Reinterpretation of Relations Between Vegetation Removal and Water Yield

Transcription

1 Department f Gegraphical and Sustainability Sciences Publicatins Reinterpretatin f Relatins Between Vegetatin Remval and Water Yield Gerge P. Malansn University f Iwa D. P. Pst Cpyright Gamma Theta Upsiln, Psted by permissin f the publisher. Gegraphic Bulletin, 36 (1994), pp Hsted by Iwa Research Online. Fr mre infrmatin please cntact: lib-ir@uiwa.edu.

2 Reinterpretatin f Relatins Between Vegetatin Remva! and Water Yield David P. Pst Graduate Student Gerge P. Malansn Prfessr Department f Gegraphy University f Iwa Iwa City, IA ABSTRACT While the relatin between vegetatin clearance and increasing streamflw appears t be strng fr data aggregated amng gegraphic regins, results are equivcal in lcal areas. Earlier data are re-analyzed t cnsider the rle f hydrclimatlgy. While vegetatin clearance increases abslute streamflw, the prprtinal change is nt significant. Residuals f regressins f abslute and prprtinal change in streamflw n vegetatin clearance are related t precipitatin, with psitive and negative slpes, respectively. A few utliers with high respnses are imprtant in creating a pattern, and hydrclimatlgy is a better predictr f change in streamflw than is vegetatin clearance fr aggregate data. With data disaggregated in five classes f precipitatin, significant regressins are fund nly in ne class. N significant relatins are fund fr selected reginal data sets. Reginal hydrclimatlgy affects respnses at bth glbal and lcal scales. The aggregate result, influenced by utliers, cannt be used t guide water resurces management at particular lcatins. KEY WORDS: defrestatin, frest hydrlgy, scale, streamflw, water yield. INTRODUCTION Many studies have examined data n changes in basin water yield r streamflw fllwing vegetatin management treatments. The standard reference is t Hibbert (1967), wh examined changes in 39 catchment experiments. In summary he made three generalizatins: 1. Reductin in frest cver increases water yield. 2. Establishment f frest cver n sparsely vegetated land decreases water yield. 3. Respnse t treatment is highly variable, and fr the mst part, unpredictable. Despite the caveat f the third generalizatin, Hibbert's summary has led 94

3 t use f frmulas fr predicting the effects f frest cver n water yield in lcal regins, at least in the U.S. (Hewlett, 1982), t cnclusins that vegetatin management fr water yield is a basis fr resurces planning (e.g., Pnce and Meiman, 1983), and t a textbk view f the relatin. Sme individual studies nte, hwever, that the respnse is equivcal. Veen and Dlman (1989) specifically nted that the methdlgy f experimental basin studies permits neither extraplatin nr predictin and they rejected the cnclusin f Bsch and Hewlett (1982) that mre such studies are needed. The textbk case is well illustrated by Dunne and Lepld (1978) wh shwed linear increase in first year water yield with percentage f vegetatin cut in the basin, based n Hibbert (1967). It is ntable that the results fr different studies vary greatly in slpe, frm a minr respnse in the suthwestern U.S. t a sensitive respnse in the Oregn Cascades. The textbk case has led t cgent arguments fr the management f vegetatin as an indirect means t manage water (e.g., Duglass, 1983). The research data supprt the ntin that frest harvest will increase water yield, but adds cmplicating factrs fr specific cases. Bth views are based n experimental results, but are ften analyzed at different degrees f generality. The first view is supprted by aggregatin f results f several studies, the latter view by analysis f individual studies. Trimble et al. (1987) best expressed the scale-dependence f the analysis by nting that the change in yield was nt linked t the prprtinal change in vegetatin in their study, but that their data fit well within the universal mdel fr many studies. The within regin applicability f the cncept was demnstrated by Kucera (1987) fr use in Suth Australia. Our purpse is t examine a general trend in the sensitivity and variability f the respnse f basin water yield t vegetatin management. We are particularly interested in elucidating Trimble et al.'s (1987) finding f a difference between lcal and aggregated, r universal, results. T this end we re-examine data frm past studies as did Hibbert (1967), Bsch and Hewlett (1982), and, in part, Trimble et al. (1987). Several factrs lead t variability in respnse. One f the mst ntable cmplicating factrs is seasnality f precipitatin and snwmelt. Kattelman et al. (1983) and Trendle (1983) bth nted that the secndary depsitin and subsequent fate f snw in frested catchments is influenced by the pattern f frest cutting as well as by the prprtinal area. Anther factr is the pattern f vegetatin within the basin. Sme individual experiments have varied the lcatin f cut sectins in the basin, but the results were nt cnclusive (cf. Patric and Reinhart, 1971). Others have fund that basin gemrphlgy and vegetatin, including the existence f wider fldplains supprting deciduus riparian tree species in a cnifer envirnment, wuld have an effect n the sensitivity f the basin t cutting practices (Verry, 1986; Hicks et al., 1991). A mre general phenmenn is the effect f actual precipitatin amunts n the respnse (Trendle ilnd King, 1985). Harr (1983) fund that yield increases were greatest during the rainy seasn and in years with the mst precipitatin. Trimble et al. (1987), examining the effects f refrestatin, fund that yield was decreased mre in dry years. This imprtance in seasnal and annual precipitatin is als expressed ver a gegraphic range related t vegetatin type. As nted abve, the respnse is mst sensitive in thse areas with mst precipitatin and high bimass. Thus Hibbert (1983) argued that water yield wuld nt be increased by cutting r remving lw-density shrubs and wdland trees in arid regins, while Harr (1983) nted that sustained increases in flw wuld be unlikely in the very mesic frests f Oregn and Washingtn. The water yield fr a drainage basin can be calculated using a simple water balance equatin: P = E + Q + (S, - S'-1) where P is precipitatin, E is evap- 95

4 transpiratin, Q is vlume discharge, and S is strage at tw time intervals. The mechanism behind the argument abut cutting is that decreases in vegetatin will lead t decreased E, thrugh a reductin in bth interceptin and transpiratin, and thus increased runff and Q r strage. The flux t E is dependent n the amunt f vegetatin in the system. Changes in vegetatin have usually been measured as area r prprtinal area f the basin changed by management. The bimass per unit area usually has nt been cnsidered, althugh basic hydrlgical studies indicate the imprtance f specific characteristics such as bimass and leaf area. This distinctin may help t explain the reginal differences is sensitivity shwn by the summary and textbk interpretatins: streamflw respnds mre dramatically in areas f large vegetatin structure (i.e., high bimass in prductive areas with high precipitatin) than in arid areas with sparse vegetatin because a unit area cut in the frmer affects mre bimass and leaf area (Figure 1). Here we examine three questins: Is respnse primarily a functin f treatment? Des the respnse vary with hydrclimatlgical cnditins? D patterns f respnse shw a difference between analyses f lcal data versus aggregated data? METHODS In this study we re-analyze the data presented by Bsch and Hewlett (1982). We analyze the relatin between water yield and vegetatin management including, hwever, the influence f lngterm precipitatin and streamflw. Trimble et al. (1987) calculated a regressin equatin fr the data f Bsch and Hewlett (1982) based n the first-year increases in streamflw. We prceed differently. First, we use an average value fr the first 5 years fllwing vegetatin treatment (in sme cases where nly a single figure within 8 yr was given we used it; in ther cases where nly lnger intervals were given, r where n quantitative result was reprted, we did nt a Precipitatin b Precipitatin Evaptranspiratin Streaulflw Evaptranspiratin Streamflw FIGURE 1. Cnceptual relatins f basin hydrlgy; in 1 b, where precipitatin, bimass, and abslute evaptranspiratin and streamflw utputs are lwer, utputs are a higher prprtin f strage than in 1 a. use that bservatin) because water yield implies water resurce; althugh the different prcesses f initial cutting and later recvery are cmbined in this apprach, the chsen variable is meaningful. We thus derived 53 cases. Secnd, we additinally examine the prprtinal increase in streamflw because abslute differences depend strngly n reginal climatlgy, althugh in the data there is n systematic relatin between treatment area and precipitatin. Third, we did nt cnstrain ur equatins t pass thrugh the rigin, but nt nly because Trimble et al. (1987) fund n significant difference in ding s. This cnstraint assumes that the frm f the relatin between zer and ur lwest data pint is the same as fr the rest f the data. Ntwithstanding Trimble et al.'s (1987) imprvement in regressin fit by adding such pints fr large, nn-experimental basins, this assumptin may nt be generally acceptable. Bsch and Hewlett's (1982) cn- 96

5 tended that lw area treatments will nt prduce interpretable results, and unknwn nnlinearities may exist. The data presented by Bsch and Hewlett (1982) (and cdes we used) included fur backgrund variables: mean annual precipitatin (MAP), mean annual stream flw (MAS), basin area (AREA)' mid-basin elevatin (ELEV); a treatment variable: percent f basin cleared (%CLEAR); and a result variable: the incremental change in streamflw (INC)' ver varius intervals. We used the incremental change in streamflw t calculate a prprtinal increment (PINC) by dividing it by mean annual streamflw. This value became an additinal dependent variable in ur analyses. We als calculated a percentage f the incming precipitatin that we assigned t evaptranspiratin: %ET = (MAP-MAS)/ MAP, and its cmplement %MAS = 1 - %ET. We used these data and sme transfrmatin theref. While the backgrund variables are lng term averages and data specific t the experiments wuld be mre useful, these are nt readily available. We began ur analysis by prducing a table f Pearsn crrelatin cefficients t examine general relatins amng the pssible pairs f variables and t cnsider multicllinearity in additinal analyses. Based n thse results we then used stepwise regressins f the dependent variables n several independent variables. Our next step was t regress bth INC and PINC n %CLEAR. The general cncept that we examined was: I~~C r PINC = f(%clear, MAP, MAS, ELEV, AREA, %ET, %MAS). After examining these results we als cmputed the residual f simple regressins f INC and PINC n %CLEAR and then regressed thse values n mean annual precipitatin. Because f a wider range f hydrlgical inputs, it might be expected that larger residuals fr INC and PINC were fund in areas f greater and lesser precipitatin, respectively, there is n a priri reasn t expect that the residuals wuld be biased in terms f psitive r negative sign. T further analyze the data we separately examined cases in five classes f precipitatin. Because earlier reprts suggest that the respnse differs amng regins, we subdivided the data int five grups f apprximately equal number f cases in classes f MAP «815 mm, mm, mm, -2150, >2150) and repeated each f the tw regressins. We als examined data fr drainage basins in fur specific areas: Cweeta, Nrth Carlina; Andrews, Oregn; Fernw, West Virginia; and Three Bar and White Spar, Arizna (Figure 2). Because f the apparent imprtance f utliers, we perfrmed the regressins f INC and PINC n CLEAR a secnd time after deleting fur and three cases, respectively. RESULTS Our initial results indicate high crrelatins amng the general hydrlgical variables fr the basins: MAP and MAS and als fr the calculated r transfrmed variables such as %ET; the treatment variable, %CLEAR, is nt highly crrelated with any ther variable (Table 1). Regressin f the increase in runff n treatment prduced: INC = % CLEAR; adjusted R2: 0.108, standard errr 137, P < PINC = %CLEAR; adjusted R2: 0.017, standard errr 0.77, p> Examinatin f scatter plts (Figure 3) indicated that additinal analyses shuld include natural lg transfrmatins f the independent variables (labeled as LN... ) The plts d indicate that streamflw des increase fllwing clearing, but the predictability is lw, especially where clearing exceeds 30% f the catchment. 97

6 FIGURE 2. Lcatins f the experimental sites analyzed as fur separate grups. TABLE 1 Pearsn Crrelatin Cefficients f the Primary Variables Used in the Analysis inc PINC %CLEAR PINC %CLEAR MAP MAS ET %MAS AREA ELEV MAP MAS ET %MAS AREA In stepwise regressins f INC nly tw independent variables entered the equatins at significant levels, in the rder shwn: INC = MAP %CLEAR; standard errr ; p < 0.Q1. The cumulative adjusted R2'S were and Fr the prprtinal increment fur variables entered. PINC = LN%NlAS %MAS LN%ET %CLEAR; standard errr 0.377; P<O.Ol. This equatin had cumulative adjusted 98

7 a 500 U 400 ~ j :::p::~q: ~ '70 CLEAR 0 '" 300 W 100 0:; a t--.~~~~_~~~_~~~~~' \ ' MAP " b 35, b 35 3 ~ 2.5 0: 2 '.5 5 n. en. n 0 n DO 25 '" 2 ~ 15 tii, %CLEAR FIGURE 3. Scatter plts f abslute (a) and prprtinal (b) change in streamflw fr percentage f basin vegetatin cleared. R2's f 0.593,0.710, 0.744, and This equatin may have value fr management, but because f the multicllinearity induced by using MAS in the calculatin f bth PINC and %MAS may be difficult t interpret, hwever, the actual hydrlgical cnnectins shuld be cnsidered. In the regressin f the residual (RES) f the regressin f INC ~ %CLEAR n MAP the equatin was: RES = MAP, adjusted R2;.247, standard errr , p<.001. Here the residuals increase linearly with increasing precipitatin, with negative :esiduals in areas f lw precipitatin, a balance f negative and psitive residuals in the middle ranges, and psitive residuals with high precipitatin (Figure 4a). In the regressin f the residual MAP FIGURE 4. Scatter plts f residuals f abslute (a) and prprtinal (b) change in streamflw regressed n percentage f basin vegetatin cleared ver mean annual precipitatin. (%RES) f PINC n %CLEAR, the equatin was: %RES = MAP, adjusted R2;.254, standard errr 0.214, p <.001. Here the residuals are highest in the driest areas (Figure 4b). Given the relatins f the residuals t precipitatin, the subdivisin by precipitatin level becmes interesting. Table 2 shws the regressin equatins fr the five precipitatin classes fr INC n %CLEAR, and fr PINC n %CLEAR. Amng the classes a significant relatin is fund nly in the mm class. Within small ranges f precipitatin, such as might be fund within a given regin, n predictable relatin between vegetatin treatment and altered streamflw is fund except fr this ne class. Why this class shu Id shw a pattern when hig her r slightly lwer classes d nt cannt 99

8 TABLE 2 Regressin Equatins fr the Set f Data Subdivided Int Five Classes f Precipitatin with Nearly Equal Number f Cases Per Class be explained by these data. Of these nine pints, tw are in Duglas fir in Oregn, five are in mixed hardwds in Nrth Carlina, and tw are in high mntane bamb in Kenya. This result may represent Type I errr. It is als ntable that in bth cases the significant regressins have intercepts clsest t the rigin. It may be that there is less variatin in the kinds f secndary influences discussed abve amng these cases. Nne f the regressins are significant fr the specific areas examined: Duglas fir at Andrews, mixed hardwds at bth Cweeta and Fernw, and chaparral at Three Bar and White Spar. This lack f predictability within given areas reinfrce)s Trimble et a/.'s (1987) finding fr the Gergia Piedmnt. Fr the abslute increase, fur utliers are particularly ntewrthy (i.e., thse greater than 400 mm) (Figure 3a). These fur utliers are frm areas f high precipitatin (Table 3), but they are nt the nly such cases. The tw sites at Maimai, N.Z., hwever, represent nly the first year increase, and the tw sites in Oregn were burned as well as cleared; the frmer difference wuld certainly cntribute t the higher respnses, the latter might als. When 100

9 these fur cases are deleted, the equatin changes t: INC = %CLEAR, adjusted R2: 0.091, standard errr: 0.419, p <.05. Fr the prprtinal increase, three utliers are ntewrthy (i.e., thse greater that 200%) (Figure 3b). These three utliers are frm areas f lw precipitatin (Table 3), but they are nt the nly such cases. All are frm the same area, and all were subjected t multiple treatments, which may have lead t higher respnses. When these three cases are deleted the equatin changes t: PINC = %CLEAR, adjusted R2: 0.048, standard errr: 0.001, p >.06. DISCUSSION Unlike earlier interpretatins f the same data we find that the predictability f water yield t vegetatin treatment is lw. Because we use the less sensitive five-year average, wherein different recvery rates are cmbined, instead f first-year respnse, the amunt f variatin explained in ur study drps frm 38 percent (Trimble et al. 1987) t 10 percent. When we examined the prprtinal change in streamflw, the relatin lst significance altgether. When we examined the verall statistics and the residual f the relatin between yield and treatment we see that reginal hydrclimatlgical variables explain much f the respnse. When we examine a subdivisin f the data by precipitatin class significant relatins are I"are, and when we examine specific experimental areas they are nnexistent. If the experiments had varied s that cleared area varied with precipitatin, then the difference in significance between the separate precipitatin classes and the aggregated data wuld be due t a data prblem, but there is n systematic relatin between precipitatin and management treatment. The differences in Figure 1 a and 1 b may give sme indicatin f a physical explanatin. Where precipitatin and bimass are high, changes in area cleared will have a greater effect n abslute changes because f the high rates f water transfer alng all pathways. Fr the same reasn any change will have less prprtinal effect in this system. Cnversely, in the dry areas with less bimass anv treatment will have less abslute effect, but can be prprtinally higher. The analysis f the residuals indicates that the effects f treatment are, hwever, biased bv precipitatin. The actual changes in streamflw shw better respnse fr treatment area in wet areas, while the prprtinal increase in streamflw shws a better respnse t treatment in the dry areas, but this respnse is influenced by utliers. This bias in the utliers may be the strngest explanatin fr why significance f universal pattern fr aggregated data is fund while lcal patterns are nt significant. This effect f utliers is demnstrated in part fr the abslute change in streamflw, where the deletin f the fur highest residuals leads t decreased explanatin, but in the analysis f the prprtinal change the deletin f the three highest residuals leads t an imprvement f the regressin int the area that sme wuld cnsider marginally statistically significant. These effects mal' als arise because precipitatin mre strngly affects the initial respnse while differences in vegetatin recvery affect the five-year respnse. CONCLUSION Bth the universal and lcal effects f vegetatin management are cnditined by the reginal pattern f hydrclimatlgy. At the lcal scale the effects f treatments seem t be relatively unpredictable. Within lcal areas the variability f secndary influences becme imprtant. Ntable lcal influences are patterns f natural vegetatin, vegeta- 101

10 tin treatment gemrphlgy, and f snw, which are themselves related. The pattern f riparian vegetatin may be especially significant (Malansn, 1993). In the future mre site specific appraches using prcess mdels will be mre useful. Many spatially explicit basin hydrlgical mdels are being develped (Band and Wd, 1988). These mdels can take int accunt patterns f vegetatin, gemrphlgy, and hydrlgy and calculate a hydrlgical budget fr specific basins with hypthetical vegetatin management plans. The wider availability f prcess mdels eventually will render the statistical apprach bslete, but in the meantime its prblems must be recgnized. The statistical apprach shws that at the aggregate level a general pattern emerges, but althugh significant, it is weak. Part f this result may be due t the increase in sample size alne. An additinal prblem which shuld be cnsidered is the lack f independence amng cases bth serial and spatial autcrrelatin are prbable in these data. It is clear that the general result, which is presented in hydrlgy textbks withut caveat, cannt be used t guide water resurces management at particular lcatins. REFERENCES Band, L. E. and Wd, E. F Strategies fr Large-scale, Distributed Hydrlgic Simulatin. Applied Mathematics and Cmputatin, 27, Bsch, J. M. and Hewlett, J. D A Review f Catchment Experiments t Determine the Effect f Vegetatin Changes n Water Yield and Evaptranspiratin. Jurnal f Hydrlgy, 55, Bsch, J. M. and Hewlett, J. D The Dependence f Strm Flws n Rainfall Intensity and Vegetal Cver in Suth Africa. Jurnal f Hydrlgy, 75, Duglass, J. E The Ptential fr Water Yield Augmentatin frm Frest Management in the Eastern United States. Water Resurces Bulletin, 19, Dunne, T. and Lepld, L. B Water in Envirnmental Planning. W. H. Freeman, San Francisc, Harr, R. D Ptential fr Augmenting Water Yield Thrugh Frest Practices in Western Washingtn and Western Oregn. Water Resurces Bulletin, 19, Hewlett, J. D Principles f Frest Hydrlgy. University f Gergia Press, Athens. Hibbert, A. R Frest Treatment Effects n Water Yield. Internatinal Sympsium n Frest Hydrlgy, edited by W. E. Sapper and H. W. Lull, pp , Pergamn Press, Oxfrd. Hibbert, A. R Water yield imprvement ptential by vegetatin management n western rangelands. Water Resurces Bulletin, 19, Hicks, B. J., Beschta, R. L., and Harr, R. D Lng-term Changes in Streamflw Fllwing Lgging in Western Oregn and Assciated Fisheries Implicatins. Water Resurces Bulletin, 27, Kattelman, R. C., Berg, N. H., and Rectr, J The Ptential fr Increasing Streamflw frm Sierra Nevada Watersheds. Water Resurces Bulletin, 19, Kucera, Predictin f Water Yield Reductins Fllwing a Bushfire in Ash-Mixed Species Eucalypt Frest. Jurnal f Hydrlgy, 94, Malansn, G. P Riparian Landscapes. Cambridge University Press, Cambridge. Patric, J. H. and Reinhart, K. G Hydrlgic Effects f Defresting Tw Muntain Watersheds in West Virginia. Water Resurces Research, 7, Pnce, S. L. and Meiman, J. R Water Yield Augmentatin Thrugh Frest and Range Management-Issues fr the Future. Water Resurces Bulletin, 19, Trimble, S. w., Weirich, F. H., and Haag, B. L Refrestatin and the Reductin f Water Yield n the Suthern Piedmnt Since circa 1940, Water Resurces Research, 23, Trendle, C. A The Ptential fr Water Yield Augmentatin frm Frest Management in'the Rcky Muntain Regin. Water Resurces Bulletin, 19, Trendle, C. A. and King, R. M The Effect f Timber Harvest n the Fl Creek Watershed, 30 Years Later. Water Resurces Research, 21, Veen, A. W. L. and Dlman, A. J Water Dynamics f Frests: One-dimensinal Mdeling. Prgress in Physical Gegraphy, 13, Verry, E. S Frest Harvesting and Water: the Lake States Experience. Water Resurces Bulletin, 22,