应用人工神经网络推算洪水流量的计算方法

天然河道洪水期的水位－流量关系，因受洪水涨落率和回水顶托等因素的影响，一般成为非线性绳套状曲线，洪水流量过程的计算往往根据大量实测水位，流量资料，采用定性判断和实践经验手工绘制水位与流量的时序列关系曲线，由水位过程插补求得。本文运用人工神经以向传播模型，引入与流量变化密切相关的水位，涨率，落差等因子，建立多因素相关的人工神经网络推流模型。     

Comparison of Self-Organizing Map,Artificial Neural Network,and Co-Active Neuro-Fuzzy Inference System Methods in Simulating Groundwater Quality: Geospatial Artificial Intelligence

Water quality experiments are difficult, costly, and time-consuming. Therefore, different modeling methods can be used as an alternative for these experiments. To achieve the research objective, geospatial artificial intelligence approaches such as the self-organizing map (SOM), artificial neural network (ANN), and co-active neuro-fuzzy inference system (CANFIS) were used to simulate groundwater quality in the Mazandaran plain in the north of Iran. Geographical information system (GIS) techniques were used as a pre-processer and post-processer. Data from 85 drinking water wells was used as secondary data and were separated into two splits of (a) 70 percent for training (60% for training and 10% for cross-validation), and (b) 30 percent for the test stage. The groundwater quality index (GWQI) and the effective water quality factors (distance from industries, groundwater depth, and transmissivity of aquifer formations) were implemented as output and input variables, respectively. Statistical indices (i.e., R squared (R-sqr) and the mean squared error (MSE)) were utilized to compare the performance of three methods. The results demonstrate the high performance of the three methods in groundwater quality simulation. However, in the test stage, CANFIS (R-sqr?=?0.89) had a higher performance than the SOM (R-sqr?=?0.8) and ANN (R-sqr?=?0.73) methods. The tested CANFIS model was used to estimate GWQI values on the area of the plain. Finally, the groundwater quality was mapped in a GIS environment associated with CANFIS simulation. The results can be used to manage groundwater quality as well as support and contribute to the sustainable development goal (SDG)-6, SDG-11, and SDG-13.

     

清江流域遥测和报汛站网雨量数据对比分析

清江水电开发有限责任公司在清江流域布设有水情自动测报系统,又对地方水文部门进行了委托报汛,两套报汛系统站点分布不完全重合,其面雨量数据存在差异。对两套报汛系统的面雨量数据进行了统计对比,找出差异所在,分析造成差异的原因,对站网布设提出了调整建议。     

Evaluation of Global Water Resources Reanalysis Data for Estimating Flood Events in the Brahmaputra River Basin

Water Resources Management - Bangladesh and India are in a long-standing conflict with regard to the sharing of hydro-meteorological information of the Brahamaputra River. Consequently, it limits...     

基于人工神经网络的黄河源区枯季径流预报

分析了黄河源区枯季径流的影响因素,并选取基于枯季径流形成机理的、与径流相关性高的因子作为人工神经网络模型的输入,运用误差逆传播算法的多层前向网络,利用VC^ 语言调用随机函数克服了网络全局寻优的缺陷,建立了黄河源区枯季径流预报的BP模型。对黄河源区枯季径流长期预报的结果表明,ANN(7,1,15,1)模型预报结果精度高,容错能力强,是枯季径流预报的有效手段。     

Allocation of Flood Control Capacity for a Multireservoir System Located at the Yangtze River Basin

The paper presents a three step procedure to allocate flood reserve capacity of the reservoirs in a river basin to manage floods and increase hydropower generation. The first step is trying to identify the flood reserve space and reservoir storage availability during the post-flood season in dry year to evaluate the feasibility for future planned flood reserve capacity. Step 2 is dividing the flood reserve space, by using a novel partitioning method to obtain flood protection coefficient. Step 3 is allocating of flood reserve capacity with various storage options of multi-reservoirs, using a simulation-optimization approach. The results show that the most satisfactory solution both reduces downstream overflow and maximizes hydropower, firm power and target storage rate.     

Model Conceptualization Procedure for River (Flood) Hydraulic Computations: Case Study of the Demer River, Belgium

Model-supported real-time flood control requires the development of effective and efficient hydraulic models. As large numbers of iterations are to be executed in optimization procedures, the hydraulic model needs to be computationally efficient. At the same time, it is also required to generate high-accuracy results. Therefore, an identification and calibration procedure was developed for the purpose of having this conceptual model built up and calibrated based on a limited number of simulations with a more detailed full hydrodynamic model. The performance of the conceptual model was evaluated for historical events under different regulation conditions. Robustness test results show close agreement, with Nash-Sutcliffe Efficiency values higher than 0.90. In addition, it is found that the conceptual model is capable of accomplishing simulation of historical flood events within few seconds. That is much faster than the detailed full hydrodynamic model, which enables the conceptual model to be applied for real-time flood control.     

Ecological Regime versus Minimum Environmental Flow:Comparison of Results for a River in a Semi Mediterranean Region

Water Resources Management - Maintaining Environmental Flow (EF) plays a critical role in protecting rivers and their ecosystems. Because of shortage of data and limited financial resources in...     

Evaluating Methods to Establish Habitat Suitability Criteria: A Case Study in the Upper Delaware River Basin,USA

Defining habitat suitability criteria (HSC) of aquatic biota can be a key component to environmental flow science. HSC can be developed through numerous methods; however, few studies have evaluated the consistency of HSC developed by different methodologies. We directly compared HSC for depth and velocity developed by the Delphi method (expert opinion) and by two primary literature meta‐analyses (literature‐derived range and interquartile range) to assess whether these independent methods produce analogous criteria for multiple species (rainbow trout, brown trout, American shad, and shallow fast guild) and life stages. We further evaluated how these two independently developed HSC affect calculations of habitat availability under three alternative reservoir management scenarios in the upper Delaware River at a mesohabitat (main channel, stream margins, and flood plain), reach, and basin scale. In general, literature‐derived HSC fell within the range of the Delphi HSC, with highest congruence for velocity habitat. Habitat area predicted using the Delphi HSC fell between the habitat area predicted using two literature‐derived HSC, both at the basin and the site scale. Predicted habitat increased in shallow regions (stream margins and flood plain) using literature‐derived HSC while Delphi‐derived HSC predicted increased channel habitat. HSC generally favoured the same reservoir management scenario; however, no favoured reservoir management scenario was the most common outcome when applying the literature range HSC. The differences found in this study lend insight into how different methodologies can shape HSC and their consequences for predicted habitat and water management decisions. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.     

Correction to: An Integrated Modelling Approach for Flood Simulation in the Urbanized Qinhuai River Basin,China

Water Resources Management - The original version of this article contains incorrect symbol in eq. 7 and incorrect font style in eq. 8 which have been corrected.     

Real-time Neural-network-based Ensemble Typhoon Flood Forecasting Model with Self-organizing Map Cluster Analysis: A Case Study on the Wu River Basin in Taiwan

Accurate hourly real-time flood forecasting is necessary for early flood warning systems, especially during typhoon periods. Artificial intelligence methods have been increasingly used for real-time flood forecasting. This study developed a real-time flood forecasting model by using back-propagation networks (BPNs) with a self-organizing map (SOM) to create ensemble forecasts. Random weights and biases were set for the BPNs to learn the characteristics of a catchment system. An unsupervised SOM network with a classification function was then used to cluster representative BPN weights and biases; clusters of BPNs with high accuracy were selected to act as experts for the ensemble models to forecast flow rates. The model was applied to flood events in the Wu River Basin of Taiwan. Most observed values were within the forecasting intervals of the BPN clusters in the calibration and validation phases, indicating that the models had acceptable accuracy. For the large flood events of typhoons Saola in the calibration phase and Soulik in the validation phase, the mean average error of the ensemble mean model for the cluster A was 143.1 and 327.4 m³/s, respectively; these values were lower than those for the best individual model within the cluster (194.3 and 917.9 m³/s). The ensemble model thus outperformed the individual models and can accurately forecast flood values and intervals. Therefore, the model can be used to accurately forecast floods.

     

结合西江防洪控制工程发展广西水电建设

从我区水系分布和保障沿江两岸经济发展的情况分析，极需建设大型防洪控制工程。１９９４年广西连续多次遭受巨大的洪涝灾害，灾害损失达３６２亿元。深刻总结教训，我区水电建设应优先选择有较大防洪控制作用的项目。本文重点论述了广西江河几个大型防洪工程和水电建设的关系，并提出了开发意见和建议。     

Integrated Index for Assessment of Vulnerability to Drought,Case Study: Zayandehrood River Basin,Iran

Drought is an extended period of deficient precipitation that causes damage to crops and reducing their performance, causes temporary scarcity of water for human/livestock consumption. Over the years, various indices have been proposed to identify onset, characterize and quantify the attributes of meteorological, hydrological and agricultural drought by various researchers. Because of the spatial and temporal variability and multiple impacts of drought, it is necessary to develop an integrated index for assessment of vulnerability of this natural phenomenon. The aim of this paper is presenting an integrated index for assessment of vulnerability to drought using multiple factors which includes hydrological, meteorological, land use and other factors. Spatial information of various factors was categorized in to various sub-classes and maps were prepared in spatial domain using Geographic Information System (GIS). This study has been carried out in the Zayandehrood River basin located in west-central Iran with semi-arid region. Due to continue droughts at recent decade, this area has been chosen as a case study. The long-term climate data (1991–2011) used for assessment. The results show that Zayandehrood River basin has experienced 11 dry years, 4 normal years, and 6 wet years in the 21 years. The results have been validated with intensive field surveys.     

Drought Forecasting Using Neural Networks,Wavelet Neural Networks,and Stochastic Models: Case of the Algerois Basin in North Algeria

Drought forecasting is a major component of a drought preparedness and mitigation plan. This paper focuses on an investigation of artificial neural networks (ANN) models for drought forecasting in the algerois basin in Algeria in comparison with traditional stochastic models (ARIMA and SARIMA models). A wavelet pre-processing of input data (wavelet neural networks WANN) was used to improve the accuracy of ANN models for drought forecasting. The standard precipitation index (SPI), at three time scales (SPI-3, SPI-6 and SPI-12), was used as drought quantifying parameter for its multiple advantages. A number of different ANN and WANN models for all SPI have been tested. Moreover, the performance of WANN models was investigated using several mother wavelets including Haar wavelet (db1) and 16 daubechies wavelets (dbn, n varying between 2 and 17). The forecast results of all models were compared using three performance measures (NSE, RMSE and MAE). A comparison has been done between observed data and predictions, the results of this study indicate that the coupled wavelet neural network (WANN) models were the best models for drought forecasting for all SPI time series and over lead times varying between 1 and 6 months. The structure of the model was simplified in the WANN models, which makes them very convenient and parsimonious. The final forecasting models can be utilized for drought early warning.

     

Assessment of Upstream Human Intervention Coupled with Climate Change Impact for a Transboundary River Flow Regime: Nile River Basin

Water Resources Management - The aim of this article is to determine how human interventions in upstream countries coupled with drought events are affecting the flow regime of downstream countries...     

Artificial Neural Network and Support Vector Machine Models for Inflow Prediction of Dam Reservoir (Case Study: Zayandehroud Dam Reservoir)

Inflow prediction of reservoirs is of considerable importance due to its application in water resources management related to downstream water release planning and flood protection. Therefore, in this research, different new input patterns for predicting inflow to Zayandehroud dam reservoir is proposed employing artificial neural network (ANN) and support vector machine (SVM) models. Nine different models with different patterns of input data such as inflow to the dam reservoir considering time duration lags, time index, and monthly rainfall of Ghaleh-Shahrokh station have been proposed to predict the inflow to the dam reservoir. Comparison of the results indicates that the ninth proposed model has the least error for inflow prediction in which the results of SVM model outperform those of ANN model. That is, the least error has been obtained using the ninth SVM (ANN) model with correlation coefficient (R) values of 0.8962 (0.89296), 0.9303 (0.92983) and 0.9622 (0.95333) and root mean squared error (RMSE) values of 47.9346 (48.5441), 42.69093 (43.748) and 23.56193 (28.5125) for training, validation and test data, respectively.

     

Recent Flood Control Measures for Urban Rivers in Japan: Case Study of the Kanda River in Tokyo

ABSTRACT

Recently, floods occurred frequently almost everywhere in urban areas in Japan. These urban disasters became an important social problem. In the present study, we investigated floods on the Kanda River in Tokyo. The history of flooded areas, and flood control projects in progress, involving river improvements, expansion of sewerage projects, and urbanization, are reviewed. We also have presented our recent survey results for the flood of August 27, 1993 that occurred in the Kanda River Basin. Hydraulic and hydrologic impacts of historical floods are also given, including an investigation of the economic and social impacts. In urban areas, it is difficult to increase the width of the river. Thus, river improvement works essentially consist of the use of underground diversion channels. In Tokyo, Takadanobaba, Edogawabashi, and Suidobashi diversion channels have been completed. Regulating reservoirs along these rivercourses have been constructed in the Myoshoji River Basin and Zenpukuji River Basin. It is quite difficult to buy land along river courses in Japan. An interesting decision was recently made about the 75mm Plan, which introduces a new method for an underground river; the so-called Tokyo Loop 7. The underground river consists of a pipe having a diameter of 10.0–12.5 m. Loop 7 starts from the upstream section of the Shirako River; and draws flood water from ten different rivers, including the Myoshoji, Zenpukuji, and Kanda rivers. The total length of the pipe is 30 km. The flood water through Loop 7 is pumped out to Tokyo Bay.     

Application of Monte Carlo Simulation Technique to Design Flood Estimation: A Case Study for North Johnstone River in Queensland, Australia

The traditional rainfall-runoff modelling based on the Design Event Approach has some serious limitations as this ignores the probabilistic nature of the key flood producing variables in the modelling except for rainfall depth. A more holistic approach of design flood estimation such as the Joint Probability Approach/Monte Carlo simulation can overcome some of the limitations associated with the Design Event Approach. The Monte Carlo simulation technique is based on the principle that flood producing variables are random variables instead of fixed values. This allows accounting for the inherent variability in the flood producing variables in the rainfall-runoff modelling. This paper applies the Monte Carlo simulation technique and hydrologic model URBS to a large catchment with multiple pluviograph and stream gauging stations. It has been found that it is quite feasible to apply the Monte Carlo simulation technique to large catchments. The Monte Carlo simulation technique has much greater flexibility than the Design Event approach and can provide more realistic design flood estimates with multiple scenarios, which is likely to replace the Design Event Approach. The method developed here can be applied to other catchments in Australia and other countries.     

River Basin Management: A Case Study of Narmada Valley Development with Special Reference to the Sardar Sarovar Project in Gujarat,India

Intra-basin and inter-basin transfer of water have become a necessity in view of severe regional imbalances in availability of water and drought conditions in India. This paper addresses the fundamental issues of river basin management in a multi-objective framework with a unique case study of Narmada River Valley Development, and demonstrates that the socioeconomic needs of the people override the rest of the working objectives. In inter-state water allocation, even a non-riparian state is considered when looking at the needs of the people. This paper focuses on the Sardar Sarovar Project on the river Narmada and highlights its rehabilitation, environmental and social aspects, and concludes that the project is a lifeline for people in western India.