drought analysis of the haihe river basin based on …...drought analysis of the haihe river basin...

Research ArticleDrought Analysis of the Haihe River Basin Based onGRACE Terrestrial Water Storage

Jianhua Wang1 Dong Jiang2 Yaohuan Huang2 and Hao Wang1

1 State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin Department of Water ResourcesChina Institute of Hydropower ampWater Resources Research Beijing 100038 China

2 Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China

Correspondence should be addressed to Dong Jiang jiangdigsnrraccn

Received 24 April 2014 Revised 4 July 2014 Accepted 25 July 2014 Published 18 August 2014

Academic Editor Arun Singh

Copyright copy 2014 Jianhua Wang et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

The Haihe river basin (HRB) in the North China has been experiencing prolonged severe droughts in recent years that areaccompanied by precipitation deficits and vegetation wilting This paper analyzed the water deficits related to spatiotemporalvariability of three variables of the gravity recovery and climate experiment (GRACE) derived terrestrial water storage (TWS)data precipitation and EVI in the HRB from January 2003 to January 2013 The corresponding drought indices of TWS anomalyindex (TWSI) precipitation anomaly index (PAI) and vegetation anomaly index (AVI) were also compared for drought analysisOur observations showed that theGRACE-TWSwasmore suitable for detecting prolonged and severe droughts in theHRB becauseit can represent loss of deep soil water and ground water The multiyear droughts of which the HRB has sustained for more than5 years began in mid-2007 Extreme drought events were detected in four periods at the end of 2007 the end of 2009 the end of2010 and in the middle of 2012 Spatial analysis of drought risk from the end of 2011 to the beginning of 2012 showed that humanactivities played an important role in the extent of drought hazards in the HRB

1 Introduction

Driven by global change and population pressure droughtsare one of themost serious natural hazards [1] that can lead tocrop losses and economic havoc in many areas For examplein China the direct economic loss associated with droughtsin 2011 was up to 1028 billion Yuan [2] Various globalresearch projects including ISCCP IHDP-IRG andCLIVARhave included drought research as an important part oftheir research plans For basin-scale drought monitoring andevaluation an understanding of the spatiotemporal variationpattern of water deficit is needed

A drought is regional by nature and it is characterizedby its total water deficit (including surface water biologicalwater soil water and ground water or snowice) Howeverquantifying total water deficit over large areas is a majorchallenge in drought studies unfortunately conventionaldata resources are not sufficient in TWS evaluations formonitoring drought occurrence extent and intensity on aregional scale First in situ meteorological and hydrological

measurements are limited in both space and time becausethey are pointmeasurements that cover a small region aroundthe gauging station Globally or even at a basin scale in situmonitoring networks that include all TWS parameters areincomplete [3] which leads to a shortage of sufficient andprecise data in vast regions Furthermore other parameters(eg evapotranspiration) are measured indirectly whichmay reduce the accuracy of TWS estimation in droughtestimation Second hydrological and climate models basedon in situmeasurements are valuable for estimating the distri-bution of changes in TWS while the need for various inputsof land surface parameters (eg land cover) which are alwaysdifficult to observe and hasve increased the uncertainty of theTWS simulation in drought estimation [4 5] In additionthe modeling results for of the TWS were insufficient forevaluating severe extreme droughts and climate events suchas droughts [6] Lastly conventional optical remote sensingand altimetry based measurements which have been provento be helpful for water balance studies at basin scales [7]However they are also problematic in drought evaluation

Hindawi Publishing Corporatione Scientific World JournalVolume 2014 Article ID 578372 10 pageshttpdxdoiorg1011552014578372

2 The Scientific World Journal

They are limited in detecting land-water changes severalcentimeters below the surface of the earth which are justsome of the components needed for TWS estimation Forexample it is not valid for evaluating groundwater which isessential for drought monitoring [8 9]

Due to the difficultly of measuring the integrated bulkvariables of TWS at basin scales recent drought evaluationshave mainly relied upon subcomponents (eg precipita-tion) or proxies (eg NDVI CWSI) [10 11] such as thefour drought categories of ldquometeorologicalrdquo ldquohydrologicalrdquoldquoagriculturalrdquo and ldquosocioeconomicrdquo [12] However droughtindicators rely upon these proxies and approximations are notrepresentative to quantify the integrated temporal variationsof water resources at basin scales Considering that the hor-izontal water cycle at the basin scale surface flow interflowand ground water flow from upstream basins may alleviatedroughts in downstream basins drought severity will beoverestimated when based only on proxies for precipitationIn the vertical view the water cycle processes of infiltrationand evapotranspiration for surface water soil water andgroundwater also affect the proxies used for drought eval-uation For example the soil moisture or vegetation indexproxies will ignore the initial drought due to the surfacewater supply of deeper water resources In addition usingindices based on surface water (rain fall flow rates) mayunderestimate the severity of effects in the later stage ofdroughts for the deep water recharge from surface waterFor regions with prolonged drought conditions deep soilwater and ground water may be more suitable for evaluatingdroughts [13] Furthermore droughts are becoming morecomplicated due to anthropogenic impacts For exampleirrigation for agriculture will increase precipitation throughevaporation and transpiration [14] which is in contrast to theresult of irrigation leading to reductions in regional waterresources [15] It has also been shown that using proxiesfor evaluating long time-series droughts is problematicHerewith the only way to evaluate droughts at the basin scaleis through an integrated measure of TWS [3]

The gravity recovery and climate experiment (GRACE)is the first dedicated satellite gravity mission that was jointlylaunched by the National Aeronautics and Space Adminis-tration (NASA) and the German Aerospace Center (DLR) inMarch 2002 [16] At the basin scale GRACE provides a newdata source for measuring integrated water storage changeon time scales ranging from months to decades [17] Theprecision of the GRACE-retrieved TWS has been verifiedin different basins around the world [18ndash21] Several studieshave used GRACE satellite data to monitor TWS depletionat large river basin scales during droughts [3 6 8 9 22ndash24]Some of them have been used in actual drought monitoring[8] (httpdroughtunleduMonitoringToolsaspx) Overalldrought evaluations based on GRACE still need furtherresearch Furthermore few studies have investigated the dis-tinction between drought monitoring results using GRACE-derived TWS and other proxies in the basins of China

In the present study we use three types of observationaldata to characterize a multiyear drought in the HRB of China(see Figure 1 for location) the GRACE-derived TWS pre-cipitation and the vegetation index Rather than considering

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LuanheNorth Haihe

South HaiheTuhai Majia

Datong

Tianjin

Beijing

Tangshan

ShijiazhuangBohai Sea

Figure 1 Location of the Haihe River basin with its main subbasins

the HRB as a whole as has been done in most studies weanalyzed the spatiotemporal variability patterns of droughtsdetected by GRACE-derived TWS and the other two proxiesalong the main river from upstream to downstream as wellas along its main tributaries The results of this paper can beused to investigate the consistency between GRACE-derivedTWS changes and droughts of China at the basin scale

2 Study Area and Data

21 Location and Hydrology of the HRB The HRB is thefourth basin in China which lies in North China from34∘091015840N to 43∘111015840N and from 111∘211015840E to 120∘431015840E The totalarea of theHRB ismore than 318000 km2 and approximately40 of the area is plain while 60 is mountainous Theelevation of the basin which ranges from higher than 2900mto below 3m decreases from the Yunzhong and Taiyuemountains to the West to the littorals of the Bohai Seainthe East [25] The HRB is dominated by a semimoist andsemiarid continental monsoon climate with cold dry wintersand hot humid summers The spatiotemporal distributionof precipitation within the basin is uneven with a multiyearaverage of 550mmyear which is the lowest along the Eastcoast of China Most of the precipitation is temporallyconcentrated in July and August and spatially concentratedalong the coast and the windward side of the mountains [26]On longer time scales precipitation analysis has detected adecreasing trend from 1961 to 2010 of minus17 which is thelargest among the ten major river basins in China [27] Moststudies have projected significant reductions in precipitationevapotranspiration and runoff together with increased airtemperature As observed in Figure 1 the HRB consists offour parts the Luan subbasin the north Haihe subbasin thesouth Haihe subbasin and the Tuhai-Majia subbasin

The Scientific World Journal 3

The HRB consists of eight provinces including BeijingTianjin most areas of Hebei and some parts of ShandongHenan Shanxi Inner Mongolia and Liaoning It is thepolitical and economic center of China The population ofthe basin accounts for approximately 10 of China and just33 of the geographical area of the nation According to thecensus register the urban population of the basin ismore than36-million and the rate of urbanization has reached 289Approximately 15 of the national GDP is concentrated inthe basin which is above the national average Agriculture isthe largest land-use type and accounts for over 90 of thearable lands The basin is one of the major grain producingareas of China as it accounts for 10 of the total agriculturaloutput The basin produces some 30 of the wheat and 20of the corn in China [28ndash31] To meet the demand for waterresources massive amounts of water have to be diverted fromthe Yangtze and Yellow Rivers to the basin The combinedeffects of climate change and human activities have caused theHRB to continually suffer fromdroughts over the last 30 years[32] Several severe droughts occurred in HRB in the pastcentury which significantly restricted its social and economicdevelopment

22 Data Acquisition

221 GRACE Data GRACE gravity satellite program wasjointly developed by the National Aeronautics and SpaceAdministration (NASA) of the United States and the GermanAerospace Center (DLR) with the objective of providingspatiotemporal variations of the Earthrsquos gravity field TheUS Jet Propulsion Laboratory (JPL) is responsible forthe project management of the GRACE gravity satelliteprogram Monthly gravity field solutions are computed atthe University of Texas at Austin Center for Space Research(CSR) the German Research Centre for GeosciencesPotsdam (GFZ) JPL Groupe de Recherche de GeodesieSpatiale (GRGS) and the Delft Institute of Earth Observationand Space Systems (DEOS) as well as Delft University ofTechnology among others Originally the GRACE resultswere provided in the form of spherical harmonic coefficientsof geoid heights at monthly (or submonthly) intervalsAt time scales that ranged from months to decadestemporal changes in Earthrsquos gravity field were detectedby GRACE and related to the surface mass redistributionof continental water storage [18] Gridded monthly datafrom the land which were expressed as equivalent waterheight (EWH) were also released Here we used themost recent release (RL05) of GRACE products preparedby the CSR GRACE science working team (available athttpgracejplnasagovdatagracemonthlymassgridsland)These aremonthly equivalent water height solutions providedas 1∘ times 1∘ global grids from January 2003 through January2013There are 116 monthly equivalent water height solutionsfor the land with four months missing (June 2003 January2011 June 2011 May 2012) This new data set replaced thedegree two order zero and degree one with parameters fromprevious studies [33 34] A spherical harmonic filter cutoffat degree 60 acted as a third filter on the data The widthof the Gaussian filter that was used for product smoothing

was 200m which was less critical than earlier solutions toimprove the destripping procedure [17] The product of theland also removed a postglacial rebound signal according tothe models of Paulson [35] At our study area location in theHRB the impact of the postglacial rebound signal was smallTo restore much of the energy that removed by destrippingapproach to the land grids a grid of multiplicative scalingcoefficients was applied to the monthly land GRACE massgrids The scaling coefficients were derived independently ofthe GRACE data by applying the same filtering techniquesto the modeled TWS data and then computing the signalattenuation at each geographic location [19 20 36] Usingthe monthly GRACE-TWS data the TWS anomaly index(TWSI) from January 2003 to January 2013 in the HRB wascalculated by removing the means of annual TWS change

TWSI = TWS119894119884minus TWS

119894

(1)

where TWS119894119884was the TWS change of 119894month of119910 year TWS

119894

was the average TWS change in the 119894 month in the normalperiod which was calculated from 10 years of data from 2003to 2013

222 Precipitation Data In this study a normal indexof meteorological droughts of the precipitation anomalyindex (PAI) was proposed which is used to comparewith the TWS anomaly index (TWSI) in drought detec-tion The PAI is calculated from the version 20 monthlyprecipitation data from the China meteorological datasharing service system (CMDSSS) of the China meteo-rological administration (CMA) which are available athttpcdccmagovcnhomedo These data consist of anational gridded time series with a spatial resolution of05

∘

times 05

∘ that covers the time span from 1961 to 2013The data were generated using a ldquoclimatological backgroundfield interpolationrdquo based on monthly precipitation from2416 national meteorological stations and resampled DEMTo be consistent with the GRACE estimates the monthlyprecipitation data were linearly interpolated to a 1∘ times 1∘ gridThe PAI from January 2003 to January 2013 in the HRB wascalculated as follows

PAI =119875

119894minus 119875

119894

119875

119894

(2)

where 119875119894denotes the precipitation of 119894month 119875

119894denotes the

average precipitation in the 119894 month in the normal periodwhich is calculated using the 10 years of data from 2003 to2013

223 Vegetation Index Data The vegetation index data usedin this paper were 1 km 16 days composited MODIS EVI(MOD13A12) which were downloaded from the NASA EOSdata Gateway (EDG) (httpmodisgsfcnasagovindexphp)To be consistent with monthly GRACE estimates the 16 daysEVI product was recomposited using the maximum valuecomposite (MVC) The composited monthly EVI data werethen linearly interpolated to a 1∘ times 1∘ grid Anomalies in the

4 The Scientific World Journal42∘N

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98

654

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15

131211

10

1614

Bohai Sea

Figure 2 Location of 1 times 1 pixels for drought evaluation using theTWS from GRACE the precipitation and the vegetation index

EVI for the study period were computed based on averagesfrom 2003 to 2013 [37]

AVI = EVI119894minus EVI

119894 (3)

where EVI119894was the EVI value of 119894 month and EVI

119894was the

long term average the EVI of 119894month

3 Results

31 Spatiotemporal Variability in TWS Precipitation andEVI The time-series total water storage (TWS) change fromGRACE precipitation and EVI from January 2003 to January2013 was computed with a 1∘ times 1∘ grid resolution along therivers of the HRB (pixel locations are shown in Figure 2)TWS change was expressed in GRACE equivalent waterheight Because the area of Tuhai Majia basin was smallcompared to the resolution of the 1∘ times 1∘ grid we simplycombined it with the South Haihe River basin

311 Luanhe River (Pixels 1 to 3 in Figure 3) Pixels 1 to 3in Figure 3 show the temporal evolution of TWS changeprecipitation and EVI in the Luanhe River In contrast tothe annual cycles of precipitation and EVI the interannualvariability in theTWSevolved significantly from2003 to 2013Because it is dominated by a temperate monsoon climatethe time-series profile of the EVI shows less interannualvariability with a strong seasonal signal peak in summerwhen the vegetation was flourishing This indicated thatsimply using the EVI profile to monitor for droughts islimiting The time-series profiles for precipitation showedseasonal trends that were similar to those observed for theEVI with high rainfall during the summer monsoon Fordroughtmonitoring slight fluctuations in the peak amplitude

of the precipitation profile were more evident than withthe EVI However both profiles lacked significant waterdeficits associated with droughts The TWS changes time-series profiles that were collected from GRACE showedthe most zigzag water resources diminishment with less ofan innerannual cycle which indicated the extreme hazardsassociated with droughts The TWS pixel change from 1 to3 showed that the water resources in the Luanhe River basincontinued to be reduced with lower than 5 cmofwater heightincrease Moreover the area suffered a prolonged period ofdiminishingwater storage frommid-2007 tomid-2012 whichmay imply that the frequent drought events in recent yearsmay be subject to an extreme sustained drought for 5 yearsThe minimum TWS decrease was reached by the end of 2011which indicated that there may have been a drought eventin the Luanhe river basin A consecutive low value of TWSchange and a decrease from the end of 2009 to the middle of2010 may have also brought about an extreme drought eventWhereas after a period of decreasingwater storage frommid-2007 these regions showed a slight recovery trend whichmayindicate the ending of the five-year drought in the Luanhebasin in pixel 3 which is downstream of the Luanhe Riverthe amplitude is relatively lower than the two pixels upstream

312 North Haihe River (Pixels 4 to 7 in Figure 3) Thefiguresof pixels 4 to 7 in theNorthHaihe basin presented similar EVIand precipitation temporal stability patterns to the Luanhebasin The upstream area of pixels 4 and 5 showed a slightpositive TWS anomaly from the beginning of 2003 to mid-2005 where and when droughts were unlikely to occurWhereas a period of continuous negative TWS anomaly wasobserved from the end of 2005 to the beginning of 2013 witha low trough between 2012 and 2013 temporal TWS changesin pixels 6 and 7 fluctuated more significantly with thelargest positive and negative TWS anomalies beingmore than5 cm and 15 cm in water height This indicated that the areadownstream had a higher risk for droughts The figures showthat the TWS reductions of pixels 6 and 7 reached aminimumby the end of 2011 and the beginning of 2012 but recoveredaftermid-2012This indicated a slight drought event occurredat the beginning of 2012 The time series corresponding topixel 7 showed large water decrease in the North Haihe riverfrom 2007 which was supposed to be affected by the TWSdecrease in the South Haihe river basin and leakage from theocean

313 South Haihe River and Tuhai Majia River (Pixels 8 to16 in Figure 3) For narrow shape of the Tuhai Majia Basinby comparing to the resolution of GRACE TWS [2] wecombined the South Haihe basin with the Tuhai Majia basinas one region (pixels 8 to 16 in Figure 3) The magnitudeof the TWS change of combined sub-basin is larger thanthe other two sub-basins of Luanhe River and North HaiheRiver which indicated a higher potential for floods anddroughts in the combined sub-basin From pixels 8 to 16in Figure 3 we notice that the temporal variability of TWSevolved significantly A wet period between 2004 and 2005was observed with large TWS increases (more than 20 cm


0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(1)

EVI

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2(2)

0

1

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0

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20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 EVI

TWS

and

pre (

cm)

minus10

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20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(3)

EVI

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(4)

EVI

EVI

EVI

EVI

EVI

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(5)

EVI

EVI

EVI

EVI

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(6)

TWS

and

pre (

cm)

minus10

minus20

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0

1

2

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20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(7)

TWS

and

pre (

cm)

minus10

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1

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20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(8)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(9)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(10)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(11)

TWS

and

pre (

cm)

minus10

minus20

minus1

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0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(12)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

(a)

Figure 3 Continued


0

1

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15

30

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(13)

TWS

and

pre (

cm)

minus15

minus30

minus1

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0

1

2

0

15

30

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(14)

TWS

and

pre (

cm)

minus15

minus30

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minus2

0

1

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2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(15)

TWS

and

pre (

cm)

minus10

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0

1

2

0

15

30

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(16)

TWS

and

pre (

cm)

minus15

minus30

minus1

minus2

PreTWSEVI

PreTWSEVI

EVI

EVI

EVI

EVI

(b)

Figure 3 Time-series of TWS precipitation and the EVI of selected pixels (the unit of TWS change is cm the unit of precipitation is 2 cm)

EWH in Pixel 13) Whereas there was no significant increasein precipitation the TWS increase may be attributed to watertransfer from irrigation [38] After a period of water storageincrease these regions experienced a prolonged decreasingtrend from the beginning of 2006 to the beginning of 2012with nearly negative TWS changes during the whole periodThis indicated that these regions may have suffered froman extreme sustained drought for more than 6 years Thetime series TWS change profiles clearly indicated severalsignificant TWS deficit peaks such as mid-2007 mid-2009mid-2010 mid-2011 and the beginning of 2012 Integratedanalysis of time-series TWS change profiles of all 9 pixelsimplied that extreme droughts may occur at the end of2007 end of 2009 end of 2010 and in the middle of 2012The minimum at the beginning of 2012 and the relativelylow value of TWS change in all 10 profiles from mid-2011indicated that there may have been an extreme droughtduring the 6 years before the middle of 2012 The slightTWS recovery which was only detected in pixels 9 10 13during the end of 2012 indicated that this 6 years droughtwill be prolonged in this region In pixels 10 13 and 16 whichare located downstream the magnitude of fluctuations weremore evident than that in the upstream pixels Profiles of thethree pixels showed that the largest water storage decrease ofmore than 20 cm EWH occurred at the beginning 2012 andthat the maximum amplitude of the other TWS decreasingpeaks all exceed 15 cm EWH Due to the monsoon climate inthe study area there ismore precipitation in the regions closerto the sea (for example pixel 3) The abnormal reduction inthe TWS downstream where associated with a small changein precipitation may have been attributed to human water

consumption or agriculture It indicates that downstreampixels are more likely to suffer from droughts

32 Drought Analysis Droughts are common in the HRBand several episodes of potential severe droughts weredetected using temporal variability analysis of the GRACETWS change (Figure 3) To evaluate drought events in theHRB from 2003 to 2013 three indicators were taken intoaccount the PAI the AVI and the annual cycle removedTWS (TWSI) It can be instructive to compare GRACEobservations with these common droughts indicators [2439] To compute the TWSI monthly averaged GRACE TWSchange data for ten years were removed at each pixel Usingthe spatio-temporal variability analysis described above forthe TWS the precipitation and the EVI we chose fourrepresentative pixels (pixels 3 7 10 13) from three regions fordrought analysis Figure 4 shows the time series of the threedroughts indicators within the four pixels between 2006 and2012 when droughts were likely to occur in the HRB

In contrast to the annual cycle of EVI and precipitationthat are shown in Figure 3 temporal variability of the threedrought indicators all lack consistency (Figure 4) The cor-relation coefficients between EVI and precipitation for thefour pixels (3 7 10 13) were all more than 084 from 2003to 2013 whereas they were 005 007 008 and 016 betweenPAI and AVI respectively The low correlation coefficientsbetween PAI and AVI imply that these two drought indica-tors predict different water resources deficit conditions thataccompany droughts However correlation analysis showedthat both TWS and TWSI present low correlation with EVI


0

8

16

0

3

6

2006 2007 2008 2009 2010 2011 2012 2013

AVIPAITWSI

AVI a

nd P

AI

TWSI

(3)minus16

minus8minus3

minus6

0

8

16

0

3

6

2006 2007 2008 2009 2010 2011 2012 2013

AVI a

nd P

AI

TWSI

(7)minus16

minus8minus3

minus6

0

8

16

0

3

6

2006 2007 2008 2009 2010 2011 2012 2013

AVI a

nd P

AI

TWSI

(10)minus16

minus8minus3

minus6

0

8

16

0

4

8

2006 2007 2008 2009 2010 2011 2012 2013

AVI a

nd P

AI

TWSI

(13)minus16

minus8minus4

minus8

AVIPAITWSI

Figure 4 Time-series of the TWSI the PAI and the AVI for selected pixels

precipitation and corresponding droughts indicators Themaximum correlation coefficient was 034 in pixel 13 betweenEVI and TWS which indicated that TWS represented adifferent drought scene from the two common indicatorsFigure 4 shows that the occurrence and release of droughtAVI lagged behind PAI for 1ndash3 months and droughts ofAVI were more severe than PAI This is because of thedelay in recharge of surface and soil water from rainfalland the vegetation growth Both indicators mainly reflectedwater depletion in surface water and shallow soil waterFor HRB which included important urban agglomerationareas (Beijing and Tianjin in North Haihe) and agriculturalregions (South Haihe and Tuhai Majia) water deficit was themain limitation to maintaining healthy social development[7 40] Over the long-term persistent water shortage inthe HRB in recent years has used transferred water andgroundwater as the main water supplies Overexploitation ofgroundwater caused a depression in the groundwater conewhich has exacerbated the risk for droughts in the HRB[2] PAI and AVI were both invalid for detecting droughtsrelated to decreases in HRB groundwater where there was aprolonged drought region with strong impacts from humanactivities This was most obvious during the period fromthe end of 2011 to the beginning of 2012 in Figure 4 whenthe time-series for PAI and AVI had no extreme droughtsand a normal and gentle amplitude fluctuation HoweverTWSI showed that HRB experienced great water resourcedecreases during this period which may have caused anextreme drought in 2006 Considering the annual cycle ofprecipitation and vegetation growth and their relation toshallow water the TWS change mainly contributed to thedischarge of groundwater to surface water which implied adrought risk

To analyze the spatial distribution of droughts in theperiod between the end of 2011 and the beginning of 2012we accumulated GRACE TWS anomalies of 6 months fromOctober 2011 to March 2012 in the HRB (Figure 5) As shownin Figure 5 the 6 months of accumulated TWS changespresent spatial variability clearly Most area of the HRBexcept a small area of Tuhai-Majia River basin in the southernpart of the region was dominated by drought risk Thedroughts in the northern subbasins of the Haihe River basinwere more severe with accumulated TWS decreases over anarea larger than 20 cm EWH The drought risk differencein the southern region can be explained by more than 32times 108m3 of water being transferred annually to the Tuhai-Majia subbasin for irrigation from the Yellow River whichis the second river in China bordering with southern HaiheRiver basin Due to the impact of the monsoon climatethere was a trend of higher droughts risk in the westernarea when compared to the eastern regions near the ocean(Figure 5) The upstream region of the HRB suffered moresevere droughts than the downstream region However thespatial distribution trend of droughts risk from upstream todownstream was contaminated by scattered urban locationpixels In addition the accumulated TWS change in pixelsaround Beijing was lower than those in the upstream regionThis azonal distribution was also detected in the areas wherethe cities of Tianjin Shijiazhuang Tangshan and Datong arelocated Therefore we propose that urban areas with higherdomestic and industrial water demand are more susceptibleto droughtsThe analysis of the spatial distribution of droughtrisk in the HRB within the selected period indicated thatbesides natural climate change human activity played animportant role in drought risk


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minus35 minus20 minus10 minus5 0

(cm)

Datong

Tianjin

Beijing

Tangshan


Figure 5 Spatial distribution of accumulated TWS anomaliesduring the period fromOctober 2011 to March 2012 for drought riskanalysis

4 Summary and Discussion

Drought is a recurring issue inmany parts of China includingtheHRB In recent years severe droughts have occurredmorefrequently over wider regions GRACE derived verticallyintegrated water storage (TWS) change precipitation andthe vegetation index have been widely used in quantifyingthe severity and characterizing droughts at the basin scalein several studies [3 11 14] In this study we have analyzeddroughts by comparing the spatiotemporal evolution of theTWS change the precipitation and the vegetation index aswell as three corresponding drought indices over the HRB forthe time period between January 2003 and January 2013

The precipitation and EVI time series correlated wellwith similar seasonal cycles The slight fluctuations in thepeak amplitude of precipitation and EVI profiles limitedtheir direct application in drought monitoring The TWSchange time series showed less of an interannual cycle whichmay be more useful to indicate TWS deficits accompanyingdrought events While both precipitation and EVI presentedthe drought conditions of surface water the TWS had a lowcorrelation to the EVI and precipitation The GRACE-TWSwas more suitable for evaluating prolonged droughts in theHRB region whose water deficit was mainly dominated bydeep soil water and ground water anomalies

Although the three drought indices of TWSI PAI andAVI all detected the drought events in the HRB the extentand length of the droughts were different Correlation anal-ysis showed that the correlation coefficients for all threeindiceswere lowwhich indicated that they represent differentwater deficit conditions in droughts Droughts predicted

by the TWSI are more prolonged and more severe thanthose predicted by the other two indices In addition theoccurrence and release of drought AVI indicated a longerand more severe drought than with PAI This can also beattributed to the different parts of the integrated water bulksthat the three indices represent

The combined analysis of the spatiotemporal variabilityof the TWS and the TWSI showed that the overall droughtconditions in the HRB began around 2007 The North HaiheRiver subbasin suffered the longest period of sustained waterdiminishment for 7 years An extreme water deficit occurredin the South Haihe River subbasin with the largest EWHdecrease during a 6 year period of sustained water reductionDrought analysis also shows that extreme drought eventsmayhave occurred in four periods at the end of 2007 end of 2009end of 2010 and middle of 2012 which was consistent withdrought reports [2] Furthermore a slight water recoveryat the end of 2012 was detected in the Luanhe and NorthHaihe subbasin which may indicate an end to the prolongeddroughts

In the period from the end of 2011 to the beginning of2012 the drought in the HRB abated with a return to nearlyaveragemonthly precipitation and EVI however the GRACETWSI data show that a substantial accumulated bulk waterdeficit remains in the basin Spatial analysis of TWSI droughtduring this period showed that drought risk in the HRB wasimpacted both by the natural climate and human activitiesDue to the dominating temperate monsoon climate thedownstream regions near the ocean are less threatened bydroughts However droughts in urban areas will be moresevere due to their higher domestic and industrial waterconsumptionThe agricultural areas such as the Tuhai-MajiaRiver basin will suffer fewer extended droughts due to watertransfer for irrigation

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This project was supported by National Natural ScienceFoundation of China (Grant no 51309210) the ChineseAcademy of Sciences (Grant KZZD-EW-08) and the OpenResearch Fund of State Key Laboratory of Simulation andRegulation of Water Cycle in River Basin (Grant no IWHR-SKL-201206) GRACE land data were processed by SeanSwenson supported by the NASAMEASURES Program andare available at httpgracejplnasagov

References

[1] E Bryant Natural Hazards Cambridge University Press Cam-bridge UK 2005

[2] J Wang Z Feng and H Li Identification and ComprehensiveResponse Strategy to Severe Water shortage System of HebeiScience Press Beijing China 2013


[3] M J Leblanc P Tregoning G Ramillien S O Tweed andA Fakes ldquoBasin-scale integrated observations of the early21st century multiyear drought in Southeast Australiardquo WaterResources Research vol 45 no 4 Article IDW04408 2009

[4] A Cazenave and R S Nerem ldquoRedistributing earthrsquos massrdquoScience vol 297 no 5582 pp 783ndash784 2002

[5] C M Cox and B F Chao ldquoDetection of a large-scale massredistribution in the terrestrial system since 1998rdquo Science vol297 no 5582 pp 831ndash833 2002

[6] J L Chen C R Wilson B D Tapley Z L Yang and GY Niu ldquo2005 drought event in the Amazon River basin asmeasured byGRACE and estimated by climatemodelsrdquo Journalof Geophysical Research B Solid Earth vol 114 no 5 Article IDB05404 2009

[7] Y H Huang D Jiang D Zhuang J Wang H Yang and HRen ldquoEvaluation of relative water use efficiency (RWUE) at aregional scale a case study of Tuhai-Majia Basin ChinardquoWaterScience and Technology vol 66 no 5 pp 927ndash933 2012

[8] R Houborg M Rodell B Li R Reichle and B F ZaitchikldquoDrought indicators based on model-assimilated GravityRecovery and Climate Experiment (GRACE) terrestrial waterstorage observationsrdquo Water Resources Research vol 48 no 72012

[9] D Long B R Scanlon L Longuevergne A Y Sun D NFernando and H Save ldquoGRACE satellite monitoring of largedepletion in water storage in response to the 2011 drought inTexasrdquo Geophysical Research Letters vol 40 no 13 pp 3395ndash3401 2013

[10] J A Keyantash and J A Dracup ldquoAn aggregate droughtindex assessing drought severity based on fluctuations in thehydrologic cycle and surface water storagerdquo Water ResourcesResearch vol 40 no 9 2004

[11] Y Huang J Wang D Jiang and Q Zhou ldquoRegionalization ofsurface water shortage of China based on evapotranspirationrdquoJournal of Hydraulic Engineering vol 40 no 8 pp 927ndash9332009

[12] J Keyantash and J A Dracup ldquoThe quantification of droughtan evaluation of drought indicesrdquo Bulletin of the AmericanMeteorological Society vol 83 no 8 pp 1167ndash1180 2002

[13] A K Mishra and V P Singh ldquoA review of drought conceptsrdquoJournal of Hydrology vol 391 no 1-2 pp 202ndash216 2010

[14] M-H Lo and J S Famiglietti ldquoIrrigation in CaliforniasCentral Valley strengthens the southwestern US water cyclerdquoGeophysical Research Letters vol 40 no 2 pp 301ndash306 2013

[15] M Rodell I Velicogna and J S Famiglietti ldquoSatellite-basedestimates of groundwater depletion in Indiardquo Nature vol 460no 7258 pp 999ndash1002 2009

[16] B D Tapley S Bettadpur M Watkins and C Reigber ldquoThegravity recovery and climate experiment mission overview andearly resultsrdquo Geophysical Research Letters vol 31 no 9 2004

[17] L Xavier M Becker A Cazenave L Longuevergne W Lloveland O C R Filho ldquoInterannual variability in water storageover 2003ndash2008 in the Amazon Basin from GRACE spacegravimetry in situ river level and precipitation datardquo RemoteSensing of Environment vol 114 no 8 pp 1629ndash1637 2010

[18] J Wahr S Swenson V Zlotnicki and I Velicogna ldquoTime-variable gravity from GRACE first resultsrdquo GeophysicalResearch Letters vol 31 no 11 2004

[19] S C Swenson and P C D Milly ldquoClimate model biases inseasonally of continental water storage revealed by satellitegravimetryrdquoWater Resources Research vol 42 no 3 Article IDW03201 2006

[20] S C Swenson and J Wahr ldquoPost-processing removal of corre-lated errors in GRACE datardquo Geophysical Research Letters vol33 no 8 Article ID L08402 2006

[21] R Klees E A Revtova B C Gunter et al ldquoThe design of anoptimal filter for monthly GRACE gravity modelsrdquo GeophysicalJournal International vol 175 no 2 pp 417ndash432 2008

[22] S Z Yirdaw K R Snelgrove and C O Agboma ldquoGRACEsatellite observations of terrestrialmoisture changes for droughtcharacterization in the Canadian Prairierdquo Journal of Hydrologyvol 356 no 1-2 pp 84ndash92 2008

[23] M M Billah and J L Goodall ldquoAnnual and interannual varia-tions in terrestrial water storage during and following a periodof drought in South Carolina USArdquo Journal of Hydrology vol409 no 1-2 pp 472ndash482 2011

[24] B LiM Rodell B F Zaitchik R H Reichle R D Koster and TM van Dam ldquoAssimilation of GRACE terrestrial water storageinto a land surface model evaluation and potential value fordrought monitoring in western and central Europerdquo Journal ofHydrology vol 446-447 pp 103ndash115 2012

[25] Y H Huang D Jiang D F Zhuang H Y Ren and Z J YaoldquoFilling gaps in vegetation indexmeasurements for crop growthmonitoringrdquoAfrican Journal of Agricultural Research vol 6 no12 pp 2920ndash2930 2011

[26] Y Yang M Watanabe X Zhang J Zhang Q Wang andS Hayashi ldquoOptimizing irrigation management for wheat toreduce groundwater depletion in the piedmont region of theTaihang mountains in the North China Plainrdquo AgriculturalWater Management vol 82 no 1-2 pp 25ndash44 2006

[27] D Yan Z Yuan Z Yang Y Wang and Y Yu ldquoSpatial andtemporal changes in drought since 1961 in Haihe River basinrdquoAdvances in Water Science vol 24 no 1 pp 34ndash41 2013

[28] J P Moiwo Y Yang H Li S Han and Y Hu ldquoComparisonof GRACE with in situ hydrological measurement data showsstorage depletion in Hai River Basin Northern Chinardquo WaterSA vol 35 no 5 pp 663ndash670 2009

[29] J Chu J Xia C Xu L Li and Z Wang ldquoSpatial and temporalvariability of daily precipitation in Haihe River basin 1958ndash2007rdquo Journal of Geographical Sciences vol 20 no 2 pp 248ndash260 2010

[30] H Ma L Liu and T Chen ldquoWater security assessment inHaihe River Basin using principal component analysis based onKendall 120591rdquo Environmental Monitoring and Assessment vol 163no 1ndash4 pp 539ndash544 2010

[31] Y Zhu S Drake H Lu and J Xia ldquoAnalysis of temporaland spatial differences in eco-environmental carrying capacityrelated to water in the Haihe river basins Chinardquo WaterResources Management vol 24 no 6 pp 1089ndash1105 2010

[32] Z Ma ldquoThe interdecadal trend and shift of drywet over thecentral part of North China and their relationship to the PacificDecadal Oscillation (PDO)rdquo Chinese Science Bulletin vol 52no 15 pp 2130ndash2139 2007

[33] M Cheng and B D Tapley ldquoVariations in the Earthrsquos oblatenessduring the past 28 yearsrdquo Journal of Geophysical Research vol109 no 9 2004

[34] S C Swenson D P Chambers and J Wahr ldquoEstimatinggeocenter variations from a combination of GRACE and oceanmodel outputrdquo Journal of Geophysical Research B Solid Earthvol 113 no 8 Article ID B08410 2008

[35] A Paulson S J Zhong and J Wahr ldquoLimitations on the inver-sion formantle viscosity frompostglacial reboundrdquoGeophysicalJournal International vol 168 no 3 pp 1195ndash1209 2007


[36] F W Landerer and S C Swenson ldquoAccuracy of scaled GRACEterrestrial water storage estimatesrdquo Water Resources Researchvol 48 no 4 2012

[37] C Mongkolsawat P Thirangoon R Suwanweramtorn NKarladee S Paiboonsank and P Champathet ldquoAn evaluation ofdrought risk area in Northeast Thailand using remotely senseddata and GISrdquo Asian Journal of Geoinformatics vol 1 pp 1ndash42001

[38] The Chinese Ministry of Water Resources China WaterResources Bulletin China WaterPower Press Beijing China2005

[39] Q Zhang J Li V P Singh C-Y Xu and J Deng ldquoInfluence ofENSO on precipitation in the East River basin South ChinardquoJournal of Geophysical Research D Atmospheres vol 118 no 5pp 2207ndash2219 2013

[40] Y Huang D Jiang D Zhuang Y Zhu and J Fu ldquoAn improvedapproach for modeling spatial distribution of water use profitmdasha case study in Tuhai Majia Basin Chinardquo Ecological Indicatorsvol 36 pp 94ndash99 2014


They are limited in detecting land-water changes severalcentimeters below the surface of the earth which are justsome of the components needed for TWS estimation Forexample it is not valid for evaluating groundwater which isessential for drought monitoring [8 9]

Due to the difficultly of measuring the integrated bulkvariables of TWS at basin scales recent drought evaluationshave mainly relied upon subcomponents (eg precipita-tion) or proxies (eg NDVI CWSI) [10 11] such as thefour drought categories of ldquometeorologicalrdquo ldquohydrologicalrdquoldquoagriculturalrdquo and ldquosocioeconomicrdquo [12] However droughtindicators rely upon these proxies and approximations are notrepresentative to quantify the integrated temporal variationsof water resources at basin scales Considering that the hor-izontal water cycle at the basin scale surface flow interflowand ground water flow from upstream basins may alleviatedroughts in downstream basins drought severity will beoverestimated when based only on proxies for precipitationIn the vertical view the water cycle processes of infiltrationand evapotranspiration for surface water soil water andgroundwater also affect the proxies used for drought eval-uation For example the soil moisture or vegetation indexproxies will ignore the initial drought due to the surfacewater supply of deeper water resources In addition usingindices based on surface water (rain fall flow rates) mayunderestimate the severity of effects in the later stage ofdroughts for the deep water recharge from surface waterFor regions with prolonged drought conditions deep soilwater and ground water may be more suitable for evaluatingdroughts [13] Furthermore droughts are becoming morecomplicated due to anthropogenic impacts For exampleirrigation for agriculture will increase precipitation throughevaporation and transpiration [14] which is in contrast to theresult of irrigation leading to reductions in regional waterresources [15] It has also been shown that using proxiesfor evaluating long time-series droughts is problematicHerewith the only way to evaluate droughts at the basin scaleis through an integrated measure of TWS [3]

The gravity recovery and climate experiment (GRACE)is the first dedicated satellite gravity mission that was jointlylaunched by the National Aeronautics and Space Adminis-tration (NASA) and the German Aerospace Center (DLR) inMarch 2002 [16] At the basin scale GRACE provides a newdata source for measuring integrated water storage changeon time scales ranging from months to decades [17] Theprecision of the GRACE-retrieved TWS has been verifiedin different basins around the world [18ndash21] Several studieshave used GRACE satellite data to monitor TWS depletionat large river basin scales during droughts [3 6 8 9 22ndash24]Some of them have been used in actual drought monitoring[8] (httpdroughtunleduMonitoringToolsaspx) Overalldrought evaluations based on GRACE still need furtherresearch Furthermore few studies have investigated the dis-tinction between drought monitoring results using GRACE-derived TWS and other proxies in the basins of China

In the present study we use three types of observationaldata to characterize a multiyear drought in the HRB of China(see Figure 1 for location) the GRACE-derived TWS pre-cipitation and the vegetation index Rather than considering

42∘N

40∘N

38∘N

36∘N

42∘N

40∘N

38∘N

36∘N

112∘E 114

∘E 116∘E 118

∘E 120∘E

112∘E 114

∘E 116∘E 118

∘E 120∘E

LuanheNorth Haihe

South HaiheTuhai Majia

Datong

Tianjin

Beijing

Tangshan


Figure 1 Location of the Haihe River basin with its main subbasins

the HRB as a whole as has been done in most studies weanalyzed the spatiotemporal variability patterns of droughtsdetected by GRACE-derived TWS and the other two proxiesalong the main river from upstream to downstream as wellas along its main tributaries The results of this paper can beused to investigate the consistency between GRACE-derivedTWS changes and droughts of China at the basin scale

2 Study Area and Data

21 Location and Hydrology of the HRB The HRB is thefourth basin in China which lies in North China from34∘091015840N to 43∘111015840N and from 111∘211015840E to 120∘431015840E The totalarea of theHRB ismore than 318000 km2 and approximately40 of the area is plain while 60 is mountainous Theelevation of the basin which ranges from higher than 2900mto below 3m decreases from the Yunzhong and Taiyuemountains to the West to the littorals of the Bohai Seainthe East [25] The HRB is dominated by a semimoist andsemiarid continental monsoon climate with cold dry wintersand hot humid summers The spatiotemporal distributionof precipitation within the basin is uneven with a multiyearaverage of 550mmyear which is the lowest along the Eastcoast of China Most of the precipitation is temporallyconcentrated in July and August and spatially concentratedalong the coast and the windward side of the mountains [26]On longer time scales precipitation analysis has detected adecreasing trend from 1961 to 2010 of minus17 which is thelargest among the ten major river basins in China [27] Moststudies have projected significant reductions in precipitationevapotranspiration and runoff together with increased airtemperature As observed in Figure 1 the HRB consists offour parts the Luan subbasin the north Haihe subbasin thesouth Haihe subbasin and the Tuhai-Majia subbasin



22 Data Acquisition




119894

(1)


119894



∘

times 05


PAI =119875

119894minus 119875

119894

119875

119894

(2)


119894denotes the




40∘N

38∘N

36∘N

42∘N

40∘N

38∘N

36∘N

112∘E 114

∘E 116∘E 118

∘E 120∘E

112∘E 114

∘E 116∘E 118

∘E 120∘E

3

21

98

654

7

15

131211

10

1614

Bohai Sea




119894 (3)


119894was the


3 Results







0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(1)

EVI

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2(2)

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 EVI

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(3)

EVI

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(4)

EVI

EVI

EVI

EVI

EVI

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(5)

EVI

EVI

EVI

EVI

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(6)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(7)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(8)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(9)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(10)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(11)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(12)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

(a)

Figure 3 Continued


0

1

2

0

15

30

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(13)

TWS

and

pre (

cm)

minus15

minus30

minus1

minus2

0

1

2

0

15

30

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(14)

TWS

and

pre (

cm)

minus15

minus30

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(15)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

15

30

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(16)

TWS

and

pre (

cm)

minus15

minus30

minus1

minus2

PreTWSEVI

PreTWSEVI

EVI

EVI

EVI

EVI

(b)







0

8

16

0

3

6

2006 2007 2008 2009 2010 2011 2012 2013

AVIPAITWSI

AVI a

nd P

AI

TWSI

(3)minus16

minus8minus3

minus6

0

8

16

0

3

6

2006 2007 2008 2009 2010 2011 2012 2013

AVI a

nd P

AI

TWSI

(7)minus16

minus8minus3

minus6

0

8

16

0

3

6

2006 2007 2008 2009 2010 2011 2012 2013

AVI a

nd P

AI

TWSI

(10)minus16

minus8minus3

minus6

0

8

16

0

4

8

2006 2007 2008 2009 2010 2011 2012 2013

AVI a

nd P

AI

TWSI

(13)minus16

minus8minus4

minus8

AVIPAITWSI





40∘N

38∘N

36∘N

42∘N

40∘N

38∘N

36∘N

112∘E 114

∘E 116∘E 118

∘E 120∘E

112∘E 114

∘E 116∘E 118

∘E 120∘E


(cm)

Datong

Tianjin

Beijing

Tangshan












Acknowledgments


References













































22 Data Acquisition




119894

(1)


119894



∘

times 05


PAI =119875

119894minus 119875

119894

119875

119894

(2)


119894denotes the




40∘N

38∘N

36∘N

42∘N

40∘N

38∘N

36∘N

112∘E 114

∘E 116∘E 118

∘E 120∘E

112∘E 114

∘E 116∘E 118

∘E 120∘E

3

21

98

654

7

15

131211

10

1614

Bohai Sea




119894 (3)


119894was the


3 Results







0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(1)

EVI

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2(2)

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 EVI

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(3)

EVI

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(4)

EVI

EVI

EVI

EVI

EVI

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(5)

EVI

EVI

EVI

EVI

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(6)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(7)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(8)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(9)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(10)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(11)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(12)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

(a)

Figure 3 Continued


0

1

2

0

15

30

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(13)

TWS

and

pre (

cm)

minus15

minus30

minus1

minus2

0

1

2

0

15

30

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(14)

TWS

and

pre (

cm)

minus15

minus30

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(15)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

15

30

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(16)

TWS

and

pre (

cm)

minus15

minus30

minus1

minus2

PreTWSEVI

PreTWSEVI

EVI

EVI

EVI

EVI

(b)







0

8

16

0

3

6

2006 2007 2008 2009 2010 2011 2012 2013

AVIPAITWSI

AVI a

nd P

AI

TWSI

(3)minus16

minus8minus3

minus6

0

8

16

0

3

6

2006 2007 2008 2009 2010 2011 2012 2013

AVI a

nd P

AI

TWSI

(7)minus16

minus8minus3

minus6

0

8

16

0

3

6

2006 2007 2008 2009 2010 2011 2012 2013

AVI a

nd P

AI

TWSI

(10)minus16

minus8minus3

minus6

0

8

16

0

4

8

2006 2007 2008 2009 2010 2011 2012 2013

AVI a

nd P

AI

TWSI

(13)minus16

minus8minus4

minus8

AVIPAITWSI





40∘N

38∘N

36∘N

42∘N

40∘N

38∘N

36∘N

112∘E 114

∘E 116∘E 118

∘E 120∘E

112∘E 114

∘E 116∘E 118

∘E 120∘E


(cm)

Datong

Tianjin

Beijing

Tangshan












Acknowledgments


References












































40∘N

38∘N

36∘N

42∘N

40∘N

38∘N

36∘N

112∘E 114

∘E 116∘E 118

∘E 120∘E

112∘E 114

∘E 116∘E 118

∘E 120∘E

3

21

98

654

7

15

131211

10

1614

Bohai Sea




119894 (3)


119894was the


3 Results







0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(1)

EVI

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2(2)

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 EVI

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(3)

EVI

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(4)

EVI

EVI

EVI

EVI

EVI

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(5)

EVI

EVI

EVI

EVI

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(6)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(7)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(8)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(9)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(10)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(11)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(12)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

(a)

Figure 3 Continued


0

1

2

0

15

30

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(13)

TWS

and

pre (

cm)

minus15

minus30

minus1

minus2

0

1

2

0

15

30

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(14)

TWS

and

pre (

cm)

minus15

minus30

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(15)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

15

30

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(16)

TWS

and

pre (

cm)

minus15

minus30

minus1

minus2

PreTWSEVI

PreTWSEVI

EVI

EVI

EVI

EVI

(b)







0

8

16

0

3

6

2006 2007 2008 2009 2010 2011 2012 2013

AVIPAITWSI

AVI a

nd P

AI

TWSI

(3)minus16

minus8minus3

minus6

0

8

16

0

3

6

2006 2007 2008 2009 2010 2011 2012 2013

AVI a

nd P

AI

TWSI

(7)minus16

minus8minus3

minus6

0

8

16

0

3

6

2006 2007 2008 2009 2010 2011 2012 2013

AVI a

nd P

AI

TWSI

(10)minus16

minus8minus3

minus6

0

8

16

0

4

8

2006 2007 2008 2009 2010 2011 2012 2013

AVI a

nd P

AI

TWSI

(13)minus16

minus8minus4

minus8

AVIPAITWSI





40∘N

38∘N

36∘N

42∘N

40∘N

38∘N

36∘N

112∘E 114

∘E 116∘E 118

∘E 120∘E

112∘E 114

∘E 116∘E 118

∘E 120∘E


(cm)

Datong

Tianjin

Beijing

Tangshan












Acknowledgments


References












































0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(1)

EVI

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2(2)

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 EVI

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(3)

EVI

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(4)

EVI

EVI

EVI

EVI

EVI

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(5)

EVI

EVI

EVI

EVI

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(6)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(7)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(8)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(9)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(10)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(11)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(12)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

(a)

Figure 3 Continued


0

1

2

0

15

30

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(13)

TWS

and

pre (

cm)

minus15

minus30

minus1

minus2

0

1

2

0

15

30

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(14)

TWS

and

pre (

cm)

minus15

minus30

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(15)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

15

30

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(16)

TWS

and

pre (

cm)

minus15

minus30

minus1

minus2

PreTWSEVI

PreTWSEVI

EVI

EVI

EVI

EVI

(b)







0

8

16

0

3

6

2006 2007 2008 2009 2010 2011 2012 2013

AVIPAITWSI

AVI a

nd P

AI

TWSI

(3)minus16

minus8minus3

minus6

0

8

16

0

3

6

2006 2007 2008 2009 2010 2011 2012 2013

AVI a

nd P

AI

TWSI

(7)minus16

minus8minus3

minus6

0

8

16

0

3

6

2006 2007 2008 2009 2010 2011 2012 2013

AVI a

nd P

AI

TWSI

(10)minus16

minus8minus3

minus6

0

8

16

0

4

8

2006 2007 2008 2009 2010 2011 2012 2013

AVI a

nd P

AI

TWSI

(13)minus16

minus8minus4

minus8

AVIPAITWSI





40∘N

38∘N

36∘N

42∘N

40∘N

38∘N

36∘N

112∘E 114

∘E 116∘E 118

∘E 120∘E

112∘E 114

∘E 116∘E 118

∘E 120∘E


(cm)

Datong

Tianjin

Beijing

Tangshan












Acknowledgments


References












































0

1

2

0

15

30

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(13)

TWS

and

pre (

cm)

minus15

minus30

minus1

minus2

0

1

2

0

15

30

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(14)

TWS

and

pre (

cm)

minus15

minus30

minus1

minus2

0

1

2

0

10

20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(15)

TWS

and

pre (

cm)

minus10

minus20

minus1

minus2

0

1

2

0

15

30

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

(16)

TWS

and

pre (

cm)

minus15

minus30

minus1

minus2

PreTWSEVI

PreTWSEVI

EVI

EVI

EVI

EVI

(b)







0

8

16

0

3

6

2006 2007 2008 2009 2010 2011 2012 2013

AVIPAITWSI

AVI a

nd P

AI

TWSI

(3)minus16

minus8minus3

minus6

0

8

16

0

3

6

2006 2007 2008 2009 2010 2011 2012 2013

AVI a

nd P

AI

TWSI

(7)minus16

minus8minus3

minus6

0

8

16

0

3

6

2006 2007 2008 2009 2010 2011 2012 2013

AVI a

nd P

AI

TWSI

(10)minus16

minus8minus3

minus6

0

8

16

0

4

8

2006 2007 2008 2009 2010 2011 2012 2013

AVI a

nd P

AI

TWSI

(13)minus16

minus8minus4

minus8

AVIPAITWSI





40∘N

38∘N

36∘N

42∘N

40∘N

38∘N

36∘N

112∘E 114

∘E 116∘E 118

∘E 120∘E

112∘E 114

∘E 116∘E 118

∘E 120∘E


(cm)

Datong

Tianjin

Beijing

Tangshan












Acknowledgments


References












































0

8

16

0

3

6

2006 2007 2008 2009 2010 2011 2012 2013

AVIPAITWSI

AVI a

nd P

AI

TWSI

(3)minus16

minus8minus3

minus6

0

8

16

0

3

6

2006 2007 2008 2009 2010 2011 2012 2013

AVI a

nd P

AI

TWSI

(7)minus16

minus8minus3

minus6

0

8

16

0

3

6

2006 2007 2008 2009 2010 2011 2012 2013

AVI a

nd P

AI

TWSI

(10)minus16

minus8minus3

minus6

0

8

16

0

4

8

2006 2007 2008 2009 2010 2011 2012 2013

AVI a

nd P

AI

TWSI

(13)minus16

minus8minus4

minus8

AVIPAITWSI





40∘N

38∘N

36∘N

42∘N

40∘N

38∘N

36∘N

112∘E 114

∘E 116∘E 118

∘E 120∘E

112∘E 114

∘E 116∘E 118

∘E 120∘E


(cm)

Datong

Tianjin

Beijing

Tangshan












Acknowledgments


References












































40∘N

38∘N

36∘N

42∘N

40∘N

38∘N

36∘N

112∘E 114

∘E 116∘E 118

∘E 120∘E

112∘E 114

∘E 116∘E 118

∘E 120∘E


(cm)

Datong

Tianjin

Beijing

Tangshan












Acknowledgments


References











































drought analysis of the haihe river basin based on …...drought analysis of the haihe river basin...

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