Climate Change in Relation with Productivity of Rice and Wheat in Tarai Region of Uttarakhand

The study has analysed changes in climate variables, viz. temperature and rainfall during the period 1969–2005 and has assessed their impact on yields of important food crops. A significant rise was observed in mean monthly temperature, but more so during the post-rainy season. The changes in rainfall, however, were not as significant. While an increase in maximum temperature was found to have an adverse effect on the crop yields, a similar increase in minimum temperature had a favourable effect on yields of most crops, but it was not sufficient to fully compensate the damages caused by the rise in maximum temperature. Pigeonpea, rice, chickpea and wheat were more vulnerable to rise in temperature. Rainfall had a positive effect on most crops, but it could not counterbalance the negative effect of temperature. The projections of climate impacts towards 2100 have suggested that with significant changes in temperature and rainfall, the rice yield will be lower by 15 per cent and wheat yield by 22 per cent. Coarse cereals will be affected less, while pulses will be affected more than cereals. If the changes in climate are not significant, damages to crops will be smaller. In the short-run too climate impacts will not be so severe.

Agriculture is highly dependent on climate because rainfall, temperature and sunlight are the primary determinants of crop development. Climate change driven effects such as variation in precipitation and changes in temperatures are likely to affect agricultural yields. Systematic planning of agricultural activities considering these effects is essential. As a first step towards this longer term objective, this work quantifies the effect of climate change on crop in short and long term in India. Wheat is chosen as the crop of interest. Madhya Pradesh, one of the leading wheat producing states in India, is the region under focus, and Betul district is selected for a initial studies. The CERES-wheat model in the Decision Support System for Agrotechnology Transfer (DSSAT) tool is used to estimate the impact of climate change on wheat yield. The CERES-wheat model has been calibrated and validated, and the calibrated parameters have been used to simulate wheat yield in the future. The base period for calculating base wheat yield is 2009-2019. Future wheat yields are calculated for two periods (2025-2055 and 2056-2085). The projected changes in precipitation, maximum temperature (Tmax) and minimum temperature (Tmin) in future compared to the base period are calculated using four different General Circulation Models (GCMs) and four Shared Socioeconomic Pathways (SSPs). To increase the study's robustness, 1000 samples are systematically generated using Latin Hypercube Sampling (LHS). A stochastic weather generator (WG), WeaGETS, is used to create a synthetic time series of climate variables. Using the 1000 different combinations of changes in climate variables, 1000 climate scenarios are generated using WeaGETS. The climate variables used to determine the relationship between climate and wheat yield were mean rainfall, rainfall variance, Tmax, and Tmin. Wheat yield ranged from 2065 to 3207 kg/ha during the baseline period, and it is expected to vary from 1629 to 3638 kg/ha between 2025 and 2055. Looking ahead to 2056-2085, wheat yields are estimated to range from 1363 to 3555 kg/ha. The sensitivity analysis results between climate variables and wheat yield for both periods suggest that wheat yield is positively correlated with mean rainfall and rainfall variance and negatively correlated with Tmax and Tmin. Maximum temperature has a significant negative correlation with wheat yield in both periods after excluding the effect of other climate variables. However, in the last stage of wheat yield development, the grain filling stage, Tmin is more critical than Tmax. These results highlight the need for systematic planning to manage negative impacts of climate change on wheat cultivation in India. These results will used as a basis for suggesting adaptation strategies to manage the impact of climate change on wheat yield.

Effect of changes in interannual climatic variability on CERES-wheat yields: sensitivity and [formula omitted] general circulation model studies

Inter-annual climatic variability in Bangladesh is critical and the probability of occurrence of extreme episodic/ climatic events has increased in the last couple of decades and thus threatening food security. Impact of inter-seasonal climatic va riability on Boro rice (dry season) yield in north-western parts of Bangladesh was analyzed using the historic weather datasets for 1971 to 2010 and MAKESENS model. Boro rice yield increased from 1980 onwards and the growth rate picked up with time. Inter-annual and inter-seasonal climatic variability was noticed through maximum and minimum temperatures, rainfall and sunshine hours. Typically, temperatures and rainfall showed increasing trends but sunshine hours were decreasing gradually during the study period. Growth rates in average annual maximum, minimum and mean air temperatures were 0.001, 0.016 and 0.009°C year-1, respectively. On regional scale, Boro-rice seasonal maximum temperature was decreasing by 0.013°C year-1 yet minimum and mean temperatures were increasing by 0.024 and 0.006°C year-1, respectively. Annual average sunshine hours in the study location were in decreasing trend by 0.027 hr year-1, but reduction in seasonal sunshine hours was 0.035 hr year-1. Inter-seasonal climatic variability was characterized through the Boro-rice yields in four test regions of north-west region of Bangladesh. Trend line equations were evolved for assessing the impact of climatic variations on Bororice yield. If maximum temperature changes by 1oC, Boro rice yield could be increased by 0.13 t ha-1, but it would reduce by 0.34 t ha-1 with one degree rise in minimum temperature. If sunshine hour decreases by 1 hr, Boro rice yield would decrease by 0.70 t ha-1 in study locations. Combined effects of maximum and minimum temperatures and sunshine hours showed significant influence on grain yields of Boro rice. These imply that temperature tolerant and solar radiation use-efficient rice varieties need to be bred for combating climate change impact in Bangladesh. There is a need to identify optimum sowing/transplanting window for the region, choice of suitable cultivars/ideo-types, and adoption of appropriate water and nutrients management strategies and adoption of appropriate resource conservation technologies for sustainable Boro rice production in Bangladesh.

This paper presents the results of the first stage of an ongoing project of evaluating the spatial and temporal variability of soil water as fundamental factors for vegetation regeneration in the arid ecosystems in the Blue Nile-eastern Sudan. The specific aim of the present study is to understand the temporal and spatial variations of the major climate variables in the region and discuss its relevance to regional climate variability and changes. In this case, we systematically analyze the major climate variables (maximum and minimum air temperature, relative humidity, and net solar radiation). To evaluate the different characteristics of the climate variables, Mann–Kendall method, two-phase regression scheme, and wavelet transform technique are used; each method has its own strength and weakness, and the results of the three methods complement each other. The results show that the annual and seasonal maximum temperatures are increasing significantly. The annual minimum temperature and minimum temperature in dry seasons are decreasing. The minimum temperature in rainy season is increasing with a smaller rate as compared with the increase of maximum temperature in the season. The difference between maximum and minimum temperature is increasing in all the seasons. Net solar radiation in the region shows a significant increasing trend in all seasons, which corresponds well with the changes of maximum temperature. Besides, significant decreasing trends can be identified for relative humidity in all the seasons.

The study assessed the changes in climatic variables in Hadeja Nguru wetland. Parameters evaluated includes; variation in climatic variables over a 40-year window (1979-2019) Data on climatic variables on daily basis were obtained for a period 40years and Satellite imageries of the study area were officially downloaded from the United State Geological Survey website. Paired sample T-test and chi-square test of association were used in assessing the variation in climatic factors. Result showed that indicated sparse distribution as a major effect of climate change. Decreased production in crops, land shade, damaged of harvested crops, increase in insect population, shortening the time of germinating seeds were thought to be the consequences of reduction in rainfall, excessive rainfall, irregular rain pattern and increase in temperatures respectively, Food scarcity, reduction in income due to depletion of crops were also pinpointed as impacts of climate change. Information on climate change and its impact were obtained majorly from radio, while major mitigating strategy for changing climatic variables. Maximum and minimum temperatures, precipitation, wind speed, relative humidity and solar intensity between 1979 and 2019 were 40.07℃ and 36.46℃, 1180.36mm and 58.18mm, 2.97m/s and 2.29m/s, 0.33g/kg and 0.22g/kg and 23.68w/m2 and 20.70w/m2 respectively. There was also a significant Chi-square value (33.481a) between respondents’ effect of climate change and increase in farm sizes. It is therefore concluded that there has been fluctuations in climatic variables. There is the need to put in place right policies to protect and preserve wetlands to enhance their sustainability and resilience to climatic changes and variability.

The study assessed the changes in climatic variables in Hadeja Nguru wetland. Parameters evaluated includes; variations in climatic variables over a 40-year window (1979-2019) Data on climatic variables on daily basis were obtained for a period 40years and Satellite imageries of the study area were officially downloaded from the United State Geological Survey website. Paired sample T-test and chi-square test of association were used in assessing the variation in climatic factors. Result showed that indicated sparse distribution as a major effect of climate change. Decreased in crops production, land shade, destruction of harvested crops, increase in insect population and shortened seed germination period were thought to be the consequences of reduction in rainfall, excessive rainfall, irregular rainfall pattern and increase in temperatures, Food scarcity, reduction in income due to depletion of crops were also pinpointed as impacts of climate change.. Maximum and minimum temperatures, precipitation, wind speed, relative humidity and solar intensity between 1979 and 2019 were 40.07 and 36.46, 1180.36mm and 58.18mm, 2.97m/s and 2.29m/s, 0.33g/kg and 0.22g/kg and 23.68w/m2 and 20.70w/m2 respectively. There was also a significant Chi-square value (33.481a) between respondents’ effect of climate change and increase in farm sizes. The paper concluded that there were fluctuations in climatic variables. There is the need to put in place right policies to protect and preserve wetlands to enhance their sustainability and resilience to climatic changes and variability.

This study focuses on the relationships between climate variability and wheat yield in Tashkent province. It contains a time series study of precipitation, temperature, and wheat yield, as well as the assessment of the link between yield and climatic factors and an examination of the influence of climate change on crop production using a regression model. Time series results of temperature present a positive trend in mean temperature in Bustanlik and Urtachirchik. Annual minimum temperature, the minimum temperature in spring, minimum temperature between September and May have changed significantly in Bustanlik over the years (p<0.05). Total precipitation shows a favourable trend in Bustanlik but a negative trend in Urtachirchik. There is no significant change detected in the time series. The magnitude of the change in climate variables shows no clear tendency. Wheat yield has changed significantly and increased up to 1.34 c/ha every year between 1998-2014. The highest association is determined between wheat yield and minimum temperature in the growing season (0.77) while the highest correlation was identified with the summer maximum temperature (-0.41) in Urtachirchik. The linear multiple regression model forecasted the wheat yield with a mean error of 0.08 c/ha in Urtachirchik and 0.06 c/ha in Bustanlik district.

Assessing the impact of climate change is crucial for addressing the challenges of sustaining and increasing rice production. This study employed the APSIM model driven by climate data from 27 global climate models under SSP245 and SSP585 emission scenarios to evaluate climate change effects on irrigated and rainfed rice in three key rice‐growing regions (Rangpur, Bogura, and Rajshahi) in northwest Bangladesh. Relative changes in climate variables, rice yield, and yield components were analysed for the near future (NF: 2031–2065) and far future (FF: 2066–2100), compared to a baseline period (1988–2022). Results indicate a substantial increase in temperature during FF under the SSP585 scenario, with maximum temperature rising by up to 3.3°C (3.1°C) and minimum temperature up to 3.7°C (3.3°C) during irrigated (rainfed) rice seasons. This increase could shorten the growth period of irrigated and rainfed rice by up to 18 days and 10 days, respectively, under SSP585. Rice yields were projected to increase in the NF by up to 14.7% (irrigated) and 6.5% (rainfed) under SSP245. However, yields were expected to decline in the FF by 21% (irrigated) and 11% (rainfed) under SSP585 scenario. These projected yield changes are primarily explained by variations in spikelet number (NSP) and spikelet fertility (SPFERT) across locations. While projected climate conditions enhance NSP by 22% (irrigated) and 11% (rainfed) due to increased CO 2 concentration and solar radiation, SPFERT was projected to decline sharply, by up to 47% and 35% in irrigated and rainfed rice seasons, respectively, in the FF under SSP585. The change in SPFERT was largely attributed to the change in elevated maximum temperatures during the anthesis period across the locations. While yields may increase in NF, an adaptation strategy is needed to sustain rice production during far future in Bangladesh.

Field‐based investigations of land use/cover changes are time‐consuming and challenging for large areas, where short‐ and long‐term changes in climatic and hydrologic variables affect ecosystem services. Thus, there is a substantial demand to boost the new modelling framework and employ remote sensing capabilities to quantify hydro‐climatic impacts on land dynamics. In this study, a conceptual framework has used to assess the climatic land greening, climatic land degradation, nonclimatic (hydrological) land greening, and nonclimatic (anthropogenic) land degradation responses with hydro‐climatic variables under dry and wet spells' effect in the Betwa River basin (BRB) of central India. Remotely sensed moderate‐resolution imaging spectro‐radiometer (MODIS) (normalized difference vegetation index [NDVI] and land cover) time‐series datasets had been used to quantify spatiotemporal changes in major land use/cover classes. The standardized coefficients for rainfall (β = 0.62) and relative humidity (β = 0.32) showed their high relative importance in the relationship analysis performed using multiple linear regression (MLR). The result indicates that dominant agricultural cropland has been significantly impacted by changes in maximum and diurnal temperature, which affirm degradation, and positively responded by changes in rainfall, minimum temperature, and aridity index, which demonstrate greening wet period. Spatial analysis showed that land degradation affecting ecosystem services had been variedly distributed from the upper to lower basin due to more climatic impacts than anthropogenic disturbances. Thus, the developed conceptual framework can be adopted to discover dynamic land consequences and understand their responses for sustaining ecosystem services in the dominant agricultural region.

The present study has analyzed variability in climate variables annually and seasonally (kharif and rabi season), viz. rainfall and temperature during from 1985 to 2021 and found its their impact on productivity of maize and wheat crops at different seven locations of Himachal Pradesh. The study found that, except for the maximum temperature in the kharif season, practically all of the seven sites had significant increases in maximum and minimum temperatures annually and seasonally over the study period. Highest positive deviation was found in minimum temperature of Kangra district rabi season i.e., 2.12ºC while lowest was found in kharif season i.e., 0.50 ºC. Pettit’s homogeneity test showed climate change year 1998 and afterward annually minimum temperature was significantly rise. Climate change year showing positive change in rainfall that is showing increasing trend after 1998 at all the locations. Increases in maximum temperature had adverse impact on maize crop yield in the kharif season and a positive impact on wheat yield in the rabi season, whereas rainfall had a positive impact on maize and wheat crop yield.

It is generally assumed that rainfall intensity will increase with temperature increase, irrespective of the underlying changes to the average rainfall. This study documents and investigates long-term trends in rainfall intensities, annual rainfall, and mean maximum and minimum temperatures using the Mann–Kendall trend test for nine sites in eastern Australia. Relationships between rainfall intensities at various durations and 1) annual rainfall and 2) the mean maximum and minimum temperatures were investigated. The results showed that the mean minimum temperature has increased significantly at eight out of the nine sites in eastern Australia. Changes in annual rainfall are likely to be associated with changes in rainfall intensity at the long duration of 48 h. Overall, changes in rainfall intensity at short durations (<1 h) positively correlate with changes in the mean maximum temperature, but there is no significant correlation with the mean minimum temperature and annual rainfall. Additionally, changes in rainfall intensity at longer durations (≥1 h) positively correlate with changes in the mean annual rainfall, but not with either mean maximum or minimum temperatures for the nine sites investigated.

CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials CR 58:133-148 (2013) - DOI: https://doi.org/10.3354/cr01194 ENSO, climate variability and crop yields in China Jiabing Shuai1,2, Zhao Zhang1,*, De-Zheng Sun2,3, Fulu Tao4, Peijun Shi1,** 1State Key Laboratory of Earth Surface Processes and Resource Ecology, Academy of Disaster Reduction and Emergency Management, Beijing Normal University, Beijing 100875, China 2Cooperative Institute for Research in Environmental Sciences, University of Colorado and 3NOAA, Earth System Research Laboratory, Physical Science Division, Boulder, Colorado 80305, USA 4Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China *Corresponding author. Email: zhangzhao@bnu.edu.cn **Corresponding author. Email: spj@bnu.edu.cn ABSTRACT: The El Niño-Southern Oscillation (ENSO) is one of the most important contributors to global interannual climate variability, but the relationship between seasonal climate and crop yield variations associated with ENSO in China remains inconclusive. In this study, we investigated the impacts of ENSO on the yield of 3 staple crops (rice, wheat, and corn) at the provincial scale. We found that ENSO has significant impacts on wheat yields throughout China, and on rice and corn yields in major production areas. Specifically, more (less) rainfall during the wheat growing season in El Niño (La Niña) years leads to increases (decreases) in wheat yield, especially in southeastern China. Increases (decreases) in rice yield in northeastern China are due to warming (cooling) in El Niño (La Niña) years. In southern China, the variability of rainfall plays a more important role in rice yield than that in northern China. Corn yields in northern China are significantly affected by ENSO-induced changes in maximum temperature, solar radiation, and rainfall. Moreover, all of the staple crop yields are highly correlated with the ENSO index with a lead of at least 6 mo. For rice and corn in many provinces, the yields are typically most correlated with the index of the spring season during the ENSO developing years, suggesting that such yields can be predicted 1 yr before the growing season. The large variability in seasonal climate and agricultural production associated with ENSO warrants the application of ENSO information to food market management in China. KEY WORDS: ENSO · Crop yields · Climate variability · China Full text in pdf format PreviousNextCite this article as: Shuai J, Zhang Z, Sun DZ, Tao F, Shi P (2013) ENSO, climate variability and crop yields in China. Clim Res 58:133-148. https://doi.org/10.3354/cr01194 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in CR Vol. 58, No. 2. Online publication date: December 09, 2013 Print ISSN: 0936-577X; Online ISSN: 1616-1572 Copyright © 2013 Inter-Research.

<strong class="journal-contentHeaderColor">Abstract.</strong> This study used high-quality daily temperature data from 1960&ndash;2019, recorded at five observing stations (Huoqiu, Huoshan, Jinzhai, Lu&rsquo;an, and Shucheng) in the city of Lu&rsquo;an (China), to study the asymmetric changes of maximum and minimum temperatures in the region of the Dabie Mountains in western Anhui Province (China). Results showed that changes in annual maximum and minimum temperatures over the studied 60 years were asymmetric; the average climatic trend rate of minimum temperature was 0.262 &deg;C/10a, while that of maximum temperature was 0.198 &deg;C/10a, i.e., the temperature increase of the former was approximately 1.3 times that of the latter. Asymmetric changes of maximum and minimum temperatures were evident in winter, summer, and autumn throughout the entire 60-year period and in spring for the first 45 years. The spatial distribution of the asymmetric changes was uneven with decrease both from high latitudes to low latitudes and from high elevations to low elevations. High-elevation high-latitude areas such as Jinzhai, Lu&rsquo;an, and Huoqiu exhibited the most significant asymmetric changes seasonally and annually. Abrupt changes in the trends of maximum and minimum temperatures occurred in 1994. Three periodicities were found in the maximum temperature series, i.e., 15&ndash;18, 32, and 4&ndash;6 years, and four periodicities were found in the minimum temperature series, i.e., 9&ndash;10, 32, 20&ndash;22, and 4 years. The 4&ndash;6-year periodicity of maximum temperature and the 4-year periodicity of minimum temperature (which passed the 95% significance test) should be associated with El Ni&ntilde;o.

This paper shows the effects of changes in the spatial-temporal behavior and phase shift of climate variables on rainfed agriculture in the Lerma-Chapala-Santiago Basin in central Mexico. Specifically, changes in rainfall (R), maximum temperature (Tmax), and minimum temperature (Tmin) were analyzed over two 25-year periods (1960 to 1985 and 1986 to 2010). Climate surfaces were generated by interpolation using the thin-plate smoothing spline algorithm in the software ANUSPLIN. Climate data were Fourier-transformed and fitted to a sinusoidal curve model, and changes in amplitude (increase) and phase were analyzed. The temporal behavior (1960–2010) indicated that rainfall was the most stable variable at the monthly level and presented no significant changes. However, Tmax increased by 2°C in the final period, and Tmin increased by 0.7°C at the end of the final period. The basin was discretized into ten rainfed crop areas (RCAs) according to the extent of changes in the amplitude and phase of the climate variables. The central and southern portions (55% of the area) presented more significant changes in amplitude, mainly in Tmin and Tmax. The remaining RCAs were smaller (14.6%) but presented greater variation: the amplitude of the Tmin decreased in addition to showing a phase shift, whereas Tmax increased in addition to showing a phase shift. These results translate into a delay in the characteristic temperatures of the spring and summer seasons, which can impact the rainfed crop cycle. Additionally, rainfall showed an annual decrease of approximately 50 mm in all RCAs, which can affect the phenological development of crops during critical stages (emergence through flowering). These changes represent a significant threat to the regional economy and food security of Mexico.