Assessment of environmental flows under limited data availability: case study of the Acheloos River,Greece

Abstract

The lower course of the Acheloos River is an important hydrosystem in Greece, heavily modified by a cascade of four hydropower dams upstream, which is now being extended by two more dams in the upper course. The design of the dams and hydropower facilities that are in operation has not considered any environmental criteria. However, in the last 50 years, numerous methodologies have been proposed to assess the negative impacts of such projects to both the abiotic and biotic environment, and to provide decision support towards establishing appropriate constraints on their operation, typically in terms of minimum flow requirements. In this study, seeking a more environmentally-friendly operation of the hydrosystem, we investigate the outflow policy from the most downstream dam, examining alternative environmental flow approaches. Accounting for data limitations, we recommend the basic flow method, which is parsimonious and suitable for Mediterranean rivers, whose flows exhibit strong variability across seasons. We also show that the wetted perimeter–discharge method, which is an elementary hydraulic approach, provides consistent results, even without using any flow data. Finally, we examine the adaptation of the proposed flow policy (including artificial flooding) to the real-time hydropower generation schedule, and the management of the resulting conflicts.

Editor Z.W. Kundzewicz; Guest editor M. Acreman

Citation Efstratiadis, A., Tegos, A., Varveris, A., and Koutsoyiannis, D., 2014. Assessment of environmental flows under limited data availability: case study of the Acheloos River, Greece. Hydrological Sciences Journal, 59 (3–4), 731–750.     

SIMULATION AND PREDICTION OF DEBRIS FLOW USING ARTIFICIAL NEURAL NETWORK

Debris flow is one of the most destructive phenomena of natural hazards. Recently, major natural haz-ard, claiming human lives and assets, is due to debris flow in the world. Several practical methods for forecasting de-bris flow have been proposed, however, the accuracy of these methods is not high enough for practical use because of the stochastic and non-linear characteristics of debris flow. Artificial neural network has proven to be feasible and use-fill in developing models for nonlinear systems. On the other hand, predicting the future behavior based on a time se-ries of collected historical data is also an important tool in many scientific applications. In this study we present a three-layer feed-forward neural network model to forecast surge of debris flow according to the time series data collect-ed in the Jiangjia Ravine, situated in north part of Yunnan Province of China. The simulation and prediction of debris flow using the proposed approach shows this model is feasible, however, further studies are needed.     

Effects of geology and human activity on the dynamics of salt-water intrusion in three coastal aquifers in southern Spain

 Mathematical modelling of salt-water intrusion processes in three aquifers on the southern coast of Spain (Río Verde, Río Vélez and Castell de Ferro) reveals that, although all three systems are subject to the same climate and seasonal over-exploitation, geological and human factors have very different effects on the dynamics of contamination. In the Río Verde aquifer, the most important influence is the high volume of extractions occurring during the dry season; in Río Vélez, the intrusion is strongly controlled by infiltration of water from the river to the aquifer, and, in the Castell de Ferro system, an intensely karstified carbonate massif lying in contact with both the sea water and the detrital aquifer represents the main entrance point for influx of sea water and subsequent washing of the aquifer. We have undertaken a mathematical simulation of various possible measures to counteract intrusion, according to the specific characteristics of the process in each aquifer. These measures include artificial recharge, use of natural recharge from the river as a hydraulic barrier, and the construction of a low-permeability barrier. Received: 5 December 1995 · Accepted: 12 April 1996     

卫星面降水估计人工神经网络方法

介绍了人工神经网络原理和卫星云图估计降水的原理.从GMS红外卫星云图资料中抽取12个降水云图特征量,构造了网络结构为12-98-7的降水估计人工神经网络模型,并用1993年的小时地面雨量资料和GMS数字云图资料对神经网络模型进行训练,用1992和1994年资料对该神经网络模型分别进行测试.在日面降水估计试验中,地面雨量计值和卫星估计降水之间的相关系数分别为0.94和0.97,相对误差分别为41%和32%.     

人工井液电阻率测井测量时间确定方法

测量时间是人工井液电阻率测井的关键参数,长期依靠施工经验来确定,尚缺少该参数的计算模型和计算方法。为解决这一问题,从影响测量时间的地层富水性、渗透率、地层水的视电阻率、示踪剂溶解速度等多种因素入手,应用质量衡算定律建立测井最佳测量时间计算模型,推导出最佳测量时间计算公式,并通过现场钻孔对比实验验证。结果表明,模型建立的最佳测量时间计算公式可以为盐化测井测量时间的选取提供可靠的依据,可为人工井液电阻率测井获取含（隔）水层水文地质参数提供技术支持,更好地指导现场水文测井工作。     

基于决策到决策路径的遗传算法软件测试用例设计

测试用例生成优劣是软件测试自动化效率高低至关重要的一点,常用的随机测试用例自动生成方法虽然实现简单,但具有效率低、冗余大的缺点,而遗传算法适合于处理传统方法难以解决的非线性问题。为了提高测试效率、降低测试成本,通过分析测试用例自动生成和遗传算法的基本理论,在面向决策到决策路径的软件测试基础上,利用程序控制流图详细阐释了对基于遗传算法的测试用例自动生成技术的设计。通过与随机法自动用例生成进行试验对比,表明其效率至少是随机法10倍。     

高轨卫星轨道预报中神经网络模型优化设计

高轨卫星是我国卫星导航系统的重要组成部分。提升该类卫星的轨道预报精度有利于用户定位精度的提高。提出了一种改进高轨卫星轨道预报精度的新方法。该方法避开了精化动力学模型的困难,尝试从轨道预报误差的规律中寻找突破。利用神经网络作为建立预报模型的工具,将某历史时刻的轨道预报误差作为训练样本,利用训练好的神经网络模型补偿当前时刻的预报轨道以提高轨道预报精度。对影响神经网络模型补偿效果的各因素进行了详细分析,制定了适应于高轨卫星短期、中期和长期预报的神经网络最优模型。利用实测数据进行了试验分析,结果表明:预报8,15及30 d应选择的训练步长分别为10,20及25 min;轨道预报8~30 d时,训练噪声均选取0.01。神经网络模型有效地改进了高轨卫星的轨道预报精度,预报4~30 d,轨道精度提高幅度为34.67%~82.37%不等。     

一种导航卫星中长期轨道预报方法

基于神经网络混合建模的思想提出一种针对导航卫星的中长期轨道预报方法,在原动力学模型的基础上引入神经网络模型作为补偿,从而获得新的预报模型。在训练过程中神经网络通过学习动力学模型轨道预报误差来掌握其变化规律,并在预报过程中为动力学模型预报提供补偿,以提高预报精度。对GPS卫星动力学模型中长期预报误差的特点进行分析,然后根据所得结论提出混合模型的中长期(15 d以上)预报方案,最后通过对GPS卫星的仿真试验证明混合模型的改进效果,结果表明新方法在15~40 d的预报上表现出很好的改进效果。     

Recharge source and hydrogeochemical evolution of shallow groundwater in a complex alluvial fan system,southwest of North China Plain

Many cities around the world are developed at alluvial fans. With economic and industrial development and increase in population, quality and quantity of groundwater are often damaged by over-exploitation in these areas. In order to realistically assess these groundwater resources and their sustainability, it is vital to understand the recharge sources and hydrogeochemical evolution of groundwater in alluvial fans. In March 2006, groundwater and surface water were sampled for major element analysis and stable isotope (oxygen-18 and deuterium) compositions in Xinxiang, which is located at a complex alluvial fan system composed of a mountainous area, Taihang Mt. alluvial fan and Yellow River alluvial fan. In the Taihang mountainous area, the groundwater was recharged by precipitation and was characterized by Ca–HCO₃ type water with depleted δ¹⁸O and δD (mean value of −8.8‰ δ¹⁸O). Along the flow path from the mountainous area to Taihang Mt. alluvial fan, the groundwater became geochemically complex (Ca–Na–Mg–HCO₃–Cl–SO₄ type), and heavier δ¹⁸O and δD were observed (around −8‰ δ¹⁸O). Before the surface water with mean δ¹⁸O of −8.7‰ recharged to groundwater, it underwent isotopic enrichment in Taihang Mt. alluvial fan. Chemical mixture and ion exchange are expected to be responsible for the chemical evolution of groundwater in Yellow River alluvial fan. Transferred water from the Yellow River is the main source of the groundwater in the Yellow River alluvial fan in the south of the study area, and stable isotopic compositions of the groundwater (mean value of −8.8‰ δ¹⁸O) were similar to those of transferred water (−8.9‰), increasing from the southern boundary of the study area to the distal end of the fan. The groundwater underwent chemical evolution from Ca–HCO₃, Na–HCO₃, to Na–SO₄. A conceptual model, integrating stiff diagrams, is used to describe the spatial variation of recharge sources, chemical evolution, and groundwater flow paths in the complex alluvial fan aquifer system.     

Comments on ‘A comparative study of ANN and neuro-fuzzy for the prediction of dynamic constant of rockmass’

Singh et al (2005) examined the potential of the ANN and neuro-fuzzy systems application for the prediction of dynamic constant of rockmass. However, the model proposed by them has some drawbacks according to fuzzy logic principles. This discussion will focus on the main fuzzy logic principles which authors and potential readers should take into consideration.