Study of Lake Urmia (Urmiye) Level Fluctuations

8/8/2019 Study of Lake Urmia (Urmiye) Level Fluctuations

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Study of Lake Urmia Level Fluctuations and Predict Probable Changes Using

Multi-Temporal Satellite Images and Ground Truth Data Period (1976-2010)

New Challenge about Climate Change or Human Impact

http://tinyurl.com/36rnpah

http://tinyurl.com/2vtw3rj

Mohsen Ahadnejad Reveshty

Assistance Professor, Dept. of Geography, Zanjan University, Iran

[email protected]

Yoshihisa Maruyama

Associated Professor, Chiba University, Japan

[email protected]





fluctuations occurred at this stage, Markov chain and cellular automata methods were used .Based

on

results probable survival value for the lake in next ten years has been estimated about 64 percent .Also

for

evaluation of role each of the natural factors, including climate change and human impact as

major

challenges discussed in this paper was investigated.

Key word : Urmia Lake, Fluctuations, GIS, Satellite imagery, Markov Chain

Introduction

Features and phenomena in the Earth's surface were changed due to over time, the lakes as

one of these phenomena and due to having a closed environment is not exception and due to

climatic changes such as reduced rainfall and increased temperature and uncontrolled use

of surface water resources in watershed areas in agriculture, industrial and drinking ever level

they are exposed to change .Supervision and monitoring changes in these lakes should be

considered as important in the national and regional development and natural resource

management .Currently monitoring the coastal areas and extraction of water level changes at

different intervals is an infrastructure research of interest because the coastal zone management

and dynamic nature of such sensitive ecological environments need to accurate information

about the various intervals(Rasoli,2007). Among the remote sensing data are considered as

useful tools for the continuously monitoring and sequentially compared with traditional methods .

With regard to temporal resolution from half days to one month, and spatial resolution of less

than one meter to several kilometers and multi-spectral resolution of this data and applying

mathematical and statistical methods to detection of changes, the satellite image has become as a

valuable resource for earth sciences specialist for studying earth surface and its changing

(Ahadnejad, 2010)

In the field of application satellite images to monitoring of lakes and lagoon surface



changes much research that is most important, they note :

Ahadnejad et al(2010), in paper entitled “Detecting and Environmental Assessment

of Spatial Changes of Hamun-E-Saberi Lagoon Using Satellite Imagery and GIS studied these

lagoon in the period of 1976-2008 using LANDSAT and MODIS satellite images and analyzes

them with utilizing the Normalized Difference Water Index (NDWI) during the August months,

to assess and evaluate its spatial variations .Al Sheikh et al (2007), in article entitled "coastline

change detection using remote sensing "study changes in coastline Urmia Lake during 1989,

1998 and 2001 and paid to utilizing Landsat satellite images and processing them Coastline

change detection is about Urmia Lake .Ma and Wan (2007),"change in area of Ebinur Lake

during the 1998-2005", they used indicators such as NDWI for detection of water level changes

in this lake .Rasoli et al (2007), in paper “monitoring of Urmia Lake Water level fluctuations

using multi-temporal satellite images processing .Qulin TAN et al (2004), in paper entitled "

measuring Lake water level using multi-source remote sensing combined with hydrological

statistical data for changing Poyang Lake in China and etc.

In this paper using multi-temporal satellite images such as MSS, TM, MODIS data and

using Normalized Difference Water Index (NDWI), firstly occurred changes detected in Urmia

Lake and then using data such as water level measured in ground stations and the amount of

rainfall and water input to the lake to the trend of modeling with integrated remote sensing data

and ground truth data and ultimately Urmia Lake drying reasons will be discussed in recent

years.

Study Area

Urmia Lake as the largest water body in Iranian plateau is located between two major

provinces of East Azerbaijan and west Azerbaijan .The lake is bounded between 37°5´ -38°16 ́

latitudes and 45°01´ -46° longitudes at 1275 m above sea level .Its surface area ranges from

4750 to 6100 km2 and the average and greatest depths account for 6 and 16 m, respectively

(Azari Takami, 1993) .More than 20 permanent and seasonal rivers as well as a few submarine



streams and springs feed the lake .Average salinity of the lake ranges between 220-300 mg/lit

depending upon temporal and spatial conditions, in recently years it arrived more than 380

mg/lit. Due to the ecological heritage of Urmia Lake it is recorded as a protected habitat in the

world by the United Nations.

Material and methods

-Material

The data used in this paper refer to August month that acquired from Landsat and Terra

satellite sensors data. Table and figure 1 shows characteristic of data used in this paper.

Table1 :The characteristic of data used in this paper

Also in this paper ground truth data such as daily water level data that measured in during

1976-2009 by east and west Azerbaijan water organizations in ground station at Sharaf khaneh

and Golmankhaneh ports .Statistics related to rainfall and water volume input to the lake are

other data that used in this paper .Table 2 shows summarized data used in this article.

Table 2 :The summarized ground truth data form Urmia Lake





Methods

Fig1: Satellite Image of Urmia Lake in during 1976-2009

-Image processing :

There are many methods for detecting of changes with using satellite images such as

subtraction images, and ratio and difference method, supervised classification, vector change

analysis (VCA), indices and normalized difference ...mentioned.

For detecting of occurred changes in this study satellite images of the area and available

resources, including U.S .Geological Survey were collected .After the initial corrections such as

geometric and radiometric correction changes detection of water level changes has been applied .



Since the separation of water bodies on satellite imagery is done carefully and high

accuracy in compared with other phenomena in the earth surface .In this paper for separation and

detection of water from other phenomena, normalized difference water index were used .In this

index by using near and middle infrared bands in the TM and ETM sensors, green and near

infrared bands in MSS sensor and middle infrared and short wave in MODIS sensor and

applying ratio and difference method water bodies has been separated from other phenomena's in

case study area .The equation number 1 to 3 show normalized difference water index for satellite

data are used in this paper.

Based on normalized difference water index images produced by this index value for water

levels towards desire to +1 value and for other surface without water towards desire -1 value.

Fig 2 shows images resulting from applying this index for Urmia Lake.

-Trend Analaysis

The other object of this paper is to predict the trend of land use changes in the future .Many

methods can be applied to predict the trend .In this paper, two methods are used. Fig3 shows

trend change map of Urmia Lake in during 1976-2009.

(1) Markov chain

The Markov chain method analyzes a pair of water classification images and outputs a

transition probability matrix, a transition area matrix, and a set of conditional probability images .

The transition probability matrix shows the probability that one class will change to the others .



The transition area matrix tells the number of pixels that are expected to change from one class

to the others over the specified period .

The conditional probability images illustrate the probability that each class type would be

found after a specific time passes. These images are calculated as projections from the two input

land cover images .The output conditional probability images can be used as direct input for

specification of the prior probabilities in Maximum Likelihood Classification of remotely sensed

imagery (such as with the MAXLIKE and BAYCLASS modules) .A raster group file is also

created listing all the conditional probability images .

In this study, a series of image processing was performed to predict the trend of Urmia

Lake change in 2019 .



Fig2 :Images resulted from NDWI reclassify for separated land from water (1976-2009)

(2) Combination of Cellular Automata and Markov Chain

To know the changes that have occurred in the past may help to predict future changes .

Combination of Cellular Automata and Markov Chain is often employed to predict Urmia Lake

change estimation .

In order to predict the trends of Lake Changes, first 1976 and 2009 Lake Map was

analyzed with Markov Chain .Then, combined method of Cellular Automata and Markov Chain

was used for forecasting land use change in 2019 .According to the results Urmia Lake areas

decrease from 3107.78 Km2 in 2009 to 2095.44 km2 in 2019. Fig4 shows predicted map

of Urmia Lake in 2019 .

The results of satellite images processing show that most changes occurred in the southern

and eastern part of lake that indicates the water depth is low in these areas compared with other

areas of the lake .The lowest lake retreat occurred in the north and northwest of lake. However

high the river water from flowing into the area to the lake but not much depth of water in these

areas has caused a retreat in this section are vertically regions and less in these regions compared

with southern parts of East coverts to salty land .

Notable in recent years especially in 2008 and 2009 connecting the Aspire and Ashk

islands in the middle part of Urmia Lake has caused this intensification and increasing areas of

salt in this area .The resulting map method based on Markov chain and the Cellular Automata

with the likely trend of the islands of the East Lake are connected to the land where the eastern

and southern areas of the lake completely dry and this can be associated irreparable

environmental effects.



Change trends analysis using ground truth data and image processing

Based on existing data in Table 2 can be realized that Urmia Lake long-term average

water level in the periods 1976-1998 about 1276.042 m above sea level, except in 1998 than the

long-term average of about 0.365 m high in the rest of the years. From 1999 to 2009 the lake

water level has fallen and garlic to the long-term average of about 4.898 meters has decreased.

Based on the predictions done based on time series method if this trend continues to be in the

lake water level in 2019 decreased to 1267 meters and this will mean that the level of the lake

with an average long-term reduction of about 9 m. Figure 5 shows graphs of Urmia Lake water

level trend.

Reducing the lake water level will be reduced lake area. Especially in the southern half and



eastern parts of the lake that available evidence shows to be shallow in these areas than the

northern half of the lake. According to the results obtained from satellite image processing in the

long term average lake area of about 5277 sq. km area is that from 1999 to 2009 had reduced the

garlic so the lake area in 2009 reached approximately 3107 sq. km with average long-term

reduction of about 2119 sq. km. Based on the analysis carried out using the Markov chains and

Cellular Automata analysis and time series until 2019 this trend with regard to the lake area

decreased by approximately 2000 square kilometers. Figure 4 shows predicted changes in 2019

and also figure 6 show trend graphs area of Urmia Lake also figure 7 shows comparison

between water level and area in Urmia Lake.



Fig7: The comparison plot between Water Level and Area (KM2)

The main Factors in reducing of Urmia Lake water level

Data of rainfall in Table 2 shows that the long-term average rainfall in the Basin of

Urmia Lake is about 281 mm. During 1998 to 2001 for three consecutive years the amount of

rainfall markedly decreased in the years 1998-1999 and reaches about 165 mm. this decreasing

in rainfall is starting point in Lake water level reductions. Because of concern that has caused

droughts in dams after this year will be built or existing dams will be save water. During after

2001 significantly on the amount of rainfall in Urmia Lake basin been increased and many

long-term average of these years has been even higher. Then with consider to statistics such as

rainfall, climate change has been not considered only factor in Urmia lake water level



reductions. But also uncontrolled use of water resources in the basin has led in recent years; the

lake water level was decline. Finally, we can say that the role of human factors and impacts

is more than natural factors in the destruction of lake.

The results of this paper shows that human effects and uncontrolled exploitation of water

resources has caused the water level of the Urmia Lake suffered a sharp drop during the last

decade so that this period approximately 5 meters reduced lake water and lake area of 5200

square kilometers in 1998 reduced to about 3107 square kilometers in 2009. According to

analysis conducted in this paper include the use of Markov Chains, Cellular Automata and time

series if this trend continues, lake area in 2019 will be reduced to about 2000 sq. km. The issue

that caused irreparable environmental effects of increased salt in the region, the loss of

agricultural lands adjacent to the lake of salt transport by the winds and thus cause large

economic losses will be happen in this region. on other hand reduce the water level increases the

amount of saturated salt water will face that the amount currently reached 380 mg/lit, causing

destruction of the only existing live Artemia in the lake that as food for migratory birds.

Also in this article the role and importance of remote sensing data and processing them

for purposes such as monitoring and continuous monitoring, even during the days, weeks or

months can be considered the traditional methods no such ability and speed to act and sometimes

due to natural and human problem is not possible quickly data collecting.

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Study of Lake Urmia (Urmiye) Level Fluctuations