Improving ANN-based streamflow estimation models for the Upper Indus Basin using satellite-derived snow cover area

This study considered glacier and snow meltwater by using the degree–day method with ground-based air temperature and fractional glacier/snow cover to simulate discharge at Skardu, Partab Bridge (P. Bridge), and Tarbela Dam in the Upper Indus Basin during the monsoon season, from the middle of June to the end of September. The optimum parameter set was determined and validated in 2010 and 2012. The simulated discharge with glaciermelt and snowmelt could capture the variations of the observed discharge in terms of peak volume and timing, particularly in the early monsoon season. The Moderate Resolution Imaging Spectroradiometer (MODIS) daily and eight-day snow cover products were applied and recommended with proper settings for application. This study also investigated the simulations with snow packs instead of daily snow cover, which was found to approach the maximum magnitude of observed discharge even from the uppermost station, Skardu.This study estimated the glacier and snow meltwater contribution at Skardu, Partab Bridge, and Tarbela as 43.2–65.2%, 22.0–29.3%, and 6.3–19.9% of average daily discharge during the monsoon season, respectively. In addition, this study evaluated the main source of simulation discrepancies and concluded that the methodology proposed in the study worked well with proper precipitation.

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Changes in Snow Cover Dynamics over the Indus Basin: Evidences from 2008 to 2018 MODIS NDSI Trends Analysis

Remote Sensing ◽

10.3390/rs12172782 ◽

2020 ◽

Vol 12 (17) ◽

pp. 2782

Author(s):

Sikandar Ali ◽

Muhammad Jehanzeb Masud Cheema ◽

Muhammad Mohsin Waqas ◽

Muhammad Waseem ◽

Usman Khalid Awan ◽

...

Keyword(s):

Time Series ◽

Snow Cover ◽

River Basins ◽

Google Earth ◽

Indus Basin ◽

Least Squares Regression ◽

Snow Cover Area ◽

Standard Product ◽

Moderate Resolution Imaging Spectroradiometer ◽

Normalized Difference Snow Index

The frozen water reserves on the Earth are not only very dynamic in their nature, but also have significant effects on hydrological response of complex and dynamic river basins. The Indus basin is one of the most complex river basins in the world and receives most of its share from the Asian Water Tower (Himalayas). In such a huge river basin with high-altitude mountains, the regular quantification of snow cover is a great challenge to researchers for the management of downstream ecosystems. In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) daily (MOD09GA) and 8-day (MOD09A1) products were used for the spatiotemporal quantification of snow cover over the Indus basin and the western rivers’ catchments from 2008 to 2018. The high-resolution Landsat Enhanced Thematic Mapper Plus (ETM+) was used as a standard product with a minimum Normalized Difference Snow Index (NDSI) threshold (0.4) to delineate the snow cover for 120 scenes over the Indus basin on different days. All types of errors of commission/omission were masked out using water, sand, cloud, and forest masks at different spatiotemporal resolutions. The snow cover comparison of MODIS products with Landsat ETM+, in situ snow data and Google Earth imagery indicated that the minimum NDSI threshold of 0.34 fits well compared to the globally accepted threshold of 0.4 due to the coarser resolution of MODIS products. The intercomparison of the time series snow cover area of MODIS products indicated R2 values of 0.96, 0.95, 0.97, 0.96 and 0.98, for the Chenab, Jhelum, Indus and eastern rivers’ catchments and Indus basin, respectively. A linear least squares regression analysis of the snow cover area of the Indus basin indicated a declining trend of about 3358 and 2459 km2 per year for MOD09A1 and MOD09GA products, respectively. The results also revealed a decrease in snow cover area over all the parts of the Indus basin and its sub-catchments. Our results suggest that MODIS time series NDSI analysis is a useful technique to estimate snow cover over the mountainous areas of complex river basins.

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Early 21st century climatology of snow cover for the western river basins of the Indus River System

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-10-13145-2013 ◽

2013 ◽

Vol 10 (11) ◽

pp. 13145-13190 ◽

Cited By ~ 6

Author(s):

S. Hasson ◽

V. Lucarini ◽

M. R. Khan ◽

M. Petitta ◽

T. Bolch ◽

...

Keyword(s):

Snow Cover ◽

River System ◽

River Basins ◽

Indus Basin ◽

Lower Latitude ◽

Climate Data ◽

Indus River ◽

Early 21St Century ◽

Upper Indus Basin ◽

Area Of Interest

Abstract. In this paper we assess the snow cover and its dynamics for the western river basins of the Indus River System (IRS) and their sub-basins located in Afghanistan, China, India and Pakistan for the period 2001–2012. Moderate Resolution Imaging Spectro-radiometer (MODIS) daily snow products from Terra (MOD) and Aqua (MYD) have been first improved and then analysed on seasonal and annual basis against different topographic parameters (aspect, elevation and slope). Our applied cloud filtering technique has reduced the cloud cover from 37% (MOD) and 43% (MYD) to 7%, thus improving snow cover estimates from 7% (MOD) and 5% (MYD) to 14% for the area of interest (AOI) during the validation period (2004). Our results show a decreasing tendency for the annual average snow cover for the westerlies-influenced basins (Upper Indus Basin, Astore, Hunza, Shigar, Shyok) and an increasing tendency for the monsoon-influenced basins (Jhelum, Kabul, Swat and Gilgit). Regarding the seasonal snow cover, decrease during winter and autumn and increase during spring and summer has been found, which is consistent with the observed cooling and warming trends during the respective seasons. Sub-basins at relatively higher latitude/altitude show higher variability than basins at lower latitude/mid-altitude. Northeastern and northwestern aspects feature larger snow cover. The mean regional snow line altitude (SLA) zones range between 3000 and 5000 m a.s.l. for all basins. Our analysis provides an indication of a decrease in the regional SLA zone, thus indicating a change in the water resources of the studied basins, particularly for the Upper Indus Basin (UIB). Such results are consistent with the observed hydro-climate data, recently collected local perceptions and glacier mass balances for the investigated period. Moreover, our analysis suggests some potential for the seasonal stream flow forecast as a significant negative correlation has been detected for the inter-annual variability of winter snow cover and value of the North Atlantic Oscillation (NAO) index of the previous autumn.

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INVESTIGATION OF CRYOSPHERE DYNAMICS VARIATIONS IN THE UPPER INDUS BASIN USING REMOTE SENSING AND GIS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xliv-3-w1-2020-59-2020 ◽

2020 ◽

Vol XLIV-3/W1-2020 ◽

pp. 59-63

Author(s):

J. Iqbal ◽

M. Ali ◽

A. Ali ◽

D. Raza ◽

F. Bashir ◽

...

Keyword(s):

Climate Change ◽

Remote Sensing ◽

Mass Balance ◽

Snow Cover ◽

Landsat Imagery ◽

Low Cost ◽

Melting Rate ◽

Indus Basin ◽

Upper Indus Basin ◽

Snow Mass

Abstract. Glaciers are storehouses for freshwater. Glaciers Monitoring is one of the most important research areas especially when climate change has been accelerated snowmelt process. The major goal of research was to find snow cover trend for glaciated regions of Pakistan followed by estimation of snow mass balance. The area chosen for it was Upper Indus basin, which includes ranges of Hindukush, Karakoram and Himalayas extended in Pakistan, India and China. This region exhibits high topographic relief and climate change variability. Snow cover trend analysis was performed for eleven years ranging from 2004 to 2014 using Moderate Resolution Imaging Spectroradiometer (MODIS) data imagery product with daily temporal resolution. These results were combined with respective year’s average monthly temperature. Further quantitative analysis was performed to relate presence of greater vegetation as an indication of greater snowmelt using Landsat Imagery for these years. Snow mass balance curves reveal that glaciers are regaining their mass balance after losing mass balance in middle of last decade. In addition to that, only freely available data is used for this study. This purpose behind this approach is to prove RS and GIS has an effective and low-cost tool for snow cover monitoring, also mass balance calculations. Continuous monitoring of snow cover dynamics is effective for prediction and mitigation of hazards associated with areas in proximity of glaciated regions. One common hazard is glacial lake outburst phenomenon, which cause severe flash flooding in downstream areas. Year 2004 has the lowest mass snow balance and 2014 has the highest snow mass balance. These different parameters were analysed and results show that snow start melting in months of May and June and faster melting rate observed in months of July and August. With the advancement in computing technologies, it has been easier for computers to handle and manipulate massive datasets. Remote sensing has proved to be an excellent tool for extraction of data from glaciers, snow and oceans for remote areas. In particular, snow cover/snowmelt can tell us continuously changing melting patterns, which helps concerned authorities to take necessary measures for preserving these storehouses of water and to mitigate effect of global warming.

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