@article { author = {khalili, reza and panahi, Hamid reza and Montaseri, Hossein and Hekmat Zadeh, Ali Akbar}, title = {Evaluating the effects of climate change on precipitation and runoff using IHACRES models (case study: Bashar River)}, journal = {Journal of Environmental Science Studies}, volume = {7}, number = {4}, pages = {5805-5815}, year = {2022}, publisher = {}, issn = {2588-6851}, eissn = {2645-520X}, doi = {10.22034/jess.2022.353450.1833}, abstract = {Abstract Introduction Due to the space and time limitations, measuring the flow of rivers, this task will face problems that in recent years, researchers have turned to designing hydrological models to check and estimate the flow of rivers. The existence of a tool to estimate discharge can lead to the best possible management of surface water and its optimal use. In addition to these, climate change, water quality changes and ecological studies can be evaluated using runoff estimation hydrology models. Successful management of water resources requires a qualitative analysis of the effects of climate change and land use practices on water flow and quality. While expert knowledge can provide indications of such impacts, detailed analysis requires the use of mathematical models to dynamically disentangle the water balance (at the time scale at which important processes are involved). This includes separating precipitation into evapotranspiration losses, runoff to streams, recharge to groundwater systems, and changes in short-term watershed storage. Some of the processes to consider are: evapotranspiration. and feedback to Joe. vegetation dynamics; The level of underground water and its effect on waterlogging and soil salinization; Reliability of tank storage capacity; wetland dynamics; flood urban runoff; Erosion in agricultural and pasture lands as well as channel erosion and sedimentation and aquatic ecosystem functions. Arid and semi-arid regions are usually affected by heavy rainfall events with a high degree of spatial variability. This usually results in a fast response profile, and in areas without weather radar coverage, the poor density of rain gauges prevents accurate estimation of precipitation depth and spatial distribution for a particular event. Furthermore, if only daily precipitation data are available, precipitation model calibration -Runoff in a daily step means that most of the information in the hydrograph is not used (note that runoff here means total streamflow, not just surface runoff). ). Another important consideration for calibrating models for watersheds in arid and semi-arid regions is the frequency of events. Such watersheds have less flow than watersheds in wetter climates. This means that longer calibration periods are needed to reduce the uncertainty in the model parameters. Otherwise, the parameter values are more prone to errors in the data, with a significant decrease in performance in the simulation compared to the calibration.Methodology In this research, IHCRAES model is used for rainfall-runoff simulation. Due to physical and time limitations, the measurement of river flow is facing problems, researchers have turned to designing hydrological models to investigate and estimate river flow. Due to the lack of hydrometric stations in small or upstream basins, the development of tests that can estimate the water flow on a daily time scale and in a desired location is one of the necessary things that leads to the improvement of the information needed for management purposes related to water resources. In order to evaluate the performance of the model parameters, the coefficient of determination of the model (D), the Nash-Sutcliffe coefficient, the average relative error of the parameter (ARPE) and the total error in the flow volume (Bias) which are calculated and used by the model itself. The higher the D value and the lower the ARPE parameter values, the more ideal the model results. Bias parameter values also indicate whether the simulated flow is more or less than the observed flow, and in other words, it specifies that the model simulates the flow more than the reality or less than the reality. After validating the IHACRES model and ensuring its effectiveness, exponential microscale results are entered into it and the runoff of the next decade is predicted and evaluated. In the figure, we can see the model of the IHACRES model and how to simulate rainfall and runoff.In general, this model is an integrated metric conceptual model for rainfall-runoff simulation, which was developed by Jackman in 1990. The IHACRES model has always been of interest due to the need for less data and high power in daily estimation. Due to physical and time limitations, the measurement of river flow is facing problems, researchers have turned to designing hydrological models to check and estimate river flow. The existence of a tool to estimate discharge can lead to the best possible management of surface water and its optimal use. In addition, climate change, water quality changes and ecological research can be evaluated using hydrological models for runoff estimation. Hydrological relationships between precipitation and runoff have always been investigated and tested by water researchers. The IHACRES model has always been of interest due to the need for low data and high power in daily estimation. This model has been used by Karenko et al. (2008) for purposes such as evaluating climate variables such as changes in precipitation, temperature, and runoff coefficient changes. Due to the lack of hydrometric stations in small or upstream basins, the development of tests that can estimate the water flow on a daily time scale and in a desired location is one of the necessary things that leads to the improvement of the information needed for management purposes related to water resources.Conclusion In the section of predicting the amount of changes in discharge and runoff in the future using IHACRES rainfall and runoff simulation software, the results show that this model has a high ability to estimate discharge for basins with low discharge and is less suitable for high discharges. The main and essential point in this study is that the main factor affecting the reduction of water resources in the coming periods is the increase in temperature and, as a result, the increase in evaporation and transpiration in the river basin and the lack of proper management of water resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .}, keywords = {"Climate change","rainfall and runoff","IHACRES models","Bashar river"}, title_fa = {بررسی اثرات پدیده تغییر اقلیم بر بارش و رواناب با استفاده از مدل‌های IHACRES (مطالعه موردی : رودخانه بشار)}, abstract_fa = {به علت محدودیت‌های مکانی و زمانی، اندازه‌گیری دبی رودخانه‌ها این کار با مشکلاتی روبه‌رو خواهد بود که در سال های اخیر محققین جهت بررسی و برآورد دبی رودخانه‌ها روی به طراحی مدل‌های هیدرولوژیکی آورده‌اند. وجود ابزاری برای برآورد دبی، می‌تواند به مدیریت هرچه بهتر آب‌های سطحی و استفاده بهینه از آن منجر گردد. علاوه بر این موارد، تغییر اقلیم، تغییرات کیفیت آب و مطالعات اکولوژی می‌توانند با استفاده از مدل‌های هیدرولوژی برآورد رواناب مورد ارزیابی قرار گیرند.یکی ازمدل های بررسی بارش-رواناب مدل IHACRESمی باشد. مدل IHACRES همواره به دلیل احتیاج به داده‌های کم و قدرت بالا در برآورد روزانه موردتوجه قرار گرفته است. مدل بارش-رواناب IHACRES که داده‌های سری زمانی ماهانه دبی، بارش و دما را به‌عنوان ورودی مدل دریافت می کند و میزان تغییرات دبی رودخانه پیش‌بینی می‌شود. در بخش پیش‌بینی میزان تغییرات دبی و رواناب در آینده با استفاده از نرم‌افزار شبیه‌ساز بارش و رواناب IHACRES نتایج نشان می‌دهد که این مدل توانایی بالا در برآورد دبی برای حوضه‌هایی با دبی پایین دارد و برای دبی‌های زیاد کمتر مناسب است. نکته اصلی و ضروری در این مطالعه این است که عامل اصلی تأثیرگذار بر کاهش منابع آبی در دوره‌های آتی، افزایش درجه حرارت دما و درنتیجه آن افزایش میزان تبخیر و تعرق در حوضه رودخانه و عدم مدیریت مناسب منابع آبی می‌باشد.}, keywords_fa = {" تغییر اقلیم "," بارش و رواناب "," مدل‌های IHACRES "," رودخانه بشار "}, url = {https://www.jess.ir/article_160196.html}, eprint = {https://www.jess.ir/article_160196_01625e15e01984186e52d632d0fca98a.pdf} }