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No: 86, 201336

Spatio-Temporal Trend Analysis of the Depth andSalinity of the Groundwater, Using GeostatisticsIntegrated with GIS, of the Menemen IrrigationSystem, Western Turkey

AbstractA rise in the level of the water table to the effective root zone results in decreasing yields because of salinityand sodicity, and eventually such areas cannot be cultivated. For sustainable irrigated agriculture, the salinityand level of the water table should be monitored continuously and held within tolerable limits.The aim of this study was to evaluate spatial and temporal changes in the salinity and level of the water tablein the command area of the Menemen Irrigation System for the years 1995-2006 using geostatisticalmethods integrated with GIS. The salinity and level of the water table in the study area were evaluated interms of both spatial and temporal variation.Trend analyses of these values were performed using the Mann-Kendall test. The non-parametric Sen’sSlope Estimator was used to calculate the magnitudes of the trends. A risk map of the study area was formedby performing geostatistical analyses by GIS, based on the intensity of the trend. It was observed that therewas no current problem with the depth and salinity of the groundwater in the study area in general, but thatthere would be a potential risk of a problem in the future.Keywords: Geostatistics, GIS, groundwater, Mann-Kendall, trend analysis.

Türkiye’nin Batısında Yer Alan Menemen Sulama Sisteminde CBS ile Entegre JeoistatistikKullanılarak Yeraltı Suyu Derinliği ve Tuzluluğunun Mekansal ve Zamansal Trend AnaliziÖzetSu tablasının etkili kök bölgesine yükselmesi, tuzluluk ve sodyumluluk nedeniyle, verimin azalmasına vesonuçta bu alanların tarım dışı kalmasına neden olmaktadır. Sürdürülebilir bir sulu tarım için su tablasınıntuzluluğu ve seviyesi sürekli izlenmeli ve kabul edilebilir sınırlar içerisinde tutulmalıdır.Bu çalışmanın amacı, CBS ile entegre jeoistatistiksel yöntemler kullanarak, 1995-2006 yılları içinMenemen Sulama Sisteminde, yeraltı suyunun tuzluluğu ve seviyesindeki mekansal ve zamansaldeğişimleri değerlendirmektir. Çalışma alanındaki yeraltı suyunun tuzluluğu ve seviyesi hem mekansal hemde zamansal değişim açısından değerlendirilmiştir.Bu değerlerin trend analizi Mann-Kendall testi kullanılarak gerçekleştirildi. Trendlerin büyüklüğünühesaplamak için non-parametrik Sen’s Slope Tahmincisi kullanıldı. Çalışma alanına ait risk haritası, trendinşiddetine göre, CBS ortamında gerçekleştirilen jeoistatistiksel analizlerle oluşturuldu. Genel olarak çalışmaalanında yeraltı suyu tuzluluğu ve derinliğinin mevcut durumda sorun olmadığı, ancak gelecekte potansiyelbir risk oluşturabileceği belirlendi.Anahtar Kelimeler: CBS, jeoistatistik, Mann-Kendall, trend analizi, yeraltı suyu.

Karatas BS, Camoglu G, Olgen MK (2013) Spatio-Temporal Trend Analysis of the Depth and Salinity ofthe Groundwater, Using Geostatistics Integrated with GIS, of the Menemen Irrigation System, WesternTurkey. Ekoloji 22 (86): 36-47.

Ekoloji 22, 86, 36-47 (2013)doi: 10.5053/ekoloji.2013.865

Received : 16.01.2011 / Accepted: 30.01.2013

Bekir Sıtkı KARATAS1*, Gokhan CAMOGLU2, Muhibullah Kirami OLGEN3

1Adnan Menderes University, Faculty of Agriculture, Department of Farm Structures andIrrigation 09100, Aydın- TURKEY2Canakkale Onsekiz Mart University, Faculty of Agriculture, Department of Farm Structuresand Irrigation 17020, Canakkale- TURKEY3Ege University, Department of Geography 35100, Izmir- TURKEY*Corresponding author: [email protected]

INTRODUCTIONManaging irrigation systems designed to develop

soil productivity and water resources and to prolongtheir durability not only entails providing the waterused in irrigation but also entails applying theirrigation methods and controlling the soil humidity

and salinity (Güngör and Erözel 1994). In the early and mid 20th century, the rapid

development of irrigation, often without properirrigation management or drainage, caused a rise inthe water table of irrigated areas, leading to wi-despread waterlogging and salinization (Smedema et

al. 2000). For soils, salinity may be an importantproblem. It disrupts the soil productivity andecological balance by affecting the physical,chemical, and biological properties of the soil(Kizildag et al. 2012).

Anthropogenic secondary salinization, caused byunsuitable soils and a lack of water management,generally occurs on irrigated agricultural land in aridand semi-arid regions (Kendirli et al. 2005). Salinityreduces agricultural production and agriculturalactivities, and in time may result in the terminationof agricultural activities and production (Kavurmacıet al. 2010).

Salinity problems encountered in irrigatedagriculture frequently occur with an uncontrolledwater table within 1-2 meters of the soil surface. Itmay not be possible to control problems ofincreasing salinity which occur in bad drainageconditions in arid or semi-arid climates unless thewater table is kept at a safe depth of at least 2 m. Inmost soils with a shallow water table, water risesinto the active root zone through capillarity, and ifthe water table contains salt, it becomes acontinuous source of salt to the root zone as water isused by the crop or evaporates at the soil surface.Salinization caused in this way can accelerate as timegoes on, especially in hot climates and clayey soilconditions. Therefore a shallow water table shouldbe continuously monitored and held withintolerable limits in order to control salinity and tomaintain successful sustainable irrigated agriculture(Ayers and Westcot 1994, Bilgili 2012).

In order to surmount these problems withgroundwater, it is crucial to know the depth andsalinity of the groundwater and their variation overtime, and to take the necessary measures in line withthe data obtained (Kara and Arslan 2004).

One of the most important factors negativelyaffecting crop yield is salinization in the root zone.The depth of a shallow saline water table cansignificantly increase salinity in the root zone. Adeep water table therefore reduces soil salinization(Ali et al. 2000). Information on the increasingpotential risks of soil salinization is of greatimportance for soil salinity management in irrigatedareas (Demir et al. 2009).

Studying the variations of the depth and salinitylevel of groundwater by means of classical statisticalmethods alone is not enough because the calculationof the variance and standard deviation concerning

any variable in classical statistics does not take intoaccount the effect of sampling locations. The spatialvariation model was developed as a solution to thisproblem and was defined by the concept ofgeostatistics (Gündoğdu 2004). Geostatistics is atechnique which, as well as saving a great deal oftime, money, and labor with the help of computertechnology, also enables terrain features to begeneralized by utilizing the relationships amongparameters (Warrick et al. 1986, Yates and Warrick1987, Ditzler 1994, Zhang et al. 1995).

Thanks to recent developments in GeographicInformation System (GIS) software, geostatisticalanalysis studies have been integrated with GIS. Thishas a large field of application includinggroundwater modeling and soil mapping (Burroughand McDonnell 1998). Geostatistics and GIS areused as successful tools for efficient planning andmanagement of groundwater resources (Machiwalet al. 2012). Groundwater quality analysis and GIS-based mapping are important components of agroundwater planning strategy (Adhikary et al.2011). Geostatistics which has been introduced as amanagement and decision tool by many researchershas been applied to reveal the spatial and temporalstructure of groundwater level fluctuation (Ahmadiand Sedghamiz 2007). Summaries of the literatureon some of these studies are given below:

Ahmadi and Sedghamiz (2007) carried out astudy on the Darab plain in the south-east of theFars province in the south of Iran using 12 years ofdata from 39 wells, analyzing the spatial andtemporal variations in groundwater levels bygeostatistical methods. Additionally Zhang et al.(2009) used groundwater data recorded over sixyears from 51 wells in an arid and semi-arid regionto examine the temporal and spatial variations ingroundwater depths by geostatistical methods.Results of their studies, which used both ordinaryand universal kriging methods, showed that the useof kriging was very effective in the estimation ofgroundwater trends. Also Triantafilis et al. (2004)used non-linear (indicator, multiple indicator, anddisjunctive) kriging methods to ascertain theoptimal method of showing the risk of salinizationin the lower Namoi Valley of New South Wales, inAustralia.

McGrath et al. (2004) studied the spatialdistribution and evaluated the danger of ground leadin the Silvermines mining area of Ireland by

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Spatio-Temporal Trend Analysis of the Depth and Salinity of the.. Eko lo ji

geostatistical methods integrated with GIS. Theymapped the ordinary point kriging of leadconcentration, kriging standard deviation, and thepotential for exceeding the threshold value ofground lead. The researchers showed that thismapping gave valuable data for risk evaluation anddecision support systems. Also Hamad (2009)carried out geostatistical analysis with GIS supporton groundwater levels in 95 wells in the south AlJabal al Akhdar area in the northeast of Libya. As thetransformation was required to drive the data intonormality, groundwater level data were firstexplored for normality using ESDA (ExploratorySpatial Data Analysis) tools. The geostatisticsordinary kriging method integrated with GIS wasused in the study for spatial interpolation. Inanother study by Adhikary at al. (2011), ordinarykriging geostatistical methods integrated with GISwere used in the thematic mapping of manygroundwater quality parameters including electricalconductivity (EC).

Cay and Uyan (2009) conducted a study inKonya, Turkey in 1999-2003, in which they useddata from 91 groundwater wells to evaluate thespatial and temporal variations of groundwaterlevels by the ordinary kriging geostatistical methodintegrated with GIS. Also Xiao-li and Ling (2009)analyzed the distribution of groundwater sourcesand the spatial heterogeneity of groundwater depthsin the Zhangye Oasis, located in the Heihe RiverBasin in China, by geostatistical methods integratedwith GIS. Jiazhong et al. (2011) examined the spatialheterogeneity of the depth of groundwater by amethod in which the geostatistical and spatialanalysis function of GIS were combined. It wasshown in the study that the depth of groundwatershowed significant spatial heterogeneity. In addition,Machiwal et al. (2012) conducted a study in a semi-arid hard rock aquifer in western India, whichshowed that geostatistics and GIS could be appliedto determine the temporal and spatial variations ingroundwater levels. They used monthly ground-water level data from 50 locations from May 2006 toJune 2009. The study showed that geostatisticsintegrated with GIS were a very reliable andpractical means for the sustainable management ofgroundwater sources. Additionally, Kambhammettuet al. (2011) used the universal kriging method forthe interpolation of the heights of the water tableobtained by measurements in random areas in the

Carlsbad area alluvial aquifer located in the south-east of New Mexico, USA. They made use of GISmeans to form the continuous surface of heights ofthe water table.

Bilgili (2012) took soil samples from 140 pointschosen at random to determine the spatial distribu-tion of areas affected by salinization on the HarranPlain in Turkey. Many soil salinity parameters wereanalyzed the soil salinity parameters in thesesamples, such as EC, soluble anions and cations, andexchangeable sodium and sodium percentage. Thestudy showed that there was a strong correlationbetween the EC and the other parameters. Thegeostatistical method integrated with the GIS ofmultiple kriging technics was used in determiningspatial variations in soil salinity. Also Alfy (2012)conducted a study in the El Arish area of NorthSinai, Egypt, to determine the effects of nutrientelements and trace metals on potential pollutionsources and groundwater sources. It was found thatthe water table was shallow (<4 m) especially in thenorth, and that its buffering capacity was weak andthe risk of pollution was very high.

Demir et al. (2009) conducted a study in whichthey evaluated the spatial and temporal variations ingroundwater salinity and depth by the indicatorkriging technique in northern Turkey. They useddata on groundwater salinity and depth measuredmonthly from 60 observation wells in an irrigatedarea of 8187 ha from the irrigation season (August2003) to the rainy season (April 2004). Results of thestudy showed that the greatest risk of landsalinization was areas affected by drainage problemscaused by a malfunctioning drainage infrastructure.It was found that the spatial distribution of theupper threshold for groundwater salinity and thelower threshold of groundwater depth in theirrigation season were very similar. The researchersevaluated this by showing that both parameters weregreatly affected by irrigation.

As seen from the summaries of the studies ofwhich are given above, many studies have beenconducted evaluating the depth and/or salinity ofgroundwater temporally and/or spatially usinggeostatistics and/or GIS. However, no studies werefound which used GIS and integrated geostatisticsin the spatial and temporal evaluation ofgroundwater depth and salinity depending on thetrend. In this way, our work represents an approachwhich is novel and different from all other studies in

Karatas et al.Ekolo ji

No: 86, 201338

term of the mapping of the groundwater level andthus salinization risks on the basis of irrigationsystems. The purpose of this study was to show thatin an evaluation of the risks of sustainableagriculture, account should be taken not only ofgroundwater depth or groundwater EC, but of thetwo together. In addition, it sets out the importanceof knowing not only the actual state of the risk levelsof these two parameters but also the size and thedirection of the trend of this risk. Along with this, inthis type of study it shows the necessity of separatelyassessing not only the risk map but maps of allparameters used in deriving this map wheninterpreting the results. Finally, it shows theusability and effectiveness of trend analysis andgeostatistical methods integrated with GIS whenobtaining all these results.

In this study, the trend analysis of the salinity anddepth of the groundwater lying under the commandarea of the Menemen irrigation system for the years1995-2006 was evaluated using the Mann-Kendalltest. The non-parametric Sen’s Slope Estimator wasused to calculate the magnitudes of the trends. Arisk map of the research area was created usinggeostatistical methods in the GIS environmentbased on the intensity of the trend.

MATERIAL AND METHODSMaterial The main material consisted of the depth and

salinity (EC) data of groundwater from 319 obser-vation wells, which were monitored by the GeneralDirectorate of the State Water Administration (DSI)between the years 1995 and 2006 in the MenemenIrrigation System (Anonymous 2007) (Fig. 1). Fromthis data, only the EC values measured in Augustwhen irrigation is at its highest level, and valuesfrom the month when the groundwater is at itslowest level since this is the month of greatest risk,were taken into consideration.

The irrigation system which constitutes theresearch area, and which serves 22865 hectares ofland at the end of the lower Gediz Basin, is locatedon the Menemen Plain, which lies at a latitude ofbetween 38º26' and 38º40' north and a longitude of26º40'-27º07' east (Anonymous 1971). The soils ofthe plain are largely medium to medium-heavytextured and generally light by the old bed of theGediz River, becoming progressively heavierwestwards of the same area (Anonymous 1973).

Soils located in the lower parts of the plain are

usually salty, and have poor or damaged drainage.Groundwater can rise to a depth of 50 cm in therainy season and in some places it can reach thesurface (Anonymous 1971). Drainage studies werecarried out in 1994 to combat these problems(Ertem 1994).

The Menemen Plain has a Mediterraneanclimate. It is uniform in terms of climate and has thetypical features of the Aegean Region in general. Anarid-humid mesothermal climate prevails with-inthe plain. Summers are hot and dry, and winters arewarm and rainy (Anonymous 1971). The averagetemperature between the years 1954 and 2000 was17°C and the average rainfall was 543.2 mm(Anonymous 2001).

Cotton and grapes are the dominant crops inaddition to maize, vegetables, and other fruit alsobeing grown (Anonymous 2000).

MethodsFirstly, the trends and the change rate of the

variables in the depth and EC values of thegroundwater were assessed for every groundwatermonitoring well. For this purpose the Mann-Kendall test was used. This test is a nonparametricstatistical test used to identify trends in time seriesdata (Mann 1945, Kendall 1975). The technique isappropriate for data exhibiting one or more of thefollowing characteristics: free distribution, missingvalues, outliers, and seasonality (Ribeiro andMacedo 1995).

As a result of the Mann-Kendall analysis, linearequations were obtained concerning the trends ofthe depth and EC values of the groundwater foreach well as given below (Equation 1).

Y= QX+B (1)where Q: The slope of the trend curve (cm/year or

μmhos/cm/year);

Fig. 1. Location of the Menemen irrigation system.


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B: Intercept value (cm or μmhos/cm);The non-parametric Sen’s Slope Estimator was

used to calculate the magnitudes of the trends.These tests were performed with use of the Exceltemplate MAKESENS (Mann-Kendall test for trendand Sen's slope estimates) developed by Salmi et al.(2002).

The Q value shows the trend slope, in otherwords, changes of a parameter in unit time (year),and the B value shows the value of the intersectionof the Y-axis of the starting point of the slope, inother words, the value of a parameter in a currentstate in the linear equation relating to groundwaterdepth and EC parameter trends.

In order to define the most appropriate interpo-lation method to represent the Q and B values inEquation 1, the ESDA tools in the GeostatisticalAnalyst module of ArcGIS 9.2 software were used.As a result of this, the most appropriate interpo-lation method was found to be ordinary kriging(Cay and Uyan 2009, Zhang et al. 2009, Hamad2009, Adhikary et al. 2011).

Maps for the Q and B values of the depth and theEC of the groundwater were obtained using thismethod. These maps were then converted to rasterformat to apply arithmetic operations. Mapsrasterized on a scale of 10x10 m were reclassified bygiving a value to each pixel of the maps. The value-assignation process was performed based on criticalvalues of Q and B for both depth and EC. Thecritical value of Q for both depth (QGD) and EC(QEC) were taken as 0. Values above the critical valuewere assessed as risky for QEC and risk-free for QGD.The critical value relating to the B value of EC (BEC)was taken as the threshold value (2250 μmhos/cm)of the "very high" class in the classificationAnonymous (1954). The effective root zones (100-170 cm) of cotton and maize, the two dominantcrops of the region, and the effective root zone ofthe grapevines (100-200 cm), whose average of 150cm is approximately the average effective root zonedepth, was taken as the critical value for the B valueof groundwater depth (BGD) (Allen et al. 1998). Thefact that salinity problems encountered in irrigatedagriculture usually emerge in uncontrolledgroundwater 1-2 m below the surface was also afactor in taking this depth into account. Thesevalues above the critical value were assessed as risk-free for BGD and risky for BEC (see Fig. 2).

There is the potential for a shallow groundwater

level to affect soil salinization (Ayers and Westcot1994, Ali et al. 2000). For this reason, in the assess-ment of the risk in sustainable irrigated agriculture,it is a better approach to take into account not justthe groundwater depth or groundwater EC, butboth together. In addition, it is not only the risk levelarising from the current state of the two parameterswhich is very important, but also the trend of thisrisk, or the amount and direction of future changes.For this reason, these four parameters formed froma combination of the current state of the twoparameters (BGD and BEC) and their trends (QGD

and QEC) were taken into account together and withequal weighting. Nevertheless, these parameterswere also assessed separately and in risk assessment,potential effects of these parameters, in other words,ranges in scoring, were accepted as equal.

Finally, the raster calculator was used tosuperimpose the four maps of the Q and B maps ofthe depth and the EC of the groundwater, then therisk values were calculated for each pixel and the riskmaps were formed for the depth and salinity of thegroundwater (Equation 2).

Rv= QGD+QEC+BGD+BEC (2)Where: Rv - Risk value, QGD - Slope of the

groundwater depth trend (cm/year), QEC - Slope of the groundwater salinity trend (μmhos/cm/year),

BGD - Y-intercept for groundwater depth (cm), andBEC - Y-intercept for groundwater EC (μmhos/cm)

In order to obtain maps of these four parameters,used in forming the risk maps, value ranges werefirst determined by trend analysis.

The risk effect of each parameter in the equationwas considered to be equal (-0.25 min and 0.25max). In this case, the total value that each pixelcould take for these four parameters would be max1 and min -1. Thus, it was accepted that the area ofhighest risk in terms of trend on the risk map wasequal to values closest to -1 and that the value forthe risk-free area was that closest to 1 (Equation 3).

-1≤Rv≤ 1 (3)RESULTS AND DISCUSSION

Results of the analysis showed that the QGD

values varied between -12 and 12 cm/year, BGD

values were between 0-300 cm, QEC values werebetween -600 and 600 μmhos/cm/year, and the BEC

values were between 0 and 4500 μmhos/cm. Despitethe fact that the QGD had values greater than 2 andQEC had values greater than 500 and the BGD hadvalues smaller than 50, areas with these values can-


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not be observed on the maps formed using kriginginterpolation. Therefore, no areas between thesevalues are shown on the trend maps. The value ofeach parameter in this range, which was divided intoa total of 20 equal classes which were all ten aboveor below the critical value, was graded between aminimum of -0.25 and a maximum of 0.25.Graphics concerning grading are given in Fig. 2.

Here, Fig. 2a shows the base criteria for assessingthe trends of the parameters of the depth and the ECof groundwater in brief. This figure shows that forthe two parameters the risk scoring, which is thebasis for calculating the risk value (Rv) on the X-axis,and the criteria that are critical, risky and risk-freefor trend on the Y-axes, and the risky and the risk-free areas formed according to those criteria.Likewise Fig. 2b shows the base criteria for assessingthe current situations of the two parameters in brief.This figure shows for the two parameter the riskscoring which is the basis for calculating the riskvalue (Rv) on the X-axis, and the criteria that arecritical, risky and risk-free for current situation onthe Y-axes, and the risky and risk-free areas formedaccording to those criteria.

Maps associated with Q and B values concerningthe depth and EC trends of groundwater are givenbelow in Figs. 3 and 4 respectively.

If the above maps of the trend of groundwaterdepth are evaluated separately, problematic areas interms of QGD are all areas except the northern andnorth-western parts of the research area (see Fig.3a). In these problem areas it was observed thatthere was a decrease in the groundwater depth, i.e.the groundwater level rose, with different degrees ofrisk and at different rates. Sizes and rates of areas inthe risk groups on the map are given in Table 1.Accordingly, the area of the medium-risk class (-6 to-4), which covers approximately one-third (29.32%)of the whole area, constitutes the largest group. It isseen that the risky areas (<0) cover approximately96% of the total area.

In the north and north-west extremities of thearea, the fact is there were no observation wells, sothat interpolation was performed in line with thenearest wells, which were partly in the low riskareas, might have affected the result, which showedthese areas as risk-free (Fig. 1). According to thisthere is a problem with the slope of the groundwaterdepth trend at varying levels in almost all of theresearch area. In other words, it can be said that the

groundwater level shows an increasing trend todifferent degrees in almost all of the study area.

When the study area is assessed in terms of theBGD value, the problematic areas are seen to beconcentrated in the north and north-west and in thecentral part, in contrast to the slope map (see Fig.3b). In these areas, the groundwater level was foundto be high at different rates and with differentdegrees of risk. The size of the risk group areas aregiven in Table 2. According to this, the area in therisk-free class (150-200 cm), which constitutesmore than half of the whole area (54.73 %),constitutes the biggest group. The total at-risk area(<150 cm) is shown to be about 27% of the wholearea.

In dealing with the at-risk areas of the north andnorth-west, the fact that there were no observationwells in this area (Fig. 1) and that interpolation wascarried out according to the nearest observationwells, which were in relatively high-risk areas, mayhave affected the results in a similar way as theevaluation of QGD. Accordingly, it can be said thatthere was no problem in most of the study area(73%) in terms of BGD, although this occurred atdifferent levels. In other words, the existinggroundwater level in most of area did not constitutea problem.

From this, it can be said that there is a problemin terms of the slope of the groundwater depth trendin the study area; however, there is no problem interms of intersection values. That is to say, eventhough the groundwater depth does not pose athreat currently, it is likely to become a problem inthe future. Evaluated together, both maps show thatplaces where the slope of the groundwater depthtrend increases are places without problems in termsof intersection value.

When groundwater salinity trend maps areevaluated separately, it is seen that the problematicareas in terms of QEC are the north-west, a smallarea in the east, and other areas south-east of thestudy area. In particular, the area where the trend ismost intense is in the south (see Fig. 4a). It can besaid that sea water intrusion has a direct impact sincethe Aegean Sea surrounds these areas very closely(Richter and Kreitler 1993). The size in hectares andpercentage terms of the risk groups are given inTable 3. It can be interpreted that 61.17% of theresearch area in terms of QEC is problematic, yetmost of this area consists of the class between values


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of 0 and 100 μmhos/cm, which is at the same timethe least problematic one. The rest of the area wasfound to be risk-free (38.83%). However, most ofthese risk-free areas (32.16%) were found to be inthe least unproblematic range of this classification[(-100)-0]. According to these results, it can be saidin general that at-risk and risk-free classes areconcentrated around the critical value.

When the research area is assessed in terms of theBEC value, the problematic areas are seen to beconcentrated in a narrow area in the north-west (seeFig. 4b). The size of the risk groups are given inTable 4. According to this, the areas which make up92.62% of the whole area and which are in the“high” salinity class (750-2250 μmhos/cm) accor-

ding to Anonymous (1954) classification, constitutethe biggest group. Water of this quality may not posea problem in areas where plants that are resistant tomedium level salty water are grown underappropriate drainage conditions. This water can goup to the effective root zone without causing adecrease in yield in the dominant plants of theregion: cotton, maize, and grapes (Güngör et al.1996).

The rest, 7.38% of the total area, is seen to be inthe “very high” salinity class (>2250 μmhos/cm).These waters containing a very high level of salt maynot exhibit a problem in the areas where soils arepermeable and have proper drainage and where salt-tolerant plants are grown (Anonymous 1954). Thesewaters can go up to the effective root zone withoutcausing a decrease in yield to cotton, one of thedominant plants of the region, but this may not bethe case for maize and grapes (Güngör et al. 1996).

The raster calculator was used to combine theQGD, BGD, QEC, and BEC maps, and the risk values(Rv) were calculated for each pixel as explained inthe Methods section of this study. The risk map forthe Menemen Irrigation System formed in line withthis grading is given in Fig. 5, and the sizes of theareas in the risk group are given in Table 5.

As seen in the risk map (Fig. 5), we can observethe common effects of the other four maps, and inTable 5, about 35% of the research area is at risk interms of the combined effects of the trend in thedepth and salinity of the groundwater, while the restis risk-free. Besides this, the most problematic areasare concentrated in the north-west and south,similar to the salinity trend maps. The fact that themaps obtained in terms of the QGD and BGDvaluesshow opposite spatial values has led these twoparameters to neutralize one another, causing therisk map to look more similar to the salinity map.This result revealed not only the importance of riskmap assessment but also the importance of theindividual assessment of the maps relating to theother parameters. In conclusion, although the riskmaps resemble the salinity trend maps, theparameters associated with depth were used as wellas the salinity trend maps in obtaining the risk maps.

In a different study done in the region, the ECvalues of 18 samples taken along the Gediz River in1998 were found to be between 200 and 1650μmhos/cm. Overall, the study indicated that thequality of the water of the Gediz River deteriorated

Table 1. Sizes (% and ha) of the areas in the risk groups by QGD values.

Table 2. Sizes (% and ha) of the areas in the risk groups by BGD

Fig. 2. Rating values of [a] BEC and BGD and [b] QEC and QGD.


No: 86, 201342

along the river from the source to the end. It wasalso determined that the N/P ratio diminished fromthe source to the end, which is an indicator ofdomestic pollution (Delibacak et al. 2002). Inanother study performed in the research area, theEC values were found to be 520-710 μmhos/cm and400-580 μmhos/cm respectively according to theanalysis results of water samples taken in the 2004and 2005 irrigation seasons from three differentpoints (Adala, Ahmetli, and Emiralem regulators)and on four different dates in each year. In thisstudy, water quality was found to deteriorate forboth years from the upper stream to the river mouth(Aşık et al. 2008).

Groundwater EC values of the research area,which is located at the lower end of the Gediz River,proved to be higher than the highest EC values of

the two studies on the quality of irrigation water atmany points on the river. This high EC can beinterpreted as being caused not directly by irrigationwater but derived from different factors. The firstone of these may be that the groundwater going upto the active root zone by capillarity action afterirrigation and is used by the plants or evaporates onthe soil surface, leaving behind a continuousaccumulation of salt (Ayers and Westcot 1994). Itcan be said that water given in large amounts by thesurface irrigation methods for a short time duringthe irrigation period acts as an element that increasesthe groundwater level regardless of the currentdrainage, affecting the salinity. In fact, in a study byÇamoğlu et al (2006), in which the depth andsalinity values of the groundwater of the Maltepemain canal service area in the Menemen IrrigationSystem were evaluated, it was discovered that thegroundwater raised most in July and August whenirrigation peaked. In the same study, identificationof the areas with high salinity problems as the placeswhich have the worst groundwater problem alsosupports this idea. Secondly, high EC can be said tobe caused by sea water in the parts near the sea(Richter and Kreitler 1993). The fact that the partswhere the highest salinity values were detected werethe parts near the Aegean Sea supports this idea.

Table 3. Sizes (% and ha) of the areas in the risk groups by QEC

Table 4. Sizes (% and ha) of the areas in the risk groups by BEC

Table 5. Sizes (% and ha) of the areas in the risk classes.

Fig. 3. [a] QGD and [b] BGD maps.


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The waters whose EC values were determined inboth studies are accepted as “low-high” (0-2250 μmhos/cm) in terms of irrigation by the Anonymous(1954) classification and as “good-medium” (0-3000μmhos/cm) by Ayers and Westcot (1994). Thesewaters are not very problematic and may not pose athreat when they reach the root zone. However,when we evaluate the groundwater of this salinityclassification along with the finding of this studythere is an increasing trend in groundwater levels, itcan be said that in the long term these waters willincrease the soil salinity around the effective rootzone. This finding also agrees with the result thatthere is a problem in a large area in the slope of thesalinity trend.

A rise in the level of the water table to the

effective root zone results in decreasing yieldsbecause of salinity and sodicity, and eventually suchareas cannot be cultivated. For sustainable irrigatedagriculture, the salinity and level of the water tableshould be monitored continuously and held withintolerable limits. Although the drainage system wascomplete in the research area (Ertem 1994), thetendency of both the level and salinity trend ofgroundwater to increase could not be prevented.This situation necessitates solutions other than theestablishment of a drainage system.

One of these measures is that instead of lowefficiency surface irrigation, high efficiency irriga-tion systems should be utilized. Leaks from theirrigation network and reservoir as well as theunthought-out and uncontrolled irrigations alsohave an influence on the high groundwater level. Toprevent this, open irrigation canals must besubjected to a maintenance and repair process andbe turned into a closed irrigation system at thehighest possible level. With these two measurestaken, both water application and conveyanceefficiency will increase. In this manner the rise inthe groundwater level and the salinization relatingto it will be prevented. Another possible measure isto improve the irrigation water quality. In order todo this, monitoring to stop the industrial anddomestic wastewater from entering the Gediz Riverand the source of irrigation water in the researcharea, must be carried out more frequently. In theprevious two studies mentioned above it was foundthat water quality improved over time. This isthought to be the result of checks being carried outby officials (Anonymous 2009).

Shallow groundwater has a potential for soilsalinization (Ayers and Westcot 1994; Ali et al.2000). However, groundwater which does notconstitute a risk from the point of view of currentEC value will not encourage soil salinization even ifit is located at a shallow depth. In the same way,groundwater which is very deep but with a highcurrent EC value will not result in salt accumulationby capillarity in the effective root zone. For thisreason, it is not only groundwater depth or the ECof groundwater which must be taken intoconsideration when assessing the risks of sustainableirrigated agriculture, but both together. In addition,if a parameter which is risky because of its highvalue in the current situation shows a falling trend,or in contrast, if a parameter which is risk-free

Fig. 4. [a]QEC and [b] BEC maps.

Fig. 5. Risk map of the Menemen irrigation system.


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because of its low value shows an increasing trend,these situations must be assessed separately. For thisreason, in our approach of these two parameters andtheir trends together, and the current situationstogether must be taken into account. In this way arisk map has been derived by summing the values ofthese four parameters. However, it was shown inthis study that in interpreting results, not only therisk map but also the maps of the other parametersmust be evaluated separately. For example, as wasexplained above, it could have been said that the riskfor sustainable irrigated agriculture derived onlyfrom the trend of groundwater EC because of therisk map has a great similarity to the QEC map. Itmight have been thought that the other parametershad no effect on the risk map, that is, that theirvalues according to our scoring system were zero orvery close to zero. In fact it was determined that theQGD and BGD maps formed from areas with scoresthat were quite far from zero showed values whichwere spatially opposite to each other, and that thevalues of these two parameters neutralized eachother. This was the reason why the risk map showedgreater similarity to the salinity map. This result

showed the importance of assessing the maps of allparameters, also separately.

CONCLUSIONIt was concluded that the depth and salinity of

groundwater in the research area are not a problemat present but are likely to pose a danger in thefuture.

In conclusion, it was shown in this study thatevaluating only the slope values of the trends of bothparameters is not enough when evaluating the depthand salinity values of groundwater of an area interms of the problem they create, and intersectingvalues, in other words, the current situation shouldalso be taken into account.

At the same time, it was determined that it isnecessary to assess separately not only the risk mapbut the maps of all the parameters used in derivingthis map when interpreting the results in suchstudies.

In addition it showed that trend analysis andgeostatistical methods integrated with GIS can beused in obtaining all these results faster and moreefficiently for large areas using intensive data.

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