Did annual run-off and low flow decrease with reduced forestry practices in Japan

HYDROLOGICAL PROCESSESHydrol. Process. 24, 2440–2451 (2010)Published online 12 April 2010 in Wiley InterScience(www.interscience.wiley.com) DOI: 10.1002/hyp.7657

Did annual run-off and low flow decrease with reducedforestry practices in Japan?

Hikaru Komatsu,1* Tomonori Kume,2 Yoshinori Shinohara,1 Yoshiyuki Miyazawa1

and Kyoichi Otsuki1

1 Kasuya Research Forest, Kyushu University, 394 Tsubakuro, Sasaguri, Kasuya, Fukuoka 811-2415, Japan2 School of Forestry and Resource Conservation, National Taiwan University, 1, Sce. 4, Roosevelt Road, Taipei 106, Taiwan

Abstract:

Japan developed large areas of coniferous plantations for timber production between the 1950s and 1970s; however, forestrypractices such as thinning, pruning, and harvesting in most of the plantations have declined since the 1980s. Researchersspeculated that reduced forestry practices could reduce run-off and therefore available water resources. As a countermeasureto this potential risk, many local governments have introduced local taxes to stimulate forestry practices in the plantations.However, no studies have presented evidence for decreased annual run-off and/or low flow in watersheds where forestrypractices have declined. As a starting point for assessing this risk, this study examined potential changes in the annual run-offand low flow in the Terauchi watershed. A large area of this watershed was covered with coniferous plantations. We firstsurveyed the annual investment in forestry operations and the number of forest owners in the city of Amagi. (Note that Amagiincludes the Terauchi watershed.) Both decreased during the period 1979–2007, indicating reduced forestry practices. Thefrequency distribution of plantation tree ages in the watershed also suggested reduced forestry practices. After excluding theeffect of precipitation, we examined potential changes in the annual run-off and low flow during the period 1979–2007. Wedid not observe significant decreases in the annual run-off and low flow during the period. Thus, the risk of decreased waterresources might be less than expected, and countermeasures to the risk should be reconsidered. Copyright 2010 John Wiley& Sons, Ltd.

KEY WORDS forestry; low flow; coniferous plantations; run-off; water yield; watershed

Received 11 August 2009; Accepted 11 February 2010

INTRODUCTION

Watershed run-off is influenced by many factors suchas climate, geology, topography, and vegetation (Wardand Robinson, 2000; Brooks et al., 2003; Iroume et al.,2006; Yao et al., 2009). Human activities that influencevegetation cover could affect the run-off regime (e.g.Langford, 1976; Watson et al., 1999; Swank et al., 2001).As available water resources are often represented by theannual run-off and low flow, changes in these in concertwith vegetation changes have been examined in earlierstudies (e.g. Swank and Douglass, 1974; Robinson andDupeyrat, 2005; Pizzaro et al., 2006).

Deforestation (forestry clear-felling or conversion fromforests to pasture) and reforestation (development offorest cover following clear-felling or conversion frompasture to forests) are the most significant examplesof vegetation change. Thus, many studies (e.g. Boschand Hewlett, 1982; Hornbeck et al., 1993; Lesch andScott, 1997) have examined the effect of deforestationor reforestation on the annual run-off and low flow.Results of these studies were summarized in severalreview studies (Andreassian, 2004; Brown et al., 2005;

* Correspondence to: Hikaru Komatsu, Kasuya Research Forest, KyushuUniversity, 394 Tsubakuro, Sasaguri, Kasuya, Fukuoka 811-2415, Japan.E-mail: [email protected]

Farley et al., 2005) and the effects of deforestationand reforestation are considered to be well understood.Conversely, other types of vegetation changes (e.g.tree species conversion and forest ageing) and theireffects on water resources are still under debate in somecountries (e.g. Lane and Mackay, 2001; Vertessy et al.,2001; Komatsu et al., 2007a, 2008a,b). In Japan, forestrypractices and their effect on run-off have recently beenraised as a concern (e.g. Kuraji, 2004; Komatsu et al.,2007b, 2009a; Onda, 2008).

Japan developed large areas of coniferous plantationsfor timber production from the 1950s to the 1970s,mainly by converting natural broadleaved forests (Fuji-mori, 2000). Coniferous plantations occupy approxi-mately 40% of forested areas and approximately 25%of Japan’s land surface (National Astronomical Obser-vatory, 2009). To develop these plantations, seedlingsare planted typically at approximately 3000 stems ha�1.Trees are thinned and pruned several times in thedecades after planting and are harvested at an ageof 40–50 years (e.g. Kikuzawa, 1999). By this stage,stem density is typically 500 stems ha�1. Practicessuch as thinning, pruning, and harvesting were con-ducted in these plantations during the 1950–1980period. However, these practices have gradually declinedsince the 1980s because of low timber prices andincreased employment costs (Fujimori, 2000; Japan

Copyright 2010 John Wiley & Sons, Ltd.

RUN-OFF CHANGE WITH REDUCED FORESTRY PRACTICES 2441

Forestry Agency, 2007). Thus, many plantations in Japanare now unmanaged.

Researchers in Japan (Tsukamoto, 1998; Yorimitsu,2001, 2004; Kuraji, 2003) have speculated that reducedforestry practices could have reduced available waterresources. This speculation is based on the following.First, several previous studies have reported positive cor-relations between stem density and interception evapo-ration (e.g. Komatsu et al., 2008b, 2009a) and betweenleaf area and canopy-tree transpiration (e.g. Granier et al.,2000; Vertessy et al., 2001). In areas of reduced forestrypractices, leaf area and stem density would be high, whichimplies reduced annual run-off and low flow in associatedwatersheds (e.g. Komatsu et al., 2009a; Reid and Lewis,2009). Second, several studies have reported reduc-tions in canopy-tree transpiration (Morikawa et al., 1986)and interception evaporation (Hattori and Chikaarashi,1988; Murai and Kumagai, 1989) due to the thinningof Japanese coniferous plantations. This suggests that anabsence of forestry practices could increase evapotran-spiration and therefore reduce run-off.

On the basis of researchers’ speculation (Tsukamoto,1998; Yorimitsu, 2001, 2004; Kuraji, 2003), 16 of the 51prefectures in Japan have introduced local taxes, referredto as water or forest taxes, to stimulate forestry practices(Imawaka and Sato, 2008), and 8 further prefectures arenow considering similar measures. Japanese researchers(e.g. Nakane, 2004; Nakashizuka, 2004; Ohgaki, 2005;Onda, 2008) have also noted other potential problemsresulting from reduced forestry practices, including soilprotection and fertility, water quality, flood control,carbon sequestration, and biodiversity.

In reality, no studies have presented evidence forreductions in the annual run-off and low flow due toreduced forestry practices on the basis of watershed run-off data. Although there are numerous studies examiningthe effects of vegetation change on annual run-off andlow flow in Japan, most of these have focused on theeffects of harvesting or natural disturbance such as winddamage and insect infestation (e.g. Abe and Tani, 1985;Fujieda et al., 1996; Maita et al., 2005). Thus, the riskof decreased water resources due to reduced forestrypractices has not been assessed. As a starting point forassessing this risk, this study examines potential changesin the annual run-off and low flow (i.e. changes inthe annual run-off and low flow when precipitation isassumed to be unchanged) in a watershed where forestrypractices are known to have declined.

STUDY AREA

The study area was the Terauchi watershed located innorthern Kyushu, Japan (Figure 1). This watershed is51 km2 in area and ranges 120–720 m in elevation.The mean annual precipitation in the watershed dur-ing the 1979–2007 period, measured at Ohshiro sta-tion (approximately 460 m in elevation), was 2176 mm.Although temperature measurements were not conducted

Figure 1. Study area location

in the watershed, data recorded at Asakura station located³10 km to the southwest were available from the JapanMeteorological Agency (http://www.jma.go.jp/jma/index.html). The mean annual temperature during the 1978–2007 period at Asakura station was 15Ð5 °C. The geol-ogy of the watershed was Tertiary formations, withbedrock comprising black schist according to the geo-logical map produced by the Geological Survey of Japan(http://www.gsj.jp/geomap/indexE.html).

The watershed was selected for three reasons. First,run-off data before the 1980s are available for thiswatershed. We aimed at examining changes in theannual run-off and low flow with reduced forestrypractices. Forestry practices in Japan generally beganto reduce in the 1980s. Second, the watershed areawas extensively covered with coniferous plantations.This was unlike other watersheds in Japan whereconiferous plantations occupied a relatively small por-tion of the watershed area. Third, the watershed waslocated in the wider catchment area of the city ofFukuoka (Figure 1), which suffers the highest fre-quency of water shortages in Japan (Jinno et al., 2005;http://www.mlit.go.jp/tochimizushigen/mizsei/hakusyo/index5.html). Because Fukuoka is a major economic andhighly populated centre in Kyushu, water shortages canhave significant adverse effects on the economic activ-ity and human welfare. Furthermore, Fukuoka introducedlocal taxes to aid forestry in 2009 for the purpose ofsecuring water resources. A portion of these taxes willbe used to stimulate forestry practices in the Terauchiwatershed.

Copyright 2010 John Wiley & Sons, Ltd. Hydrol. Process. 24, 2440–2451 (2010)

2442 H. KOMATSU ET AL.

DATA AND METHODS

Forestry activity

Before analysing the annual run-off and low flow,we examined evidence of reduced forestry practices.Forestry practices in the Terauchi watershed have beenundertaken mainly by the Fukuoka Water Source For-est Foundation since 1979. We examined changes in theannual investment in forestry operations and the num-ber of forest owners in the city of Amagi. This cityincludes the Terauchi watershed. (Note that the city wasincorporated as the city of Asakura in 2006.) Data wereobtained from the Fukuoka Water Source Forest Founda-tion (http://www.f-suigen.or.jp/) and Fukuoka Prefecture(http://www.pref.fukuoka.lg.jp/dataweb/index.html).

We obtained a vegetation zone map from FukuokaPrefecture and identified the areas within the Terauchiwatershed using a Geographical Survey Institute topo-graphic map (http://www.gsi.go.jp/). We then requestedvegetation data for these areas. The dataset was dividedinto sections according to the forest type (plantation ornatural), tree species, and age. Because earlier data hadbeen discarded by the Fukuoka Prefecture governmentfollowing its data reservation policy, our analysis wasconducted using observations from 2003.

Annual run-off and low flow

We obtained precipitation and run-off data for theperiod 1979–2007 from the Chikugo Regional Bureau,Japan Water Agency. We used daily precipitation datarecorded at the Ohshiro station in the Terauchi watershedand daily inflow data recorded at the Terauchi Damreservoir. The dam reservoir captured all run-off flowfrom the Terauchi watershed. Besides precipitation datafor Ohshiro station, we obtained daily precipitation datafor the period 1979–2007 recorded at two other stationsin the Terauchi watershed. The annual precipitationat these two stations correlated well with that of theOhshiro station for the period 1979–2007, and usingthese stations’ data did not qualitatively alter our resultsand conclusions.

We examined the relationship between the annual pre-cipitation and annual run-off for the period 1979–2007.After developing a regression model to predict the annualrun-off with the input of annual precipitation, we cal-culated the difference between the observed and themodelled run-off (i.e. observed minus modelled). Wethen investigated whether the difference decreased duringthe period 1979–2007. If the reduced forestry practicesincreased watershed evapotranspiration, the differencewould decrease with time (i.e. the annual run-off for agiven annual precipitation would decrease).

The decrease in the difference between the observedand the modelled run-off was tested using a non-parametric method described by Kundzewicz and Robson(2004). In employing the method, we first calculated theslope of linear regression, Spearman’s rho, and Kendall’stau from the original time-series of the difference between

the observed and the modelled run-off. We then cal-culated these parameters after resampling the originaltime-series data using the bootstrap method. This pro-cess was repeated 1000 times (note that our conclusionsdid not change when this process was repeated 5000 or10 000 times). From the parameter values obtained byresampling, we produced probability density functions forthe three parameters. We finally compared the parametervalues based on the original time-series data with theprobability density functions. If there was a significantincreasing or decreasing trend in the original time-seriesdata, the parameter values based on the original time-series data would be situated at the foot of the probabilitydensity functions.

We performed the same analysis for low flow as thatfor annual run-off. We defined ‘low flow’ as the annualminimum of daily run-off, following earlier studies(Pizzaro et al., 2006; Komatsu et al., 2008a). Otherstudies (e.g. Fahey and Jackson, 1997; Sikka et al., 2003;Maita et al., 2005; Komatsu et al., 2009b) have usedalternative low flow indices, such as the 7-day or 10-day average minimum run-off, and the daily run-off that97% of data exceed. We examined whether using theseindices altered our results and conclusions.

In addition, we conducted the same analysis for thebase flow ratio as that for low flow. The base flow ratiois defined as the annual base flow divided by the annualrun-off. Thus, the ratio represents run-off fluctuationsand is therefore an index for evaluating available waterresources. In this analysis, we separated daily run-offdata into base flow and storm flow components using thetime-based separation method (Hornberger et al., 1997;Ward and Robinson, 2000) and a line with a constantgradient. The gradient was determined following themethod described by Dingman (2002) and Blume et al.(2007) with the input of watershed area data.

Effects of changes in the precipitation pattern

The above analysis relates the annual run-off andlow flow to the annual precipitation without consideringchanges in the precipitation pattern (i.e. the numberof precipitation days and precipitation intensity) duringthe analysis period. If precipitation patterns changedsignificantly, this could mask possible decreases in theannual run-off and/or low flow.

To examine this possibility, we checked whether thenumber of days with daily precipitation of at least 5,10, and 30 mm changed significantly over the analysisperiod. The precipitation intensity and the number of pre-cipitation days are inversely related; i.e. when assumingconstant annual precipitation, higher precipitation inten-sity indicates a smaller number of precipitation days(Kumagai et al., 2004; Shinohara et al., 2009). Thus, weanalysed the number of precipitation days only and didnot directly analyse the precipitation intensity.

Run-off in low precipitation years

The analysis described above examines changes in theannual run-off, low flow, and the base flow ratio using



all available data during the period 1979–2007. Watershortages occur in years with low precipitation. Thus,analysis of such years is also important.

We thus selected data for an early year and late yearwith low precipitation in the period 1979–2007. We thencompared the annual run-off, low flow, and the base flowratio between these two years.

RESULTS

Forestry activity

Figure 2 shows changes in the annual investment inforestry operations during the period 1979–2007. Themean annual investment was 360 million yen in theperiod 1979–1983 but decreased gradually and reached57 million yen in the period 2003–2007. The num-ber of forest owners in Amagi was 1539 in 1970 and655 in 2000, although the percentage of forested area(approximately 60%) and population of the city (approx-imately 43 000) were largely unchanged during the period1970–2000. These data suggest reduced forestry prac-tices in recent decades. Note that, although Japan hastried to promote the mechanization of forestry activitysince the late 1980s (Taniyama, 2005), such mechaniza-tion has not proceeded in northern Kyushu (http://www.rinya.maff.go.jp/puresu/h18-12gatu/1226ringyoukikai.html). Thus, the decrease in the investment and the num-ber of forest owners was not because of the developmentof an efficient forestry system due to mechanization.

There were 10 112 sections of vegetation data forthe Terauchi watershed. The total area registered in thevegetation data was 39 km2, while the entire watershedarea was 51 km2. Thus, 76% of the watershed areawas registered in the vegetation dataset. According tothe vegetation zone map, the remaining 24% consistedof mainly other land uses, such as water bodies andorchards. Within the 39 km2 vegetation area, coniferousplantations occupied 93%, while natural broadleavedforests and natural pine forests occupied 5%. The major

Figure 2. Changes in the annual investment in forestry operations for theperiod 1979–2007. One million Japanese yen is equivalent to US$10 190

on the basis of the exchange rate on 6 June 2009

coniferous plantation species were Cryptomeria japonicaand Chamaecyparis obtusa, occupying 61 and 32%of the area, respectively. C. japonica and C. obtusaare the most common plantation species in Japan andaccount for approximately 70 and 90% of the plantationarea nationally and in Kyushu respectively (NationalAstronomical Observatory, 2009).

Figure 3a shows the tree age frequency distributionversus coniferous plantation area in 2003. The verticalaxis indicates the area of each age class divided by thewhole area of coniferous plantations. Frequencies werelower for trees less than 35 years old, higher for trees35–55 years old, and lower again for trees more than55 years old. Figure 3b presents similar data, but for thewhole country. In 1985, frequencies were lower for treesless than 5 years old, higher for trees 5–35 years old, andlower again for trees more than 35 years old. In 2001,frequencies were lower for trees less than 20 years old,higher for trees 20–50 years old, and lower again fortrees more than 50 years old. Thus, national frequencies

Figure 3. Frequency distributions of coniferous plantation tree ages for(a) the Terauchi watershed and (b) the whole country. The vertical axisindicates the area of each age class divided by the whole area ofconiferous plantations. Data for the whole country were obtained from

the Japan Forestry Agency (2007)



Figure 4. Time-series of (a) annual precipitation, run-off, (b) low flow,and (c) base flow ratio

were higher for mid-age classes in 2001, similar to theTerauchi watershed distribution.

Timber harvesting of coniferous plantations in Japan isusually conducted when trees are older than 40 years. Ifforestry activity had been continuous, the age frequencyfor trees less than 40 years old should be nearly constantand the age frequency for trees more than 40 yearsold should decrease with age. Thus, the frequencydistribution suggests reduced forestry practices in theTerauchi watershed over recent decades.

Annual run-off and low flow

Figure 4 shows time-series of the annual precipitation,annual run-off, low flow, and base flow ratio. Themean annual precipitation and run-off during the period1979–2007 were 2176 and 1351 mm, respectively. Thus,the mean annual evapotranspiration, calculated as thedifference between annual precipitation and run-off, was825 mm, which is comparable to values reported forother forested watersheds in Kyushu (Shimizu et al.,2003; Komatsu et al., 2007c, 2008c). The mean lowflow and base flow ratio were 0Ð53 mm day�1 and 0Ð72,respectively.

Figure 5a shows the relationship between annual pre-cipitation and run-off. We obtained a positive (p <

Figure 5. (a) Relationship between annual precipitation and run-offfor the period 1979–2007. The solid line was determined usingthe least-squares method. The determination coefficient was 0Ð949.(b) Difference between observed run-off and run-off calculated by theregression equation. The solid line was determined using the least-squaresmethod. The determination coefficient was 0Ð00387 and the slope was

�0Ð689

0Ð001) correlation according to Pearson’s correlationcoefficient test. Using the least-squares method, themodel function was determined as Q D 0Ð958 P C 734,where Q and P are the annual run-off and precipitation,respectively. Figure 5b shows the difference betweenobserved and modelled run-off (i.e. observed minus mod-elled). The slope of linear regression, Spearman’s rho,and Kendall’s tau were �0Ð689, �0Ð00443, and 0Ð00493respectively. Figure 6 shows probability density func-tions for these three parameters obtained by resamplingoriginal time-series data. The three parameters based onthe original time-series data were higher than the lower5% threshold values of the probability density functions(�3Ð28, �0Ð303, and �0Ð261, respectively).

Figure 7a shows the relationship between annual pre-cipitation and low flow. We obtained a positive (p <0Ð005) correlation according to Pearson’s correlationcoefficient test. Using the least-squares method, themodel function was determined as q D 0Ð000190 P C0Ð118, where q is low flow. Figure 7b shows the dif-ference between observed and modelled low flow (i.e.observed minus modelled). The slope of linear regres-sion, Spearman’s rho, and Kendall’s tau were 0Ð00626,



Figure 6. Probability density functions for (a) the slope of linear regres-sion, (b) Spearman’s rho, and (c) Kendall’s tau. These functions wereproduced by resampling original time-series data of the differencebetween observed and modelled annual run-off. Values of the threeparameters based on the original time-series data are indicated. The lower5% threshold values of the probability density functions are also indicated

0Ð276, and 0Ð177, respectively. Figure 8 shows probabil-ity density functions for these three parameters obtainedby resampling original time-series data. The three param-eters based on the original time-series data were higherthan the lower 5% threshold values of the probability den-sity functions (�0Ð00534, �0Ð328, and �0Ð291, respec-tively). We obtained qualitatively the same results whenusing other low flow indices, such as the 7- or 10-dayaverage minimum run-off, or the daily run-off that 97%of data exceed (data not shown).

Figure 9a shows the relationship between annual pre-cipitation and the base flow ratio. We obtained a negative(p < 0Ð001) correlation according to Pearson’s correla-tion coefficient test. Using the least-squares method, themodel function was determined as Rb D �0Ð000156 P C1Ð06, where Rb is the base flow ratio. Figure 9b shows

Figure 7. (a) Relationship between annual precipitation and low flowfor the period 1979–2007. The solid line was determined usingthe least-squares method. The determination coefficient was 0Ð322.(b) Difference between observed low flow and low flow calculatedusing the regression equation. The solid line was determined using theleast-squares method. The determination coefficient was 0Ð205 and the

slope was 0Ð00626

the difference between observed and modelled base flowratios (i.e. observed minus modelled). The slope of lin-ear regression, Spearman’s rho, and Kendall’s tau were�0Ð000205, 0Ð133, and 0Ð0739, respectively. Figure 10shows probability density functions for these three param-eters obtained by resampling original time-series data.The three parameters based on the original time-seriesdata were higher than the lower 5% threshold values ofthe probability density functions (�0Ð00333, �0Ð308, and�0Ð251, respectively).

Effects of changes in the precipitation pattern

Figure 11a shows the relationship between annual pre-cipitation and the number of days on which daily pre-cipitation was at least 5 mm. We obtained a positive(p < 0Ð001) correlation according to Pearson’s corre-lation coefficient test. Using the least-squares method,the model function was determined as N D 0Ð02185 P C34Ð7, where N is the number of days on which dailyprecipitation was at least 5 mm. Figure 11b shows thedifference between the observed and modelled numbersof precipitation days (i.e. observed minus modelled). Theslope of linear regression, Spearman’s rho, and Kendall’stau were �0Ð181, �0Ð153, and �0Ð09852 respectively.



Figure 8. Probability density functions for (a) the slope of linear regres-sion, (b) Spearman’s rho, and (c) Kendall’s tau. These functions wereproduced by resampling original time-series data of the differencebetween observed and modelled low flow. Values of the three param-eters based on the original time-series data are indicated. The lower 5%threshold values of the probability density functions are also indicated

Figure 12 shows probability density functions for thesethree parameters obtained by resampling the originaltime-series data. The three parameters based on the origi-nal time-series data were lower than the higher 5% thresh-old values of the probability density functions (0Ð257,0Ð323, and 0Ð187, respectively). We obtained the sameresults for the numbers of days with daily precipitationof at least 10 and 30 mm (data not shown). Thus, ourresults for the analysis of the annual run-off and lowflow (i.e. no significant decrease in the annual run-offand low flow) were not affected by possible changes inthe precipitation pattern during the analysis period.

Run-off in low precipitation years

Annual precipitation amounts in 1984 and 2002 werethe second and third lowest respectively in the period1979–2007 (Figure 4a). Table I lists the annual precipita-tion, the number of precipitation days, annual run-off, low

Figure 9. (a) Relationship between annual precipitation and the baseflow ratio for the period 1979–2007. The solid line was determinedusing the least-squares method. The determination coefficient was 0Ð548.(b) Difference between observed base flow ratios and those calculatedusing the regression equation. The solid line was determined using theleast-squares method. The determination coefficient was 0Ð000827 and

the slope was �0Ð000205

flow, and the base flow ratio for the 2 years. The annualprecipitation was approximately the same for the 2 years.Although the number of precipitation days differed for the2 years, the difference was small. For example, the differ-ence in the number of days with precipitation of at least5 mm was only three. On the other hand, the numberof days with precipitation of at least 5 mm often var-ied by approximately 10 for a given annual precipitation(Figure 11a).

The annual run-off, low flow, and the base flow ratiowere approximately the same for the 2 years, with 2002having slightly higher values than 1984 (Table I). Wetherefore found no evidence for a decrease in waterresources with reduced forestry practices in the 2 yearsof very low rainfall.

DISCUSSION

Dependency on the statistical method

We used a non-parametric method described byKundzewicz and Robson (2004). Andreassian et al.(2003) proposed a different non-parametric method todetect temporal trends in watershed run-off. We appliedAndreassian et al.’s (2003) method to our analysis and



Figure 10. Probability density functions for (a) the slope of linear regres-sion, (b) Spearman’s rho, and (c) Kendall’s tau. These functions wereproduced by resampling original time-series data of the differencebetween observed and modelled base flow ratios. Values of the threeparameters based on the original time-series data are indicated. The lower5% threshold values of the probability density functions are also indicated

found that our conclusions did not change. For simplic-ity, we present only the results for annual run-off trendsobtained using Andreassian et al.’s (2003) method.

The method separates the whole data period intoseveral periods of the same length. We separated thewhole period into four periods: 1979–1985, 1986–1992,1993–1999, and 2000–2006. We did not use data for2007 so that the four periods had the same length.

We then determined model parameters for each periodusing the least-squares method in the same way aswas done to obtain the results presented in Figure 5a.The annual run-off (Q) was modelled by the annualprecipitation (P) as Q D 1Ð09 P � 996 (Model I), Q D0Ð929 P � 719 (Model II), Q D 0Ð856 P � 489 (ModelIII), and Q D 0Ð966 P � 759 (Model IV) for the fourperiods separately. On the basis of these models, thematrix of Andreassian et al. was calculated as shown in

Figure 11. (a) Relationship between annual precipitation and the numberof days on which precipitation was at least 5 mm for the period1979–2007. The solid line was determined using the least-squaresmethod. The determination coefficient was 0Ð631. (b) Difference betweenobserved number of precipitation days and that calculated using theregression equation. The solid line was determined using the least-squaresmethod. The determination coefficient was 0Ð0464 and the slope was

�0Ð181

Figure 13a. The value in each cell indicates the meanannual run-off calculated by each model (note that ifwe calculate the total run-off for each 4-year periodrather than the mean annual run-off, our results do notchange because our models assume linear relationshipsbetween P and Q). Values in each row were based ondifferent precipitation data inputs: precipitation data for1979–1985, 1986–1992, 1993–1999, and 2000–2006.

The statistical measure S used by Andreassian et al.(2003) is calculated as:

S D4∑

iD1

i�1∑jD1

�Qi,i � Qi,j� C4∑

jDiC1

�Qi.j � Qi.i�

�1�

where Qi,j is the mean annual run-off for the cell (i, j).When there are increasing/decreasing trends in Q, S ispositively/negatively great. For the matrix in Figure 13a,S was calculated as �104. We produced matrixes byresampling numerals in cells of the original matrix.We iterated this process 1000 times and obtained theprobability density function for S (Figure 13b). The Svalue based on the original matrix was higher than the



Figure 12. Probability density functions for (a) the slope of linear regres-sion, (b) Spearman’s rho, and (c) Kendall’s tau. These functions wereproduced by resampling original time-series data of the differencebetween the observed and modelled numbers of days on which the dailyprecipitation was at least 5 mm. Values of the three parameters basedon the original time-series data are indicated. The higher 5% threshold

values of the probability density functions are also indicated

Table I. Comparison of precipitation and run-off between 1984and 2002

Year

1984 2002

Annual precipitation (mm) 1642 1675Precipitation days

½5 mm day�1 67 70½10 mm day�1 43 48½30 mm day�1 18 15

Annual run-off (mm) 877 896Low flow (mm day�1) 0Ð41 0Ð46Base flow ratio 0Ð76 0Ð83

lower 5% threshold of the probability density function,�784.

Figure 13. (a) Andreassian et al.’s (2003) matrix for the annual run-offdata. (b) The probability density function for the statistical measure (S)proposed by Andreassian et al. (2003). The S value based on the originalmatrix and the lower 5% threshold value of the probability density

function are indicated

Possible explanations for no discernable run-offdecrease

Our results suggest no clear decrease in availablewater resources in the Terauchi watershed area in recentdecades, despite reduced forestry practices. This mightbe explained by two factors: natural disturbance and theageing of planted trees.

Previous studies (Tsukamoto, 1998; Yorimitsu, 2001,2004; Kuraji, 2003) have speculated decreased waterresources with reduced forestry practices under theassumption of higher stem density and leaf area forareas for unmanaged plantations (see Section Introduc-tion). However, natural disturbances such as wind, flood,and snow damage, fire, and insect infestation couldalso reduce leaf area and stem density and thereforeevapotranspiration (e.g. Abe and Tani, 1985; Maita,2005; Komatsu et al., 2009b). This suggests that reducedforestry practices might not necessarily correspond tohigh stem density and leaf area. Such natural disturbancesoften occur in Japan (Japan Forestry Agency, 2007;Suzuki et al., 2009). Extensive and significant typhoonwind damage in the Terauchi watershed was recorded in1991, 1994, and 2004 (http://www.f-suigen.or.jp/). Thus,natural disturbance might inhibit increases in leaf areaand decreases in stem density despite reduced forestry



practices, resulting in no net decrease in the annual run-off and low flow.

A decrease in transpiration with tree age (or height) hasbeen reported for many coniferous forests (Law et al.,2001; Komatsu, 2003, 2004, 2005; Irvine et al., 2004).Whether such decreases are common for coniferousplantations in Japan is still controversial (e.g. Murakamiet al., 2000; Komatsu et al., 2007a; Tsuruta et al., 2008).If this is the case, a decrease in transpiration due totree senescence might effectively balance the increase intranspiration and interception evaporation because of theleaf area increasing with declining forestry practices.

The present study did not evaluate changes in run-off in the absence of forestry practices and forest ageingseparately. From a scientific viewpoint, it is interesting toevaluate the effects of these two processes separately. Onthe other hand, the two processes occur simultaneously.Thus, evaluating changes in run-off due to both processesis more important from a practical viewpoint. This studymade this practical evaluation.

To evaluate the effect of each process separately,studies at catchment scale (typically several hectares)rather than watershed scale (typically several tens ofsquare kilometres) are required. For this purpose, catch-ments with different ages and intensities of forestrypractices should be prepared. Besides rainfall–run-offmeasurements, transpiration, and interception evapora-tion measurements should be made on the basis of sapflux measurements (e.g. Kumagai et al., 2008; Kumeet al., 2010) and throughfall and stemflow measure-ments (e.g. Onozawa et al., 2009; Shinohara et al., 2010),respectively. From these measurements, we can evaluatechanges in run-off caused by the high canopy density dueto the absence of thinning and pruning and those causedby forest ageing separately.

CONCLUSIONS

As a countermeasure to reduce the risk of decreasedwater resources due to reduced forestry practices, manylocal governments in Japan have introduced local taxesto stimulate forestry practices in coniferous plantationareas (Imawaka and Sato, 2008). However, we foundno evidence of decreasing water resources with reducedforestry practices. Therefore, the risk might be less thanexpected.

This study is the first to quantitatively assess such riskon the basis of watershed run-off data. Further stud-ies are required to generalize the results. This studywas conducted in northern Kyushu, where water short-ages frequently occur. Frequent water shortages alsooccur on Shikoku and western Honshu (http://www.mlit.go.jp/tochimizushigen/mizsei/hakusyo/index5.html), andstudies for these regions are highly recommended. If theresults of these future studies support ours, then counter-measures for reduced forestry practices might be unnec-essary. If different results are obtained among regions,current forest policies should be modified to accommo-date the risk for each region.

Researchers in Japan (Nakane, 2004; Nakashizuka,2004; Ohgaki, 2005; Onda, 2008) have noted other risksdue to reduced forestry practices from the viewpointsof soil protection and fertility, water quality, flood con-trol, carbon sequestration, and biodiversity. Although thisstudy has focused on water run-off processes, the forestwater cycle affects soil transport and forest carbon andnutrient cycling (Landsberg and Gower, 1997; Brookset al., 2003). Thus, the results of this study have impli-cations for research examining these risks.

ACKNOWLEDGEMENTS

We acknowledge Mr K. Takeda and Mr F. Yamamotofrom the Japan Water Agency for providing precipita-tion and run-off data for the Terauchi watershed. We alsothank Mr O. Funakoshi and Ms N. Ogawa from FukuokaPrefecture for providing vegetation data for the Terauchiwatershed. We are grateful to Ms A. Kawasaki and DrT. Kajisa from Kyushu University and Ms A. Miyazawafrom Fukuoka Prefecture for their assistance in collat-ing and analysing vegetation data. We express sincerethanks to Mr K. Tsuruta from Kyushu University, whointroduced us to several critical papers. Thanks are alsodue to Prof. A Iroume and two anonymous reviewersfor their critical comments. This research was supportedby the Japanese Ministry of Education, Culture, Sports,Science and Technology through a Grant-in-Aid for Sci-entific Research (#20780119) and by Core Research forEvolution Science and Technology of the Japan Scienceand Technology Agency.

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Did annual run-off and low flow decrease with reduced forestry practices in Japan

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