Application of principal component analysis to long-term reservoir management

1988 ◽  
Vol 24 (7) ◽  
pp. 907-912 ◽  
Author(s):  
Maarouf Saad ◽  
André Turgeon
Atmosphere ◽  
2016 ◽  
Vol 7 (12) ◽  
pp. 155 ◽  
Author(s):  
Barbara Giussani ◽  
Simone Roncoroni ◽  
Sandro Recchia ◽  
Andrea Pozzi

2020 ◽  
Author(s):  
Huihui Dai

<p>The formation of runoff is extremely complicated, and it is not good enough to forecast the future runoff only by using the previous runoff or meteorological data. In order to improve the forecast precision of the medium and long-term runoff forecast model, a set of forecast factor group is selected from meteorological factors, such as rainfall, temperature, air pressure and the circulation factors released by the National Meteorological Center  using the method of mutual information and principal component analysis respectively. Results of the forecast in the Qujiang Catchment suggest the climatic factor-based BP neural network hydrological forecasting model has a better forecasting effect using the mutual information method than using the principal component analysis method.</p>


2016 ◽  
Vol 30 (4) ◽  
pp. 431-445
Author(s):  
Angelica Durigon ◽  
Quirijn de Jong van Lier ◽  
Klaas Metselaar

AbstractTo date, measuring plant transpiration at canopy scale is laborious and its estimation by numerical modelling can be used to assess high time frequency data. When using the model by Jacobs (1994) to simulate transpiration of water stressed plants it needs to be reparametrized. We compare the importance of model variables affecting simulated transpiration of water stressed plants. A systematic literature review was performed to recover existing parameterizations to be tested in the model. Data from a field experiment with common bean under full and deficit irrigation were used to correlate estimations to forcing variables applying principal component analysis. New parameterizations resulted in a moderate reduction of prediction errors and in an increase in model performance. Agsmodel was sensitive to changes in the mesophyll conductance and leaf angle distribution parameterizations, allowing model improvement. Simulated transpiration could be separated in temporal components. Daily, afternoon depression and long-term components for the fully irrigated treatment were more related to atmospheric forcing variables (specific humidity deficit between stomata and air, relative air humidity and canopy temperature). Daily and afternoon depression components for the deficit-irrigated treatment were related to both atmospheric and soil dryness, and long-term component was related to soil dryness.


2011 ◽  
Vol 50-51 ◽  
pp. 404-408
Author(s):  
Xiao Qiang Guo ◽  
Zhen Dong Li ◽  
Dong Dong Hao ◽  
Xin Xie ◽  
Jian Min Wang

This paper from the economic analysis, quantitative evaluation of the 2010 Shanghai World Exop impact. First, from the short-term and long-term benefits of the two considerations, the loss of earnings, base construction costs on the percentage of total funding, permanent building retained, the number of daily tours, the number of participating countries for the evaluation index, subjectively weight to the five indicators,calculate its scores to rank for five World Expos including Shanghai World Expo. Second, using principal component analysis, we get the five indicators of objective weighting and ranking for above five World Expos. The results show that the Shanghai World Expo will boost the economic development and has a huge influence on the economy


2017 ◽  
Vol 167 ◽  
pp. 113-122 ◽  
Author(s):  
Agustín Herrera ◽  
Davide Ballabio ◽  
Natalia Navas ◽  
Roberto Todeschini ◽  
Carolina Cardell

Author(s):  
O. E. Abiodun ◽  
J. B. Olaleye ◽  
J. O. Olusina ◽  
O. g> Omogunloye

Urban expansion has been identified as a major cause of global climatic and environmental changes. Accurate and up-to-date information about urban expansion in terms of the drivers responsible for this expansion are important for long term planning and sustainable urban development. Lagos is one of the cities that have undergone rapid urban enlargement in the last few decades and, many factors have been adduced to contribute to its sprawling. Therefore, this study aims at using the Principal Component Analysis (PCA) for identifying the principal drivers of urban expansion in greater Lagos. In this study, a set of fourteen (14) drivers of expansion are considered in a multinucleic structure. A sequence of Landsat images of the study area for 1984, 2001, 2006 and 2013 was acquired and processed to six land use classes: dense, moderate urban, water, vegetation, wetland and mangrove. The study area was partitioned into 25 regular cells of 20km by 25km each from where proximate driver values were obtained. The effectiveness of each driver was tested using PCA. The results show that Land Availability accounted for 37.836% of total variance. This result of this study may form the basis for a renewed attention on land policy in the study area as a way to enhance sustainable development.


Sign in / Sign up

Export Citation Format

Share Document