Exploring controls on rainfall–runoff events:spatial dynamics of event runoff coefficients in Iran

This study investigates the controls that influence the spatial variability of event runoff coefficients (RCs) based on the comparative hydrology concept. We analysed 18 468 storm events in 963 Iranian catchments ranging in size from 101 to 8467 km2. The mean RCs vary spatially due to long-term hydro-climate conditions and other catchment descriptors (CDs). The controls on spatial variability of RCs are investigated using a correlation analysis of the statistical moments of the RCs and CDs. The results indicate (1) catchment elevation is the most important control on RCs at the country scale, and hydro-climatic attributes such as mean annual precipitation, ratio of actual evaporation to precipitation, and the ratio of potential evaporation to precipitation are other important controls on RCs; and (2) at the regional scale, catchment area is a major control on RCs, although it is not as important as hydro-climatic controls at the national scale.</p

Prediction of Heat Transfer Coefficients in Drag Reducing Turbulent Pipe Flows

Mechanical Engineerin

Comparing spatial and temporal scales of hydrologic model parameter transfer: A guide to four climates of Iran

Simulating streamflow in ungauged catchments remains a challenging task in hydrology and increases the demand for regionalization studies worldwide. Here, we investigate the effect of three modes of parameter transfer, including temporal (transferring across different periods), spatial (transferring between same calibration periods but different sites), and spatiotemporal (transferring across both different periods and sites) on simulating streamflow using HBV conceptual rainfall-runoff model at 576 unregulated catchments throughout Iran (407,000 Km2). Our main conclusions are: (1) temporal mode shows the best performance, with the lowest decline in performance (median decline of 5.8%) as measured using the NSE efficiency metric, (2) difference between spatial and spatiotemporal options was negligible (median decline of 13.7% and 15.1% respectively), (3) all parameters are associated with some uncertainties and those related to runoff and snow components of the model are associated with the highest and lowest uncertainties, respectively, (4) overall, the model performance in arid regions is not as good as humid regions which confirmed that elevation and climate play a major role in parameter estimation in these areas, and (5) aridity and catchment elevation are two major controls on model transferability at regional (climate classes) and local (the whole country) scales. We also show that the superiority of the temporal mode is maintained with: (i) increasing spatial distance between gauged (donor) and ungauged (target) catchments, (ii) increasing time lag (10 years) between calibration and validation, and (iii) gradually increased time lags between calibration and validation. Our study suggest that spatiotemporal parameter transfer can be a reliable option for PUB studies and climate change-related studies, at least in wetter catchments. However, further research is needed to explore the complicated relationship between temporal and spatial aspects of hydrological variability

Flood process types and runoff coefficient variability in climatic regions of Iran

This study analysed the spatiotemporal variability of runoff coefficients (RCs) in four climatic regions based on 18 468 events recorded in 963 Iranian catchments. Five flood process types were identified using a classification scheme. The results show that winter and spring have higher mean RCs of 0.46 and 0.42, respectively, confirming the role of snowmelt and heavy precipitation in flood runoff generation in these seasons. Event saturation conditions (i.e. event rainfall depth) had a stronger impact on RC variability than pre-event saturation conditions (i.e. antecedent rainfall depth). Flood occurrence varies significantly by season and region, with short rains being the most common type of flooding. Rain-on-snow floods, snowmelt, and long-rain floods had higher RCs than other types, and significant differences in RCs were observed across the four climate regions using the non-parametric Kolmogorov-Smirnov test. The median flood time scale is between 1 and 20 days in all catchments.</p