Abstract: Drawing on advances in nonstationary frequency analysis and the science of causation and attribution, this study employs a newly developed nonstationary stochastic paired watershed approach to determine the effect of forest harvesting on snowmelt-generated floods. Moreover, this study furthers the application of stochastic physics to evaluate the environmental controls and drivers of flood response. Physically-based climate and time-varying harvesting data are used as covariates to drive the nonstationary flood frequency distribution parameters to detect, attribute, and quantify the effect of harvesting on floods in the snow-dominated Deadman River (878 km2) and nested Joe Ross Creek (99 km2) watersheds. Harvesting only 21% of the watershed caused a 38% and 84% increase in the mean but no increase in variability around the mean of the frequency distribution in the Deadman River and Joe Ross Creek, respectively. Consequently, the 7-year, 20-year, 50-year, and 100-year flood events became approximately two, four, six, and ten times more frequent in both watersheds. An increase in the mean is posited to occur from an increase in moisture availability following harvest from suppressed snow interception and increased net radiation reaching the snowpack. Variability was not increased because snowmelt synchronization was inhibited by the buffering capacity of abundant lakes, evenly distributed aspects, and widespread spatial distribution of cutblocks in the watersheds, preventing any potential for harvesting to increase the efficiency of runoff delivery to the outlet. Consistent with similar recent studies, the effect of logging on floods is controlled not only by the harvest rate but most importantly the physiographic characteristics of the watershed and the spatial distribution of the cutblocks. Imposed by the probabilistic framework to understanding and predicting the relation between extremes and their environmental controls, commonly used in the general sciences but not forest hydrology, it is the inherent nature of snowmelt-driven flood regimes which cause even modest increases in magnitude, especially in the upper tail of the distribution, to translate into surprisingly large changes in frequency. Contrary to conventional wisdom, harvesting influenced small, medium, and very large flood events, and the sensitivity to harvest increased with increasing flood event size and watershed area.

Abstract: Study region Wadi Tayyibah is located in south Sinai, Egypt, in a region called Abou Zenima, and it is used to develop this study. Study focus Flash floods tremendously impact many facets of human life due to their destructive consequences and the costs associated with mitigating efforts. This study aims to evaluate the harvesting of Runoff by delineating the watersheds using the Hydrologic Engineering Center-1 (HEC-1) model and ArcGIS software in trying to benefit from it in different ways. All morphometric parameters of the basin were considered, and the risk degree of the different sub-basins was determined. The suitable locations of dams were identified using a Geographical Information System (GIS) using the basin’s morphometric characteristics. New hydrological insights for the region The study proposed a total number of eight dams, including five dams that were recommended for sub-basin (1) and three dams in sub-basin (4), while sub-basins (2) and (3) are not suitable locations to build dams according to the contour map of Wadi Tayyibah. Results indicate that, based on the constructed flash flood hazard maps and the basin’s detailed morphometric characteristics, the best locations of dams are Dam (3) in sub-basin (1) and Dam (7) in sub-basin (4), where the runoff volume reached 3.13 million cubic meters (Mm3) and 5.56 Mm3 for return period 100, respectively. This study is useful for decision-makers and designers for using morphometric parameters and flash flood hazard degree maps to select dam locations. Also, the cost-benefit analysis for using the morphometric parameters is required to be investigated.

Abstract: Leaky dams are an increasingly popular natural flood management measure, yet their impacts on flood peak magnitude have not yet been empirically quantified for a range of event types and magnitudes, even at the stream scale. In this study, the novel application of a transfer function noise modelling approach to empirical Before-After-Control-Impact stage data from an upland catchment allowed leaky dam effectiveness in reducing flood peak magnitude to be quantified. Flood peak stage and discharge magnitude changes were assessed from empirical data for 50 single and multi-peaked high flow events with return periods ranging from less than one year to six years. Overall, event peak magnitude was significantly reduced following the installation of eight leaky dams on the impact stream. Effectiveness was highly variable, but on average, flood peak magnitude was reduced by 10% for events with a return period up to one year. Some of the variability was explained by the size of the event and whether it was a single or multi-peaked event. This finding emphasises the need to manage expectations by considering both a range of event magnitudes and types when designing or assessing leaky dam natural flood management schemes.