Quantifying groundwater sensitivity and resilience over peninsular India     

Nikhil Kumar  Jhilam Sinha  Chandra A. Madramootoo  Manish Kumar Goyal 《水文研究》2020,34(26):5327-5339

Groundwater in India plays an important role to support livelihoods and maintain ecosystems and the present rate of depletion of groundwater resources poses a serious threat to water security. Yet, the sensitivity of the hydrological processes governing groundwater recharge to climate variability remains unclear in the region. Here we assess the groundwater sensitivity (precipitation–recharge relationship) and its potential resilience towards climatic variability over peninsular India using a conceptual water balance model and a convex model, respectively in 54 catchments over peninsular India. Based on the model performance using a comprehensive approach (Nash Sutcliffe Efficiency [NSE], bias and variability), 24 out of 54 catchments are selected for assessment of groundwater sensitivity and its resilience. Further, a systematic approach is used to understand the changes in resilience on a temporal scale based upon the convex model and principle of critical slowing down theory. The results of the study indicate that the catchments with higher mean groundwater sensitivity (GWS) encompass high variability in GWS over the period (1988–2011), thus indicating the associated vulnerability towards hydroclimatic disturbances. Moreover, it was found that the catchments pertaining to a lower magnitude of mean resilience index incorporates a high variability in resilience index over the period (1993–2007), clearly illustrating the inherent vulnerability of these catchments. The resilience of groundwater towards climatic variability and hydroclimatic disturbances that is revealed by groundwater sensitivity is essential to understand the future impacts of changing climate on groundwater and can further facilitate effective adaptation strategies.  相似文献   

喜马拉雅中部甘达基河流域尼泊尔国鸟(棕尾虹雉)生境分布变化     

Raju RAI  Basanta PAUDEL  谷昌军  Narendra Raj KHANAL 《资源与生态学报(英文版)》2020,11(2):223-231

甘达基河流域(Gandaki River Basin,GRB)是喜马拉雅中部地区的一部分,该地区栖息着许多珍稀的野生动物。由于气候和人类活动的影响,许多珍稀保护物种的生境处于危险之中。本研究基于最大熵(MaxEnt)模型,运用生物气候、土地覆被和DEM数据,分析各环境要素对棕尾虹雉(Lophophorusimpejanus)的生境适宜性的影响,评估棕尾虹雉现在状况和未来栖息地分布的变化。研究表明,目前棕尾虹雉的高度适宜栖息地面积约为749 km^2,主要分布在流域北部、东部和西部,尤其是郎塘国家公园、马纳斯卢峰自然保护区和安纳布尔纳峰自然保护区等保护区内。到2050年,棕尾虹雉的高度适宜栖息地面积将减少至561 km^2,主要在流域北部和西北部(即Chhyo,Tatopani,Humde和Chame地区)。未来环境变化的模拟表明,由于适宜栖息地面积的减少,棕尾虹雉面临的生存风险将增加。  相似文献   

The sudden stratospheric warming and chemical ozone loss in the Antarctic winter 2019: comparison with the winters of 1988 and 2002     

Roy  R.  Kuttippurath  J.  Lefèvre  F.  Raj  S.  Kumar  P. 《Theoretical and Applied Climatology》2022,149(1-2):119-130

Theoretical and Applied Climatology - Sudden stratospheric warmings (SSWs) are associated with rapid rise in temperature in a short period of time in the polar vortex and reversal of the zonal...  相似文献   

Spatio-temporal variations of respirable particles at residential areas located in the vicinity of opencast coal projects,India: a case study     

Satya Prakash Sahu  Manish Yadav  Dhruti Sundar Pradhan  Neha Rani  Arka Jyoti Das 《Arabian Journal of Geosciences》2018,11(10):241

The objective of the study is to investigate spatio-temporal variations of PM₁₀, PM_2.5, and PM₁ concentrations at seven residential sites, located in the vicinity of opencast coal projects, Basundhara Garjanbahal Area (BGA), India. Meteorological parameters such as wind speed, wind direction, relative humidity, and temperature were collected simultaneously with PM concentrations. Mean concentrations of PM₁₀ in the range 215 ± 169–526 ± 412 μg m^?3, PM_2.5 in the range of 91 ± 79–297 ± 107 μg m^?3, PM₁ in the range of 68 ± 60–247 ± 84 μg m^?3 were obtained. Coarse fractions (PM_2.5–10) varied from 27 to 58% whereas fine fractions (PM_1–2.5 and PM₁) varied in the range of 51–73%. PM_2.5 concentration was 41–74% of PM₁₀ concentration, PM₁ concentration was 31–62% of PM₁₀ concentration, and PM₁ concentration was 73–83% of PM_2.5 concentration. Role of meteorology on PM concentrations was assessed using correlation analysis. Linear relationships were established among PM concentrations using least square regression analysis. With the aid of principal component analysis, two components were drawn out of eight variables, which represent more than 75% of variance. The results indicated that major sources of air pollutants (PM₁₀, PM_2.5, PM₁, CO, CO₂) at the residential sites are road dust raised by vehicular movement, spillage of coal generated during transportation, spontaneous combustion of coal, and biomass burning in village area.  相似文献   

Vegetation damage assessment due to Hudhud cyclone based on NDVI using Landsat-8 satellite imagery     

Venkata Giri Raj Kumar Konda  Venkatesh Reddy Chejarla  Venkata Ravibabu Mandla  Vani Voleti  Nagaveni Chokkavarapu 《Arabian Journal of Geosciences》2018,11(2):35

Developing nations are abandoned against tropical cyclones because of climatic changeability; the atmosphere is probably going to expand the recurrence and extent of some outrageous climate and calamity occasions. Urban areas and towns arranged along the coastline front belt in Visakhapatnam region experienced serious harm because of Hudhud cyclone, which happened on October 12, 2014. The fundamental motivation behind this exploration was to distinguish the vegetation damage in Visakhapatnam and neighbouring towns. In this analysis, Landsat-8 satellite datasets procured prior and then afterward the cyclone have been utilized; image processing techniques have been completed to evaluate the progressions of pre- and post-disaster condition. Vegetation index strategy was utilized to assess the damage to vegetation. Arrangement results and land utilize land cover change investigation demonstrate that 13.25% of agriculture Kharif and 31.1% of vegetation was damaged. Normalized difference vegetation index (NDVI) maps were produced for the previously, then after the cyclone circumstance, and vegetation biomass damage was evaluated in Visakhapatnam and Bhimunipatanam. General loss of vegetation in both the spots was 30.67 and 43.37 km². The result of this review can be utilized by decision makers for the post-disaster support for rebuilding of influenced regions.  相似文献   

Structure,mechanical properties and evolution of the lithosphere below the northwest continental margin of India     

Rao  G. Srinivasa  Kumar  Manish  Radhakrishna  M. 《International Journal of Earth Sciences》2018,107(6):2191-2207

International Journal of Earth Sciences - The continental breakup history at the northwest continental margin of India remained conjectural due to lack of clearly discernable magnetic anomaly...  相似文献   

Verification of two hydrological models for real-time flood forecasting in the Hindu Kush Himalaya (HKH) region     

Tsering  Karma  Shrestha  Manish  Shakya  Kiran  Bajracharya  Birendra  Matin  Mir  Lozano  Jorge Luis Sanchez  Nelson  Jim  Wangchuk  Tandin  Parajuli  Binod  Bhuyan  Md Arifuzzaman 《Natural Hazards》2022,110(3):1821-1845

Natural Hazards - The Hindu Kush Himalayan region is extremely susceptible to periodic monsoon floods. Early warning systems with the ability to predict floods in advance can benefit tens of...  相似文献   

Microseismic events enhancement and detection in sensor arrays using autocorrelation‐based filtering          下载免费PDF全文

Entao Liu  Lijun Zhu  Anupama Govinda Raj  James H. McClellan  Abdullatif Al‐Shuhail  SanLinn I. Kaka  Naveed Iqbal 《Geophysical Prospecting》2017,65(6):1496-1509

Passive microseismic data are commonly buried in noise, which presents a significant challenge for signal detection and recovery. For recordings from a surface sensor array where each trace contains a time‐delayed arrival from the event, we propose an autocorrelation‐based stacking method that designs a denoising filter from all the traces, as well as a multi‐channel detection scheme. This approach circumvents the issue of time aligning the traces prior to stacking because every trace's autocorrelation is centred at zero in the lag domain. The effect of white noise is concentrated near zero lag; thus, the filter design requires a predictable adjustment of the zero‐lag value. Truncation of the autocorrelation is employed to smooth the impulse response of the denoising filter. In order to extend the applicability of the algorithm, we also propose a noise prewhitening scheme that addresses cases with coloured noise. The simplicity and robustness of this method are validated with synthetic and real seismic traces.  相似文献   

Impact of Kalpana-1 retrieved multispectral AMVs on Mahasen tropical cyclone forecast     

Inderpreet Kaur  Prashant Kumar  S. K. Deb  C. M. Kishtawal  P. K. Pal  Raj Kumar 《Natural Hazards》2015,77(1):205-222

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Simulating rainfall time-series: how to account for statistical variability at multiple scales?     

Fabio?OrianiEmail authorView author&#;s OrcID profile  Raj?Mehrotra  Grégoire?Mariethoz  Julien?Straubhaar  Ashish?Sharma  Philippe?Renard 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(2):321-340

Daily rainfall is a complex signal exhibiting alternation of dry and wet states, seasonal fluctuations and an irregular behavior at multiple scales that cannot be preserved by stationary stochastic simulation models. In this paper, we try to investigate some of the strategies devoted to preserve these features by comparing two recent algorithms for stochastic rainfall simulation: the first one is the modified Markov model, belonging to the family of Markov-chain based techniques, which introduces non-stationarity in the chain parameters to preserve the long-term behavior of rainfall. The second technique is direct sampling, based on multiple-point statistics, which aims at simulating a complex statistical structure by reproducing the same data patterns found in a training data set. The two techniques are compared by first simulating a synthetic daily rainfall time-series showing a highly irregular alternation of two regimes and then a real rainfall data set. This comparison allows analyzing the efficiency of different elements characterizing the two techniques, such as the application of a variable time dependence, the adaptive kernel smoothing or the use of low-frequency rainfall covariates. The results suggest, under different data availability scenarios, which of these elements are more appropriate to represent the rainfall amount probability distribution at different scales, the annual seasonality, the dry-wet temporal pattern, and the persistence of the rainfall events.  相似文献