共查询到9条相似文献，搜索用时 15 毫秒
1.
Spatio‐temporal variability in river flow is a fundamental control on instream habitat structure and riverine ecosystem biodiversity and integrity. However, long‐term riverine ecological time‐series to test hypotheses about hydrology–ecology interactions in a broader temporal context are rare, and studies spanning multiple rivers are often limited in their temporal coverage to less than five years. To address this research gap, a unique spatio‐temporal hydroecological analysis was conducted of long‐term instream ecological responses (1990–2000) to river flow regime variability at 83 sites across England and Wales. The results demonstrate clear hydroecological associations at the national scale (all data). In addition, significant differences in ecological response are recorded between three ‘regions’ identified (RM1–3*) associated with characteristics of the flow regime. The effect of two major supra‐seasonal droughts (1990–1992 and 1996–1997) on inter‐annual (IA) variability of the LIFE scores is evident with both events showing a gradual decline before and recovery of LIFE scores after the low flow period. The instream community response to high magnitude flow regimes (1994 and 1995) is also apparent, although these associations are less striking. The results demonstrate classification of rivers into flow regime regions offers a way to help unravel complex hydroecological associations. The approach adopted herein could easily be adapted for other geographical locations, where datasets are available. Such work is imperative to understand flow regime–ecology interactions in a longer term, wider spatial context and so assess future hydroecological responses to climate change and anthropogenic modification of riverine ecosystems. Copyright © 2008 John Wiley & Sons, Ltd. 相似文献
2.
Flow is widely considered one of the primary drivers of instream ecological response. Increasingly, hydroecological models form the basis of integrated and sustainable approaches to river management, linking flow to ecological response. In doing so, the most ecologically relevant hydrological variables should be selected. Some studies have observed a delayed macro‐invertebrate (ecological) response to these variables (i.e. a cumulative inter‐annual effect, referred to as multi‐annual) in groundwater‐fed rivers. To date, only limited research has been performed investigating this phenomenon. This paper examines the ecological response to multi‐annual flow indicators for a groundwater‐fed river. Relationships between instream ecology and flow were investigated by means of a novel methodological framework developed by integrating statistical data analysis and modelling techniques, such as principal component analysis and multistep regression approaches. Results demonstrated a strong multi‐annual multi‐seasonal effect. Inclusion of additional antecedent flows indicators appears to enhance overall model performance (in some cases, goodness of fit statistics such as the adjusted R‐squared value exceeded 0.6). These results strongly suggest that, in order to understand potential changes to instream ecology arising from changing flow regimes, multi‐annual and multi‐seasonal relationships should be considered in hydroecological modelling. © 2017 The Authors River Research and Applications Published by John Wiley & Sons Ltd. 相似文献
3.
This study demonstrates the use of inferential models for scenario analyses by simulating direct and indirect effects of predictor variables on state variables through model ensembles. Two model ensembles have been designed to predict the response of the cyanobacterium Microcystis aeruginosa and the diatom Stephanodiscus hantzschii to modified flow regimes of the River Nakdong (Korea) by a scenario analysis. Whilst flow‐independent predictor variables of growth of Microcystis and Stephanodiscus such as water temperature and pH remain unchanged during the scenario analysis, flow‐dependent predictor variables such as turbidity, electrical conductivity, phosphate, nitrate, silica and chlorophyll a are forecasted by inferential models. In the course of scenario analysis, flow‐independent and flow‐dependent predictor variables feed into the Microcystis and Stephanodiscus models to make sure that both direct and indirect effects of altered flow regimes are taken into account. The eight inferential models that were incorporated into the model ensembles have been developed by the hybrid evolutionary algorithm based on 19 years of time‐series monitored in the River Nakdong between 1993 and 2012. The models achieved good accuracy in terms of timing and magnitudes reflected by coefficients of determination r2 = 0.94 for Microcystis and r2 = 0.83 for Stephanodiscus. The scenario analysis revealed that extreme summer blooms of Microcystis as observed between 1994 and 1997, and winter blooms of Stephanodiscus as observed between 1994 and 1997 and in 2004 can be prevented in the River Nakdong by adaptive management of seasonal water release from adjacent dams. Copyright © 2017 John Wiley & Sons, Ltd. 相似文献
4.
River damming and associated reservoir causes intense and dramatic changes that create new environments, with particular structure and functioning. In these systems, flow control and artificial variations in water level are important determinants of the structure of fish assemblages. Planned reduction in water level (drawdown) is used to manage productivity in reservoirs. However, the effects of non‐planned reductions, such as those related to the collapse of spillway gates, are rarely studied. The objective of this study was to evaluate the effects of a rapid reservoir drawdown, because of the collapse of a gate, on the structure of fish assemblage in a Neotropical reservoir, in Southern Brazil, operated as run‐of‐the‐river. Water level variation because of the collapse reached up to 20 m. A canonical analysis of principal coordinates (CAP) was used to summarize the structure of fish assemblage. Spearman rank correlations were performed between each CAP axes retained for interpretation and fish species abundances, to assess the ones that most contributed to observed patterns. The first CAP axis identified strong variations in the spatial scale, while the third axis identified variations in the time scale (before and after the collapse). The most notable negative effect was the loss of several fish that perished during the reservoir drawdown, probably because of adverse limnological conditions. Results showed significant benefits of water level variation on the entire fish assemblage, and we suggest that, observed some peculiarities, this variation can be used to manage reservoirs, as a tool to enhance fish abundances. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
5.
依据主成分分析法和化学热力学的基本理论,编写了基于FORTRAN语言的程序,优化了模型阈值的确定方法,根据计算目的不同,分别选取不同的目标离子作为控制模型循环的阈值.结合某工程实例,与传统算法进行了比较,证明该模型的算法在坝址区的计算具有更好的稳定性和计算精度. 相似文献
6.
为提高径流预报精度,研究提出主成分分析(PCA)、未来搜索算法(FSA)、多元线性回归(MLR)相融合的径流预测模型。利用PCA对样本数据进行降维处理,选取8个标准测试函数在不同维度条件下对FSA进行仿真验证,利用FSA优化MLR常数项和偏回归系数,提出PCA-FSA-MLR径流预测模型,并构建基于PCA降维处理的PCA-LS-MLR、PCA-FSA-SVM、PCA-SVM模型和未经降维处理的FSA-MLR、LS-MLR、FSA-SVM、SVM作对比模型,通过云南省龙潭站年径流及枯水期12月月径流预测实例对各模型进行验证。结果表明:①FSA在不同维度条件下均具有较好的寻优精度和全局极值搜索能力;②PCA-FSA-MLR模型对龙潭站年径流及12月月径流预测的平均相对误差绝对值分别为1.63%、3.91%,预测精度均优于其他7种模型,具有更高的预测精度和更强的泛化能力;③对于同一模型,经PCA降维处理的预测精度优于未经降维处理的预测精度,PCA数据降维对提升模型预测精度具有帮助。 相似文献
7.
The northern Shaanxi province of China has severe water shortages, especially in coal mining areas, and it is very important to calculate the riverine ecological instream flows (EIFs) and analyse the runoff profit‐loss situation. Using the Kuye River as a case study, the EIF was calculated for different years and seasons using the instream flows rate (IFR) method and compared with the Tennant and the minimum monthly average flow (MAF) methods. The recommended value of the Kuye River EIF was obtained by an analysis of the results of these three methods. The river runoff profit‐loss situation associated with the EIF was also calculated and the main reason for the loss explained. The Kuye River EIF was calculated to be 1.69 to 11.14 m3/s by the IFR method, 1.94 to 8.50 m3/s by the Tennant method, and 3.81 to 10.87 m3/s by the MAF method. Based on these results, the EIF annual recommended value of the Kuye River was 4.00 m3/s for the 1961–2010 period. The wet season (July–October), average season (March–June), and dry season (November–following Feb) EIFs were 6.50, 3.50, and 2.00 m3/s, respectively. The Kuye River had a large surplus runoff within the EIF prior to1999, but from 1999 to 2010, the runoff and EIF were very close and the April to June average runoff did not meet the EIF. The main factors that affected the river runoff were rainfall, temperature, water and soil conservation, coal mining, and water consumption for industry and domestic use, with coal mining becoming a more important factor since 1999. This case study provides important technical support and guidance for the ecological restoration of the Kuye River basin, and the concept can be applied to other similar coal mining areas. 相似文献
8.
李代华 《水资源与水工程学报》2021,32(1):97-102
为提高径流预测精度,研究主成分分析(PCA)、斑鬣狗优化(SHO)算法与支持向量机(SVM)、BP神经网络相融合的预测方法.在样本数据筛选上选取PCA方法进行数据降维,使数据样本简洁且更具代表性.利用SHO算法优化SVM关键参数及BP神经网络权阈值,分别提出PCA-SHO-SVM、PCA-SHO-BP径流量预测模型,并... 相似文献
9.
S. Zazo P. Rodríguez‐Gonzálvez J.‐L. Molina D. Hernández‐López D. González‐Aguilera 《河流研究与利用》2017,33(4):620-631
Today, it is increasingly clear that non‐stationarity hydrological and hydraulic variables and processes are occurring largely because of global warming. Accordingly, extreme hydrological events are becoming more common over time, and their effects are creating greater negative impacts on the environment (fluvial geomorphology and floodplains) and society (flood damage). Given this situation, the implementation of adaptation‐mitigation measures is vital, as well as an increased knowledge of the interaction between water and physical environments. In the binominal water‐terrain, having a reliable digital elevation model (DEM) is essential because of its important influence on fluvial modelling. However, this is frequently a technical‐economic problem. The aim of this paper is first to evaluate the compatibility between hydraulics and geometrics for fluvial applications and second to determine the quality of a novel DEM by robust estimators. This was obtained through the photogrammetric processing of digital aerial images acquired from a low‐cost camera mounted on an alternative aerial platform. Flood modelling and hydraulic parameters were obtained with the assistance of photogrammetric DEM (mesh size: 0.15 m, vertical accuracy: 0.102 ± 0.081 m, point density: ≈40 point/m2). Finally, our other goal is to develop a comparative analysis between light detection and ranging and digital photogrammetry on‐demand. This comparison revealed that flood modelling by photogrammetric DEM was considerably more detailed than that by light detection and ranging‐DEM, mainly because of higher point density and vertical accuracy. Consequently, flood analysis assisted by this novel geometric modelling approach qualifies as a reliable and competitive approach. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献