Search

This paper releases two regional precipitation products produced in the Himalayan Re-gridded and Observational Experiment (HiROX) conducted over the Central (Uttarakhand) Himalayas including the Upper Ganga Basin. The distributed precipitation products cover a period of about 70 yrs: HiROX-1 ranges from 1972 to 2018 (47 yrs) and is a regridded static daily precipitation product, and HiROX-2 ranges from 2000 to 2021 (22 yrs) and is a regridded dynamic daily precipitation product with continuous upgradation capacity. These datasets are capable of (a) precisely capturing and reproducing refined spatial distribution of precipitation and (b) preserving data accuracy along with other spatiotemporal characteristics over the study region, better than that observed in popular precipitation products covering the study region. The comparative investigation established HiROX-1 as better than some or all the tested datasets in terms of (a) spatial resolution, (b) accuracy, (c) temporal resolution, (d) temporal coverage, and (e) spatial distribution, and presents their application suitability. The second precipitation product, HiROX-2, closely followed HiROX-1, as reported in the ensuing investigation. We employed an open-source precipitation model, HiROX-M1, a flexible machine learning framework capable of processing precipitation information at fine spatial resolution. These regional precipitation products are provided at a spatial resolution of 5 × 5 km2 on daily scale over projected and geographic coordinate systems. HiROX-1 is a station-dependent product and HiROX-2 is a near real-time station-independent product with an updated frequency equal to that of Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG) Final Precipitation L3 1 day 0.1° × 0.1° V06 (GPM_3IMERGDF V06) product. The released products are platform-independent in choice of operating system and geographic information system (GIS) interface. The released data shall assist in closing the spatial discontinuity of ground station information over the Central Himalayan region over Uttarakhand, including the Upper Ganga Basin. [ABSTRACT FROM AUTHOR]

The Kachchh region of western India is located in a plate interior region, but falls under one of the highest seismic zones of India, having very active crustal deformation and erosion. The drainage system, as well as the geomorphic evolution of the region under a semi-arid climate zone with high to very high strength of rocks in areas with high relief, is dominantly controlled by the seismic instability associated with continual tectonics. In the present paper, we have analysed a block close to the epicentre of the 2001 Bhuj earthquake to understand the role of relative active tectonics in the evolution of domal landscape morphology. Shuttle Radar Topographic Mission Digital Elevation Model data were used to extract drainage network in the GIS platform and evaluate active tectonics using different geomorphic indices of the Habo Hill, the second largest domal structure situated in Northern Hill Range of the Kachchh region. The average cumulative weightage of different geomorphic indices provides a quantitative tool, Index of Relative Active Tectonics (IRAT), which shows significant variations in and around the Habo Dome. Activation of earlier lineaments and generation of new lineaments controlled the morphometric evolution of the fault bound block of the region to form the Habo Dome. The undulating topography in addition to the domal shape of the study area resulted from the differential movements along several active transverse faults striking NE–SW, N–S, and NW–SE, and the regional faults striking E–W (the Kachchh Mainland Fault, the Kas Fault, and the Jikadi Fault). Stress propagations from the Himalayan range in the northeast and Suleiman range in the northwest are identified to be the causative factors for active tectonics and drainage anomalies in the area. [ABSTRACT FROM AUTHOR]

Landslides are the natural geomorphic processes that are essential for the landscape development. Loss of tremendous amount of life, natural resources as well as property has made this phenomenon a natural disaster. Number of researches have been done to understand this phenomenon and how to overcome this calamity with the aid of upcoming modern information services and technological advancements. Despite all these, there are still certain undocumented slope failure events due to inaccessibility and lack of a proper database. With the advancement of satellite remote sensing and geographical information system (GIS), it has certainly become easier to monitor and prepare landslide database especially in rough and rugged terrain of the Himalaya for delineation of risk zones. Free availability of high-resolution images and an open source efficient software have certainly been proved advantageous for this purpose. This paper aims at quick and accurate landslide inventory mapping, using high resolution Sentinel 2 data along with normalized difference vegetation index (NDVI), over which unsupervised and object-based image analysis (OBIA) was done to extract landslide features in an efficient manner. Both these processes were achieved with the aid of open source SAGA (System for Automated Geoscientific Analyses) software. The performances of these classifications were analyzed for their quantitative reliability in extracting the landslide features in two different areas (test area 1 and 2). In this, the object based image classification outstands, with the overall accuracy percentage difference of 17.11% higher than pixel-based classification approach in test area 1 and about 21% higher in test area 2. [ABSTRACT FROM AUTHOR]

Complex mountainous environments such as Himalayas are highly susceptibility to natural hazards particular those that are triggered by the action of water such as floods, soil erosion, mass movements and siltation of the hydro-electric power dams. Among all the natural hazards, soil erosion is the most implicit and the devastating hazard affecting the life and property of the millions of people living in these regions. Hence to review and devise strategies to reduce the adverse impacts of soil erosion is of utmost importance to the planners of watershed management programs in these regions. This paper demonstrates the use of satellite based remote sensing data coupled with the observational field data in a multi-criteria analytical (MCA) framework to estimate the soil erosion susceptibility of the sub-watersheds of the Rembiara basin falling in the western Himalaya, using geographical information system (GIS). In this paper, watershed morphometry and land cover are used as an inputs to the MCA framework to prioritize the sub-watersheds of this basin on the basis of their different susceptibilities to soil erosion. Methodology included the derivation of a set of drainage and land cover parameters that act as the indicators of erosion susceptibility. Further the output from the MCA resulted in the categorization of the sub-watersheds into low, medium, high and very high erosion susceptibility classes. A detailed prioritization map for the susceptible sub-watersheds based on the combined role of land cover and morphometry is finally presented. Besides, maps identifying the susceptible sub-watersheds based on morphometry and land cover only are also presented. The results of this study are part of the watershed management program in the study area and are directed to instigate appropriate measures to alleviate the soil erosion in the study area. [ABSTRACT FROM AUTHOR]

The goal of this paper is to evaluate and compare the consistency of GIS-based heuristic and bivariate landslide susceptibility mapping techniques in the Himalayan region, taking the Kulekhani watershed of central Nepal as an example. For this purpose, a heuristic and two statistical bivariate landslide susceptibility mapping methods are applied, and three separate landslide susceptibility zonation maps are produced. The maps are compared using three approaches: landslide density analysis, success rate analysis, and agreed area analysis. A comparison of the values obtained from landslide density analysis and the curves of success rate analysis indicate that the two bivariate methods produce almost identical results, whereas the map produced with the heuristic method differs significantly from the others. On the other hand, the agreed area analysis highlights significant spatial differences in the maps obtained from the three methods. Although the three approaches evaluate the consistency of susceptibility maps, only the agreed area analysis is capable of spatially comparing them. Hence, this approach proves to be more suitable for spatially and quantitatively evaluating the consistency of various landslide susceptibility zonation maps. [ABSTRACT FROM AUTHOR]

Landslide susceptibility maps are modelled either by knowledge-driven methods (qualitative) or data-driven methods (quantitative) depending on apriori expert knowledge or complete landslide inventory data, respectively, which hinders land regulatory authorities from taking quick decisions for land use planning at a regional scale. To overcome these limitations, a new modelling methodology is proposed which can perform equally with the existing established models and needs minimum knowledge of geo-environmental variables without any model testing data. In this method, common variances of the geo-environmental variables are extracted from initially equally weighted variables and are termed as equal weight method (EWM). The extracted common variances are used to weight the variables for the preparation of a landslide susceptibility map on a regional scale. The output of the model can be interpreted to understand the inter-relationship of different geo-environmental variables along with the identification and prioritization of variables on model performance by delineating the non-performing variables. The proposed modelling methodology is tested at the eastern Himalayan road corridor, the result of which is compared with the results of the analytical hierarchy process (qualitative) and frequency ratio (quantitative) modelling methods by area under curve (AUC) of receiver operating characteristic (ROC) curves and cost analysis. AUC of ROC curves for the analytical hierarchy process, frequency ratio method and equal weight method models are 0.755, 0.809 and 0.774, respectively, indicating little performance differences. Cost analysis of all models shows a maximum bounding cost of 0.4 indicating that all models are cost-effective. The study concludes that the equal weight method is quick, robust and cost-effective at par with other well tested knowledge-driven and data-driven methods. [ABSTRACT FROM AUTHOR]

The Mw 7.8 Gorkha earthquake in Nepal on April 25, 2015, produced thousands of landslides in the Himalayan mountain range. After the earthquake, two field investigations along Araniko Highway were conducted. Then, using remote sensing technology and geographic information system (GIS) technology, 1481 landslides were identified along the Bhote Koshi river. Correlations between the spatial distribution of landslides with slope gradient and lithology were analyzed. The power-law relationship of the size distribution of earthquake-induced landslides was examined in both the Higher Himalaya and Lesser Himalaya. Possible reasons for the variability of the power exponent were explored by examining differences in the geological situations of these areas. Multi-threshold cellular automata were introduced to model the complexity of system components. Most of the landslides occurred at slope gradients of 30°-40°, and the landslide density was positively correlated with slope gradient. Landslides in hard rock areas were more common than in soft rock areas. The cumulative number-area distribution of landslides induced by the Gorkha earthquake exhibited a negative power-law relationship, but the power exponents were different: 1.13 in the Higher Himalaya, 1.36 and Lesser Himalaya. Furthermore, the geological conditions were more complex and varied in the Lesser Himalaya than in the Higher Himalaya, and the cellular automata simulation results indicated that, as the complexity of system components increased, the power exponent increased. Therefore, the variability of the power exponent of landslide size distribution should ascribe to the complexity of geological situations in the Bhote Koshi river watershed. [ABSTRACT FROM AUTHOR]

The Himalayan watersheds are susceptible to various forms of degradation due to their sensitive and fragile ecological disposition coupled with increasing anthropogenic disturbances. Owing to the paucity of appropriate technology and financial resources, the prioritization of watersheds has become an inevitable process for effective planning and management of natural resources. Lidder catchment constitutes a segment of the western Himalayas with an area of 1,159.38 km. The study is based on integrated analysis of remote sensing, geographic information system, field study, and socioeconomic data. Multicriteria evaluation of geophysical, land-use and land-cover (LULC) change, and socioeconomic indicators is carried out to prioritize watersheds for natural resource conservation and management. Knowledge-based weights and ranks are normalized, and weighted linear combination technique is adopted to determine final priority value. The watersheds are classified into four priority zones (very high priority, high priority, medium priority, and low priority) on the basis of quartiles of the priority value, thus indicating their ecological status in terms of degradation caused by anthropogenic disturbances. The correlation between priority ranks of individual indicators and integrated indicators is drawn. The results reveal that socioeconomic indicators are the most important drivers of LULC change and environmental degradation in the catchment. Moreover, the magnitude and intensity of anthropogenic impact is not uniform in different watersheds of Lidder catchment. Therefore, any conservation and management strategy must be formulated on the basis of watershed prioritization. [ABSTRACT FROM AUTHOR]

While dealing with slope stability issues, determining the state of stress and the relation between driving force and resisting force are the fundamental deterministic steps. Gravitational stresses affect geologic processes and engineering operations in slopes. Considering this fact, a concept of topo-stress evaluation is developed in this research and used to produce a shallow landslide susceptibility map in a model area. The topo-stress introduced in this research refers to the shear stress induced by the gravitational forces on the planes parallel to the ground surface. Weight of the material on a slope and friction angle of the jointed rock mass are the two fundamental parameters that are considered to govern topo-stress in this study. Considering topo-stress as a main factor for initiating shallow landslides, a GIS-based probabilistic model is developed for shallow landslide susceptibility zonation. An ideal terrain in central Nepal is selected as the study area for this purpose. Two event-based shallow landslide inventories are used to predict accuracy of the model, which is found to be more than 78 % for the first event-landslides and more than 76 % for the second event-landslides. It is evident from these prediction rates that the probabilistic topo-stress model proposed in this work is quite acceptable when regional scale shallow landslide susceptibility mapping is practiced, such as in the Himalayan rocky slopes. [ABSTRACT FROM AUTHOR]

Reservoirs are the key infrastructure for the socio-economic development of a country. The reservoirs are proven to be a remedial solution of highly erratic spatial and temporal availability of water. The growth in population and consequent developmental activities within a catchment area has shown to aggravate the problem of sedimentation which comprised of erosion, sediment transport and its deposition in these reservoirs. Among all above mentioned, reservoir sediment deposition is most important as it reduces its useful life and impairs the purposes of these vast water resource. The sediment yield has been considered as comprehensive index for assessing sustainability of such resources. The present study investigates the suitability of Pacific Southwest Inter-Agency Committee (PSIAC) model in determining the sediment yield rate for a drainage basin considering nine basin factors in geographical information system (GIS) environment. For the analysis, a large river basin at the foothill of Himalayas in India has been considered as case study. It was realized that the GIS approach made large basin characteristic sampling very easy and efficient for this hilly basin. A regression equation between specific sediment yield and effective model factors was established based on geomorphic features for this basin. It was observed that most of the basin area is falling under moderate to high sediment yielding potential zone, leading to high sediment yield. [ABSTRACT FROM AUTHOR]

Land degradation reduces the ability of the land to perform many biophysical and chemical functions. The main aim of this study was to determine the status of land degradation in the Budgam area of Kashmir Himalaya using remote sensing and geographic information system. The satellite data together with other geospatial datasets were used to quantify different categories of land degradation. The results were validated in the field and an accuracy of 85% was observed. Land use/land cover of the study area was determined in order to know the effect of land use on the rate of land degradation. Normalized differential vegetation index (NDVI) and slope of the area were determined using LANDSAT-enhanced thematic mapper plus (ETM+) data, advanced space borne thermal emission and reflection radiometer, and digital elevation model along with other secondary data were analysed to create various thematic maps, viz., land use/land cover, geology, NDVI and slopes used in modelling land degradation in the Kashmir Himalayan region. The vegetation condition, elevation and land use/land cover information of the area were integrated to assess the land degradation scenario in the area using the ArcGIS 'Spatial Analyst Module'. The results reveal that about 13.19% of the study area has undergone moderate to high degradation, whereas about 44.12% of the area has undergone slight degradation. [ABSTRACT FROM AUTHOR]

Assessment of erosion status of a watershed is an essential prerequisite of integrated watershed management. This not only assists in chalking out suitable soil and water conservation measures to arrest erosion and conserve water but also helps in devising best management practices to enhance biomass production in watersheds. The geologic stages of development and erosion proneness of the watersheds are quantified by hypsometric integral. The estimation of hypsometric integral is carried out from the graphical plot of the measured contour elevation and encompassed area and by using empirical formulae. In this study, efforts were made to estimate the hypsometric integral values of the Sainj and Tirthan watersheds and their sub watersheds in the Lesser Himalayas using four different techniques, and to compare the procedural techniques of its estimation and relevance on erosion status. It was revealed that the hypsometric integral calculated by elevation-relief ratio method was accurate, less cumbersome and easy to calculate within GIS environment. Also comparison of these hypsometric integral values revealed that the Sainj watershed (0.51) was more prone to erosion than the Tirthan watershed (0.41). Further, the validation of these results with the recorded sediment yield data of 24 years (1981-2004) corroborated that the average annual sediment yield during this period for Sainj watershed (0.53 Mt) was more than that of the Tirthan watershed (0.3 Mt). Thus, the hypsometric integral value can be used as an estimator of erosion status of watersheds leading to watershed prioritization for taking up soil and water conservation measures in watershed systems. [ABSTRACT FROM AUTHOR]