Raaj Ramsankaran

Weakening of Indian Summer Monsoon Rainfall due to Changes in Land Use Land Cover

Weakening of Indian summer monsoon rainfall (ISMR) is traditionally linked with large-scale perturbations and circulations. However, the impacts of local changes in land use and land cover (LULC) on ISMR have yet to be explored. Here, we analyzed this topic using the regional Weather Research and Forecasting model with European Center for Medium range Weather Forecast (ECMWF) reanalysis data for the years 2000–2010 as a boundary condition and with LULC data from 1987 and 2005. The differences in LULC between 1987 and 2005 showed deforestation with conversion of forest land to crop land, though the magnitude of such conversion is uncertain because of the coarse resolution of satellite images and use of differential sources and methods for data extraction. We performed a sensitivity analysis to understand the impacts of large-scale deforestation in India on monsoon precipitation and found such impacts are similar to the observed changes in terms of spatial patterns and magnitude. We found that deforestation results in weakening of the ISMR because of the decrease in evapotranspiration and subsequent decrease in the recycled component of precipitation.

Inter-comparison of remote sensing sensing-based shoreline mapping techniques at different coastal stretches of India

Many techniques are available for detection of shorelines from multispectral satellite imagery, but the choice of a certain technique for a particular study area can be tough. Hence, for the first time in literature, an inter-comparison of the most widely used shoreline mapping techniques such as Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), Improved Band Ratio (IBR) Method, and Automatic Water Extraction Index (AWEI) has been done along four different coastal stretches of India using multitemporal Landsat data. The obtained results have been validated with the high-resolution images of Cartosat-2 (panchromatic) and multispectral images from Google Earth. Performance of the above indices has been analyzed based on the statistics, such as overall accuracy, kappa coefficient, user’s accuracy, producer’s accuracy, and the average deviation from the reference line. It is observed that the performance of NDWI and IBR techniques are dependent on the physical characteristics of the sites, and therefore, it varies from one site to another. Results indicate that unlike these two indices, the AWEI algorithm performs consistently well followed by MNDWI irrespective of the land cover types.

Multi-Index Rain Detection: A New Approach for Regional Rain Area Detection from Remotely Sensed Data

AbstractIn this article, a new approach called Multi-Index Rain Detection (MIRD) is suggested for regional rain area detection and was tested for India using Kalpana-1 satellite data. The approach was developed based on the following hypothesis: better results should be obtained for combined indices than an individual index. Different combinations (scenarios) were developed by combining six commonly used rain detection indices using AND and OR logical connectives. For the study region, an optimal rain area detection scenario and optimal threshold values of the indices were found through a statistical multi-decision-making technique called the Technique for Order Preference by Similarity Ideal Solution (TOPSIS). The TOPSIS analysis was carried out based on independent categorical statistics like probability of detection, probability of no detection, and Heidke skill score. It is noteworthy that for the first time in literature, an attempt has been made (through sensitivity analysis) to understand the influ...

Physically-based distributed soil erosion and sediment yield model (DREAM) for simulating individual storm events

Abstract A relatively simple process-oriented, physically-based distributed (PBD) hydrological model, the distributed runoff and erosion assessment model (DREAM), is described, and a validation study conducted in the semi-forested watershed of Pathri Rao, in the Garhwal Himalayas, India, is reported. DREAM takes account of watershed heterogeneity as reflected by land use, soil type, topography and rainfall, measured in the field or estimated through remote sensing, and generates estimates of runoff and sediment yield in spatial and temporal domains. The model is based on simultaneous solution of flow dynamics, based on kinematic wave theory, followed by solution of soil erosion dynamics. As the storm rainfall proceeds, the process of overland flow generation is dependent on the interception storage and infiltration rates. The components of the soil erosion model have been modified to provide better prediction of sediment flow rates and sediment yields. The validation study conducted to test the performance of the model in simulating soil erosion and sediment yield during different storm events monitored in the study watershed showed that the model outputs are satisfactory. Details of a sensitivity analysis, model calibration and the statistical evaluation of the results obtained are also presented and discussed. It is noteworthy that the distributed nature of the model combined with the use of geographical information system (GIS) techniques permits the computation and representation of the spatial distribution of sediment yield for simulated storm events, and a map of the spatial distribution of sediment yield for a simulated storm event is presented to highlight this capability. Citation Ramsankaran, R., Kothyari, U.C., Ghosh, S.K., Malcherek, A., and Murugesan, K., 2013. Physically-based distributed soil erosion and sediment yield model (DREAM) for simulating individual storm events. Hydrological Sciences Journal, 58 (4), 872–891.

Spatially distributed ice-thickness modelling for Chhota Shigri Glacier in western Himalayas, India

ABSTRACT Estimation of glacier ice-thickness distribution is important for many glacio-hydrological applications such as runoff projections, glacial lake outburst flood (GLOF) predictions, future evolution of glaciers. Varieties of modelling approaches are available for estimating ice-thickness distribution depending upon the data availability. In the present study, we estimated the ice-thickness distribution and total ice volume of Chhota Shigri Glacier using an optimally parameterized Glacier Bed Topography version 2 (GlabTop2) model, a shallow ice approximation (SIA)-based spatially distributed approach. Among the model input parameters, the shape factor (f), a non-measurable factor compensating for unaccounted effects such as valley shape needs to be calibrated using field measurements of ice-thickness. However, the lack of direct measurements of ice-thickness over many glaciers worldwide restricts model calibration and effective implementation. Therefore, to overcome this limitation, in this study, a novel approach using a relationship between shape factor, glacier cross-sectional width, and ice-thickness at the centre of a cross-section has been proposed and also tested to estimate optimal shape factor of the study glacier. Additionally, a detailed analysis of the effect of Digital Elevation Model (DEM) resolution and shape factor parameterization on the modelled ice-thickness estimates indicate that improving either the DEM resolution or calibrating the shape factor individually will not lead to improved ice-thickness estimates. In fact, both are necessary for better estimation of ice-thickness distribution. The high resolution DEM used in this study is TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X) DEM of 10 × 10 m grid size. Finally, a comparison of the results from a previous study where they used Shuttle Radar Topography Mission (SRTM) 90 m DEM indicates that the improved parameterisation of GlabTop2 model has led to a reduction in the error bounds of the estimated ice-thickness including the total glacier stored ice volume for the year 2013, which is estimated to be 1.74 ± 0.25 km3. Furthermore, based on the obtained results, it can be said that the GlabTop2 model combined with the proposed parameterization approach is having enormous potential to be applied over the wide range of data scarce Himalayan glaciers to quantify reliable ice-thickness estimates.

Comparison of the performance of the newly developed CDWM Filter with Enhanced LEE and Enhanced Frost Filters over the SAR image

Synthetic Aperture Radar (SAR) is an active remote sensing technique. SAR is corrupted by a signal dependent multiplicative noise called speckle noise. Speckle noise limits the data extraction capabilities and degrades the quality of the obtained data. It decreases the potentiality to interpret the image, restricts edge abstraction, image segmentation, target recognition and classification. It is important to carry out despeckling to enable any further usage of SAR data in various possible applications. In this paper, we compare a recently proposed Cornered Difference Weighted Mean (CDWM) filter with two widely use Enhanced Lee and Enhanced Frost filters. The comparison had been done to quantitatively evaluate the performance of each of the three filters using well established evaluation metrics. Based on the results, it is found that the CDWM filter is more computationally efficient and effective in speckle reduction and also preserves fine details in the images. The current study has been done using Indias first C-band (5.35 GHz) SAR based RISAT-1 satellite data.

Decadal Estimates of Surface Mass Balance for Glaciers in Chandra Basin, Western Himalayas, India—A Geodetic Approach

The Himalayas, which has the highest concentration of glaciers outside the poles, form a huge reservoir of fresh water. These glaciers are not only important because of the contribution they make to our water resources, but also because they are a great help in understanding the effects of climate change. However, monitoring even a few of these glaciers through field techniques is a tedious process due to the tough and unapproachable terrain of the Himalayas. In such situation, remote sensing techniques become a boon. In this article, one such widely used remote sensing-based technique called digital elevation model (DEM). Differencing or geodetic approach available for estimating glacier surface mass balance (SMB) is discussed. However, the accuracy of the estimated SMB using geodetic approach is highly dependent on the accuracy of the DEMs used, which ultimately decides whether this approach can be used for seasonal, annual or decadal studies. To get a better understanding of this approach, this article gives a brief overview of errors present in DEMs and how to correct it before estimating SMB by demonstrating it over 65 glaciers located in the Chandra basin, Lahaul–Spiti district of Himachal Pradesh, India. The obtained results indicate that the Chandra basin has lost 5.01 ± 2.48 Gt of ice mass during the course of 14 years (1999–2013), which gives a clear signal on the effect of climate change occurred over the study area and how climate change could cause imbalance in the health of glacier(s). Considering the advantages of this approach and recent developments in high-resolution DEM data acquisition as well as the need for such accurate mass balance estimates across Himalayas, it is therefore suggested that this modelling approach should be extended to other basins to get the current status of the health of the glaciers across Himalayas.

Quantification of annual glacier surface mass balance for the Chhota Shigri Glacier, Western Himalayas, India using an Equilibrium-Line Altitude (ELA) based approach

ABSTRACT In line with the increasing scientific interest on the Himalayan glaciers, this study focuses on estimating a long-term annual surface mass balance time series of the Chhota Shigri glacier, a ‘benchmark’ glacier in the western Himalayas. The approach used here is based on the fact that the annual glacier-wide surface mass balance can be deduced from the equilibrium-line altitude (ELA). Depending on the distribution and availability of multiple cloud free remotely sensed images during ablation period, a multi-temporal approach has been used to estimate ELA. When compared with field-based ELA, the results indicate that the multi-temporal approach resulted in better estimates of ELA than the conventional single image approach. Likewise, the annual surface mass balances quantified from this study closely match with field estimates over the common period (2003–2014) and even better than some estimates from earlier studies based on other proxies (meteorological data or glacier surface albedo). A sensitivity analysis shows that the annual surface mass balance quantified from the ELA-based approach is not very sensitive to changes in the mass balance gradient and average mass balance. Hence, the approach has been further applied to reconstruct the long-term annual surface mass balance series of the Chhota Shigri Glacier over the period 1989–2017. Our results show a good agreement between the reconstructed surface mass balance and estimates of other long-term studies. Therefore, this study indicates the great potential for this approach for quantifying the annual surface mass balance for glaciers with no ground data lying in same climatic zone.

Error modelling for modified-INSAT multi-spectral rainfall algorithm

ABSTRACT Considering the importance of the error estimates for satellite rainfall products in various applications, the present article deals with the development of an Error Model for Modified-INSAT Multi-Spectral Rainfall Algorithm (M-IMSRA) Estimates (EMME), a recently developed climate region scale rainfall algorithm across India. A non-parametric framework has been adopted to model all the four error components: Correct No-Rain Detection, Miss Rain, False Rain, and Hit Rain in M-IMSRA estimates at climate region scale. The developed error model generated convincing realization of reference rainfall for the estimated rainfall from M-IMSRA algorithm across all the climate regions of India. Exceptions are the high intensity hit rain events across arid Thar Desert and arid Himalayan regions and miss rain events across arid Himalayan region. Overall, the developed error model showed promising results in modelling hit, miss, and false error components of daily M-IMSRA estimates and thus can be associated with the M-IMSRA estimates.

Estimation of recent changes in thickness and mass balance of the Patsio glacier in the Great Himalayan region using geodetic technique and ancillary data

Abstract An understanding of glacier mass budget in the Himalayas is important for regional water resource management. This study presents a detailed estimation of mass budget of the Patsio glacier (The Great Himalaya) using SRTM-X (2000), Cartosat-1 (2005) and TanDEM-X (2013) DEMs. Geodetic findings indicate an overall mass loss by −0.26±0.11 m.w.e/yr,−0.30±0.10 m.w.e/yr and −0.16±0.11 m.w.e/yr during 2000-2013, 2000-2005 and 2005–2013 respectively. Maximum downwasting was observed in the terminus area of the glacier during the period 2000–2013. The observed lower rate of mass loss between 2005 and 2013 was attributed to declining temperature during that period. However, long-term temperature trends depict warming, so was exhibited by mass loss during 2000–2013. Geodetic based findings were found to be concordant with GPR based estimation. This study confirms the suitability of geodetic mass balance technique for mountainous glaciers, which will be useful to evaluate future changes in the glacial extent and runoff study.