Climate change and fenology of birds sprig arrival

Lietuvos matematikos rinkinys ◽

10.15388/lmr.2008.18095 ◽

2008 ◽

Vol 48 ◽

Author(s):

Feliksas Ivanauskas ◽

Remigijus Lapinskas ◽

Mečislovas Žalakevičius

Keyword(s):

Climate Change ◽

Climate Change Impact ◽

Regression Models ◽

Arrival Dates ◽

Spring Arrival ◽

Change Impact ◽

Arrival Timing

The paper investigates the climate change impact on bird first spring arrival dates, including interpretation of mechanisms of changes in dates. Regression models for 46 species of birds based on data collected in Lithuania in 1966–2000are created and discussed.An explanation of changes in arrival timing is proposed.

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Regional regression models for hydro-climate change impact assessment

Hydrological Processes ◽

10.1002/hyp.10312 ◽

2014 ◽

Vol 29 (8) ◽

pp. 1972-1985 ◽

Cited By ~ 9

Author(s):

Rabi Gyawali ◽

Veronica W. Griffis ◽

David W. Watkins ◽

Neil M. Fennessey

Keyword(s):

Climate Change ◽

Impact Assessment ◽

Climate Change Impact ◽

Regression Models ◽

Climate Change Impact Assessment ◽

Regional Regression ◽

Change Impact

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Climate change impact on water supply demands: case study of the city of Skopje

Water Science & Technology Water Supply ◽

10.2166/ws.2019.098 ◽

2019 ◽

Vol 19 (7) ◽

pp. 2172-2178 ◽

Cited By ~ 1

Author(s):

Katerina Donevska ◽

Angelco Panov

Keyword(s):

Climate Change ◽

Drinking Water ◽

Water Supply ◽

Air Temperature ◽

Climate Change Impact ◽

Regression Models ◽

Climate Change Scenarios ◽

Temperature And Precipitation ◽

Change Impact ◽

The City

Abstract The aim of the paper is to present the climate change impact on drinking water supply, and to assess the availability of current water resources to meet the increasing demands in climate change conditions, for the city of Skopje. Series of monthly precipitation and temperature data are estimated up to 2050, using recorded data and data for predicted changes of air temperature and precipitation according to climate change scenarios. Climate change impact on drinking water supply is assessed using multi-regression models for the dependence of the water supply data on the main climate parameters: temperature and precipitation. Forecast of future water quantities includes implementation of multi-regression models defined with a set of independent variables: the number of the population for time sets (t, t-1, t-2, t-3), precipitation and air temperature including predicted changes of the data under climate change conditions for the same time sets. Two scenarios are analysed: the first predicts that the number of the population until 2050 remains nearly the same as nowadays, the second predicts an increase of the number of the population at an average annual rate of increase of 0.58%. Results indicate shortage of available water resources for population and industry in climate change scenarios (increase of temperatures and decrease of precipitation) and increase of population.

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