A reevaluation of the snowmelt and glacial melt in river flows within Upper Indus Basin and its significance in a changing climate

Mukhopadhyay, Biswajit; Khan, Asif

doi:10.1016/j.jhydrol.2015.04.045

Cited by 110 publications

(72 citation statements)

References 27 publications

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“…These higher correlations in the late Kharif (relative to the early Kharif) for Indus at Tarbela could be related to the correspondingly higher relative skill scores shown in Fig. 3 for late Kharif, corresponding to late-season glacier melt processes that are a significant component of the inflow to Tarbela but not Mangla (Mukhopadhyay and Khan, 2015). Future research could investigate whether dynamical seasonal forecasts of temperature have skill of relevance to forecasting glacier melt; however, as noted above such skill has not been determined to date (e.g.…”

Section: Discussionmentioning

confidence: 92%

“…Sufficiently skilful BJP forecasts could also inform scenario selection, providing for the first time a probabilistic approach to forecasts in contrast to a single forecast as currently used. However probabilistic forecasts (such as the BJP) can be misinterpreted if the water management professionals using them to inform decisions are unfamiliar with them (Pagano et al, 2002;Ramos et al, 2013;Rayner et al, 2005;Whateley et al, 2015). Hence the successful transfer of BJP forecast tools to operational use within Pakistan would require guidance for building BJP models and generating forecasts, test cases with example results, face-to-face training and on-going support.…”

Section: Resultsmentioning

confidence: 99%

“…The Tarbela Dam on the main stem of the Indus is one of the largest individual storages in the UIB, crucial for hydropower generation and irrigation supply (Ahmed and Sanchez, 2011). Annual inflows to Tarbela constitute 70 % melt water, of which snowmelt contributes 44 % and glacial melt contribute 26 % (Mukhopadhyay and Khan, 2015). The Mangla Dam on the Jhelum River is (since enlargement) a similarly sized storage as Tarbela and one of the most important resources in Pakistan for electricity generation and water supply for irrigation (Mahmood et al, 2015).…”

Section: Upper Indus Basinmentioning

confidence: 99%

“…WAPDA has procured a version of SRM implemented in Excel © , "ExcelSRM", and for their 2012 case study for Jhelum inflow into the Mangla Reservoir (NESPAK et al, 2012), Excel-SRM was calibrated using data for 2003 to 2010 and subsequently validated against inflows for 2000 to 2002(Bogacki and Ismail, 2016. In contrast to the probabilistic forecasts produced by the BJP, the SRM is a deterministic model and so produces a single forecast for a given set of inputs.…”

Section: Srm Forecasting Modelmentioning

confidence: 99%

“…. in order to keep parameters at smooth values and to maintain a reasonable trend in time" (NESPAK et al, 2012). The mean flow simulations obtained from driving each year's SRM with all years' available precipitation and temperature are therefore not independent forecasts, and so it is not surprising that for the 2003 to 2010 period the SRM forecasts are closer to the observed flows than the median cross-validated BJP estimates.…”

Section: Verificationmentioning

confidence: 99%

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Seasonal streamflow forecasting in the upper Indus Basin of Pakistan: an assessment of methods

Charles

Wang

Ahmad

et al. 2018

Hydrol. Earth Syst. Sci.

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Abstract. Timely and skilful seasonal streamflow forecasts are used by water managers in many regions of the world for seasonal water allocation outlooks for irrigators, reservoir operations, environmental flow management, water markets and drought response strategies. In Australia, the Bayesian joint probability (BJP) statistical approach has been deployed by the Australian Bureau of Meteorology to provide seasonal streamflow forecasts across the country since 2010. Here we assess the BJP approach, using antecedent conditions and climate indices as predictors, to produce Kharif season (AprilSeptember) streamflow forecasts for inflow to Pakistan's two largest upper Indus Basin (UIB) water supply dams, Tarbela (on the Indus) and Mangla (on the Jhelum). For Mangla, we compare these BJP forecasts to (i) ensemble streamflow predictions (ESPs) from the snowmelt runoff model (SRM) and (ii) a hybrid approach using the BJP with SRM-ESP forecast means as an additional predictor. For Tarbela, we only assess BJP forecasts using antecedent and climate predictors as we did not have access to SRM for this location. Cross validation of the streamflow forecasts shows that the BJP approach using two predictors (March flow and an El Niño Southern Oscillation, ENSO, climate index) provides skilful probabilistic forecasts that are reliable in uncertainty spread for both Mangla and Tarbela. For Mangla, the SRM approach leads to forecasts that exhibit some bias and are unreliable in uncertainty spread, and the hybrid approach does not result in better forecast skill. Skill levels for Kharif (April-September), early Kharif (April-June) and late Kharif (July-September) BJP forecasts vary between the two locations. Forecasts for Mangla show high skill for early Kharif and moderate skill for all Kharif and late Kharif, whereas forecasts for Tarbela also show moderate skill for all Kharif and late Kharif, but low skill for early Kharif. The BJP approach is simple to apply, with small input data requirements and automated calibration and forecast generation. It offers a tool for rapid deployment at many locations across the UIB to provide probabilistic seasonal streamflow forecasts that can inform Pakistan's basin water management.

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Section: Discussionmentioning

confidence: 92%

Section: Resultsmentioning

confidence: 99%

Section: Upper Indus Basinmentioning

confidence: 99%

Section: Srm Forecasting Modelmentioning

confidence: 99%

Section: Verificationmentioning

confidence: 99%

See 3 more Smart Citations

Seasonal streamflow forecasting in the upper Indus Basin of Pakistan: an assessment of methods

Charles

Wang

Ahmad

et al. 2018

Hydrol. Earth Syst. Sci.

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Precipitation‐driven glacier changes in the Pamir and Hindu Kush mountains

Wang

Sun

2017

Geophysical Research Letters

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Glaciers in the Pamir‐Hindu Kush‐Karakoram appear to be less influenced by global warming and have instead experienced slight gains in mass, unlike most other glaciers around the world. Here we apply laser altimetry and satellite‐derived precipitation products to characterize the relationship between the glaciers and precipitation. We found a strong correlation (r ≥ 0.92, p < 0.005) between the year‐to‐year changes in glacier thickness and precipitation in the Pamir and Hindu Kush from 2003 to 2008, indicating the primary role of precipitation in the glacier changes. The amount of precipitation in the glacial region is underestimated by approximately 7 ± 2 times in the gridded precipitation product. This underestimation is attributed to the low resolution and lack of orographic precipitation in the gridded products. The long‐term precipitation data show strong interannual variations, which probably cause similar variations in glaciers and biases in previous glacier mass change estimates.

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A joint analysis of river runoff and meteorological forcing in the Karakoram, upper Indus Basin

Reggiani

Mukhopadhyay

Rientjes

et al. 2016

Hydrological Processes

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Satellite‐geodetic altimetry investigations in the Karakoram have indicated slight mass gain or loss of the glaciers during the early part of 21st century. Equivalent discharge in the upper Indus Basin due to these mass changes has been estimated at 5 to 10% of mean annual flow. However, satellite altimetry and geodetic glacier mass estimates in the extreme topography of the Karakoram have not yet been counter‐validated by hydrological analysis. Therefore, we present a first cross validation of three to five decades of river flow data from the three major watersheds in the Karakoram, with matching series of monthly precipitation, temperature, and evaporation provided by six atmospheric reanalysis products for 1979–2014. The analyses suggest that in most cases river flows have been increasing steadily from the end of the 1960s and 1970s to the middle of the 1990s and have stabilized or are in decline since then. Hunza watershed in Karakoram West shows consistently declining flows over the first half of the analysis period and stable flows during the second half for most of the summer melting season, suggesting mass accumulation. Rising river flows in the Shyok and Shigar watersheds, followed by stabilizing or slightly declining flows from 1995 onward, can be explained by consistently increasing precipitation during the first half of the analysis period, and successive stabilization or minor decline thereof. Flow data do not necessarily suggest considerable loss or gain of glacial mass in the Karakoram during the late 90s and early 2000s as suggested by satellite‐based altimetry studies.

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A reevaluation of the snowmelt and glacial melt in river flows within Upper Indus Basin and its significance in a changing climate

Cited by 110 publications

References 27 publications

Seasonal streamflow forecasting in the upper Indus Basin of Pakistan: an assessment of methods

Seasonal streamflow forecasting in the upper Indus Basin of Pakistan: an assessment of methods

Precipitation‐driven glacier changes in the Pamir and Hindu Kush mountains

A joint analysis of river runoff and meteorological forcing in the Karakoram, upper Indus Basin

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