Abstract
This study investigated the effects of climatic changes on temperature, rainfall, and runoff in the Doroudzan catchment in the northeast of Fars province, Iran. Temperature and rainfall changes in three periods including 2011–2030, 2046–2065, and 2080–2099 were downscaled and studied using 15 Coupled Model Intercomparison Project, Phase 3 (CMIP3) climatic models, under three scenarios of greenhouse gas emissions A2, B1, and A1B, from the database of the LARS-WG model. The difference in the amount of changes in temperature and rainfall in these three periods and the observational amounts under the 15 models indicated the uncertainty of the changes values. To reduce this uncertainty and limit the results to the management and planning of water resources, ensemble approach was considered. For the preparation of the ensemble approach, the parameters from the files of the 15-model scenarios were averaged so that a climatic ensemble model could be obtained for each period. Then, the runoffs of the next three periods, under the second approach and three emission scenarios, were produced using the feedforwad neural network. The results indicated an increase in the average monthly maximum temperature and the minimum temperature in all three periods under the three scenarios. The results also showed a decrease in the rainfall in the early months of the year as well as an increase in the rainfall in the spring in most scenarios. Generally, the average annual rainfall in all these three periods under the climatic ensemble model, and three emission scenarios showed a reduction in the average annual rainfall in the three periods. The maximum amount of reduction was in 2080–2099 (101 mm) under the scenario B1. Besides, a reduction occurred in the average runoff of the catchment under three ensemble models and the emission scenario in all three periods, as compared to the average of the long-term observational values in most years.
Highlights
Climatic changes and management of the existing water resources have recently been a serious challenge worldwide
Advances in Meteorology increased production of greenhouse gasses, especially carbon dioxide, together with overpopulation and further uses of fossil fuels due to the expansion of industries, has resulted in the rise of the earth’s temperature. e wide range in the temperature increase has been predicted to be between 1.4 and 5.8 degrees in centigrade depending on the selected scenario and the AOGCM (Atmospheric-Ocean General Circulation Model) till 2100 [1]
Among the valid and important measures used for the investigation of the effects of climatic changes on hydrologic and meteorological variables, one can refer to the simulation of climatic variables using AOGCM
Summary
Climatic changes and management of the existing water resources have recently been a serious challenge worldwide. Erefore, after downscaling, the GCMs output, rainfall, and temperature under different climatic models have been used as the input for the simulation of the runoffs of the future periods. Hassanzadeh et al, for instance, predicted the effect of climatic changes on river runoffs in the basin of Lake Urmia for the 2010–2100 period To this end, they used HADCM3 (Hadley Centre Coupled Model, version 3) parameters. Ey used the artificial neural network (ANN) to simulate the rainfall-runoff model According to their results, the outputs of most models showed an increase in the temperature and a decrease in the rainfall in the period [11]. GDX learning algorithm was found to have the highest precision and convergence speed, but the LM algorithm had the lowest speed [19,20,21]
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