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Frontiers of Earth Science

ISSN 2095-0195

ISSN 2095-0209(Online)

CN 11-5982/P

邮发代号 80-963

2019 Impact Factor: 1.62

Frontiers of Earth Science  2017, Vol. 11 Issue (2): 203-213   https://doi.org/10.1007/s11707-017-0622-7
  本期目录
Simple statistical models for relating river discharge with precipitation and air temperature—Case study of River Vouga (Portugal)
T. STOICHEV1(), J. ESPINHA MARQUES2, C.M. ALMEIDA1, A. DE DIEGO3, M.C.P. BASTO4, R. MOURA2, V.M. VASCONCELOS1
1. Interdiscplinary Center of Marine and Environmental Research (CIIMAR/CIMAR), University of Porto, 4450-208 Matosinhos, Portugal
2. Institute of Earth Sciences (ICT) and Department of Geosciences, Environment and Land Planning, Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal
3. Department of Analytical Chemistry, Faculty of Science and Technology, University of the Basque Country UPV/EHU, 48080 Bilbao, Basque Country, Spain
4. CIIMAR/CIMAR and Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal
 全文: PDF(1650 KB)  
Abstract

Simple statistical models were developed to relate available meteorological data with daily river discharge (RD) for rivers not influenced by melting of ice and snow. In a case study of the Vouga River (Portugal), the RD could be determined by a linear combination of the recent (PR) and non-recent (PNR) atmospheric precipitation history. It was found that a simple linear model including only PR and PNR cannot account for low RD. The model was improved by including non-linear terms of precipitation that accounted for the water loss. Additional improvement of the models was possible by including average monthly air temperature (T). The best model was robust when up to 60% of the original data were randomly removed. The advantage is the simplicity of the models, which take into account only PR, PNR and T. These models can provide a useful tool for RD estimation from current meteorological data.

Key wordsmultiple regression    atmospheric precipitation    river discharge    runoff    Aveiro Lagoon
收稿日期: 2016-01-27      出版日期: 2017-05-19
Corresponding Author(s): T. STOICHEV   
 引用本文:   
. [J]. Frontiers of Earth Science, 2017, 11(2): 203-213.
T. STOICHEV, J. ESPINHA MARQUES, C.M. ALMEIDA, A. DE DIEGO, M.C.P. BASTO, R. MOURA, V.M. VASCONCELOS. Simple statistical models for relating river discharge with precipitation and air temperature—Case study of River Vouga (Portugal). Front. Earth Sci., 2017, 11(2): 203-213.
 链接本文:  
https://academic.hep.com.cn/fesci/CN/10.1007/s11707-017-0622-7
https://academic.hep.com.cn/fesci/CN/Y2017/V11/I2/203
A user-built function, called “select1” was developed under R for random selection without replacement of fraction f<1 (from “fbegin” to “fend” increasing with step “fstep”) of the original data from the dataframe x:
select1<-function(x, fbegin, fend, fstep){
rounded<-function(n) floor(n+0.5)
f<-fbegin
sel<-x[sample(1:length(x[,1]),rounded(f*length(x[,1]))),]
repeat{
t<-max(f)
if (t>=fend) break
sel1<-x[sample(1:length(x[,1]),rounded((t+fstep)*length(x[,1]))),]
f<-c(f, (t+fstep))
sel<-list(sel, sel1)}
return(list(f, sel))}
  
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