Unraveling the hydrology of a Himalayan catchment through integration of high resolution in situ data and remote sensing with an advanced simulation model

Ragettli, Silvan; Pellicciotti, Francesca; Immerzeel, Walter W.; Miles, Evan; Petersen, Lene; Heynen, Martin; Shea, J. M.; Stumm, D.; Joshi, Srijana; Shrestha, A. B.

doi:10.1016/j.advwatres.2015.01.013

Cited by 160 publications

(264 citation statements)

References 70 publications

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“…In the Himalayas, seasonal Ragettli et al, 2015) or constant (Pokhrel et al, 2014) altitudinal lapse rates (LRs) are used for temperature. Figure 2 presents seasonal LRs computed from temperature time series at the 10 stations described in Sect.…”

Section: Temperaturementioning

confidence: 99%

“…The annual actual evapotranspiration accounted for 26 % of annual total precipitation for Kharikhola and 34 % for Tauche. In comparison, evapotranspiration was estimated at about 20, 14 and 53 % of total annual precipitation, respectively, by Andermann et al (2012), Nepal et al (2014) and Savéan et al (2015) over the entire Dudh Kosi Basin, and Ragettli et al (2015) estimated it at 36.2 % of annual total precipitation for the upper part of the Langtang Basin.…”

Section: Annual Simulated Water Budgetsmentioning

confidence: 99%

“…In the central Himalayas, various hydrologic and glaciological studies are based on observation networks to produce a precipitation grid. However, few studies provide precipitation fields on an hourly timescale (Ragettli et al, 2015;Heynen et al, 2016), and precipitation fields on spatial scales lower than 1 km are always obtained using altitude linear lapse rates Nepal et al, 2014;Pokhrel et al, 2014). However, the considered lapse rates are constant in time and/or uniform in space.…”

Section: Model Of Orographic Precipitationmentioning

confidence: 99%

“…However, these products are not accurate enough at the resolution required for this study. The most recent analysis (Bharati et al, 2014;Ragettli et al, 2015) exclusively used knowledge garnered from the literature. To detail the approach, in this study the parametrization was based on in situ measurements.…”

Section: Parametrization Of Surfacesmentioning

confidence: 99%

“…Annual snowfall was estimated at, respectively, 15.6 and 51.4 % of annual total precipitation by Savéan et al (2015) (entire Dudh Kosi River basin) and Ragettli et al (2015) (upper part of the Langtang Basin).…”

Section: Annual Simulated Water Budgetsmentioning

confidence: 99%

See 4 more Smart Citations

Providing a non-deterministic representation of spatial variability of precipitation in the Everest region

Eeckman¹,

Chevallier²,

Boone³

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. This paper provides a new representation of the effect of altitude on precipitation that represents spatial and temporal variability in precipitation in the Everest region. Exclusive observation data are used to infer a piecewise linear function for the relation between altitude and precipitation and significant seasonal variations are highlighted. An original ensemble approach is applied to provide non-deterministic water budgets for middle and high-mountain catchments. Physical processes at the soilatmosphere interface are represented through the Interactions Soil-Biosphere-Atmosphere (ISBA) surface scheme. Uncertainties associated with the model parametrization are limited by the integration of in situ measurements of soils and vegetation properties. Uncertainties associated with the representation of the orographic effect are shown to account for up to 16 % of annual total precipitation. Annual evapotranspiration is shown to represent 26 % ± 1 % of annual total precipitation for the mid-altitude catchment and 34% ± 3 % for the high-altitude catchment. Snowfall contribution is shown to be neglectable for the mid-altitude catchment, and it represents up to 44 % ± 8 % of total precipitation for the highaltitude catchment. These simulations on the local scale enhance current knowledge of the spatial variability in hydroclimatic processes in high-and mid-altitude mountain environments.

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Section: Temperaturementioning

confidence: 99%

Section: Annual Simulated Water Budgetsmentioning

confidence: 99%

Section: Model Of Orographic Precipitationmentioning

confidence: 99%

Section: Parametrization Of Surfacesmentioning

confidence: 99%

Section: Annual Simulated Water Budgetsmentioning

confidence: 99%

See 3 more Smart Citations

Providing a non-deterministic representation of spatial variability of precipitation in the Everest region

Eeckman¹,

Chevallier²,

Boone³

et al. 2017

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

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High‐resolution modeling of atmospheric dynamics in the Nepalese Himalaya

2015

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High-altitude meteorological processes in the Himalaya are influenced by complex interactions between the topography and the monsoon and westerly circulation systems. In this study, we use the Weather Research and Forecasting model configured with high spatial resolution to understand seasonal patterns of near-surface meteorological fields and precipitation processes in the Langtang catchment in the central Himalaya. Using a unique high-altitude observational network, we evaluate a simulation from 17 June 2012 to 16 June 2013 and conclude that, at 1 km horizontal grid spacing, the model captures the main features of observed meteorological variability in the catchment. The finer representation of the complex terrain and explicit simulation of convection at this grid spacing give strong improvements in near-surface air temperature and small improvements in precipitation, in particular in the magnitudes of daytime convective precipitation and at higher elevations. The seasonal differences are noteworthy, including a reversal in the vertical and along-valley distributions of precipitation between the monsoon and winter seasons, with peak values simulated at lower altitudes (~3000 m above sea level (asl)) and in the upper regions (above 5000 m asl) in each season, respectively. We conclude that there is great potential for improving the local accuracy of climate change impact studies in the Himalaya by using high-resolution atmospheric models to generate the forcing for such studies.

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Effects of input discretization, model complexity, and calibration strategy on model performance in a data‐scarce glacierized catchment in Central Asia

Tarasova

Knoche

Dietrich³

et al. 2016

Water Resources Research

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Glacierized high‐mountainous catchments are often the water towers for downstream region, and modeling these remote areas are often the only available tool for the assessment of water resources availability. Nevertheless, data scarcity affects different aspects of hydrological modeling in such mountainous glacierized basins. On the example of poorly gauged glacierized catchment in Central Asia, we examined the effects of input discretization, model complexity, and calibration strategy on model performance. The study was conducted with the GSM‐Socont model driven with climatic input from the corrected High Asia Reanalysis data set of two different discretizations. We analyze the effects of the use of long‐term glacier volume loss, snow cover images, and interior runoff as an additional calibration data. In glacierized catchments with winter accumulation type, where the transformation of precipitation into runoff is mainly controlled by snow and glacier melt processes, the spatial discretization of precipitation tends to have less impact on simulated runoff than a correct prediction of the integral precipitation volume. Increasing model complexity by using spatially distributed input or semidistributed parameters values does not increase model performance in the Gunt catchment, as the more complex model tends to be more sensitive to errors in the input data set. In our case, better model performance and quantification of the flow components can be achieved by additional calibration data, rather than by using a more distributed model parameters. However, a semidistributed model better predicts the spatial patterns of snow accumulation and provides more plausible runoff predictions at the interior sites.

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Unraveling the hydrology of a Himalayan catchment through integration of high resolution in situ data and remote sensing with an advanced simulation model

Cited by 160 publications

References 70 publications

Providing a non-deterministic representation of spatial variability of precipitation in the Everest region

Providing a non-deterministic representation of spatial variability of precipitation in the Everest region

High‐resolution modeling of atmospheric dynamics in the Nepalese Himalaya

Effects of input discretization, model complexity, and calibration strategy on model performance in a data‐scarce glacierized catchment in Central Asia

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