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1

Temporal variation of seismic b‑value in the Himalayas and foreland region and its implications on crustal stress variability

Chetia Monisha, Gogoi Priti Rekha, Lahiri Siddhartha Kumar

Acta Geophysica

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2023

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Vol. 71, no. 4

1675--1692

EN

The temporal variation of seismic b-values during 1964–2020 was investigated for the Himalayas and foreland lying between 69°E-98°E and 21°N-36°N covering a range of more than 3000 km in five different time windows; 1964–1974, 1975–1985, 1986–1996, 1997–2007, and 2008–2020. The b-values show a very significant variation from 0.4 to 3.3. Seismically active areas are either in the phase of incubation or the phase of trigger indicating stress accumulation punctuated release. Since each jump in the magnitude of earthquakes is associated with a logarithmic decrease in frequency, an incubation period can be treated as the occurrence of a large number of low-magnitude earthquakes (cumulative energy released is much smaller than a single big trigger); hence, large b-value and the vice-versa. Thus the low b-value anomaly zones may be regarded as high-stress accumulation zones approaching the phase of triggering. The study area was divided into six type zones based on geological, gravity and DEM (Digital Elevation Model) data. As expected, most of the large-magnitude earthquakes were seen to have occurred in the low b-value regions. A comparative study of variation in b-values with depth for two windows, the western Himalayan syntaxis and the Indo-Burma range shows differences in the stress accumulation and the triggering potential for different ranges of depths. The study reveals that in the central Himalayas and its adjoining region large-magnitude earthquakes are due in the near future as crustal stress accumulation is high in these zones.

2

The role of orographic barriers in the origin of extreme rainfalls as exemplified by the front of high Eastern Himalaya and the low northern slope of Carpathians

Cebulak E., Gębica P., Limanówka D., Starkel L., Pyrc R.

Landform Analysis

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2018

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Vol. 36

9--17

EN

The paper discusses the role of orographic barriers in generating torrential precipitation in mountainous regions in different climatic zones, the Eastern Himalayas (tropical zone with well-developed monsoon activity) and the northern slope of the Carpathians (temperate zone with transitional climate). Attention has been paid to the different altitudes and courses of the orographic ridges as well as their location relative to the prevailing directions of influx of moist air masses. The cases analysed included torrential rains with monsoon circulation from the S–SW direction at the 2–3 km high edge of the Himalayas, with special consideration to the distance from the margin of the mountains and the exposure of the slopes. They generate frequent flood waves, landslides, debris flows and upbuilding of the alluvial cones in the foreland of the mountain barriers. The impact of the orographic barrier is significantly less marked in the Polish Carpathians. In the western part, the compact edge of the Western Beskids with an altitude of 0.5–1 km and the WSW–NEE course, exposed to moist air masses inflowing from the northern sector, is fragmented eastward into smaller mountain groups, which facilitates the penetration of moist masses of air with occurrence of prolonged precipitation into the mountains. At times, the storm cloud moves along the mountain edge (the margin of the Western Bieszczady Mts.). The marginal scarp of the Foothills has a northern exposure and a height of 150–200 m, and promotes frequent convective precipitation causing local flash floods in small streams. The cases of downpours and high discharges selected for the analysis were those for which there was available a dense network of measuring stations. An insufficient number of stations in constructing precipitation maps based on interpolation would lead to distorting the spatial image. If this were the case, then the role of slope exposure, which has an essential impact on the distribution of precipitation in mountainous regions, would be completely neglected.

3

Reservoir's impact on the water chemistry of the Teesta River mountain course (Darjeeling Himalaya)

Wiejaczka Ł., Prokop P., Kozłowski R., Sarkar S.

Ecological Chemistry and Engineering. S

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2018

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Vol. 25, nr 1

73--88

EN

The article presents the role of the newly built reservoir in the formation of the hydrochemistry of water of the Teesta River (a tributary of the Brahmaputra) in its Himalayan course. Field research were performed in the post-monsoon season of the period 2013-2015. Sampling and measuring points were located in five points over 43 km of the Teesta River in the Darjeeling Himalaya. Analysis of water along of river longitudinal profile above and below the reservoir suggest that the reservoir caused decrease most of the basic ions concentrations (Cl−, K+, Na+, Mg2+, NO3− and PO43−). An inverse trend was observed only with respect to Ca2+, SO42− and NH4+. The dam does not influent on the F− concentration. The reservoir causes minor enrichment most of the heavy metals such Cu, Ni, Zn, Cr, Cd and Sr. The lower enrichment of Teesta water below the dam indicates the water self-purification processes for metals by the Teesta Reservoir. The changes of physicochemical properties and concentrations of ions caused by the reservoir are usually normalised by environmental factors before the Teesta River outlet from the Himalayas (within 15 km of the river).

4

A geotouristic valuation of the Marsyangdi Valley in the Annapurna Himal region and its potential for the development of geotourist attractions

Łach J.

Geotourism / Geoturystyka

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2015

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nr 3-4

39--56

EN

The Marsyangdi Valley in the Annapurna Himal region is one of the most popular tourist-trekking attractions in Nepal. The performed evaluation of geotourist (geomorphological and hydrographic) objects and phenomena demonstrated a wide range of forms and, correspondingly, a huge potential for the development of geotourist attractions. The structure of The Marsyangdi Valley, which is a representative of a valley region of the High Himalaya, situated on metamorphic rocks, shows the co-existence of three major geomorphic processes: glacial, fluvial and slope, which determine specific landscape forms. Since the late 20th century, the landscape has been heavily affected by anthropogenic factors (grazing, land cultivation, settlement), reaching as far as 3500 meters above sea level, as well as by the dynamic growth and development of tourism. Expanding tourist infrastructure contributes to, inter alia, the degradation of the narrow valley bottom (tourist accommodation) and to increased mass movement on tourist trails. Despite its negative effects, tourism also exerts a positive influence on the preservation of the cultural heritage (sacred sites), which largely dominate the landscape and are a significant tourist attraction. The research was instrumental in defining the Marsyangdi Valley, characteristic of a geomorphological trail, as an excellent and qualified attraction in geotourist-exploratory tourism.

PL

Dolina Marsyangdi należąca do regionu Annapurny Himal jest jedną z najpopularniejszych atrakcji turystycznych – trekkingowych Nepalu. Przeprowadzona pod kątem obiektów i zjawisk geoturystycznych (geomorfologicznych i hydrograficznych) ocena ukazała jej dużą różnorodność form, a tym samym duży potencjał atrakcji geoturystycznych. W strukturze doliny Marsyangdi, będącej przykładem dolin obszaru Himalajów Wysokich, wyróżniono współistnienie trzech głównych procesów geomorfologicznych: glacjalnych, fluwialnych i stokowych, warunkujących specyficzne formy o wysokich walorach krajobrazowych, które od końca XX wieku podlegają szybkiej destrukcji w wyniku antropopresji. Czynniki antropogeniczne tj. hodowla, uprawa, czy osadnictwo sięgające nawet do 3500 m n.p.m., a obecnie jeszcze turystyka, przyczyniają się do wzrostu aktywności procesów geomorfologicznych m.in. ruchów masowych, w tym na szlakach turystycznych. Jednakże oprócz negatywnego wpływu turystyki na uwagę zasługuje jej pozytywne oddziaływanie w szczególności w kwestii ochrony dziedzictwa kulturowego, czego przykładem są odnawiane obiekty sakralne stanowiące niezwykłą dominantę krajobrazu oraz istotną atrakcję turystyczną. Badania pozwoliły zdefiniować obszar Doliny Marsyangdi jako odpowiedni do uprawiania turystyki kwalifikowanej, poznawczej – geoturystyki.

5

Comparison of machine learning methods for runoff forecasting in mountainous watersheds with limited data

Adamowski J., Prasher S. O.

Journal of Water and Land Development

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2012

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no. 17 [VII-XII]

89-97

EN

Runoff forecasting in mountainous regions with processed based models is often difficult and inaccurate due to the complexity of the rainfall-runoff relationships and difficulties involved in obtaining the required data. Machine learning models offer an alternative for runoff forecasting in these regions. This paper explores and compares two machine learning methods, support vector regression (SVR) and wavelet networks (WN) for daily runoff forecasting in the mountainous Sianji watershed located in the Himalayan region of India. The models were based on runoff, antecedent precipitation index, rainfall, and day of the year data collected over the three year period from July 1, 2001 and June 30, 2004. It was found that both the methods provided accurate results, with the best WN model slightly outperforming the best SVR model in accuracy. Both the WN and SVR methods should be tested in other mountainous watershed with limited data to further assess their suitability in forecasting.

PL

Prognozowanie spływu z obszarów górskich z użyciem programowanych modeli jest często trudne i niedokładne z powodu złożonych zależności między opadem a spływem i problemów związanych z pozyskaniem niezbędnych danych. Modele uczenia maszynowego stwarzają alternatywę dla prognozowania spływu z takich regionów. W pracy analizowano i porównano dwie metody uczenia maszynowego - metodę regresji wektorów nośnych (SVR) i sieci falkowych (WN) do dobowego prognozowania spływu w górskiej zlewni Sianji, usytuowanej w indyjskiej części Himalajów. Modele opracowano na podstawie danych o spływie, wskaźniku poprzednich opadów, opadzie i kolejnym dniu roku za trzyletni okres od 1 lipca 2001 r. do 30 czerwca 2004 r. Stwierdzono, że obie metody zapewniają dokładne wyniki, przy czym najlepszy model WN nieco przewyższa najlepszy model SVR pod względem dokładności. Obie metody powinny być testowane w innych zlewniach górskich o ograniczonej liczbie danych, aby lepiej ocenić ich przydatność do prognozowania.

6

Prediction of seismicity cycles in the Himalayas using artificial neural network

Sharma M. L., Arora M. K.

Acta Geophysica Polonica

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2005

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Vol. 53, nr 3

299-309

EN

In this paper, cyclic behaviour of seismicity cycles in the Himalayas has been exploited to predict the future earthquake activity using Artificial Neural Network (ANN). The Himalayan region has been divided into six seismogenic zones. A feed forward multi-layer ANN has been used to evaluate the seismicity fluctuation in the time series containing data from historical times to 1998 for each zone. The most widely used Back Propagation Algorithm (BPA) is applied to train the neural network. BPA iteratively minimises an error function over the network outputs and a set of target outputs taken from the training data set. The results show that the probability of occurrence of moderate to great earthquake in next 50 years is relatively lower in the Hindukush-Pamirs zone. Since the intense release of energy will take place in the Kashmir-Himachal Pradesh zone, between 2030 to 2055, the probability of occurrence of moderate to great earth-quake is higher. The accumulation of energy stage is still going on in the India -Western Nepal Border zone, and there will be an increase in seismic activity after 2030 for the next 50 years. The hazard parameters could not be estimated for the Nepal-India-Sikkim Border zone because of lesser number of data to capture cyclic behaviour. In NE India, intense release and remnant release will take place up to 2030 due to which there will be an increase in the probability of occurrence of moderate to great earthquake in this zone. In Burma-Andaman Nicobar, the energy accumulation stage for the next cycle has started in 1990 and will continue till 2020.