MacKenzie, K. M.Gharabaghi, B.Binns, A. D.Whiteley, H. R....
11页
查看更多>>摘要：Unmitigated urbanization frequently alters the flow frequency distribution and changes the source and transport rates of sediments in previously "in regime" channels. These changes may result in increased stream erosion, changes in alluvial materials and degradation of water quality and habitat, conditions called "urban stream syndrome". Early identification of streams with the potential to develop urban stream syndrome may allow for additional implementation of watershed controls such as Low Impact Development or within stream mitigation (e.g. erosion controls). Regime theory applied to dynamically-stable alluvial channels has identified empirical equations linking width (W), depth (H), slope (S), mean sediment particle size (D50), and the 2-yr return bankfull discharge (Q2). This study examines the application of regime-theory equations to urban streams as a means of identifying channels with urban stream syndrome. To begin the assessment of the applicability of regime equations an extensive database of channel morphology variables for 733 in-regime channels, from North America, Britain and South Asia, was compiled from existing publications. Using this database a Group Method of Data Handling (GMDH) model was developed to predict specific stream power for comparison with observed values to determine whether a channel is in or out of regime. The application of the GMDH model was showcased using regional flow and sediment data to predict channel conditions of several watercourses in Southern Ontario, Canada. The GMDH model reliably identified channels both in and out of regime conditions compared with published in-situ assessments based on Rapid Geomorphic Assessments (RGAs). This study has identified changes in specific stream power (omega) as a reliable early detection metric for occurrence of the urban stream syndrome. The model can inform the strategies to mitigate the urban stream syndrome, including within-channel mitigation and watershed initiatives, including Low Impact Developments (LIDs).
查看更多>>摘要：Urban flood warning systems need fast response times between the rainfall forecast and the flood alarm. Flood forecasts from physically based numerical models usually need much computation time. Flood forecasts based on databases from previous events or pre-simulated events can speed up the process of decision making. This work introduces and compares four distance metrics for temporal rainfall patterns used in a nearest neighbour based forecast system for dynamic water levels and velocities during pluvial floods. The system uses a database of 960 pre-calculated flood events. The performance of each metric is evaluated by analysis of time-series of flow variables. For the error quantification,a procedure to find a small number of representative locations in an urban catchment is described. A new approach to quantify the similarity of dynamic flow fields is introduced, which makes use of particle transport tracking. The four distance metrics are tested on forecast for four exemplary pluvial flood events resulting from rainfall of durations between 15 and 50 min and return-periods between 10 and 100 years. The best metric is based on the temporal precipitation pattern and takes the response time of the drainage system into account. If the pattern has a very short duration, a simpler characterisation-metric can be used, which takes the total volume, peak intensity and peak position into account.
查看更多>>摘要：Methane is the main component of natural gas and a greenhouse gas. It usually coexists with water in geological formations. Methane adsorption onto shale has been studied extensively, but there is no report on the Simultaneous Adsorption of Water vapor and Methane (SAWM). This paper reports a new experimental method for studying SAWM onto shale. During the experiment, liquid water, water vapor and methane coexist in an adsorption cell. Water vapor is produced via evaporation of liquid water, and the processes of liquid water evaporation and water vapor and methane adsorption onto shale occur simultaneously. The rate of liquid water conversion into vapor and the free water vapor content in the gas mixture depend on Relative humidity (Rh). Changes in Rh are monitored with a humidity-sensor. In SAWM, the amount of water vapor adsorbed greatly exceeds that of methane. The adsorption of water vapor took longer to reach equilibrium than that of methane. The amount of water vapor adsorbed at equilibrium decreased with total pressure, while the opposite situation occurred with methane adsorption. Compared to Pure Methane adsorption onto Dry Shale (PMDS), the amount of methane adsorbed was lower by 10-59% in SAWM. The equilibrium time for methane adsorption was higher, and t(50) and t(80) (t(50) and t(80) represented the times required for adsorption of 50% and 80% of the equilibrium adsorption amount, respectively) increased 12.0-108.0 and 9.0-115.2 times, respectively. In the two experiments, the declines in the level of methane adsorption were equal when a critical threshold Equilibration Degree (Ed) was reached. Before reaching Ed, the rate of methane adsorption in SAWM was higher than that in PMDS. After reaching Ed, the phenomenon was reversed.
查看更多>>摘要：Eco-flows (ecosurplus (ES) and ecodeficit (ED)) calculated with flow duration curves (FDCs) have some limitations on their use in assessing the ecohydrological conditions of rivers. A new method of defining eco-flows based on discharge hydrographs (DHs) instead of FDCs is presented in this study. In this method, the annual ES is the ratio of the surplus annual runoff above the 75th percentile DH to the probable maximum surplus annual runoff above the 75th percentile DH. The annual ED is the ratio of the deficient annual runoff below the 25th percentile DH to the probable maximum deficient annual runoff below the 25th percentile DH. The monthly and seasonal eco-flows are redefined similarly. A method for ranking the risks posed by certain ecohydrological conditions is proposed that includes four risk levels: no risk, low risk, moderate risk, and high risk. Data from the Yellow River were used to illustrate these new methods. Results indicate that the new method based on DHs addresses the limitations and that the annual EDs based on DHs have the strongest correlativity to the Shannon diversity index. The risk graph produced with this method displayed the risk levels for each month, season and year over the past 60 years in an intuitive format. The changes in the dominant risk levels between the pre and post-impact periods indicated the degree to which reservoirs impacted ecohydrological conditions at monthly, seasonal and yearly scales. This study can be used in the future to design ecological regulation measures to improve ecohydrological conditions during adversely impacted months and seasons.
Azizipour, M.Sattari, A.Afshar, M. H.Goharian, E....
13页
查看更多>>摘要：In recent years, Cellular Automata (CA) has emerged as a powerful tool for solving optimization problems in water resources engineering and, in particular, reservoir operation problems. This study utilizes the capabilities of the CA-based method to maximize the firm energy yield of multi-reservoir hydropower systems. Installed capacities (ICs) are selected as decision variables in the design phase and be determined in an iterative procedure. The reservoir storages at the beginning and the end of the periods are used as the decision variables in the operation phase and be calculated by the CA. The process starts with specifying an arbitrary initial installed IC for each reservoir determined based on long-term average annual inflow. Then, the system is optimally operated to maximize the energy yield under user-specified reliability of the system using a hybrid approach, Cellular Automata-Simulating Annealing (CA-SA). The system's ICs are then increased/decreased depending on whether the system's energy yield reliability is greater/less than the target reliability. This iterative process lasts till the system's energy yield reliability is equal to the target reliability. The proposed method is used to optimally design the three-reservoir Khersan hydropower system and also the largest hydropower reservoir system in Iran composed of 16 reservoirs. The results are presented and compared with those of the existing methods in the literature. The results show that the proposed method can be efficiently and effectively used for improving the firm energy yield of real-world multi-reservoir hydropower systems.
查看更多>>摘要：Accurate remotely sensed snow depth (SD) data are essential for monitoring and modeling hydrological processes in cold regions. While the available passive microwave SD data have been widely used by the community, the coarse spatial resolution (typically at 0.25 degrees) of these data impedes the explicit representation of the hydrological processes in snow-dominated regions, especially in mountainous regions with complex terrain. To improve the spatial resolution and quality of passive microwave SD data for the Tibetan Plateau (TP), we develop a spatial-temporal downscaling method to produce a 19-year, daily 0.05 degrees SD product by combining the existing high temporal resolution daily SD data and the high spatial resolution 8-day cloud-free Moderate Resolution Imaging Spectroradiometer (MODIS)-based snow cover probability (SCP) data, the latter of which were produced using an new advanced temporal filter algorithm. Validations against the observed SD data from 92 meteorological stations suggest that the newly-developed 0.05 degrees SD product greatly improves upon the original 0.25 degrees version. Based on this 0.05 degrees SD product, we found that higher SD values are mainly distributed on the southeastern and eastern TP as well as the Himalaya and Karakoram, while much lower SD values occur on the inner TP. During 2000-2018, the TP-averaged annual SD showed a slight (p > 0.05) increasing trend because there were little changes in SD for most grids across the TP. Regarding different basins within TP, the annual SD during 2000-2018 slightly increased over most basins except for the Amu Dayra, Ganges, Brahmaputra, and Inner TP, where the basin-scale SD showed insignificant decreasing tendencies. In general, the spatial-temporal variations in the SD across the TP were very heterogeneous because SD was affected by multiple climatic factors. The newly-developed 0.05 degrees SD product could facilitate our understanding of the hydrological processes on the TP through a more explicit representation of the gridded-based snow water information.
查看更多>>摘要：Flash flood warning (FFW) systems play a fundamental role in flood hazard prevention and mitigation. In this study, we propose the first deep learning-based approach for large-scale FFW and demonstrate the application of this approach to mountainous and hilly areas of China. Specifically, the time series of precipitation before flash floods and three spatial features (maximum daily precipitation, curve number, and slope) are selected as predictors. A long short-term memory (LSTM)-based approach is adopted to predict the occurrence of flash floods, and we compare this approach with two widely used FFW methods, namely the rainfall triggering index (RTI) and flash flood guidance (FFG). The results demonstrate the following: (1) The LSTM-based approach provided a reliable FFW 1 day ahead with a hit rate (HR) of 0.84 and false alarm rate (FAR) of 0.09. It demonstrated moderate warning performance 2 days before flash floods, with an HR of 0.66 and FAR of 0.21. (2) The LSTMbased approach outperformed the benchmark RTI and FFG methods, achieving the highest critical success index (CSI) of 0.77. The FFG also provided satisfactory performance, with a CSI of 0.71, and the RTI demonstrated the lowest performance (CSI = 0.68). (3) The LSTM-based approach provides better results (CSI = 0.75) than RTI (CSI = 0.68) when only the time series of precipitation is used for prediction. The performance of the LSTMbased approach can be improved by considering the spatial features and a long time series of precipitation during model development. (4) The proposed approach did not exacerbate the effect of precipitation uncertainty on the flash flood warning; and we suggest using ensemble results for FFW to reduce the uncertainty caused by small or unbalanced learning samples. We conclude that the proposed approach is a valid method for large-scale FFW without using commercially sensitive observations, and can improve the capabilities of flood disaster mitigation, particularly in ungauged areas.
查看更多>>摘要：Fractures, faults, karstic features and/or interbedded layers of coarse sediment often manifest in the form of preferential flow features (PFFs). Previous investigations into the effects of PFFs on solute plume distributions within otherwise permeable host rocks have treated flow in PFFs as Darcian. However, flow through faults and fractures is known to exhibit non-Darcian flow behavior. The current study extends previous investigations of the effects of PFFs (e.g., a fault or fracture) on solute plumes in permeable aquifers that assume Darcian flow in the fault/fracture. The finite-element model COMSOL Multiphysics was applied to examine how non-Darcian flow in a single PFF influences flow fields and steady-state solute plume distributions in permeable aquifers, compared with the Darcian flow assumption. The Forchheimer equation was applied within numerical models to represent flow in the PFF for a variety of PFF-permeability contrasts, PFF apertures and matrix flow directions. The refraction of flow lines at matrix-PFF interfaces and the specific discharge in the PFF were found to be smaller in non-Darcian models, leading to larger peak solute concentrations (by up to 160%) and narrower plumes compared to Darcian models. In addition, the impact of non-Darcian flow on flow fields and solute plumes was greater with smaller matrix hydraulic conductivity, larger PFF aperture and larger incidence angle at the matrixPFF interface. Upstream dispersion at the matrix-PFF interface, observed in previous matrix-PFF studies of solute transport as the result of steep solute concentration gradients opposing head gradients, was found to be reduced when non-Darcian flow was considered in PFFs. This study highlights that non-Darcian flow effects may be significant in the simulation of flow and solute transport within high-permeability PFFs embedded in otherwise porous aquifers.
查看更多>>摘要：In this study, we develop a daily flow duration curve model for ungauged intermittent subbasins of gauged rivers. The long-term mean streamflow of the river basin, one of the central parts in the model, is calculated with a regression model of annual precipitation and physical characteristics of the river basin; e.g., drainage area, basin relief, topographical slope, drainage density. The input data of the model are normally accesible, and this makes the model applicable to ungauged points within the river basin. Another central part of the model is the cease-toflow point which makes the model significant for intermittent rivers. The daily streamflow discharge recorded in gauging stations over the river basin is nondimensionalized by dividing each with their own long-term mean, and their collection is transformed to fit the normal probability distribution; i.e., the normalized nondimensional daily streamflow data are used in the model. The streamflow data are inverted back to the original distribution for any given exceedance percentage by incorporating the cease-to-flow point, and are dimensionalized finally by using the empirically-derived long-term mean streamflow discharge. The model is applied on hundreds of thousands station-day daily streamflow data from three river basins in different geographical regions in Turkey. Results of the case studies are found promising to propose the model as a good foundation for the daily flow duration curve at an ungauged intermittent subbasin of gauged rivers: However, it is noticeable that the model might have low performance in some particular gauging stations where the hydrological behavior deviates from the general characteristics of the river basin. This can be overcome by developing empirical models better approaching the observed long-term mean streamflow, which is a key issue of the model.
NSTL
Elsevier