Evaluation of Synthetic Outlet Runoff Assessment Models

Quantitative understanding and prediction of the processes of runoff generation and its transmission to the outlet represent one of the most basic and challenging areas of hydrology. Traditional techniques for design flood estimation use historical rainfall-runoff data for unit hydrograph (UH) derivation. Such techniques have been widely applied for the estimation of design flood hydrograph at the sites of gauged catchment. For ungauged catchments, unit hydrograph may be derived using synthetic SCS and Snyder unit hydrograph models. This research has been carried out for comparison of the correctness of SCS and Snyder unit hydrograph models in determination of the shape and dimensions of outlet runoff hydrograph in Kasilian watershed. This watershed has 67.5 km2 area and it locates in Mazandaran province of Iran. The runoff hydrographs computed by the SCS and Snyder models were compared with observed hydrographs by using of three error functions, viz. 1-model efficiency (EFF), 2-percentage error in peak (PEP), and 3-percentage error in time to peak (PETP). The results reveal the accuracy and applicability of these synthetic models for derivation of runoff hydrograph

Copula-based probabilistic assessment of intensity and duration of cold episodes: A case study of Malayer vineyard region

Frost, particularly during the spring, is one of the most damaging weather phenomena for vineyards, causing significant economic losses to vineyards around the world each year. The risk of tardive frost damage in vine-yards due to changing climate is considered as an important threat to the sustainable production of grapes. Therefore, the cold monitoring strategies is one of the criteria with significant impacts on the yields and prosperity of horticulture and raisin factories. Frost events can be characterized by duration and severity. This paper investigates the risk and impacts of frost phenomenon in the vineyards by modeling the joint distribution of duration and severity factors and analyzing the influential parameter’s dependency structure using capabilities of copula functions. A novel mathematical framework is developed within this study to understand the risk and uncertainties associate with frost events and the impacts on yields of vineyards by analyzing the non-linear dependency structure using copula functions as an efficient tool. The developed model was successfully vali-dated for the case study of vineyard in Malayer city of Iran. The copula model developed in this study was shown to be a robust tool for predicting the return period of the frost events