Water quality changes in the world’s first special economic zone,Shenzhen, ChinaYi Chen,1 Zhao Zhang,1 Shiqiang Du,1 Peijun Shi,1 Fulu Tao,2 and Martin Doyle3

Received 28 January 2011; revised 13 September 2011; accepted 21 September 2011; published 15 November 2011.

[1] Shenzhen, as the first special economic zone in the world, has been in the process ofrapid urbanization for 30 years. Many special economic zones have been established inChina and other nations following Shenzhen’s experience. However, Shenzhen has attainedsignificant economic development with an attendant cost of environmental degradation, andsimilar results may be seen in other zones in the future. Here we use a pollution indexmethod to evaluate the effect of such rapid urban development on the surface water qualityin Shenzhen from 1991 to 2008. Rapid urbanization has affected surface water quality, butenvironmental policies can mitigate some of these effects, although such policy-inducedimprovements required some time before showing efficacy. As their use of specialeconomic zones proliferates worldwide, greater consideration of the potential effects onwater quality, and their overall sustainability, must receive greater attention.

Citation: Chen, Y., Z. Zhang, S. Du, P. Shi, F. Tao, and M. Doyle (2011), Water quality changes in the world’s first special economic

zone, Shenzhen, China, Water Resour. Res., 47, W11515, doi:10.1029/2011WR010491.

1. Introduction[2] Human populations and urban development are

increasing at unprecedented rates, creating tremendous stresson the quality of local environments throughout the world[Duh et al., 2008; Zhang et al., 2010]. In addition to popu-lation growth, there has been a distinct shift in the distribu-tion of population, as more than two-thirds of the world’spopulation will live in urban areas by 2030 [PopulationDivision of the Department of Economic and Social Affairsof the United Nations Secretariat, 2007]. In China, ourfocus in this article, urbanization levels are predicted toreach 55% by 2025, when the urban population is projectedto reach 830 million.

[3] Rapid urbanization inevitably results in substantialenvironmental changes, particularly to water quality. Manyof the effects of urbanization on water quality are increas-ingly well documented and understood. The urbanizationprocess can result in water shortages, as rapid urbanizationand concentrated populations in city areas put pressure onthe water supply [Wu and Chen, 2008]. Also, urbanizationincreases point and nonpoint source pollution [Tang et al.,2005; Wang et al., 2008; Zhang et al., 2010], increaseswater temperature [LeBlanc et al., 1997], heavy metal pol-lution [Feng et al., 2004], and results in substantialincreases in total nitrogen, phosphorus, and suspended

solids levels [Atasoy et al., 2006]. Many previous studieshave linked measures of urbanization, such as land use–cover change, to changes in water quality [Fisher et al.,2000] and aquatic ecosystems [Walton et al., 2007].

[4] Generally, previous studies of urbanization and waterquality have focused on cities with a long history of urban-ization, such as Tampa, Shanghai, and Los Angeles [Xianaet al., 2007; Wang et al., 2008]. Many of these cities alsohave a complex geography and history, in which waterquality is affected by contemporary development on thesuburban fringe convoluted with legacy impacts of long-term, historic impacts in the city core, often going backmany decades to centuries.

[5] Very few studies, however, have focused on the envi-ronmental effects associated with special economic zones(SEZs), like that found in Shenzhen, China. SEZs are anincreasingly utilized policy employed by many countries toincrease economic development by using specific geo-graphic areas in which to attract foreign investment andcommerce through special tax incentives, greater depend-ence on international trade, and greater autonomy for enter-prises and development of infrastructure with foreigncapital. Also, governments of SEZs can exert substantialautonomous control on local regulations. SEZs have beenestablished in many countries including Angola, China,India, Brazil, and the Philippines. SEZs are critical areas inwhich to understand hydrologically because they representsome of the most important economic and population cen-ters of the twenty-first century, and because the pace anddensity of development is mostly unprecedented. Yet theenvironmental effects of development via SEZs are almostcompletely unknown, and thus it is unclear if there are dis-tinct effects of such dense and rapid development in com-parison with existing literature on urbanization and waterquality. Commensurately, it is unclear if policies and regu-lations are sufficient, or adequate, to ameliorate the effects

1State Key Laboratory of Earth Surface Processes and Resource Ecol-ogy/Academy of Disaster Reduction and Emergency Management, BeijingNormal University, Beijing, China.

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

3Nicholas School of the Environment, Duke University, Durham, NorthCarolina, USA.

Copyright 2011 by the American Geophysical Union.0043-1397/11/2011WR010491

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of SEZs on water quality, and thus support long-term, sus-tainable development.

[6] Here we focus on the world’s first SEZ, Shenzhen,China. Shenzhen was established under the Chinese Gov-ernment’s development plan in 1979. Shenzhen has attainedenormous development achievements in various social andeconomic undertakings, and since 1979, has been trans-formed from a frontier fishing town into China’s fastestgrowing city and third largest container port with an annualgrowth rate of 25.8% in recent years.

[7] As the first SEZ, Shenzhen provides the prototypefrom which to understand the potential water quality implica-tions of the global use of SEZs elsewhere. Water quality deg-radation and scarcity have been recognized as critical issuespotentially threatening the sustainable socioeconomic devel-opment of Shenzhen for some time. Thus, Shenzhen is a per-fect example in which to explore the relationship betweensurface water quality and rapid urbanization.

[8] In addition to its unique role as the first SEZ, Shenz-hen also provides some insights into the efficacy of localgovernment policy in curbing water quality degradationgiven the focus of local government efforts on environmen-tal regulation since the earliest times of Shenzhen as a SEZ[Profaizer, 1993].

[9] The main objectives of the present study are: (1) tocharacterize the spatial and temporal patterns of water qual-ity at a watershed scale in Shenzhen; (2) to uncover thefactors underpinning the water quality change; (3) to quan-titatively evaluate the relative contribution of land use–cover change and the metrics of economic developmentwith water quality; and (4) to evaluate the effectiveness ofseveral policies and regulations that seek to mitigate theworsening pattern of surface water quality. The results ofthe present study provide some of the first results fromwhich to guide decision makers and city officials inaddressing water quality degradation in SEZs worldwide.

2. Methods2.1. Study Area

[10] Shenzhen is a mountainous region, in SoutheastChina at the mouth of the Pearl River (Figure 1). Shenz-hen’s total land area is 1949 km2, with a population of 8.76million, and its climate is subtropical marine, with an aver-age annual rainfall of 1933.3 mm, and annual sunshine of2010.5 h. The annual average temperature is 22.4�C, with arange of 1.4�C–36.6�C.

[11] Shenzhen has more than 310 rivers and streams,which are generally grouped into eight watersheds: theShenzhen, Maozhou, Longgang, Guanlan, Pingshan, Buji,Dasha, and Xixiang Rivers (Figure 1). The Shenzhen, Maoz-hou, Longgang, Guanlan, and Pingshan Rivers each coversan area greater than 100 km2.

[12] Despite the numerous rivers and surface waters inShenzhen, water availability per capita is approximatelyone-third of the average in China. Thus, the pollution ofthis limited available surface water in Shenzhen poses asignificant problem in terms of public health and future de-velopment opportunities.

2.2. Analytical Methods[13] We sought to compile long-term water quality data

into comprehensive, synthetic indices in order to under-stand potential broad trends during the rapid developmentof Shenzhen. Moreover, we sought to develop a metric thatcould be easily compiled to continue evaluating in thefuture, and one that could be readily used in other SEZs.From 1991 to 2008, the Shenzhen Environmental Protec-tion Bureau established a monitoring program of nine waterquality parameters for the eight watersheds: permanganateconcentration, biochemical oxygen demand (BOD5), vola-tile phenols (Ar-OH), hexavalent chromium (Cr VI), plum-bum (Pb), cadmium (Cd), oil, total phosphorus (TP), and

Figure 1. Studied watersheds in Shenzhen, China.

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ammonia-nitrogen (NH3-N); details of the sampling programand protocol are given by the Report on Environmental Qual-ity of Shenzhen (Shenzhen Environmental Protection Bu-reau, unpublished data, 1991–2008). These data, along withland use for the eight watersheds from the Shenzhen Statisti-cal Yearbook (Shenzhen Statistical Bureau, unpublisheddata, 1991–2008), were used to develop a pollution index andquantify linkages with land use–cover change through time.Pollution indexes have been used in previous studies to com-pile many measures of water quality into singular indices inorder to examine broad spatial and temporal trends. Thismethod was developed by Xu [2005] and can be seen in thework of Li et al. [2009] for the Liuyanghe River watershed.

[14] A pollution index (PI) was defined according to thefollowing function:

PI ¼Xn

i¼1

PiWi; ð1Þ

where Pi is the single water quality parameter in each riverwithout units and Wi is the weight of each parameter. Pi

and Wi can be calculated with the formulas below.

Pi ¼ X1 þ X2; ð2Þ

Wi ¼IiPni¼1 Ii

; ð3Þ

where X1 is the level of the water quality parameter accord-ing to GB3838–2002, which is the environmental qualitystandard for surface water in China, set by the State Envi-ronmental Protection Administration (hereafter calledGB3838-2002), X2 is the decimal fraction, which showsthe degree of the water quality parameter in the interval ofthe X1 level. For instance, if the concentration of NH3-N is1.2 mg L�1, it is classified as level III (1–1.5 mg L�1)according to national standard GB3838-2002 (Table 1).Then X1 ¼ 3 and X2 ¼ (NH3-N-1)/(1.5 �1) ¼ 0.4 are putinto formula (2), and Pi ¼ 3.4.

[15] In equation (3), Ii can be calculated using:

Ii ¼Ci

Si; ð4Þ

Ii ¼Si

Ci; ð5Þ

where Ci is the actual value of parameter i, Si is the mean ofthe special level according to national standards GB3838-2002 for parameter i. Equation (4) is applied when parame-ters have higher concentrations and equation (5) is used forlower concentrations.

[16] The integrated pollution index (IPI) for all water-sheds was also evaluated using

IPI ¼Xn

j¼1

PIjAj; ð6Þ

where Aj is the weight of each watershed with no units anddefined according to the ratio of the area of each watershedto total area of all watersheds.

[17] There are many indices available to assess urbaniza-tion levels, such as land use–land cover features, humanpopulation, and housing density [Fisher et al., 2000; Waltonet al., 2007]. In China, the ratio of nonagricultural popula-tion to total population is generally used as a standard toevaluate the urbanization level of a city. However, since2003, all residents living in Shenzhen City have been classi-fied as urban residents, making it impossible to evaluateurbanization rates in China with previously used methods.Thus, we have used the measure of impervious surfaces,including buildings and roads, to evaluate urbanization lev-els. In this method, the ratio of impervious surface areas(RISA) was used as an equivalent to the urbanization level.

[18] As the eight watersheds were connected spatially,there may be a close connection among them and the char-acter of water quality may be similar among several water-sheds. Thus, cluster analysis on PI values of each watershedwas used to evaluate the similarity of surface water qualityamong the eight watersheds, using a criterion value of arescaled distance between four and five. Following this,paired t-tests were used to exam the variances between anytwo groups.

[19] Also, variances of each parameter and PI values ineach group were calculated to exam the fluctuation and tomeasure the changes of water quality.

3. Results3.1. Grouping of Surface Water Quality and ItsDescriptive Statistics

[20] The cluster analysis showed that four groups wereidentified according to the PI values of each watershed(Figure 2). Group A included the Dasha, Longgang, andPingshan Rivers ; group B rivers were the Guanlan, Maoz-hou, and Xixiang; group C, the Buji River; and group D,the Shenzhen River (Figure 2). The mean values of NH3-N,TP, BOD5, and oil were 14.6, 1.61, 23.56, and 1.05 mg l�1

respectively, which were about 7, 4, 2, and 1 times the re-spective levels V of GB3838-2002. However, the means ofCr VI, Pb, and Cd were all lower than the respective levelsII of GB3838-2002 for the entire Shenzhen area (see thesummary of the parameters and index in Table 2). Accord-ing to GB3838-2002, mean concentrations for BOD5, TP,and NH3-N exceeded level V in each group and for theentire Shenzhen area, implying that the main pollutants arefrom organic and nutrient sources. Other parameters greaterthan level V included oil for groups C and D; and

Table 1. Value of Surface Water Standard Concentration for FiveGrades in Chinaa

Parameter

Grade

I II III IV V

CODMn � 2 4 6 10 15BOD5 � 3 3 4 6 10Ar-OH � 0.002 0.002 0.005 0.01 0.1Cr VI � 0.01 0.05 0.05 0.05 0.1Pb � 0.01 0.01 0.05 0.05 0.1Cd � 0.001 0.005 0.005 0.005 0.01Oil � 0.05 0.05 0.05 0.5 1TP � 0.02 0.1 0.2 0.3 0.4NH3-N � 0.15 0.5 1 1.5 2

aAll units are in mg L�1. Data according to State Environmental Protec-tion Administration [2002]; (GB3838-2002).

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parameters greater than level IV included CODMn andAr-OH for groups B–D. However, the mean concentrationsof Cr VI, Pb, and Cd do not exceed level III for all groupsand the Shenzhen area.

[21] The water quality parameters for group A generallyshowed a lower value of all the parameters compared withother groups, implying that group A’s water is compara-tively less impacted. Regarding the mean value of PI, group

C (Buji River) showed the largest values, followed bygroups B, D, and A. The paired t-tests indicated significantdifferences existed between any two groups, except groupsB and D (p < 0.05). A large variability in PI was examinedin groups B and C, with standard deviation values greaterthan 15. Similarly, parameters such as CODMn, BOD5, TP,and NH3-N also varied greatly, suggesting a significantfluctuation in surface water quality.

Figure 2. Dendrogram of watersheds according to PI cluster analysis.

Table 2. Descriptive Statistics of Four Categories of Watersheds and Integrated Index in Shenzhena

Group CODMn BOD5 Ar-OH Cr VI Pb Cd Oil TP NH3-N PI

A Min. 3.77 3.66 0.00 0.00 0.00 0.00 0.11 0.14 3.43 4.61Max. 15.65 30.33 20.00 130.00 20.00 0.00 1.92 2.11 17.39 10.10Mean 8.78 14.23 7.00 13.00 6.00 0.20 0.61 1.06 11.12 7.56

SD 3.43 8.53 5.00 20.00 5.00 0.20 0.43 0.57 3.16 1.37B Min. 3.50 2.10 0.00 0.00 0.00 0.00 0.08 0.03 8.58 5.64

Max. 25.30 64.10 30.00 30.00 30.00 10.00 2.58 4.85 29.27 15.12Mean 13.22 23.8 10.00 10.00 6.00 2.00 0.92 2.16 16.07 9.69

SD 6.02 17.02 7.00 8.00 5.00 3.00 0.61 1.58 6.09 2.86C Min. 10.93 17.80 10.00 0.00 0.00 0.00 0.21 1.40 15.88 9.97

Max. 27.90 80.00 2180.00 10.00 230.00 0.00 5.14 3.43 27.25 18.64Mean 18.86 49.07 210.00 2.00 19.00 0.40 2.04 2.42 21.42 11.94

SD 4.77 17.81 520.00 2.00 50.00 0.50 1.63 0.62 3.23 2.04D Min. 7.05 8.50 10.00 0.00 0.00 0.00 0.05 1.06 7.72 7.16

Max. 15.00 37.80 60.00 10.00 40.00 0.00 2.54 2.37 16.69 10.06Mean 10.32 18.73 20.00 2.00 9.00 0.30 1.04 1.45 13.20 8.58

SD 2.27 7.16 12.00 1.00 12.00 0.30 0.89 0.33 2.42 0.73Total Min. 3.50 2.10 0.00 0.00 0.00 0.00 0.05 0.03 3.43 4.61

Max. 27.90 100.10 2180.00 130.00 230.00 10.00 5.14 4.85 29.27 18.64Mean 12.34 23.56 40.00 13.00 9.00 1.00 1.05 1.61 14.60 8.98

SD 5.92 19.51 190.00 20.00 20.00 2.00 0.97 1.14 5.64 2.55

aUnits of CODMn, BOD5, oil, TP, and NH3-N are in mg L�1; units of Ar-OH, Cr VI, Pb, and Cd, are in mg L�1; PI does not have units.

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3.2. Yearly Changes in the Pollution Index of DifferentWatersheds and the Shenzhen Area

[22] From Figure 3, four different temporal trends of PIcould be classified. Group A showed as an ‘‘M’’ type withtwo top values of mean PI (�9 and 8.7) occurred in 2000and 2006, respectively. Group B showed as an inverted‘‘V’’ shape, with a long left and a short, sharp right shape,and the maximum of mean PI (�14) in 2006. However,group C showed a linear increasing type with the exceptionof two outliers which occurred in 1990 and 2001, and groupD showed a ‘‘U’’ shape, with the minimum of the mean PIin 2001 (Figure 3). On the basis of the IPI for the entireShenzhen area, a gentle increasing trend was shown in the1990s, followed by a sharp increase through 2006, then adecrease after 2006 (Figure 4). Additionally, curves withlong left tails were found for groups A, B, and the Shenz-hen area, reflecting a developing phase of ‘‘postpollutiontreatments’’ (Figures 3 and 4).

3.3. Relationship Between Water Pollution Index andLand Use Types

[23] There was a positive correlation between PI andRISA for groups A and B (p < 0.01; Figure 5). However, anegative correlation between the PI and the RISA was found

for the Shenzhen River (Figure 5), while no significant cor-relation was found for the Buji River (data not shown).

[24] To establish the general pattern of the entire Shenz-hen scale, we also analyzed the relationship between the IPI

Figure 3. The yearly changes in the pollution index in four groups of watersheds in Shenzhen.A) Dasha, Longgang and Pingshan Rivers. Group; B) Guanlan, Maozhou and Xixiang Rivers; C) BujiRiver; D) Shenzhen River.

Figure 4. The yearly change of the integrated pollutionindex in Shenzhen.

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and the RISA (Figure 6). The results showed a gradualincrease of the IPI before the RISA reached 0.3, then a sharpincrease of the IPI, peaking when the RISA reached 0.4,followed by a sharp decrease. This result on a macrolevelindicated a significant positive correlation between the IPIand the RISA prior to the ratio reaching 0.4, when it becamea negative correlation (Figure 6). The Shenzhen River isrepresented in the right-hand side of Figure 6.

4. Discussion4.1. Urbanization and Surface Water Quality

[25] Our study is one of the first to document the waterquality effects of rapid, intense urbanization associated witha SEZ. The results of this study are important in indicatingsome trends which may not be readily observed in studies ofmore gradually, spatially diffuse urbanization like that associ-ated with urban sprawl in the United States. Indeed, the tem-poral dynamics of development had substantial impacts onwater quality trends, allowing us to observe coupling betweenbroad political and economic forces on water quality.

[26] Shenzhen’s development can be divided into threestages: first, the process of when settlement and land useconversion began (1980–1992); second, the rate of devel-opment increased, dramatically speeding up (1993–2002);and third, the potential for a transformation stage (2003–)in which impacts from development were mitigated tosome degree. The most notable pattern from our data is thatfrom 1991 and into the second stage of Shenzhen’s devel-opment (1993–2002), the water quality of most of Shenz-hen’s rivers (groups A–C) worsened due to the impact ofthe rapid urbanization process.

[27] Among the watersheds in Shenzhen, the Shenzhenand Buji Rivers were unique, as they have been affected byboth ‘‘special economic zone development’’ and their prox-imity to Hong Kong. The RISA of these two watershedswere both larger than 0.4 in 1991, and the surface waterquality lower than level V prior to the 1980s [Huang andWang, 2007]. The two rivers also impact each other, as theBuji River is upstream of the Shenzhen. For example, thePI for the Shenzhen River increased again in 2007 becauseof pollution from the Buji River.

[28] Economic development and increases in the RISAwere the result of the urbanization process, and were twokey factors in the quality of surface water. As has beenshown in many other studies, RISA was correlated withsurface water quality, with a correlation of 0.88 (p <0.001) in the result of correlation analysis.

4.2. Economic Development and Water Quality[29] It was not particularly surprising that urbanization

and RISA were correlated with water quality. However,RISA analyses were not able to explain the pollution indexin 2008 (Figure 6), in which RISA did not decline, yet thepollution index did decline. There are two possible explan-ations for this.

[30] First, economic development may be an additionalcorrelate of water quality, and this may be more pro-nounced in SEZs than in other areas. Because of the focuson economic development in this SEZ, we had fairly robust

Figure 5. The relationships between the ratio of impervi-ous surface and pollution index in Shenzhen.

Figure 6. The relationship between the ratio of impervi-ous surface and integrated pollution index in Shenzhen.

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economic data at the regional, and found that the PI wascorrelated with per capita gross domestic product (GDP)(r2 ¼ 0.73, p < 0.001). Prior to 2000, the speed of eco-nomic development and the increment of the RISA wereboth �21%; after 2000 there was an obvious differencebetween the two, with the speed of economic developmentsurpassing the increment of the RISA, 31% and 9%, respec-tively. The PI increment increased from 10% to 16% at thesame time, which illustrates that economic developmentshowed greater influence, as urban land use developmentwas limited by land use–cover change. These results sug-gest that economic development may cause greater envi-ronmental pollution once urban development reaches aparticular level, perhaps because of the increased impact onalready impervious areas.

[31] The second broad explanation for the changes inwater quality relies on the theoretical economic argumentof the environmental kuznets curve (EKC). According tothe EKC, environmental degradation will increase duringinitial stages of economic development, but then impactswill decrease after a certain critical point of development.In our case, water quality will degrade as industry and pop-ulation increase, but after a point water quality will beginto improve either because high polluting industries moveelsewhere or because policies are implemented to reducepollution.

[32] Indeed, when analyzed in combination with eco-nomic data, the IPI of Shenzhen City fits the invertedU-shaped curve with a vertex close to $8000 (r2 ¼ 0.91 andp < 0.01), which occurs in 2006 (Figure 7). These resultsindicate that the water pollution issue worsened beforeGDP per capita reached $8000 in 2006, and that the waterquality has gradually improved since this income level wassurpassed in Shenzhen. The turning point in our study,occurring at $8000, falls in the range of $5000–$8000,identified by Zhao et al. [2005].

[33] Ours is not the first to speculate the EKC as a possi-ble explanation of degrading and then improving waterquality. Such a relationship between environmental degra-dation and per capita income in the context of the EKC hasbeen proposed by several studies in a range of regional con-ditions [Grossman and Krueger, 1991; Stern et al., 1996;Fatma and Osman, 2001], as well as major cities in China

[Wang et al., 2008]. However, our study is the first to haveconsidered applying the EKC to a SEZ such as Shenzhen.

[34] There are other possible explanations for the waterquality changes since 2006 in Shenzhen. Most notably, SEZsare particularly susceptible to macroeconomic changes, andthe economic recession began to effect global economies inlate 2007 and the years following. It is possible that thedecrease in the global economy led to decreased demand forproducts manufactured in Shenzhen, which resulted in mod-erated impacts on water quality. Indeed, other studies haveshown that changes in global economy can shift populationdistributions sufficient to impact regional environmentalcharacteristics [Song et al., 2008]. However, GDP in Shenz-hen increased even after 2007, which suggests that the influ-ence of economic recession was not as relevant in Shenzhen,but another explanation can be that manufacturing wasimpacted while other professions developed.

[35] It is likely that a combination of factors is influenc-ing the stabilization and potentially downward trend in PIin Shenzhen that can be explained partly by global eco-nomic drivers and by the concepts contained in the EKC.One change that is clear is the implementation of environ-mental policies for improving water quality. For instance,while Shenzhen has seen persistent pollution from bothindustry and urban areas, reaching as high as 1.1 billiontons in 2004, there has also been increased pressure forenvironment protection. As a result, the government invest-ment in environmental protection increased gradually until2004, and has increased sharply since then. The per capitainvestment and the investment per unit area of impervioussurface in environmental protection both showed a substan-tial increase, particularly since 2004 (Figure 8).

[36] In fact, following the developed countries, many meas-ures were adopted and many policies have been promulgatedby governments at all levels including the Central govern-ment, the Guangdong Province government, and the Shenzhengovernment to control and manage the water environment,which resulted in the promulgation of environmental laws,investment in environmental protection, and the constructionof wastewater treatment plants. For instance, over the pastdecade, 25 sewage treatment plants have been built in Shenz-hen. Consequently, the portion of industrial sewage treatedhas reached 100%, and the portion of urban sewage treatedhas reached more than 75% (inset of Figure 8). However, it isalso clear that improvement of water quality in Shenzhen willrequire continued efforts and time (Figure 4), although thedecline in PI may be an indication that some of these invest-ments in infrastructure and policy are beginning to pay divi-dends (Figures 4 and 8, and the supplement material).1

[37] Despite these improvements, in Shenzhen, and else-where in China, economic development and industrializationare often given a higher priority than environmental protec-tion [Shen et al., 2002]. Our results suggest that the speed ofeconomic development can lead to dramatic impacts on sur-face water quality. Unfortunately, the imbalances in the racefor economic development make it impossible for every cityto obtain the same level of protection for its natural envi-rons. Although the IPI for the Shenzhen area is falling, the

Figure 7. The relations between GDP per capita and theintegrated pollution index in Shenzhen, from 1991 to 2008.

1Auxiliary materials are available in the HTML. doi:10.1029/2011WR010491.

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PI for each river is not (Figure 3), which reflects the differ-ent situations and environmental characteristics.

5. Conclusion[38] This paper investigates the temporal variations in

surface water quality in Shenzhen by analyzing the datafrom eight watersheds in Shenzhen between 1991 and 2008.The results indicate that urban development levels, repre-sented by economic development and the RISAs, have a sig-nificant effect on surface water quality. Results also indicatethat water quality in SEZs may be unlike more traditionalurban areas by having a greater correlation with economicindicators than with simple metrics of land use change.

[39] Our results also show that every region has its ownunique circumstances, and the assessment of water qualitycannot be conducted solely at a macrolevel. Policies andmeasures must be appropriate for local situations, as anygiven watershed may be affected by more than one factor.In addition, local government must consider the delay(a 4-yr delay for Shenzhen City) between policy implemen-tation and recovery, and have the foresight to accommodateboth development and the natural environment. Mostimportantly, local government should strengthen the con-trol of both pollution sources, with economic developmentbeing the greater influence in the third stage, and our levelsof environmental awareness must be raised.

[40] As the world’s first SEZ, Shenzhen can be a usefulcase to explore the potential problem or environment con-sequences incurred by SEZ or other rapid urbanizationareas. Many SEZs have been set up throughout the world inthe past two decades following Shenzhen model, such asSubic Bay Metropolitan Authority in the Philippines, Chit-tagong in Bangladesh, the East Coast Economic Region

SEZ in Malaysia, etc. Such SEZs could potentially attainthe rapid economic achievements like Shenzhen; however,the policy-makers should realize the attendant cost of envi-ronmental degradation.

[41] Acknowledgments. This study was funded by National BasicResearch Program of China (2012CB955404), the Fundamental ResearchFunds for the Central Universities, State Key Laboratory of Earth SurfaceProcesses and Resource Ecology (2010-ZY-10), and International Coopera-tion Project, the Ministry of Science and Technology of China (40821140354,2010DFB20880). We are grateful to the editor and two anonymous reviewersfor their insightful comments on an earlier version of this manuscript.

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Y. Chen, S. Du, P. Shi, and Z. Zhang, State Key Laboratory of EarthSurface Processes and Resource Ecology/Academy of Disaster Reductionand Emergency Management, Beijing Normal University, 19 Xin Jie KouWai Street, Haidian District, Beijing 100875, China. (zhangzhao@bnu.edu.cn)

M. Doyle, Nicholas School of the Envinronment, Duke University, Box90328, Durham, NC 27708-0328, USA.

F. Tao, Institute of Geographical Sciences and Natural ResourcesResearch, Chinese Academy of Sciences, Beijing 100101, China.

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