Countries in Middle East and North Africa (MENA region) are considered as arid and semi-arid areas that are suffering from water scarcity. They are expected to have more water shortages problem due to climatic change....Countries in Middle East and North Africa (MENA region) are considered as arid and semi-arid areas that are suffering from water scarcity. They are expected to have more water shortages problem due to climatic change. Iraq is located in the Middle East covering an area of 433,970 square kilometers populated by 31 million inhabitants. One of the solutions suggested to overcome water scarcity is Rainwater Harvesting (RWH). In this study Macro rainwater harvesting technique had been tested for future rainfall data that were predicted by two emission scenarios of climatic change (A2 and B2) for the period 2020-2099 at Sulaimaniyah Governorate north east of Iraq. Future volumes of total runoff that might be harvested for different conditions of maximum, average, and minimum future rainfall seasons under both scenarios (A2 and B2) were calculated. The results indicate that the volumes of average harvested runoff will be reduced when average rainfall seasons are considered due to the effect of climatic change on future rainfall. The reduction reached 10.82 % and 43.0% when scenarios A2 and B2 are considered respectively.展开更多
The Middle East (ME) is characterized by its water shortage problem. This region with its arid climate is expected to be the most vulnerable in the world to the potential impacts of climate change. Iraq (located in ME...The Middle East (ME) is characterized by its water shortage problem. This region with its arid climate is expected to be the most vulnerable in the world to the potential impacts of climate change. Iraq (located in ME) is seriously experiencing water shortage problem. To overcome this problem rain water harvesting can be used. In this study the applicability of the long-term weather generator model in downscaling daily precipitation Central Iraq is used to project future changes of precipitation based on scenario of seven General Circulation Models (GCMs) outputs for the periods of 2011-2030, 2046-2065, and 2080-2099. The results indicated that December-February and September-November periods, based on the ensemble mean of seven GCMs, showed an increasing trend in the periods considered;however, a decreasing trend can be found in March, April, and May in the future.展开更多
Impact and adaptation assessments of climate change often require more detailed information of future extreme rainfall events at higher resolution in space and/or time, which is usually, projected using the Global Cli...Impact and adaptation assessments of climate change often require more detailed information of future extreme rainfall events at higher resolution in space and/or time, which is usually, projected using the Global Climate Model (GCM) for different emissions of greenhouse concentration. In this paper, future rainfall in the North West region of England has been generated from the outputs of the HadCM3 Global Climate Model through downscaling , employing a hybrid Generalised Linear Model (GLM) together with an Artificial Neural Network (ANN). Using two emission scenarios (A1FI and B1), the hybrid downscaling model was proven to have the capability to successfully simulate future rainfall. A combined peaks-over-threshold (POT)-Generalised Pareto Distribution approach was then used to model the extreme rainfall and then assess changes to seasonal trends over the region at a daily scale until the end of the 21st century. In general, extreme rainfall is predicted to be more frequent in winter seasons for both high (A1FI) and low (B1) scenarios, however for summer seasons, the region is predicted to experience some increase in extreme rainfall under the high scenario and a drop under the low scenario. The variation in intensity of extreme rainfall was found to be based on location,season, future period, return period as well as the emission scenario used.展开更多
文摘Countries in Middle East and North Africa (MENA region) are considered as arid and semi-arid areas that are suffering from water scarcity. They are expected to have more water shortages problem due to climatic change. Iraq is located in the Middle East covering an area of 433,970 square kilometers populated by 31 million inhabitants. One of the solutions suggested to overcome water scarcity is Rainwater Harvesting (RWH). In this study Macro rainwater harvesting technique had been tested for future rainfall data that were predicted by two emission scenarios of climatic change (A2 and B2) for the period 2020-2099 at Sulaimaniyah Governorate north east of Iraq. Future volumes of total runoff that might be harvested for different conditions of maximum, average, and minimum future rainfall seasons under both scenarios (A2 and B2) were calculated. The results indicate that the volumes of average harvested runoff will be reduced when average rainfall seasons are considered due to the effect of climatic change on future rainfall. The reduction reached 10.82 % and 43.0% when scenarios A2 and B2 are considered respectively.
文摘The Middle East (ME) is characterized by its water shortage problem. This region with its arid climate is expected to be the most vulnerable in the world to the potential impacts of climate change. Iraq (located in ME) is seriously experiencing water shortage problem. To overcome this problem rain water harvesting can be used. In this study the applicability of the long-term weather generator model in downscaling daily precipitation Central Iraq is used to project future changes of precipitation based on scenario of seven General Circulation Models (GCMs) outputs for the periods of 2011-2030, 2046-2065, and 2080-2099. The results indicated that December-February and September-November periods, based on the ensemble mean of seven GCMs, showed an increasing trend in the periods considered;however, a decreasing trend can be found in March, April, and May in the future.
文摘Impact and adaptation assessments of climate change often require more detailed information of future extreme rainfall events at higher resolution in space and/or time, which is usually, projected using the Global Climate Model (GCM) for different emissions of greenhouse concentration. In this paper, future rainfall in the North West region of England has been generated from the outputs of the HadCM3 Global Climate Model through downscaling , employing a hybrid Generalised Linear Model (GLM) together with an Artificial Neural Network (ANN). Using two emission scenarios (A1FI and B1), the hybrid downscaling model was proven to have the capability to successfully simulate future rainfall. A combined peaks-over-threshold (POT)-Generalised Pareto Distribution approach was then used to model the extreme rainfall and then assess changes to seasonal trends over the region at a daily scale until the end of the 21st century. In general, extreme rainfall is predicted to be more frequent in winter seasons for both high (A1FI) and low (B1) scenarios, however for summer seasons, the region is predicted to experience some increase in extreme rainfall under the high scenario and a drop under the low scenario. The variation in intensity of extreme rainfall was found to be based on location,season, future period, return period as well as the emission scenario used.