Environmental

Communication

Biosci. Biotech. Res. Comm. 10(1): 78-82 (2017)

Estimates of vegetation and changes in rainfall and

runoff in the catchment area: A case study of Latian

watershed

Mohammad Mirzai, Alireza Nazari Alavi and Aliakbar Sajadi

Water & Energy Institute, Sharif University of Technology, Tehran, Iran

ABSTRACT

The vegetation of the land, including ecological factors in the erosion and sediment in the watershed dams and rivers

is. In this study, to determine the vegetation index within a speci ed period and on the part of the catchment area

of the dam Latyan, as an important source of drinking water in Tehran, The change in comparison with the annual

river discharge and rainfall were compared. Estimates of vegetation index NDVI in the basin during the years 2001

to 2013 show Roodak Station, between 2003 and 2005, the highest value and the lowest is 2008. The annual rainfall

during those years show that the highest amount of rainfall was in 2003 and the lowest occurred in 2008. Curve

shows, vegetation index largely follows changes in annual rainfall.

KEY WORDS: VEGETATION INDEX, NDVI, REMOTE SENSING, LATYAN DAM, TEHRAN

ARTICLE INFORMATION:

*Corresponding Author: alavi@sharif.edu

Received 12

Jan, 2017

Accepted after revision 21

March, 2017

BBRC Print ISSN: 0974-6455

Online ISSN: 2321-4007 CODEN: USA BBRCBA

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Online Contents Available at: http//www.bbrc.in/

INTRODUCTION

Rivers, has long been needed and have paid attention.

Therefore, human societies and industrial and agricul-

tural centers, etc., to exploit water resources, usually

near the rivers have been set up.

With the passage of time and development of centers

of communities and an increase in abnormal manipu-

lation of water sources and causes of climate change,

changes in water quality conditions of the river. Measur-

ing and analyzing qualitative data streams compared to

the trend of in uencing factors of quality, which makes

it possible to adopt appropriate management practices

to gradually reduce river pollution. The vegetation of

the land, including ecological factors in the erosion and

sedimentation in the upper watershed of the River dams.

The study area in the study of Rivers watershed is in

Roodak Station. The river forming Latian Reservoir, as

an important source of water Tehran. Roodak station

has a watershed of 403 square kilometers, the longitude

Mirzaeia, Nazari Alavia and sajadiia

and latitude and at an altitude of 1700 meters above

sea level. Figure 1 shows the location of the area of the

basin slope and shape 2.

The average river water, 230 million cubic meters

per year (Tehran Regional Water Company 2015). Lat-

yan dam’s catchment area, has a special geographi-

cal location and climate. Studies have shown that this

area because of the proximity to Tehran, have led to

remarkable changes in population and development of

residential complexes (Mirzaei et al. 2004). Studies have

also shown that due to the high basin slope, soil type

and lack of vegetation, erosion rate is high, (Mirzaei

et al. 2010). The results of erosion modelling in the region

show that if land use changes and increased vegetation

in this area, reduced erosion rates, and sediments carried

by the river are also reduced, with water quality index

being in the middle range (Mirzaei et al. 2014).

Quantitative modeling of water erosion in the water-

shed Latian (Maleki et al. 2011 ) and Modeling erosion in

the catchment areas in the region Amameh (Pour Abdul-

lah et al. 2012), Among the various studies conducted

in the region in this regard. As well as examining the

changes in watershed land users Karkhe the quality of the

river (Salajegheh et al. 2012). Of remote sensing in vari-

ous studies such as environmental studies climate and

vegetation changes, is used. Analysis of urban ecology

plant (using - NDVI derived from satellite imagery) Case

Study: Metropolis Ahvaz (Moradi 2016) and The ef -

ciency of NDVI data to estimate the vegetation(Farahnak

et al. 2015)and have reviewed changes to green space

in Shiraz using GIS & RS. During the years 1977-2015,

Jamali (2015) has studied using satellite images to deter-

mine the vegetation index.

Study autumn NDVI contributes more and more to

vegetation improvement in the growing season across

the Tibetan Plateau (Du et al. 2017) and vegetation

response to intensive commercial horticulture and envi-

ronmental changes within watersheds in central high-

FIGURE 1. Watershed of Latian Dam and Roodak station

FIGURE 2. Classi cation slope, catchment area Jajrood River

BIOSCIENCE BIOTECHNOLOGY RESEARCH COMMUNICATIONS ESTIMATES OF VEGETATION AND CHANGES IN RAINFALL AND RUNOFF 79

Mirzaeia, Nazari Alavia and sajadiia

FIGURE 3. NDVI values during the years

2001-2013

lands, Kenya, using NDVI data (Muriithi et al. 2016) and

seasonal vegetation response to climate change in the

Northern Hemisphere (1982–2013) (Kong et al. 2017).

Determination and monitoring rangeland condition

classes with MODIS NDVI and EVI indices in Iranian

arid and semi-arid lands (Jafari et al. 2017) and correla-

tion analysis between vegetation coverage and climate

drought conditions in North China during 2001–2013

(Gong et al. 2017). Consistency of vegetation index sea-

sonality across the Amazon rainforest (Maeda et al. 2016)

and vegetation response to rainfall seasonality and inter

annual variability in tropical dry forests (Souza et al.

2016) and assessment of regional vegetation response

to climate anomalies: For Australia using GIMMS NDVI

time series between 1982 and 2006 .

Recently, De Keersmaecker et al. (2017) have stud-

ied this  eld. For impact assessment of watershed man-

agement programmes on land use/land cover dynam-

ics using remote sensing and GIS (Thakkar et al. 2017)

and vegetation greenness modelling in response to inter

annual precipitation and temperature changes have

been analyzed between 2001 and 2012 in Liao River

Basin in Jilin Province, China by Lin et al. (2016) where

this method has been used. The present study was car-

ried out to determine the vegetation index in the area

within a speci ed period, the change in comparison

with the annual river discharge and rainfall have been

investigated. In this study, we estimate the vegetation

using remote sensing (satellite imagery) and its existing

data.

MATERIALS AND METHODS

In this study, to estimate vegetation, NDVI (Normalized

Difference Vegetation Index) values in late August and

early September, according to Smith et al studies (Smith

2000)have been used. Index NDVI (Normalized Differ-

ence Vegetation Index) or normalized difference vegeta-

tion index ratios between the bands 1 and 2 are calcu-

lated. NDVI maps on vegetation density that limit the

use of bands of red (R) and near infrared range (NIR) is

extracted. The NDVI prepared using the TERRA satellite

images, the following equation was used.

In which the near-infrared range B2 and B1 band is the

red band. The index showed a good correlation with leaf

density, but on three factors height and angle of the sun,

earth and atmospheric effects is critical. The amount of

re ection at different wavelengths depending on the

(1-2)

type of vegetation cover (species, tissue, plant health,

etc.) and the type of surface soil (organic matter, moist

soil, texture, etc.) can be adjusted. During these studies,

how changes in vegetation cover in the basin during the

years 2001 to 2013 using the MODIS sensor images with

a pixel size of 250 m was investigated. Time series and

combinations (Composite) NDVI data types have many

applications. Including their types can be combined in

a 10-day, 16-day and monthly NDVI index mentioned.

Combined time series analysis of the different indica-

tors over time was associated with greater ease and does

not lead to problems such as cloudiness (Iranian Space

Agency 2015). The 16-day composite of MODIS images

were used. The images Ascii format available for years

at Exel extracted and examined.

QUANTITATIVE DATA

Roodak Station, is gauging stations of Rivers. In this

study, the mean values measured  ow rate in this station

by Tehran Regional Water Company and the amount of

annual precipitation were recorded in it.

RESULTS

Figure 3 shows the changes covered in this period. The

results show that, Index NDVI in 2003 and 2005 had the

highest value and the lowest is 2008. Figure 4 shows the

changes in annual precipitation during these years. The

greatest amount of precipitation in 2003 and the lowest

occurred in 2008

By comparing Figures 3 and 4 can be seen, a lot of

vegetation index follows changes in annual rainfall.

Figure 5 shows the average annual  ow changes to

a height of rainfall and the sixth annual average  ow

rate during the same year in Roodak stations show that

is almost linear.

NDVI







80 ESTIMATES OF VEGETATION AND CHANGES IN RAINFALL AND RUNOFF BIOSCIENCE BIOTECHNOLOGY RESEARCH COMMUNICATIONS

Mirzaeia, Nazari Alavia and sajadiia

CONCLUSION

Since NDVI values calculated for the month of August

and September, it can be concluded that the area under

cultivation and summer planting vegetation obtained is

more representative the results show that annual pre-

cipitation has increased in the high water and river

 ow increases, the amount of vegetation cover index

also increased. Considering the results of erosion in

the catchment can be concluded that Drought and low

water, the causes of erosion and sediment and nutrients

are in the river. Relatively high slope moss has increased

catchment erosion potential.

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FIGURE 4. The height of the annual rainfall

during the 2001 to 2013

FIGURE 6. Average annual discharge of

Rivers

FIGURE 5. Average Annual discharge - annual Rain-

fall at the station Roodak

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82 ESTIMATES OF VEGETATION AND CHANGES IN RAINFALL AND RUNOFF BIOSCIENCE BIOTECHNOLOGY RESEARCH COMMUNICATIONS