بررسی نوسانات روانآب حاصل از ذوب برف تحت تاثیر پدیده تغییر اقلیم در دهه‌های آینده

با توجه به گسترش رشته کوه‌های زاگرس در بخش‌های غرب و جنوب غرب کشور، پوشش برفی این رشته کوه‌ها یکی از منابع بزرگ تامین آب در حوزه‌های آّبریز دز، ‌کرخه و کارون می‌باشد این در حالی است که تغییر در سطح پوشش برف در دهه‌های آینده می‌تواند روانآب حاصل از ذوب برف که نقش عمده‌ای در تامین پتانسیل آبی در این مناطق را دارا می‌باشد، دستخوش تغییراتی قرار دهد. در پژوهش حاضر نوسان روانآب حاصل از ذوب برف تحت تاثیر تغییرات دما و بارش با استفاده از مدل srm در دوره‌های 2020 (2010-2039)، 2030 (2020-2049)، 2040 (2030-2059)، 2050 (2040-2069)، 2060 (2050-2079)، 2070 (2060-2089) و 2080 (2070-2099) با بهره‌گیری از برونداد مدل hadcm3 از مرکز تحقیقات و پیش بینی اقلیمhadley تحت سناریوی a1b در حوضه آبریز بختیاری مورد بررسی قرار گرفته است. در این مطالعه دوره آماری 1961-1990دوره اقلیمی پایه در نظر گرفته شده است و سری زمانی داده‌های مشاهداتی دما و بارش برای ایستگاه‌های منطقه مورد مطالعه در دوره مذکور جمع آوری گردیده ‌است. برای پیش بینی متغیرهای اقلیمی از مدل‌های گردش عمومی جو (general circulation model) مدل  hadcm3انتخاب و برونداد‌های این مدل برای متغیرهای دما و بارش در مقیاس (0/5 * 0/5 درجه) از پایگاه داده‎های climgen با سناریو انتشارa1b  برای هر دوره سی‌ساله 2020 (2010-2039) تا 2080 (2070-2099) استخراج و تحلیل شده است. سپس با اعمال سناریوهای تغییر اقلیم و تغییرات سطح پوشش برف، شبیه‎سازی روانآب با استفاده از مدلsrmدر دوره‌های یاد شده ارزیابی گردیده است. نتایج بدست آمده از شبیه‌سازی، کاهش حجم روانآب در دوره‎های یاد شده را نشان می‌دهد.

Estimating the Impact of Climate change on Snowmelt Runoff on Feature

IntroductionAccording to the Intergovernmental Panel on Climate Change (IPCC), mean global surface temperature increased 0.6 ± 0.2ºC in the 20th century. Snow cover decreased by 10% since the late 1960’s.General Circulation Models (GCMs) are an important tool in the assessment of climate change. These numerical coupled models represent various earth systems including the atmosphere, oceans, land surface and seaice and offer considerable potential for the study of climate change and variability (H. J. Fowler).The spatial resolutions of GCMs are about 1.1° or 4° in latitude and from 1.1° to 5° in longitude. Tether for, major problems in using the output of GCM is their low degree of resolution and large scaling. So to make them appropriate for use, downscaling methods have been developed to overcome this problem.ClimGendownscling method ClimGen combines GCMresolution climate change data derived from the pattern scaling method at a 5 degree resolution with observations of climate at half –degree resolution to simulate future climates at halfdegree resolution contains a database of outputs from GCMs and currently produces 8 climate variables on a 0.5 x 0.5 degree grid: temperature (max1, mean and min), precipitation, vapor pressure, cloud cover and wetday frequency. For each month, season, or annually.Materials and MethodsThe climate change scenario data used in this study are based on simulations carried out using General Circulation Models (GCMs) for the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC, 2007). For our assessment we used simulations of monthly temperature and precipitation over the period 20102099 carried using the climate model HADCM3 and future projections in the context of the A1B scenario.The A1B scenario describes a world of very rapid economic growth, global population that peaks in the mid21st Century and declines thereafter, and the rapid introduction of new and more efficient technologies.The Snowmelt Runoff Model (SRM (is one of the applied models for simulation and forecasting of Snowmelt runoff in mountainous areas where snowmelt is a major runoff factor. This model based on the DegreeDay factor, which is used to simulate snowmelt runoff during the melt season. The input parameters for the model are derived from satellite data, metrological and hydrological data.In this study, MODIS8 daily (MOD10A2) snow cover products are used for snow cover maps (2006). Topographic Mission (SRTM) data is used to obtain the digital elevation model (DEM) of the region and to create different elevation zones.The Normalized Difference Snow Index (NDSI) algorithm is applied with the reflectance of band 4 and band 6 for snow cover mapping and to differentiate the snow from other land features. Because The NDSI is a useful tool to calculate the snow covered area. The Snow Cover Depletion Curve (SCDC) is made using the DEM and snow cover maps to get daily percent values of snow covered area. The SCDC is an important variable for the SRM simulations. Other variables (temperature and precipitation) and parameters (degreeday factor, recession coefficient, runoff coefficients, time lag, critical temperature and temperature lapse rate) are used as input to the SRM model for snowmelt simulation.In order to analyze climate change impacts on Snowmelt by HadCM3 model, we compared the simulated values for the baseline period 19611990 with the values for 7 periods in the future: (20102039….20702099) based ClimGen model.ResultsMean monthly temperature and precipitation for the base period (1961 1990) with the observed data at stations in the same period, the study was conducted and the results showed that the model simulated temperature and precipitation ClimGen is acceptable.Climate change scenarios of temperature and precipitation in the region shows that the temperature rise and changes in precipitation in the basin in the coming years is fluctuating.Snow melt runoff in the month of January to December 2006 was simulated. The results show value of (R2) is 0.71 and the volume difference DV is 0.45 %.Then consider scenarios of climate change and changes in the values of snow cover, runoff simulations were performed for the future.ConclusionFor study the effects of climate change on river flow and snow cover in the study area use SRM model. Result shows Due to the increased temperatures and increased snow melt, because of reduced snow cover, basin runoff does not increase.