scholarly journals Climatic Impact on Wheat Production in Terai of Nepal

2016 ◽  
Vol 23 (1-2) ◽  
pp. 1-22 ◽  
Author(s):  
Niranjan Devkota ◽  
Ram Kumar Phuyal
Keyword(s):  
Population Density ◽  
Climatic Change ◽  
Minimum Temperature ◽  
Wheat Yield ◽  
Maximum Temperature ◽  
Climatic Impact ◽  
Wheat Production ◽  
Average Maximum ◽  
Human Labour ◽  
Net Revenue

This study examines the climatic impact on wheat production in Terai of Nepal. This paper employs a Ricardian cross-sectional approach to estimates the relationship between wheat production and net revenue associated with wheat production in the plain area of Nepal (i.e. Terai) with different temperatures (average, maximum and minimum), precipitation and other traditional inputs like population density, seed, fertilizer, human labour, bullock labour and tractor. By using district level secondary data of 25 years, this study finds significant positive impact of the average and maximum temperature and significant negative impact of the minimum temperature on net revenue and wheat yield of the Terai region. Similarly, precipitation has mixed impacts. With the maximum temperature, increase in precipitation reduces net revenue and wheat yield whereas with average and minimum temperature, precipitation increases wheat yields as well as revenue. Other traditional inputs like population density, seed, manure, human labour and tractor used are positively associated with climatic change and increase net revenue as well as wheat yield whereas fertilizer and bullock used are negatively associated with climatic change and reduce net revenue and wheat yield.The Journal of Development and Administrative Studies (JODAS), Vol. 23(1-2), pp. 1-22

scholarly journals Nature of transmission of Covid19 in India

2020 ◽  
Author(s):  
Anushree Roy ◽  
Sayan Kar
Keyword(s):  
Population Density ◽  
Minimum Temperature ◽  
Maximum Temperature ◽  
Weak Correlation ◽  
Average Maximum ◽  
Average Maximum Temperature ◽  
Average Relative Humidity ◽  
Maximum Temperatures ◽  
Number Of Individuals

AbstractWe examine available data on the number of individuals infected by the Covid-19 virus, across several different states in India, over the period January 30, 2020 to April 10, 2020. It is found that the growth of the number of infected individuals N(t) can be modeled across different states with a simple linear function N(t) = γ + αt beyond the date when reasonable number of individuals were tested (and when a countrywide lockdown was imposed). The slope α is different for different states. Following recent work by Notari (arxiv:2003.12417), we then consider the dependency of the α for different states on the average maximum and minimum temperatures, the average relative humidity and the population density in each state. It turns out that like other countries, the parameter α, which determines the rate of rise of the number of infected individuals, seems to have a weak correlation with the average maximum temperature of the state. In contrast, any significant variation of α with humidity or minimum temperature seems absent with almost no meaningful correlation. Expectedly, α increases (slightly) with increase in the population density of the states; however, the degree of correlation here too is negligible. These results seem to barely suggest that a natural cause like a hot summer (larger maximum temperatures) may contribute towards reducing the transmission of the virus, though the role of minimum temperature, humidity and population density remains somewhat obscure from the inferences which may be drawn from presently available data.

scholarly journals Drought, Climate Change, and Dryland Wheat Yield Response: An Econometric Approach

2020 ◽  
Vol 17 (14) ◽  
pp. 5264 ◽  
Author(s):  
Samira Shayanmehr ◽  
Shida Rastegari Henneberry ◽  
Mahmood Sabouhi Sabouni ◽  
Naser Shahnoushi Foroushani
Keyword(s):  
Climate Change ◽  
Linear Model ◽  
Climatic Change ◽  
Minimum Temperature ◽  
Wheat Yield ◽  
Maximum Temperature ◽  
Yield Variability ◽  
Non Linear ◽  
The Mean ◽  
The Impact

Agriculture has been identified as one of the most vulnerable sectors affected by climate change. In the present study, we investigate the impact of climatic change on dryland wheat yield in the northwest of Iran for the future time horizon of 2041–2070. The Just and Pope production function is applied to assess the impact of climate change on dryland wheat yield and yield risk for the period of 1991–2016. The Statistical Downscaling Model (SDSM) is used to generate climate parameters from General Circulation Model (GCM) outputs. The results show that minimum temperature is negatively related to average yield in the linear model while the relationship is positive in the non-linear model. An increase in precipitation increases the mean yield in either model. The maximum temperature has a positive effect on the mean yield in the linear model, while this impact is negative in the non-linear model. Drought has an adverse impact on yield levels in both models. The results also indicate that maximum temperature, precipitation, and drought are positively related to yield variability, but minimum temperature is negatively associated with yield variability. The findings also reveal that yield variability is expected to increase in response to future climate scenarios. Given these impacts of temperature on rain-fed wheat crop and its increasing vulnerability to climatic change, policy-makers should support research into and development of wheat varieties that are resistant to temperature variations.

scholarly journals The effect of average temperature on suicide rates in five urban California counties, 1999–⁠2019: an ecological time series analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sierra Cheng ◽  
Rebecca Plouffe ◽  
Stephanie M. Nanos ◽  
Mavra Qamar ◽  
David N. Fisman ◽  
...  
Keyword(s):  
Public Health ◽  
Suicide Rate ◽  
Minimum Temperature ◽  
The United States ◽  
Additive Models ◽  
Maximum Temperature ◽  
Mortality Data ◽  
Average Temperature ◽  
Suicide Rates ◽  
Average Maximum

Abstract Background Suicide is among the top 10 leading causes of premature morality in the United States and its rates continue to increase. Thus, its prevention has become a salient public health responsibility. Risk factors of suicide transcend the individual and societal level as risk can increase based on climatic variables. The purpose of the present study is to evaluate the association between average temperature and suicide rates in the five most populous counties in California using mortality data from 1999 to 2019. Methods Monthly counts of death by suicide for the five counties of interest were obtained from CDC WONDER. Monthly average, maximum, and minimum temperature were obtained from nCLIMDIV for the same time period. We modelled the association of each temperature variable with suicide rate using negative binomial generalized additive models accounting for the county-specific annual trend and monthly seasonality. Results There were over 38,000 deaths by suicide in California’s five most populous counties between 1999 and 2019. An increase in average temperature of 1 °C corresponded to a 0.82% increase in suicide rate (IRR = 1.0082 per °C; 95% CI = 1.0025–1.0140). Estimated coefficients for maximum temperature (IRR = 1.0069 per °C; 95% CI = 1.0021–1.0117) and minimum temperature (IRR = 1.0088 per °C; 95% CI = 1.0023–1.0153) were similar. Conclusion This study adds to a growing body of evidence supporting a causal effect of elevated temperature on suicide. Further investigation into environmental causes of suicide, as well as the biological and societal contexts mediating these relationships, is critical for the development and implementation of new public health interventions to reduce the incidence of suicide, particularly in the face increasing temperatures due to climate change.

scholarly journals Evaluation of Climate Change on Streamflow, Sediment, and Nutrient Load at Watershed Scale

Climate ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 165
Author(s):  
Prem B. Parajuli ◽  
Avay Risal
Keyword(s):  
Climate Change ◽  
Water Quality ◽  
Minimum Temperature ◽  
Future Climate ◽  
Maximum Temperature ◽  
Nutrient Load ◽  
Climate Scenarios ◽  
Monthly Average ◽  
Average Maximum ◽  
Monthly Streamflow

This study evaluated changes in climatic variable impacts on hydrology and water quality in Big Sunflower River Watershed (BSRW), Mississippi. Site-specific future time-series precipitation, temperature, and solar radiation data were generated using a stochastic weather generator LARS-WG model. For the generation of climate scenarios, Representative Concentration Pathways (RCPs), 4.5 and 8.5 of Global Circulation Models (GCMs): Hadley Center Global Environmental Model (HadGEM) and EC-EARTH, for three (2021–2040, 2041–2060 and 2061–2080) future climate periods. Analysis of future climate data based on six ground weather stations located within BSRW showed that the minimum temperature ranged from 11.9 °C to 15.9 °C and the maximum temperature ranged from 23.2 °C to 28.3 °C. Similarly, the average daily rainfall ranged from 3.6 mm to 4.3 mm. Analysis of changes in monthly average maximum/minimum temperature showed that January had the maximum increment and July/August had a minimum increment in monthly average temperature. Similarly, maximum increase in monthly average rainfall was observed during May and maximum decrease was observed during September. The average monthly streamflow, sediment, TN, and TP loads under different climate scenarios varied significantly. The change in average TN and TP loads due to climate change were observed to be very high compared to the change in streamflow and sediment load. The monthly average nutrient load under two different RCP scenarios varied greatly from as low as 63% to as high as 184%, compared to the current monthly nutrient load. The change in hydrology and water quality was mainly attributed to changes in surface temperature, precipitation, and stream flow. This study can be useful in the development and implementation of climate change smart management of agricultural watersheds.

scholarly journals Agro-metrological investigation of bumper apple productivity in Himachal Pradesh, India

2016 ◽  
Vol 8 (1) ◽  
pp. 133-139
Author(s):  
Ranbir Singh Rana ◽  
Manmohan Singh ◽  
Ramesh Ramesh ◽  
Aditya Aditya ◽  
Ranu Pathania
Keyword(s):  
Low Temperature ◽  
Temperature Rise ◽  
Minimum Temperature ◽  
Fruit Set ◽  
Himachal Pradesh ◽  
Maximum Temperature ◽  
Metrological Investigation ◽  
Bloom Period ◽  
Average Maximum ◽  
Average Maximum Temperature

The study aimed to investigate the productivity and weather relationship for the apple growing areas of Himachal Pradesh viz., Kalpa, Bhuntar and Shimla in district Kinnaur, Kullu and Shimla, respectively. The results revealed that pre bloom period (November to February) in the year 2009-10 remained cooler. The minimum temperature of 0.4 to 0.9, 1.0 to 1.1°C and 1.9 to 2.2°C and maximum temperature of 6.7, 1.0 to 1.1 and 1.7°C were lower in Shimla, Bhuntar and Kalpa region, respectively compared to 1995-2009.. The maximum temperature for the chill accumulation months of November, December, January and February during 2009-10 showed 13 to 19 per cent lower compared to 1995-2009. The average pre bloom rainfall during 2010 was 39 to 57 per cent higher than 1995-2009 indicating sustainable bloom period. The 3 to 4°C temperature rise during March 2010 (19 to 24°C) as compared to 1995-2009 (16 to 21.4°C) coupled with 52 per cent higher precipitation benefited the crop in profuse flowering and hence good fruit set. The average maximum temperature during the post bloom period (May-June) in 2009-10 was 1°C higher compared to the previous years coupled with 23 per cent higher rainfall resulting in an highest productivity. The highest productivity (8.57 MT/ha) during 2010 which was 58 per cent higher than the previous years can be ascribed due to the favorable low temperature in pre bloom period and increase in the temperature inthe month of March along with adequate rainfall in the bloom and post bloom period.

scholarly journals Seasonal Trend Analysis of Climatic Parameters Relation to Impacts on the Crop Productivity of the Major Crops in Bangladesh

2016 ◽  
Author(s):  
Nafia Jahan Rashmi ◽  
Md. Forhad Hossain ◽  
Mirza Hasanuzzaman
Keyword(s):  
Minimum Temperature ◽  
Rice Yield ◽  
Pearson Correlation ◽  
Wheat Yield ◽  
Seasonal Trend ◽  
Series Data ◽  
Maximum Temperature ◽  
Climatic Parameters ◽  
Positive Effects ◽  
The Relationship

In Bangladesh, climate change is a major concern because of its geophysical location and climate dependent agriculture. As sessile organisms, crops plants have to face difficulties often in this environmentally vulnerable country. Therefore, this study examines the seasonal trend of two climatic parameters viz. temperature (maximum and minimum) and rainfall over a period of 1983 to 2013. Besides, this study provides insight into the relationship between climatic parameters and crop yield of two major crops viz. rice and wheat during 1997-2013. To assess the relationship of climatic parameters with time and yield using Pearson correlation analysis, time series data used at an aggregate level. SPSS software utilized for this analysis. The cropping seasons such as rice growing seasons Aus (summer rice), Aman (autumn rice) and Boro (winter rice) exhibited a significant increase in maximum and minimum temperature. Rainfall found to have a decreasing trend for all the seasons. This study also revealed that the climatic parameters had significant effects on rice yield, but these results varied among three rice crops. Maximum temperature had positive effects on all rice yields, especially on Aus and Aman. Minimum temperature had a negative effect on Aman rice yield but a positive effect on Aus rice yield. Wheat yield negatively associated with temperature. Rainfall exhibited negative relation with both rice and wheat yield.

scholarly journals Influence of prevailing weather parameters on population dynamics of spotted stem borer, Chilo partellus (Swinhoe) and its natural enemies on maize in Haryana

2021 ◽  
Vol 22 (3) ◽  
pp. 295-304
Author(s):  
GAURAV SINGH ◽  
MAHA SINGH JAGLAN ◽  
TARUN VERMA ◽  
SHIVANI KHOKHAR
Keyword(s):  
Population Dynamics ◽  
Chilo Partellus ◽  
Natural Enemies ◽  
Minimum Temperature ◽  
Significant Positive Correlation ◽  
Maximum Temperature ◽  
Positive Correlation ◽  
Average Maximum ◽  
Weather Parameters ◽  
Average Minimum Temperature

The experiment was conducted at CCS Haryana Agricultural University Regional Research Station, Karnal to ascertain the influence of prevailing meteorological parameters on population dynamics of Chilo partellus and its natural enemies on maize during Kharif, 2017. Maximum oviposition (0.75 egg masses per plant) was recorded during 28th standard meteorological week (SMW) whereas larval population was at peak during 31st SMW (3.8 larvae per plant). Cumulative (47.5%) and fresh plant infestation (11.5%) were maximum during 34th and 28th SMW, respectively. Maximum egg parasitisation (6.53%) by Trichogramma sp. and larval parasitisation (31.64%) by Cotesia flavipes was recorded during 28th and 33rd SMW, respectively. Changes in pest population were correlated and regressed with weather parameters. Egg and larval populations of C. partellus and parasitisation by Trichogramma sp. exhibited significant positive correlation with average minimum temperature whereas C. flavipes exhibited significant negative correlation with average maximum temperature (r = -0.741) and highly significant positive correlation with evening relative humidity (r = 0.695). Plant infestation and dead heart formation were significantly correlated with average minimum temperature and non-significantly correlated with all other weather parameters. The multiple linear regression analysis explained the variability due to various weather parameters. This information can be utilised while formulating integrated management tactics against this pest.

scholarly journals Temporal Variability, Trends of Climatic Variables and Drought Analysis of Rajshahi and Sylhet District, Bangladesh

2021 ◽  
Vol 46 (2) ◽  
pp. 133-141
Author(s):  
Fatamatuj Sunny ◽  
Md Selim Miah ◽  
Md Younus Mia ◽  
Ruksana Haque Rimi
Keyword(s):  
Relative Humidity ◽  
Minimum Temperature ◽  
Climatic Variables ◽  
Maximum Temperature ◽  
Climate Index ◽  
Climatic Data ◽  
Climatic Indices ◽  
Sen’S Slope ◽  
Average Maximum ◽  
Average Rainfall

The study was conducted to quantify the change of selected climatic variables (rainfall, relative humidity, maximum and minimum temperature) over 50 years at Rajshahi and Sylhet districts in Bangladesh. Annual, seasonal, and monthly climatic data comparisons have been executed between 1968-1992 and 1993-2017 through trend analysis. The Mann-Kendall statistic and Sen's Slope model were used to reveal the trends and estimate the magnitude of change respectively. Prediction of the climatic variable of 10 years (2018-2027) was made based on the ARAR algorithm using MaxStat Pro software. Rainfall data were used to analyze drought by using climatic indices (De Mortone Aridity Index, IdM; Seleaninov Hydrothermic Index, IhS; Donciu Climate Index, IcD). Average rainfall was decreasing dramatically in monsoon season at Rajshahi and in both premonsoon and monsoon seasons at Sylhet. The negative change of average rainfall in the monsoon at Rajshahi from 1968-1992 to 1993-2017 was found 29.17 mm. The maximum temperature was increasing in all seasons in both Rajshahi and Sylhet. Annual Mannkendall trend test and Sen’s slope revealed that relative humidity was decreasing and maximum temperature was increasing significantly at Sylhet for the period 1993-2017. At Rajshahi, during 1968-1992, relative humidity was increasing by 0.247 % per year, and minimum temperature was decreasing 0.049℃ per year. Rainfall was decreasing insignificantly in both time scales. ARAR algorithm predicted that average maximum temperature might become comparatively higher than the previous 50 years. 1992 and 2010 were identified as drought years from all climatic indices, and 1969, 1981, and 1997 as excessive wet years at Rajshahi. No drought events were identified during 1968-2017 at Sylhet and the year 2017 to be an excessively wet year. IhS predicted 2020, 2025, and 2027 as drought years and 2024 as an excessive wet year at Sylhet. Asiat. Soc. Bangladesh, Sci. 46(2): 133-141, December 2020

scholarly journals Impact of Climate Change on Rice and Wheat Yield in Punjab State of India: A District-Level Analysis

2021 ◽  
Author(s):  
Mandeep Bhardwaj ◽  
Pushp Kumar ◽  
Siddharth Kumar ◽  
Ashish Kumar
Keyword(s):  
Climate Change ◽  
Least Squares ◽  
Minimum Temperature ◽  
Rice Yield ◽  
Wheat Yield ◽  
Ordinary Least Squares ◽  
District Level ◽  
Maximum Temperature ◽  
Impact Of Climate Change ◽  
The Impact

Abstract The present study aims to examine the impact of climate change on wheat and rice yield of the Punjab state of India. Using district-level panel data from 1981 to 2017, the study employs fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS), and pooed mean group (PMG) approaches. The Pedroni cointegration has established a long-run relationship of climate variables with rice and wheat crops. The results of FMOLS and DOLS show that minimum temperature has a positive effect on both wheat and rice, while maximum temperature is found to be negatively contributing to both the crops. Rainfall has a significant adverse effect on wheat yield. Seasonal rainfall has been detrimental to wheat and rice yield in the study period, indicating that excess rainfall proved counterproductive. Pooled mean group (PMG) model confirms the robustness of the results obtained by FMOLS and DOLS techniques. Moreover, Dumitrescu-Hurlin causality test has revealed a unidirectional causality running from minimum temperature, rainfall & maximum temperature to rice and wheat yield. The findings of the study suggest that the government should invest in developing stress-tolerant varieties of wheat and rice, managing crop residuals to curb further environmental effect and sustain natural resources for ensuring food security.

scholarly journals Climate Change and Sugarcane Productivity in India: An Econometric Analysis

2014 ◽  
Vol 5 (2) ◽  
pp. 111-122 ◽  
Author(s):  
Ajay Kumar
Keyword(s):  
Minimum Temperature ◽  
Rainy Season ◽  
Climatic Factors ◽  
Maximum Temperature ◽  
Empirical Results ◽  
Average Maximum ◽  
Average Maximum Temperature ◽  
Cane Productivity ◽  
Sugarcane Productivity ◽  
Average Minimum Temperature

This study provides an understanding for the relationship between climatic factors and sugarcane productivity in India. The main objective of this paper is to estimates the impact of climatic and non-climatic factors on sugarcane productivity. To check the consistency of empirical results, simple linear regression model, Ricardian productivity regression (non-linear) model and Cobb-Douglas production function models are employed. The data set incorporates 390 observations corresponding to thirteen states with panel data for 30 years during 1980 to 2009. These all models include sugarcane productivity as dependent variable. Irrigated area, agriculture labour, consumption of fertilizers, literacy rate, tractors and farm harvest price (at constant level) are considered as explanatory variables. Average rainfall, average maximum and average minimum temperature include as climatic factors to capture the effect of climatic conditions on cane productivity. These climatic factors are incorporate for three weather seasons such as rainy, winter and summer. Empirical results based on Prais Winsten models with panels corrected standard errors (PCSEs) estimation shows that climatic factors i.e. actual rainfall, average maximum and average minimum temperature have a statistically significant impact on sugarcane productivity. The climatic effect for various factors on cane productivity are varies within different seasons. Average maximum temperature in summer and average minimum temperature in rainy season have a negative and statistically significant effect on sugarcane productivity. While, sugarcane productivity positively get affect with increasing average maximum temperature in rainy season and winter seasons. The study concluded that there is non-linear relationship between climatic factors and sugarcane productivity in India.

Sign in / Sign up

Export Citation Format

Share Document