Time series analysis of climate variability and trends in Kashmir Himalaya

Dad, Javaid M.; Muslim, Mohammad; Rashid, Irfan; Reshi, Zafar A.

doi:10.1016/j.ecolind.2021.107690

Cited by 75 publications

(15 citation statements)

References 64 publications

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“…On the other hand, rainfall patterns in many regions of the world are expected to result in a more widespread variable and extended dry spells. According to a recent climate precipitation trend analysis for the previous few decades, the total amount of annual precipitation is escalating along with increasing trends in consecutive dry days (CDD) (Mudelsee, 2018;Parey, 2019;Dad et al, 2021). Under the predicted importance of rainfall patterns for Olea europaea subsp.…”

Section: Discussionmentioning

confidence: 99%

Ensemble modeling to predict the impact of future climate change on the global distribution of Olea europaea subsp. cuspidata

Khan

Verma

2022

Front. For. Glob. Change

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Climate change is one of the significant factors influencing global species redistribution. As a result, a better understanding of the species' possible range change in future climate conditions is needed. Therefore, this study compiles global geographic occurrence data of a wild olive sub-species, Olea europaea subsp. cuspidate, and projected potential distribution models in current and future climate scenarios. This study using ensemble modeling predicted that the species will undergo a significant decrease in habitat suitability under future climatic conditions with a contraction ranging from ca. 41 and 42% under RCP4.5 2050 and to about 56 and 61% under RCP8.5 2070 for committee averaging and weighted mean, respectively. More specifically, there will be a decrease in habitat suitability in regions of the southeastern part of the United States in North America; coastal regions in South America; coastal regions in the majority of eastern Africa; coastal parts of Spain, France, Italy, and Greece in Europe; coastal parts of Yemen and Saudi Arabia; the southeastern parts of Pakistan and the southern part of China in Asia; and southwestern and eastern parts of Australia when compared to current habitat suitability. The results of this ensemble modeling could be extremely valuable in identifying cultivation hotspots for the effective restoration and protection of this olive lineage under future climatic conditions.

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Section: Discussionmentioning

confidence: 99%

Ensemble modeling to predict the impact of future climate change on the global distribution of Olea europaea subsp. cuspidata

Khan

Verma

2022

Front. For. Glob. Change

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“…The average elevation of the UJB is about 2684 m above sea level and is generally precipitous with an average slope of 29.4%. Average annual precipitation (based on 38 years of data) is 1005 mm and the majority of its precipitation is received in the form of snowfall from the western disturbances during the winter season [57,58]. However, the mountainous parts of the basin receive early snowfall from October and normally continues till late April.…”

Section: Study Areamentioning

confidence: 99%

Impact of Land System Changes and Extreme Precipitation on Peak Flood Discharge and Sediment Yield in the Upper Jhelum Basin, Kashmir Himalaya

Romshoo¹,

Yousuf²

2022

Preprint

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The Kashmir valley is prone to flooding due to its peculiar geomorphic setup compounded by the rapid anthropogenic land system changes and climate change. The study assesses the impact of land use and land cover (LULC) changes between 1980 and 2020 and extreme rainfall on peak discharge and sediment yield in the Upper Jhelum Basin (UJB), Kashmir Himalaya, India using KINEROS2 model. Analysis of LULC change revealed a notable shift from natural LULC to more intensive human-modified LULC, including a decrease in vegetative cover, deforestation, urbanization, and improper farming practices. The findings revealed a strong influence of the LULC changes on peak discharge, and sediment yield relative to the 2014 timeframe, which coincided with the catastrophic September 2014 flood event. The model predicted a peak discharge of 115101 cubic feet per second (cfs) and a sediment yield of 56.59 tons/ha during the September 2014 flooding, which is very close to the observed peak discharge of 115218 cfs indicating that the model is reliable for discharge prediction. The model predicted a peak discharge of 98965 cfs and a sediment yield of 49.11 tons/ha in 1980, which increased to 118366 cfs and, 58.92 tons/ha respectively in 2020, showing an increase in basin’s flood risk over time. In the future, it is anticipated that the ongoing LULC changes will make flood vulnerability worse, which could lead to another major flooding in the event of an extreme rainfall as predicted under climate change and, in turn compromise achievement of sustainable development goals (SDG). Therefore, regulating LULC in order to modulate various hydrological and land surface processes would ensure stability of runoff and reduction in sediment yield in the UJB, which is critical for achieving many SDGs.

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“…Due to the frequent occurrence of extreme values, it can occasionally be di cult to interpret the trends in data linked with high variability. These extremes, meanwhile, may not often represent long-term patterns in the data (Dad et al, 2021).…”

Section: Monthly Change Point Detectionmentioning

confidence: 99%

Time series analysis of variability and trends in precipitation on annual, seasonal and monthly scales of Jammu region of Western Himalaya from 1925-2020

Khan

Jaral

Verma

2022

Preprint

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Planning agricultural practises relies entirely on the timely prediction of rainfall based on data analysis. Early forecasting aids in the preparation of disaster management plans in high-risk locations in the event of predicted severe or limited rainfall. In this study, we analyzed the trends of precipitation and climatic variability for of Jammu region from 1925-2020. The non-parametric Mann-Kendall test was used to analyze the significance of trends in precipitation data on monthly seasonal and annual scales, whereas the non-parametric Sens’s estimator of the slope was used to quantify the magnitude of climatic trends. The results revealed that the Jammu region shows a statistically significant positive (p <0.005) for annual mean precipitation. In annual trend magnitude, the Jammu region showed a statistically significant increasing trend of 0.5260079 mm a-1 for the observed 95 years' climatic time series. The seasonal trends of precipitation statistics exhibit statistically significant positive trends over the observed time series in the case of the summer season only. Further, a significant precipitation increase of 1.484841 mm-1 was observed for the summer season only. The results of Pettit’s test for detecting annual change points for precipitation show a statistically significant change in the years 1988, 1951, and 1985 and seasonally in the year 1993 for the summer season only. Further, the results of the Mann–Kendall test for detecting monthly trends in the precipitation variables for the 95 years of observed climatic time series exhibit a statistically significant increasing trend for the months of May, June, August, and November. The results of this study are extremely useful in many sectors including agriculture, water resources, and most notably climatology studies in most striking aspects of developmental planning in recent times.

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Time series analysis of climate variability and trends in Kashmir Himalaya

Cited by 75 publications

References 64 publications

Ensemble modeling to predict the impact of future climate change on the global distribution of Olea europaea subsp. cuspidata

Ensemble modeling to predict the impact of future climate change on the global distribution of Olea europaea subsp. cuspidata

Impact of Land System Changes and Extreme Precipitation on Peak Flood Discharge and Sediment Yield in the Upper Jhelum Basin, Kashmir Himalaya

Time series analysis of variability and trends in precipitation on annual, seasonal and monthly scales of Jammu region of Western Himalaya from 1925-2020

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