A Test of Snowmelt-Runoff Model for a Major River Basin in Western Himalayas

Dey, B.; Sharma, Vaibhav; Rango, A.

doi:10.2166/nh.1989.0013

Cited by 36 publications

(24 citation statements)

References 5 publications

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“…Therefore, they cannot be directly used for the projection of extreme events (floods) [14]. A recent study by Lutz et al [15] evaluated 94 GCM runs for RCP4.5 and 69 GCM runs for RCP8.5 for the HKH region using an advanced envelop-based selection approach that is integrated with the past performance of the GCMs. They shortlisted a climate model based on the projected average annual changes in the mean temperature and precipitation sum for the 2071-2100 period over the 1971-2000 period.…”

Section: Gcm and Scenario Selectionmentioning

confidence: 99%

Impact of Climate Change on Flood Frequency and Intensity in the Kabul River Basin

Iqbal

Dahri

Querner³

et al. 2018

Geosciences

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Devastating floods adversely affect human life and infrastructure. Various regions of the Hindukush-Karakoram-Himalayas receive intense monsoon rainfall, which, together with snow and glacier melt, produce intense floods. The Kabul river basin originates from the Hindukush Mountains and is frequently hit by such floods. We analyses flood frequency and intensity in Kabul basin for a contemporary period and two future periods (i.e., 2031-2050 and 2081-2100) using the RCP4.5 and RCP8.5 scenarios based on four bias-corrected downscaled climate models (INM-CM4, IPSL-CM5A, EC-EARTH, and MIROC5). Future floods are modelled with the SWAT hydrological model. The model results suggest an increasing trend due to an increasing precipitation and higher temperatures (based on all climate models except INM-CM4), which accelerates snow and glacier-melt. All of the scenario results show that the current flow with a 1 in 50 year return period is likely to occur more frequently (i.e., 1 in every 9-10 years and 2-3 years, respectively) during the near and far future periods. Such increases in intensity and frequency are likely to adversely affect downstream population and infrastructures. This, therefore, urges for appropriate early precautionary mitigation measures. This study can assist water managers and policy makers in their preparation to adequately plan for and manage flood protection. Its findings are also relevant for other basins in the Hindukush-Karakoram-Himalayas region.

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Section: Gcm and Scenario Selectionmentioning

confidence: 99%

Impact of Climate Change on Flood Frequency and Intensity in the Kabul River Basin

Iqbal

Dahri

Querner³

et al. 2018

Geosciences

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“…Dey et al presented the application of SRM in the Western Himalayas. They used ambient air temperature values from one climate station outside of the basin and degree-day values determined by extrapolating the ambient air temperature to the mean elevation according to certain temperature lapse rates [11]. At the current study, temperature data recorded from five different stations at different elevation levels were applied to obtain zonal temperature by extrapolating the station altitude to mean zone altitude with a certain temperature lapse rate.…”

Section: Inputs Variables and Parametersmentioning

confidence: 99%

Application of Snow Melt Runoff Model in a Mountainous Basin of Iran

Firouzi¹,

Sadeghian²

2016

GEP

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Simulation and modeling the stream flow provide major data while it is a challenge in mountainous basins with regard to the important role of snowmelt runoff as well as the data scarcity in these places. The main purpose of this paper is to examine the capability of an integrated application of remote sensing data and Snowmelt Runoff Model (SRM) to simulate scheme of daily stream flow in the snow-dominated catchment, located in the North-East region of Iran. The main parameters of the model are Snow Cover Area (SCA), temperature and participation. Regarding to the lack of measured data, the input variable and parameters of the model are extracted or estimated based on accessible maps, satellite data and available meteorological and hydrological stations. The changes of snow-cover, as spatial-temporal data, which are the most effective variable in performance of SRM, are obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) eight-day composite snow cover images. The evaluation of the model application efficiency was tested by the coefficient of determination and the volume difference, which are 0.85% and −4.6% respectively. The result depicts the relative capability of SRM though it is evident that the more accurate the estimation of model parameters, the more efficient simulation results can be obtained.

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“…These simple relationships worked well for some applications and particularly in data-sparse regions of the world. Estimation of daily snow melt runoff in the Himalayan river basins using satellite-derived SCA is being increasingly recognized as an immensely useful procedure in water resources research and management (Rango et al 1977;Ramamoorthi and Subba Rao 1981;Gupta et al 1982;Dey et al 1983Dey et al , 1989Dey and Goswami 1984;Jain 2001). The prediction of snow melt induced runoff in the Himalayan rivers has a great potential for application in irrigation, hydropower generation, and domestic and industrial water supply.…”

Section: Introductionmentioning

confidence: 99%