Prediction of changes in climatic parameters using CanESM2 model based on Rcp scenarios (case study): Lar dam basin

Javaherian, Mohammadreza; Ebrahimi, Hossein; Aminnejad, Babak

doi:10.1016/j.asej.2020.04.012

Cited by 16 publications

(4 citation statements)

References 10 publications

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“…As the location of the wetland is located in a semi-arid region, the canESM2 model was used based on the previous researchers' suggestion (Javaherian et al 2021;Al-Shurafat and Abdullah, 2020;Chim et al 2021;Zhao et al 2020, Tukimat et al 2019 was also used to improve the results (Morid et al 2020;Almagroa et al 2020;Khazaei et al 2019). The selected scenarios are RCP 2.6, 4.5, and 8.5, which are optimistic, moderate, and pessimistic, respectively.…”

Section: Methodsmentioning

confidence: 99%

“…Previous studies indicate the increasing trends of precipitation and runoff in different regions such as Tonga Bhadra River, India (Meenu et al 2013), Malaysia (Tan et al 2017), and Lar Dam, Iran (Javaherian et al 2021). Other researchers have also reported a reduction in runoff in several regions: British Columbia, Canada (Schnorbus and Cannon, 2014), Kermanshah, Iran (Rajabi et al 2012;Salajegheh et al 2016), and the Yarmouk River, Jordan, and Syria (Al-Shurafat and Abdullah, 2020).…”

Section: Introductionmentioning

confidence: 93%

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Predicting the impact of climate change on the area of wetlands using remote sensing

Heidarzadeh,

Eghbal,

Esmaeili

et al. 2024

Theor Appl Climatol

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Climate change has been the main environmental challenge in recent years. In this research, the impact of climate change on the Arjan Wetland, Iran, has been investigated. The global climate models of canESM2 and hadGEM2 were used to predict the air temperature and precipitation for 2025-2066 in scenarios of RCP 2.6, 4.5, and 8.5. Temperature and precipitation data were downscaled using SDSM and LARS-WG software, respectively. Then, the wetland area was measured by processing the Landsat satellite images using the MNDWI algorithm. Forecast data were applied to estimate the wetland area for 2025-2066 and the scPDSI drought index. The results indicate that the estimated areas of the future period will slightly decrease; as a result, 90% of the areas in the years 2045-2066 are less than 800 hectares, and more than1100 hectares have not been dried in these years. The reduction of the area compared to the observation period is due to climate change and it shows the Arjan wetland is going towards drought.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 93%

Predicting the impact of climate change on the area of wetlands using remote sensing

Heidarzadeh,

Eghbal,

Esmaeili

et al. 2024

Theor Appl Climatol

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“…Even while the climate system is in a constant change state, achieving RCP2.6 would certainly present the smallest impacts on natural ecosystems and human activities [11]. To reach such radiation levels, greenhouse gas emissions should be significantly reduced [34]. Moreover, the other scenarios consider the increase of greenhouse gas emissions and radiative forcing in different tendencies, with RCP8.5 the most critical scenario [11].…”

Section: Databasesmentioning

confidence: 99%

Estimation of the Climate Change Impact on the Hydrological Balance in Basins of South-Central Chile

Martínez-Retureta

Aguayo

Abreu

et al. 2021

Water

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In this study, the SWAT (Soil Water Assessment Tool) hydrological model is implemented to determine the effect of climate change on various hydrological components in two basins located in the foothills of the Andes: the Quino and Muco river basins. The water cycle is analyzed by comparing the model results to climatic data observed in the past (1982–2016) to understand its trend behaviors. Then, the variations and geographical distribution of the components of the hydrological cycle were analyzed using the Representative Concentration Pathway (RCP)8.5 climate scenario to model two periods considering the immediate future (2020–2049) and intermediate future (2050–2079). In this way, in the study area, it is predicted that yearly average temperatures will increase up to 1.7 °C and that annual average precipitation will decrease up to 210 mm for the intermediate future. Obtained results show that the analyzed parameters presented the same trend behavior for both periods of time; however, a greater impact can be expected in the intermediate future. According to the spatial distribution, the impact worsens for all the parameters as the elevation increases in both basins. The model depicted that yearly average evapotranspiration would increase around 5.26% and 5.81% for Quino and Muco basins, respectively, due to the large increase in temperature. This may cause, when combined with the precipitation lessening, a decrease around 9.52% and 9.73% of percolation, 2.38% and 1.76% of surface flow, and 7.44% and 8.14% of groundwater for Quino and Muco basins, respectively, with a consequent decrease of the water yield in 5.25% and 4.98% in the aforementioned watersheds, respectively.

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“…The CanESM2 was developed by the Canadian Centre for Climate Modelling and Analysis (CCCma) of Environment and Climate Change Canada and is one of the high performing GCMs used by many researchers around the world (Gao et al 2021;Javaherian et al 2021;. The CSIRO model was first developed in Queensland Climate Change Centre, Australia and has been used by many researchers around the globe (Silva et al 2017).…”

Section: Regional Climate Model Datamentioning

confidence: 99%

Variability and trends of climate extremes indices from the observed and downscaled GCMs data over 1950–2020 period in Chattogram City, Bangladesh

Pervin

Khan

2021

Journal of Water and Climate Change

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This study was intended to evaluate the variability and trends of climate extremes by incorporating daily data from Chattogram station and from the high-resolution Coordinated Regional Climate Downscaling Experiment (CORDEX) for two different time series. Here, we also focused on evaluating the performance of the selected RCMs (CanESM2, CSIRO, and GFDL from CORDEX) using Taylor diagrams and heat map analysis. Twenty-two extreme climate indices from ETCCDI were computed for 1950–1989 and 1990–2020 periods. Mann–Kendall and Sen's slope test were performed to estimate the trends from the indices from both station and RCMs data. Highly significant increasing trend for the warm days and warm nights’ frequencies were found, whereas, the frequency of cold days and cold nights indicated significantly decreasing trend. On the other hand, mild increasing trend in 1-day and 5-day maximum rainfall was detected. Also, the average annual precipitation has increased by 6% from the 1950–1989 to 1990–2020 period. During the last three decades, the region has experienced more heavier rainfall in the monsoon but increased water stress in the dry season. The two-fold effects of climate change on the local hydrology revealed by this study need to be addressed properly for the sustainable development of this region.

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Prediction of changes in climatic parameters using CanESM2 model based on Rcp scenarios (case study): Lar dam basin

Cited by 16 publications

References 10 publications

Predicting the impact of climate change on the area of wetlands using remote sensing

Predicting the impact of climate change on the area of wetlands using remote sensing

Estimation of the Climate Change Impact on the Hydrological Balance in Basins of South-Central Chile

Variability and trends of climate extremes indices from the observed and downscaled GCMs data over 1950–2020 period in Chattogram City, Bangladesh

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