A century scale hydro-climatic variability and associated risk in Subarnarekha river basin of India

Yaduvanshi, Aradhana; Sinha, Abhishek; Haldar, Kaushik

doi:10.1007/s40808-019-00580-4

Cited by 8 publications

(7 citation statements)

References 33 publications

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“…Their projections also anticipate an escalation in maximum and minimum temperatures within the basin, with a change ranging from −2.6 °C to 4.7 °C and −0.5 °C to 5.6 °C, respectively, for future timeframes spanning 2030, 2050, 2070, and 2080. Yaduvanshi et al [15] highlighted the basin's long-term vulnerability to Notably, there was significant growth in built-up areas at the expense of vegetation and agricultural land. In 2001, the main categories were vegetation, agriculture, and grassland, with few settlements.…”

Section: Spatio-temporal Assessment Of Rainfall and Temperaturementioning

confidence: 99%

Temporal Change Dynamics of the Hydrometeorological Conditions of Upper Subarnarekha River Basin (SRB) Using Geospatial Techniques

Tabassum,

Krishna

2023

Ecrs 2023

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Section: Spatio-temporal Assessment Of Rainfall and Temperaturementioning

confidence: 99%

Temporal Change Dynamics of the Hydrometeorological Conditions of Upper Subarnarekha River Basin (SRB) Using Geospatial Techniques

Tabassum,

Krishna

2023

Ecrs 2023

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“…The comprehensive summaries from the recent studies conducted on Subarnarekha river basin (e.g., Jana et al, 2015;Yaduvanshi, et al, 2017Yaduvanshi, et al, & 2019Kumar and Joshi, 2019) demonstrated that this river basin is found to be prone to climate change. There is decrease in rainfall and ensuing decreased streamflows of the river basin mostly in June to September period for almost half of the future years.…”

Section: Study Areamentioning

confidence: 99%

“…Though the Subarnarekha river basin is a major river basin in India, significant research work is not done on this river basin. Few research works (e.g., Jana, et al, 2015;Yaduvanshi, et al, 2017;Yaduvanshi, et al, 2019;Kumar and Joshi, 2019;Banerji and Mukhopadhyay, 2018) are available in literature, but they failed to explain the uncertainties in streamflow projections under the climate change scenarios, even though they are very important for water management and agricultural practices in the river basin. This research gap motivated us to select this river basin for present study.…”

Section: Introductionmentioning

confidence: 99%

Uncertainties and nonstationarity in streamflow projections under climate change scenarios and the ensuing adaptation strategies in Subarnarekha river basin, India

2020

Global NEST: The International Journal

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<p>The present study analyses the various uncertainties and nonstationarity in the streamflow projections of Subarnarekha river basin in Eastern India using two widely used hydrological climate models: 1) general circulation model (GCM), and 2) forcing climate change scenarios. These two climate models are used to force the ArcSWAT model. Subsequently this model is calibrated using SUFI-2 optimization technique. The downscaled and bias-corrected data from an ensemble of 10 climate projections with representative concentration pathways (RCP) 4.5 and 8.5 scenarios (five each) were used in first model, whereas in second model a total of 63 (7 perturbed precipitations and 9 perturbed temperatures) combinations of hypothetical climate change scenarios were used. The results show very good correlation during monthly calibration time steps and relatively good agreement between the observed and simulated streamflows in daily calibration time steps. The uncertainties are expressed in probabilistic terms using probability density function (PDF) and cumulative distribution function (CDF) as they provide significant information for decision process in climate change adaptation in the river basin. The uncertainties associated with climate models, return periods and streamflow extremes are also analysed in the present work. The RCP 8.5 scenarios seem more appropriate than RCP 4.5 scenarios in quantifying the uncertainties under nonstationarity assumptions. The mean values of water balance components and their percentage variation for both historic and future periods reveal that the water balance components get affected significantly due to climate change in a future period. Consequently, the streamflows are likely to decline in the river basin. The present study also highlights the comprehensive approaches that are being planned to facilitate adaptation to climate change as well as those that are specific to the water resources management in the study region. The findings in this work are useful for overall well-being of people in the study area.</p>

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“…Since, the study of rainfall variability using continuous data based on Entropy approach has received less attention in the state of Uttarakhand, therefore, this region has been preferred for the study. Furthermore, understanding rainfall's temporal variability is precarious for water resource planning and management and in the prevention of extreme events like floods, droughts and as well as the control of soil erosion (Karmakar et al 2017;Pendergrass et al 2017;Jin and Wang 2017;Kurths et al 2019;Yaduvanshi et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Entropy based assessment of rainfall dynamics with varying elevations for hilly areas of Uttarakhand, India

Singh

Kumar

Kumar³

2022

Preprint

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Rainfall is the main element of the hydrological cycle and has a direct impact on agriculture sectors. A regular pattern of rainfall results in a healthy crop production, extreme events such as flood and drought, industrial and domestic sectors etc. The present study tried to explore the variability in rainfall pattern with elevation differences in hilly areas, using different measure of entropy indices based on monthly, seasonal and annual scale. The study was carried out for the hilly areas of Uttarakhand. The selected hilly districts of Uttarakhand for this study was Almora, Kashipur, Lansdowne, and Mukteshwar stations. The rainfall data of 116 years from 1901 to 2016 has been used. In the present study, Shannon entropy has been used and variability in rainfall pattern has been done using Mean Marginal Disorder Index (MMDI) and apportionment disorder index. The results suggested that in light of seasonal analysis, post-monsoon season had a high MMDI (0.345) for Lansdowne station followed by Mukteshwar (0.309), and Almora (0.304). However, the highest MMDI (0.340) was recorded for Kashipur during pre-monsoon season, while pre-monsoon season had lowest MMDI for Mukteshwar station followed by Almora and Lansdowne station, although, lowest MMDI was recorded during winter season of Kashipur station. The results revealed that Kashipur and Lansdowne station had high rainfall variability, whereas Almora and Mukteshwar stations had less rainfall variability. The present study revealed that variability in rainfall and rainy days was not uniform everywhere and places at higher elevation has less temporal variability of rainfall patterns and number of rainy days.

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A century scale hydro-climatic variability and associated risk in Subarnarekha river basin of India

Cited by 8 publications

References 33 publications

Temporal Change Dynamics of the Hydrometeorological Conditions of Upper Subarnarekha River Basin (SRB) Using Geospatial Techniques

Temporal Change Dynamics of the Hydrometeorological Conditions of Upper Subarnarekha River Basin (SRB) Using Geospatial Techniques

Uncertainties and nonstationarity in streamflow projections under climate change scenarios and the ensuing adaptation strategies in Subarnarekha river basin, India

Entropy based assessment of rainfall dynamics with varying elevations for hilly areas of Uttarakhand, India

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