This study presents a comprehensive review of the published literature on the evidences of a changing climate in the Indian Himalayan Region (IHR) and its impacts on the glacio-hydrology of the region. The IHR serves as an important source of fresh water for the densely populated areas downstream. It is evident from the available studies that temperature is significantly increasing in all parts of the IHR, whereas precipitation is not indicative of any particular spatiotemporal trend. Glacio-hydrological proxies for changing climate, such as, terminus and areal changes of the glaciers, glacier mass balance, and streamflow in downstream areas, highlight changes more evidently in recent decades. On an average, studies have predicted an increase in temperature and precipitation in the region, along with increase in streamflow of major rivers. Such trends are already apparent in some sub-basins of the western IHR. The region is particularly vulnerable to changing climate as it is highly dependent on snow and glacier melt run-off to meet its freshwater demands. We present a systematic review of key papers dealing with changing temperature, precipitation, glaciers, and streamflow in the IHR. We discuss these interdisciplinary themes in relation to each other, in order to establish the present and future impacts of climatic, glaciological, and hydrological changes in the region.
To date, there is a gap in the data about the state and mass balance of glaciers in the climate-sensitive subtropical regions during the Little Ice Age (LIA). Here, based on an unprecedented tree-ring sampling coverage, we present the longest reconstructed mass balance record for the Western Himalayan glaciers, dating to 1615. Our results confirm that the later phase of LIA was substantially briefer and weaker in the Himalaya than in the Arctic and subarctic regions. Furthermore, analysis of the time-series of the mass-balance against other time-series shows clear evidence of the existence of (i) a significant glacial decay and a significantly weaker magnitude of glaciation during the latter half of the LIA; (ii) a weak regional mass balance dependence on either the El Niño-Southern Oscillation (ENSO) or the Total Solar Irradiance (TSI) taken in isolation, but a considerable combined influence of both of them during the LIA; and (iii) in addition to anthropogenic climate change, the strong effect from the increased yearly concurrence of extremely high TSI with El Niño over the past five decades, resulting in severe glacial mass loss. The generated mass balance time-series can serve as a source of reliable reconstructed data to the scientific community.
The reconstruction of glacio-hydrological records for the data deficient Himalayan catchments is needed in order to study the past and future water availability. The study provides outcomes of a glacio-hydrological model based on the degree-day approach. The model simulates the discharge and mass balance for glacierised Shaune Garang catchment. The degree-day factors for different land covers, used in the model, were estimated using daily stake measurements on Shaune Garang glacier and they were found to be varying between 2.6 ± 0.4 and 9.3 ± 0.3 mm°C −1 day −1 . The model is validated using observed discharge during ablation season of 2014 with coefficient of determination (R 2 ) 0.90 and root mean square error (RMSE) 1.05 m 3 sec −1 . The model is used to simulate discharge from 1985 to 2008 and mass balance from 2001 to 2008. The model results show significant contribution of seasonal snow and ice melt in total discharge of the catchment, especially during summer. We observe the maximum discharge in July having maximum contribution from snow and ice melt. The annual melt season discharge shows following a decreasing trend in the simulation period. The reconstructed mass balance shows mass loss of 0.89 m we per year between 2001 and 2008 with slight mass gain during 2000/01 and 2004/05 hydrological years.Water Resour Manage
Changes in ice velocity of a glacier regulate its mass balance and dynamics. The estimation of glacier flow velocity is therefore an important aspect of temporal glacier monitoring. The utilisation of conventional ground-based techniques for detecting glacier surface flow velocity in the rugged and alpine Himalayan terrain is extremely difficult. Remote sensing-based techniques can provide such observations on a regular basis for a large geographical area. Obtaining freely available high quality remote sensing data for the Himalayan regions is challenging. In the present work, we adopted a differential band composite approach, for the first time, in order to estimate glacier surface velocity for non-debris and supraglacial debris covered areas of a glacier, separately. We employed various bandwidths of the Landsat 8 data for velocity estimation using the COSICorr (co-registration of optically sensed images and correlation) tool. We performed the accuracy assessment with respect to field measurements for two glaciers in the Indian Himalaya. The panchromatic band worked best for non-debris parts of the glaciers while band 6 (SWIR -short wave infrared) performed best in case of debris cover. We correlated six temporal Landsat 8 scenes in order to ensure the performance of the proposed algorithm on monthly as well as yearly timescales. We identified sources of error and generated a final velocity map along with the flow lines. Over-and underestimates of the yearly glacier velocity were found to be more in the case of slow moving areas with annual displacements less than 5 m. Landsat 8 has great capabilities for such velocity estimation work for a large geographic extent because of its global coverage, improved spectral and radiometric resolutions, free availability and considerable revisit time.
The surface and near-surface air temperature observations are primary data for glacio-hydro-climatological studies. The in situ air temperature (Ta) observations require intense logistic and financial investments, making it sparse and fragmented particularly in remote and extreme environments. The temperatures in Himalaya are controlled by a complex system driven by topography, seasons, and cryosphere which further makes it difficult to record or predict its spatial heterogeneity. In this regard, finding a way to fill the observational spatiotemporal gaps in data becomes more crucial. Here, we show the comparison of Ta recorded at 11 high altitude stations in Western Himalaya with their respective land surface temperatures (Ts) recorded by Moderate Resolution Imagining Spectroradiometer (MODIS) Aqua and Terra satellites in cloud-free conditions. We found remarkable seasonal and spatial trends in the Ta vs. Ts relationship: (i) Ts are strongly correlated with Ta (R2 = 0.77, root mean square difference (RMSD) = 5.9 °C, n = 11,101 at daily scale and R2 = 0.80, RMSD = 5.7 °C, n = 3552 at 8-day scale); (ii) in general, the RMSD is lower for the winter months in comparison to summer months for all the stations, (iii) the RMSD is directly proportional to the elevations; (iv) the RMSD is inversely proportional to the annual precipitation. Our results demonstrate the statistically strong and previously unreported Ta vs. Ts relationship and spatial and seasonal variations in its intensity at daily resolution for the Western Himalaya. We anticipate that our results will provide the scientists in Himalaya or similar data-deficient extreme environments with an option to use freely available remotely observed Ts products in their models to fill-up the spatiotemporal data gaps related to in situ monitoring at daily resolution. Substituting Ta by Ts as input in various geophysical models can even improve the model accuracy as using spatially continuous satellite derived Ts in place of discrete in situ Ta extrapolated to different elevations using a constant lapse rate can provide more realistic estimates.
The presence and extent of permafrost in the Himalaya, which is a vital component of the cryosphere, remains severely under-researched with its future climatic-driven trajectory only partly understood and the future consequences on high-altitude ecosystem tentatively sketched out. Previous studies and available permafrost maps for the Himalaya relied primarily upon the modelled meteorological inputs to further model the likelihood of permafrost. Here, as a maiden attempt, we have quantified the distribution of permafrost at 30 m grid-resolution in the Western Himalaya using observations from multisource satellite datasets for estimating input parameters, namely temperature, potential incoming solar radiation (PISR), slope, aspect and land use, and cover. The results have been compared to previous studies and have been validated through field investigations and geomorphological proxies associated with permafrost presence. A large part of the study area is barren land (~69%) due to its extremely resistive climate condition with ~62% of the total area having a mean annual air temperature of (MAAT) <1 °C. There is a high inter-annual variability indicated by varying standard deviation (1–3 °C) associated with MAAT with low standard deviation in southern part of the study area indicating low variations in areas with high temperatures and vice-versa. The majority of the study area is northerly (~36%) and southerly (~38%) oriented, receiving PISR between 1 and 2.5 MW/m2. The analysis of permafrost distribution using biennial mean air temperature (BMAT) for 2002-04 to 2018-20 suggests that the ~25% of the total study area has continuous permafrost, ~35% has discontinuous permafrost, ~1.5% has sporadic permafrost, and ~39% has no permafrost presence. The temporal analysis of permafrost distribution indicates a significant decrease in the permafrost cover in general and discontinuous permafrost in particular, from 2002-04 to 2018-20, with a loss of around 3% for the total area (~8340.48 km2). The present study will serve as an analogue for future permafrost studies to help understand the permafrost dynamics associated with the effects of the recent abrupt rise in temperature and change in precipitation pattern in the region.
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