Long-term change in rainfall distribution in Northeast Thailand: will cropping systems be able to adapt?

Abstract

-Climate vagaries and the lack of irrigation, frequently combined with coarse-textured sandy and unevenly distributed saline soils, explain low crop yields and the endemic relative poverty of the rural population in Northeast Thailand (NET). Local and regional trends in agriculturally-relevant rainfall variables were investigated using the Mann-Kendall test, modified to account for serial correlation, and applied to 17 stations across NET, and the regional average Kendall's statistic. Limited changes in rainfall frequency, intensity and seasonality are observed at individual stations over the study period (1953-2004). But we found a significant regional trend toward a wetter dry season. Based on an intimate knowledge of the local farming systems, we discuss the cropping systems adaptation to these rainfall changes. If the wetting of the dry season extends in the future, as expected according to most climate projections, households would not find it difficult to adapt, except for the problems caused by temperature rise, mainly due to their renowned adaptive capacity and high mobility that historically produced diverse and resilient rural livelihood systems.Keywords: climate change adaptation / cropping systems / rainfall patterns / Thailand / trend Résumé -Évolution de la pluviométrie au Nord-Est de la Thaïlande : les systèmes de culture pourront-ils s'adapter ? Les irrégularités climatiques combinées à des conditions édaphiques défavorables expliquent les faibles rendements agricoles du Nord-Est de la Thaïlande, la région la plus pauvre du pays où l'agriculture est majoritairement non irriguée. Des tendances locales et régionales sont recherchées dans des variables pluviométriques contrôlant la production agricole. Une version modifiée du test de Mann-Kendall prenant en compte l'autocorrélation est appliquée aux chroniques de 17 stations dans cette région. La statistique régionale moyenne de Kendall est utilisée pour les tests régionaux. Quasiment aucune tendance locale n'est observée dans la fréquence, l'intensité et la saisonnalité des pluies sur la période d'étude . En revanche, la saison sèche est devenue significativement plus pluvieuse à l'échelle régionale. La capacité des systèmes de culture locaux à s'adapter à ce changement climatique est discutée. Si, comme la plupart des modèles climatiques le prévoient, l'augmentation des pluies de saison sèche se confirme dans le futur, les agriculteurs n'éprouveront probablement pas de difficultés pour s'y adapter, à l'exception des problèmes liés à l'augmentation des températures. Leur capacité d'adaptation, forgée par des siècles de pratiques agricoles en régime pluvial incertain, et le recours aux migrations saisonnières ont permis l'établissement de systèmes agraires diversifiés et résilients.

Indicator-to-impact links to help improve agricultural drought preparedness in Thailand

“…The cropland-masked monthly VIs were then averaged to the province level, the time series filtered to only include the growing season of the spatially-dominant crop within each province, and an annual average was taken. The growing season was taken from Lacombe et al (2017) for Cassava, FAO GIEWS Country Brief (FAO, 2021) for Paddy rice, Arunrat et al (2022) for Corn and FFTC (2015) for Longan. The annual time series for the VIs for each province was correlated with the yield of the dominant crop for that province using a Pearson correlation (Pearson, 1920).…”

Comparison of Two Hydrological Models, HEC-HMS and SWAT in Runoff Estimation: Application to Huai Bang Sai Tropical Watershed, Thailand

“…Therefore, the SWAT model performed moderately well compared the HEC-HMS model on a seasonal basis for the HBS watershed, Thailand. Lacombe et al [46] stated that northeastern Thailand receives approximately 80-90% of annual precipitation from May to October and above. Figure 8 shows the mean seasonal discharge for the HEC-HMS and SWAT models with the observed mean seasonal discharge at kh.92 hydrologic station for the 2007-2014 period.…”

“…Therefore, the SWAT model performed moderately well compared with the HEC-HMS model on a seasonal basis for the HBS watershed, Thailand. Lacombe et al [46] stated that northeastern Thailand receives approximately 80-90% of annual precipitation from May to October and above. In fact, in the SWAT model, the precipitation for a specific sub-basin is derived from the nearest weather station.…”

Cassava as an insurance crop in a changing climate: The changing role and potential applications of cassava for smallholder farmers in Northeastern Thailand

“…There is a distinct rainy season from May to October that exhibits a bimodal pattern with a first peak in May to June and the second in July to October (Polthanee, 1990). Average annual rainfall varies from 1,200 mm to 1,500 mm, based on isohytes (Lacombe et al 2017). The critical climatic factor affecting agriculture however, is the extreme variability of rainfall both within a year and between years, rather than the total amount of rainfall.…”