Changjiang River Scientific Research Institute

Wuhan, China

Changjiang River Scientific Research Institute

Wuhan, China
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Agency: European Commission | Branch: FP7 | Program: CP-FP-SICA | Phase: ENV.2009. | Award Amount: 4.00M | Year: 2010

LEDDRA aims to advance the comprehensive study of the socio-environmental fit of responses to land and ecosystem degradation and desertification (LEDD) in various contexts. It adopts the ecosystem approach and an integrated methodology with continuous feedbacks between theory, methods and applications. It focuses on response assemblages (combinations of response types and prevailing environmental, socio-economic and institutional conditions that contribute to or detract from sustainable land management and societal welfare), the associated costs and benefits to diverse stakeholders, barriers to and opportunities for adoption, and knowledge transfer processes. Optimal response assemblages comprise coordinated, mutually supportive and complementary measures that preserve the ecological and the community resilience of affected areas. LEDDRA develops the theory of responses to LEDD, in general, and in cropland, grazing land and forests/shrubland, in particular, and the study of knowledge transfer for diverse stakeholder types. It negotiates the links between land degradation, ecosystem services decline and biodiversity change, the links between biophysical and human determinants, welfare impacts, and responses to drought (drought preparedness). It improves existing and develops new integrated methodologies for assessing the impacts and fit of various types of responses to LEDD and the socio-ecological vulnerability of affected regions, and for identifying response assemblages in different European and other cultural-institutional contexts drawing on applications in selected sites in EU and ICPC countries. It analyzes the policy context to offer recommendations for policy and land management actions at the international, EU and national levels. To better organize, show case, disseminate and add value to project results, a web-based information system will be developed to make findings accessible to a wide range of stakeholders with different levels of expertise.

Zhou J.,Tsinghua University | Zhang M.,Tsinghua University | Lu P.,Changjiang River Scientific Research Institute
Water Resources Research | Year: 2013

We investigated the effect of the Three Gorges Project and other dams on the load of phosphorus (P) to the middle and lower Yangtze River (MLY) and discussed the alteration of P on the ecosystem of the MLY. We collected data for continuous flow and sediment over the past 60 years and observed the concentrations of total P (TP) and particulate P (PP) in the pool reaches of the Three Gorges Reservoir (TGR), both before and after the impoundment in 2003. As a result, we obtained highly positive correlations between P and sediment and revealed two changes that were caused by the impoundments: (1) the sediment load to the MLY decreases by 91% and the river becomes almost clear; and (2) the loads of TP and PP to the MLY are sequestered by 77% and 83.5% annually and 75% and 92% in dry seasons, respectively. Because P was the limiting nutrient for bioactivity in the MLY before 2003, such significant reductions, along with the many other consequences of the dams, will not only further reduce the bioavailability of P but also increase the existing high ratio of nitrogen (N) to P. Therefore, it is quite possible to alter the nutrient regime and reduce the aquatic primary productivity of the MLY. Given that many large dams with huge reservoirs are under construction or planned upstream and elsewhere, studies focused on the long-term effects of sediment and P reduction deserve a high priority for the protection of lowland rivers and aquatic ecosystems. ©2013. American Geophysical Union. All Rights Reserved.

Wu C.L.,Hong Kong Polytechnic University | Wu C.L.,Changjiang River Scientific Research Institute | Chau K.W.,Hong Kong Polytechnic University | Fan C.,Ryerson University
Journal of Hydrology | Year: 2010

This study is an attempt to seek a relatively optimal data-driven model for rainfall forecasting from three aspects: model inputs, modeling methods, and data-preprocessing techniques. Four rain data records from different regions, namely two monthly and two daily series, are examined. A comparison of seven input techniques, either linear or nonlinear, indicates that linear correlation analysis (LCA) is capable of identifying model inputs reasonably. A proposed model, modular artificial neural network (MANN), is compared with three benchmark models, viz. artificial neural network (ANN), K-nearest-neighbors (K-NN), and linear regression (LR). Prediction is performed in the context of two modes including normal mode (viz., without data preprocessing) and data preprocessing mode. Results from the normal mode indicate that MANN performs the best among all four models, but the advantage of MANN over ANN is not significant in monthly rainfall series forecasting. Under the data preprocessing mode, each of LR, K-NN and ANN is respectively coupled with three data-preprocessing techniques including moving average (MA), principal component analysis (PCA), and singular spectrum analysis (SSA). Results indicate that the improvement of model performance generated by SSA is considerable whereas those of MA or PCA are slight. Moreover, when MANN is coupled with SSA, results show that advantages of MANN over other models are quite noticeable, particularly for daily rainfall forecasting. Therefore, the proposed optimal rainfall forecasting model can be derived from MANN coupled with SSA. © 2010 Elsevier B.V.

Wu C.L.,Hong Kong Polytechnic University | Wu C.L.,Changjiang River Scientific Research Institute | Chau K.W.,Hong Kong Polytechnic University
Journal of Hydrology | Year: 2011

Accurately modeling rainfall-runoff (R-R) transform remains a challenging task despite that a wide range of modeling techniques, either knowledge-driven or data-driven, have been developed in the past several decades. Amongst data-driven models, artificial neural network (ANN)-based R-R models have received great attentions in hydrology community owing to their capability to reproduce the highly nonlinear nature of the relationship between hydrological variables. However, a lagged prediction effect often appears in the ANN modeling process. This paper attempts to eliminate the lag effect from two aspects: modular artificial neural network (MANN) and data preprocessing by singular spectrum analysis (SSA). Two watersheds from China are explored with daily collected data. Results show that MANN does not exhibit significant advantages over ANN. However, it is demonstrated that SSA can considerably improve the performance of prediction model and eliminate the lag effect. Moreover, ANN or MANN with antecedent runoff only as model input is also developed and compared with the ANN (or MANN) R-R model. At all three prediction horizons, the latter outperforms the former regardless of being coupled with/without SSA. It is recommended from the present study that the ANN R-R model coupled with SSA is more promisings. © 2011 Elsevier B.V.

Zhang S.,North China Electrical Power University | Pan B.,Changjiang River Scientific Research Institute
Journal of Hydrology | Year: 2014

With the increase of urbanization, conditions of the underlying surface and climate have been changed by human activities. This results in more frequent flooding and inundation problems in urban areas. Storm-inundation models based on hydrology and hydrodynamics require a large amount of input data (detailed terrain, sewer system and land use data). Simulation models are complex and difficult to build and run. To determine inundation conditions quickly with only a few commonly available input data, an urban storm-inundation simulation method (USISM) based on geographic information systems (GIS) is proposed in this paper. The method is a kind of simplified distributed hydrologic model based on DEM, in this method, depressions in the terrain are regarded as the basic inundated area. The amount of water that can be stored in a depression indicates the final inundation distribution. The runoff catchment area and maximum storage volume of a depression, and the flow direction between these depressions are all considered in the final inundation simulation. GIS technology is used to find the depressions in an area, divide the subcatchment for each depression, and obtain the flow order of the depressions based on a digital elevation model (DEM). The SCS method is used to calculate storm runoff, and a water balance equation is used to calculate water storage in each depression. Nangang District in Harbin City, China, is selected as the study area to verify the USISM. The result reveals that the USISM could find inundation locations in the urban area and quickly calculate inundation depth and area. The USISM is valuable for simulating storms of short duration in an urban area with a few commonly available input data. © 2014 Elsevier B.V.

Niu X.,Changjiang River Scientific Research Institute | Ding X.,Yangtze River Scientific Research Institute
Yanshilixue Yu Gongcheng Xuebao/Chinese Journal of Rock Mechanics and Engineering | Year: 2013

As restricted by project layout, geological and topographical conditions, the underground powerhouse of Three Gorges Project is arranged inside the mountain on right bank. The minimum thickness of rockmass over powerhouse is almost the same magnitude of powerhouse span. Obviously, it cannot meet the code's requirement that overburden thickness of caverns should be not less than 2 times of the excavation span. For such shallowly buried underground cavern with large span and high sidewall, overburden thickness of rock mass is limited but initial geostress magnitude should be also taken into account. Therefore, the top arch stability is viewed as the primary issue that should be addressed. Based on rockmass structure and rock mass strength characteristics, and the concept that horizontal geostress controls surrounding rock stability, the bearing mechanism of surrounding rock at top arch area of underground cavern is studied. Definition of stable arch and its existence mechanical condition are presented. The method for determining stable arch of underground cavern is proposed as well. The feasibility of applying stable arch concept to determine overburden depth of underground cavern is analyzed. A methodology for stable arch design of overburden depth of shallowly buried underground cavern is then formed. It is revealed that surrounding rock at top arch area of underground powerhouse of Three Gorges Project possesses such stable arch formation conditions in terms of overburden depth and horizontal stress. Its minimum overburden thickness for stable arch formation is two-thirds of powerhouse span. The minimum and maximum values of horizontal lateral pressure coefficients for stable arch formation are 1.5 and 3.0, respectively. The proposed methodology was adopted in the arch design of underground powerhouse of Three Gorges Project. The observations of several years show that the surrounding rock at top arch area of underground powerhouse is stable, thus indicating that under given rock mass strength, rock mass structure and initial geostress conditions of Three Gorges Project, the overburden thickness determined by stable arch design methodology is appropriate and reliable. The surrounding rock stability and project safety can be both satisfied. The design of shallowly buried large scale caverns is therefore provided with reliable guidance.

El Kateb H.,TU Munich | Zhang H.,TU Munich | Zhang P.,Changjiang River Scientific Research Institute | Mosandl R.,TU Munich
Catena | Year: 2013

The southern of the Shaanxi Province in central China is a region of great magnitude for water conservation. Long term anthropogenic interference in terms of deforestation and inappropriate land use has dramatically accelerated soil erosion in this region. A field experiment in the Shangnan County using 33 small erosion plots of 7m2 in size was carried out to determine and compare the soil loss and surface runoff from five vegetation covers and three levels of slope gradient (>10°-≤20°, >20°-≤30°, and >30°). The five vegetation covers embraced the most frequent rural land-use forms in the study area: farmlands including horticulture (tea plantation with peanut as an intercrop) and agriculture (maize in a winter-wheat-summer-maize rotation) activities, grasslands that have developed on abandoned farmlands, and forestlands including low and high forests (Chinese cork-oak coppices and pine plantations, respectively). The change in the runoff among the vegetation covers and slope gradients was high but not as significantly pronounced as for the change in the soil loss. Results showed that the slope gradient has an impact on the runoff and soil loss: the greater the slope gradient the higher the potential for runoff and soil loss. In addition, results exhibited that the rate of erosion is substantially affected by changes in vegetation cover. Farmlands generated the highest runoff and soil loss, whereas the tea plantations at slopes >30° were most susceptible to erosion. Grasslands had less runoff and soil loss than farmlands. Forestlands provided evidence for their suitability for soil and water conservation in the study area, as negligible soil-losses in comparison to the other vegetation covers were generated. © 2013 Elsevier B.V.

Cheng W.,Changjiang River Scientific Research Institute
Shuikexue Jinzhan/Advances in Water Science | Year: 2013

The rainfall threshold is an important indicator of flash flood conditions. In this study, the existing methods for computing rainfall thresholds are divided into two categories and reviewed on the basis of their technical principles. The two categories include the data-driven statistical and inductive methods and the physical process-based hydrologic hydraulic methods. As expansions of rainfall thresholds, the dynamic rainfall threshold and the storm critical curve are also introduced and discussed together with advances in uncertainty analysis of rainfall thresholds. In our review, the statistical and inductive methods have been more widely accepted in China. Moreover, antecedent rainfall (or antecedent soil saturation) and cumulative rainfall at particular time intervals are the two governing factors commonly considered in the calculation of rainfall thresholds. Cumulative rainfall may be the loneliness factor to be considered at times. Further, it is found that the rainfall threshold conveys poorly the magnitude of flash flooding. Understanding of the uncertainty in rainfall threshold calculations would be helpful for the improvement of flash flood warnings. However, how to incorporate the uncertainty into the decision-making process still remains a major challenge.

Lin Y.F.,Changjiang River Scientific Research Institute
Water Resources and Environment - Proceedings of the International Conference on Water Resources and Environment, WRE 2015 | Year: 2016

During 1970 to 1980, 28 cross-sections were measured and observed along 91. 75 km to 117. 11 km within Danjiangkou (DJK) Reservoir in order to study the non-equilibrium sediment transport. In this study, the equations for the non-equilibrium sediment concentration and composition were applied in a two-dimensional numerical model to simulate the non-equilibrium sediment transport in DJK Reservoir. The simulation results coincided better with the measured value. According to the comparison results, they can be used for analysis of the long-term sediment transport within DJK Reservoir. © 2016 Taylor & Francis Group, London.

Changjiang River Scientific Research Institute | Date: 2015-05-08

A coating material, including a bottom layer, a middle layer and a surface layer. The bottom layer is an epoxy mortar having a thickness of between 1 and 3 mm, the middle layer is an epoxy resin adhesive having a thickness of between 0.1 and 0.5 mm, and the surface layer is a nanomaterial-modified polyaspartic having a thickness of between 0.3 and 0.5 mm. The epoxy resin adhesive has a viscosity of between 50 and 200 mPas.

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