scholarly journals The Impacts of Climate Change on Maximum Daily Discharge in the Payab Jamash Watershed, Iran

2019 ◽  
Vol 11 (1) ◽  
pp. 1035-1045
Author(s):  
Farzad Parandin ◽  
Asadollah Khoorani ◽  
Ommolbanin Bazrafshan
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Climate Models ◽  
River Flow ◽  
Flow Simulation ◽  
Global Climate Models ◽  
Historical Period ◽  
Future Period ◽  
The Future ◽  
Daily Discharge

Abstract One of the most crucial consequences of climate change involves the alteration of the hydrologic cycle and river flow regime of watersheds. This study was an endeavor to investigate the contributions of climate change to maximum daily discharge (MDD). To this end, the MDD simulation was carried out through implementing the IHACRES precipitation-runoff model in the Payyab Jamash watershed for the 21st century (2016-2100). Subsequently, the observed precipitation and temperature data of the weather stations (1980-2011) as well as 4 multi-model outputs of Global Climate Models (GCMs) under the maximum and minimum Representative Concentration Pathways (RCPs) (2016-2100) were utilized. In order to downscale the output of GCMs, Bias Correction (BC) statistical method was applied. The projections for the 21st century indicated a reduction in Maximum Daily Precipitation (MDP) in comparison with the historic period in the study area. The average projected MDP for the future period was 9 mm/day and 5 mm/ day under 2.6 and 8.5 RCPs (4.6% and 2.6% decrease compared with the historical period), respectively. Moreover, the temperature increased in Jamash Watershed based on 2.6 and 8.5 RCPs by 1∘C and 2∘C(3.7% and 7.4% increase compared with the historical period), respectively. The findings of flow simulation for the future period indicated a decrease in MDD due to the diminished MDP in the study area. The amount of this decrease under RCP8.5 was not remarkable (0.75 m3/s), whereas its value for RCP2.6 was calculated as 40m3/s (respectively, 0.11% and 5.88% decrease compared with the historical period).

scholarly journals Twenty-first-century glacio-hydrological changes in the Himalayan headwater Beas River basin

2019 ◽  
Vol 23 (3) ◽  
pp. 1483-1503 ◽  
Author(s):  
Lu Li ◽  
Mingxi Shen ◽  
Yukun Hou ◽  
Chong-Yu Xu ◽  
Arthur F. Lutz ◽  
...  
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Bias Correction ◽  
Hydrological Modeling ◽  
Global Climate Models ◽  
Historical Period ◽  
Northern India ◽  
Hydrological Changes ◽  
The Future ◽  
Total Discharge

Abstract. The Himalayan Mountains are the source region of one of the world's largest supplies of freshwater. The changes in glacier melt may lead to droughts as well as floods in the Himalayan basins, which are vulnerable to hydrological changes. This study used an integrated glacio-hydrological model, the Glacier and Snow Melt – WASMOD model (GSM-WASMOD), for hydrological projections under 21st century climate change by two ensembles of four global climate models (GCMs) under two Representative Concentration Pathways (RCP4.5 and RCP8.5) and two bias-correction methods (i.e., the daily bias correction (DBC) and the local intensity scaling (LOCI)) in order to assess the future hydrological changes in the Himalayan Beas basin up to Pandoh Dam (upper Beas basin). Besides, the glacier extent loss during the 21st century was also investigated as part of the glacio-hydrological modeling as an ensemble simulation. In addition, a high-resolution WRF precipitation dataset suggested much heavier winter precipitation over the high-altitude ungauged area, which was used for precipitation correction in the study. The glacio-hydrological modeling shows that the glacier ablation accounted for about 5 % of the annual total runoff during 1986–2004 in this area. Under climate change, the temperature will increase by 1.8–2.8 ∘C at the middle of the century (2046–2065), and by 2.3–5.4 ∘C until the end of the century (2080–2099). It is very likely that the upper Beas basin will get warmer and wetter compared to the historical period. In this study, the glacier extent in the upper Beas basin is projected to decrease over the range of 63 %–87 % by the middle of the century and 89 %–100 % at the end of the century compared to the glacier extent in 2005. This loss in glacier area will in general result in a reduction in glacier discharge in the future, while the future streamflow is most likely to have a slight increase because of the increase in both precipitation and temperature under all the scenarios. However, there is widespread uncertainty regarding the changes in total discharge in the future, including the seasonality and magnitude. In general, the largest increase in river total discharge also has the largest spread. The uncertainty in future hydrological change is not only from GCMs, but also from the bias-correction methods and hydrological modeling. A decrease in discharge is found in July from DBC, while it is opposite for LOCI. Besides, there is a decrease in evaporation in September from DBC, which cannot be seen from LOCI. The study helps to understand the hydrological impacts of climate change in northern India and contributes to stakeholder and policymaker engagement in the management of future water resources in northern India.

scholarly journals Application of SWAT in Hydrological Simulation of Complex Mountainous River Basin (Part II: Climate Change Impact Assessment)

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1548
Author(s):  
Suresh Marahatta ◽  
Deepak Aryal ◽  
Laxmi Prasad Devkota ◽  
Utsav Bhattarai ◽  
Dibesh Shrestha
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Climate Models ◽  
Assessment Tool ◽  
Swat Model ◽  
Global Climate Models ◽  
Climate Data ◽  
The Future ◽  
The Impact ◽  
Mountainous River

This study aims at analysing the impact of climate change (CC) on the river hydrology of a complex mountainous river basin—the Budhigandaki River Basin (BRB)—using the Soil and Water Assessment Tool (SWAT) hydrological model that was calibrated and validated in Part I of this research. A relatively new approach of selecting global climate models (GCMs) for each of the two selected RCPs, 4.5 (stabilization scenario) and 8.5 (high emission scenario), representing four extreme cases (warm-wet, cold-wet, warm-dry, and cold-dry conditions), was applied. Future climate data was bias corrected using a quantile mapping method. The bias-corrected GCM data were forced into the SWAT model one at a time to simulate the future flows of BRB for three 30-year time windows: Immediate Future (2021–2050), Mid Future (2046–2075), and Far Future (2070–2099). The projected flows were compared with the corresponding monthly, seasonal, annual, and fractional differences of extreme flows of the simulated baseline period (1983–2012). The results showed that future long-term average annual flows are expected to increase in all climatic conditions for both RCPs compared to the baseline. The range of predicted changes in future monthly, seasonal, and annual flows shows high uncertainty. The comparative frequency analysis of the annual one-day-maximum and -minimum flows shows increased high flows and decreased low flows in the future. These results imply the necessity for design modifications in hydraulic structures as well as the preference of storage over run-of-river water resources development projects in the study basin from the perspective of climate resilience.

scholarly journals Appropriateness of Potential Evapotranspiration Models for Climate Change Impact Analysis in Yarlung Zangbo River Basin, China

Atmosphere ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 453 ◽  
Author(s):  
Pan ◽  
Xu ◽  
Xuan ◽  
Gu ◽  
Bai
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Climate Change Impact ◽  
Impact Analysis ◽  
Potential Evapotranspiration ◽  
Global Climate Models ◽  
Historical Period ◽  
Yarlung Zangbo River ◽  
The Future ◽  
Change Impact

Evapotranspiration (ET) is an important element in the water and energy cycle. Potential evapotranspiration (PET) is an important measurement of ET. Its accuracy has significant influence on agricultural water management, irrigation planning, and hydrological modelling. However, whether current PET models are applicable under climate change or not, is still a question. In this study, five frequently used PET models were chosen, including one combination model (the FAO Penman-Monteith model, FAO-PM), two temperature-based models (the Blaney-Criddle and the Hargreaves models) and two radiation-based models (the Makkink and the Priestley-Taylor models), to estimate their appropriateness in the historical and future periods under climate change impact on the Yarlung Zangbo river basin, China. Bias correction methods were not only applied to the temperature output of Global Climate Models (GCMs), but also for radiation, humidity, and wind speed. It was demonstrated that the results from the Blaney-Criddle and Makkink models provided better agreement with the PET obtained by the FAO-PM model in the historical period. In the future period, monthly PET estimated by all five models show positive trends. The changes of PET under RCP8.5 are much higher than under RCP2.6. The radiation-based models show better appropriateness than the temperature-based models in the future, as the root mean square error (RMSE) value of the former models is almost half of the latter models. The radiation-based models are recommended for use to estimate PET under climate change in the Yarlung Zangbo river basin.

scholarly journals Estimation of the Future Probable Precipitation based on the Assumption of Non-Stationarity in Seoul

2020 ◽  
Vol 20 (1) ◽  
pp. 19-29
Author(s):  
Minsu Jeong ◽  
Taesam Lee ◽  
JooHeon Lee ◽  
Hyeonseok Choi ◽  
Sunkwon Yoon
Keyword(s):  
Climate Change ◽  
Markov Chain ◽  
Differential Evolution ◽  
Frequency Analysis ◽  
Climate Models ◽  
Time Series Data ◽  
Global Climate Models ◽  
Series Data ◽  
Hourly Rainfall ◽  
The Future

In this study, an estimation of the future probable rainfall in Seoul, Korea, was performed, using non-stationary frequency analysis according to climate change and it was compared with the current probable rainfall. Hourly rainfall data provided by the Korea Meteorological Administration with durations of 1, 2, 3, 6, 12, 24, and 48-h were used as input. For the future projection of precipitation, the RCP 8.5 scenario was selected with the same durations. Moreover, the future hourly rainfall was extracted from using the daily precipitation from 29 Global Climate Models (GCMs), based on the statistical temporal down-scaling method and their corresponding bias corrections. Subsequently, the annual maximum precipitation was extracted for each year. In this study, both stationary and non-stationary frequency analysis was applied based on the observed and predicted time series data sets. In particular, for the non-stationary frequency analysis, the Differential Evolution Markov Chain technique, which combines the Bayesian-based Differential Evolution and Markov chain Monte Carlo methods, was adopted. Finally, the current and future intensity-duration-frequency curves were derived from the optimal probability distribution, and each probable rainfall was estimated. The results of the 29-scenario are presented with quantile estimations. The non-stationary frequency analysis results for Seoul revealed rainfalls of 94.4 mm/h for 30 y, 101.7 mm/h for 50 y, and 111.5 mm/h for 100 y return periods. The average value of the 29-GCM model ensemble was estimated to be approximately 5 mm/h higher than that obtained from the stationary frequency analysis. Considering the changes in hydrological characteristics due to climate change in Seoul, the results of this study could be utilized to pro-actively respond to natural disasters due to such phenomena.

scholarly journals Modelling climate change impact on water resources of the Upper Indus Basin

2021 ◽  
Author(s):  
Jamal H. Ougahi ◽  
Mark E. J. Cutler ◽  
Simon J. Cook
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Climate Models ◽  
River Flow ◽  
Assessment Tool ◽  
Global Climate Models ◽  
Indus Basin ◽  
Water Yield ◽  
River Flows ◽  
Upper Indus Basin

Abstract Climate change has implications for water resources by increasing temperature, shifting precipitation patterns and altering the timing of snowfall and glacier melt, leading to shifts in the seasonality of river flows. Here, the Soil & Water Assessment Tool was run using downscaled precipitation and temperature projections from five global climate models (GCMs) and their multi-model mean to estimate the potential impact of climate change on water balance components in sub-basins of the Upper Indus Basin (UIB) under two emission (RCP4.5 and RCP8.5) and future (2020–2050 and 2070–2100) scenarios. Warming of above 6 °C relative to baseline (1974–2004) is projected for the UIB by the end of the century (2070–2100), but the spread of annual precipitation projections among GCMs is large (+16 to −28%), and even larger for seasonal precipitation (+91 to −48%). Compared to the baseline, an increase in summer precipitation (RCP8.5: +36.7%) and a decrease in winter precipitation were projected (RCP8.5: −16.9%), with an increase in average annual water yield from the nival–glacial regime and river flow peaking 1 month earlier. We conclude that predicted warming during winter and spring could substantially affect the seasonal river flows, with important implications for water supplies.

scholarly journals Drought assessment and trends analysis from 20th century to 21st century over China

2015 ◽  
Vol 371 ◽  
pp. 89-94 ◽  
Author(s):  
X. L. Yang ◽  
L. L. Ren ◽  
R. Tong ◽  
Y. Liu ◽  
X. R. Cheng ◽  
...  
Keyword(s):  
20Th Century ◽  
21St Century ◽  
Climate Models ◽  
Local Economic Development ◽  
Standardized Precipitation Index ◽  
Cmip5 Models ◽  
Climate Projections ◽  
Future Period ◽  
Drought Assessment ◽  
The Future

Abstract. Droughts are becoming the most expensive natural disasters in China and have exerted serious impacts on local economic development and ecological environment. The fifth phase of the Coupled Model Intercomparison Project (CMIP5) provides a unique opportunity to assess scientific understanding of climate variability and change over a range of historical and future period. In this study, fine-resolution multimodel climate projections over China are developed based on 7 CMIP5 climate models under RCP8.5 emissions scenarios by means of Bilinear Interpolation and Bias Correction. The results of downscaled CMIP5 models are evaluated over China by comparing the model outputs with the England Reanalysis CRU3.1 from 1951 to 2000. Accordingly, the results from the output of downscaled models are used to calculate the Standardized Precipitation Index (SPI). Time series of SPI has been used to identify drought from 20th century to 21st century over China. The results show that, most areas of China are projected to become wetter as a consequence of increasing precipitation under RCP8.5 scenarios. Detailed examination shows that the SPI show a slightly increasing trend in the future period for the most parts of China, but drought in Southwest region of China will become the norm in the future RCP8.5 scenarios.

Analysis of EURO-CORDEX sub-daily rainfall simulations and derived event characteristics

2021 ◽  
Author(s):  
Paola Nanni ◽  
David J. Peres ◽  
Rosaria E. Musumeci ◽  
Antonino Cancelliere
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Rainfall Event ◽  
Historical Period ◽  
High Temporal Resolution ◽  
Hydrological Hazards ◽  
The Future

<p>Climate change is a phenomenon that is claimed to be responsible for a significant alteration of the precipitation regime in different regions worldwide and for the induced potential changes on related hydrological hazards. In particular, some consensus has raised about the fact that climate changes can induce a shift to shorter but more intense rainfall events, causing an intensification of urban and flash flooding hazards.  Regional climate models (RCMs) are a useful tool for trying to predict the impacts of climate change on hydrological events, although their application may lead to significant differences when different models are adopted. For this reason, it is of key importance to ascertain the quality of regional climate models (RCMs), especially with reference to their ability to reproduce the main climatological regimes with respect to an historical period. To this end, several studies have focused on the analysis of annual or monthly data, while few studies do exist that analyze the sub-daily data that are made available by the regional climate projection initiatives. In this study, with reference to specific locations in eastern Sicily (Italy), we first evaluate historical simulations of precipitation data from selected RCMs belonging to the Euro-CORDEX (Coordinated Regional Climate Downscaling Experiment for the Euro-Mediterranean area) with high temporal resolution (three-hourly), in order to understand how they compare to fine-resolution observations. In particular, we investigate the ability to reproduce rainfall event characteristics, as well as annual maxima precipitation at different durations. With reference to rainfall event characteristics, we specifically focus on duration, intensity, and inter-arrival time between events. Annual maxima are analyzed at sub-daily durations. We then analyze the future simulations according to different Representative concentration scenarios. The proposed analysis highlights the differences between the different RCMs, supporting the selection of the most suitable climate model for assessing the impacts in the considered locations, and to understand what trends for intense precipitation are to be expected in the future.</p>

Projection of future daily precipitation series and extreme events by using a multi-site statistical downscaling model over the great Montréal area, Québec, Canada

2012 ◽  
Vol 44 (1) ◽  
pp. 147-168 ◽  
Author(s):  
D. I. Jeong ◽  
A. St-Hilaire ◽  
T. B. M. J. Ouarda ◽  
P. Gachon
Keyword(s):  
Statistical Downscaling ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Historical Period ◽  
Precipitation Series ◽  
Statistical Downscaling Model ◽  
The Future ◽  
Consistent Increase ◽  
Ipcc Sres

This study suggested strategies to project future precipitation series based on a multi-site hybrid SDM (statistical downscaling model), which can downscale precipitation series at multiple observation sites simultaneously by combining the multivariate multiple linear regression (MMLR) model and the stochastic randomization procedure. The hybrid SDM and future projection methodologies applied to 10 observation sites located in the great area of Montréal, Québec, Canada. Six future independent precipitation series were projected from six sets of future atmospheric predictors using three AOGCMs (Atmosphere-Ocean Global Climate Models, i.e. CGCM2, CGCM3, HadCM3) and three IPCC SRES emission scenarios (B2, A1B and A2). Downscaled climate change signals on wet/dry sequences and extreme indices of precipitation time series were evaluated over the future period from 2060 to 2099 with respect to the historical period from 1961 to 2000. The future scenarios of all three AOGCMs showed a consistent increase of 7.9–44.6% in winter while only those of HadCM3 and CGCM3 showed a decrease of 2.3–23.0% in summer compared to their historical values. Precipitation series of CGCM2 A2 and CGCM3 A2 scenarios yielded the largest increase in winter, while those of HadCM3 B2 and A2 scenarios yielded the largest decrease in summer for all statistics indices.

Assessing the spatio-temporal variation and uncertainty patterns of historical and future projected water resources in China

2013 ◽  
Vol 4 (3) ◽  
pp. 302-316
Author(s):  
Qiuan Zhu ◽  
Hong Jiang ◽  
Changhui Peng ◽  
Jinxun Liu ◽  
Xiuqin Fang ◽  
...  
Keyword(s):  
Climate Change ◽  
Temporal Variation ◽  
Spatial And Temporal Variation ◽  
Historical Period ◽  
Precipitation Pattern ◽  
Climate Change Scenarios ◽  
Emission Scenarios ◽  
Future Period ◽  
Dynamic Global Vegetation Model ◽  
The Future

The spatial and temporal variation and uncertainty of precipitation and runoff in China were compared and evaluated between historical and future periods under different climate change scenarios. The precipitation pattern is derived from observed and future projected precipitation data for historical and future periods, respectively. The runoff is derived from simulation results in historical and future periods using a dynamic global vegetation model (DGVM) forced with historical observed and global climate models (GCMs) future projected climate data, respectively. One GCM (CGCM3.1) under two emission scenarios (SRES A2 and SRES B1) was used for the future period simulations. The results indicated high uncertainties and variations in climate change effects on hydrological processes in China: precipitation and runoff showed a significant increasing trend in the future period but a decreasing trend in the historical period at the national level; the temporal variation and uncertainty of projected precipitation and runoff in the future period were predicted to be higher than those in the historical period; the levels of precipitation and runoff in the future period were higher than those in the historical period. The change in trends of precipitation and runoff are highly affected by different climate change scenarios. GCM structure and emission scenarios should be the major sources of uncertainty.

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