scholarly journals Desert Locust in India: The 2020 invasion and associated risks

2020 ◽  
Author(s):  
Sayantan Ghosh ◽  
arindam roy
Keyword(s):  
Wind Direction ◽  
Desert Locust ◽  
Breeding Ground ◽  
Indian States ◽  
Kharif Season ◽  
Reverse Migration ◽  
Super Cyclone ◽  
Controlling Measures ◽  
Local Ecology

Wind direction, often used in forecasting locust migration, indicates a non-zero probability of desert locust invasion in eastern Indian states. Apart from present controlling measures, we are additionally suggesting to be cautious about the eggs of locust as the rainfall associated with Super Cyclone Amphan has created a favorable breeding ground for the gregarious locust. Also reverse migration of these locusts might affect the Indian states for the second time. Long-term controlling policy (till Kharif season; June to October) is required to minimize the damage. Also, increasing the farmers awareness and sensitized local ecology groups might be helpful in desert locust reporting.

scholarly journals Simultaneous generalized and low-layer SCIDAR turbulence profiles at san pedro mártir observatory

2019 ◽  
Vol 490 (1) ◽  
pp. 1397-1405 ◽  
Author(s):  
R Avila ◽  
O Valdés-Hernández ◽  
L J Sánchez ◽  
I Cruz-González ◽  
J L Avilés ◽  
...  
Keyword(s):  
High Altitude ◽  
Wind Direction ◽  
Close Agreement ◽  
Baja California ◽  
Ground Level ◽  
Combined Effect ◽  
Moderate Altitude ◽  
San Pedro ◽  
Simultaneous Measurements

ABSTRACT We present optical turbulence profiles obtained with a Generalized SCIDAR (G-SCIDAR) and a low-layer SCIDAR (LOLAS) at the Observatorio Astronómico Nacional in San Pedro Mártir (OAN-SPM), Baja California, Mexico, during three observing campaigns in 2013, 2014, and 2015. The G-SCIDAR delivers profiles with moderate altitude-resolution (a few hundred metres) along the entire turbulent section of the atmosphere, while the LOLAS gives high altitude resolution (on the order of tens of metres) but only within the first few hundred metres. Simultaneous measurements were obtained on 2014 and allowed us to characterize in detail the combined effect of the local orography and wind direction on the turbulence distribution close to the ground. At the beginning of several nights, the LOLAS profiles show that turbulence peaks between 25 and 50 m above the ground, not at ground level as was expected. The G-SCIDAR profiles exhibit a peak within the first kilometre. In 55 per cent and 36 per cent of the nights stable layers are detected between 10 and 15 km and at 3 km, respectively. This distribution is consistent with the results obtained with a G-SCIDAR in 1997 and 2000 observing campaigns. Statistics computed with the 7891 profiles that have been measured at the OAN-SPM with a G-SCIDAR in 1997, 2000, 2014, and 2015 campaigns are presented. The seeing values calculated with each of those profiles have a median of 0.79, first and third quartiles of 0.51 and 1.08 arcsec, which are in close agreement with other long term seeing monitoring performed at the OAN-SPM.

scholarly journals Using Long-Term Earth Observation Data to Reveal the Factors Contributing to the Early 2020 Desert Locust Upsurge and the Resulting Vegetation Loss

2021 ◽  
Vol 13 (4) ◽  
pp. 680
Author(s):  
Lei Wang ◽  
Wen Zhuo ◽  
Zhifang Pei ◽  
Xingyuan Tong ◽  
Wei Han ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Arabian Peninsula ◽  
Vegetation Coverage ◽  
Observation Data ◽  
Desert Locust ◽  
Meteorological Observations ◽  
Earth Observation Data ◽  
Vegetation Loss

Massive desert locust swarms have been threatening and devouring natural vegetation and agricultural crops in East Africa and West Asia since 2019, and the event developed into a rare and globally concerning locust upsurge in early 2020. The breeding, maturation, concentration and migration of locusts rely on appropriate environmental factors, mainly precipitation, temperature, vegetation coverage and land-surface soil moisture. Remotely sensed images and long-term meteorological observations across the desert locust invasion area were analyzed to explore the complex drivers, vegetation losses and growing trends during the locust upsurge in this study. The results revealed that (1) the intense precipitation events in the Arabian Peninsula during 2018 provided suitable soil moisture and lush vegetation, thus promoting locust breeding, multiplication and gregarization; (2) the regions affected by the heavy rainfall in 2019 shifted from the Arabian Peninsula to West Asia and Northeast Africa, thus driving the vast locust swarms migrating into those regions and causing enormous vegetation loss; (3) the soil moisture and NDVI anomalies corresponded well with the locust swarm movements; and (4) there was a low chance the eastwardly migrating locust swarms would fly into the Indochina Peninsula and Southwest China.

The transition of a socio-technical system to a smart grid: illustrated with the Indian electricity network

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lakshminarayana Kompella
Keyword(s):  
Technical System ◽  
Transition Theory ◽  
Short Term ◽  
Indian States ◽  
Content Type ◽  
External Pressures ◽  
Policy Systems ◽  
Transition Trajectory ◽  
Practical Implications

Purpose This paper aims to explain transitions in a socio-technical system characterized by non-economic entities that influence economic activity, i.e. embeddedness and coalitions. The selected socio-technical system is an Indian electric network with an interventionist policy. Its embeddedness and coalitions drive the transition. The insights from such analysis expand socio-technical transition theory and provide valuable insights to practitioners in their policymaking. Design/methodology/approach The authors need to observe the effects of non-economic institutions in their setting. Moreover, in India, the regional policies influence decision-making; therefore, selected two Indian states. The two Indian states, along with their non-economic entities, provided diverse analytic and heuristic views. Findings The findings show that coalitions, with their embeddedness in the absence of any mediating policy systems, act as external pressures and influence innovation and the socio-technical system’s transition trajectory. Their coalitions’ embeddedness follows a shaping, not selection logic. Thereby influence innovations in cumulating as stable designs. Such an approach provides benefits in the short-term but not in the long-term. Research limitations/implications The study selected two states and examined two of the four trajectories. By considering other states, the authors can obtain more renewable energy investments and further insights into the transformational trajectory. Practical implications The study highlights the coalition dynamics specific to the Indian electric power network and its transition trajectories. The non-economic entities influenced transition trajectories, innovation and policymaking of the socio-technical system. Originality/value The study expands the socio-technical transition theory by including embeddedness. The embeddedness brings a shaping logic instead of a selection logic.

scholarly journals Hydrodynamics of a small trained tidal inlet (Currumbin Creek, Australia)

2014 ◽  
Vol 39 ◽  
pp. 45-53 ◽  
Author(s):  
S. Shaeri ◽  
R. B. Tomlinson ◽  
A. Etemad-Shahidi ◽  
D. Strauss ◽  
L. P. Hughes
Keyword(s):  
Marginal Effect ◽  
Beach Profile ◽  
Physical Processes ◽  
Inlet Channel ◽  
Tidal Variation ◽  
Bathymetric Survey ◽  
Term Evolution ◽  
Nearshore Waves ◽  
Local Ecology

Abstract. Small tidal inlets are important features of coastal areas, in terms of provision of access from a back barrier water-body to the ocean as well as periodic circulation of fresh nutrients for the local ecology. Usually, dimensional and geometrical characteristics contribute significantly to morphological stability or instability of a particular inlet and necessitate an individual investigation of any desired location. In other words, generalized usage of previous empirical and experimental research of a different position can hardly be used for other places. In this regard, one of the powerful tools to understand the physical processes of a particular region is to collect as much field data as possible. Such a dataset is used to further analyse and explore the governing processes and can also be used for building a numerical computer model for supplementary studies. In this research, the results of a comprehensive field measurement at Currumbin Creek, Queensland, Australia are presented. This study is part of broader research to investigate the long term evolution of the Currumbin entrance and its adjacent beaches. Currently, an annual dredging campaign is needed to reduce the risk of flooding due to excess rainfall inundations and to maintain water quality. The majority of data were collected over a three month period consistent with the time of the 2012 dredging operation. However, due to the loss of some instrumentation, data collection for some of the parameters was repeated till the middle of May 2013. All collected data included: (1) nearshore waves and tide; (2) creek tidal variation; (3) creek flow discharge and velocity; (4) bathymetric survey of the creek; (5) beach profile evolution survey; and (6) sediment sampling. The measurement showed that the creek entrance is tidally dominated, with flood events having a major role in sediment transport into the creek. The nearshore stations' wave data illustrated the marginal effect of the beach curvature between updrift and downdrift stations. Thus, the historical dataset available from the updrift wave rider buoy will be selected to be used for future numerical modelling. Although changes of some beach profiles were comparatively insignificant, the dramatic changes of the profile lines nearby the inlet channel and also rapid bathymetric change of the flood shoal following the dredging completion are valuable information to better calibrate and interpret a local sediment modelling study for the next phase. Essentially, this evaluation needs to be considered for proposing any alternative maintenance activities.

A model to predict the incubation and nymphal development periods of the desert locust, Schistocerca gregaria (Orthoptera: Acrididae)

1992 ◽  
Vol 82 (4) ◽  
pp. 517-520 ◽  
Author(s):  
J.A.W.A. Reus ◽  
P.M. Symmons
Keyword(s):  
Computer Program ◽  
Schistocerca Gregaria ◽  
Development Stage ◽  
Desert Locust ◽  
Nymphal Development ◽  
Mean Temperature ◽  
Weather Stations

AbstractA model has been developed which estimates the egg and nymphal development periods of the desert locust Schistocerca gregaria (Forskål). The model uses long-term monthly mean temperatures from a number of weather stations in the desert locust area. The computer program calculates the daily mean temperature and the daily related amount of development. It then accumulates the percentage of development estimated on successive days until the total reaches or exceeds 100. The model can be started on any day of the year at any given development stage and it can calculate development backwards in time as well as forwards. The model should be a useful aid in forecasting desert locust population developments and for the planning of surveys.

A novel framework for owner driven reconstruction projects to enhance disaster resilience in the long term

2018 ◽  
Vol 27 (4) ◽  
pp. 421-446 ◽  
Author(s):  
Mittul Vahanvati
Keyword(s):  
Visual Analysis ◽  
Case Study Research ◽  
Comparative Case Study ◽  
Disaster Resilience ◽  
Construction Technology ◽  
Structured Interviews ◽  
Indian States ◽  
Content Type

Purpose Post-disaster reconstruction poses a double-edged sword to its implementers as it demands addressing survivors’ need for speed as well as meeting the growing expectation to trigger resilience. While an owner-driven housing reconstruction (ODHR), inter-disciplinary and long-term approach has been promoted internationally; however, there is limited research focussed on the long-term impacts (>10 years after a disaster) of ODHR. Furthermore, there is no one accepted framework for practitioners to guide through the process of ODHR projects to carve pathways for disaster resilience. The purpose of this paper is to assimilate findings—contingent and generalisable—into a novel framework for future change in practice. Design/methodology/approach This paper deployed a mixed methods methodology with a comparative case study research method. Two case study projects were from the Indian state of Gujarat, 13 years after the 2001 earthquake and the other two from Bihar, 6 years since the 2008 Kosi river floods. Due to multi-disciplinary nature of research, empirical data collection relied on a mix of social sciences methods including 80 semi-structured interviews, and architectural research methods including the visual analysis of photographs and sketches. Three sample groups of agency members, beneficiaries and non-beneficiaries were purposively selected. Thematic content analysis was used for the data analysis. Findings The paper provides empirical insights on how ODHR projects in Indian states of Gujarat and Bihar succeeded at enhancing disaster resilience of communities. It suggests that the civil society organisations acted as “enablers” at four stages: envisioning strategically based on systemic understanding, building soft assets including community trust and dignity for social mobilisation prior to, proposing minor modifications to construction technology for its multi-hazard safety as well as cultural relevance, and sustaining capacity building efforts beyond reconstruction completion or beyond one project life-cycle. Research limitations/implications The author of this paper cautions that the spiral framework needs further development to make it flexibility and customisable to suit the specifics of a particular context. Originality/value The implications of the findings discussed in this paper are primarily for practitioners involved in disaster recovery and development sector. Since prevailing models or frameworks neither incorporate multi-disciplinary approach (demanded by socio-ecological systems resilience concept), nor represent project scale, a novel, four-pronged framework for ODHR has been proposed in this paper for strategic success. The framework has been illustrated in spiral and tabular forms, and has been kept abstract to provide practitioners the much-needed flexibility for adapting it to suit the specifics of a particular context.

scholarly journals The Importance of Climate Variability to Wind-Driven Modulation of Hypoxia in Chesapeake Bay

2010 ◽  
Vol 40 (6) ◽  
pp. 1435-1440 ◽  
Author(s):  
Malcolm E. Scully
Keyword(s):  
Time Series ◽  
Climate Variability ◽  
Chesapeake Bay ◽  
Wind Direction ◽  
Large Scale ◽  
Nitrogen Loading ◽  
Nutrient Inputs ◽  
Westerly Direction ◽  
Hypoxic Volume

Abstract Extensive hypoxia remains a problem in Chesapeake Bay, despite some reductions in estimated nutrient inputs. An analysis of a 58-yr time series of summer hypoxia reveals that a significant fraction of the interannual variability observed in Chesapeake Bay is correlated to changes in summertime wind direction that are the result of large-scale climate variability. Beginning around 1980, the surface pressure associated with the summer Bermuda high has weakened, favoring winds from a more westerly direction, the direction most correlated with observed hypoxia. Regression analysis suggests that the long-term increase in hypoxic volume observed in this dataset is only accounted for when both changes in wind direction and nitrogen loading are considered.

scholarly journals Network-based Modeling of COVID-19 Dynamics: Early Pandemic Spread in India

2021 ◽  
Author(s):  
Rupam Bhattacharyya ◽  
Sayantan Banerjee ◽  
Shariq Mohammed ◽  
Veerabhadran Baladandayuthapani
Keyword(s):  
Hot Spots ◽  
Direct Interaction ◽  
Mitigation Strategies ◽  
Epidemiological Models ◽  
Model Framework ◽  
Indian States ◽  
Individual Level ◽  
Level Data ◽  
Multiple Scenarios

Modeling the dynamics of COVID-19 pandemic spread is a challenging and relevant problem. Established models for the epidemic spread such as compartmental epidemiological models e.g. Susceptible-Infected-Recovered (SIR) models and its variants, have been discussed extensively in the literature and utilized to forecast the growth of the pandemic across different hot-spots in the world. The standard formulations of SIR models rely upon summary-level data, which may not be able to fully capture the complete dynamics of the pandemic growth. Since the disease spreads from carriers to susceptible individuals via some form of contact, it inherently relies upon a network of individuals for its growth, with edges established via direct interaction, such as shared physical proximity. Using individual-level COVID-19 data from the early days (January 30 to April 15, 2020) of the pandemic in India, and under a network-based SIR model framework, we performed state-specific forecasting under multiple scenarios characterized by the basic reproduction number of COVID-19 across 34 Indian states and union territories. We validated our short-term projections using observed case counts and the long-term projections using national sero-survey findings. Based on healthcare availability data, we also performed projections to assess the burdens on the infrastructure along the spectrum of the pandemic growth. We have developed an \href{https://bayesrx.shinyapps.io/COV-N/}{interactive dashboard} summarizing our results. Our predictions successfully identified the initial hot-spots of India such as Maharashtra and Delhi, and those that emerged later, such as Madhya Pradesh and Kerala. These models have the potential to inform appropriate policies for isolation and mitigation strategies to contain the pandemic, through a phased approach by appropriate resource prioritization and allocation.

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