Spatiotemporal variations in precipitation extremes based on CMIP6 models and Shared Socioeconomic Pathway (SSP) scenarios over MENA

Hejazizadeh, Zahra; Hosseini, Seyed Asaad; Karbalaee, Alireza; Barabadi, Roya Poorkarim; Mousavi, Seyed Mohammad

doi:10.1007/s12517-022-10887-9

Cited by 6 publications

(3 citation statements)

References 36 publications

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“…El-Rawy et al [100] investigated the influence of climate change in Saudi Arabia and projected an increase in the long-term period of 27% and 32% under the SSP2-4.5 and SSP5-8.5 scenarios, respectively. Numerous recent studies have consistently reported an expected rise in future rainfall amounts across various regions of the region (e.g., [19,[101][102][103][104]).…”

Section: Projected Changes In Climatic Variables In Saudi Arabiamentioning

confidence: 99%

Towards Sustainable Water Resources Management Considering Climate Change in the Case of Saudi Arabia

Alodah

2023

Sustainability

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Saudi Arabia is one of the most water-scarce nations in the world, with a huge demand-supply gap, and the situation is expected to worsen due to climate change. Conventional surface water resources are limited, while nonrenewable groundwater sources are depleted. To build a more resilient and sustainable water sector, the production of non-conventional water resources, specifically desalinated seawater and treated domestic wastewater, has steadily increased in recent years. As the country lacks perennial water resources, such as rivers or water bodies, it relies mainly on nonrenewable groundwater and desalinated water to meet its daily requirements. Although the government is attempting to regulate the agricultural sector, water consumption in agriculture remains relatively high. It presents an environmental challenge due to its heavy reliance on non-renewable groundwater resources. The anticipated increase in temperature and highly uncertain changes in the rainfall patterns in Saudi Arabia could lead to greater uncertainty when attempting to develop effective water resource management plans. In this work, we review the status of the present and future of water resources and the challenges local authorities face in managing water resources amidst a changing climate in Saudi Arabia. This study employed a narrative research methodology, utilizing various databases, including Scopus, Web of Science, and Science Direct, to extract relevant articles within the subject area. This study proposes a number of recommendations and conclusions aimed at improving decision-makers’ ability to adapt to and mitigate the anticipated adverse impacts of climate change to manage scarce water resources sustainably.

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Section: Projected Changes In Climatic Variables In Saudi Arabiamentioning

confidence: 99%

Towards Sustainable Water Resources Management Considering Climate Change in the Case of Saudi Arabia

Alodah

2023

Sustainability

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“…The results showed that in the study area in the future period (2041-2060), the amount of precipitation decrease 4.5 % compared to the base period, and the minimum and maximum temperature will decrease 2.6 and 1.3 Cº, respectively. Hejazizadeh et al (2022) assessed the variations trend in precipitation extremes over MENA in the base period and the future period . The results demonstrated that the amount of precipitation will decrease, but the precipitation extremes and their intensities will increase in the future period compared to the base period.…”

Section: Introductionmentioning

confidence: 99%

Modeling Hydrological Responses of Watershed Under Climate Change Scenarios Using Machine Learning Techniques

Karimizadeh,

2023

Water Resour Manage

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Climate change is the most important problem of the earth in the current century. In this study, the effects of climate change on precipitation, temperature, wind speed, relative humidity and surface runoff in Saghez watershed in Iran investigated. The main methods were using the Coupled Model Intercomparison Project phase 6 (CMIP6), the Soil and Water Assessment Tool (SWAT) and the Artificial Neural Network (ANN) model under the Shared Socio-economic Pathway scenarios (SSPs) using the Linear Scaling Bias Correction (LSBC) for the future period (2021-2050) compared to the base period (1985-2014). MAE, MSE, RMSE and R 2 indices used for model calibration and validation.The results of forecasting temperature, precipitation, wind speed and relative humidity showed the average percentage of precipitation decrease in the future period will be 6.1%. In terms of the temperature, 1.4, 1.5 and 1.6 Cº increase predicted for minimum, average and maximum temperatures, respectively. The results of studying the surface runoff changes using the SWAT model also illustrated that based on all three scenarios SSP1-2.6, SSP3-7.0 and SSP5-8.5 in the future period, the amount of surface runoff will decrease, which based on three mentioned scenarios is equals to 17.5%, 23.7% and 26.3% decrease, respectively. Furthermore, the assessment using the artificial neural network (ANN) also showed that the parameters of precipitation in the previous two days, wind speed and maximum relative humidity have the greatest effect on the watershed runoff.

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“…They discovered that each CMIP6 model had its own adaptive specific climate zones, such as the model that performed well in a humid zone but poorly in ultra-arid and arid zones. H. Zahra [23] examined trends in extreme precipitation in the Middle East and North Africa (MENA) during historical periods and future periods (2021-2050), and the results suggest that extreme precipitation and its intensity will continue to increase despite the decrease in precipitation in the Middle East and North Africa region. J. d. M. Felipe et al [24] estimated the changes in CMIP6's worst-case scenario for the medium term (2046-2065) and future (2081-2100), predicting more severe, frequent, and persistent extreme precipitation events in all regions of Brazil and more pronounced changes in heavy precipitation and severe drought in north-central and southern Brazil.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Future Urban Rainfall and Waterlogging Scenarios Based on CMIP6: A Case Study of Beijing Urban Area

Wang,

Zhang,

Zhao

et al. 2023

Water

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Extreme weather events will become more frequent and severe as a result of climate change, necessitating an immediate need for cities to adapt to future climate change. Therefore, the prediction of future precipitation and waterlogging is of utmost importance. Using Beijing as an example, the simulation capability of different models was evaluated, and the optimal model for the study area was screened using Taylor diagrams and interannual variability scores, along with actual monthly precipitation data from Chinese weather stations from 1994 to 2014 and historical monthly precipitation data from 10 coupled models from Coupled Model Intercomparison Project Phase 6 (CMIP6). The SWMM model was then used to simulate future rainfall and waterlogging scenarios for the study area using precipitation forecast data for 2020–2050 from the best model to investigate the impact of climate change on future rainfall and waterlogging in urban areas. CMIP6 brings together the most recent simulation data from major climate models on a global scale, providing a broader and more diverse range of model results and thereby making future predictions more accurate and dependable, and its findings provide a theoretical foundation for the emergency management of and scientific responses to urban flooding events. The following major conclusions were reached: 1. The best-performing models are EC-Earth3, GFDL-ESM4, and MPI- ESM1-2-HR. EC-Earth3 is a modular Earth system model developed collaboratively by a European consortium. MPI-ESM1-2 is a climate precipitation prediction model developed in Germany and promoted for global application, whereas the GFDL-ESM4 model was developed in the United States and is currently employed for global climate precipitation simulations. 2. Under future climate circumstances, the total annual precipitation in the example region simulated by all three models increases by a maximum of 40%. 3. Under future climatic conditions, urban surface runoff and nodal overflow in the study area will be more significant. The node overflow will become more severe with the increase in climate scenario oppression, and the potential overflow nodes will account for 1.5%, 2.7%, and 2.9% of the total number of nodes under the SSP1–2.6, SSP2–4.5, and SSP5–8.5 scenarios, respectively. 4. In the future, the effectiveness of stormwater drainage systems may diminish. To increase climate change resilience, the impacts of climate change should be considered when planning the scope of stormwater optimization and the integrated improvement of gray–green–blue facilities.

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Spatiotemporal variations in precipitation extremes based on CMIP6 models and Shared Socioeconomic Pathway (SSP) scenarios over MENA

Cited by 6 publications

References 36 publications

Towards Sustainable Water Resources Management Considering Climate Change in the Case of Saudi Arabia

Towards Sustainable Water Resources Management Considering Climate Change in the Case of Saudi Arabia

Modeling Hydrological Responses of Watershed Under Climate Change Scenarios Using Machine Learning Techniques

Prediction of Future Urban Rainfall and Waterlogging Scenarios Based on CMIP6: A Case Study of Beijing Urban Area

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