Climate change and water resources of Himalayan region—review of impacts and implication

Mir, Bintul Huda; Kumar, Rohitashw; Lone, M. A.; Tantray, Fayaz Ahmad

doi:10.1007/s12517-021-07438-z

Cited by 12 publications

(3 citation statements)

References 92 publications

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“…On the other hand, agricultural showed increase in area by 45.1 km 2 and 79.2 km 2 , and slight increase in water body by 11.46 km 2 and 12.56 km 2 in 2050 and 2080, respectively. The future projection portrays an increase in water bodies from 2000 to 2080, which is in contradiction to the observations ofMir et al (2021). They observed large spells of droughts and water scarcity for the future time period in the Himalayan river basins.…”

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confidence: 70%

Land use/land cover change projection of Tawi Catchment, Western Himalayas using Markov-CA

Jasrotia

Kour

Singh

et al. 2022

Preprint

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Land use/land cover has become a prime concern that urgently needs to be addressed in the study of global environmental change. In the present study, supported by the land use/land cover maps of the retrospective time periods 2000, 2010 and 2020, derived using Landsat TM and OLI datasets, respectively; we used the land-use transition matrix, Markov-CA chain model to derive detailed information of the spatio-temporal variation of the land use/land cover change. Additionally, we highlight decrease in forest land (19 km2 and 37.7 km2, i.e., 0.88% and 1.75% of the total area), rangeland (0.2 km2 and 1.9 km2, 0.01% and 0.09%), and perennial snow or ice (8 km2 and 9 km2, 0.37% and 0.42%); on the other hand, increase in agricultural land (19 km2 and 33.9 km2, 0.88% and 1.58%), urban or built-up land (4.44 km2 and 8.6 km2, 0.21% and 0.40%) and water (4.18 km2 and 6.28 km2, 0.19% and 0.29%), during 2010 and 2020 relative to baseline period 2000. Finally, based on the CA transition rules and the transition area matrix produced from the Markov-CA chain model based calibration process, the future land use/land cover maps were projected for 2050 and 2080.

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contrasting

confidence: 70%

Land use/land cover change projection of Tawi Catchment, Western Himalayas using Markov-CA

Jasrotia

Kour

Singh

et al. 2022

Preprint

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“…The impact of climate change on water quality are expected with regard to the linked process to simulate future climatewater quality scenarios. Moreover, the analysis of the impact of climate change has been developed from the GCM (Global Climate Model) and RCM (Regional Climate Model) on water quantity [218]. One of the impacts of climate change on water quality is the increase in cyanobacteria [219].…”

Section: Other Water Quality Related Aspectsmentioning

confidence: 99%

Surface Water Monitoring Systems—The Importance of Integrating Information Sources for Sustainable Watershed Management

2023

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The complex interactions from anthropogenic activities, climate change, sedimentation and the input of wastewater has significantly affected the aquatic environment and entire ecosystem. Over the years, the researchers have investigated water monitoring approaches in terms of traditional monitoring or even integrated systems to handle such an environmental assessment and predictions based on warning systems. However, research into the selection and optimisation of water monitoring systems by the combination of parallel approach in terms of sampling techniques, process analysis and results is limited. The research objectives of the present study are to evaluate the existing water monitoring systems based on the latest approach and then provide insights into factors affecting sensor implementation at sampling locations. Here we summarize the advancement and trends of various water monitoring systems as well as the suitability of sensor placement in the area by reviewing more than 300 papers published between 2011 and 2022. The research highlights the urgency of an integrative approach with regard to water monitoring systems including water quality model and water quantity model. A framework is proposed to incorporate all water monitoring approaches, sampling techniques, and predictive models to provide comprehensive information about environmental assessment. It was observed that the urgency of model-based approaches as verification and fusion of data assemble has the ability to improve the performances of the systems. Furthermore, integrated systems with the inclusion of a separate modeling approach through integrated -semi-mechanistic models, data science and artificial intelligence are recommended in the future. Overall, this study provides guidelines for achieving standardized water management by implementing integrated water monitoring systems INDEX TERMS infrastructure, integrated monitoring, water monitoring system, modelling, water quality

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“…Recent investigations specified significant trends in precipitation and temperature in the northwest Himalayan region (Bhutiyani et al 2010;Bharti et al 2016;Malik & Kumar 2020) and the neighbouring Himalayan regions (Archer & Fowler 2004;Khatiwada et al 2016). Mir et al (2021) reviewed different studies on the impact of climate change on the water resources in the Himalayas, reporting a consistent rise in air temperature, precipitation, and extreme climatic events. With the limited research and higher occurrences of extreme events, extreme event analysis has gained popularity in recent times in India and the Himalayan region.…”

Section: Introductionmentioning

confidence: 99%

Spatio-temporal trends in precipitation and temperature means/extremes in the Himalayan states of India

Manzoor

Ahanger

2022

Journal of Water and Climate Change

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Covering sixty years (1955–2016), this paper analyzed the spatio-temporal trends of daily annual and seasonal means of precipitation, temperature, and extreme climate indices. The long-term decadal change analysis was carried out in two timeframes for consecutive analysis periods of 1955–1985 and 1986–2016 to capture the relative regional variations. The trends were evaluated using the modified Mann-Kendall (MMK) and Sen's slope (SS) statistical tests. The pattern visualized on maps was assessed for regions and districts located in the four states of the Indian Himalayan Region. The results revealed significant increases in the annual mean precipitation (1.61 mm/year) and temperature (0.07°/year) in Uttarakhand, followed by Himachal Pradesh from 1986 to 2016. The seasonal monsoonal precipitation showed a significantly increasing trend in parts of Himachal Pradesh, followed by Uttarakhand. The maximum and minimum temperature values increased in all the states, increasing temperature extremes. Significant trends in climate indices were observed in the second period of analysis. A rise of 0.02 °C/year in temperature extremes was observed in Uttarakhand. There is a progressive rise in precipitation indices, specifically in Uttarakhand (0.49 mm/year), and a drop in cold extremes with an increase of hot events in most states. The spatio-temporal variations were driven by multiple dominant mechanisms like orography, anthropogenic activities, land-use changes, teleconnections, and the emission of greenhouse gases. This study highlights the influence of climate change in different divisions of the Himalayas.

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Climate change and water resources of Himalayan region—review of impacts and implication

Cited by 12 publications

References 92 publications

Land use/land cover change projection of Tawi Catchment, Western Himalayas using Markov-CA

Land use/land cover change projection of Tawi Catchment, Western Himalayas using Markov-CA

Surface Water Monitoring Systems—The Importance of Integrating Information Sources for Sustainable Watershed Management

Spatio-temporal trends in precipitation and temperature means/extremes in the Himalayan states of India

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