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Hydrological Modeling and Climate Change Impact Assessment using HBV-Light Model: A Case Study of Karnali River Basin of Nepal

IWRA World Water Congress 2017 - Cancun Mexico
5. Water ecosystems and physical regimes
Author(s): Sagar Shiwakoti
Sagar Shiwakoti
Hydroelectricity Investment and Development Company Limited
sagar.shiwakoti111@gmail.com


Keyword(s): HBV, Climate Change, Hydrological Modeling, Snowmelt Contribution
Article:

Abstract

This study has been performed to predict the impacts of climate change on the runoff pattern of the snow-fed Karnali River Basin of Far-Western Nepal, with an area of 127,950 km2 and elevation ranging from 140 m to 7498 m. Work has also been done to estimate snowmelt contribution to streamflow and its variation in increased temperatures. The future climatic Had CM3 GCM (Hadley Center, General Circulation Model) scenario developed using the 'Providing Regional Climate for Impact Studies-Regional Climate Model' (PRECIS-RCM, a climate modeling system developed by the Hadley Centre, UK Met Office) has been forced into the Hydrologiska Byråns Vattenbalansavdelning (HBV) model to estimate future river discharge of the basin. HBV, developed by Dr. Sten Bergström at Swedish Meteorological and Hydrological Institute in the 1970s, is a conceptual precipitation-runoff model used to simulate runoff based on precipitation, air temperature and potential evapotranspiration data. It has been extensively used for runoff modeling in many countries including Nepal. It estimates snowmelt based on the degree-day method and computes snow accumulation, ground water storage and catchment runoff. Model calibration has been done by the Generalized Likelihood Uncertainty Estimation method by applying it to the basin with relevant ground information and refined hydro-meteorological data available from 1963 to 2008.

Analyzing the model performance indicates its suitability to simulate streamflow in the catchment with values of Nash Sutcliffe efficiency upto 0.85 during calibration and upto 0.87 during validation. Due to its structural complexity, the model shows difficulties in simultaneously modeling low and high flows accurately. Low flows are generally underestimated and peaks are correctly estimated except for some sharp peaks due to isolated precipitation events. Contribution of snowmelt to annual flow has been estimated to be the highest (30%) at the beginning of May, as the accumulated snow begins to melt and lowest (2%) in January.  Examination of this contribution under conditions of increased temperatures indicates that increase in average basin temperature due to global warming will significantly lead to higher snowmelt contribution to runoff. Rise in temperature by 1.5ºC causes increase in snowmelt contribution from 22% to 30% at the basin outlet in summer and from 11% to 17% annually. Running the model with the HadCM3 GCM (A1B scenario) downscaled to the station level indicates significantly wetter months in the 2040s. It is observed that runoff will increase by 3% to 250% in various months as compared to the control period. The impact will be highly pronounced in the flooding season. Shift in hydrological regime is also indicated by the movement of peak flow. This may have consequence on water abstraction activities, leading to changes in cropping patterns, electricity production and supply of drinking water in the basin, which will have impacts on the economy of the region. 

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