پيش‌بيني رواناب حوضه آبريز تيره با استفاده از پيش‌بيني كمي بارش خروجي مدل WRF

Real time runoff forecasting of Tire basin using Quantitative Precipitation Forecasting of WRF model

هدف از انجام اين پژوهش پيش بيني رواناب با استفاده از پيش بيني كمي بارش حاصل از برونداد مدل هاي پيش بيني عددي جو مي باشد. لذا در جهت انجام پژوهش حاضربراي پيش بيني بارش از مدلWRFوبراي پيش بيني رواناب از مدل HECHMS استفاده گرديد. نخست براي آماده سازي مدل HMS جهت پيش بيني رواناب، ازداده هاي ديدباني بارش در مقياس ساعتي و روزانه و همچنين دبي ساعتي اخذ شده از سازمان هاي ذيربط استفاده شد. پس از بررسي آمار مأخوذه تعدادي رويداد سيلاب جهت واسنجي مدل HECHMS انتخاب گرديد،اين رويدادها با مدل HMS شبيه سازي شد. در پي آن با آزمون هاي متوالي و روش سعي و خطا براي بهترين شبيه سازي انجام شده جهت تعيين پارامترهايي از قبيل شماره منحني، زمان تاخير و ضريب دبي اوج بهينه گرديدندو از آنها جهت اعتبارسنجي مدل بهره برده شد. پس از واسنجي مدل HECHMS سه رويداد سيل جهت راست آزمايي مدل انتخاب گرديد. در اين مرحله از كار بارش مولد سيلاب هاي منتخب جهت راست آزمايي مدل HECHMS توسط مدل پيش بيني عددي جو، WRF پيش بيني شد. سپس بارش حاصل از برونداد اين مدل ها به عنوان ورودي مولفه بارش مدل HECHMS بكارگرفته شد، و مدل HECHMS با اين مقادير بارش اجرا گرديد. نتايج حاصل به طور خلاصه به اين شرح مي باشد مقادير رواناب پيش بيني شده كمتر از مقادير مشاهده اي آن مي باشد در پيش بيني رواناب،  نتايج حاصل در رويداد ارديبهشت 1382و1383 قابل قبول بوده و نتايج رويداد اسفند 1383 چشم گير نبودهاست. به گونه اي كه ميانگين خطاي مطلق پيش بيني، قدرمطلق خطاي نسبي دبي اوج و حجم براي رويداد اسفند 1383به ترتيب 76، 4/41و 7/39 مي باشد. اين مقادير براي رويداد ارديبهشت 1382 به ترتيب 23، 13/16 و 48/15و براي رويداد ارديبهشت 1383به ترتيب 13، 22/1 و 94/18 به دست آمده است. بنابراين مي توان گفت در بررسي رويداد هاي فوق دو رويداد كه در فصل بهار رخ داده اند نتايج بهتري به دست آمده است. شايان ذكر است كه اين نتايج مربوط به بررسي هاي انجام شده است و تعميم آن منوط به بررسي هاي مكاني و زماني بيشتري مي باشد.

Introduction Due to their high speed, flash floods are placed among the most important devastating disasters to humanity in contrast to other disasters such as drought and famine. The event is usually results from heavy precipitation. If the flood forecasting is done by an appropriate method, dealing with can be managed more properly. There are many parameters which are effective on models of flood forecasting. An essential component for flood forecasting is quantitative precipitation forecasting (QPF). At present, QPF is provided using limited area numerical models. The output of these local models is also used for operational and research purposes in Iran. Concerning the importance of QPF for flood forecasting of, in this research, the QPF output of the WRF model is used as an input for the HECHMS hydrology model to forecast the flood of Tire basin in Lorestan province of Iran.   Materials and Methods The Tire basin, in the west and southwest of Iran, is one of the subbasins of the large Dez basin. In this research, hourly and daily precipitation data of rain gauges and also hourly discharge  data from stations were collected and studied,. After preparation and qualitative control of the mentioned data sets, some preparations were applied for calibration of the HECHMS model and some of its hydrological parameters such as lag time, curve number and coefficient of maximum discharge were reconsidered. By topographic evaluation and assessment of soil and plant coverage of the region, needed preliminary data for performing of HECHMS model were estimated by trial and error method. After calibration and obtaining the optimum parameters, model verification was done using ther results obtained from 3 events thatwere not used for calibration already. For verification of rainfallrunoff models, forecasted precipitation of the meteorological WRF model was used. Simulated precipitations were used in the HECHMS model as an input and then runoff was simulated. Finally, simulated runoff was verified by statistical gauges.   Results Three statistical criteria are computed in order to evaluate the capability of the coupled model including: the bias, the Mean Absolute Error (MAE), and the absolute relative error. The minimum MAE for the studied events was 13 (m3/s) and the maximum was 76 (m3/s). The minimum and maximum of absolute relative error for peak discharge in the studied events were 1.22, 41.4 (m3/s), respectively. The Minimum and the maximum of absolute relative error for volume of discharge in the studied events were 15.48 and 39.7. Time lags between the observed peak discharge and simulated peak discharge is calculated as 3 to 6 hours. Examining the results, we conclude that the coupled model is working much better for spring events in comparison to winter events. Conclusion According to this research it can be said that the combination of WRF and HECHMS models increases the lead time of runoff prediction in real time forecasting. In spite of low errors in the forecasting, it can be said that the complete simulation were partly desirable. These results related to the tested cases in the research and generalizing of these results depend on to the more and extended research in the different fields and events. According to the importance of these kinds of forecasts, we suggest to eliminate the errors of these forecasts performing more studies and investigations.