Abstract: Combined large-scale rainwater harvesting (RWH) and flood mitigation systems are promising as a sustainable water management strategy in urban areas. These are multi-purpose infrastructure that not only provide a secondary, localised water resource, but can also reduce discharge and hence loads on any downstream wastewater networks if these are integrated into the wider water network. However, the performance of these systems is dependent on the specific design used for its local catchment which can vary significantly between different implementations. A multitude of design strategies exist, however there is no universally accepted standard framework. To tackle these issues, this paper presents a two-player optimisation framework which utilises a stochastic design optimisation model and a competing, high-intensity rainfall design model to optimise passively-operated RWH systems. A customisable tool set is provided, under which optimisation models specific to a given catchment can be built quickly. This reduces the barriers to implementing computationally complex sizing strategies and encouraging more resource-efficient systems to be built. The framework was applied to a densely populated high-rise residential estate, eliminating overflow events from historical rainfall. The optimised configuration resulted in a 32% increase in harvested water yield, but its ability to meet irrigation demands was limited by the operational levels of the treatment pump. Hence, with the inclusion of operational levels in the optimisation model, the framework can provide an efficient large-scale RWH system that is capable of simultaneously meeting water demands and reducing stresses within and beyond its local catchment.

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: Urban flooding in Chittagong City usually occurs during the monsoon season and a rainwater harvesting (RWH) system can be used as a remedial measure. This study examines the feasibility of rain barrel RWH system at a distributed scale within an urbanized area located in the northwestern part of Chittagong City that experiences flash flooding on a regular basis. For flood modeling, the storm water management model (SWMM) was employed with rain barrel low-impact development (LID) as a flood reduction measure. The Hydrologic Engineering Center’s River Analysis System (HEC-RAS) inundation model was coupled with SWMM to observe the detailed and spatial extent of flood reduction. Compared to SWMM simulated floods, the simulated inundation depth using remote sensing data and the HEC-RAS showed a reasonable match, i.e., the correlation coefficients were found to be 0.70 and 0.98, respectively. Finally, using LID, i.e., RWH, a reduction of 28.66% could be achieved for reducing flood extent. Moreover, the study showed that 10%–60% imperviousness of the subcatchment area can yield a monthly RWH potential of 0.04–0.45 m3 from a square meter of rooftop area. The model can be used for necessary decision making for flood reduction and to establish a distributed RWH system in the study area.

Abstract: This study, investigates the hydraulic of flow in a subterranean channel headspring. The continuity and momentum equations of flow in porous media considering real conditions were used and the basic equation of flow in a subterranean channel was resulted. This equation is very similar to the spatially varied flow with increasing discharge. An equation, defining the hydraulic parameters of a subterranean channel section was adopted. Then differential quadrature method (DQM), was applied to the equation of flow in subterranean channel, consequently the water surface profile was resulted. To illustrate the rightness of model, the hydraulic parameters of flow in the Gavgard branch of the Joopar Goharriz Qanat were measured and the water surface profile was determined. This water surface profile was compared to the water surface profile computed by the model, which are in good agreement.

Abstract: Study region Zohreh River Basin, Southwest Iran Study focus The salinity of Zohreh River sharply increases in three salinity zones (SZs) along the river named SZ1, SZ2 (the focus of this study), and SZ3. Determining the salinity sources and salinization mechanism using an integrated approach including geological, hydrochemical, isotopic, geophysical, river sinuosity and hydrocarbon analysis are the main objectives of this study. The study focuses on the combination of evidence of regional-scale (i.e., river sinuosity and seismic data) and small-scale (i.e., drilling core analysis). New hydrologic insights for the region Among several known sources of river salinity, it was found that the water quality of the Zohreh River is mainly threatened by the salt-bearing Gachsaran Formation and oil-field brine. It is concluded that halite brine and oil-field brine simultaneously cause the salinization in SZ2, and their contributions were delineated to be 95% and 5%, respectively. The lack of reliable geological evidence to support halite dissolution in surficial layers by circulating waters suggests the possibility of a deep source of halite brine in SZ2. The results revealed that deep halite brine of the salt layers of Gachsaran Formation is mainly responsible for the salinization of SZ2. The mechanism of deep brine penetration to the river through the hidden fault failures detected by the combination of river sinuosity analysis and geophysical data for the first time.