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Hydrological effects of hypotheticalclimate change in the East Riverbasin, Colorado, USAGREGORY J. McCABE Jr a & LAUREN E. HAY aa US Geological Survey, Denver Federal Center , MS 412,Lakewood, Colorado, 80225, USAPublished online: 24 Dec 2009.

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HydrologicalSciences -Journal- des Sciences Hydrologiques,40,3, June 1995 3 0 3

Hydrological effects of hypothetical climate change in the East River basin, Colorado, USA

GREGORY J. McCABE, Jr & LAUREN E. HAY US Geological Survey, Denver Federal Center, MS 412, Lakewood, Colorado 80225, USA

Abstract In 1988, the US Geological Survey began a study of the effects of potential climate change on the water resources of the Gunnison River basin. The Gunnison River, in southwestern Colorado, is an important tributary of the Colorado River, contributing approxi­mately 40% of the flow of the Colorado River at the Colorado/Utah stateline. As part of the study, the sensitivity of annual and seasonal runoff in the East River basin, a sub-basin of the Gunnison River basin, to changes in temperature and precipitation was examined. To perform the sensitivity analyses, hypothetical climate changes were used to alter current time series of temperature and precipitation. The altered time series were then used as inputs to a hydrological model that translated these inputs into estimates of runoff. Mean annual and seasonal runoff resulting from a range of hypothetical climate changes were compared and evaluated. Results indicated that in general, changes in precipitation had a larger effect on changes in runoff than did changes in temperature. Changes in precipitation had significant effects on runoff during all seasons. Changes in temperature primarily affected the temporal distri­bution of runoff through the year. Changes in temperature affected the timing of snowmelt and the ratio of rain to snow, and therefore the effects of temperature were particularly significant during the spring and summer seasons. On an annual basis, increases in temperature led only to slight decreases in runoff. Results also indicated that the effects of an increase in mean annual temperature of 4°C on annual runoff could be offset by an increase in annual precipitation of between 4 and 5 %, and that the magnitude of natural climatic variability was large and might mask the effects of long term climate changes.

Effets hydrologiques de modifications climatiques potentielles dans la bassin de l'East River, Colorado, Etats-Unis Résumé En 1988, l'US Geological Survey a engagé une étude concernant les effets de modifications climatiques potentielles sur les ressources en eau du bassin de la rivière Gunnison. La rivière Gunnison, dans le sud ouest de l'état du Colorado, est un affluent important du fleuve Colorado. Elle contribue pour à peu près 40% au débit de ce fleuve à la limite entre les états du Colorado et de l'Utah. Dans le cadre de cette étude, on a étudié la sensibilité des écoulements annuels et saisonniers à des modifications des températures et des précipitations dans le bassin de l'East River, sous bassin de la rivière Gunnison. Pour réaliser les analyses de sensibilité, d'hypothétiques modifications climatiques ont été imaginées concernant les séries chronologiques

Open for discussion until 1 December 1995

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304 G. J. McCabe & L. E, Hay

actuelles de températures et de précipitations. Les séries ainsi modifiées ont été utilisées comme données d'entrée d'un modèle hydrologique qui les a transformées en écoulements estimés. Les résultats relatifs aux écoulements moyens annuels et saisonniers ont été comparés et évalués. Ils montrent qu'en général les effets dûs aux modifications des précipi­tations sont plus importants que ceux dûs aux modifications des tempéra­tures. Les modifications des précipitations ont un effet direct sur les écoulements qui est sensible quelle que soit la saison considérée. Les modifications de températures affectent principalement la distribution temporelle des écoulements au cours de l'année. Elles modifient le calendrier de la fonte des neiges et le rapport pluie sur neige. Par conséquent les effets des modifications de la température sont partic­ulièrement sensibles au printemps et en été. Sur l'ensemble de l'année, des augmentations de température ne produisent qu'une légère diminution des écoulements. Les résultats indiquent également qu'une augmentation de la température moyenne annuelle de 4 à 5°C peut être compensée par une augmentation des précipitations de 4 à 5 %, et que la grande ampli­tude de la variabilité climatique naturelle peut masquer les effets de modifications climatiques à long terme.

INTRODUCTION

Scientists have estimated that increasing concentrations of atmospheric carbon dioxide and other radiatively active gases will cause changes in regional temperature and precipitation (Gammon et al., 1985; Bolin, 1986; Lins et al., 1988). Changes in climate may affect hydrological processes such as precipi­tation, snowpack accumulation and melt, évapotranspiration, streamflow, and recharge to subsurface storage (Gleick, 1987, 1989; Rango & van Katwijk, 1990; Kuhn & Parker, 1992). These potential changes in climate may have important effects on the water resources of the western United States.

Previous studies that have examined the effects of potential climate change on water resources in the western United States include those by Gleick (1987), Lettenmaier & Gan (1990), Rango & van Katwijk (1990) and Nash & Gleick (1991, 1993). Gleick (1987) examined the sensitivity of soil moisture and runoff in northern California to changes in temperature and precipitation using a water balance model. Results indicated that changes in precipitation and temperature had major effects on the timing and magnitude of runoff and soil moisture. Increases in temperature produced increases in winter runoff and decreases in summer runoff. Lettenmaier & Gan (1990) examined the sensi­tivity of streamflow in four medium-sized mountainous watersheds in the Sacramento and San Joaquin River basins in California to changes in tempera­ture and precipitation by coupling the snowmelt and the soil moisture accounting models of the US National Weather Service River Forecast System. In all four basins they found a significant seasonal shift in snow accumulation as temperature was increased. The increase in temperature caused more winter precipitation to fall as rain rather than as snow and produced a shift in runoff from the spring to the winter due to earlier snowmelt. Rango & van Katwijk (1990) used a snowmelt-runoff model to examine the effects of changes in climate (e.g. temperature and precipitation) on runoff in the Rio Grande basin. They reported that increases in temperature caused increases in runoff during

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Hydrological effects of hypothetical climate change 305

the spring in April and May and decreases in runoff during summer months. Nash & Gleick (1991, 1993) examined the sensitivity of streamflow in several sub-basins of the Colorado River basin to regional changes in precipitation and temperature using a conceptual hydrological model. They found that runoff was more sensitive to changes in precipitation than to changes in temperature. Their results also indicated that, with increases in temperature, seasonal runoff shifted to earlier in the year, generally producing decreases in summer runoff and increases in winter/spring runoff.

Previous research has indicated that runoff in many river basins in the western United States is sensitive to changes in temperature and precipitation. Previous research has also shown that both the timing and the magnitude of runoff in high-elevation river basins can be affected by changes in climate. Because runoff from high-elevation river basins represents a large percentage of the water supply in the western United States, it is important to understand the effects of climate change and variability on runoff from these basins. There is concern that climate change may have an adverse effect on the limited water resources in the arid and semi-arid regions of the western United States. Thus research is needed to increase the understanding of the sensitivity of water resources in high-elevation river basins in the western United States to climatic variability and climate change. The objectives of this study were to perform a preliminary assessment of the effects of a range of hypothetical climate changes on runoff in the East River basin in southwestern Colorado and to examine these effects in relation to natural variability.

THE STUDY AREA

The East River basin is a sub-basin of the Gunnison River basin. The Gunnison River is an important tributary of the Colorado River (Figs 1(a) and 1(b)). The Gunnison River contributes approximately 40% of the flow of the Colorado River at the Utah/Colorado stateline, and the East River accounts for approximately 25% of the flow in the Gunnison River basin (Ugland et al., 1990). The East River basin was chosen for this study because it is an important water resource in the Colorado River system and is representative of many high-elevation river basins in the upper Colorado River basin that supply much of the water to downstream users.

Current climate and runoff

Mean monthly temperature, precipitation and runoff for the East River basin are illustrated in Fig. 2 (average values for water years 1973-1989). Monthly temperature and precipitation data were obtained from the Crested Butte meteorological station and runoff data were obtained from the gauge at Almont (Fig. 1). Mean monthly temperatures range from just below -10°C during

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306 G. J. McCabe & L. E. Hay

Fig. 1 Locations of (a) the Gunnison River basin; (b) the East River basin; and (c) the Crested Butte meteorological station, the Almont stream gauging station and 5 x 5 km grid cells used to represent hydrological response units (HRUs).

1 I T O N D J F M A M J J A S

Month Fig. 2 Mean monthly temperature, T (°C), precipitation, P (mm) and runoff, Q (mm) for the water years 1973-1989 for the East River basin. Temperature and precipitation data were obtained from the Crested Butte meteorological station and runoff data were obtained from the streamgauge at Almont.

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Hydrological effects of hypothetical climate change 307

January to almost 13°C during July. Mean monthly temperatures are below 0CC from November to March. Precipitation is not as variable from month to month as is temperature, but is higher during November-March than during the rest of the year (Fig. 2).

Because the mean monthly temperatures are below or just above freezing from October to April, potential évapotranspiration (PET) is low and precipi­tation exceeds PET during these months producing a surplus of water that is available to fill soils to their moisture holding capacities and to become runoff. During the summer months, PET exceeds precipitation and little of the summer precipitation becomes runoff. Because of the freezing temperatures during the winter months, the majority of the precipitation during the winter season falls as snow and accumulates throughout the winter. Thus the surplus of precipita­tion in excess of PET that occurs during the cold months is stored as snowpack accumulations.

The snow accumulations melt as temperatures increase to above freezing point during the spring. The effects of snowmelt are evident in the mean monthly values of runoff (Fig. 2). Runoff is relatively low for most of the year, except during the spring and summer months when snowmelt occurs. The majority of the annual runoff in the East River basin occurs during the months from April to August, with the peak occurring during June. Because the snowmelt accounts for such a large proportion of the annual runoff, snowpack accumulations measured on or about 1 April (the period when the snow accumulations generally reach their maximum values) can be used to estimate annual runoff in the East River basin. A regression of annual runoff measured at Almont for the water years 1973-1985 with 1 April snowpack measurements in the East River basin indicates that 70% of the variability of annual runoff in the East River basin can be explained by variations in 1 April snowpack accumulations.

METHODS

In this study, a hydrological model was used to simulate runoff in the East River basin for current climatic conditions, and for prescribed hypothetical climatic conditions that represent a range of possible climate changes. The hypothetical changes in climate included changes in mean seasonal and annual temperatures of-4°C,0°C, and +4°C and changes in precipitation of -20%, 0%, and +20% (a total of nine scenarios) (Gleick, 1989). These changes in climate were computed by uniformly changing current values of daily tempera­ture and precipitation by the specified amounts for all months of the year. By altering the current time series, the natural temporal variabilities in temperature and precipitation were preserved. The current and altered time series of daily temperature and precipitation were input to a hydrological model to simulate time series of daily runoff. The resulting time series of runoff were then compared on a seasonal and annual basis to evaluate the effects of changes in

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308 G. J. McCabe & L. E. Hay

temperature and precipitation on runoff in the East River basin. Annual analyses were performed on a water year basis and seasonal analyses were performed for winter (January, February and March), spring (April, May and June), summer (July, August and September), and autumn (October, November and December).

The hydrological model

The hydrological model used in this study is the US Geological Survey's Precipi­tation-Runoff Modelling System (PRMS) (Leavesley et al, 1983). PRMS is a modular-design, distributed-parameter, physical-process watershed model that was developed to evaluate the effects of various combinations of precipitation, climate and land use on watershed response. Watershed response to normal and extreme rainfall and snowmelt can be simulated to evaluate changes in water balance relations, flow regimes, flood peaks and volumes, soil-water relations, sediment yields, and groundwater recharge (Leavesley et al,, 1992). A complete description of PRMS can be found in Leavesley et al. (1983).

Distributed parameter capabilities are provided by partitioning a watershed into physically relatively homogenous units. Each unit is assumed to be homogenous with respect to its hydrological response and is called a hydrological response unit (HRU). A water balance is computed daily and an energy balance is computed twice each day for each HRU. The sum of the responses of all HRUs, weighted on a unit-area basis, produces the daily water­shed response (Leavesley et al., 1992). In this study, the HRU's were delineated using a geographical information system (GIS) with 5 x 5 km grid cells covering the basin following the method of Battaglin et al. (in press) (Fig. 1(c)). Battaglin et al. found that a 5 x 5 km grid resolution was adequate to describe the variability in most physical characteristics of drainage basins in the Gunnison River basin.

The snow components of PRMS simulate the accumulation and depletion of a snowpack on each HRU. A snowpack is maintained and modified both as a water reservoir and as a dynamic heat reservoir. An energy balance approach is used to simulate the snowmelt processes. The energy balance computations include net shortwave and longwave radiation, approximation of convection and condensation terms, and the heat content of precipitation.

Model inputs were daily precipitation, maximum and minimum air temp­erature, and solar radiation. Daily climate data were obtained for each HRU or extrapolated to each HRU using data from meteorological stations and a set of user-defined adjustment coefficients developed from regional climate data (Leavesley et al, 1983, 1992).

The East River basin contains 43 HRUs that are complete or partial 5 x 5 km grid cells (Fig. 1(c)). PRMS parameters were estimated for each HRU using relations between parameter values and measurable basin and climatic characteristics that were defined in previous studies (Leavesley et al., 1992).

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Hydrological effects of hypothetical climate change 309

PRMS parameters were not calibrated to observed runoff and climate inputs in the East River basin because the objective of the study was to evaluate the effects of altered climatic conditions on runoff. Some of the parameters in PRMS are sensitive to climate inputs. By fitting model parameters to current runoff and climate time series, a bias toward current climatic conditions would be introduced into the model parameters. This bias might affect simulations of runoff when altered climate time series, representing future climatic conditions, come to be used as model inputs. In addition, by calibrating the model, errors in observed data, such as precipitation, are included in the fitted parameters. Nash & Gleick (1991) suggested that the use of calibrated models for climate change studies could produce erroneous results if the climatic conditions used for climate change scenarios differed significantly from the climatic conditions used to calibrate the hydrological model. In addition, Nash & Gleick (1991) pointed out that because hydrological models often include many parameters, several combinations of parameter values could be used to develop equally good calibration fits to observed data, but would have different effects on model sensitivity to climate inputs.

Climate and runoff data

Temperature data were obtained from a National Weather Service meteoro­logical station at Crested Butte for the water years 1973-1989 (17 years) (Fig. 1(c)). Solar radiation data were not available so solar radiation was estimated as a function of daily maximum temperature using procedures provided in PRMS. These values of solar radiation were not changed in the hypothetical climate change scenarios. Measured runoff data were computed from stream-flow measured at Almont, Colorado (Fig. 1(c)).

Because precipitation measurements were available for only one station in the East River basin before 1982 (the Crested Butte station) and because the complex terrain made extrapolation of precipitation data from this one station to all areas of the basin difficult, modelled precipitation was used from October to April and data from the Crested Butte station were used from May to Sep­tember. The modelled precipitation was obtained for each 5 x 5 km HRU from an orographic precipitation model applied to the Gunnison River basin by Leavesley et al. (1992). Those authors found that the orographic precipitation model provided improved spatial resolution and better estimates of the temporal variability of October-April precipitation than could be achieved by extra­polation from the Crested Butte station. May-September precipitation accounts for only a small portion of annual runoff and is not simulated well by the orographic precipitation model used by Leavesley et al. (1992). Therefore, for simplicity, during these months precipitation data measured at Crested Butte were applied uniformly to all HRUs.

Although the hydrological model was not calibrated to runoff measured in the East River basin, the model was able to simulate reliably seasonal and

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310 G. J. McCabe & L. E. Hay

annual runoff in the East River basin (Leavesley et al, 1992). Figure 3 illustrates the time series of observed and simulated monthly runoff for the water years 1973-1989. The correlation between the two time series was 0.91. Table 1 presents a statistical comparison of observed runoff to simulated runoff for these water years. The statistics used in the comparison were the coefficient of determination (r2), the root mean square error (RMSE), the index of agree­ment (£>), and the mean observed and simulated values of annual and seasonal runoff.

100 150 200 Time (months)

Fig. 3 Simulated and observed monthly runoff (mm) in the East River basin for the water years 1973-1989.

Table 1 Statistical comparison of observed and simulated runoff for the water years 1973-1989

RMSE (mm) D XOBS (mm) XPRED (mm)

Winter Spring Summer Autumn

Annual

0.60 0.59 0.87 0.56

0.79

3.1 48.5 23.9 11.4

64.8

0.51 0.80 0.87 0.75

0.94

19.1 252.2 101.6 29.0

401.8

11.4 205.5 135.1 36.3

388.1

r2 = coefficient of determination; RMSE = root mean square error; D = index of agreement; XOBS = mean of observed runoff; and XPRED = mean of simulated runoff.

The index of agreement was used because the coefficient of determination cannot account for additive differences or differences in proportionality (Willmott, 1981). The index of agreement is sensitive to differences between

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Hydrological effects of hypothetical climate change 311

observed and simulated means as well as to certain changes in proportionality (Willmott, 1981). The index of agreement (D) was computed by:

D = 1.0- ; = 1

E ( | P ; - O | + | C ; - O | ) 2

(1)

where Pt is the model simulated value, Oi is the corresponding observed value, and Ô is the mean of the observed data. The index of agreement is dimension-less and ranges between 0.0 and 1.0, where 0.0 describes complete disagree­ment between the simulated and observed values and 1.0 indicates that the simulated and observed values are identical.

The simulated values of runoff from the hydrological model explained 79% of the variability in observed annual runoff (Table 1). Seasonally, the simulated values explained from 56 to 87% of the variability in observed runoff (all coefficients of determination were significant at a 99% confidence level). Root mean square errors in simulated runoff ranged from 16% of observed runoff for the annual and winter values, to 39% for the autumn season. The index of agreement was at least 0.75 for the annual and seasonal comparisons, except for the winter season.

Because the hydrological model was not calibrated, a near-perfect fit of simulated to observed runoff was not expected. The statistics comparing the observed runoff to the simulations from the non-calibrated hydrological model indicated that the model simulated reasonable values of seasonal and annual runoff. In addition, the ability of the hydrological model to simulate reliably the seasonal and annual variability in runoff (as indicated by the coefficients of determination in Table 1) showed that the model realistically responded to variability in climate inputs and could reasonably simulate changes in runoff resulting from variability and changes in climate.

RESULTS AND DISCUSSION

Changes in mean seasonal and annual runoff for each of the hypothetical climate change scenarios expressed as a difference from current conditions, and as a percentage change from current conditions (in parentheses), are presented in Table 2. Analysis of the effects of changes in temperature on changes in annual runoff indicated that changes in temperature had only a minor effect on the magnitude of annual runoff. The effects of changes in precipitation on changes in annual runoff were about three to seven times as great as the effects of changes in temperature.

The results also indicated that the largest absolute changes in runoff almost always occurred during the spring and summer seasons (Table 2). These

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312 G. J. McCabe & L. E. Hay

Table 2 Changes in mean seasonal and annual runoff expressed as a difference from current conditions (mm) and as a percentage change from current conditions (% in parentheses) resulting from specified hypothetical changes in temperature and precipitation

Climate scenario

Temperature change

No change No change No change +4°C +4°C +4°C - 4 ° C - 4 ° C - 4 ° C

Precipitation change

+20% No change - 2 0 % +20% No change - 2 0 % +20% No change - 2 0 %

Change in

Winter

+ 3(+26) -- 3 ( - 2 6 ) + 8(+70) +4( + 35) - K - 9 ) + 5(+44) +2( + 17) - 2 ( - 1 7 )

runoff [mm(%)]

Spring

+43(+21) --49 ( -24 ) + 80(+39) +24( + 12) -34 ( -17 ) -32 ( -16 ) - 55 ( -27 ) - 84 ( -41 )

Summer

+55(+41) --46 ( -34 ) —19(—14) — 51( —38) -76 ( -56 )

Autumn

+ 12( + 33) --10 ( -28 ) +21( + 58) + 7(4-19) - 6 ( - 1 7 )

+ 174(+129)+9(+25) + 91( + 67) + 15(+11)

- 2 ( - 6 ) - l l ( - 3 0 )

Annual

+ 114(429) --107( -28) +90(+23) - 1 6 ( - 4 ) -116( -30) + 157(+40) + 36(+9) -81( —21)

results suggested that the hypothetical changes in temperature had an effect on the timing of snowmelt and subsequent runoff during the spring and summer seasons. For example, for the scenarios that included an increase in tempera­ture and no decreases in precipitation, runoff for the spring season increased and summer runoff decreased. In contrast, for the scenarios with a decrease in temperature and no decreases in precipitation, spring runoff decreased and summer runoff increased. The increase in temperatures produced an earlier snowmelt and subsequently less summer runoff, and decreases in temperature generally produced snowmelt later in the water year and increased summer runoff (Fig. 4). Changes in precipitation, however, directly affected the magnitude of runoff during all seasons (Table 2, Fig. 5). The smallest absolute changes in runoff, resulting from changes in precipitation, occurred during the winter season (Table 2). This was because, during the winter season, the majority of the precipitation fell as snow and accumulated. Therefore, changes in winter precipitation resulted in only small changes in winter runoff.

Correlations between the changes in temperature and precipitation and changes in runoff were computed to evaluate the relative strengths of the effects of changes in temperature and precipitation on changes in runoff (Table 3). Correlations between the hypothetical changes in precipitation and changes in runoff indicated that changes in precipitation had a large effect on changes in seasonal and annual runoff. This is not surprising because precipitation repre­sented the input of water that ultimately became runoff. Correlations between changes in temperature and changes in runoff indicated that changes in temp­erature only had effects on runoff comparable to those of changes in precipi­tation during the spring and summer seasons. During the spring, changes in temperature had an effect on the ratio of rain to snow which affected spring runoff, and during both the spring and summer seasons, changes in temperature affected the timing of snowmelt runoff. As temperatures increased, peak runoff shifted to earlier in the year, generally causing decreases in summer runoff (as indicated by the strong negative correlation) and increases in spring runoff (as indicated by the positive correlation).

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Hydrological effects of hypothetical climate change

200-

313

1 5 0 -

E

15 100-

5 0 -

No change T - 4°C

1 1 1 I 1 I I OCT NOV DEC JAN FEB MAR APR MAY JUN JUL AUG SEP

Fig. 4 Mean monthly runoff (mm) in the East River basin simulated for current climatic conditions (No Change), for a 4°C increase in temperature (T + 4°C), and for a 4°C decrease in temperature (T - 4°C).

200 - i

150-

sioo-

50-

No change ,< \ P + 20%

OCT NOV DEC JAN FEB MAR APR MAY JUN JUL AUG SEP Fig. 5 Mean monthly runoff (mm) in the East River basin simulated for current climatic conditions (no change), for a 20% increase in precipitation (P + 20%), and for a 20% decrease in precipitation (P - 20%).

A comparison of the magnitudes of the correlations indicated that, except for the summer season, changes in precipitation had a greater effect on changes in runoff than did changes in temperature. A regression of changes in annual runoff with changes in mean annual temperature and annual precipitation indi­cated that the effects of a 4°C increase in temperature (this is 5.4 standard deviations of mean annual temperature) on runoff could be offset by a 4-5 % increase in mean annual precipitation (about 0.18 standard deviations of mean annual precipitation).

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G. J. McCabe & L. E. Hay

Table 3 Correlations between hypothetical changes in temperature and precipitation and changes in runoff

Changes in temperature Changes in precipitation

Winter +0.23 +0.89** Spring +0.66** +0.71** Summer -0.78** +0.58 Autumn +0.34 +0.93** Annual -0.23 +0.97**

** correlations significant at a 99% confidence level.

The results of this study were similar to those of other studies that examined the effects of potential climate change on water resources in the western United States (Gleick, 1987; Lettenmaier & Gan, 1990; Rango & van Katwijk, 1990; Nash & Gleick, 1991, 1993). In these studies, when the effects of an increase in temperature on runoff were examined, results indicated a shift in seasonal runoff to earlier in the year, generally producing decreases in summer runoff and increases in winter/spring runoff. Nash & Gleick (1991, 1993) performed an evaluation of the effects of climate change on seasonal and annual runoff in the East River basin. Similar to the results of this study, Nash & Gleick found that annual runoff in the East River basin was more sensitive to changes in precipitation than to changes in temperature. Nash & Gleick (1991, 1993) showed that annual runoff in the East River basin decreased 16.5% with a hypothetical temperature increase of 4CC. The results of this study showed only a 4% decrease in annual runoff with a hypothetical tempera­ture increase of 4°C. These differences would be due, in part, to the different modelling algorithms used in each study to compute the hydrological processes such as snowmelt and evaporation. In addition, Nash & Gleick used a cali­brated model that was not validated. They pointed out that the use of a cali­brated model is problematic for climate change studies if the climate change scenarios differ significantly from the climatic conditions used to calibrate the model (Nash & Gleick, 1991). In the study presented in this paper, model cali­bration was not performed in order to avoid those problems. Although there were some differences in the magnitudes of changes in runoff estimated by this study and by the Nash & Gleick study, the general directions of changes in runoff, and the relative inter-seasonal changes in runoff, in response to changes in temperature and precipitation estimated by both studies were similar.

Effects of natural variability

The changes in runoff resulting from changes in temperature and precipitation discussed in this study were also evaluated with respect to natural climatic variability. Natural climatic variability has a large effect on mean seasonal and annual runoff. For a given expected climate, natural variability creates the potential for a wide range of climatic conditions. For example, in this study,

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Hydrological effects of hypothetical climate change 315

annual and seasonal runoff were computed for each of 17 water years. Thus, for each of the specified climatic conditions, 17 values of annual and seasonal runoff were computed. Figure 6 illustrates a comparison of the distributions of annual runoff values for current climatic conditions, conditions with a tempera­ture increase of 4°C, and conditions with both a 4°C increase in temperature and a 20% decrease in precipitation. The range of each distribution was wide and there was a large amount of overlap between the distributions for the three climate scenarios. The overlap in these distributions indicated that the effects of natural climatic variability are large and can mask the effects of climate changes. Thus, even if accurate estimates of future climatic conditions could be made, a wide range of runoff values would be possible because of unpre­dictable random variability in precipitation and temperature.

0.5-

0 . 4 -

I 0.3 H

ce 0 . 2 -

0.1-

0.0-

T + 4°C, P - 20%

0

T + 4°C

No change

200 600 800 400 Annual runoff (mm)

Fig. 6 Distributions of annual runoff (mm) in the East River basin simulated for current climatic conditions (no change), for a 4°C increase in temperature (T 4- 4°C), and for both a 4°C increase in temperature and a 20% decrease in precipitation (T + 4°C, P - 20%).

Because of the large amount of natural variability in temperature, precipitation and runoff, changes in runoff resulting from climate change may take many years to be detected (McCabe & Wolock, 1991, 1992). To illustrate this point a stochastic equation was used to generate time series of annual mean temperature and annual precipitation that were subsequently used to estimate annual runoff. In these time series, mean annual temperature was increased linearly at a rate of 4°C per 100 years and mean annual precipitation was decreased at a rate of 20% per 100 years. The standard deviations of mean annual temperature and precipitation were held at current (1973-1989) values

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(0.74°C and 202 mm respectively). This scenario was not intended to represent the most likely climate change scenario, but was within the range of the scenarios examined in this study and represented an extreme change. This scenario was chosen to induce a change in annual runoff in order to examine the effects of natural climatic variability on the detection of trends in runoff.

Examination of the distributions of current annual mean temperatures and annual precipitation (1973-1989) indicated that both variables appeared to be normally distributed. Therefore, the following equation was used to generate the time series of annual mean temperatures:

Tj = [Tm + (0.04/)] + (TsDj) (2)

where Tj is the predicted annual mean temperature in year j , Tm is the mean annual temperature for the years 1973-1989, Ts is the observed standard deviation of annual mean temperature, and Dj is a standard normal random deviate with a mean of zero and a variance of one (Press et al., 1986). The component (0.04/) induces a gradual warming trend of 4°C per 100 years.

Time series of annual precipitation were generated by using the following equation:

Pj = {pm * [l - (0.002/)]} + (PsD'j) W

where P- is the predicted annual precipitation for year j , Pm is the observed mean annual precipitation for the years 1973-1989, Ps is the observed standard deviation of mean annual precipitation and Dj is a standard normal random deviate with a mean of zero and a variance of one. The component [1 - (0.002/)] induces a gradual decrease in mean annual precipitation of 20% per 100 years.

Given a sequence of random deviates, Dj and Dj, and the parameters Tm, Ts, Pm and Ps, and excluding the components that induce a gradual warming and a gradual decrease in precipitation, equations (2) and (3) generated a sequence of temperature and precipitation values that were similar in their statistical properties to the observed time series for the East River basin. The Tj and P- values were taken as a time series of annual mean temperature and annual precipitation and in this study, for simplicity, zero autocorrelation was assumed.

Equations (2) and (3) were used to generate multiple time series of annual mean temperature and annual precipitation for the East River basin. The only difference among the multiple time series was the random number sequence used to add "noise" to the time series. These time series were used with a regression equation to generate time series of annual runoff. The regression equation was developed using the annual runoff simulated for the nine climate change scenarios discussed in this study (Table 2) as the dependent variable and values of annual temperature and precipitation for the nine climate change scenarios as the independent variables. The simulated results for the climate change scenarios were used to include the effects of a wide range of changes in temperature and precipitation on annual runoff.

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Hydrological effects of hypothetical climate change 317

0 120 30 60 90 Length of time series (years)

Fig. 7 Percentage of simulations indicating a significant decrease in annual runoff for time periods of 10-150 years in length for a gradual warming of 4°C per 100 years and a gradual 20% decrease in precipitation per 100 years. The trend in runoff was identified by computing Kendall's slope and the significance of the slope was determined using Kendall's tau statistic (Hirscheïa/., 1982).

One hundred simulations of 150-year long time series were performed. Trend statistics for annual runoff were computed for incrementally (increased by 10-year increments) longer periods of the 150-year long simulations (i.e. 10 years, 20 years, 30 years, ..., 150 years). The slopes of the trends in runoff were calculated from estimates of Kendall's slope (Hirsch et al., 1982), and the significance of the trend was tested with Kendall's tau statistic (Press et al., 1986). The percentage of the 100 simulations that showed a significant trend (at a 95% confidence level) was determined for each period.

The results of this analysis for a gradual increase in temperature of 4°C per 100 years and a gradual decrease in precipitation of 20% per 100 years indicated that it takes between 80 and 90 years to have at least a 50% chance of detecting a significant decrease in annual runoff at a 95 % confidence level (Fig. 7). This result indicated the masking effect natural climatic variability can have on the detection of changes in annual runoff. Thus, meaningful long term trends in hydrological variables may occur that may not be detected for many decades into the future. The long term effects of climate change on hydro-logical variables therefore might be discounted even though they may even­tually be problematic.

CONCLUSIONS

A non-calibrated physically-based hydrological model was used to simulate runoff for a range of hypothetical climate change scenarios. The results

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indicated that changes in temperature had a minor effect on the magnitude of annual runoff, but strongly affected the temporal distribution of runoff by affecting the ratio of rain to snow during the winter and spring seasons, and by affecting the timing of snowmelt during the spring and summer seasons. In contrast, changes in precipitation had a large effect on the magnitude of seasonal and annual runoff. In addition, the magnitude of natural climatic variability is large and may mask the effects of long term climate changes.

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Hirsch, R. M., Slack, J. R. & Smith, R. A. (1982) Techniques of trend analysis for monthly water quality data. Wat. Resour. Res. 18, 107-121.

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Leavesley, G. H., Lichty, R. W., Troutman, B. M. & Saindon, L. G. (1983) Precipitation-runoffmodelling system user's manual. US Geological Survey Water-Resources Investigations Report 83-4238. USGS, Reston, Virginia, USA.

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Lettenmaier, D. P. & Gan, T. Y. (1990) Hydrological sensitivities of the Sacramento-San Joaquin River basin, California, to global warming. Wat. Resour. Res. 26, 69-86.

Lins, H. F., Sundquist, E. T. & Ager, T. A. (1988) Information on selected climate and climate-change issues. US Geological Survey Open-File Report 88-718. USGS, Reston, Virginia, USA.

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McCabe, G. J. & Wolock, D. M. (1992) Effects of climatic change and climatic variability on the Thornthwaite moisture index in the Delaware River basin. Climatic Change 20, 143-153.

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Nash, L. L. & Gleick, P. H. (1993). The Colorado River basin and climatic change: the sensitivity of streamflow and water supply to variations in temperature and precipitation. US Environmental Protection Agency Report EPA 230-R-93-009. US Environmental Protection Agency, Washington, DC, USA.

Press, W. H., Flannery, B. P., Teukolsky, S. A. & Vetterling, W. T. (1986) Numerical Recipes. Cambridge University Press, New York, USA.

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Ugland, R. C , Cochran, B. J., Hiner, M. M., Kretschman, R. G. Wilson, E. A. & Bennett, J. D. (1990) Water resources data for Colorado, water year 1990, volume 2, Colorado River basin. US Geological Survey Water-Data Report CO-90-2. USGS, Reston, Virginia, USA.

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Received 2 June 1994; accepted 27 November 1994

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