scholarly journals Temperature influence on leafhopper population and its potential distribution in predicting spread of chickpea stunt disease in India

2021 ◽  
Vol 42 (5) ◽  
pp. 1281-1288
Author(s):  
M.G. Reddy ◽  
◽  
G.P. Rao ◽  
P. Sinha ◽  
S.M. Shukla ◽  
...  
Keyword(s):  
Potential Distribution ◽  
Population Distribution ◽  
Agricultural Research ◽  
Indian Agricultural Research Institute ◽  
Geographical Area ◽  
Temporal Distribution ◽  
Disease Spread ◽  
Effect Of Temperature ◽  
Maximum Temperature ◽  
Spatio Temporal

Aim: To study the influence of temperature on leafhopper population for predicting potential distribution of chickpea stunt disease. Methodology: Leaf hopper population was sampled at weekly intervals from chickpea experimental plots at Indian Agricultural Research Institute, New Delhi, during Dec-May 2018-2019 and 2019-2020 by using yellow sticky trap. Effect of temperature on leafhopper population was fitted to a non-linear beta model and Briere model by utilizing cardinal temperature for leafhopper growth and reproduction. Daily minimum and maximum temperature data were collected from 146 geo referenced meteorological stations of important chickpea growing states of India. The cumulative temperature indices (MTI) as a measure of monthly leafhopper population was plotted using ArcGis10.0 software. Results: Temperature index estimated as a measure of leafhopper population based on the beta model potential leafhopper population distribution was predicted. Spatio-temporal pattern of vector population indicated that the entire country is favourable for leafhopper growth round the year, except the Northern parts of India during December to February. Interpretation: Since leafhoppers are the natural vectors of virus and phytoplasma pathogens associated with chickpea stunt disease, beta model based prediction of environmental suitability indicates leafhopper as the causative agent for the natural spread of disease in larger geographical area. Spatio-temporal distribution pattern would be useful in predicting the disease spread in different chickpea growing areas for evolving efficient management strategies.

scholarly journals Spatio-Temporal Distribution of Environmental Health Risk of Heavy Metals in Industrial Wastewater of China during 1999–2018

2021 ◽  
Vol 18 (11) ◽  
pp. 5920
Author(s):  
Ruru Han ◽  
Beihai Zhou ◽  
Huilun Chen
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Health Risk ◽  
Environmental Health ◽  
Industrial Wastewater ◽  
Population Distribution ◽  
Temporal Distribution ◽  
Life Years ◽  
Environmental Health Risk ◽  
Spatio Temporal

In recent decades, environmental health risk caused by heavy metals in industrial wastewater (EHR-IHM) has become a serious issue globally, especially for China. Given the spatial difference of heavy metal emissions, hydrogeography, population distribution, etc., it is essential to estimate China’s EHR-IHM from a high-resolution perspective. Based on the framework of USEtox, this study constructs an environmental health risk assessment method for heavy metals discharged from industrial wastewater by coupling the Pollutant Accumulation Model (PAM). This method also considers the process of heavy metal flows between upstream and downstream areas. Based on this constructed method, we investigate the spatio-temporal distribution of EHR-IHM of As, Cd, Cr(VI), Hg, and Pb in China from 1999 to 2018. Results showed that the EHR-IHM in China increased rapidly during 1999–2007 and decreased gradually during 2007–2018, with the highest Damage Level (DL) of 6.8 × 104 disability-adjusted life years (DALY). As and Cr(VI) were the major heavy metal pollutants, which induced 58.9–70.6% and 23.9–36.2% of the total EHR-IHM, respectively. Intake of aquatic products was the dominant exposure route, accounting for over 84.1% of national EHR-IHM, followed by drinking water intake, accounting for 9.5–15.8%. Regarding spatial distribution, the regions with high EHR-IHM are mainly distributed in the middle–lower reaches of the Yangtze River, southeast coastal cities, Bohai Rim, etc.

Snow Cover Dynamics and its Spatio-Temporal Distribution in the Central Higher Himalaya of India

2021 ◽  
Vol 14 (9) ◽  
pp. 15-22
Author(s):  
Masoom Reza ◽  
Ramesh Chandra Joshi
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
Geographical Area ◽  
Temporal Distribution ◽  
Melting Rate ◽  
Optical Data ◽  
Snow Cover Area ◽  
Central Himalayas ◽  
Spatio Temporal ◽  
The Impact

Retreating glaciers, changing timber line and decreasing accumulation of snow in the Himalaya are considered the indicators of climate change. In this study, an attempt is made to observe the snow cover change in the higher reaches of the Central Himalayas. Investigation of climate change through snow cover is very important to understand the impact and adaptation in an area. Landsat thematic and multi spectral optical data with a spatial resolution of 60m and 30m are considered for the estimation and extraction of snow cover. Total 3,369 Km2 snow cover area is lost since 1972 out of total geographical area i.e. 17,227 Km2. The accumulation of snow during winter is lower than the melting rate during summer. The current study identified the decrease of 19.6 % snow cover in 47 years since 1972 to 2019. Composite satellite imageries of September to December show that the major part of the study area covered with snow lies above 3600m. Overall observation indicates that in 47 years, permanent snow cover is decreasing in Central Himalayas.

scholarly journals Modelling the high-resolution dynamic exposure to flood in city-region

2018 ◽  
Author(s):  
Xuehong Zhu ◽  
Qiang Dai ◽  
Dawei Han ◽  
Lu Zhuo ◽  
Shaonan Zhu ◽  
...  
Keyword(s):  
Population Distribution ◽  
Temporal Distribution ◽  
Temporal Variations ◽  
Urban Flooding ◽  
City Region ◽  
Loss Assessment ◽  
Urban Flood ◽  
Flood Exposure ◽  
Spatio Temporal ◽  
Dynamic Exposure

Abstract. Urban flooding exposure is generally investigated with the assumption of stationary disasters and disaster-bearing bodies within an event, and thus cannot satisfy the increasingly elaborative modelling and management of urban flood. In this study, a comprehensive method was developed to simulate dynamic exposure to urban flooding considering residents’ travel behavior. First, a flood simulation was conducted using the LISFLOOD-FP model to predict the spatio-temporal distribution of flooding. Second, an agent-based model was used to simulate residents’ movements during the period of urban flooding. Finally, to study the evolution and patterns of urban flooding exposure, the exposure of population, roads, and buildings to urban flooding was simulated using Lishui, China as the case study. The results indicated evident spatio-temporal variations in urban flooding and population distribution. Additionally, the exposure increased with increasing rainfall and flooding severity. The urban area near the Oujiang River was the most severely flooded and indicated the largest amount of exposure of population, roads, and buildings. Furthermore, the impacts of flooding on roads were greater than those on population and on buildings. This study presents the first fully formulated method for dynamic urban flood exposure simulation at high spatio-temporal resolution. The results of this study can provide baseline data for determining urban flood disaster vulnerability, socioeconomic loss assessment, urban disaster risk management, and for establishing emergency response plans.

Nutrient economy through land configuration and residue management in a greengram (Phaseolus radiatus L.)-wheat (Triticum aestivum L.) cropping sequence with limited water supplies

2005 ◽  
Vol 52 (4) ◽  
pp. 369-379
Author(s):  
B. G. Shivakumar ◽  
B. N. Mishra ◽  
R. C. Gautam
Keyword(s):  
Grain Yield ◽  
Agricultural Research ◽  
Indian Agricultural Research Institute ◽  
Residual Effect ◽  
Residue Management ◽  
Phosphorus Fertilization ◽  
Significant Interaction Effect ◽  
Preceding Crop ◽  
Cropping Sequence ◽  
Phosphorus Application

A field experiment on a greengram-wheat cropping sequence was carried out under limited water supply conditions in 1997-98 and 1998-99 at the farm of the Indian Agricultural Research Institute, New Delhi. The greengram was sown either on flat beds or on broad beds 2 m in width, divided by furrows, with 0, 30 and 60 kg P2O5/ha. After the harvest of greengram pods, wheat was grown in the same plots, either with the greengram stover removed or with the stover incorporated along with 0, 40, 80 and 120 kg N/ha applied to wheat. The grain yield of greengram was higher when sown on broad beds with furrows compared to flat bed sowing, and the application of 30 or 60 kg P2O5/ha resulted in significantly higher grain yields compared to no phosphorus application. The combination of broad bed and furrows with phosphorus fertilization was found to be ideal for achieving higher productivity in greengram. The land configuration treatments had no impact on the productivity of wheat. The application of phosphorus to the preceding crop had a significant residual effect on the grain yield of wheat. The incorporation of greengram stover also significantly increased the grain yield of wheat. The increasing levels of N increased the grain yield of wheat significantly up to 80 kg/ha. The combination of greengram stover incorporation and 80 kg N/ha applied to wheat significantly increased the grain yield. Further, there was a significant interaction effect between the phosphorus applied to the preceding crop and N levels given to wheat on the grain yield of wheat.

Influence of Planting Density on Root Spatio-Temporal Distribution of Different Types of Maize under High-Yielding Cultivation Conditions

2013 ◽  
Vol 38 (7) ◽  
pp. 1286-1294 ◽  
Author(s):  
Zong-Xin LI ◽  
Yuan-Quan CHEN ◽  
Qing-Cheng WANG ◽  
Kai-Chang LIU ◽  
Wang-Sheng GAO ◽  
...  
Keyword(s):  
Temporal Distribution ◽  
Planting Density ◽  
Cultivation Conditions ◽  
Different Types ◽  
Spatio Temporal
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