scholarly journals Selection of Effective GCM Bias Correction Methods and Evaluation of Hydrological Response under Future Climate Scenarios

Climate ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 108
Author(s):  
Yaogeng Tan ◽  
Sandra M. Guzman ◽  
Zengchuan Dong ◽  
Liang Tan
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Bias Correction ◽  
Global Climate ◽  
Global Climate Model ◽  
Swat Model ◽  
Correction Method ◽  
Climate Change Scenarios ◽  
Hydrological Variables ◽  
Precipitation And Temperature

Global climate change is presenting a variety of challenges to hydrology and water resources because it strongly affects the hydrologic cycle, runoff, and water supply and demand. In this study, we assessed the effects of climate change scenarios on hydrological variables (i.e., evapotranspiration and runoff) by linking the outputs from the global climate model (GCM) with the Soil and Water Assessment Tool (SWAT) for a case study in the Lijiang River Basin, China. We selected a variety of bias correction methods and their combinations to correct the lower resolution GCM outputs of both precipitation and temperature. Then, the SWAT model was calibrated and validated using the observed flow data and corrected historical GCM with the optimal correction method selected. Hydrological variables were simulated using the SWAT model under emission scenarios RCP2.6, RCP4.5, and RCP8.5. The results demonstrated that correcting methods have a positive effect on both daily precipitation and temperature, and a hybrid method of bias correction contributes to increased performance in most cases and scenarios. Based on the bias corrected scenarios, precipitation annual average, temperature, and evapotranspiration will increase. In the case of precipitation and runoff, projection scenarios show an increase compared with the historical trends, and the monthly distribution of precipitation, evapotranspiration, and runoff shows an uneven distribution compared with baseline. This study provides an insight on how to choose a proper GCM and bias correction method and a helpful guide for local water resources management.

scholarly journals Predicting hydrologic responses to climate changes in highly glacierized and mountainous region Upper Indus Basin

2020 ◽  
Vol 7 (8) ◽  
pp. 191957 ◽  
Author(s):  
Muhammad Izhar Shah ◽  
Asif Khan ◽  
Tahir Ali Akbar ◽  
Quazi K. Hassan ◽  
Asim Jahangir Khan ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Climate Model ◽  
Assessment Tool ◽  
Model Simulation ◽  
Global Climate ◽  
Meteorological Data ◽  
Swat Model ◽  
Indus Basin ◽  
Upper Indus Basin

The Upper Indus Basin (UIB) is a major source of supplying water to different areas because of snow and glaciers melt and is also enduring the regional impacts of global climate change. The expected changes in temperature, precipitation and snowmelt could be reasons for further escalation of the problem. Therefore, estimation of hydrological processes is critical for UIB. The objectives of this paper were to estimate the impacts of climate change on water resources and future projection for surface water under different climatic scenarios using soil and water assessment tool (SWAT). The methodology includes: (i) development of SWAT model using land cover, soil and meteorological data; (ii) calibration of the model using daily flow data from 1978 to 1993; (iii) model validation for the time 1994–2003; (iv) bias correction of regional climate model (RCM), and (v) utilization of bias-corrected RCM for future assessment under representative concentration pathways RCP4.5 and RCP8.5 for mid (2041–2070) and late century (2071–2100). The results of the study revealed a strong correlation between simulated and observed flow with R 2 and Nash–Sutcliff efficiency (NSE) equal to 0.85 each for daily flow. For validation, R 2 and NSE were found to be 0.84 and 0.80, respectively. Compared to baseline period (1976–2005), the result of RCM showed an increase in temperature ranging from 2.36°C to 3.50°C and 2.92°C to 5.23°C for RCP4.5 and RCP8.5 respectively, till the end of the twenty-first century. Likewise, the increase in annual average precipitation is 2.4% to 2.5% and 6.0% to 4.6% (mid to late century) under RCP4.5 and RCP8.5, respectively. The model simulation results for RCP4.5 showed increase in flow by 19.24% and 16.78% for mid and late century, respectively. For RCP8.5, the increase in flow is 20.13% and 15.86% during mid and late century, respectively. The model was more sensitive towards available moisture and snowmelt parameters. Thus, SWAT model could be used as effective tool for climate change valuation and for sustainable management of water resources in future.

scholarly journals Analysis of Rainfall-Runoff Characteristics on Bias Correction Method of Climate Change Scenarios

2015 ◽  
Vol 31 (3) ◽  
pp. 241-252 ◽  
Author(s):  
Donghyuk Kum ◽  
Younsik Park ◽  
Young Hun Jung ◽  
Min Hwan Shin ◽  
Jichul Ryu ◽  
...  
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Correction Method ◽  
Climate Change Scenarios ◽  
Rainfall Runoff ◽  
Bias Correction Method

scholarly journals Coupling Remote Sensing and Hydrological Model for Evaluating the Impacts of Climate Change on Streamflow in Data-Scarce Environment

2021 ◽  
Vol 13 (24) ◽  
pp. 14025
Author(s):  
Fazlullah Akhtar ◽  
Usman Khalid Awan ◽  
Christian Borgemeister ◽  
Bernhard Tischbein
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Water Resources ◽  
Swat Model ◽  
Coefficient Of Determination ◽  
Climate Change Scenarios ◽  
Impact Of Climate Change ◽  
Streamflow Data ◽  
The Impact ◽  
Impacts Of Climate Change

The Kabul River Basin (KRB) in Afghanistan is densely inhabited and heterogenic. The basin’s water resources are limited, and climate change is anticipated to worsen this problem. Unfortunately, there is a scarcity of data to measure the impacts of climate change on the KRB’s current water resources. The objective of the current study is to introduce a methodology that couples remote sensing and the Soil and Water Assessment Tool (SWAT) for simulating the impact of climate change on the existing water resources of the KRB. Most of the biophysical parameters required for the SWAT model were derived from remote sensing-based algorithms. The SUFI-2 technique was used for calibrating and validating the SWAT model with streamflow data. The stream-gauge stations for monitoring the streamflow are not only sparse, but the streamflow data are also scarce and limited. Therefore, we selected only the stations that are properly being monitored. During the calibration period, the coefficient of determination (R2) and Nash–Sutcliffe Efficiency (NSE) were 0.75–0.86 and 0.62–0.81, respectively. During the validation period (2011–2013), the NSE and R2 values were 0.52–0.73 and 0.65–0.86, respectively. The validated SWAT model was then used to evaluate the potential impacts of climate change on streamflow. Regional Climate Model (RegCM4-4) was used to extract the data for the climate change scenarios (RCP 4.5 and 8.5) from the CORDEX domain. The results show that streamflow in most tributaries of the KRB would decrease by a maximum of 5% and 8.5% under the RCP 4.5 and 8.5 scenarios, respectively. However, streamflow for the Nawabad tributary would increase by 2.4% and 3.3% under the RCP 4.5 and 8.5 scenarios, respectively. To mitigate the impact of climate change on reduced/increased surface water availability, the SWAT model, when combined with remote sensing data, can be an effective tool to support the sustainable management and strategic planning of water resources. Furthermore, the methodological approach used in this study can be applied in any of the data-scarce regions around the world.

scholarly journals Converting Climate Change Gridded Daily Rainfall to Station Daily Rainfall—A Case Study at Zengwen Reservoir

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1516
Author(s):  
Tse-Yu Teng ◽  
Tzu-Ming Liu ◽  
Yu-Shiang Tung ◽  
Ke-Sheng Cheng
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Bias Correction ◽  
Climate Change Impact ◽  
Daily Rainfall ◽  
Correction Method ◽  
Two Stage ◽  
Climate Change Impact Assessment ◽  
Daily Data ◽  
Change Impact

With improvements in data quality and technology, the statistical downscaling data of General Circulation Models (GCMs) for climate change impact assessment have been refined from monthly data to daily data, which has greatly promoted the data application level. However, there are differences between GCM downscaling daily data and rainfall station data. If GCM data are directly used for hydrology and water resources assessment, the differences in total amount and rainfall intensity will be revealed and may affect the estimates of the total amount of water resources and water supply capacity. This research proposes a two-stage bias correction method for GCM data and establishes a mechanism for converting grid data to station data. Five GCMs were selected from 33 GCMs, which were ranked by rainfall simulation performance from a baseline period in Taiwan. The watershed of the Zengwen Reservoir in southern Taiwan was selected as the study area for comparison of the three different bias correction methods. The results reveal that the method with the wet-day threshold optimized by objective function with observation rainfall wet days had the best result. Error was greatly reduced in the hydrology model simulation with two-stage bias correction. The results show that the two-stage bias correction method proposed in this study can be used as an advanced method of data pre-processing in climate change impact assessment, which could improve the quality and broaden the extent of GCM daily data. Additionally, GCM ranking can be used by researchers in climate change assessment to understand the suitability of each GCM in Taiwan.

Future changes of circulation types associated with extremes over Sweden

2020 ◽  
Author(s):  
Felicitas Hansen ◽  
Danijel Belusic ◽  
Klaus Wyser
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Radiative Forcing ◽  
Large Scale ◽  
Extreme Values ◽  
Global Climate Model ◽  
Historical Period ◽  
Climate Change Scenarios ◽  
Circulation Types ◽  
Precipitation And Temperature

<p>The large-scale atmospheric circulation is one of the most important factors influencing weather and climate conditions on different timescales. Its short- and long-term changes considerably determine both mean and extreme values of surface parameters like temperature or precipitation rates. Future changes of circulation patterns are of particular interest as these may significantly alter or amplify the expected thermodynamic changes due to changing concentrations of greenhouse gases, albedo and land use. We analyse both historical as well as future climate simulations of the SMHI large ensemble (S-LENS) performed with the EC-Earth3 global climate model to examine large-scale circulation situations and their association to extremes in precipitation and temperature over Sweden. Various methods exist to classify mostly sea level pressure or geopotential height fields into characteristic circulation types, and we compare several of these methods for their applicability to represent precipitation and temperature variability over our region of interest. S-LENS consists of a 50-member ensemble for a historical period (1970-2014) and four 50-member climate change scenario ensembles covering the 21st century differing in terms of assumptions made for future radiative forcing development. We study the efficiency of circulation types in the historical period to give rise to extremes, and examine further the frequency and within-type changes of those circulation types associated with extremes by the middle and the end of the 21st century under the different climate change scenarios. S-LENS with its comparatively large number of both multi-decadal scenarios and realizations for each scenario serves as a perfect testbed to study potential changes in events of low frequency within the environment of a single model.</p>

scholarly journals Impacts of climate and catastrophic forest changes on streamflow and water balance in a mountainous headwater stream in Southern Alberta

2013 ◽  
Vol 17 (12) ◽  
pp. 4941-4956 ◽  
Author(s):  
V. Mahat ◽  
A. Anderson
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Similar Amount ◽  
Climate Change Scenarios ◽  
Climate Data ◽  
Stochastic Weather Generator ◽  
Precipitation Decrease ◽  
Southern Alberta

Abstract. Rivers in Southern Alberta are vulnerable to climate change because much of the river water originates as snow in the eastern slopes of the Rocky Mountains. Changes in likelihood of forest disturbance (wildfire, insects, logging, etc.) may also have impacts that are compounded by climate change. This study evaluates the impacts of climate and forest changes on streamflow in the upper parts of the Oldman River in Southern Alberta using a conceptual hydrological model, HBV-EC (Hydrologiska Byråns attenbalansavdelning, Environment Canada), in combination with a stochastic weather generator (LARS-WG) driven by GCM (global climate model) output climate data. Three climate change scenarios (A1B, A2 and B1) are selected to cover the range of possible future climate conditions (2020s, 2050s, and 2080s). The GCM projected less than a 10% increase in precipitation in winter and a similar amount of precipitation decrease in summer. These changes in projected precipitation resulted in up to a 200% (9.3 mm) increase in winter streamflow in February and up to a 63% (31.2 mm) decrease in summer flow in June. Flow also decreased in July and August, when irrigation is important; these reduced river flows during this season could impact agriculture production. The amplification in the streamflow is mostly driven by the projected increase in temperature that is predicted to melt winter snow earlier, resulting in lower water availability during the summer. Uncertainty analysis was completed using a guided GLUE (generalized likelihood uncertainty estimation) approach to obtain the best 100 parameter sets and associated ranges of streamflows. The impacts of uncertainty in streamflows were higher in spring and summer than in winter and fall. Forest change compounded the climate change impact by increasing the winter flow; however, it did not reduce the summer flow.

scholarly journals Climatic impacts on water resources in a tropical catchment in Uganda and adaptation measures proposed by resident stakeholders

2021 ◽  
Vol 164 (1-2) ◽  
Author(s):  
Bano Mehdi ◽  
Julie Dekens ◽  
Mathew Herrnegger
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Mean Annual Precipitation ◽  
Adaptation Measures ◽  
The Mean ◽  
The Impact ◽  
Far Future

AbstractThe Ruhezamyenda catchment in Uganda includes a unique lake, Lake Bunyonyi, and is threatened by increasing social and environmental pressures. The COSERO hydrological model was used to assess the impact of climate change on future surface runoff and evapotranspiration in the Lake Bunyonyi catchment (381 km2). The model was forced with an ensemble of CMIP5 global climate model (GCM) simulations for the mid-term future (2041–2070) and for the far future (2071–2100), each with RCP4.5 and RCP8.5. In the Ruhezamyenda catchment, compared to 1971–2000, the median of all GCMs (for both RCPs) showed the mean monthly air temperature to increase by approximately 1.5 to 3.0 °C in the mid-term future and by roughly 2.0 to 4.5 °C in the far future. The mean annual precipitation is generally projected to increase, with future changes between − 25 and + 75% (RCP8.5). AET in the Lake Bunyonyi catchment was simulated to increase for the future by approximately + 8 mm/month in the median of all GCMs for RCP8.5 for the far future. The runoff for future periods showed much uncertainty, but with an overall increasing trend. A combination of no-regrets adaptation options in the five categories of: governance; communication and capacity development; water, soil, land management and livelihoods improvement; data management; and research, was identified and validated with stakeholders, who also identified additional adaptation actions based on the model results. This study contributes to improving scientific knowledge on the impacts of climate change on water resources in Uganda with the purpose to support adaptation.

scholarly journals Impacts of climate change on water resources in the major countries along the Belt and Road

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12201
Author(s):  
Panpan Du ◽  
Ming Xu ◽  
Renqiang Li
Keyword(s):  
Climate Change ◽  
Water Stress ◽  
Water Resources ◽  
Water Supply ◽  
Climate Model ◽  
Global Climate Model ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Belt And Road ◽  
The Belt And Road

Background Climate change has altered global hydrological cycles mainly due to changes in temperature and precipitation, which may exacerbate the global and regional water shortage issues, especially in the countries along the Belt and Road (B&R). Methods In this paper, we assessed water supply, demand, and stress under three climate change scenarios in the major countries along the Belt and Road. We ensembled ten Global Climate Model (GCM) runoff data and downscaled it to a finer resolution of 0.1° × 0.1° by the random forest model. Results Our results showed that the GCM runoff was highly correlated with the FAO renewable water resources and thus could be used to estimate water supply. Climate change would increase water supply by 4.85%, 5.18%, 8.16% and water demand by 1.45%, 1.68%, 2.36% under RCP 2.6, 4.5, and 8.5 scenarios by 2050s, respectively. As a result, climate change will, in general, have little impact on water stress in the B&R countries as a whole. However, climate change will make future water resources more unevenly distributed among the B&R countries and regions, exacerbating water stress in some countries, especially in Central Asia and West Asia. Our results are informative for water resource managers and policymakers in the B&R countries to make sustainable water management strategies under future climate change.

scholarly journals Climate Predictions for Ludhiana District of Indian Punjab under RCP 4.5 and RCP 8.5

2019 ◽  
pp. 128-141 ◽  
Author(s):  
Mehraj U. Din Dar ◽  
Rajan Aggarwal ◽  
Samanpreet Kaur
Keyword(s):  
Climate Change ◽  
Food Security ◽  
Water Resources ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Climate Prediction ◽  
Global Food Security ◽  
Rcp 8.5 ◽  
Global Food

Climate change poses significant threats to global food security and water resources. In a present study, a Global Climate Model HAD GEM2-ES under RCPs 4.5 and 8.5 was used for climate prediction study. The study spanned 46 years of baseline (1970-2015) as well as two future periods’ mid-century (MC) (2020-2050) and end century EC (2060-2090). The results showed that the temperature would increase by 1.56°C and rainfall would decrease by 98 mm in MC (2020-2050); and 3.11°C and 90 mm in EC (2060-2090), respectively under RCP 4.5. In RCP 8.5 the increase in temperature and rainfall was 2.75°C and 153 mm, respectively in MC and the corresponding values in EC was 5.46°C and 251 mm, respectively.

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