TY - JOUR ID - 61697 TI - Daily Rainfall Temporal Distribution Patterns and its Relations with Short-Term Precipitations in Coastal – Forest Areas (Case Study: Nowshahr Station, Northern Iran) JO - Journal of Range and Watershed Managment JA - JRWM LA - en SN - 5044-2008 AU - Moradnezhadi, Maryam AU - Malekian, Arash AU - Jourgholami, Meghdad AU - Ghasemi, Ali AD - MSc. Student of Forest Engineering, Faculty of Natural Resources, University of Tehran, I.R.IRAN. AD - Assistant professor, Faculty of Natural resources, University of Tehran, I.R.IRAN AD - Assistant professor, Department of Forestry and Forest Economics, Faculty of Natural Resources, University of Tehran, I.R.IRAN AD - MSc. Student of Watershed Management, Faculty of Natural Resources, University of Tehran, I.R.IRAN. Y1 - 2016 PY - 2016 VL - 69 IS - 2 SP - 475 EP - 485 KW - Nowshahr station KW - SCS pattern KW - Huff pattern KW - Rainfall Temporal Distribution KW - 24 hour precipitation KW - riparian forest DO - 10.22059/jrwm.2016.61697 N2 - 24 hour precipitation distribution pattern and its relationship to short-term rainfall is an important issue in hydrology studies such as in flood simulation and in design of hydraulic structures. Accordingly, this study made an attempt to investigate the relationship between daily precipitation and hourly and minute precipitation using data from rain gauge station of Nowshahr in a coastal-forest region in north of Iran. The patterns of daily rainfall temporal distribution were examined using Pilgrim and Huff techniques. Finally, the obtained regional pattern using statistics were analyzed to evaluate absolute percent relative error, mean absolute error, root mean squared error and mean square error. Results of the relationship between 24 hour precipitation and 5 and 30 minutes and 1, 2, 3, 6, 9, 12, and 18 h rainfall showed that in all cases an exponential relationship can better explain this relationship than linear regression equations and logarithmic relations. Study of the rainfall temporal distribution pattern showed that in all extracted 24 hour events, the highest rainfall occurred in the lower quartile and in all rainfall events constant decrease in rainfall intensity occurred from the moment it started till it ended so that no fluctuation was observed in precipitation over time signaling that rainfall intensity would increase again. The results indicated that in similar areas, l SCS-type IA model could show reasonably better estimation in comparison with other models. UR - https://jrwm.ut.ac.ir/article_61697.html L1 - https://jrwm.ut.ac.ir/article_61697_435fa92f0ca316153761873bab264d2c.pdf ER -