Assessing the influence of watershed characteristics on the flood vulnerability of Jhelum basin in Kashmir Himalaya: reply to comment by Shah 2015

Meraj, Gowhar; Romshoo, Shakil Ahmad; Yousuf, A. R.; Altaf, Sadaff; Altaf, Farrukh

doi:10.1007/s11069-015-1861-0

Cited by 28 publications

(16 citation statements)

References 24 publications

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“…Addressing the issue of the implementation of restricting the virus spread, requires de ning the risk zones according to the nest scale of administrative coverage. COVID-19 risk assessment and mapping (labeled hereafter as CRAM) framework, as proposed here, involves the mapping of the risk, using its de ned hazard and vulnerability components, for informed decision making to declare red, orange, blue, and green zones of containment [12][13] . We used proximity to hotspots and settlements as the hazard components because the pandemic spread is directly proportional to the distance from the hotspot and density of settlements.…”

Section: Introductionmentioning

confidence: 99%

Risk assessment to curb COVID-19 contagion: A preliminary study using remote sensing and GIS

Kanga

Meraj²,

Sudhanshu

et al. 2020

Preprint

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Globally, COVID-19 pandemic has become a threat to humans and to the socio-economic systems they have developed since the industrial revolution. Hence, governments and stakeholders are calling for strategies that could help to restore the normalcy while dealing with this pandemic effectively. Since, till now, the disease is yet to have a cure; therefore, only risk-based decision-making can help governments to achieve a solution that is sustainable in the long term. To help the decision-makers to explore viable actions, we here propose a risk assessment framework for analyzing COVID-19 risk to areas, using integrated hazard and vulnerability components associated with this pandemic for effective risk mitigation. The study is carried on a region administrated by Jaipur municipal corporation (JMC), India. Based on the current understanding of this disease, we hypothesized different COVID-19 risk indices (C19Ri) of the wards of JMC such as proximity to hotspots, total population, population density, availability of clean water and associated land use/ land cover, are related with COVID-19 contagion and calculated them in a GIS-based multi-criteria risk reduction method. The results showed disparateness in COVID-19 risk areas with higher risk in north-eastern and south-eastern zone wards within the boundary of JMC. We proposed to prioritize wards that are under higher risk zones for intelligent decision-making regarding COVID-19 risk reduction through appropriate management of resources-related policy consequences. This study aims to serve as a baseline study to be replicated in other parts of the country or world to eradicate the threat of COVID-19 effectively.

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Section: Introductionmentioning

confidence: 99%

Risk assessment to curb COVID-19 contagion: A preliminary study using remote sensing and GIS

Kanga

Meraj²,

Sudhanshu

et al. 2020

Preprint

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“…Having an average altitude of 1545 m, the temperature of the valley varies from -9 °C in winter months to 38 °C in summer months. The mean maximum and minimum temperatures of the Kashmir valley are 19.27 and 7.29 °C, respectively (Meraj et al 2015;Gujree et al 2017). Mumbai has a wet and dry, tropical climate which is moderately hot and signi cantly humid.…”

Section: Introductionmentioning

confidence: 99%

Coronavirus Pandemic vs. Temperature in the context of Indian Subcontinent – A preliminary statistical analysis

Meraj¹,

Farooq²,

Singh

et al. 2020

Preprint

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The novel coronavirus (COVID-19) has unleashed havoc across different countries and was declared a pandemic by the World Health Organization. Since certain evidences indicate a direct relationship of various viruses with the weather (temperature in particular), the same is being speculated about COVID-19; however, it is still under investigation as the pandemic is advancing the world over. In this study, we tried to analyze the spread of COVID-19 in the Indian sub-continent with respect to the local temperature regimes from 9 March, 2020, to 27 May, 2020. To establish the relation between COVID-19 and temperature in India, three different eco-geographical regions having significant temperature differences were taken into consideration for the analysis. We observed that except Maharashtra, Rajasthan and Kashmir showed a significantly positive correlation between the number of COVID-19 cases and the temperature during the period of study. The evidences based on the results presented in this research lead us to believe that the increasing temperature is beneficial to the COVID-19 spread, and the cases are going to rise further with the increasing temperature over India. We, therefore, conclude that the existing data, though limited, suggests that the spread of COVID-19 in India is not explained by the variation of temperature alone and is most likely driven by a host of other factors related to epidemiology, socio-economics and other climatic factors. Based on the results, it is suggested that temperature should not be considered as a yardstick for planning intervention strategies for controlling the COVID-19 pandemic.

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“…Since 2014, the flooding threats in this region have been a recurring phenomenon every year [2]. The magnitude of this event crossed all bounds of the recorded history of floods in the region, not only in terms of discharge, but also in terms of loss of life and property [3][4][5][6]. The event has generated a scientific consensus for an alarming need of a robust flood mitigation strategy for the Kashmir region.…”

Section: Introductionmentioning

confidence: 99%

“…Further, such a setup would also help in assessing the comparative basin lag times of the Jhelum watersheds, thus helping in prioritizing the watersheds for the construction of hydraulic structures that could help in extending the peak concentration, so that rapid concentrations of water in the Jhelum river that result in a huge wave of water to promulgate, as has been witnessed in the September 2014 floods, are delayed [3]. The third important step is the vulnerability assessment of the Jhelum basin, so that a final plan is drafted where people can be desisted from building structures in the flood prone areas or those who are already living in them could be resettled in safer zones [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

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An Integrated Geoinformatics and Hydrological Modelling-Based Approach for Effective Flood Management in the Jhelum Basin, NW Himalaya

Meraj¹,

Khan

Romshoo

et al. 2018

Ecws-3

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In the present study, using static land system parameters, such as geomorphology, land cover, and relief, we calculated the water yield potential (RP) of all the watersheds of the Jhelum basin (Kashmir Valley) using the analytical hierarchy process (AHP) based watershed evaluation model (AHP-WEM). The results revealed that among the 24 watersheds of the Jhelum basin, the Vishav watershed, with the highest RP, is the fastest water yielding catchment of the Jhelum basin followed by Bringi, Lidder, Kuthar, Sind, Madhumati, Rembiara, Sukhnag, Dal, Wular-II, Romshi, Sandran, Ferozpur, Viji-Dhakil, Ningal, Lower Jhelum, Pohru, Arin, Doodganga, Arapal, Anchar, Wular-I, Gundar, and Garzan in the case of a same intensity storm event. The results were validated with the mean annual peak discharge values of the watersheds and a strong positive correlation of 0.71 was found. Further, for the forecasting of the floods in the watersheds that had a small lag time, such as in the case of Vishaw, Bringi, and Lidder, we evaluated the performance of the HEC-GeoHMS hydrological model to simulate stream discharge during storm events. It was observed that the model performs well for August-September period with a strong positive correlation (0.94) between the observed and simulated discharge and hence could be used as a flood forecasting model for this period in the region.

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Assessing the influence of watershed characteristics on the flood vulnerability of Jhelum basin in Kashmir Himalaya: reply to comment by Shah 2015

Cited by 28 publications

References 24 publications

Risk assessment to curb COVID-19 contagion: A preliminary study using remote sensing and GIS

Risk assessment to curb COVID-19 contagion: A preliminary study using remote sensing and GIS

Coronavirus Pandemic vs. Temperature in the context of Indian Subcontinent – A preliminary statistical analysis

An Integrated Geoinformatics and Hydrological Modelling-Based Approach for Effective Flood Management in the Jhelum Basin, NW Himalaya

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