نوع مقاله : مقاله پژوهشی
نویسندگان
1 دانشجوی دکتری مهندسی منابع آب، گروه مهندسی آبیاری و آبادانی، پردیس کشاورزی و منابع طبیعی، دانشگاه تهران
2 دانشیار گروه مهندسی آبیاری و آبادانی، پردیس کشاورزی و منابع طبیعی، دانشگاه تهران،
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
The climate change (CC) shall certainly affect the water resources. As the presumed negative effects are serious matter of concern to countries experiencing water shortage, these phenomena have to be studied. Therefore, a new probabilistic approach was taken to evaluate the CC impacts on stream flow. To generate climate change scenarios in the foreseeable future and under A2 emission scenarios, the HadCM3 model was employed. By introducing climatic variable time series in future periods to the IHACRES hydrological model, long-term stream flow simulation scenarios were produced. By fitting the statistically different distributions on the runoff produced by using the goodness-to-fit tests, the most appropriate statistical distribution for each month was chosen and relevant statistical parameters were extracted and compared with the statistical parameters of runoff during the base period. Results showed that the long-term average annual runoff during the three future periods will decrease compared with the base period. Despite the reduction in the total runoff volume in the future periods compared with the baseline period, the decrease was concerned with the medium and high flow. The low flow rates, the total volume of runoff for the future periods compared with the baseline period will increase 47, 41, and 14%, respectively. To assess the further impact of annual average runoff on flow rates, it is necessary to examine the correlations of time series using the stream flow transmission probability. To compare the stream flow probability in each of the future periods with base period stream flow in each month, the stream flow was discretized and the performance criteria were used.
This approach was used for the Aidoghmoush River, East Azerbaijan. Results show a low coefficient of correlation and high error indicators.
کلیدواژهها [English]