impacts of climate change and land use change on runoff of forest catchment in northeast china

HYDROLOGICAL PROCESSESHydrol. Process. 28, 186–196 (2014)Published online 23 October 2012 in Wiley Online Library(wileyonlinelibrary.com) DOI: 10.1002/hyp.9564

Impacts of climate change and land use change on runoff offorest catchment in northeast China

Yongfang Zhang,1,2 Dexin Guan,1 Changjie Jin,1 Anzhi Wang,1* Jiabing Wu1 and Fenghui Yuan11 State Key Laboratory of Forest and Soil Ecology, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110164, P. R. China

2 Graduate University of Chinese Academy of Sciences, Beijing, 100049, P.R. China

*CAcP.E-m

Co

Abstract:

Hydrological processes change from the impacts of climate variability and human activities. Runoff in the upper reaches of theHun-Taizi River basin, which ismainly covered by forests in northeast China, decreased from1960 to 2006. The data used in this studywere based on runoff records from six hydrological stations in the upper reaches of the Hun-Taizi River basin. NonparametricMann–Kendall statistic was used to identify change trends and abrupt change points and consequently analyze the changecharacteristics in hydrological processes. The abrupt change in the annual runoff in most subcatchments appeared after 1975. Finally,the effects of climate change and land cover change on water resources were identified using regression analysis and a hydrologymodel. Results of the regression analysis suggest that the correlation coefficients between precipitation and runoff prior to the abruptchange were higher compared with those after the abrupt change. Moreover, using hydrology model analysis, the water yield wasfound to increase because of the decrease in forest land. Copyright © 2012 John Wiley & Sons, Ltd.

KEY WORDS runoff trends; Mann–Kendall test; change-point analysis; climate variability; land use/cover change

Received 15 February 2012; Accepted 18 September 2012

INTRODUCTION

Climate variability changes the annual runoff and theseasonal distribution of runoff, affecting water resourcesavailability and ecosystem environments. The increase inglobal average surface air temperature during the 20thcentury caused by anthropogenic activities, which raiseatmospheric concentrations of carbon dioxide and othergreenhouse gases, has been widely recognized (Houghtonet al., 2001). The water cycle is accelerated becausethe air-holding capacity of water vapor exponentiallyincreases when the climate becomes warmer (Brutsaertand Parlange, 1998; Huntington, 2006). Regional changepatterns in surface hydroclimate are complex. The rise inglobal temperature and the change in precipitationpatterns have significant impacts on the changes in runoffregimes (Milly et al., 2005; Chen et al., 2006; Huo et al.,2008). With increases in precipitation variability and airtemperature, water moves at different rates and amountsat various periods in the hydrologic cycle. Spatial andtemporal changes in runoff regime will potentiallythreaten regional water resource sustainability (Chang andJung, 2010). Information about observed and anticipatedchanges in the climate systemwas summarized in the FourthAssessment Report of the Intergovernmental Panel onClimate Change (Solomon et al., 2007), which related thatglobal warming has exhibited an accelerative tendency sincethe 1910s.Global annualmean temperature has increased by

orrespondence to: Anzhi Wang, Institute of Applied Ecology, Chineseademy of Sciences, P. O. Box 417, Shenyang 110016, P. R. China,R. Chinaail: [email protected]

pyright © 2012 John Wiley & Sons, Ltd.

0.74�Cduring the last century and is predicted to increase by1.1�C to 6.4�C by 2100. The temperature in China hasincreased by 0.4�C to 0.5�C from 1860 to 2005 (Li et al.,2010). China has experienced unusual climate events, suchas the continuous and particularly dry climate during the1990s (Yang et al., 2004). Studies have shown that theclimate continuously becomes warmer and drier in theHun-Taizi River catchments, which is consistent with that ofChina (Ren et al., 2005).Studies on climate change traditionally include both the

development of possible future projections and the analysisof possible climate change signals in historical data. Theeffects of climate change on runoff have been largelydiscussed using the general circulation model’s (GCM)projection on global warming (Arnell, 1999). The GCM’sprojection depends on various scenarios assumed forgreenhouse gas emission, making its accuracy questionable(Yang et al., 2004; Gardner, 2009). Meanwhile, studies thatdetect the relationship between climate and hydrologicalvariability based on historical data can provide referencesfor studies on the impact of climate fluctuations on waterresources, in which changes can be detected annually andmonthly. In some cases, annual averages may remainunchanged although monthly averages change (Wilsonet al., 2010). Such phenomenon is commonly investigatedusing the trend analysis method (Burn andHag Elnur, 2002).To better understand the changes in a watershed

hydrologic cycle, knowledge on the natural response ofrunoff to climatic change and the quantification of theimpacts of human activities on river runoff are necessary(Xu et al., 2008). Land use changes induced by humanactivities, such as deforestation or forestation, agricultural

187IMPACTS OF CLIMATE AND LAND USE CHANGE ON RUNOFF OF FOREST CATCHMENT

development, and urban construction (such as irrigation anddrainage), have direct effects on hydrological processes(Fohrer et al., 2001), and they can also affect the hydrologiccycle (Ren et al., 2002; Huo et al., 2008). Some studies haveshown that runoff is significantly affected by land coverchanges and that cutting down forests leads to an increase inrunoff (Bosch and Hewlett, 1982; Matheussen et al., 2000;Costa et al., 2003; Brown et al., 2005; Siriwardena et al.,2006). Hibbert (1967) showed that reduction in forest coverincreases water yield, and vice versa. Bosch and Hewlett(1982) showed that the water yield increased to 100mm asthe percentage of forest decreased by 20%. The claim thatthe water balance in an area changes in response toalterations in land use remains controversial (Sahin andHall, 1996). On the other hand, Wilk and Andersson (2001)showed that hydrological responses to alteration of forestcovers are insignificant in large-scale catchments. Paired orreplication methods are popular studies on small-scalewatersheds (< 100 km2), but they are not feasible for large-scale watersheds, in which suitable controls are difficult tofind (Fohrer et al., 2005). Moreover, results from small-scalewatersheds are difficult to apply to large-scale watersheds.Lack of information on the hydrological impacts of large-scaleforest disturbances greatly constrains researchers from devel-oping forest and watershed management strategies on large-scale watersheds (Lin and Wei, 2008), and thus, alternativeapproaches must be explored. The watershed water balancemodel is probably the best tool for assessing water-yieldchange caused by land cover change (Sun et al., 2006).The population of China has tripled during the last

50 years of the 20th century. The pressure of the increasingpopulation has caused the water crisis to become moreserious in northern China (Yang et al., 2004). The Hun andTaizi Rivers are main tributaries of the Liao River innortheast China. The upper reaches of the Hun-Taizi basinare the main components of the water sources of the LiaoRiver. Thus, runoff change in the upper forest reaches of theHun-Taizi basin will affect all the hydrological processes ofthe Liao River. The idea that hydrological processes arecontrolled by climate and land surface characteristics iswidely accepted. Changing land cover is usually recognizedas having influence on the interception of overland flow andtotal water yield. This study aims to determine the changingcharacteristics of the annual runoff in the upper reaches ofthe Hun-Taizi basin in northeast China and to assess theeffects of climate variability and land cover change onrunoff. Change trends and abrupt change points of the runoffin six hydrological stations were detected using the Mann–Kendall trend test and the sequential version of the Mann–Kendall test method (Mann, 1945; Kendall, 1975). Thewater balance model was applied to project change in wateryield and to detect the effects of land cover change on runoff.

MATERIALS AND METHODS

Study area

The Hun-Taizi basin is located in northeast China withlongitude of 122.0�E to 125.5�E and latitude of 40.5�N to

Copyright © 2012 John Wiley & Sons, Ltd.

42.5�N. The Hun-Taizi River basin covers an area of27 327 km2, in which the Hun River basin covers11 481 km2 and the Taizi River basin covers 13 883 km2.The Hun and Taizi rivers originate from the ChangbaiMountain in northeast China and flow into the Liao River,and they function as water sources for the LiaoningProvince. The study area covers the upper reaches of theHun-Taizi River basin, including six subcatchmentscovered mainly by forest and with temperate continentalmonsoon climate. The upper reaches of the Hun River basininclude two subcatchments (HHW-Hunhewaterhead andHSZH-Hunsuzihe), whereas the upper reaches of theTaizi River basin include four subcatchments (TZHW-Taizihewaterhead, XH-Xihe, LH-Lanhe, and TH-Tanghe).Figure 1 shows the locations of the study area and theobservation stations. Table I lists the characteristics of thehydrological stations.

Data

Daily runoff data from six hydrological stations in thestudy area from 1960 to 2006 were used to analyze changetrends and points. Observations from 34 rainfall stationsand 11 meteorological stations located within and near thebasin were chosen to calculate total monthly and annualprecipitation. The daily average wind speed, relativehumidity, sunshine hours, minimum air temperature, andmaximum air temperature were also used. The Penman–Monteith equation recommended by the Food and Agricul-ture Organization (FAO) (Allen et al., 1998) was used tocalculate potential evapotranspiration.Land use/cover data (at 1:100 000 scale) for two periods,

1980 and 2000, were obtained from the Chinese NaturalResources Database. Land use data mainly describe sixtypes in level-one classes, including farmland, forestland,grassland, water body, residential area, and bare land.

Trend tests

The Mann–Kendall trend test (Mann, 1945; Kendall,1975) was applied in this study. The Mann–Kendall trendtest can effectively detect change trends in long-time seriesof hydrological and meteorological data (Li et al., 2007;Muet al., 2007; Ma et al., 2008; Zhang and Lu, 2009). TheMann–Kendall test is one of the most widely usednonparametric tests. Compared with parametric statisticaltests, nonparametric tests are thought to be more suitable forhydrometeorological time series data that are not normallydistributed (Yue et al., 2002). Moreover, theMann–Kendalltest is a rank-based method based on the proportionatenumber of subsequent observations that exceed a particularvalue (Hamed, 2008).TheMann–Kendall’s statistic can be expressed as follows:

S ¼Xn�1

i¼1

Xnj¼iþ1

Sgn xj � xi� �

(1)

where xi(i=1, 2, . . ., n� 1) and xj(j= i+1, . . ., n) are thesequential data values and n is the length of the data series,and sgn denotes the sign function.

Hydrol. Process. 28, 186–196 (2014)

Figure 1. Locations of the study area and the main rainfall and hydrological stations in the Hun-Taizi River basin (A-HHW, B-HSZH, C-TZHW, D-XH,E-LH, and F-TH)

Table I. Characteristics of the six subcatchments in the upper reaches of the Hun-Taizi River

Subcatchment Hydrological stations Control area (km2) Average runoff (mm) Average precipitation (mm)

Hunhe waterhead (HHW) Beikouqian 1832 314 755Hunhe waterhead (HSZH) Zhanbei 2040 261 766Taizihe waterhead (TZHW) Benxi 4324 322 800Xihe (XH) Qiaotou 1023 335 787Lanhe (LH) Libiyu 417 223 729Tanghe (TH) Tanghe reservoir 1228 191 761

188 Y. ZHANG ET AL.

The standard normal Zc statistic can be calculated asfollows:

Zc ¼

s� 1ffiffiffiffiffiffiffiffiffiffiffiffiffiVar S½ �p0

sþ 1ffiffiffiffiffiffiffiffiffiffiffiffiVar s½ �p

s > 0s ¼ 0s < 0

8>>>><>>>>:

(2)

With normal distribution, the variance values are given by:

var s½ � ¼ n n� 1ð Þ 2nþ 5ð Þ18

In a two-side test, a null hypothesis for no trend isaccepted when |Zc|≤Z1� a/2, where a is the significancelevel and Z1� a/2 is the standard normal quantile(at probability level 1� a/2). Zc<� Z1� a/2 indicates a


decreasing trend, while Zc> Z1� a/2 indicates an increasingtrend (Mann, 1945; Kendall, 1975). At a specified level ofsignificance of a, standard Z1� a/2 value can be obtainedfrom the table of standard normal distribution. In this study,a was set at 0.05 significance level and Z1� a/2 = 1.96.

Change point analysis

The sequential version of the Mann–Kendall test(Sneyers, 1975) was applied to detect the abruptchange against trend. In the sequential version of theMann–Kendall test, the time series is presumed to bestationary, and the elements are random and independentfrom one another (Liu et al., 2009). The null hypothesisstates that the samples under investigation show nobeginning of a developing trend. The test statistic wasdetermined as follows:

Hydrol. Process. 28, 186–196 (2014)


Sk ¼Xki¼1

ri (3)

Let x1, x2, . . . xn be the data values, ri is the rank ofseries, as xi exceeded xj (j< i), the numbers ri werecalculated, k(k= 1,. . .,n) is the size of the sample.The mean of test statistic Sk is zero, and variance values

of Sk can be calculated as follows:

Var Skð Þ ¼ k k � 1ð Þ 2k þ 5ð Þ72

(4)

A reduced variable, called statistic ufk, is calculated foreach of the test statistic variables Sk as follows:

ufk ¼ Sk � E Skð Þ½ �ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiVar Skð Þp (5)

where ufk is the forward sequence and ubk is the backwardsequence. ubk can be calculated using functions (3)–(5),but with the reverse data series. The points of ufkconstitute the forward sequence uf. Similarly, a backwardseries ub of statistic ubk can be calculated using functions(3)–(5) backwards starting from the end of the originaltime series.In a two-sided trend test, when |(ufk)|≤ Z1� a/2 for all

k (where Z1� a/2 is, as before, the standard normalquantile at probability level 1� a/2), the null hypothesiscannot be rejected, i.e. no significant trend is detected. Allpoints in uf are inside the confidence interval and thesequences uf and ub overlap several times. When instead |(ufk)|>Z1� a/2 for at least one value of k, the nullhypothesis is rejected and a statistically significant trend(either increasing or decreasing) is revealed within theoriginal time series. The intersection point of the curvesuf and ub provides the point in time of the beginning ofthe trend development. (Demaree and Nicolis, 1990; Fuand Wang, 1992; Moraes et al., 1998; Li et al., 2007). Adetailed description of the nonparametric test can befound in the study of Sneyers (1975).

Regression analysis

Regression analysis was used to measure the strength ofthe relation between climate, namely precipitation, andrunoff. Based on the results of the abrupt change pointanalysis, the period of runoff record for each subcatchmentwas divided into two parts, namely, ‘the period before theabrupt change’ representing runoff under natural conditionsand ‘the period after abrupt change’ representing runoffunder the influence of land use change. The relationshipbetween precipitation and runoff during the two periods wasanalyzed. Comparisons of correlation coefficients for thetwo periods indicates the decrease in the dependence ofrunoff on precipitation.

Response of land use/cover change to water-yield model

Hydrological sensitivity can be used to measure theresponse of land use change and climate change to runoff,


which can be defined as the percentage change in meanannual runoff that occurs in response to a change in meanannual precipitation and potential evapotranspiration. Thewater balance in a catchment can be quantified as follows:

P ¼ E þ Qþ ΔS (6)

where P is the precipitation, E is the actual evapotrans-piration, Q is the runoff, and ΔS is the change in waterstorage in the catchment. Over a long period of time(e.g. 5 to 10 years), ΔS may be reasonably assumed to bezero (Zuo and Wang, 2006; Ma et al., 2008).For the two periods, namely, before- and after-land use/

cover change, the water balance in a catchment can bedescribed as follows:

For the before-land use/cover change period:

P1 ¼ Q1 þ E1 � ΔS1 (7)

For the after-land use/cover change period:

P2 ¼ Q2 þ E2 � ΔS2 (8)

Then, the effects of climate and land cover change onwater yield can be quantified as follows:

Q2 � Q1 ¼ P2 � P1 þ E1 � E2 � ΔS2 � ΔS1ð Þ (9)

The amount of change in soil water storage is assumed tobe similar during the two periods (ΔS2�ΔS1 = 0), andthus, the change in Q caused by land cover change can beexpressed as the change in precipitation and evapotrans-piration between the two periods as follows:

ΔQ ¼ P2 � P1 þ E1 � E2 (10)

The annual actual evapotranspiration (E) can be calcu-lated using the model (Equation (11)) developed byZhang et al. (2001) as follows:

E ¼ ð 1þ mPETP

1þ m PETP þ P

PET

Þ � P (11)

where m is the model parameter related to vegetation type,hydraulic property, and topography (Sun et al., 2005) andPET is the potential evapotranspiration obtained using thePenman–Monteith equation recommended by FAO (Allenet al., 1998). For a watershed withmixed land uses,E can becalculated as follows:

E ¼X

Ei � Rið Þ (12)

whereRi is the percentage of each of the land use types, suchas grass land, crop land, and forest land (Sun et al., 2006).Them parameter was set to 0.5 for short grass and crops and2.0 for forests (Sun et al., 2005). The water-yield model hasthe potential to be used to examine the sensitivity of wateryield in response to land use.

Hydrol. Process. 28, 186–196 (2014)

190 Y. ZHANG ET AL.

RESULTS AND DISCUSSION

Annual temperature and precipitation trends

The long-term trend in hydrological processes is naturallyaffected by climate change. The analysis of the historicaltrend in climate variables may help reveal the effect ofclimate change on water resource systems (Chen et al.,2006). The subcatchments have an average annual precipi-tation of 700mm to 850mm. Precipitation in the upperreaches of the Hun-Taizi River basin is relatively stable,decreasing at a rate of 9.77mm/10 yr from 1960 to 2006.The subcatchments have an average annual temperature of5.96�C to 8.05�C, which increased at the rate of 0.3�C/10yrin the upper reaches of the Hun-Taizi River basin during thestudy period.Figure 2 shows the Mann–Kendall trend test results with

the standard normal statistic (2) computed over the annualprecipitation and temperature series for the six subcatch-ments from 1960 to 2006. As can be seen in Figure 2,all subcatchments, except for the HHW subcatchment,exhibited negative annual trends of precipitation (1960 to2006). Based on the Mann–Kendall analysis, all the trendsof the six subcatchments are statistically insignificantwith Zc values of 0.42, �1.06, �1.19, �0.68, �0.79, and�1.33 for HHW, HSZH, TZHW, XH, LH, and TH,respectively. The results of the analysis on the annual meantemperature of the six subcatchments show that all thesubcatchments have positive Zc values, indicating an

Figure 2. Mann–Kendall trend test for annual precipitation andtemperature in the six subcatchments in the study area (1960–2006)

Figure 4. Mann–Kendall trend test for annual precipitation (a) and temperaturmeteorological stations in th


obvious increasing trend in temperature from 1960 to2006. HHW, HSZH, TZHW, XH, LH, and TH hadstatistical Zc values of 3.63, 3.60, 0.97, 4.05, 4.07, and4.64, respectively. Zc values greater than 1.96 indicated asignificant increase trend, and thus, only the TZHWsubcatchment was found to have an insignificant increasetrend. Annual temperature in the HHW, HSZH, TZHW,XH, LH, and TH basins increase at a rate of 0.28, 0.28, 0.09,0.31, 0.30, and 0.36�C/10 yr, respectively. The abruptincrease in the average annual temperature in the upperreaches of the Hun-Taizi River occurred in 1993, as shownin Figure 3, where the intersection of the forward (uf) andbackward (ub) curves indicate an abrupt change in theannual temperature. Piao et al. (2010)) found that theregions of Northeast China are warmer in recent years.Mann–Kendall trend test results with the standard normal

statistic (2) computed over the annual precipitation andtemperature series of every station. Figure 4 shows thetrends of annual precipitation (34 stations) and temperature(11 stations) in the six subcatchments from 1960 to 2006.Six precipitation stations exhibited insignificant upwardtrends, which three of the six stations in the HHWcatchment. One station exhibited a significant downwardtrend with a Zc value of �2.2, which in the TZHWcatchment. Moreover, 27 stations exhibited insignificantdownward trends in the study area. The annual meantemperatures of all the 11 meteorological stations exhibitedupward trends. Ten stations had significant upward trends,

Figure 3. Sequential Mann–Kendall test for annual average temperaturewith forward trend uf (solid line) and backward trend ub (dotted line);dashed horizontal lines represent critical values corresponding to the 0.05

significant level

e (b) at 0.05 significant level based on data from 34 rainfall stations and 11e study area (1960–2006)

Hydrol. Process. 28, 186–196 (2014)


and only one station (the Benxi Station in the TZHWcatchment) had an insignificant upward trend with a Zcvalue of 0.97.

Monthly temperature and precipitation trends

The Mann–Kendall test was also used to determine themonthly mean temperature and precipitation trends for thesix subcatchments (Figure 5). Most of the subcatchmentsshowed variability in monthly precipitation that isgenerally insignificant, except in September, which iswhen four of the six subcatchments (HHW, HSZH,TZHW, and XH) exhibited significant downward trendsin precipitation. The trends in the monthly meantemperature of the six subcatchments were also testedusing the Mann–Kendall statistic, and the results showthat most of the subcatchments had positive Zc values foreach month. Moreover, at least 4 of the 12monthsexceeded the significant level, indicating an obviousincrease from 1960 to 2006, except for the TZHWsubcatchment, which showed no clear monthly change. Interms of seasonal variability, warming trends in winterand spring were greater compared with those in autumnand summer, and warming trend in September is alsoquite large, especially in the LH and TH subcatchments,and these results are consistent with the researches ofDong and Wu (2008). Spatially, a north-south orientationdifference was observed, and the temperature increasedmore significantly in the north area (HHW, HSZH, andTZHW) than in the south area (XH, LH, and TH).

Annual runoff trend

Figure 6 shows the annual runoff of each subcatchment inthe study area from 1960 to 2005. All the annual runoffsexhibited declining trends from 1960 to 2006. The annualrunoffs of the HHW, HSZH, TZHW, XH, LH, and TH

Figure 5. Mann–Kendall trend test for monthly precipitation and tem


subcatchments declined at rates of 35.6, 11.4, 27.3, 26.9,17.7, and 37.7mm/10 yr, respectively. As can be seen inFigure 6, each subcatchment had a peak runoff value in1985, indicating the occurrence of a flood that year. Thelinear change ratios of the annual runoff were higher after1985 than before for the six subcatchments.Results of the Mann–Kendall trend test for the six

subcatchments show that the annual runoffs of all thesubcatchments exhibited declining trends, of which theHHW, TZHW, and TH subcatchments exhibited significantdeclines with Zc values of �2.15, �2.27, and �2.46,respectively (see Figure 7). The HSZH, XH, and LHsubcatchments had annual runoff declines that weregenerally insignificant.

Monthly runoff trend

The Mann–Kendall trend test was also used to determinemonthly runoff trend, and the results are presented inFigure 8. Monthly runoff generally exhibited a downwardtrend that was significant for most of the subcatchments in atleast three months of the year. Although the monthly runofftrend was not consistent in all of the subcatchments, somemonths exhibited consistent trends. Five of the sixsubcatchments showed significant downward trends inMarch and September.

Abrupt change character of runoff decline

The annual runoffs of the six subcatchments from 1960 to2006 were tested using the Mann–Kendall sequentialmethod to graphically illustrate the forward and backwardtrends of annual runoff in Figure 9. The intersection of theforward and backward curves indicated a starting point forthe abrupt runoff change in each subcatchment. The abruptchange in runoff is statistically significant only if at least onepoint in the curve uf (solid line) falls outside the confidence

perature in the six subcatchments in the study area (1960–2006)

Hydrol. Process. 28, 186–196 (2014)

Figure 6. Interannual changes of runoff in the six subcatchments from 1960 to 2006 (Solid line is the observed value. Dotted line represents the linetrend. Dashed line is the polynomial trend analysis)

Figure 7. Annual runoff trend test for the six subcatchments in the studyarea (1960–2006)

192 Y. ZHANG ET AL.

interval (dotted lines). The results show that the annualrunoff abrupt change point occurred in 1975 in the HHWsubcatchment of the Hun River, whereas the annual runoffabrupt change occurred around 1998 in the TZHW and THsubcatchments of the Taizi River.

Effects of climate variability on runoff

To estimate the impact of climate change on the runoffs ofthe six subcatchments, regional relationships betweenaverage annual precipitation and runoff were developedfor the periods separated by the abrupt change points.Figure 10 shows the correlation comparison betweenprecipitation and runoff for the two periods. In most of thesubcatchments, the correlation between precipitation andrunoff before the change point was stronger than that afterthe change point because the value of R1

2 in the first period isalways larger than that after the change point. The regressiontrend lines before the change period lie above the trend linesafter the change point, indicating that the runoff after the


change period was less than that before the change pointunder the same annual precipitation and suggesting thatrunoff was less influenced by precipitation after the changepoint. In other words, the impact of climate became less afterthe change point, and thus, the change in runoff may havebeen driven more by human activities, such as land use/cover change and construction of new dams and reservoirs(e.g. The Shenwo and Tanghe Reservoirs, which controlledthe LH and TH subcatchments, respectively, and wereconstructed during the 1990s). The construction of newdams and reservoirs was one of the reasons for the greatdecrease in the correlation between precipitation and runoffafter the abrupt change.

EFFECTS OF LAND USE CHANGES ON RUNOFF

The results of the regression analysis suggest that humanactivities have increasing impact on runoff. Furthermore, thesequential Mann–Kendall tests clearly show that the abruptdecline of the runoff in most of the subcatchments occurredfrom 1975 to 1998. The period from 1978 to 1985 was thebeginning of China’s land reform policy, which motivatedfarmers to productively manage reallocated land andincrease agricultural production. Thus, land use data fromthe years 1980 and 2000 were obtained to represent theperiod before and after the changes, respectively. Due to theland use data in 1975 is lack, so we take the data of 1980sinstead. Land cover effects on water yield during the twoperiods were also detected to illustrate the response of landcover change on hydrology. Figure 11 shows the pattern ofland use in the six subcatchments in 2000. Themain types ofland use in the subcatchments include forest land, farmland,and grassland, which collectively accounts for 92%–98% ofeach subcatchment for the two periods of 1980 and 2000, asshown in Table II. Forest land is the main type of land use in

Hydrol. Process. 28, 186–196 (2014)

Figure 8. Mann–Kendall trend test for monthly runoff in the six subcatchments in the study area (1960–2006)

Figure 9. Sequential Mann–Kendall test for annual runoff with forwardtrend uf (solid line), and backward trend ub (dashed line); dottedhorizontal lines represent critical values corresponding to the 0.05

significant level



the study area. Forests are known to have significant effectson water yield. Increased agricultural activities result inincreased agricultural water use. The increase in the numberof farmlands results in the loss of other types of land use.Farmland increase in the study area is mainly caused by theloss of forest land (see Table II), although the percentage ofland cover change was less than 4% for each subcatchment.The impact of land cover change on water yield can beestimated using themethod described in the previous section(Equations (10–12)). The results show that the change inwater yield caused by land cover change was 40, 33, 6, 9,�15, and 17mm for the HHW, HSZH, TZHW, XH, LH,and TH subcatchments, respectively, during 1980 and 2000.Due to water balance equation, the evapotranspirationdecrease is one reason for the increase in water yield. Thepercentage of water yield change on runoff was 13%, 14%,2%, 3%, �7%, and 9% for the HHW, HSZH, TZHW, XH,LH, and TH subcatchments, respectively (see Table III).This finding is nearly consistent with the results of the priorstudies (Bosch and Hewlett, 1982; Matheussen et al., 2000;Costa et al., 2003; Brown et al., 2005; Siriwardena et al.,2006; Sun et al., 2006).The results suggest that the reductionin forest cover may be one among many reasons for theincrease in water yield, but there is no clear evidence of astrong univocal relation.

CONCLUSIONS

In this study, the following conclusions were drawn:

1. The results of the Mann–Kendall test indicate anincreasing tendency in temperature time series at the

Hydrol. Process. 28, 186–196 (2014)

Figure 10. Relationship between runoff and precipitation for the two periods (before and after change periods); R12 denotes the correlation coefficientbefore the change point, and R22 denotes the correlation coefficient after the change point

Figure 11. Land use/cover maps for the six subcatchments in the study area in 2000

194 Y. ZHANG ET AL.

0.05 significance level. This result indicates that the areais becoming warmer. Analyses of precipitation data showdecreasing trends, which, however, are not significantat the 0.05 significance level according to the Mann–Kendall test.


2. Runoffs in all six subcatchments exhibited decreasingtrends, in which four subcatchments showed significantdownward trends at the 0.05 significance level. Usingthe sequential Mann–Kendall test, an abruptchange point was detected for all the subcatchments.

Hydrol. Process. 28, 186–196 (2014)

Table II. Proportion of major land use type in the six subcatchments in the study area

River Catchment Crop (%) Forest (%) Pasture (%) Water body (%) Residential (%) Bare (%)

HHW 1980 17.68 78.51 1.32 1.21 1.282000 18.60 77.37 1.50 1.14 1.39

HSZH 1980 15.37 82.09 0.39 1.33 0.822000 15.71 81.65 0.47 0.95 1.22

TZHW 1980 14.62 79.73 1.58 1.81 2.22 0.042000 14.96 79.38 1.39 1.94 2.28 0.05

XH 1980 15.25 80.84 0.67 0.71 2.532000 16.04 79.75 0.58 0.71 2.92

LH 1980 24.62 65.91 2.39 3.69 3.00 0.392000 25.61 64.76 2.50 3.67 3.07 0.39

TH 1980 19.28 75.35 1.07 2.66 1.642000 20.77 74.46 0.91 1.89 1.97

Table III. Results of water-yield change caused by land cover change

SubcatchmentP1

(mm)P2

(mm)ET1(mm)

ET2(mm)

ΔE(mm)

Q(mm)

Changepercentage (%)

HHW 781 789 495 455 40 307 13HSZH 768 764 419 386 33 236 14TZHW 819 816 527 521 6 300 2XH 748 761 433 424 9 300 3LH 796 837 390 405 �15 214 �7TH 762 757 438 421 17 189 9


The abrupt change point generally occurred in 1975 in theHui River basin and in 1998 in the Taizi River basin.

3. Results of the regression analysis show that thecorrelation between runoff and precipitation was lowerafter the abrupt change point than that before thechange point period under similar precipitation. Thisresult confirms that the effect of climate (namelyprecipitation) on runoff has reduced in recent years.

4. The land use and land cover change during the twoperiods considered in the research was deemed to havean impact on the water yield of the watershed. Thereduction in forest land may be one among manyreasons for the increase in water yield in the study areafrom 1980 to 2000.

ACKNOWLEDGEMENTS

The research was funded by the National Key BasicDevelopment Plan Research Program of China(2009CB421101), the Key Direct Project of ChineseAcademy of Sciences (KZCX2-YW-Q06-2-1), and theNon-profit Industry Financial Program (200804001).

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