Relative Impacts of Climate Change and Land Cover Relative Impacts of Climate Change and Land Cover Change on Streamflow Using SWAT in the Change on Streamflow Using SWAT in the Clackamas River Watershed, USA Clackamas River Watershed, USA

To understand the spatial – temporal pattern of climate and land cover (CLC) change effects on hydrology, we used three land cover change (LCC) coupled scenarios to estimate the changes in stream ﬂ ow metrics in the Clackamas River Watershed in Oregon for the 2050s (2040 – 2069) and the 2080s (2070 – 2099). Coupled scenarios, which were split into individual and combined simulations such as climate change (CC), LCC, CLC change, and daily stream ﬂ ow were simulated in the Soil and Water Assessment Tool. The interannual variability of stream ﬂ ow was higher in the lower urbanized area than the upper forested region. The watershed runoff was projected to be more sensitive to CC than LCC. Under the CLC scenario, the top 10% peak ﬂ ow and the 7-day low ﬂ ow are expected to increase (2 – 19%) and decrease ( þ 9 to (cid:2) 20 cm s), respectively, in both future periods. The center timing of runoff in the year is projected to shift 2 – 3 weeks earlier in response to warming temperature and more winter precipitation falling as rain. High stream ﬂ ow variability in our ﬁ ndings suggests that uncertainties can stem from both climate models and hydrologic model parameters, calling for more adaptive water resource management in the watershed.

• Snow-influenced, forested watershed is more sensitive to CC than LCC.
• Hydrologic variability is higher in the urban, agricultural part than the forested part.
• Top 10% flow is projected to increase, while low flow is projected to decline.• Warming will shift the center timing of flow volume earlier from mid-May to late-April.Watershed scale hydrological predictions rely on the transfer of large-scale climate variables to more regional meteorological factors such as precipitation and temperature.The multi-ensemble means of different general circulation models (GCMs) have been popular among researchers for projecting future climate and impacts on streamflow.However, using multiple GCMs as inputs may increase data and modeling uncertainties, as climate and water resource projections vary between each GCM (Guimberteau et al. ; Thompson et al. ; Shen et al. ).
Under CC, the Willamette River Basin (WRB) in the Pacific Northwest (PNW) region will exhibit significant changes in water balance and temperature (Jaeger et al. ).The magnitude of change will vary based on seasonality and location, as well as regional climate interactions with land cover (LC) and land use (Jung & Chang ; Vano et al. b).Catchments in the WRB rely heavily on snowpack for summer water supply.The projected change in precipitation patterns showed that more precipitation would fall as rain than snow and snowpack will be drastically reduced in the Cascade range (Catalano et al. ).
Snow-fed rivers in the WRB provide essential water resources for irrigation and municipal consumption.Under CC, short-term drought risk is projected to increase in the summer due to earlier snowmelt and less precipitation (Jung & Chang ).As population increases, urban development sprawls toward city boundaries and converts rural landscapes into more impervious landscapes (Hoyer & Chang ).Water demand grows with population increases, adding stress to the currently vulnerable water system that is impacted by recent extreme climatic events in the region such as the 2015 drought (Marlier et al. ).Water demand in the Portland metropolitan area of the WRB is expected to increase in the coming decades under GCM scenarios and projected land-use change (Parandvash & Chang ).
Hydrologic modeling using data from downscales GCMs have underlying uncertainties that are yet to be quantified and resolved ( Jung et

Study area
We chose the CRW, located geographically between longitudes 121 45 0 12″ and 122 36 0 25″ E and latitudes 44 49 0 26″ and 45 22 0 20″ N in the Lower WRB of Oregon in the United States as the study area (Figure 1).   1. Evapotranspiration (ET) is an important component in the water balance equation when estimating streamflow, and we used the Hargreaves method for estimating ET in SWAT.The Hargreaves method is simpler than the Penman-Monteith method because it requires fewer input data (maximum and minimum daily temperature) while resulting in a reasonable estimation of ET.The simplicity of the Hargreaves, along with our limited input data, showed the best estimation of ET that led to the SWAT simulated flow closest to historical streamflow conditions.Additionally, as a temperature-based method, the Hargreaves method projects future ET with changes in temperature with CC.
After calibration, the simulated SWAT output will be daily streamflow in units of cubic meters per seconds (cms).In addition to examining the statistical distribution of the streamflow metrics we selected, we will also use the Kruskal-Wallis test to see how monthly changes are significantly different between individual and combined modeled scenarios.

LC and CC scenarios
To establish a baseline of historical LC scenario, the 2006   The MACA dataset was validated using reanalysis across the

Change in CT of flow
The mean center-of-volume date for the Clackamas river was found to be shifting earlier across all emission scenarios; both future simulation periods showed a shorter range than historical conditions (Figure 6).Observation of the results showed that in low climate emission scenarios, CT in the 2080s is earlier than the 2050s.However, in refer-

ACKNOWLEDGMENT
This research was sponsored by the Institute of Sustainable Solutions at PSU and Clackamas River Water Providers.We appreciate reviewers who clarified many points of the manuscript.Views expressed are our own and do not necessarily reflect those of the sponsoring agencies.
(CC) and rapid urbanization are likely to have strong impacts on water resources around the world (IPCC ).Water scarcity, distribution, and access to water remain as some of the biggest challenges in the 21st century.Billions of people globally will not have sustainable access to clean drinking water due to the impacts of global warming (Mukheibir ; Schewe et al. ).CC impacts the hydrologic cycles across multiple scales (Arnell & Gosling ; Hattermann et al. ).
al. ; Hattermann et al. ; Her et al. ).As trends of CC and urban development continue throughout the 21st century, researchers need to improve modeling techniques to more accurately predict the combined effects of climate and land use on water quantity and quality (Praskievicz & Chang ; Xie & Lian ; Chen et al. ).Models such as the Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) and Windows-based Hydrologic Simulation Program (WinHSPF) have also been used to access the separate and combined impacts of climate and land cover (CLC) change scenarios in surrounding watersheds (Praskievicz & Chang ).The U.S. Geological Survey's (USGS) Precipitation-Runoff Modeling System model was run by researchers in the region to model changes in runoff, and hydrological variability was expected to increase with seasonal flow becoming more sensitive to CC (Chang & Jung ).The close relationship between CC and land cover change (LCC) calls for a more systemic approach to modeling hydrology (Sterling et al. ; Devia et al. ; Dwarakish & Ganasri ).The semidistributed Soil and Water Assessment Tool (SWAT) model has been a useful tool utilized frequently by researchers to predict runoff, nutrient, and sediment transport (Raneesh & Santosh ; Arnold et al. ; Leta et al. ; Suttles et al. ; Hajihosseini et al. ).Additionally, SWAT is well capable of simulating and projecting hydrologic responses to CC and LCC in small to large watersheds, by allowing the feedback between CC and evaporative demand (Praskievicz & Chang ; Kim et al. ; Psaris ; Tan et al. ; Pervez & Henebry ).This study aims to investigate the hydrologic response to CC and LCC of the Clackamas River Watershed (CRW) in the WRB.CC and LCC closely interact with each other on multiple scales when used to predict hydrologic responses (Lahmer et al. ).The separate and combined impacts of CLC change on hydrology (Zhang et al. ) have been researched and applied in projecting streamflow (Kim et al. ; Zhang et al. ), stormwater runoff (Talib & Randhir ), water availability (López-Moreno et al. ), and water quality (Sun et al. ).However, the development of LCC scenarios that are representative of the variability and range in climate modeling remains difficult.Past studies have used statistically downscaled GCMs to model LCC, but uncertainties can still occur during data processing and scaling (Solecki & Oliveri ; Tan et al. ; Prestele et al. ).To reduce assumptions and uncertainties in hydrologic models, LCC modeling efforts must include a subset of CC models that are representative of a range of possible future scenarios (Turner et al. ; Vano et al. a).In terms of scale, past studies (He et al. ; Farinosi et al. ) often modeled and compared hydrologic responses at the basin scale, between sub-basins, or across two different basins with similar climate and topography.As humans influence CLCs with increasing urbanization, modeling CLC changes on a landscape gradient from urban to rural is becoming more critical, as it can distinguish land-use change processes and different types of disturbances across the landscape (Clavero et al. ).The goal of this study is to understand the separate and combined impacts of CLC change through streamflow indices that are able to represent the timing and magnitude of flow over time.Low flow, peak flow, seasonal mean flow, and center timing (CT) of flow are all useful streamflow indices used to predict spatial and temporal changes in runoff of complex watershed systems facing CC and urbanization (Chang & Jung ; Choi et al. ).Unlike previous studies, our work aims to use these streamflow metrics as indicators of change and also incorporate tightly coupled CLC change scenarios (individual and combined) into our models to yield a reasonable range of impact scenarios between the lower and upper watershed in the near future (2050s) and the distant future (2080s).
The lower part of the watershed is heavily urbanized with medium-to low-density developments.Geology of the watershed is dominated by the western cascade volcanic rocks, with a small portion of the lower watershed falling in the Willamette Valley alluvium deposits and the very upper part of the watershed falling inside the high cascade range with colder and more snow deposits.The total population of the watershed is approximately 200,000 people across a drainage area of 2,435 km 2 .The entire watershed consists of 5% urban developments, 10% agricultural lands, and 85% forested lands.However, urban developments and agricultural lands are more concentrated on the lower watershed, while forested lands dominate the middle and upper parts of the watershed.The main stem of the Clackamas River originates from Mount Hood, flowing through the pristine mixed forest from southeast to northwest into the Willamette River.The Clackamas River flows through both rural and urban areas as well, providing drinking water to roughly 350,000 people within and adjacent to the watershed.Drinking and wastewater treatment plants are all located near the mouth of the river downstream as well as a USGS stream gauge with continuous discharge and water quality monitoring.The study area is highly vulnerable to CC, as it is heavily dependent on diminishing snowpack for water supply and highly sensitive to wet season floods and dry season droughts (Graves & Chang ).Both high and low flows are concerns for water managers, as high flows typically accompany turbid water (Chen & Chang ), while low flows reduce available water for drinking and irrigation.The climate of the study area is considered Mediterranean, with a prolonged winter and fall rainfall period and dry, warm summer.Climate data from 1981 to 2010 showed that mean air temperature is approximately 4.6 C in January and 20 C in July.Precipitation is the most abundant during December, averaging 183 mm and driest in July with only 19 mm.The majority of precipitation falls as snow on the upper part of the watershed and becomes essential runoff in the following spring and summer.The mean annual runoff is 138 cm/year in the watershed from 1981 to 2010.Runoff patterns vary by season with highs during late winter early spring and lows in mid-summer.With a growing population and drinking water demand, LC in the watershed is expecting significant changes in the year 2040-2070 and 2070-2100 based on projected CC and LC (Turner et al. ).We divided the watershed into the lower and upper watersheds.The lower watershed represents the more urbanized and agricultural heavy area, while the upper watershed consists of mainly evergreen forest.SWAT model SWAT was selected to model hydrologic changes under individual and combined CLC scenarios in our studied watershed due to its ability to capture physical hydrology processes at the watershed to basin-level on a continuoustime scale.The SWAT is a semi-distributed continuoustime model capable of modeling streamflow, sediment transport, and nutrient runoff at the watershed to basin scale (Arnold et al. ).Through 30 years of research and development, SWAT is well-documented with a userfriendly interface.Unlike other process-based hydrologic models, SWAT has its own calibration and sensitivity analysis

Figure 1 |
Figure 1 | Map of study area in the CRW showing LC and elevation gradient.
(mid-point year within historical streamflow record) National Land Cover Dataset with a 30 m × 30 m cell size was used to run SWAT for this watershed.A total of 18 LC classifications from NLCD 2006 were collapsed into 13 LC classifications in order to be used by the SWAT model for processing (Appendix I).Historic daily climate data were downloaded from the gridMET dataset, a spatially and temporally continuous surface meteorological dataset that are available from 1979 to present (Abatzoglou ).Daily maximum and minimum precipitation and cumulative precipitation were the three climate variables extracted and used in the initial run of SWAT.The GridMET dataset has a high spatial resolution of 4 km grids and was validated by Abatzoglou () extensively with surface weather station data.Although the dataset is not good at capturing microclimate under the 4 km spatial scale, it does provide better estimation in SWAT modeling than surface station climate data with more coarse resolution as seen in previous studies (Grusson et al. ; Bhattacharya et al. ).
Figure 2 | Map showing LC type in 2050 and 2080s and their distribution in three climate emission scenarios.
Figure 3 | Boxplots showing percent change in monthly streamflow in the CLC combined scenario for lower and upper watersheds in 2050 and 2080s.
ence and high climate emission, this change is reversed with CT shifting later in the 2080s than the 2050s.There are no major differences in the shift between lower and upper parts of the watershed, and CC remains the biggest driver for change in timing of flow in all simulated scenarios.DISCUSSIONSeparate versus combined scenarios on streamflow CC only and combined scenarios showed the most change compared to LCC only scenarios.Streamflow impacts from LCC only scenarios were found to be minimal.Both peak flow and low flow were projected to decrease with LCC, possibly due to the increase of woody wetlands (þ12%) and the abundance of mixed forest (þ28%).Although the sensitivity of streamflow metrics to LCC was low, peak flow showed somewhat the opposite trajectory of change than CC only scenarios where LCC would decrease peak flow while CC will increase peak flow.These changes in peak flow can be explained by the nature of our study sites, which is heavily dominated by precipitation in the forms of snow and rain, and peak flow events are largely influenced by extreme short-duration precipitation or rain-on-snow events triggered by sudden warming in spring (Safeeq et al. ).The CC only scenarios in all streamflow metrics look identical to the combined scenarios, suggesting that CC impacts are driving a big portion of the change even in the CLC combined scenarios.We speculate that in other heavily snow-fed watersheds, basin (large-scale) hydrological change is primarily driven by CC, while local (small-scale) hydrological change is driven by LCC (He et al. ; Ahiablame et al. ).Highly sensitive streamflow due to climate means the timing, magnitude, and type of precipitation during wet seasons is extremely important for water availability during dry seasons and wet seasons due to concerns for hydrologic extremes (Vano et al. b; Feng & Beighley ).Similarly, increasing spring and summer temperatures (2-5 C) can alter the timing of snowmelt events, causing higher risks of hydrologic drought in dry seasons (Table 3).CC was shown to be impacting runoff on the annual and monthly scale, increasing peak flow, and reducing low flow.The extreme impacts of CC are also dependent on location, where more developed areas can show high sensitivity to streamflow change during extreme events such as winter storms and flooding.Our study confirms that in a highly forested watershed, LCC plays a minimal role compared to CC due to minimal land converted to impervious surfaces (Figure 2).The most significant change observed in this study was the CT of flow.The combined scenarios showing a range of 0-30 days earlier in reaching 50% of annual flow volume can mean that snowmelts will occur much earlier in the year and deplete the already reduced snowpack early enough to cause water availability concerns for managers.The majority of the CRW sits on the colder wetter western cascade that is mountainous and receives rain and snow, while the urbanized part lies on the lower elevation drier Willamette valley.The geologic and geographic differences of the watershed can influence the amount of precipitation and moisture holding properties and can be highly sensitive to climatic changes that will influence the form of precipitation and mechanisms of groundwater recharge.The majority (70%) of our studied watershed lies in western cascade and

Figure 5 |
Figure 5 | Boxplots showing change in 7-day minimum flow and standard deviations.

Figure 6 |
Figure 6 | Boxplots showing change in CT of flow.

Table 1 |
Summary of input data used to run SWAT model scenarios ponents.For example, the vegetation model simulates changes in forest composition, forest area burned by wildfires, and the subsequent impact on timber harvesting and succession of vegetation due to CC (Turner et al. ).The WW2100 dataset contains projected LC maps for the period between 2010 and 2100 in the WRB under three different climate scenarios.The three climate scenarios (Table 2) were all part of the CMIP5 GCMs to represent low CC (GFDL-ESM2M), reference CC (MIROC5), and high CC (HadGEM2-ES) (Rupp et al. ).With warmer, We selected the three coupled climate scenarios from a set of 20 CMIP5 models under RCP 8.5 (Table2).The daily climate data come from the Multivariate Adaptive Constructed Analogs (MACA) dataset, which is a type of the statistical downscaling method for GCMs that uses bias correction procedures and a constructed analogs approach(Abatzoglou & Brown ).The downscaled climate data have a spatial resolution of 4 km, capturing near-surface weather conditions for watersheds with complex terrain.

Table 2 |
Summary of SWAT scenario analysis, LCC only: B,C,D; CC only: E,F,G; LC and CC: H,I,J

Table 3 |
Summary of change in temperature and precipitation by season in future CC scenarios efficiency (NSE) index, and the percent bias (PBIAS).