Analysis of Process Controls in Land Surface Hydrological Cycle Over the Continental United States

The paper uses two years (1997–1999) of data from the North American Land Data Assimilation System at National Centers for Environmental Prediction to analyze the variability of physical variables contributing to the hydrological cycle over the conterminous United States. The five hydrological variables considered in this study are precipitation, top layer soil moisture (0–10 cm), total soil moisture (0–200 cm), runoff, and potential evaporation. There are two specific analyses carried out in this paper. In the first case the principal components of the hydrological cycle are examined with respect to the loadings of the individual variables. This helps to ascertain the contribution of physical variables to the hydrological process in decreasing order of process importance. The results from this part of the study had revealed that both in annual and seasonal timescales the first two principal components account for 70–80% of the variance and that precipitation dominated the first principal component, the most dominant mode of spatial variability. It was followed by the potential evaporation as the secondmost dominant process controlling the spatial variability of the hydrologic cycle over the continental United States. In the second case each hydrological variable was examined individually to determine the temporal evolution of its spatial variability. The results showed the presence of heterogeneity in the spatial variability of hydrologic variables and the way these patterns of variance change with time. It has also been found that the temporal evolution of the spatial patterns did not resemble white noise; the time series of the scores of the principal components showed proper cyclicity at seasonal to annual timescales. The northwestern and the southeastern parts of the United States had been found to have contributed significantly toward the overall variability of potential evaporation and soil moisture over the United States. This helps in determining the spatial patterns expected from hydrological variability. More importantly, in the case of modeling as well as designing observing systems, these studies will lead to the creation of efficient and accurate land surface measurement and parameterization schemes

Remote sensing of coal fires in India: A review

Coal fires are a persistent threat to major coal producing countries in the world. Alongside massive wastage of coal resources, coal fires pose enormous constraints to mining operations in adjacent areas. Beyond its dire denouement for a country's economy, coal fires pose potential risk to the environment, infrastructure and human health at local and regional scales. Owing to its dynamic nature and widespread occurrence, remote sensing provides the most cost-effective technology for mapping and monitoring of coal fires in India and the world over. This work presents a brief discussion on the principles of various remote sensing techniques and an in-depth review of the applications of remote sensing as a reliable tool to detect and monitor coal fires in India. While we review the capabilities and efficiencies of various remote sensing techniques, implemented since its inception in the late 1980s, we also highlight their limitations and advantages. Also, included are a broad overview of coal and coal fires in India, factors inducing them and their impact on the environment. Finally, we discuss the existing knowledge gaps, prospective challenges, urgent requirements and recommendations for extending the scope of remote sensing based coal fire investigations in the future

Detecting and Analyzing the Evolution of Subsidence Due to Coal Fires in Jharia Coalfield, India Using Sentinel-1 SAR Data

Public safety and socio-economic development of the Jharia coalfield (JCF) in India is critically dependent on precise monitoring and comprehensive understanding of coal fires, which have been burning underneath for more than a century. This study utilizes New-Small BAseline Subset (N-SBAS) technique to compute surface deformation time series for 2017–2020 to characterize the spatiotemporal dynamics of coal fires in JCF. The line-of-sight (LOS) surface deformation estimated from ascending and descending Sentinel-1 SAR data are subsequently decomposed to derive precise vertical subsidence estimates. The most prominent subsidence (~22 cm) is observed in Kusunda colliery. The subsidence regions also correspond well with the Landsat-8 based thermal anomaly map and field evidence. Subsequently, the vertical surface deformation time-series is analyzed to characterize temporal variations within the 9.5 km2 area of coal fires. Results reveal that nearly 10% of the coal fire area is newly formed, while 73% persisted throughout the study period. Vulnerability analyses performed in terms of the susceptibility of the population to land surface collapse demonstrate that Tisra, Chhatatanr, and Sijua are the most vulnerable towns. Our results provide critical information for developing early warning systems and remediation strategies

Manifestation of topography and climate variations on long-term glacier changes in the Alaknanda Basin of Central Himalaya, India

Here, we present a detailed analysis of glaciers in the Alaknanda Basin, Central Himalaya, starting with a novel glacier inventory for 1968 and 2020 using high-resolution datasets of Corona and Sentinel-2A. Primarily, we examine the factors influencing changes in glacier characteristics. Results show that glacier area reduced to 683 ± 47.81 km2 from 742 ± 44.4 km2, and the number of glaciers increased to 116 from 98 between 1968 and 2020. The annual average recession of glaciers in the basin is 11.75 ± 1.6 m/year for the corresponding period. Also noted is a significant increase (∼38%) in supraglacial debris cover extent of the glaciers during 2000–2020. Interestingly, smaller glaciers (< 5 km2) with lower altitude snout and higher slope have registered more significant area loss and higher retreat rate. Alongside topographic parameters, the significant deglaciation and fragmentation observed in the basin are augmented by the increase in winter-time temperature (0.03 °C/year) between 1968 and 2020

Glacier mass loss in the Alaknanda basin, Garhwal Himalaya on a decadal scale

The Himalayan glaciers significantly contribute to the largest river systems like the Indus, Ganga, and the Brahmaputra. The change in glacial area and mass can affect the mountain community and people living in the Indo-Gangetic plain. The present study adopted the geodetic method to estimate the elevation change and mass budget of 61 glaciers in the Alaknanda Basin, using the satellite data of Cartosat-1 (2011, 2014, 2017) and SRTM (2000). Besides, the DEM of 1962 (SOI Toposheet) and 2000 (SRTM) is used to estimate the mass budget of Satopanth (SPG) and Bhagirath Kharak glaciers (BKG). The field debris thickness of SPG (2015-2017) is compared with the elevation change (2000-2017). Further, we have compared the mass loss of the glaciers with their volume. The results suggest the sustained mass loss of 1.85 ± 0.10 Gt out of 33.9 ± 8.8 Gt for 61 glaciers in the basin from 2000-2017. The mass loss of SPG and BKG during 2000-2017 is 0.20 ± 0.02 Gt and 0.24 ± 0.03 Gt, whereas from 1962 to 2000, is 0.083 ± 0.03 Gt and 0.091 ± 0.04 Gt, respectively. The analysis facilitates a better understanding of glacier mass changes in the Alaknanda basin on a multi-decadal scale

Analysis of process controls in land surface hydrological cycle over the continental United States

The paper uses two years (1997–1999) of data from the North American Land Data Assimilation System at National Centers for Environmental Prediction to analyze the variability of physical variables contributing to the hydrological cycle over the conterminous United States. The five hydrological variables considered in this study are precipitation, top layer soil moisture (0–10 cm), total soil moisture (0–200 cm), runoff, and potential evaporation. There are two specific analyses carried out in this paper. In the first case the principal components of the hydrological cycle are examined with respect to the loadings of the individual variables. This helps to ascertain the contribution of physical variables to the hydrological process in decreasing order of process importance. The results from this part of the study had revealed that both in annual and seasonal timescales the first two principal components account for 70–80% of the variance and that precipitation dominated the first principal component, the most dominant mode of spatial variability. It was followed by the potential evaporation as the secondmost dominant process controlling the spatial variability of the hydrologic cycle over the continental United States. In the second case each hydrological variable was examined individually to determine the temporal evolution of its spatial variability. The results showed the presence of heterogeneity in the spatial variability of hydrologic variables and the way these patterns of variance change with time. It has also been found that the temporal evolution of the spatial patterns did not resemble white noise; the time series of the scores of the principal components showed proper cyclicity at seasonal to annual timescales. The northwestern and the southeastern parts of the United States had been found to have contributed significantly toward the overall variability of potential evaporation and soil moisture over the United States. This helps in determining the spatial patterns expected from hydrological variability. More importantly, in the case of modeling as well as designing observing systems, these studies will lead to the creation of efficient and accurate land surface measurement and parameterization schemes

Analysis of process controls in land surface hydrological cycle over the continental United States

The paper uses two years (1997–1999) of data from the North American Land Data Assimilation System at National Centers for Environmental Prediction to analyze the variability of physical variables contributing to the hydrological cycle over the conterminous United States. The five hydrological variables considered in this study are precipitation, top layer soil moisture (0–10 cm), total soil moisture (0–200 cm), runoff, and potential evaporation. There are two specific analyses carried out in this paper. In the first case the principal components of the hydrological cycle are examined with respect to the loadings of the individual variables. This helps to ascertain the contribution of physical variables to the hydrological process in decreasing order of process importance. The results from this part of the study had revealed that both in annual and seasonal timescales the first two principal components account for 70–80% of the variance and that precipitation dominated the first principal component, the most dominant mode of spatial variability. It was followed by the potential evaporation as the secondmost dominant process controlling the spatial variability of the hydrologic cycle over the continental United States. In the second case each hydrological variable was examined individually to determine the temporal evolution of its spatial variability. The results showed the presence of heterogeneity in the spatial variability of hydrologic variables and the way these patterns of variance change with time. It has also been found that the temporal evolution of the spatial patterns did not resemble white noise; the time series of the scores of the principal components showed proper cyclicity at seasonal to annual timescales. The northwestern and the southeastern parts of the United States had been found to have contributed significantly toward the overall variability of potential evaporation and soil moisture over the United States. This helps in determining the spatial patterns expected from hydrological variability. More importantly, in the case of modeling as well as designing observing systems, these studies will lead to the creation of efficient and accurate land surface measurement and parameterization schemes