Optimal Location of Wells for Storage and Recovery of Surplus Desalinated Water in Coastal Aquifers     

Chefi Triki  Slim Zekri  Ali Al-Maktoumi  Mohammad R. Bazargan-Lari 《Ground water》2020,58(5):831-841

Storage of water in aquifers using injection wells is an efficient way for utilizing excess desalinated water in arid regions. In this investigation we estimate the benefits of optimally recharging seasonal surplus desalinated water into a strategic coastal aquifer already benefitting from natural recharge of flash-floods water by a recharge dam. Since, usually the buyers of desalinated water commit to purchase surplus desalinated water under take-or-pay contracts, any attempt in utilizing the paid water is beneficial. Coastal cities are observing an increased urbanization leaving limited space for aquifer recharge infrastructure. In order to determine the optimal location of wells and maximize the use of surplus desalinated water available in winter period, a decision tool combining a numerical groundwater flow simulation model (MODFLOW) with an optimization model is developed. The results of this study show that increasing the number of wells from the existing 45 wells to 173 would allow storing 31.4 million cubic meter per year of excess desalinated water into the aquifer that can be used during later during summer months. The net benefit would reach US$55 million/year while the cost of drilling the new wells is US$5.11 million.  相似文献   

Intercomparison of measurements of bulk snow density and water equivalent of snow cover with snow core samplers: Instrumental bias and variability induced by observers     

J. Ignacio López-Moreno  Leena Leppänen  Bartłomiej Luks  Ladislav Holko  Ghislain Picard  Alba Sanmiguel-Vallelado  Esteban Alonso-González  David C. Finger  Ali N. Arslan  Katalin Gillemot  Aynur Sensoy  Arda Sorman  M. Cansaran Ertaş  Steven R. Fassnacht  Charles Fierz  Christoph Marty 《水文研究》2020,34(14):3120-3133

Manually collected snow data are often considered as ground truth for many applications such as climatological or hydrological studies. However, there are many sources of uncertainty that are not quantified in detail. For the determination of water equivalent of snow cover (SWE), different snow core samplers and scales are used, but they are all based on the same measurement principle. We conducted two field campaigns with 9 samplers commonly used in observational measurements and research in Europe and northern America to better quantify uncertainties when measuring depth, density and SWE with core samplers. During the first campaign, as a first approach to distinguish snow variability measured at the plot and at the point scale, repeated measurements were taken along two 20 m long snow pits. The results revealed a much higher variability of SWE at the plot scale (resulting from both natural variability and instrumental bias) compared to repeated measurements at the same spot (resulting mostly from error induced by observers or very small scale variability of snow depth). The exceptionally homogeneous snowpack found in the second campaign permitted to almost neglect the natural variability of the snowpack properties and focus on the separation between instrumental bias and error induced by observers. Reported uncertainties refer to a shallow, homogeneous tundra-taiga snowpack less than 1 m deep (loose, mostly recrystallised snow and no wind impact). Under such measurement conditions, the uncertainty in bulk snow density estimation is about 5% for an individual instrument and is close to 10% among different instruments. Results confirmed that instrumental bias exceeded both the natural variability and the error induced by observers, even in the case when observers were not familiar with a given snow core sampler.  相似文献   

Streamwater ages in nested,seasonally cold Canadian watersheds     

Samuel Bansah  Genevieve Ali 《水文研究》2019,33(4):495-511

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Artificial neural network simulation for prediction of suspended sediment concentration in the River Ramganga,Ganges Basin,India     

Mohd Yawar Ali Khan  Fuqiang Tian  Faisal Hasan  Govind Joseph Chakrapani 《国际泥沙研究》2019,34(2):95-107

The relation between the water discharge (Q) and suspended sediment concentration (SSC) of the River Ramganga at Bareilly, Uttar Pradesh, in the Himalayas, has been modeled using Artificial Neural Networks (ANNs). The current study validates the practical capability and usefulness of this tool for simulating complex nonlinear, real world, river system processes in the Himalayan scenario. The modeling approach is based on the time series data collected from January to December (2008–2010) for Q and SSC. Three ANNs (T1-T3) with different network configurations have been developed and trained using the Levenberg Marquardt Back Propagation Algorithm in the Matlab routines. Networks were optimized using the enumeration technique, and, finally, the best network is used to predict the SSC values for the year 2011. The values thus obtained through the ANN model are compared with the observed values of SSC. The coefficient of determination (R²), for the optimal network was found to be 0.99. The study not only provides insight into ANN modeling in the Himalayan river scenario, but it also focuses on the importance of understanding a river basin and the factors that affect the SSC, before attempting to model it. Despite the temporal variations in the study area, it is possible to model and successfully predict the SSC values with very simplistic ANN models.  相似文献   

Quantitative Analysis and Efficiency Assessment of Floodwater Harvesting System in Arid Region: Case of Touzouz ephemeral stream—Mzab Valley     

Ali Taleb Bahmed  Souad Bouzid-Lagha 《Water Resources》2020,47(1):54-64

Water Resources - The Mzab Valley is characterized by an arid climate with limited amounts of rainfall. In the context of water scarcity, the Mzab water management system recovers floodwater for...  相似文献   

Relative quantification of wind erosion in argan woodlands in the Souss Basin,Morocco     

Miriam Marzen  Mario Kirchhoff  Irene Marzolff  Ali Aït Hssaine  Johannes B. Ries 《地球表面变化过程与地形》2020,45(15):3808-3823

The endemic argan woodlands cover large parts of South Morocco and create a characteristic landscape with areas of sparsely vegetated and bare soil surfaces between single trees. This unique ecosystem has been under extensive agrosilvopastoral management for centuries and is now at risk of degradation caused by overgrazing and increasing scarcity and variability of rainfall. To investigate susceptibility to wind erosion, we conducted an experimental–empirical study including wind tunnel tests and a drone-generated digital elevation model and quantified wind-erodible material on five different associated surface types by means of sediment catchers. The highest emission flux was measured on freshly ploughed surfaces (1875 g m^–2 h^–1), while older ploughed areas with a re-established crust produced a much lower emission flux (795 g m^–2 h^–1). Extensive tillage may have been a sustainable practice for generations, but increasing drought and uncertainty of rainfall now lead to an acute risk of severe soil erosion and dust production. The typical crusted surfaces characterized by residual rock fragment accumulation and wash processes produced the second highest emission flux (1,354 g m^–2 h^–1). Material collected from tree-shaded areas (933 g m^–2 h^–1) was revealed to be a considerable source of organic material, possibly affecting substrate conditions positively on a larger regional scale. The lowest flux was measured on rock fragment-covered surfaces (301 g m^–2 h^–1). The data show that open argan woodland may be a considerable source for wind erosion and dust production, depending on surface characteristics strongly related to management. An adapted management must include the conservation of argan trees to offer a promising approach to prevent severe wind erosion and dust production and mitigate possible impacts of land-use change and climate change related shifts in wind and rainfall patterns. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd  相似文献   

Factors associated with unnecessary requests for an ambulance by non-traumatic patients after the acute earthquake responding phase: a qualitative content analysis     

Ebrahimian  Abbasali  Babaei  Hossein  Fakhr-Movahedi  Ali 《Natural Hazards》2020,103(2):2009-2020

The pre-hospital emergency staff played a key role in transferring the injured patients to health centers. Usually, they reported changes in their decisions on the transfer of non-traumatic patients to hospitals. So, this study was aimed to explore the reasons for unnecessarily requesting an ambulance by non-traumatic patients after the acute responding-to-earthquake phase. This study was a qualitative study that data were analyzed by content analysis approach. Participants were eleven pre-hospital emergency technicians. Data were collected by three sessions of focus group discussion. Data analysis was led to emergence of a main theme: “feeling urgency due to turmoil and uncertainty.” This theme illustrates the basic approach of the inhabitants of the earthquake-stricken region when unnecessarily requesting an ambulance. This theme was derived from two main categories of “turbulent and uncertain conditions” and “psychological turmoil.” The category of “turbulent and uncertain conditions” was comprised of three subcategories: “unreliable care,” “inadequate facilities” and “turbulent living conditions.” The category of “psychological turmoil” was comprised of three subcategories: “psychological turmoil in survivors,” “healthcare providers deciding under pressure” and “turmoil in providing psychological and psychiatric services.” Ambulance dispatch may be unnecessarily performed owing to turbulent and unsure conditions and psychological turmoil in earthquake-stricken people and pre-hospital emergency staff. Providing earthquake-stricken people with psycho-medical services in their place of residence can significantly reduce the workload of pre-hospital emergency staff and consequently that of hospital staff and therefore save time and treatment costs and increase the quality of health services provided for the injured.

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Using uncertainty and sensitivity analysis for finding the best rainfall-runoff model in mountainous watersheds(Case study: the Navrood watershed in Iran)     

Arash ADIB  Morteza LOTFIRAD  Ali HAGHIGHI 《山地科学学报》2019,(3)

In watersheds that have not sufficient meteorological and hydrometric data for simulating rainfall-runoff events, using geomorphologic and geomorphoclimatic characteristics of watershed is a conventional method for the simulation. A number of rainfall-runoff models utilize these characteristics such as Nash-IUH, Clark-IUH, Geomorphologic Instantaneous Unit Hydrograph(GIUH), Geomorphoclimatic Instantaneous Unit Hydrograph(GcIUH), GIUH-based Nash(GIUH-Nash) and GcIUH-based Clark(GcIUH-Clark). But all these models are not appropriate for mountainous watersheds. Therefore, the objective of this study is to select the best of them for the simulation. The procedure of this study is: a) selecting appropriate rainfall-runoff events for calibration and validation of six hybrid models, b) distinguishing the best model based on different performance criteria(Percentage Error in Volume(PEV); Percentage Error in Peak(PEP); Percentage Error in Time to Peak(PETP); Root Mean Square Error(RMSE) and Nash-Sutcliffe model efficiency coefficient(ENS)), c) Sensitivity analysis for determination of the most effective parameter at each model, d) Uncertainty determination of different parameters in each model and confirmation of the obtained results by application of the performance criteria. For application of this procedure, the Navrood watershed in the north of Iran as a mountainous watershed has been considered. The results showed that the ClarkIUH and GcIUH-Clark are suitable models for simulation of flood hydrographs, while other models cannot simulate flood hydrographs appropriately. The sensitivity analysis shows that the most sensitive parameters are the infiltration constant rate and time of concentration in the Clark-IUH model. Also, the most sensitive parameters include the infiltration constant rate and storage coefficient in the GcIUHClark model. The Clark-IUH and GcIUH-Clark models are more sensitive to their parameters. The Latin Hypercube Sampling(LHS) on Monte Carlo(MC) simulation method was used for evaluation of uncertainty of data in rainfall-runoff models. In this method 500 sets of data values are produced and then the peak discharge of flood hydrographs for each produced data set is simulated with rainfall-runoff models. The uncertainty of data changes the value of simulated peak discharge of flood hydrograph. The uncertainty analysis shows that the observed peak discharges of different rainfall-runoff events are within the range of values of simulated by the six hybrid rainfall-runoff models and IUH that inputs of these models were the produced data sets. The range of the produced peak discharge of flood hydrographs by the Clark-IUH and GcIUH-Clark models is wider than those of other models.  相似文献   

Estimation of crowd density from UAVs images based on corner detection procedures and clustering analysis     

Ali Almagbile 《地球空间信息科学学报》2019,22(1):23-34

With rapid developments in platforms and sensors technology in terms of digital cameras and video recordings, crowd monitoring has taken a considerable attentions in many disciplines such as psychology, sociology, engineering, and computer vision. This is due to the fact that, monitoring of the crowd is necessary to enhance safety and controllable movements to minimize the risk particularly in highly crowded incidents (e.g. sports). One of the platforms that have been extensively employed in crowd monitoring is unmanned aerial vehicles (UAVs), because UAVs have the capability to acquiring fast, low costs, high-resolution and real-time images over crowd areas. In addition, geo-referenced images can also be provided through integration of on-board positioning sensors (e.g. GPS/IMU) with vision sensors (digital cameras and laser scanner). In this paper, a new testing procedure based on feature from accelerated segment test (FAST) algorithms is introduced to detect the crowd features from UAV images taken from different camera orientations and positions. The proposed test started with converting a circle of 16 pixels surrounding the center pixel into a vector and sorting it in ascending/descending order. A single pixel which takes the ranking number 9 (for FAST-9) or 12 (for FAST-12) was then compared with the center pixel. Accuracy assessment in terms of completeness and correctness was used to assess the performance of the new testing procedure before and after filtering the crowd features. The results show that the proposed algorithms are able to extract crowd features from different UAV images. Overall, the values of Completeness range from 55 to 70 % whereas the range of correctness values was 91 to 94 %.  相似文献   

Experimental Evaluation of A New Developed Algorithm for An Autonomous Surface Vehicle and Comparison with Simulink Results     

Mousazadeh  Hossein  Kiapey  Ali 《中国海洋工程》2019,33(3):268-278

China Ocean Engineering - Performing repeatable duties automatically was the dreams of human being for centuries. Although full autonomy has long been dreamed of by visionaries, many researches...  相似文献