Hydrologiska Byrans Vattenbalansavdeling(HBV) Light model was used to evaluate the performance of the model in response to climate change in the snowy and glaciated catchment area of Hunza River Basin. The study aimed...Hydrologiska Byrans Vattenbalansavdeling(HBV) Light model was used to evaluate the performance of the model in response to climate change in the snowy and glaciated catchment area of Hunza River Basin. The study aimed to understand the temporal variation of streamflow of Hunza River and its contribution to Indus River System(IRS). HBV model performed fairly well both during calibration(R2=0.87, Reff=0.85, PBIAS=-0.36) and validation(R2=0.86, Reff=0.83, PBIAS=-13.58) periods on daily time scale in the Hunza River Basin. Model performed better on monthly time scale with slightly underestimated low flows period during bothcalibration(R2=0.94, Reff=0.88, PBIAS=0.47) and validation(R2=0.92, Reff=0.85, PBIAS=15.83) periods. Simulated streamflow analysis from 1995-2010 unveiled that the average percentage contribution of snow, rain and glacier melt to the streamflow of Hunza River is about 16.5%, 19.4% and 64% respectively. In addition, the HBV-Light model performance was also evaluated for prediction of future streamflow in the Hunza River using future projected data of three General Circulation Model(GCMs) i.e. BCC-CSM1.1, CanESM2, and MIROCESM under RCP2.6, 4.5 and 8.5 and predictions were made over three time periods, 2010-2039, 2040-2069 and 2070-2099, using 1980-2010 as the control period. Overall projected climate results reveal that temperature and precipitation are the most sensitiveparameters to the streamflow of Hunza River. MIROC-ESM predicted the highest increase in the future streamflow of the Hunza River due to increase in temperature and precipitation under RCP4.5 and 8.5 scenarios from 2010-2099 while predicted slight increase in the streamflow under RCP2.6 during the start and end of the 21 th century. However, BCCCSM1.1 predicted decrease in the streamflow under RCP8.5 due to decrease in temperature and precipitation from 2010-2099. However, Can ESM2 predicted 22%-88% increase in the streamflow under RCP4.5 from 2010-2099. The results of this study could be useful for decision making and effective future strategic plans for water management and their sustainability in the region.展开更多
Hydrological models are considered as necessary tools for water and environmental resource management. However, modelling poorly gauged watersheds has been a challenge to hydrologists and hydraulic engineers. Research...Hydrological models are considered as necessary tools for water and environmental resource management. However, modelling poorly gauged watersheds has been a challenge to hydrologists and hydraulic engineers. Research done recently has shown the potential to overcome this challenge through incorporating satellite based hydrological and meteorological data in the measured data. This paper presents results for a study that used the semi-distributed conceptual HBV Light Model to model the rainfall-runoff in the Mara River Basin, Kenya. The model simulates runoff as a function of rainfall. It is built on the basis established between satellite observed and in-situ rainfall, evaporation, temperature and the measured runoff. The model’s performance and reliability were evaluated over two sub-catchments namely: Nyangores and Amala in the Mara River Basin using the Nash-Sutcliffe Efficiency which the model referred to as Reff and the coefficient of determination (R2). The Reff for Nyangores and Amala during the calibration and (validation) period were 0.65 (0.68) and 0.59 (0.62) respectively. The model showed good flow simulations particularly during the recession flows, in the Nyangores sub-catchment whereas it simulated poorly the short term fluctuations of the high-flow for Amala sub-catchment. Results from this study can be used by water resources managers to make informed decision on planning and management of water resources.展开更多
The glaciers of the Hengduan Mountains play an important role in the hydrology processes of this region. In this study, the HBV Light model, which relies on a degree-day model to simulate glacier melting, was employed...The glaciers of the Hengduan Mountains play an important role in the hydrology processes of this region. In this study, the HBV Light model, which relies on a degree-day model to simulate glacier melting, was employed to simulate both glacier runoffand total runoff. The daily temperature and precipitation at the Hailuo Creek No. 1 Glacier from 1952 to 2009 were obtained from daily meteorological observed data at the glacier and from six national meteorological stations near the Hailuo Creek Basin. The daily air temperature, precipitation, runoff depth, and monthly potential evaporation in 1995, 1996, and 2002 were used to obtain a set of optimal parameters, and the annual total runoff and glacier runoff of the Hailuo Creek Glacier （1952--2009） were calculated using the HBV Light model. Results showed the average annual runoff in the Hailuo Creek Basin was 2,114 mm from 1952 to 2009, of which glacial melting accounted for about 1,078 mm. The river runoff in the Hailuo Creek catchment increased as a result of increased glacier runoff. Glacier runoff accounted for 51.1% of the Hailuo Creek stream flow in 1994 and increased to 72.6% in 2006. About 95% of the increased stream flow derived from the increased ~lacier runoff.展开更多
This study was aimed to assess the impact of climate change on the water resource of Megech river catchment. In this study, large scale regional climate model (REMO) output was downscaled statistically to metrological...This study was aimed to assess the impact of climate change on the water resource of Megech river catchment. In this study, large scale regional climate model (REMO) output was downscaled statistically to metrological variables at a daily resolution using SDSM model version 5.11. We noticed that statistical downscaling smooth out the bias between REMO output and observed data. According to the projected climate data, the maximum temperature is likely to have an increasing trend +0.57°C while the minimum temperature shows a decreasing trends ﹣0.61°C. There is no clear trend for precipitation, both increasing and decreasing trend observed in the catchment. The HBV-Light hydrological model was successfully calibrated (1991-1995) and validated (1998-2000) using current climatic inputs and observed river flows. The overall performances of the model was good at monthly time scale both on calibration (NSE = 0.91) and validation (NSE = 0.86). Future discharge (2015-2050) was simulated using statistically downscaled 20 ensembles climate scenario data for both A1B and B1 scenarios. HBV-Light model simulation results showed a reduction of the peak discharge in August and September.展开更多
基金the National Natural Science foundation of China(Grant Nos.41690145 and 41670158)
文摘Hydrologiska Byrans Vattenbalansavdeling(HBV) Light model was used to evaluate the performance of the model in response to climate change in the snowy and glaciated catchment area of Hunza River Basin. The study aimed to understand the temporal variation of streamflow of Hunza River and its contribution to Indus River System(IRS). HBV model performed fairly well both during calibration(R2=0.87, Reff=0.85, PBIAS=-0.36) and validation(R2=0.86, Reff=0.83, PBIAS=-13.58) periods on daily time scale in the Hunza River Basin. Model performed better on monthly time scale with slightly underestimated low flows period during bothcalibration(R2=0.94, Reff=0.88, PBIAS=0.47) and validation(R2=0.92, Reff=0.85, PBIAS=15.83) periods. Simulated streamflow analysis from 1995-2010 unveiled that the average percentage contribution of snow, rain and glacier melt to the streamflow of Hunza River is about 16.5%, 19.4% and 64% respectively. In addition, the HBV-Light model performance was also evaluated for prediction of future streamflow in the Hunza River using future projected data of three General Circulation Model(GCMs) i.e. BCC-CSM1.1, CanESM2, and MIROCESM under RCP2.6, 4.5 and 8.5 and predictions were made over three time periods, 2010-2039, 2040-2069 and 2070-2099, using 1980-2010 as the control period. Overall projected climate results reveal that temperature and precipitation are the most sensitiveparameters to the streamflow of Hunza River. MIROC-ESM predicted the highest increase in the future streamflow of the Hunza River due to increase in temperature and precipitation under RCP4.5 and 8.5 scenarios from 2010-2099 while predicted slight increase in the streamflow under RCP2.6 during the start and end of the 21 th century. However, BCCCSM1.1 predicted decrease in the streamflow under RCP8.5 due to decrease in temperature and precipitation from 2010-2099. However, Can ESM2 predicted 22%-88% increase in the streamflow under RCP4.5 from 2010-2099. The results of this study could be useful for decision making and effective future strategic plans for water management and their sustainability in the region.
文摘Hydrological models are considered as necessary tools for water and environmental resource management. However, modelling poorly gauged watersheds has been a challenge to hydrologists and hydraulic engineers. Research done recently has shown the potential to overcome this challenge through incorporating satellite based hydrological and meteorological data in the measured data. This paper presents results for a study that used the semi-distributed conceptual HBV Light Model to model the rainfall-runoff in the Mara River Basin, Kenya. The model simulates runoff as a function of rainfall. It is built on the basis established between satellite observed and in-situ rainfall, evaporation, temperature and the measured runoff. The model’s performance and reliability were evaluated over two sub-catchments namely: Nyangores and Amala in the Mara River Basin using the Nash-Sutcliffe Efficiency which the model referred to as Reff and the coefficient of determination (R2). The Reff for Nyangores and Amala during the calibration and (validation) period were 0.65 (0.68) and 0.59 (0.62) respectively. The model showed good flow simulations particularly during the recession flows, in the Nyangores sub-catchment whereas it simulated poorly the short term fluctuations of the high-flow for Amala sub-catchment. Results from this study can be used by water resources managers to make informed decision on planning and management of water resources.
基金funded by the Chinese Postdoctoral Science Foundation(No.2015M570864)the Open-Ended Fund of the State Key Laboratory of Cryospheric Sciences+3 种基金Chinese Academy of Sciences(No.SKLCS-OP-2014-11)a project of the Northwest Normal University Young Teachers Scientific Research Ability Promotion Plan(No.NWNU-LKQN-13-10)a project of the National Natural Science Foundation of China(Nos.41273010,41271133)a project of the Major National Research Projects of China(No.2013CBA01808)
文摘The glaciers of the Hengduan Mountains play an important role in the hydrology processes of this region. In this study, the HBV Light model, which relies on a degree-day model to simulate glacier melting, was employed to simulate both glacier runoffand total runoff. The daily temperature and precipitation at the Hailuo Creek No. 1 Glacier from 1952 to 2009 were obtained from daily meteorological observed data at the glacier and from six national meteorological stations near the Hailuo Creek Basin. The daily air temperature, precipitation, runoff depth, and monthly potential evaporation in 1995, 1996, and 2002 were used to obtain a set of optimal parameters, and the annual total runoff and glacier runoff of the Hailuo Creek Glacier （1952--2009） were calculated using the HBV Light model. Results showed the average annual runoff in the Hailuo Creek Basin was 2,114 mm from 1952 to 2009, of which glacial melting accounted for about 1,078 mm. The river runoff in the Hailuo Creek catchment increased as a result of increased glacier runoff. Glacier runoff accounted for 51.1% of the Hailuo Creek stream flow in 1994 and increased to 72.6% in 2006. About 95% of the increased stream flow derived from the increased ~lacier runoff.
文摘This study was aimed to assess the impact of climate change on the water resource of Megech river catchment. In this study, large scale regional climate model (REMO) output was downscaled statistically to metrological variables at a daily resolution using SDSM model version 5.11. We noticed that statistical downscaling smooth out the bias between REMO output and observed data. According to the projected climate data, the maximum temperature is likely to have an increasing trend +0.57°C while the minimum temperature shows a decreasing trends ﹣0.61°C. There is no clear trend for precipitation, both increasing and decreasing trend observed in the catchment. The HBV-Light hydrological model was successfully calibrated (1991-1995) and validated (1998-2000) using current climatic inputs and observed river flows. The overall performances of the model was good at monthly time scale both on calibration (NSE = 0.91) and validation (NSE = 0.86). Future discharge (2015-2050) was simulated using statistically downscaled 20 ensembles climate scenario data for both A1B and B1 scenarios. HBV-Light model simulation results showed a reduction of the peak discharge in August and September.
