scholarly journals Delineation of maize growing areas vis-à-vis climate and technology using statistical and geospatial techniques in Punjab

2021 ◽  
Vol 23 (1) ◽  
pp. 93-99
Author(s):  
GURPREET KAUR ◽  
SOM PAL SINGH ◽  
R.K. SETIA ◽  
P.K. KINGRA

In the present investigation, maize growing areas in Punjab were delineated with respect toclimate and technology variables using statistical and geospatial techniques. The effect of the climate(maximum temperature, minimum temperature and rainfall) and technology variables (fertilizers, irrigation)on maize yield was studied in spatio-temporal domain in maize growing areas of Punjab. Long-termdata on climate and technology variables as well as maize productivity was collected for maize growingdistricts of the state. The maximum temperature during maize growing season was highest (35.7°C) inAmritsar, the minimum temperature was highest (25.3°C) in Ludhiana, whereas rainfall was highest (765.4 mm) in Gurdaspur. The results of Mann-Kendall test showed significant increase in maximum temperature @ 0.03°C year-1 in Hoshiarpur, Kapurthala, Patiala and Roopnagar and minimum temperature @ 0.04°C year-1in Gurdaspur, Hoshiarpur, Kapurthala and Roopnagar, @ 0.03°C year-1 in Jalandhar and @ 0.05°C year-1 in Ludhiana and Patiala districts. Analysis indicated that the maize yield was significantly higher in Ludhiana than other districts. Spatial variability in maize yield, climate and technology was studied using Geographic Information System (GIS). The integration of the layers of climate parameters with yield in GIS demarcated four major maize growing zones in Punjab.

Author(s):  
Rongxiang Rui ◽  
Maozai Tian ◽  
Man-Lai Tang ◽  
George To-Sum Ho ◽  
Chun-Ho Wu

With the rapid spread of the pandemic due to the coronavirus disease 2019 (COVID-19), the virus has already led to considerable mortality and morbidity worldwide, as well as having a severe impact on economic development. In this article, we analyze the state-level correlation between COVID-19 risk and weather/climate factors in the USA. For this purpose, we consider a spatio-temporal multivariate time series model under a hierarchical framework, which is especially suitable for envisioning the virus transmission tendency across a geographic area over time. Briefly, our model decomposes the COVID-19 risk into: (i) an autoregressive component that describes the within-state COVID-19 risk effect; (ii) a spatiotemporal component that describes the across-state COVID-19 risk effect; (iii) an exogenous component that includes other factors (e.g., weather/climate) that could envision future epidemic development risk; and (iv) an endemic component that captures the function of time and other predictors mainly for individual states. Our results indicate that maximum temperature, minimum temperature, humidity, the percentage of cloud coverage, and the columnar density of total atmospheric ozone have a strong association with the COVID-19 pandemic in many states. In particular, the maximum temperature, minimum temperature, and the columnar density of total atmospheric ozone demonstrate statistically significant associations with the tendency of COVID-19 spreading in almost all states. Furthermore, our results from transmission tendency analysis suggest that the community-level transmission has been relatively mitigated in the USA, and the daily confirmed cases within a state are predominated by the earlier daily confirmed cases within that state compared to other factors, which implies that states such as Texas, California, and Florida with a large number of confirmed cases still need strategies like stay-at-home orders to prevent another outbreak.


Author(s):  
S.S. Mote ◽  
D.S. Chauhan* and Nilotpal Ghosh1

The study was undertaken to evaluate the effect of different macro climatic variables on lactation milk yield and lactation length of Holdeo (Holstein Friesian x Deoni) crossbred cattle. Milk data of 145 Holdeo crossbred cows with 619 lactation records and the meteorological data over a period of 15 years (1995-2009) were obtained from Cattle Cross Breeding Project, Vasantrao Naik Marathwada Krishi Vidyapeeth, Parbhani and University Meteorological Observatory, respectively. It was observed that maximum temperature has significant correlation with lactation milk yield; whereas maximum temperature, minimum temperature, sunshine hours and wind speed have significant correlation with lactation length. Regression analysis indicated that all the climatic variables except minimum temperature exhibited significant regression results with lactation milk yield, and maximum temperature, minimum temperature and maximum humidity have significant regression results with lactation length. All the climatic variables considered in the study accounted for 75 % and 65 % direct variation on lactation milk yield and lactation length, respectively, as verified by the value of coefficient of determination (R2). It was observed that lactation milk yield (1136.56 + 21.04 kg.) and lactation length (295.29 + 5.51 days) were highest among the cows calved during winter season as compared to rainy and summer season. All the climatic variables considered in the study accounted for 57% , 56 % and 48 % direct variation on milk yield and 68% , 53 % and 46 % direct variation on lactation length in rainy, winter and summer season, respectively, as verified by the value of coefficient of determination (R2). This research indicated that crossbred cows were sensitive to seasonal changes on their lactation performance. The optimum ranges of temperature; humidity and THI for better performance of crossbred in subtropical region of India were found to be 19-26 oC, 52-66 % and 65-68 %, respectively.


Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 1090 ◽  
Author(s):  
Saima Nauman ◽  
Zed Zulkafli ◽  
Abdul Halim Bin Ghazali ◽  
Badronnisa Yusuf

The study aims to evaluate the long-term changes in meteorological parameters and to quantify their impacts on water resources of the Haro River watershed located on the upstream side of Khanpur Dam in Pakistan. The climate data was obtained from the NASA Earth Exchange Global Daily Downscaled Projection (NEX-GDDP) for MIROC-ESM model under two Representative Concentration Pathway (RCP) scenarios. The model data was bias corrected and the performance of the bias correction was assessed statistically. Soil and Water Assessment Tool was used for the hydrological simulation of watershed followed by model calibration using Sequential Uncertainty Fitting version-2. The study is useful for devising strategies for future management of Khanpur Dam. The study indicated that in the future, at Murree station (P-1), the maximum temperature, minimum temperature and precipitation were anticipated to increase from 3.1 °C (RCP 4.5) to 4.0 °C (RCP 8.5), 3.2 °C (RCP 4.5) to 4.3 °C (RCP 8.5) and 8.6% to 13.5% respectively, in comparison to the baseline period. Similarly, at Islamabad station (P-2), the maximum temperature, minimum temperature and precipitation were projected to increase from 3.3 °C (RCP 4.5) to 4.1 °C (RCP 8.5), 3.3 °C (RCP 4.5) to 4.2 °C (RCP 8.5) and 14.0% to 21.2% respectively compared to baseline period. The streamflows at Haro River basin were expected to rise from 8.7 m3/s to 9.3 m3/s.


Author(s):  
Elizangela Selma da Silva ◽  
José Holanda Campelo Júnior ◽  
Francisco De Almeida Lobo ◽  
Ricardo Santos Silva Amorim

The homogeneity investigation of a series can be performed through several nonparametric statistical tests, which serve to detect artificial changes or non-homogeneities in climatic variables. The objective of this work was to evaluate two methodologies to verify the homogeneity of the historical climatological series of precipitation and temperature in Mato Grosso state. The series homogeneity evaluation was performed using the following non-parametric tests: Wald-Wolfowitz (for series with one or no interruption), Kruskal-Wallis (for series with two or more interruptions), and Mann-Kendall (for time series trend analysis). The results of the precipitation series homogeneity analysis from the National Waters Agency stations, analyzed by the Kruskal-Wallis and Wald-Wolfowitz tests, presented 61.54% of homogeneous stations, being well distributed throughout Mato Grosso state, whereas those of the trend analysis allowed to identify that 87.57% of the rainfall-gauging stations showed a concentrated positive trend, mainly in the rainy season. Out of the conventional stations of the National Institute of Meteorology of Mato Grosso, seven were homogeneous for the precipitation variable, five for maximum temperature and four stations were homogeneous for minimum temperature. For the trend analysis in the 11 stations, positive trends of random nature were observed, suggesting increasing alterations in the analyzed variables. Therefore, the trend analysis performed by the Mann-Kendall test in the precipitation, and maximum and minimum temperature climate series, indicated that several data series showed increasing trends, suggesting a possible increase in precipitation and temperature values over the years. The results of the Kruskal-Wallis and Wald-Wolfowitz tests for homogeneity presented more than 87% of homogeneous stations.


Author(s):  
S. S. Mote ◽  
D. S. Chauhan ◽  
Nilotpal Ghosh

The study was undertaken to evaluate the effect of different macro climatic variables on lactation milk yield and lactation length of Holdeo (Holstein Friesian x Deoni) crossbred cattle. Milk data of 145 Holdeo crossbred cows with 619 lactation records and the meteorological data over a period of 15 years (1995-2009) were obtained from Cattle Cross Breeding Project, Vasantrao Naik Marathwada Krishi Vidyapeeth, Parbhani and University Meteorological Observatory, respectively. It was observed that maximum temperature has significant correlation with lactation milk yield; whereas maximum temperature, minimum temperature, sunshine hours and wind speed have significant correlation with lactation length. Regression analysis indicated that all the climatic variables except minimum temperature exhibited significant regression results with lactation milk yield, and maximum temperature, minimum temperature and maximum humidity have significant regression results with lactation length. All the climatic variables considered in the study accounted for 75 % and 65 % direct variation on lactation milk yield and lactation length, respectively, as verified by the value of coefficient of determination (R2). It was observed that lactation milk yield (1136.56 + 21.04 kg.) and lactation length (295.29 + 5.51 days) were highest among the cows calved during winter season as compared to rainy and summer season. All the climatic variables considered in the study accounted for 57% , 56 % and 48 % direct variation on milk yield and 68% , 53 % and 46 % direct variation on lactation length in rainy, winter and summer season, respectively, as verified by the value of coefficient of determination (R2). This research indicated that crossbred cows were sensitive to seasonal changes on their lactation performance. The optimum ranges of temperature; humidity and THI for better performance of crossbred in subtropical region of India were found to be 19-26 oC, 52-66 % and 65-68 %, respectively.


2020 ◽  
Author(s):  
Balasubramani Karuppusamy ◽  
Devojit Kumar Sarma ◽  
Pachuau Lalmalsawma ◽  
Lalfakzuala Pautu ◽  
Krishanpal Karmodiya ◽  
...  

Abstract Background Malaria and dengue are the two major vector-borne diseases in Mizoram. Malaria is endemic in Mizoram, and dengue was first reported only in 2012. It is well documented that climate change has a direct influence on the incidence and spread of vector-borne diseases. The study was designed to study the trends and impact of climate variables (temperature, rainfall and humidity) in the monsoon period (May to September) and deforestation on the incidence of dengue and malaria in Mizoram. Methods Temperature, rainfall and humidity data of Mizoram from 1979–2013 were obtained from the National Centers for Environmental Prediction Climate Forecast System Reanalysis and analyzed. Forest cover data of Mizoram was extracted from India State of Forest Report (IFSR) and Land Processes Distributed Active Archive Centre. Percent tree cover datasets of Advanced Very High Resolution Radiometer and Moderate Resolution Imaging Spectroradiometer missions were also used to study the association between deforestation and incidence of vector-borne diseases. The study used non-parametric tests to estimate long-term trends in the climate (temperature, rainfall, humidity) and forest cover variables. The trend and its magnitude are estimated through Mann-Kendall test and Sen's slope method. Year-wise dengue and malaria data were obtained from the State Vector Borne Disease Control Program, Mizoram. Results The Mann-Kendall test indicates that compared to maximum temperature, minimum temperature during the monsoon period is increasing (p < 0.001). The Sen’s slope estimation also shows an average annual 0.020C (0.01–0.03 at 95% CI) monotonic increasing trend of minimum temperature. The residuals of Sen’s estimate show that temperature is increasing at an average of about 0.10C/year after 2007.Trends indicate that both rainfall and humidity are increasing (p <. 0.001); on an average, there is a 20.45 mm increase in monsoon rainfall per year (5.90–34.37 at 95% CI), while there is a 0.08% (0.02–0.18 at 95% CI) increase in relative humidity annually. IFSR data shows that there is an annual average decrease of 162 sq.km (272.81–37.53 at 95% CI, p < 0.001) in the dense forest cover. Mizoram in 2012 was the last state in India to report the incidence of dengue. Malaria transmission continues to be stable in Mizoram; compared to 2007, the cases have increased in 2019. Conclusion Over the study period, there is an ~ 0.80C rise in the minimum temperature in the monsoon season which could have facilitated the establishment of Aedes aegypti, the major dengue vector in Mizoram. In addition, the increase in rainfall and humidity may have also helped the biology of Ae. aegypti. Deforestation could be one of the major factors responsible for the consistently high number of malaria cases in Mizoram.


2019 ◽  
Vol 11 (4) ◽  
pp. 1339-1354 ◽  
Author(s):  
O. E. Adeyeri ◽  
P. Laux ◽  
A. E. Lawin ◽  
S. O. Ige ◽  
H. Kunstmann

Abstract Spatiotemporal trends in daily observed precipitation, river discharge, maximum and minimum temperature data were investigated between 1971 and 2013 in the Komadugu-Yobe basin. Significant change points in time series are corrected using Adapted Caussinus-Mestre Algorithm for homogenizing Networks of Temperature series algorithm. Mann–Kendall test and Sen's slope are used to estimate the trend and its magnitude at dry, wet and annual season time scales, respectively. Preliminary results show an increasing trend of the observed variables. There is a latitudinal increase (decrease) in the basin temperature (precipitation) from lower to higher latitudes. The minimum temperature (0.05 °C/year) increases faster than the maximum temperature (0.03 °C/year). Overall, the percentage changes in minimum temperature range between 3 and 10% while that of maximum temperature ranges between 1 and 3%. Due to precipitation dependence on regional characteristics, the highest percentage change was recorded in precipitation with values between −5 and 97%. In all time scales, river discharge and precipitation have strong positive correlations while the correlation between river discharge and temperature is negative. It is imperative to advocate and support positive developmental practices as well as establishing necessary mitigation measures to cope with the effects of climate in the basin.


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