and Belg season minimum temperatures increased up to 0.5 °C and 1 °C and temperatures decreased in the range of 0.1 to 0.5 oC per decade. The Kiremit season minimum temperature increased by a range of 0.05 to 0.5 °C. The annual, Bega, Belg and Kiremit season stream flow increased insignificantly by 0.32, 0.31, 0.02 and 0.68 mm3/s respectively. In general, the subbasin experienced hydroclimatic variability which affects the life of the people, agricultural production and the economy of the area. This needs further investigation for planning and management of water resource management for the success of future water resources projects.

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Determinants of climate variability adaptation strategies: A case of Itang Special District, Gambella Region, Ethiopia

Cited by 32 publications

References 21 publications

Adaptation to climate variability of rainfed farmers in Seluma Regency, Bengkulu, Indonesia

Adaptation to climate variability of rainfed farmers in Seluma Regency, Bengkulu, Indonesia

Vulnerability and adaptation to climate change in Rajasthan

Spatio-temporal variability and trends of hydroclimatic variables at Zarima Sub-Basin North Western Ethiopia

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