1
Geography and Development
10nd Year - No. 29 - Winter 2013
Received : 21/9/2011 Accepted : 17/7/2012
PP : 1- 5
The Relationship Between Atmospheric Circulation Patterns and Total Ozone
Variations in Isfahan
Dr. Abbasali Arvin (Spanani)
Assistant Professor of Climatology
University of Payame Noor
Introduction
The ozone layer as a protective shield life on biosphere has very oscillations from view point of
quantity and volume. The ozone gases in both troposphere and stratosphere layers have been affecting
on human life by two ways. The ozone in stratospheric that its name is surface ozone is an extremely
poisonous gases and has destructive affect on lung and plant tissue. The surface ozone has been
measured in measurement pollutant stations as one of seven pollutant gases. The ozone gas in
stratospheric layer unlike the surface ozone is very necessary for human and other organism lives. The
stratospheric ozone is measured in meteorological stations by name of total ozone (TO). Studies show
that amount of ozone in stratospheric layer has been reduced. Variations in ozone layer were effected
of changing in solar radiation, volcano eruption cosmic dust, meteoric stones and etc. that those get
name as natural parameter of ozone changes. Effect of natural parameter concentration on
stratospheric ozone lead to fix ozone content in long term (spanani 2004). The amount of ozone in
stratospheric layer particularly in the lower stratospheric has considerable oscillations
(increase/decrease) under the affection of atmospheric activities . For example V. C. Roldugin (2000)
showed that passing the wave crest in the pressure field ceases the convergence of ozone poor air
under the tropopause and divergence of ozone rich air above the tropopause and decreases the ozone
content. The passing of a wave through simulate the opposite process and increase the ozone content
T. Narayana Rao at all (2003) opining that the climatology of ozone clearly shows a significant
seasonal cycle with the ozone maxima changing with height. The monthly variability of ozone as well
as its seasonal maximum is found near the tropopause. Variation in tropopause height is due mainly to
the passage of tropospheric weather systems and is responsible for the large monthly variability of
ozone near the tropopause. In the lower stratosphere, inter annual variations are at a maximum in
winter and spring, and are the result of variations in wave driven stratospheric circulation, which peaks
in winter. Regarding this matter that total ozone have been affected from atmospheric parameter in
lower stratosphere or upper troposphere, we decide to study the role of pattern circulation on ozone
variations in Isfahan.
Research Methodology
Geography and Development, 10nd Year, No.29, Winter 2013
2
In this research the environmental to circulation method has been used for synoptic patterns analysis.
The mean daily of total ozone (TO) data related to Isfahan ozone survey center in the time period of
2005-2009 were used. From the total 1975 days, 174 days was missing value therefore the daily data
of 1801 days (TO) have been used in analysis. The days that (TO) were under 250/above 310Du
considered as min/max amount of ozone. The days that (TO) also was around the mean (284 Du) and
had highest frequency (274 Du) had been used.
Then mean daily of geo-potential height for 100, 300 and 500mb levels for distance of 0 to 80° east
and 10° to 70° North was taken from the NCEP/NCAR climatic data center. The 100 and 300mb
levels were selected for finding the trough or ridge affect and the 500mb to find the low height (low
pressure) or high height (high pressure) have been selected to find atmospheric stability or instability
affecting on ozone variation. Correlation methods and multiple liner regression have been used for
relation analysis between TO maps and synoptic pattern maps. For this aim, mean daily data of total
ozone for distance of geographical 10°*10° degree had been got from the total ozone spectrometer
mapping center (NASSA/GSFC). Then the total ozone isolate maps were drawn for days that the total
ozone is max, min or high frequency. Then by the use of correlation relation, the total daily amount of
ozone and geo potential were analyzed.
Discussion and Results
The ozone variability depends on the atmospheric activity. Thus it is so variable in winter due to
atmospheric instability, high contents in spring due to universal increasing, low variability caused by
atmospheric stability in summer and low content cased by the global decrease of ozone in autumn.
We review two periods (one of them related to minimum and another to maximum of total ozone (TO)
content) of circulation patterns from the 21 periods. The maps of 8 to 10 December 2005 were
analyzed as the minimum ozone indicates a stable and calm atmosphere on Iran. On December eighth,
a ridge is entering in to Iran at elevation 100 & 300 mb, and includes the negative vortices and
anticyclone. In this day the amount of ozone is 236 Du. At December ninth, the ridge pattern is at 100
and 300mb elevation and anticyclone condition , at 500mb elevation is placed on Iran completely and
the content of total ozone has decreased to 222Du. Thus in time that ridge axes is at 100 and 300mb
elevation and dynamic anticyclone at elevation 500mb is placed on Isfahan completely, the ozone
poor air is transferred to Isfahan and the total ozone is decreased to the lowest amount. The maps of 30
March to 1 April 2009 are analyzed as the maximum pattern of TO. An instability atmospheric has
overcome on Isfahan in this period. The trough pattern in 100mb and a completely cyclone typical in
500mb that deepens to 300mb level was on Iran that has caused the increase of TO to 349Du. The
trough axes in 100mb level and very deep cyclone in 500mb to 300mb level has been set in center of
Iran that the TO has increased to 371Du in day 31 March. Amount of 7.4 millimeter rainfall has been
recorded in Isfahan meteorological station on 31March.
Thus the
relation
between
the daily
The Relationship
Between
Atmospheric
Circulation
Patternsmaps
and …of
TO with the pattern of synoptic maps were analyzed through correlation relations.
The analyses show that at he three levels of 100,300 and 500 mb , there are a significant inverse
relation between TO and geo-potential height in 0.01 sig level. The most important effective variable
3
in maximum occurrence time is the changes of 100mb level height and in mode occurrence and
minimum amount of ozone is the changes of 300 mb level height . Relationship between geo-potential
variation and TO content in upper level of troposphere (100 and 300mb) is stronger because density of
ozone is higher under the tropopouse. Thus with increase/decrease of geo-potential height (high/low
pressure conditions), the TO increase/ decrease simultaneously. Mass effect of three level balance on
TO variability is surveyed by linear multiple regression method and show that geo-potential height
affect on TO by correlation coefficient of R=0.994, R=0.885 and R=0.897 in order to mod, maximum
and minimum of TO occurrences. Thus 89.1%, 80.5% and 78.4% of TO variations is explained by
variability of geo-potential height in order mod, maximum and minimum of TO occurrences. Density
of ozone iso-path in around of low pressure center in 500mb level show that the TO have been
increased with the decrease of atmospheric pressure.
Conclusion
Our research showed that a part of TO variation in Isfahan correlated with geo-potential height
variations in troposphere layer. The occurrence of content min/max of TO has been adapted with
ridge/trough pattern in 100 and 300mb levels and dynamic anticyclone/dynamic cyclone in 500mb
level. The lowest/highest TO content occurred in time that ridge/trough axes taken place on Iran and
Isfahan. TO oscillation is low in warm season and synoptic parameter affect on its variation is very
low. Thus atmospheric instability ceased variety and oscillation of TO in cold season but atmospheric
stability ceased to fix content of TO in warm season. There is a significant reverse correlation between
geo-potential height and content of TO that this relation is stronger in upper level of troposphere.
Keywords: Isfahan, Total ozone (TO), Circulation patterns, Stratosphere, Multi variable linear
regression.
Refrences
1. Spanani, Abbasali (2004). Ozone and its Role in the life of earth, Geographical Space
Magazine, No.11.
2. Atayee, Hoshmand (2008). Identification and Analysis of Circular Patterns of ,Middle
atmosphere in Heavy precipitation Years of Iran, No.90.
3. Alijani, Bohlool (2006). Synoptic climatology, Samt Publication, Tehran.
4. Mahamed, Ahmad (1998), (1999). Ozone Layer (Shield of Life), Iran Research Group.
5. Masoodian. A (2005). Thirty years ridge of circular patterns of Iran middle atmosphere,
Geography and Regional Development Magazine, No.7.
6. Alijani. B (2006). Synoptic Climatology, Samt publication, Tehran.
7. Ataei. H (2008). Recognition and Analysis of circulation pattern middle atmospheric Level in
Rainy Region in Iran, Geographical Research, No. 90.
8. Chandramadhab Pal (2010) Variability of total ozone over India and its adjoining regions during
1997-2008, Atmospheric Environment 44.
Geography and Development, 10nd Year, No.29, Winter 2013
4
9. E. Rozanov, M. Schraner, C. Schnadt, T. Egorova, M. Wild, A. Ohmura, V. Zubov, W.
Schmutz, Th. Peter (2005). Assessment of the ozone and temperature variability during 1979–
1993 with the chemistry-climate model SOCOL, Advances in Space Research 35.
10. E. Rozanova, T. Egorovab, W. Schmutzb, Th. Peter (2006). Simulation of the stratospheric
ozone and temperature response to the solar irradiance variability during sun rotation cycle,
Journal of Atmospheric and Solar-Terrestrial Physics 68.
11. Ezatian. V. Bagheri. A (2009). Quality Control of Ozone Data By Use of TOMS Spectrometers
Data. 4th International Conference of Climate Chang.
12. Ezatian. V. Asadieskoei. E (2010). Application of Statistical Methods in Tropospheric ozone
oscillation analysis, Iran Geo-physic Journal.
13. Ghvidelrahimi. Y (2010). Mapping and interpretation of Climate Synoptic by Use of Grads
Softward, Sahadanesh, Tehran.
14. Jahanbakhsh. S. Karami. F (1999). Geographical Research, No. 54 & 55.
15. J. Leclair De Bellevuea, J. L. Baraya, S. Baldya, G. Ancelletb, R. Diabc, F. Ravetta (2007).
Simulations of stratospheric to tropospheric transport during the tropical cyclone Marlene event,
Atmospheric Environment 41.
16. Johannes Staehelin, Jorg Moder, Andrea K. Weiss, Christof Appenzeller (2002). Long-team
ozone trends in Northern mid – latitudes With special emphasis on the contribution of changes
in dynamics. Physics and Chemistry of the earth.
17. J. L. Atti, and R. Abida (2004). An observed and analyzed stratospheric ozone intrusion over
the high Canadian Arctic UTLS region during the summer of 2003, Advances in Space
Research 34.
18. M. Antón, M. López, A. Serrano, M. Bañón, J. A. García (2010). Diurnal variability of total
ozone column over Madrid (Spain), Atmospheric Environment.
19. M. Martin, T. Toroshelidze, W. E. Alves, M. G. S Mello, A. A. Guser, G. I. Pugacheva (1999).
Solar cycle and global long team variations of stratospheric ozone, Adv Space Res.
20. Matthew R. Bassford, Chris A. McLinden, Kimberly Strong (2001). Zenith-sky observations of
stratospheric gases: the sensitivity of air mass factors to geophysical parameters and the
influence of troposphere clouds, Journal of Quantitative Spectroscopy & Radiative Transfer 68.
21. Mohamed. A (1998). Ozone Layer (Shield of Life) Iran Research Grop. Tehran.
22. Masoodian. A (2006). Synoptic Climatology and its Application in Environmental Studies,
Brant Yarnal, Isfahan University.
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Winds of Bahman 1982 Sanandaj) Geographical Research, No. 90.
24. Nasiri. B. Ghaemi. H (1999). Synoptic andTheDynamic
RelationshipPatterns
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Nevodovskiy, Alexsandr V. Morozhenko (2009). Studies of stratospheric ozone layer from
near-earth orbit utilizing ultraviolet Polari meter, Acta Astronautica 64.
5
26. Renata De winter-Sorkina (2001). Impact of ozone layer depletion I: ozone depletion
climatology, Atmospheric Environmen.
27. S. Hassanzadeha, F. Hosseinibalama, M. Omidvari (2008). Statistical methods and regression
analysis of stratospheric ozone and meteorological variables in Isfahan, Physica A 387.
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la couched ozone, C. R. Geosciences 342.
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the troposphere and lower stratosphere over the European ArcticAdvances in Space Research
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ozone distribution and its links with the global scale for the years 1992 and 2015, Atmospheric
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Geography and Development, 10nd Year, No.29, Winter 2013
6
Geography and Development
10nd Year - No. 29 - Winter 2013
Received : 17/8/2011 Accepted : 17/7/2012
PP : 6 - 9
Spatial Modeling of Annual Precipitation in Iran
Dr. Hossein Asakereh
Associate Professor of Climatology
University of Zanjan
Zohre SeifiPour
M. Sc of Climatology
University of Zanjan
Introduction
Due to deep, complex and everlasting interaction between precipitation and climatic elements-factors,
there are changes and varieties in both time and space dimensions of precipitation. So that climate
experts and related scientists take their attentions to this phenomenon. An approach to do this kind of
investigations is to describe spatial variations based on spatial statistics.
The major spatial non-stationary of Iran precipitation is due to variation in situation, elevation and
topography characters (slope and its direction) in this country. Circumstances of every one of these
characters could determine the precipitation spatial patterns. Accordingly understanding spatial
distribution of precipitation and its mechanism are important aspect in climatological researches.
One of the common statistical models in which it is possible to determine the relation between
variables as well as reconstruct, estimating and forecasting data is multivariate regression model.
These sorts of models are useful for time series analyses as well as spatial modeling. One of the
regression models that could be used in spatial analyses is called Geographically Weighted Regression
(GWR). In current study it will be attempted to introduce this approach and using General Regression
(GR) to justify spatial variation of precipitation in Iran based on 1436 stations in Iran.
Research Methodology
In this research Esfezary data base have been used. This daily data based contain 15998 days and
7187 pixels (15*15 KM) of precipitation over Iran. Accordingly the data matrix is created in 15998*
7187 and S-mode dimension. This matrix data base is estimated by using 1436 stations and Kriging
method.
To achieve independent variables, digital elevation map by 15*15 KM resolution has been created. So
that, spatial (including longitude and latitude) and topographic (including slope magnitude and aspect)
characters have been derived. Accordingly a data base has been created that contain spatial characters,
topographic features and precipitation amounts.
Spatial Modeling of Annual Precipitation in Iran
7
The proper regression model on precipitation has been chosen based on spatial and topographical
characters. Multivariate General Regression (MGR) for these m independent variables is defined as
follow:
m
Ri  b0   bk xk   k
k 1
Where Ri is precipitation in a given pixel that depends on” m “climatic factors.
Geographical Weighted Regression (GWR) allows local rather than global parameters to be estimated
and the above model is rewritten as:
k
Ri  b0 (i , i )   bk (i , i ) xik   i
i 1
In geographically weighted regression, the parameter estimates are made using an approach in which
the contribution of a sample to the analysis is weighted based on its spatial proximity to the specific
location under consideration. Thus the weighting of an observation is no longer constant in the
calibration but varies with different locations. Data from observations close to the location under
consideration are weighted more than data from observations far away.
In this paper spatial distribution of precipitation had been modeled using General Regression and
Geographical Weighted Regression. Finally the most effective variables on precipitation have been
clustered using Euclidean distance method and Ward clustering method.
Discussion and Results
Annual mean of Iran precipitation is about 256 mm. Spatial coefficient of variation of Iran
precipitation is about 79%. Generally distribution of precipitation isohyets over Iran follows
topographic features. The General Regression Model for precipitation is as follow:
R  236.6s  0.07a  0.04h  0.000007  0.00017  1107.819
47.98
7.67
14.14
16.748
44.863
r 2  0.48
This model can justify about 48% of spatial distribution of precipitation.
Using GWR model tends to different coefficients of spatial variables. Accordingly three regions have
been denoted: The first region in which precipitation is affected by elevation. This region is about 43%
out of the all area of the country that located in northwest, inner parts and southeast of Iran.
Precipitation of second region is affected by hillside of mountains in west of country that covers 18%
of Iran. The precipitation of third region that is about 39% of the country is determined by slope more
than other factors. This region located in small parts of northwest, west and southeast of Iran.
Conclusion
In order to justifying spatial changes of precipitation over Iran, 1436 stations and GWR technique
have been applied. Based on GWR model, elevation in northwest and inner parts of Iran, direction of
slop in Zagros mountain chain and the slop in northeast and Caspian coast are the spatial factors that
more controlling precipitation
Keywords: Cluster analyses, Spatial autocorrelation, Geographically weighted regression (GWR),
Spatial Modeling.
Refrences
Geography and Development, 10nd Year, No.29, Winter 2013
8
1. Alijani. B (1995). The Role of Alborz Mountain Chain on Elevation Distribution of
Precipitation. Geographic Research Quarterly. Vol 38.
2. Alijani. B (2002). The Role of Statistics on Developing of Geography Science. The 6 th of
International Conference of Iran Statistic. Trbiat Modares University. Tehran. Iran.
3. Alijani B (2008). Effect of Zagros Mountain on the Spatial Distribution of Precipitation,
Journal of Mountain Sciences, 5.
4. Asakereh. H (2000). Spatial Modeling of Climate Elements. A Case Study: Annual
Precipitation of Isfahan Province. Geographic Research Quarterly. Vol 74.
5. Asakereh. H (2010). Study of Dry Days Probability in Golestan Province by Using Markov
Chain Model. Geography and Development. Vol 17.
6. Brunsdon C, McClatchey. J and Unwin. D.J (2001). Spatial Variation in the Average Rainfall –
Altitude Relationship in Great Britain: An Approach Using Geographically Weighted
Regression. Int. J. Climatol. 21.
7. Fotheringham. A. S, Brunsdon. C , Charlton. M (2002). Geographically Weighted Regression,
John Wiley & Son, UK.
8. Foody G. M (2003). Geographical Weighting as a Further Refinement to Regression Modeling
an Example Focused on the NDVI-Rainfall Relationship, Remote Sensing of Environment, 88.
9. Gao. X, Asami. Y and Chung Chang-Jo F (2006). An Empirical Evaluation of Spatial
Regression Models. Computers & Geosciences 32 (2006) 1040–1051
10. Ghayoor H, Masodian S. A (1996). Study of Spatial Correlation of Precipitation and Elevation
in Iran. Geographic Research Quarterly. Vol 41.
11. Glazirin G.E (1997). Precipitation Distribution with Altitude, Theoretical and Applied
Climatology, 58.
12. Griffith Daniel A (2009). Spatial Autocorrelation, International Encyclopedia of Human
Geography.
13. Hansen. J and Lebedeff, S (1987). Global Trend of Measured Surface Air Temperature. Journal
of Geophysical Research. 92.
14. Harris. P, Fotheringham A. S, Crespo R, Charlton M.(2010). The Use of Geographically
Weighted Regression for Spatial Prediction: An Evaluation Weighted of Models Using
Simulated Data Sets, Mathematical Geosciences, 42.
15. Hasseler,U. (1997). Simple Regression with Time Trend. Journal of Time Series Analysis
Vol.21 No1.
16. Huang Y, Leung Y (2002) Analyzing Regional Industrialization in Jiangsu Province Using
Geographically Weighted Regression. J Geogr Syst 4.
17. Jedari. E. J. (1994). Geomorphology of Iran, Payam Noor Publication.
18. Jones, P. D., Raper, S. C. B. , Bradley. R. S , Diaz. H. F. , Kelly, P.M. and Wigley, T.M.L.
(1986) Northern Hemisphere Surface Temperature Variation: 1851-1984. J.clim. Appl .
Meteorol. 25.
Spatial Modeling of Annual Precipitation in Iran
9
19. Khalili. A. (1995). Three Dimensional Changes of Long Term of Atmospheric Annual
Temperature over Iran. Nivar. Vol. 32, 13-34.
20. Legendre P.(1993). Spatial Autocorrelation: Trouble or New Paradigm, Eclogy, 74:1659-1673.
21. Masodian. S. A. (1996). Analyses of Structure of Monthly Temperature of Iran. Research
Journal of Isfahan University. Vol 1,2. 87-96.
22. Masoodian S.A(2008). On Precipitation Mapping in Iran , Journal of Humanities the University
of Isfahan , 30:68-80.
23. Mojarad F, Moradi Farhaji M. (1996). Modeling the Relationships of Precipitation and
Elevation in Zagros area. Modares Quarterly. Vol 2. 163-182.
24. Moradi. H. (1997). The Role of Caspian Sea on Precipitation of North Coast of the Country.
Marian science of Iran. Vol 2, 3. 84-85.
25. Ranhao S., Baiping Z. and Jing T.(2008). A Multivariate Regression Model for Predicting
Precipitation in the Daqing Mountains, Mountain Research and Development. 28:318-325.
26. Razai T and Azizi GH. (2008). Study of Spatial Distribution of Seasonal and Annual
Precipitation in West of Iran. Geographic Research. Vol. 65. 18-39.
27. Sari saraf. B, Rajaei B., Mesri. A. and Almdari, P. (2009). Study the Relationship of
Precipitation and Topography in East and West of Talesh Hillside. Geography and
Environmental Planning. Vol 35. 63-84.
28. Singh. P and Kumar. N. (1997). Effect of Orography on Precipitation in the Western
Himalayan Region", Journal of Hydrology,199:183-206.
29. Wheeler. D. and Tiefelsdorf M.(2005). Multicollinearity and Correlation among Local
Regression Coefficients in Geographically Weighted Regression, Journal of Geographical
Systems, 7:161-187.
30. Zhang. T., Gove. J.H and Heath. L. S (2005). Spatial Residual Analysis of Six Modeling
Techniques, Ecological Modeling, 186:154-177.
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Computational Statistics and Data Analysis, 51: 6123-6137.
Geography and Development, 10nd Year, No.29, Winter 2013
10
Geography and Development
10nd Year - No. 29 - Winter 2013
Received : 25/5/2011 Accepted : 17/7/2012
PP : 10 - 13
Modeling Deforestation Using Logistic Regression, GIS and RS
Case study: Northern Forests of the Ilam Province
Dr. Saleh Arekhi
Assistant Profesor of Geography
University of Golestan
Aliakbar Jafarzadeh
M.Sc of Forestry
University of Sari
Saleh Yousefi
M.Sc of Watershed Management
University of Tarbiat Modarres Noor
Introduction
Land use and land cover are not static and are frequently subject to change due to human activities,
also, with attention to the trend of deforestation in recent years, is very important to estimate the
degradation in the different time periods. Access to information related to the past and realizing the
changes are necessary for solving deforestation problem. Identify and detect these changes can help
planners and managers to identify effective factors in land use and land cover changes and have to be
useful and effective programming for their control. Iran west forests is important in terms of area,
environmental issues, soil and water resources conservation which during the past decades due to
social and economic factors, lack of comprehensive management and etc lost its production capacity
and this trend threatens the future of the region forests. As a result, planning and management of these
forests are associated with many problems which lack the necessary studies in this area will contribute
to the above issue. To explore and evaluate these changes, using remote sensing and GIS techniques
and tools can have a considerable effect to generate spatial information and having analytical
capabilities.
In the present study, using the information resulting from comparing satellite images of two different
periods, identify changes trend in the studied forests and then with applying GIS analyzes to identify
effective factors in these changes can measure and the results presented in thematic maps and finally
suggested degradation probability model for the study area.
Research Methodology
In this research, remote sensing data include images of MSS (1976) and TM and also 1:50.000
topographic maps and 1:20.000 aerial photos of region were used. In order to classifying and
preparing forest map related to the study years, training samples are prepared with help of ground
operations using GPS device and also using processing and satellite images enhancement in
Modeling Deforestation Using Logistic Regression, GIS and RS …
11
environment of IDRISI software and finally, training sites of forest and non-forest areas were
prepared. Also, the spectral response of different bands for each of training site classes were drawn
and interpreted. After geo-referencing satellite images using ground control points, map of forest
extent related to years of 1976 and 2007 through classification on original and processed images of
MSS and TM was prepared. After preparing maps of forest extent related to years of 1976 and 2007,
each of the mentioned maps were classified into two categories of forest and non-forest and after
ensuring the accuracy of the maps produced in GIS environment for preparing changes map in forest
area, both maps at the beginning and end of the studied period were crossed with each other. The most
important factors in the forest degradation trend are the natural and human factors .In this research,
map of slope, aspect, elevation classes as natural factors affecting changes and distance from
residential areas, roads, distance from the edge of the forest and forest fragmentation index as human
factors were considered in the event of changes. In this direction, map of above factors using Arcview
and Idrisi software was prepared in GIS environment and was used to analyze. For preparing maps of
classes of slope, aspect, elevation, digital elevation model of the study area should be prepared.
Discussion and Results
Accuracy assessment results of classified maps are presented in the related table. With consideration
to high amounts of 83% of overall accuracy, these maps can be used for preparing degradation map.
After processing the satellite images, amount map and spatial distribution of forest areas in study area
was prepared in years of 1976 and 2007 with use of MSS and TM satellite images. With overlay the
classification results of two periods, occurred changes map was obtained. From this map, we can
extract amount of degraded forest and location of these changes. Results obtained of comparison of
two maps related to beginning and end of the time period (1976 and 1388) shows that during this
period, 19294 hectare of forest regions area has been decreased. In logistic regression, chi-square
statistic (-2Log Likelihood) or (-2LL) is widely used. When a model has a poor fit, having large
amount and when a model has a good match, its value is small. In this study, chi-square value was
117.309. Coefficients of the variables in the regression equation are very important and logit equation
coefficients list. 1 equation shows statistical model of degradation probability prediction obtained of
logistic modeling with seven variables: slope, aspect, elevation, distance from roads and population
centers, distance from the edge of the forest and forest segmentation index. Pseudo R2 for the model is
0.1608 and the ROC regression coefficient amount was equal to the amount of 0.7678. Based on this
equation, the spatial distribution map of the study area forests was obtained.
(1)
Forest degradation probability = -4.2303+0.007207(aspect)- 0.020488(distance from villages) 0.001495(elevation from sea level) – 0.00116 (slope) -0.001908 (distance from road) – 0.087687
(distance from the forest edge) + 0.14544 (forest fragmentation pattern)
Conclusion
This study has been taken place with objective of estimating the spatial distribution of Zagros forests
and in order to detect effective factors on forest degradation. In this study, the effect of seven factors,
Geography and Development, 10nd Year, No.29, Winter 2013
12
distance from roads and residential areas, forest fragmentation index, aspect, elevation levels, slope
and distance from forest and non-forest edge on forest degradation rate was studied In this study, to
investigate changes in forest, MSS sensor related to year of 1976 and TM sensor data related to year
2007 were processed and classified. The Studied images were classified in to two classes of forest and
non-forest and in order to study the degradation factors, map of forest degradation with spatial
variables of physiographic and human were entered into the model. For modeling and estimating the
spatial distribution of studied forests degradation, of logistic regression statistical method was used.
Output of regression logistic with Pseudo R2 equal to 0.1608 and ROC of 0.76 represents a relative
agreement with the actual degradation and ability to fit the model to estimate changes in forest area.
Also, with consideration to negative coefficients related to distance from residential areas and roads
can say with decreasing the distance then these factors, urban expansion and man-made regions
development, road construction and increase in population plays role in forest degradation of the study
area.
Keywords: Deforestation modeling, Remote sensing, Logistic regression, Zagros forests, Ilam.
References
1. Amini M.R, Shataee S, Moaieri M.H, Ghazanfari H (2009). Deforestation modeling and
investigation on related physiographic and human factors using satellite images and GIS (Case
study: Armerdeh forests of Baneh), Iranian Journal of Forest and Poplar Research. 16 (3).
2. Bagheri R, Shataee S (2010). Modeling loss of forest extent using the logistic regression, Case
Study: Ghehal Ghay watershed of the Golestan province, Iran Journal of Forest, Iran forestry
society, second year, 2 (3).
3. Braimoh A, Vlek P.L.G (2003). Modeling land use change in Northern Ghana, Conference,
technological and institutional innovations for sustainable rural development, Gottingen,
Germany. 21.
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Forest Cover Change Patterns (1973-2020). A Case Study from South Western Ghats (India).
Sensors, 8.
7. Gomez-Mendoza L, Vega-Pen A.E, Ramirez M.I, Palacio-Prieto, J.L, Galicia L (2006).
Projecting land-use change processes in the Modeling
Sierra Deforestation
Norte ofUsing
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Logistic Regression,
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8. Gruenberg W.D, Curtin P, Shaw W (2000). Deforestation Risk for the Maya Biosphere Reserve,
Guatemala. School of Renewable Natural Resources, The University of Arizona, Tucson,
Arizona, USA.
13
9. Jat M.K, Khare P.K, Khare D (2008). Monitoring and modelling of urban sprawl using remote
sensing and GIS techniques. International Journal of Applied Earth Observation and
Geoinformation, 10.
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Artificial Neural Networks. Environmental Modeling & Software, 19.
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Centre de Morphologie Mathe´matiques de Fontainebleau, 1 (2).
12. Matthew L, Robert J, Smith R.J, Nigel L.W (2004). Mapping and predicting deforestation
patterns in the lowlands of Sumatra. Biodiversity and Conservation, 13.
13. Mertens B, Lambin E. F (1999). Modelling land cover dynamics: integration of fine-scale land
cover data with landscape attributes. International Journal of Applied Earth Observation and
Geoinformation, 1.
14. Mesghari S (2002). Investigating Changes in forest areas using GIS and remote sensing, Tehran:
Researcgh Project, Technical College, Khajeh Nasir Toosi University.
15. Miriam S.W, Taylor V.S (2010). Modeling social and land-use/land-cover change data to assess
drivers of smallholder deforestation in Belize. Applied Geography 30.
16. 16. Njarluo S (2005). Investigating Changes in forest area using aerial photographs, topographic
maps and IRS and ETM+ images, M.Sc thesis of Forestry,Gorgan University of Agriculture
and natural resources.
17. Pierre Bavqa M (2004). Investigating Changes of forest extent in relationship with topographic
factors and man-made areas, Case Study: Eastern Forests of the Gilan province, M.Sc thesis of
forestry, Tehran University.
18. Pontius R.G, Schneider L (2001). Land-use change model validation by a ROC method for the
Ipswich watershed, Massachusetts, USA. Agriculture, Ecosystems and Environment. 85(1-3).
19. Rafieian O, Darvishsefat A.A, Namiranian M (2006). Determining changes extent of the Iran
northern forests between the years of 1993 to 2001 Using ETM+ Images, Journal of Agriculture
and Natural resources sciences and technology, 10 (3).
20. Ranjbar A (2002). Investigating and estimating forests degradation trend using GIS and remote
sensing data, M.Sc thesis of remote sensing, Khajeh Nasir Toosi University.
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data. Journal of Forest Science, 53.
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in estimating the amount of organic matter in the surface soil, Rangeland Journal, first year, 1.
Geography and Development, 10nd Year, No.29, Winter 2013
14
Geography and Development
10nd Year - No. 29 - Winter 2013
Received : 29/4/2011 Accepted : 17/7/2012
PP: 14 - 16
Threshold of Acanthus Harvesting to Sediment Produce
Dr. Iraj Jabbari
Associate Professor of Geomorphology
University of Kermanshah Razi
Behrooz Borna
M.Sc of Geomorphology
University of Kermanshah Razi
Introduction
Harvesting of self-growing plants, like acanthus; from the down slopes of mountainous regions often
causes disturbances to the appearance of the slopes if it is mowed intensively.
These soil disturbances often occur with spring showers that accelerate soil erosion. On the other
hand, the harvesting is inevitable because of acanthus clinical and sustenance uses and earning a
livelihood for many local people who make a living with such crop in the harvesting seasons. So, as
the spring season starts, the harvest of self growing plants becomes a usual phenomenon on the slopes
in lower altitudes. The harvest of rooting plants as acanthus is in a way that makes pits on the ground
and this may be agent of erosion when spring rain falls; specially, precipitation contact with plant
germination in Iran. So, in this study, it has been tried to elucidate if the harvesting of acanthus makes
erosion at every situation or reaching to erosion threshold needs to increase number of the harvesting
in area unit as well as other location with more gradient and other characteristics.
Research Methodology
In this survey has been taken into consideration the sediment producing in 16 plots with and without
acanthus in the Viece Mountain, near Kermanshah city. Whereas, gradients and orientation are factors
that play roles on erosion, in this research too, others aims purpose to study roles of acanthus
harvesting on the different gradients and orientations on erosion acceleration. In this reason, these
plots established on the four different slopes and two different aspects. The amount of sediment has
been measured from plots in 9 time precipitation when it falls on late winter and early spring in 2007.
Factor analyze and two ways ANOVA were the techniques that used for data analyzing.
Discussion and Results
A Max. shower including 46.8 mm produced 5.8 L. runoff and 0.69 g/m2 sediment on a slope with
40% gradient and a Min. rainfall with 1.4 mm precipitation set in motion only 0.175L runoff and
0.00153 g/m2 sediment from control plots on 15% slope.
Threshold of Acanthus Harvesting to Sediment Produce
15
Two ways ANOVA on obtained data shows that there is a significant difference between rainfall,
slopes, aspects and erosion, that is, erosion have been deference on variety of showers, slopes and
aspects. So, these results show that data have correctly been collected.
Using Factor Analysis method show that despite of a significant difference in the sediment producing
on the different rainfall, gradient and precipitation times, there aren’t any significant difference of
sediment producing between plots with and without acanthus plants(F1,71=0.944, P>0.05). The
statistical analysis continued and limited to only days when harvesting occur. It illustrated that
erosion don’t occur when acanthus harvesting become 2 - 4 per m2 as Kermanshah region, but
erosion may be get a significant level on regions where more harvesting acanthus occur.
Conclusion
This study is carried out at a region where slopes were not acute and the number of acanthus at area
unit were less, whereas, there are a lot of regions at Kermanshah province and even other neighbor
provinces where slopes are more acute and acanthus grow up more per unit area . So, harvesting from
these regions may increase probability of erosion occurrence as the results of this study show that the
amount of significant level goes up when the study is limited to only harvesting times.
Keywords: Acanthus, Sediment yield, Erosion, Kermanshah.
References
1. Ahmadian S.H., Safaie M. and Jafari B (2005). Comparison soil erosion at dry farm, abounded
dry farms, pasture and forest areas of Kasilan catchment – Mazadaran, Proceedings of 3rd
Erosion and Sediment National Conference, Soil Conservation and Watershed Management
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17
Geography and Development
10nd Year - No. 29 - Winter 2013
Received : 30/8/2011 Accepted : 17/7/2012
PP : 17 - 20
Synoptic Analysis of Sweeping Cold Waves of Iran
Case: Chahar Mahal & Bakhtiari, 21 Dec 2004-18 Feb 2005
Dr. Sadegh Karimi
Assistant Professor of Natural Geography
University of Shahid Bahonar
Dr. Hossein Negaresh
Associate Professor of Natural Geography
University of Sistan and Baluchestan
Dr. Bohlol Alijani
Assistant Professor of Natural Geography
University of Kharazmi
Dr. Taghi Tavosi
Assistant Professor of Natural Geography
University of Sistan and Baluchestan
Introduction
Human life has been affected by the weather conditions. Since weather conditions may be favorable or
adverse, human has tried to defend himself against climatic conditions through understanding the
nature of the climate. These efforts led to the identification of the origin and how they were created.
Such knowledge is also more accurate and more scientific.
In synoptic climatology, by relying on the accepted principle of explanation and analysis of
environmental changes of the earth surface through the changes of pressure patterns, it is possible to
more explain, analyze, and forecast the climatic phenomena of the earth surface.
One of the most important climatic disasters that threaten our country, are cold wave and sever
freezing that in some years covers large areas of the country. Freezing usually occurs with the entry of
the air masses of below zero degrees. These air masses accompanied with relatively stable and multiday cold waves that may lead to adverse effects. For example, scarce and extreme cold of January and
February 2005 in Iran, which has covered a wide and extensive part of the country.
For synoptic explanation and analyze of the sweeping cold wave of Iran, minimum temperature of
the stations within the province of Chaharmahal & Bakhtiari was selected and then the data of sea
level pressure ( SLP) & geo-potential height of middle level of atmosphere was select for explaining
this event.
ResearchMethodology
This study intends to present a synoptic analysis of the sweeping cold of January and February 2004 in
Charmahal & Bakhtiari province by the “Environment to circulation analyze “model. Then specifies
the cause and continuation of this cold.
Geography and Development, 10nd Year, No.29, Winter 2013
18
Following the accomplishment of this goal, means the synoptic analysis of sweeping cold wave from
21 December 2004 up to 18 February 2005, the data of eight meteorology stations (synoptic and
climatology) in this province was used. The statistics of minimum daily temperatures for this twomonth period of 8 stations were obtained from the Statistical Center of Iran Meteorological
Organization.
Also, the daily data of sea level pressure and geo-potential height for the months of January and
February (December 21, 2004 to February 18, 2005) at the study area with location accuracy of 2.5
was obtained from NCEP / NCAR base.
Discussion and Results
In this period, high-pressure center of Siberia, through its relocation from the east to the west, sends its
spit toward the lower geographical latitudes and consequently seven severe cold wave have been
created in the region. In this study, the cold wave is called small-period. Each small-period 1, 3, 5 and
7 were continued for two consecutive days. Each small-period 2 and 6, five days and finally smallperiod 4, has been continued for six consecutive days.
In all Geo-potential height maps, simultaneously with the penetration and spread of Siberian high
pressure on the study area, heights was created up to elevation 5,800 meters. This feature justifies the
falling of severe cold weather along the east part of these heights.
Comparing the maps of sea level pressure of small-periods showed the Siberian high pressure center
simultaneously with its developing over southern latitudes has moved up to about 50 degrees east
longitude (exactly along the geographic north of Iran) .
In peak condition, (25 to 29 January 2005), the sixth period of cold wave (up to mean temperature 16.7 ° C)has been formed in the study area.
Conclusion
In the period 10.01.1383 to 30.11.1383 (December 21, 2004 to February 18, 2005), the Siberian high
pressure with displacement of its center toward the west along geographical north of Iran, as well as
strengthening and expanding its spit toward the southern latitudes, has imposed a severe cold wave to
the study area. Its effects has been appeared as the severe fall of minimum temperatures in the area.
During the small-periods that Siberian high pressure is consistent with the orientation of the west
winds, the most severe cold waves has created in the region.
Keywords: Siberian high-pressure, Cold wave, Minimum temperature, Period-Small, Geo-potential
height, Sea level pressure.
Synoptic Analysis of Sweeping Cold Waves of Iran …
19
Refrences
1. Alijani, B (1369). How Siberian High and its effect on Iran East climate, Geographical
Research Quarterly, Year. 5, No. 17.
2. Alijani, B (1381). Synoptic climatology, Samt publisher, printing.1, Tehran.
3. Barati, G (1375). Designed and spring frost forecast of synoptic patterns in Iran, climate thesis
- (Supervisors: Bahlol Alijani), Tarbiat Modares University, Tehran.
4. Azizi, G (1383). Synoptic evaluation spring pervasive frosts in the western half of Iran,
Modarres Magazine, Issue 8 (1) and No.
5. Azizi, G., A. Hanafi, M. Soltani, M. Aghajani (1390). Synoptic Analysis of Severe Late and
inclusive freezing of Farvardin (year: 1388) Journal of Geography and Environmental
Planning, Year. 22, No. 41.
6. Behyar, M.B (1382). Examining frost phenomenon of Charmahal & Bakhtiari by synoptic Dynamic view, Geographical Research Quarterly, No. 69.
7. Buishand, T.A and Brandsma, T (1997). Comparison of circulation classification schemes for
predicting temperature and precipitation in the Netherlands, International Journal of
Climatology, 17.
8. Chen, D. and Hellstrom (1999). The influence of the North Atlantic Oscillation on the
regional temp erature variability in Sweden: spatial and temporal variations. Tellus 51 A (4).
9. Ding, Y and Krishnamurti, T.N (1987). Heat budget of the Siberian high and winter monsoon,
Monthly weather Review, Vol. 115.
10. Fattahi, E., T. Salehi (1382). Analysis of synoptic patterns of winter frost in Iran, Journal of
Geography and Development, No. 13.
11. Gabriela, M and A.Tercio (2007). Dynamics of Wave Propagation Leading to Frost in the
Extratropical Latitude Versus Tropical Latitude, Department of de Ciencias Atmospherics,
University of Sao Paulo, No 67.
12. Hojabrpoor, G. and B. Alijani (1386) synoptic analysis of Ardabil Province, Journal of
Geography and Development, No. 10.
13. Kh.D, J., H. Yazdanpanah, and Kh, Hatami (1388). Identification freezing phenomena of
circulation patterns using principal component analysis and cluster analysis, case study: Fars
Province, Natural Geography Quarterly, No. 4.
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Ruosteenoja (2007). Changes in Frost, Snow and Baltic Sea ice by the end of the twenty-first
century based on climate model projections for Europe, Springer Netherlands.
15. Lashkari, H (1387). Synoptic analysis of sweeping cold wave (year: 1382) in Iran, study
Natural Geography Researches, No. 66.
16. Meehl, A, C.Tebaldi and D. Nychka (2004). Changes in frost days in simulations of twentyfirst century climate, Climate Dynamics Journal, Springer Berlin/ Heidelberg.
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Japan. Journal of Meteorological Society of Japan, 67.
Geography and Development, 10nd Year, No.29, Winter 2013
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18. Moghimi, E., Sh. Goodarzinejad (1382). environmental hazards Magazine, first edition, Samt
publisher, Tehran.
19. Smolinski, K.K and July (2004). Interrelationship among Large Scale Atmospheric
Circulation Regimes and Surface Temperature Anomalies in the North American Arctic. A
Thesis Presented to the Academic Faculty. School of Earth and Atmospheric Sciences.
20. Statistics and Informatics, Iran Meteorological Organization (1388).
21. Takahashi, H (1990). Migration of the cold air mass related to rain belt formation of the
Chinese continent and atmospheric circulation system during the baiu season (in Jepanese),
geographic review of Japan, jeries A, 64 (10).
22. Vithkevich, V.I (1963). Agricultural Meteorology. Jerusalem (Mpnson).
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translated By Seyed Abolfazl Masoudian (year: 1385), first edition, University of Isfahan
Publisher.
21
Geography and Development
1t0nd Year - No. 29 - Winter 2013
Received : 17/10/2011 Accepted : 17/7/2012
PP : 21 - 27
Analysis of Rainfall and Discharge Trend in Kashafrood Watershed
Dr. Mehdi Vafakhah
Mohammad Bakhshi Tiragani
Assistant Professor of Watershed Management
M.Sc Student of Watershed Mangement
University of Tarbiat Modares
University of Tarbiat Modares
Majid Khazaei
M.Sc Student of Watershed Mangement
University of Tarbiat Modares
Introduction
The human activates and change of the land use has made changes in the peak and base flow discharge
of the rivers. Also increasing the global average temperature has made anomalies in meteorological and
hydrological variables such as precipitation and evapotranspiration. For better management of water
resources, the data of river flow rate changes and their creating elements of such changes are required.
Therefore the review of these anomalies as the trend determination in time series of hydrological and
meteorological variables in different areas and their relation with each other can have an especial
importance. In recent years, a great deal of studies have been made for the possible impacts of climatic
changes on the river flow, which most of them have studied the changes of long term climatic averages
and hydrological characteristics. Generally these changes have been studied in two cases. Firstly, the
analysis of registered and available statistics of precipitation and river flow and the other is the impacts
of different scenarios of climatic changes on the river flow by hydrological models. The most common
method for analysis of hydrometeological time series is the review of the existence or non- existence of
trend in them by using statistical tests. Generally the existence of trend in these series may be due to
gradual natural changes and climatic changes or the impacts of human activities. Various methods
have been presented up to now for analysis of time series trend which are dividable in to two groups of
parametric and non parametric. Non-parametric methods have a more extensive use in comparing with
parametric methods. The present research was performed to the aim of detecting the existence and
amount of discharge trend and precipitation at Kashafrood watershed in 13 meteorology and
hydrometric stations with statistical length of 1972-2006 at the north east part of Iran which is c
nsidered as the areas with low precipitation in Iran.
Material and Methods
Characteristics of the study area
Geography and Development, 10nd Year, No.29, Winter 2013
22
Kashafrood watershed is located at geographical longitude of 58° 20′ up to 60° 8′N and geographical
latitude of 35° 40′ up to 36° 3′) and from the north is limited to Hezar Masjed heights and from south
is limited to Binalood heights . The basin area is about 16500 km2 which dedicated itself a vast part of
Khorasan province. Around 500 km2 of the watershed area are the plain area and the remaining is the
heights.. The characteristics of the study watershed are low rainfall and high evapotranspiration. The
climate of the study watershed is semidry-cold. The characteristics of the study watershed are low
rainfall and high evapotranspiration.
Research Methodology
13 meteorological and hydrometric stations (Table 1) have been analyzed in this research.
Table 1 : The Characteristics of the selected stations in Kashafrood basin
Code of
station
Station name
River
Longitude
(E)
Latitude
(N)
Elevation(m)
Period of series
64-003
Imamzadeh
Radekan
36° 48′
59° 61′
1200
1972-2006
64-011
Golmakan
Golmakan
36° 28′
59° 12′
1300
1972-2006
64-013
Dolatabad
Kaho
36° 24′
59° 11′
1350
1977-2006
64-015
Bande Saroj
Ardak
36° 42′
59° 22′
1340
1974-2006
64-017
Zoshk
Zoshk
36° 18′
59° 09′
1950
1977-2006
64-019
Shandiz
Zoshk
36° 20′
59° 13′
1750
1974-2006
64-021
Anderekh
Kardeh
36° 36′
59° 40′
950
1967-1989
64-027
Zirbande Golestan
Jaghargh
36° 20′
59° 26′
1200
1985-2006
64-029
Kortian
Torogh
36° 10′
59° 31′
1240
1967-1987
64-033
Olang Asadi
Kashafrood
36° 14′
59° 51′
840
1972-2006
64-037
Aghdarband
Kashafrood
36° 00′
60° 51′
620
1967-2006
64-043
Chekneholya
Chekneh
36° 50′
58° 28′
1650
1987-2006
64-962
Kalateh Monar
Kalateh Monar
35° 56′
60° 14′
990
1986-2006
For the purpose of performing the present research, firstly the data of precipitation and seasonal and
annual flow rate of each station at different years from old times to the new were sequenced and then
by using rank-based nonparametric Mann–Kendall test , the trend existence in the flow rate and
precipitation data of each stations were evaluated separately and the obtained results were drawn as a
graph. Also, Sen Test was used for magnitude of trend. For better indication and general assessment of
the area, the obtained results in GIS environment for precipitation and annual and seasonal flow rate
were presented in the form of map. In the following, the relation of Mann–Kendall test and Sen Test
is described.
Mann-Kendall test
This test that was proposed by Mann (1945) and then extended by Kendall (1975) is considered as the
most frequent nonparametric methods of analysis of time series trend. Use of this method is
recommended for two reasons: (1) it is applicable for various types of abnormal, incomplete and
seasonal data (2) it has the highest capability for data analysis. Also this test in comparing with the
Analysis of Rainfall and Discharge Trend in Kashafrood Watershed
23
other trend tests is more suitable for determining the trend of hydrologic time series. The process for
calculation of this test statistics would be as the following:
a) Calculating the difference between each observes with each other and using sign function and
extraction of S parameter which is obtained from relation (1) :
n1
S 
 sgn x
n
k 1 j k 1
j
 xk 
(1)
In which , n is the number of observes and ‫و‬xj and xk are jth and kth series respectively. The sign
function is calculated by relation (2) :
 1 if

sgn x j  xk    0 if
 1 if

( x j  xk )  0
( x j  xk )  0
( x j  xk )  0
(2)
b) variance is calculated from the following relation:


n(n  1)( 2n  5)   t (t  1)( 2t  5)
t

Var ( s)  
18
Var ( s ) 
n(n  1)( 2n  5)
18
If
n>10
(3)
If
n<10
(4)
Where n is the number of observed data, m is the number of series with at least one repeating data, and
ti is the data with similar value. In cases where the sample size n >10, the standard normal variable Z is
computed using Eq. (5):
 S 1
 Var s 

Z  0
 S 1

 Var s 
if S  0
if S  0
(5)
if S  0
In a bilateral test, for finding the trend of data series, the assumption of zero is accepted where the
following relation is used:
Z  Z
(6)
2
In which α is a meaningful level which is considered for the test and Z is a standad normal deviate at a
meaningful level, which due to the two slope of the test, α/2has been used.
Geography and Development, 10nd Year, No.29, Winter 2013
24
In this research, Mann–Kendall test has been implemented for 95% and 99% of confidence, which Z
α/2 is equal to 1.96 and 2.65 respectively. The presence of a trend is accepted if Z is statistically
significant if Z<-Zα/2 or Z>Zα/2. Positive values of Z indicate increasing trends, while negative values
of Z indicate decreasing trends.
In addition to identifying whether a trend exists, the magnitude of a trend was also estimated by a slope
estimator β, which was extended by Hirsch et al. (1982) from that proposed by Sen (1968), defined as
  Median (
xi  x j
j i
)
where 1  i  j  n
(5)
In other words, the slope estimator β is the median over all possible combinations of pairs for the whole
data set. A positive value of β indicates an ‘upward trend’ (increasing values with time), while a
negative value of β indicates a ‘downward trend’.
Discussion and Results
There is a decreasing trend of discharge and precipitation in Dolatabad station. The decreasing trend of
discharge and precipitation in Dolatabad is due to the direct relationship between discharge and
precipitation. This decreasing trend cannot relate to situation of the station due to Golmakan, Zoshk and
Shandiz stations located in the nearest of the station having different trend in discharge and
precipitation. Thus, the precipitation shows increasing trend for all seasonal and annual series expect
spring season in Golmakan station. Also, the discharge shows increasing trend in autumn and summer
seasons. There are different decreasing and increasing trend of precipitation and discharge in Zoshk and
Shandiz stations. It may be due to other factors such as harvest and usage of rivers water and land use.
The Aghdarband station located on the main river, precipitation shows increasing trend in seasonal and
annual series. The increased precipitation of this station can be signs of climate change. While
discharge of this station shows decreasing trend in seasonal and annual series due to situation of the
station located on main river and outlet of watershed. Also, Placing of the station on the main river and
flat region and usage of water resources in agricultural and urban parts around Mashhad plain causing
decreasing trend of discharge in this station. This result is consistent with Xu et al.(2010) results.
The Klateh Monar, Kortian, Anderekh and Chakneholeya sub-watersheds shows increasing trend in
seasonal and annual discharge. The trend of precipitation is observed different in the stations. The trend
of precipitation in Klateh Monar station shows a decreasing trend in seasonal and annual data except
autumn season data. Also, in Kortian station is observed increasing trend in only winter season but two
stations namely Anderekh and Cheknoleya station are observed increasing and decreasing trend in
seasonal and annual data.
The trend of precipitation in Bande Saroj station was increasing trend in seasonal and annual data but
the trend of discharge was decreasing trend except autumn season. The Imamzadeh, Olange Asadi and
Zirbande Golestan stations were observed differentAnalysis
trend ofinRainfall
seasonal
and annual
precipitation
and
and Discharge
Trend in Kashafrood
Watershed
discharge data.
Conclusion
This study was carried out for detection of rainfall and discharge trends in Kashafrood watershed, one
of the low rainfall watersheds located in north-east of Iran, on 13 meteorological and hydrometry
25
stations with data from 1972 to 2006. In this study, Mann – Kendall test, non-parametric test, was used
for assessment of existence and nonexistence trend and also Sen Test was for magnitude of trend. The
results of rainfall and discharge analysis showed that rainfall increased in the most stations in autumn
as 9 stations have the increasing trend. While 10 out of 13 stations showed the decreasing trend in
spring. In summer and winter, the numbers of stations with increasing and decreasing trends are almost
equal. The annual trend analysis of rainfall and discharge showed that 5 stations had increasing trend
and 8 other stations had decreasing trend in rainfall data. But no stations had increasing trend in
discharge data. So that no trend was found for data in 2 stations and the rest had increasing trend. This
is probability due to increasing harvest and usage of rivers water. The usage of rivers water increased
with increasing population. Thus consulting dams and increasing agricultural land under cultivation
was tried for more water control and productivity by human.
Keywords: Trend, Discharge, Rainfall, Mann–Kendall test, Sen Test, Kashafrood Watershed.
References
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Britain. Geophysics Research Letter. 33, L 19406. doi:10.1029/2006GL027325.
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12. Hajam, Sohrab, Khoshkho, Younes and Shamsedinvandi, Reza (2008). Trend Analysis of seasonal
and annual Precipitations in some selected station in central watershed of Iran using nonparametric
methods, Geographical Research, 40 (64).
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the scaling hypothesis. Journal of Hydrology, 349.
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in the headstreams of the Zambezi River Basin in Zambia. Physics and Chemistry of the Earth, 33.
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Century (a case study: Jask station). Journal of the Faculty of Letters and Humanities, (36-37).
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precipitation in five old stations of Iran during the past 160 years. Desert Journal, 9 (1).
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(2009). Identification of hydrological trends in the presence of serial and cross correlations: A
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19. Masodian, Seyed Abolfazl(2005). Temperature trend analysis of Iran during the past 50 years,
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Sciences Discussions.
21. Meryanji, Zohreh, Marofi, Safar and Abbasi, Hamed (2008). Trend variations of discharge and
relationship with meteorological parameters in Yalfan watershed using nonparametric MannKendal method. The third conference on water resources management.
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Behrawan and Jie, Huang (2009). Relationship between temperature trend magnitude, elevation
and mean temperature in the Tibetan Plateau from homogenized surface stations and reanalysis
Analysis of Rainfall and Discharge Trend in Kashafrood Watershed
data. Global and Planetary Change.
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annual precipitation in arid and semi arid regions
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27
26. Xu, Zongxue, Liu, Zhaofei, Fu, Guobin, and Yaning, Chen (2010).Trends of major hydroclimatic
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Geography and Development, 10nd Year, No.29, Winter 2013
28
Geography and Development
10nd Year - No. 29 - Winter 2013
Received : 31/1/2012 Accepted : 17/7/2012
PP: 28 - 31
Ancient Modeling of Hydrology Based on Comparison of
δo18 Carbonate and the δo13 Crbonate Parishan Lake (Fars Province)
Dariush Noorollahi
Dr. Hassan Lashkari
M.Sc Climatology
Associate Profesor of Natural Geography
University of Shahid Beheshti
University of Shahid Beheshti
Maria Amirzade
Faculty of Earth science
University of Shahid Beheshti
Introduction
stable isotopes are strong tools for environmental studies, because most of the elements are naturally
more abundant at least in one isotope. Among the studies, many researchers have considered the
Carbon (C13/C12), Oxygen, (O18/O16) Hydrogen (H2/H) and Nitrogen (N29/N28) which remain effects on
the organic (plants and animals) and inorganic (water, soils, rocks, fossils,…) material (Griffiths, 1998,
p47). In order to study the Carbon and Oxygen stable isotopes of the lake carbonates, recognizing the
effective factors on the isotope's value and identifying the relationship between the isotope values is
essential. In the lake environments many factors can determine the variability of the Oxygen isotopes of
the lake sediments which the most important of them are including: source of materials, water
temperature, residence time and the input and output amount of the lake (Benson et al, 1996, p747). In
the open hydrological systems, the Oxygen isotope components of the lake water dominantly reflect the
isotopic components of precipitation (rain and snow) (Leng& Marshal, 2004, p817). In addition to the
effective factors on the isotopic amount of carbon and oxygen, the relationship between the carbon and
Oxygen isotopes in lake systems can deliver valuable information about the history of the lake's
hydrology. The relationship between the isotope values of carbon and oxygen isotopes in the closed
lakes can be based on the hydrological changes, evaporation, biomass production and the Co2
concentration (Le and Ku, 1997, p72). There are big hydrological closed lakes especially in the arid
regions, which both carbon and oxygen isotopic values are positively high. In these cases, it shows a
close value of correlation .the magnitude of the correlations can be used to estimate the closeness of the
lakes in different time periods. In the closed lakes, the covariance of carbon and oxygen isotope values
generally indicate the interaction of carbon and oxygen isotopes with the atmosphere (Tanner, 2009,
p210). In fact, the strong correlation between the carbon and oxygen isotope values indicates a common
29
Ancient Modeling of Hydrology Based on Comparison of …
effective mechanism on the lake dissolved inorganic carbon (DIC) (Eastwood et al, 2007, p239). In the
open lakes, there is a prefencally weak correlation between the carbon and oxygen isotope values. In
fact, generally, the the strong correlation between the carbon and oxyegen isotope values ocuurs in the
lake that have a long residence time. The correlation values more than 0.7 indicate the lake carbonates
deposited in a hydrological closed lake. Furthermore, in these cases, due to the high variability of the
lake water, the oxygen isotope values in the closed lake are approximately around 0.0 %. Therefore,
this covariance could be used to estimate the closeness of the lakes with the carbonates deposition
(Talbot, 1990, p273). Based on the methods mentioned above, a core was taken from Parishan lake in
Fars. The aim of this research is to reconstruct the hydrological condition of the lake in the past using
the Carbon and Oxygen stable isotopes of the Ostracoda microfossil.
Method and Materials
The carbon and oxygen isotope components were measured in Otava university, the Faculty of Science
(Earth Sciences) (G.G. Hatch Isotope Laboratories, 130 Louis Pasteur). Totally, 36 analyses of carbon
and oxygen isotope were made on 33 samples. The accuracy of measurement analyses has been
reported ± 0.1 per thousand. The isotope components of samples based on the well- known scale of δ
have been defined and reported as per thousand.
δsample (‰) = [(Rsample - Rstandard) /(Rstandard)]×1000
Where R refers to the accumulative ratios of the O18/O17 and C13/C12 in the samples and shows the
isotopic standard reference. In this research both of the carbon and oxygen stable isotopes are reported
based on the vpdb standards. Also the below equation is suggested in order to convert this standard into
the vsmow standard.
VPDB-VSMOW d18Ovsmow = 1.0309d18Ovpdb + 30.92
VSMOW-VPDB d18Ovpdb = 0.97001d18Ovsmow -29.99
Discussion
According to the variation of the isotope values of the carbon and oxygen elements, three below zones
were defined in order to survey the environmental changes separately.
Zone 1: (900 to 1800 BP)
When water evaporates from surface of Parishan lake, watervapor is enriched by H and 16O, because
H216O has a higher watervapor in comparing with HDO and H218O (Hoefs ,2004). So the increase of
evaporation enriches the lake water and consequently the carbonate of H218O.
The δO18 values are relatively low in this zone. This indicates that evaporation had not a significant
effect on the H216Olake water. As a result, Parishan Lake experienced a wet condition during this time.
Furthermore, the weak correlation between the carbon and oxygen stable isotope values indicates that
the lake was hydrologically open and was fed by the underground water during this zone. The existence
of gypsum crystal only in this zone can show a higher fed of under ground water in to the lake.
Consequently, the P+G=E is the suggested hydrological equation for this zone.
Zone 2: (200 to 900 BP)
Geography and Development, 10nd Year, No.29, Winter 2013
30
The carbon isotopes values in this zone are relatively higher than the previous zone. Increasing the
carbon isotope values could be a result of decreasing the underground water discharge into the lake.
The higher O18 suggests a drier climatic condition. In fact, the higher O18 during this zone caused by
removing the O17 by evaporation. The weak correlation between the carbon and oxygen isotope values
suggests an open condition of Parishan Lake in this zone. Consequently, the lake level was relatively
high in this zone. However, the higher oxygen isotope values and the weaker correlation indicates that
the lake level was lower than the previous period.
Zone 3: (Two recent centuries)
There is an abrupt and significant change in the C13 values in this zone. The carbon isotopes values
exceeds 0 in this zone. The strongest correlation between the carbon and oxygen isotope values is
observed in this zone. Totally, the isotopic analysis in this zone shows that 1: the increase of carbon
isotopes indicates the decrease of underground water discharge considerably in this zone. 2: the strong
correlation of carbon and oxygen isotope values suggests that the lake experienced a closed condition
in this zone, evaporation is a common effective factor which controls the variations of both carbon and
oxygen isotope values. 3: the anthropogenic effect is an additional factor that controls the significant
change of the lake hydrology. 4: the P=E equation is suggested for this zone and the current
hydrological condition also indicates that evaporation and precipitation are the main effective factors
on the lake hydrology.
Conclusion
The gradual increasing of the O18 values indicates a weak dry trend during the study period. Also the
investigation of the isotope carbon show that the underground water recharges variation controlled the
carbon stable isotope values. The carbon isotope changes are caused by the underground water
discharge variation during different time periods. The results show that the hydrological equation of the
Parishan Lake has changed during the time period as this lake experienced an open condition in the
past. However, at the present, as a result of the human impact, the lakes become a closed lake where the
evaporation and precipitation are the main effective factor that controls the hydrology of the lake. In the
final part of the study term (zone 3) the abrupt change of the O18 suggests the impacts of the human on
the lake's environment.
Keywords: Palaeohydrology, Stable carbon and oxygen isotopes, Parishan Lake.
References
1. Aghanabati, Seyed Ali (2004). Geology of Iran, industry and mining boreua. The gology and
mining organization of Iran.
2. The water management organization (2009).
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organization of Iran.
4. Massodian, Abolfazl (2003). Recognizing the percipitation patterns using the cluster analysis.
Geography researches. No 52.
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Ancient Modeling of Hydrology Based on Comparison of …
5. Andrews, J. E, Riding, R., Dennis, P. E (1997). The stable isotope record of environmental and
climatic signals in modern terrestrial microbial carbonates from Europe. Palaeogeography,
Palaeoclimatology, Palaeoecology. 129.
6. Eastwood J.Warran, Melanie J.Leng, Neil .Robert and Basil Davis (2007). Holocene climate
change in the eastern Mediterranean region; a compartion of satble isotope and pollen data from
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7. Editorial (2008). Lake system; sedimentary archives of climate change and tecnics.
Palaeogeography, Palaeoclimatology, Palaeoecology 259.
8. Fan,Majie. David L. Dettman, Chunhui Song,Xiaomin Fang , Carmala N. Garzione (2007).
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isotope record. Palaeogeography,Palaeoclimatology,Palaeoecology 247.
9. Gates, David Murray (1993). Cliamte change and its biological consequences. Sunderland, Mass;
Sinauer Associates 551 .6973.G259C.
10. Griffiths, H (1998). Stable Isotopes; integration of biological, ecological and geochemical
processes. oxford; Bios Scientific Publishers, 551.9 G855S.
11. Hoefs, Jochen (2004). Stable isotopes Geochimistery. Berlin; Springer. 551.9H693S.
12. Jones, Matthew. Palaeoclimatic research within the Mamasani Archaeological Project.
Unpublished data.
13. L.V. Benson, J.W. Burdett, M. Kashgarian, S.P. Lund,F.M. Philips, R.O. Rye (1996). Climatic
and hydrological oscillations in the Ownes Lake Basin, and adjacent Sierra Nevada,California,
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14. Leng.J .Melanie, and Jim D.Marshal (2004). Palaeoclimate interpretion of stable isotope data
from lake sediment archives.Quaternary Science Reviews 23.
15. Li.H.c and Ku T.L (1997). δO18 - δ C13 covariance as a palaeohydrogical indicator for closedbasin lakes. Palaeogeography,Palaeoclimatology,Palaeoecology, Volume 133, issues 1-2.
16. Stable Isotopes and mineral resource investigation and palaoclimateic interpretion
17. Talbot, M.R (1990). A review of the palaeohydrologocal interpretation of carbon and oxygen
isotopic ratios in primiary lucustraine carbonates. chemical geology; Isotope geosciences section,
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Developing in sedimentology, Volume 62.
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conditions of Qinghai^Xizhang Plateau (Tibet) based on carbon and oxygen stable isotopes of
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Geography and Development, 10nd Year, No.29, Winter 2013
32
Geography and Development
10nd Year - No. 29 - Winter 2013
Received : 9/4/2011 Accepted : 17/7/2012
PP : 32 - 36
Recreational Evaluation by Analytical Hierarchy Process (AHP)
and Geographical Information System (GIS)
Case: Forest Park of Martyr Zare, Mazandaran
Dr. Hamid Jalilvand
Associate of Forestry
Sari Agricultural and Natural Resources
University
Omid Karami
Ph.D Student of Forestry
Sari Agricultural and Natural Resources
University
Annahita Shahnazary
MS.c of Forestry
Sari Agricultural and Natural Resources
University
Morteza Shabani
Ph. D Student of Urban Planning Geography
University of Tarbiat Modarres
Introduction
Tourism which today is one of the most successful industries in the world has an extensive approach in
ecotourism. Recreational planning in this type of tourism not only is considered as a tool for promoting
social and economic levels of local people, but also due to protective functions as an experienced
managerial strategy in the natural resources, provides the situation for dynamic protection. Green space
is one of the most important systems of the human life and is important not only for economic reasons
but also for environmental reasons as well. Urban Forest Park as a major green space has a positive
effect on the urban environmental characteristics and by response to the needs of recreational and
entertainment requirements can have an important effect on the urban structure and servicing.
Analytical Hierarchy Process (AHP) is one of the most important techniques of Multi Criteria Decision
Making (MCDM) that was introduced for allocation of scarce resources and planning requirements.
Also integrating GIS and AHP have many advantages for the localization and classification of human
facilities, different kinds of activities and environmental evaluations and it can be a good way for
determining the Suitable and unsuitable areas for the establishment of different types of activities in the
fields of agriculture, natural resources, environment, assessment of land capability, land evaluation
and… which have spatial dimensions.
Research Methodology
The study area is Forest Park of Martyr Zare with an area of over 70 ha in geographical position of 53˚
07ʹ 09ʺ up to 53˚ 07ʹ 57ʺ east longitudes and 36˚ 32ʹ 57ʺ up to 36˚ 32ʹ 34ʺ north latitudes. In this study,
Recreational Evaluation by Analytical Hierarchy Process (AHP)…
33
for evaluating the recreational capability of the under study park, the method of combining AHP and
GIS environment was used. For this purpose, firstly the vegetation layers, soil, topography, geology
and facilities of the study area were obtained from the Department of Natural Resources of Mazandaran
province. The layers were digitized in GIS environment and the necessary modifications were made on
them. Layers of slope, direction and landscape were obtained from topographic maps with 1:25000
scale with line spacing of 10 meter. The slope layers in 5 layers, direction in five classes and landscape
in five classes were classified. For classification of the tree coverage and facilities of the park, the
recreational demands in the park were evaluated and the most favorable coverage was identified using
tourist’s idea. Finally, weights of each layer was obtained for each of the layers with AHP and by
combining these weights with layers in GIS environment, the recreational capability map of the study
area was obtained. In continue, in order to evaluate the recreational demand, a questionnaire about the
characteristics of age and social and economical status of tourists and their demands from the park was
prepared. 500 questionnaires were distributed among tourists of the study area in different seasons and
different days of the week and their opinions and needs were investigated using Clawson method.
Discussion and Results
The results of evaluating recreational capability:
After preparation and classification of the slope layers, direction, landscape, geology, soil, tree cover
and density of facilities in the park by using preferential judgments of experts, weight of each layer and
rate of consistency of the made of judgments were calculated. Finally, maximum and minimum weights
were allocated to slope and geology layers respectively. After assigning weights to each of the layers,
layers were integrated in GIS environment. Finally, the potential recreational map for the study area
was obtained which the results of recreational capabilities showed that from the total area of the Park,
10.2% of the area has a recreational degree of 1 (excellent), 28.9% of grade 2(good) , 41.02% of grade
3 (medium) and 19.96% of grade 4(weak).
The results of evaluating recreational demand:
The results showed that 61 percent of demands for recreational users of the park were men and 66
percent were married. Also, in case of increasing the facilities, 62 percent of Tourists willing to pay
1000 up to 5000 toman for entry fee .
Conclusion
In order to evaluate the recreational demand of the study area, firstly the effective criteria and sub
criteria in this evaluation were identified. Then these criteria and sub-criteria were weighted which the
results showed that the slope layer has assigned maximum weight to itself. The slope element has a
great importance in measuring the recreation capability. The most important layer in recreational
evaluation process in this area from the view point of experts is the slope layer and slope plays an
important role in recreational capability. The best slope for recreation is placed at the layers lower than
15 % and in Dr. Makhdoom model, is the most important factor in determining the recreational
capability. In the study area, after the slope layer, the landscape, tree coverage, soil, slope direction and
geology layers were the most important in the evaluation process respectively. In this study, the tree
Geography and Development, 10nd Year, No.29, Winter 2013
34
coverage factor was used as an important factor in the evaluation of recreational capability. For this
purpose, the views of tourists were used for determining the suitability of the tree coverage, the tourists
who were more willing to engage in recreational activities and the vegetation map was classified on this
basis. The majority of the soils in the study area, although they are different in terms of depth, but are
of clay loam type. In the study area, there are four main directions and one flat class that will show that
the study area is appropriate for summer and winter recreation. After determining the weights, the final
map of recreational potential were prepared using GIS that according to the results, 10.2 % of the park
has a high quality for recreational capability. These areas are generally flat and have a slope between 0
- 5 % and the park facilities in these areas are more concentrated. Also 28.9 % of the park area has a
good recreational potential and 41.09 % has an average capability. But, since the facilities layer has a
high weight in the evaluation process, therefore it is possible to increase the recreational capability of
the park by increasing the facilities in the under study park.
In this study, for evaluating the capability of recreational Zare forest park, a combination of AHP and
GIS were used. AHP has the capability to use the expert’s knowledge in evaluation process.
Furthermore, it is flexible and it is possible to use any number of criteria and sub-criteria in it.
Since the forest park is established for people, therefore without being acquainted with their opinions,
we cannot plan for recreation. According to the results obtained from recreational demand assessment
in the study area, the facilities should be mainly for meeting the requirements of people especially the
young people. Also, given that most tourists have a bachelor's degree; Psychological needs of these
groups should be considered in future planning. Most tourists come to the park with own cars. Then, it
was trying to provide the facilities for tourists’ car parking with sufficient capacity. Also, given that
most tourists want to improve facilities at the park area, it is possible to attract more tourists by
increasing the park facilities. Results of evaluating the recreational demand showed that most tourists
come to the park from short distances and the number of non-native tourists in the park is much lower
than native tourists. The reason for this subject can be the lack of familiarity of non-native tourists and
lack of guides , signs and sufficient advertisements which has caused these regions and the likes and
their beauty not to be introduced properly.
Keywords: Recreation, Eco-tourism, AHP, GIS, Forest park.
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planning of forestry on state-owned lands in Finland. J. Multi-Criteria Dec. Anal, N. 10.
15. Kumari, S. Behera, M, D. and Tewari, H, R (2010). Identification of potential ecotourism sites in
West District, Sikkim using geospatial tools. Tropical Ecology, N. 51.
16. Laurance, W. Alonso, M. and Campbell, P (2005). Challenge for forest conservation in Gabon,
Central Africa. Futures, N. 38.
17. Makhdoom, M (2010). Fundamental of land use planning. 9th edition. Tehran University.
18. Malczewski, J (2004). GIS-based land-use suitability analysis: a critical overview. Journal of
Progress in Planning, N. 62.
19. Moreno-Jimenez, J.M (2005). A spreadsheet module for consistent consensus building in AHPgroup decision making. Group Decision and Negotiation, N. 14.
20. Rezvanfar, M. (2007).study of Potential of recreational park Chitgar use of GIS and RS technology.
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Mazandaran University.
21. Saaty, T, L (1980). The analytical hierarchy process, planning priority. Resource Allocation. RWS
Publication, USA.
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22. Shirvani, Z. (1388). Comparative evaluation of recreational forests of Neka-Zalemrood with AHP
and Gulz-Dimiril and Makhdoom methods. Thesis Submitted for the Degree of M.Sc. in Forestry,
Natural Resources department of Sari, Mazandaran University.
23. Takiehkhah, J (2008). Recreational potential Evaluation of Abidar Park using GIS. Thesis
Submitted for the Degree of M.Sc. in Forestry, Natural Resources department of Sari, Mazandaran
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37
Geography and Development
10nd Year - No. 29 - Winter 2013
Received : 20/7/2011 Accepted : 17/7/2012
PP : 37 - 39
Determination of Erosion Severity Using Fargas and BLM Models
Case : Bandre Drainage Basin
Mehdi Nojavan
Ph.D Student of Environmental Planning
University of Tehran
Dr. Aliasghar Mohammadi
Ph.D Graduated Watershed Management
University of Islamic Azad- Tehran
Dr. Vahid Gholami
Assistant Professor of Watershed Management
University of Gilan
Introduction
Erosion is a process in which soil particles separate from their main bed and move to the other place
with the help of a transferor operator where based on the type of transferor operator there will be
water, wind and glacier erosion (Refahi, 2000, p.3). Nowadays we rarely can find a region in the
ground that is not subjected to the erosion and destruction which the main reason is the population
growth and the excessive use of land (Ahmadi, 1999, p.195). Also it is considerable that erosion has
two important aspects which include the reduction of the land productivity power and the disturbance
of eroded materials (Ghadiri, 1993, p: 3-6). Therefore, the compensation of eroded soil for the nature,
especially in the arid regions that the condition is so inadequate for formation of soil, is so hard and
long process. So, the residents of these regions must be so careful in the preservation and prevention
of erosion, because erosion is naturally so intense in these regions and the possibility of soil forming is
so low (Kardovani, 1998, p.7). Thus the recognition of the sensitive regions to the erosion and
sedimentation in the various parts of a drainage basin is one of the most critical issues in the
prioritizing of the regions for executive works of soil preservation and watershed management.
Research Methodologies
1- Preparing the geological map of form with the scale of 1:100000) that is used in the models and the extraction
of basin boundary.
2- Preparing topography map of Sardasht form with the scale of 1:50000 that is used in the models
and preparing the map of water way network.
3- Preparing the aerial photographs with the scale of 1:40000 that is used for increasing the resolution of the
map of second part and water way network.
4- Fargas model: as it mentioned in the introduction, this method was presented by Fargas and et al in 1997.
Fargas model includes only two factors, the rock type erosive and drainage density in every rock unit. The steps
of implementation of this model are explained in the full paper.
Geography and Development, 10nd Year, No.29, Winter 2013
38
5- 1BLM model: this method was presented by the U.S Bureau of Land Management. BLM model includes
seven factors; the surface erosion, the litter cover, the rock cover on the surface, the affection of destruction on
the surface, the surface rill erosion, the affection of sedimentation due to the water flow and the amplification of
gully erosion. The steps of implementation of this model are explained in the full paper.
Conclusion
The identification of the different areas in drainage basin (as a natural planning unit) for occurring the
erosion and its severity has been always one of the most important purposes of the natural resources
experts. For achieving to this purpose some experimental models have been presented that some of
them have high efficiency and others have weaknesses. Fargas and BLM models are used in this
research and they are run in Bandre drainage basin in Piranshahr town, West Azerbaijan province with
2840.1 hectares area. Fargas model includes only two factors, the rock type erosive and drainage
density in every rock unit, Whereas BLM model includes seven factors; the surface erosion, the litter
cover, the rock cover on the surface, the affection of destruction on the surface, the surface rill erosion,
the affection of sedimentation due to the water flow and the amplification of gully erosion. The
objective of this paper is the handling of these two models in the study area. The results of two models
showed that there are two classes of low and moderate erosion in the basin, where in Fargas model
9.72% area of the basin has low erosion and 90.27% has moderate erosion and in BLM model 50.63%
area of the basin has low erosion and 49.36% has moderate erosion, therefore 19.206% of the area has
a low erosion and 54.64% of the area has moderate erosion, also 73.85% of the study area in Fargas
and BLM models has concurrence in the erosion severity.
Keywords : Bandare basin, Model, Severity of erosion, Gully erosion, BLM, Fargas.
Reference
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Tehran Publications, Third Edition.
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and Sediment in Sub-basin B2 of Isfahan’s Zayanderoud Dam Drainage Basin using
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Faculty of Natural Resources, University of Tehran,
Tehran,
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Determination
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1 -Bureau of Land management
39
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Geography and Development, 10nd Year, No.29, Winter 2013
40
Geography and Development
10nd Year - No. 29 - Winter 2013
Received : 27/10/2011 Accepted : 17/7/2012
PP : 40 - 43
Synoptic Analysis of July 2010 Russian Fires and Pakistan Floods
Dr. Ghasem Azizi
Dr.Aliakbar Shamsipour
Associate Profesor of Climatology
Assistant Professor of Climatology
University of Tehran
University of Tehran
Morteza Miri
Ph.D Student of Climatology
University of Tehran
Introduction
Abnormality due to the heat flow of summer2010 impacted on most of Northern Hemisphere including:
Russia, Kazakhstan, Iran, Mongolia, China and some parts of European continent. Heat flow and
consequently increasing the temperature in Russia began on late June ,with the beginning of summer
season, the temperature increase was more severe, and has caused devastating effects such as forest
fires of Russia from 31 July around Moscow town. Further, at the same month from 24 of July, upon
heavy rains and increasing the water level at Sind basin, the provinces of Baluchistan, Sind, Punjab and
Kheibar in Pakistan were flooded. So that, about one fifth of the whole of Pakistan was flooded. Based
on the reports published by Pakistan state, the life of about 20,000,000 people was affected by the
flood.
According to the reports, the total number of people injured in this flood is more than the three events
of 2004 Indian Ocean tsunami disaster, 2005 Kashmir earthquake and 2010 Haiti earthquake. Damage
to the buildings was estimated about US$4 billion, and wheat crop damages were estimated to be about
US$500 million. World Meteorological Organization considers the global warming as the main reason
for climatic changes and its consequences, such as droughts, floods, fires and heat flows.
Research Methodology
Unprecedented heat of summer months of 2010 in Russia has caused large and extensive fires in the
forests of Moscow West suburbs, at the same time, torrential precipitation occurred in Pakistan. Its
causes were analyzed by using the data of Russia meteorological stations (Moscow),(Rostov on Don),
(Volgograd) and (Kazan),and Pakistan(Risalpur), (Peshawar), (Murree),and synoptic maps of the
ground surface levels of,850,500,250hpa. In this study, the elements of temperature, wind direction and
speed, air pressure and geo-potential height at different levels in Russia and Pakistan were studied.
Synoptic Analysis of July 2010 Russian Fires and Pakistan Floods
41
Discussion and Results
Pakistan and Russia are located in different latitudes and climatic conditions, So that their effective and
controller climatic systems are quite different. Pakistan is located in lower latitudes and adjacent to
torrid area. Its eastern parts are located on Indian plateau and its west and northern part is located on
Iran plateau and Eurasia.
It has relatively mild winters and warm summers. Its Northern areas have temperate climates, and
southern parts influenced by Southern tropical and Southeast Asia monsoon systems. Central areas
have hot summers which their temperature reaches to over 45 C° and Cold winters which the
temperature reaches to freezing point.
Russia, with more than 17 million square kilometers of area, is the largest country in the world. It is
located at high geographical latitudes and most of the country is cold with low precipitation. Therefore
most of the areas of the country (especially the grand country Siberia) are empty and Agriculture is
impossible. Effective atmospheric systems includes low and high pressures temperate latitudes and
adjacent to polar area. Its temperature conditions is known with low and cold temperatures.
Although the climatic conditions of each region is under the influenced of several factors and is
different from its surrounding areas, but some climate phenomena can operate on a larger scale and in
different regions have a common origin. In this study, with regard to the simultaneous occurrence of
two climatic phenomenon of severe floods in Pakistan and fires in forests in the west of Russia, it is
tried to identify and analyze the synoptic relationship between the two events.
Based on time analysis, temperature changes at four considered stations as the West representative
stations of Russia's were studied, The annual mean of maximum temperature for June, July, August
and September were extracted and calculated from daily data and the required graphs were plotted.
Since the fires were started in Russia on late July, the data related to one month prior to the
occurrences of this phenomenon were studied. The review of average annual and temperature anomaly
of temperature data, the increase of temperature in 2010 is obvious. Based on the calculations, in the
study period, temperature increase can be observed in most regions of Russia and Pakistan.
Also the review of rainfall data of Pakistan stations in late July showed an increasing trend, So that
during three days(27 to 30 July), 400 mm of precipitation is recorded in Sialkot station. While this
volume of rainfall occurs on average during 4 months each year .According to analytical maps of
different elements of atmospheric analysis at the ground level and upper levels, a low-pressure Centre
with 998 hpa central pressure in Pakistan and a high pressure centre with central pressure 1017hpa on
the ground surface in Russian has affected on the atmospheric conditions of these areas. Maps of
high levels of atmosphere show the presence of blocking system during July. . According to the
calculations, the intensity of blocking system was weak (0.76) during the first week of July, but in the
next three weeks of July has had a moderate intensity from minimum 2.1 up to maximum 2.85.
Conclusion
Based on the obtained results, it was cleared that location of Blocking system in the upper levels of
atmosphere, on one hand caused by the currents emitted from northern latitudes to warm down areas of
Geography and Development, 10nd Year, No.29, Winter 2013
42
Russia and the rotation system causing long lasting accumulation of warm and dry air system in the
West with sunny and smooth sky which leads to drastic increase of temperature and widespread fires
of late July in Russia. Also moving subtropical high pressure system to high latitudes, causing thermal
low pressures on Arabian Sea and Persian Gulf. These systems by changing direction and moving
toward the North East of its original position, it is extended up to Pakistan. So in contacting with cold
air masses which extended under the affection of Blocking system from high latitudes, is strengthened
and created the torrential precipitation of Pakistan. Therefore, both of the discussed phenomenon are in
relation with each other due to the existing models of atmospheric systems and in particular the
occurred blocking phenomenon at high latitudes and show the climatic regional anomalies .
Keywords: Flood, Fire, Tmperature and precipitation anomalies, Blocking, Russia and Pakistan.
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