scholarly journals Hydrologic Model Evaluation and Assessment of Projected Climate Change Impacts Using Bias-Corrected Stream Flows

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2312
Author(s):  
Joseph A. Daraio
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Stream Flow ◽  
General Circulation ◽  
Model Performance ◽  
General Circulation Models ◽  
Hydrologic Model ◽  
Historical Period ◽  
Hydrologic Models ◽  
Stream Flows

Hydrologic models driven by downscaled meteorologic data from general circulation models (GCM) should be evaluated using long-term simulations over a historical period. However, simulations driven by GCM data cannot be directly evaluated using observed flows, and the confidence in the results can be relatively low. The objectives of this paper were to bias correct simulated stream flows from calibrated hydrologic models for two basins in New Jersey, USA, and evaluate model performance in comparison to uncorrected simulations. Then, we used stream flow bias correction and flow duration curves (FDCs) to evaluate and assess simulations driven by statistically downscaled GCMs for the historical period and the future time slices 2041–2070 and 2071–2099. Bias correction of stream flow from simulations increased confidence in the performance of two previously calibrated hydrologic models. Results indicated there was no difference in projected FDCs for uncorrected and bias-corrected flows in one basin, while this was not the case in the second basin. This result provided greater confidence in projected stream flow changes in the former basin and implied more uncertainty in projected stream flows in the latter. Applications in water resources can use the methods described to evaluate the performance of GCM-driven simulations and assess the potential impacts of climate change with an appropriate level of confidence in the model results.

scholarly journals Uncertainty Analysis of Monthly Precipitation in GCMs Using Multiple Bias Correction Methods under Different RCPs

2020 ◽  
Vol 12 (18) ◽  
pp. 7508 ◽  
Author(s):  
Young Hoon Song ◽  
Eun-Sung Chung ◽  
Mohammed Sanusi Shiru
Keyword(s):  
South Korea ◽  
Bias Correction ◽  
General Circulation ◽  
General Circulation Models ◽  
Coastal Areas ◽  
Historical Period ◽  
Monthly Precipitation ◽  
Opposite Pattern ◽  
Statistical Measures ◽  
Selection Of

This study quantified the uncertainties in historical and future average monthly precipitation based on different bias correction methods, General Circulation Models (GCMs), Representative Concentration Pathways (RCPs), projection periods, and locations within the study area (i.e., the coastal and inland areas of South Korea). The GCMs were downscaled using deep learning, random forest, and nine quantile mapping bias correction methods for 22 gauge stations in South Korea. Data from the Korean Meteorology Administration (1970–2005) were used as the reference data in this study. Two statistical measures, the standard deviation and interquartile range, were used to quantify the uncertainties. The probability distribution density was used to assess the similarity/variation in rainfall distributions. For the historical period, the uncertainty in the selection of bias correction methods was greater than that in the selection of GCMs, whereas the opposite pattern was observed for the projection period. The projection period had the lowest level of uncertainty in the selection of RCP scenarios, and for the future, the uncertainly related to the time period was slightly lower than that for the other sources but was much greater than that for the RCP selection. In addition, it was clear that the level of uncertainty of inland areas is much lower than that of coastal areas. The uncertainty in the selection of the GCMs was slightly greater than that in the selection of the bias correction method. Therefore, the uncertainty in the selection of coastal areas was intermediate between the selection of bias correction methods and GCMs. This paper contributes to an improved understanding of the uncertainties in climate change projections arising from various sources.

scholarly journals Modelling streamflow response to climate change in data-scarce White Volta River basin of West Africa using a semi-distributed hydrologic model

2018 ◽  
Vol 10 (4) ◽  
pp. 907-930 ◽  
Author(s):  
Sulemana Abubakari ◽  
Xiaohua Dong ◽  
Bob Su ◽  
Xiaonong Hu ◽  
Ji Liu ◽  
...  
Keyword(s):  
Climate Change ◽  
West Africa ◽  
General Circulation ◽  
Management Practices ◽  
Evaluation Criteria ◽  
General Circulation Models ◽  
Hydrologic Model ◽  
Volta Basin ◽  
Monthly Streamflow ◽  
The Future

Abstract This study uses high resolution Climate Forecast System Reanalysis (CFSR), SWAT and two IPCC climate change (CC) scenarios (A1B and B1) combined with two general circulation models (GCMs) (HADCM3 and MPEH5) to evaluate impact of CC on streamflow in the White Volta basin of West Africa. The evaluation criteria (R2 and NSE > 0.70 and PBIAS within ±25%) during calibration and validation showed good simulation of the basin hydrology. Using average streamflow from 1979 to 2008 as a baseline, there were uncertainties over the sign of variation of annual streamflow in the 2020s. Annually, streamflow change is projected to be within −4.00% to +13.00% in the 2020s and +3.00% to +16.00% in the 2050s. Monthly streamflow changes for most months vary between −13.00% and +32.00%. A shift in monthly maximum streamflow from September to August is projected, while the driest months (December, January and February) show no change in the future. Based on the model results, the White Volta basin will likely experience an increase in streamflow by the mid-21st century. This would call for appropriate investment into cost-effective adaptive water management practices to cater for the likely impact of CC on the future hydrology of the basin.

scholarly journals Hydrologic alteration and potential ecosystemic implications under a changing climate in the Chitral River, Hindukush region, Pakistan

2020 ◽  
Author(s):  
M. Usman ◽  
X. Pan ◽  
D. Penna ◽  
B. Ahmad
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Bird Species ◽  
General Circulation Models ◽  
Migratory Bird ◽  
Historical Period ◽  
Hydrologic Alteration ◽  
Study Region ◽  
Assess Climate Change ◽  
Hydrologic Alterations

Abstract This study investigates changes in the hydrologic regime of the Chitral River, Hindukush–Karakoram–Himalayan (HKH) region, Pakistan. Different statistically based methods were used to assess climate change-induced hydrologic alterations that can possibly impact aquatic habitat in the study region. The hydrological model Hydrologiska Byråns Vattenbalansavdelning (HBV) was calibrated, validated, and applied to predict streamflow in the Chitral River basin. The HBV model was forced with the ensemble of four general circulation models under different representative concentration pathway emission scenarios to generate future streamflow under climate change conditions in the basin for the mid-twenty-first century. The results of this study show that hydrologic regimes in the study area, expressed by the magnitude, duration, frequency, timing, and rate of streamflow, are likely to alter in the future. Positive (i.e., with increased frequency) hydrologic alteration is projected for most flow parameters under all scenarios for the 2021–2050 period compared with values observed during the historical period (1976–2005). These hydrologic alterations might have impacts on fish and migratory bird species in the study area. This research can be helpful in providing practical information for more effective water resources and aquatic ecosystem management in the HKH region.

scholarly journals Evaluating the effects of climate change on precipitation and temperature for Iran using RCP scenarios

2020 ◽  
Author(s):  
Shahab Doulabian ◽  
Saeed Golian ◽  
Amirhossein Shadmehri Toosi ◽  
Conor Murphy
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Climate Models ◽  
Surface Air Temperature ◽  
General Circulation Models ◽  
Skill Score ◽  
Climatic Conditions ◽  
Historical Period ◽  
Rcp Scenarios ◽  
Wide Range

Abstract Climate change has caused many changes in hydrologic processes and climatic conditions globally, while extreme events are likely to occur more frequently at a global scale with continued warming. Given the importance of general circulation models (GCMs) as an essential tool for climate studies at global/regional scales, together with the wide range of GCMs available, selecting appropriate models is of great importance. In this study, six synoptic weather stations were selected as representative of different climatic zones over Iran. Utilizing monthly data for 20 years (1981–2000), the outputs of 25 GCMs for surface air temperature (SAT) and precipitation were evaluated for the historical period. The root-mean-square error and skill score were chosen to evaluate the performance of GCMs in capturing observed seasonal climate. Finally, the outputs of selected GCMs for the three Representative Concentration Pathways emission scenarios (RCPs), namely RCP2.6, RCP4.5, and RCP8.5, were downscaled using the change factor method for each station for the period 2046–2065. Results indicate that SAT in all months is likely to increase for each region, while for precipitation, large uncertainties emerge, despite the selection of climate models that best capture the observed seasonal cycle. These results highlight the importance of selecting a representative ensemble of GCMs for assessing future hydro-climatic changes for Iran.

scholarly journals Evaluation of impact of climate change and anthropogenic change on regional hydrology

2018 ◽  
Author(s):  
Seungwoo Chang ◽  
Wendy Graham ◽  
Jeffrey Geurink ◽  
Nisai Wanakule ◽  
Tirusew Asefa
Keyword(s):  
Climate Change ◽  
Water Use ◽  
Groundwater Level ◽  
General Circulation ◽  
General Circulation Models ◽  
Hydrologic Model ◽  
Tampa Bay ◽  
Future Climate ◽  
Future Climate Change ◽  
Groundwater Levels

Abstract. General circulation models (GCMs) have been widely used to simulate current and future climate at the global scale. However, the development of frameworks to apply GCMs to assess potential climate change impacts on regional hydrologic systems and compliance with water resource regulations is more recent. It is important to predict potential impacts of future climate change on streamflows and groundwater levels to reduce risks and increase resilience in water resources management and planning. This study evaluated future streamflows and groundwater levels in the Tampa Bay region in west-central Florida using an ensemble of different GCMs, reference evapotranspiration (ET0) methods, and water use scenarios to drive an integrated hydrologic model (IHM). Eight GCMs were bias-corrected and downscaled using the Bias Correction and Stochastic Analog (BCSA) downscaling method and then used, together with three ET0 methods, to drive the IHM for eight different human water use scenarios. Results showed that changes in projected streamflow were most sensitive to GCM selection, however, projections of groundwater level change were sensitive to both GCM and water use scenario. Projected changes in streamflow and groundwater level were relatively insensitive to the ET0 methods evaluated in this study. Six of eight GCMs projected a decrease in streamflow and groundwater level in the future regardless of water use scenario or ET method. These results indicate a high probability of a reduction in future water supply in the Tampa Bay region if environmental regulations intended to protect current aquatic ecosystems do not adapt to the changing climate.

scholarly journals Isolating the impacts of land use and climate change on streamflow

2015 ◽  
Vol 12 (2) ◽  
pp. 2201-2242 ◽  
Author(s):  
I. Chawla ◽  
P. P. Mujumdar
Keyword(s):  
Climate Change ◽  
Land Use ◽  
River Basin ◽  
General Circulation ◽  
General Circulation Models ◽  
Hydrologic Model ◽  
Combined Effect ◽  
Infiltration Capacity ◽  
Ganga Basin

Abstract. Streamflow regime is sensitive to changes in land use and climate in a river basin. Quantifying the isolated and integrated impacts of land use and climate change on streamflow is challenging as well as crucial to optimally manage water resources in the river basin. This paper presents a simple hydrologic modelling based approach to segregate the impacts of land use and climate change on streamflow of a river basin. The upper Ganga basin in India is selected as the case study to carry out the analysis. Streamflow in the river basin is modelled using a calibrated variable infiltration capacity hydrologic model. The approach involves development of three scenarios to understand the influence of land use and climate on streamflow. The first scenario assesses the sensitivity of streamflow to land use changes under invariant climate. The second scenario determines the change in streamflow due to change in climate assuming constant land use. The third scenario estimates the combined effect of changing land use and climate over streamflow of the basin. Based on the results obtained from the three scenarios, quantification of isolated impacts of land use and climate change on streamflow is addressed. Future projections of climate are obtained from dynamically downscaled simulations of six general circulation models (GCMs) available from the Coordinated Regional Downscaling Experiment (CORDEX) project. Uncertainties associated with the GCMs and emission scenarios are quantified in the analysis. Results for the case study indicate that streamflow is highly sensitive to change in urban area and moderately sensitive to change in crop land area. However, variations in streamflow generally reproduce the variations in precipitation. Combined effect of land use and climate on streamflow is observed to be more pronounced compared to their individual impacts in the basin. It is observed from the isolated effects of land use and climate change that climate has a more dominant impact on streamflow in the region. The approach proposed in this paper is applicable to any river basin to isolate the impacts of land use change and climate change on the streamflow.

scholarly journals Optimal water allocation of the Zayandeh-Roud Reservoir in Iran based on inflow projection under climate change scenarios

2021 ◽  
Author(s):  
Fatemeh Saedi ◽  
Azadeh Ahmadi ◽  
Karim C. Abbaspour
Keyword(s):  
Climate Change ◽  
Water Availability ◽  
Climate Change Impact ◽  
General Circulation ◽  
Assessment Tool ◽  
General Circulation Models ◽  
Hydrologic Model ◽  
Climate Change Scenarios ◽  
Change Impact ◽  
The Impact

Abstract The climate change impact on water availability has become a significant cause for concern in the Zayandeh-Roud Reservoir in Iran and similar reservoirs in arid regions. This study investigates the climate change impact on supplying water and water availability in the Zayandeh-Roud River Basin. For better management, the Soil & Water Assessment Tool (SWAT) was used to develop a hydrologic model of the Basin. The model then was calibrated and validated for two upstream stations using the SUFI-2 algorithm in the SWAT-CUP software. The impact of climate change was modeled by using data derived from five Inter-Sectoral Impact Model Intercomparison Project general circulation models under four Representative Concentration Pathways (RCPs). For calibration (1991–2008), the Nash–Sutcliffe efficiency (NSE) values of 0.75 and 0.61 at the Ghaleshahrokh and Eskandari stations were obtained, respectively. For validation (2009–2015), the NSE values were 0.80 and 0.82, respectively. The reservoir inflow would probably reduce by 40–50% during the period of 2020–2045 relative to the base period of 1981–2006. To evaluate the reservoir's future performance, a nonlinear optimization model was used to minimize water deficits. The highest annual water deficit would likely be around 847 MCM. The lowest reservoir reliability and the highest vulnerability occurred under the extreme RCP8.5 pathway.

scholarly journals Determination of Extreme Hydrological Index using HBV Model Simulation Results (Case Study : Upper Ciliwung Watershed)

Agromet ◽  
2019 ◽  
Vol 33 (1) ◽  
pp. 20-29
Author(s):  
Isnayulia Lestari ◽  
Bambang Dwi Dasanto
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Model Simulation ◽  
Coupled Model ◽  
General Circulation Models ◽  
Low Flow ◽  
Historical Period ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Hbv Model ◽  
Hydrological Regimes

The study of climate change on hydrological response is a crucial as climate change impact will drive the change in hydrological regimes of river. Upper Ciliwung watershed is one of the critical rivers in Java Island, which has been affected by climate change. This study aims to: (i) simulate the discharge flow using the Hydrologiska Byrans Vattenbalansavdelning (HBV) model; (ii) simulate future flow using three general circulation models (GCM) namely Commonwealth Scientific and Industrial Research Organisation (CSIRO) Mk.3.6.0, Model for Interdisciplinary Research on Climate version 5 (MIROC5), and Geophysical Fluid Dynamics Laboratory-Coupled Model generation 3 (GFDL-CM3); (iii) determine the changes of extreme hydrological index during historical period (2001-2015) and projected period (2031-2045). The historical year simulation and projections are used to determine eight hydrologic extreme indices for high flow and low flow. We calibrated the HBV model for two years (2001-2002) and validated it for two years (2003-2004). Our model performed well in discharge simulation as shown by the NSE values (0.66 for calibration and validation). Then we calculated the indices for each period used (historical and projected). To show the changes in hydrological regimes, we compare the indices between two periods. Changes in the index of the two periods tend to decrease in value on the index parameters that characterize the minimum extreme events. Hence, that it is possible in the projected period there will be extreme hydrological events in the form of drought.

scholarly journals Isolating the impacts of land use and climate change on streamflow

2015 ◽  
Vol 19 (8) ◽  
pp. 3633-3651 ◽  
Author(s):  
I. Chawla ◽  
P. P. Mujumdar
Keyword(s):  
Climate Change ◽  
Land Use ◽  
River Basin ◽  
Urban Areas ◽  
General Circulation ◽  
General Circulation Models ◽  
Hydrologic Model ◽  
Combined Effect ◽  
Infiltration Capacity

Abstract. Quantifying the isolated and integrated impacts of land use (LU) and climate change on streamflow is challenging as well as crucial to optimally manage water resources in river basins. This paper presents a simple hydrologic modeling-based approach to segregate the impacts of land use and climate change on the streamflow of a river basin. The upper Ganga basin (UGB) in India is selected as the case study to carry out the analysis. Streamflow in the river basin is modeled using a calibrated variable infiltration capacity (VIC) hydrologic model. The approach involves development of three scenarios to understand the influence of land use and climate on streamflow. The first scenario assesses the sensitivity of streamflow to land use changes under invariant climate. The second scenario determines the change in streamflow due to change in climate assuming constant land use. The third scenario estimates the combined effect of changing land use and climate over the streamflow of the basin. Based on the results obtained from the three scenarios, quantification of isolated impacts of land use and climate change on streamflow is addressed. Future projections of climate are obtained from dynamically downscaled simulations of six general circulation models (GCMs) available from the Coordinated Regional Downscaling Experiment (CORDEX) project. Uncertainties associated with the GCMs and emission scenarios are quantified in the analysis. Results for the case study indicate that streamflow is highly sensitive to change in urban areas and moderately sensitive to change in cropland areas. However, variations in streamflow generally reproduce the variations in precipitation. The combined effect of land use and climate on streamflow is observed to be more pronounced compared to their individual impacts in the basin. It is observed from the isolated effects of land use and climate change that climate has a more dominant impact on streamflow in the region. The approach proposed in this paper is applicable to any river basin to isolate the impacts of land use change and climate change on the streamflow.

scholarly journals Development and Evaluation of a Pan-European Multimodel Seasonal Hydrological Forecasting System

2019 ◽  
Vol 20 (1) ◽  
pp. 99-115 ◽  
Author(s):  
Niko Wanders ◽  
Stephan Thober ◽  
Rohini Kumar ◽  
Ming Pan ◽  
Justin Sheffield ◽  
...  
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
General Circulation ◽  
Hydrological Model ◽  
General Circulation Models ◽  
Hydrologic Model ◽  
Historical Period ◽  
Seasonal Forecasts ◽  
Forecasting System ◽  
Temporal And Spatial

Abstract Hydrological forecasts with a high temporal and spatial resolution are required to provide the level of information needed by end users. So far high-resolution multimodel seasonal hydrological forecasts have been unavailable due to 1) lack of availability of high-resolution meteorological seasonal forecasts, requiring temporal and spatial downscaling; 2) a mismatch between the provided seasonal forecast information and the user needs; and 3) lack of consistency between the hydrological model outputs to generate multimodel seasonal hydrological forecasts. As part of the End-to-End Demonstrator for Improved Decision Making in the Water Sector in Europe (EDgE) project commissioned by the Copernicus Climate Change Service (ECMWF), this study provides a unique dataset of seasonal hydrological forecasts derived from four general circulation models [CanCM4, GFDL Forecast-Oriented Low Ocean Resolution version of CM2.5 (GFDL-FLOR), ECMWF Season Forecast System 4 (ECMWF-S4), and Météo-France LFPW] in combination with four hydrological models [mesoscale hydrologic model (mHM), Noah-MP, PCRaster Global Water Balance (PCR-GLOBWB), and VIC]. The forecasts are provided at daily resolution, 6-month lead time, and 5-km spatial resolution over the historical period from 1993 to 2012. Consistency in hydrological model parameterization ensures an increased consistency in the hydrological forecasts. Results show that skillful discharge forecasts can be made throughout Europe up to 3 months in advance, with predictability up to 6 months for northern Europe resulting from the improved predictability of the spring snowmelt. The new system provides an unprecedented ensemble of seasonal hydrological forecasts with significant skill over Europe to support water management. This study highlights the potential advantages of multimodel based forecasting system in providing skillful hydrological forecasts.

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