A 21st-Century perspective on snow drought in the Upper Colorado River Basin

In the Upper Colorado River Basin (UCRB), there is a deep reliance on seasonal snowpack for maintenance of water resources. The term “snow drought” has recently emerged to describe periods of anomalously low snowpack. Unique seasonal patterns in precipitation and temperature that drive snow drought can have distinct hydrologic signatures, and these relationships have not been carefully studied in the UCRB. Here we examine snow drought with a new classification scheme using peak snow water equivalent (SWE) and the ratio of basin-wide modeled peak SWE to accumulated (onset to peak) precipitation (SWE/P) that clusters snow drought years into three distinct groups—“warm,” “dry,” and “warm & dry”—that minimize within-group variance. Over the period 1916–2018, we identify 14 warm years ($\overline{P}$ = 160 mm; $\overline{\mathrm{SWE}/P}$ = 0.24), 24 dry years ($\overline{P}$ = 117 mm; $\overline{\mathrm{SWE}/P}$ = 0.35), and 21 warm & dry years ($\overline{P}$ = 94 mm; $\overline{\mathrm{SWE}/P}$ = 0.23). An elevation-based analysis reveals two distinct patterns: warm snow droughts see severe SWE reductions primarily at lower (<2600 m) elevations (65% at lower elevations, 37% overall), whereas “dry” scenarios exhibit a consistent reduction across all elevations (39% overall). Using naturalized streamflow data, we also differentiate snow droughts by their earlier streamflow timing and decreased peakedness (warm: 7 days, 2%; dry: 7 days, 2%; warm & dry: 13 days, 5%). This research provides new insights into snow drought patterns relevant for regional water management.     

Oregon Hydrologic Landscapes: A Classification Framework1

Wigington, Parker J., Jr., Scott G. Leibowitz, Randy L. Comeleo, and Joseph L. Ebersole, 2012. Oregon Hydrologic Landscapes: A Classification Framework. Journal of the American Water Resources Association (JAWRA) 1‐20. DOI: 10.1111/jawr.12009 Abstract: There is a growing need for hydrologic classification systems that can provide a basis for broad‐scale assessments of the hydrologic functions of landscapes and watersheds and their responses to stressors such as climate change. We developed a hydrologic landscape (HL) classification approach that describes factors of climate‐watershed systems that control the hydrologic characteristics of watersheds. Our assessment units are incremental watersheds (i.e., headwater watersheds or areas draining directly into stream reaches). Major components of the classification include indices of annual climate, climate seasonality, aquifer permeability, terrain, and soil permeability. To evaluate the usefulness of our approach, we identified 30 rivers with long‐term streamflow‐gauging records and without major diversions and impoundments. We used statistical clustering to group the streams based on the shapes of their annual hydrographs. Comparison of the streamflow clusters and HL distributions within river basin clusters shows that the Oregon HL approach has the ability to provide insights about the expected hydrologic behavior of HLs and larger river basins. The Oregon HL approach has potential to be a useful framework for comparing hydrologic attributes of streams and rivers in the Pacific Northwest.     

Snowmelt Runoff and Water Yield Along Elevation and Temperature Gradients in California’s Southern Sierra Nevada1

Hunsaker, Carolyn T., Thomas W. Whitaker, and Roger C. Bales, 2012. Snowmelt Runoff and Water Yield Along Elevation and Temperature Gradients in California’s Southern Sierra Nevada. Journal of the American Water Resources Association (JAWRA) 48(4): 667‐678. DOI: 10.1111/j.1752‐1688.2012.00641.x Abstract: Differences in hydrologic response across the rain‐snow transition in the southern Sierra Nevada were studied in eight headwater catchments – the Kings River Experimental Watersheds – using continuous precipitation, snowpack, and streamflow measurements. The annual runoff ratio (discharge divided by precipitation) increased about 0.1 per 300 m of mean catchment elevation over the range 1,800‐2,400 m. Higher‐elevation catchments have lower vegetation density, shallow soils with rapid permeability, and a shorter growing season when compared with those at lower elevations. Average annual temperatures ranged from 6.8°C at 2,400 m to 8.6 at 1,950 m elevation, with annual precipitation being 75‐95% snow at the highest elevations vs. 20‐50% at the lowest. Peak discharge lagged peak snow accumulation on the order of 60 days at the higher elevations and 20 to 30 days at the lower elevations. Snowmelt dominated the daily streamflow cycle over a period of about 30 days in higher elevation catchments, followed by a 15‐day transition to evapotranspiration dominating the daily streamflow cycle. Discharge from lower elevation catchments was rainfall dominated in spring, with the transition to evapotranspiration dominance being less distinct. Climate warming that results in a longer growing season and a shift from snow to rain would result in earlier runoff and a lower runoff ratio.     

Flooding and the interannual variability of hydrologic quantities in the Missouri River basin

The six mainstem reservoirs in the Missouri River basin (MRB) are managed mainly to prevent flooding from snowmelt and heavy rainfall, a goal for which the interannual variabilities of precipitation ($P$), evapotranspiration ($\mathit{ET}$), and surface air temperature ($T_{\mathrm{air}}$) are vitally important. We tested the hypothesis that under the expected higher variability owing to global climate change, the months with the highest contributions to the interannual variability of $P$, $\mathit{ET}$, and $T_{\mathrm{air}}$ in the MRB will remain unchanged and quantified likely temporal trends in these quantities. Using high-resolution, downscaled Coupled Model Intercomparison Project Phase 5 multi-model ensemble data sets, we compared the multi-year ratio of monthly and annual interannual variability and temporal trends in $P$, $\mathit{ET}$, and $T_{\mathrm{air}}$ during 2011–2020 with three future decades. Results showed that the 6 months with the highest interannual variability in $P$ and $\mathit{ET}$ (April–September) are the same in all four decades. However, for $T_{\mathrm{air}}$, only 4 months (December–March) retain their status as highly variable throughout the four decades; September and October variability is exceeded by the variability in other months. This implies that, compared to $P$ and $\mathit{ET}$, the cyclical change in the probabilities of $T_{\mathrm{air}}$ in the MRB is less stable under future global climate change. This finding can be used to consider the need to alter existing strategies for reservoir release while minimizing the likelihood of aggravating flooding below the reservoirs.     

Hydrologic Landscape Characterization for the Pacific Northwest,USA

We update the Wigington et al. (2013) hydrologic landscape (HL) approach to make it more broadly applicable and apply the revised approach to the Pacific Northwest (PNW; i.e., Oregon, Washington, and Idaho). Specific changes incorporated are the use of assessment units based on National Hydrography Dataset Plus V2 catchments, a modified snowmelt model validated over a broader area, an aquifer permeability index that does not require preexisting aquifer permeability maps, and aquifer and soil permeability classes based on uniform criteria. Comparison of Oregon results for the revised and original approaches found fewer and larger assessment units, loss of summer seasonality, and changes in rankings and proportions of aquifer and soil permeability classes. Differences could be explained by three factors: an increased assessment unit size, a reduced number of permeability classes, and use of smaller cutoff values for the permeability classes. The distributions of the revised HLs in five groups of Oregon rivers were similar to the original HLs but less variable. The improvements reported here should allow the revised HL approach to be applied more often in situations requiring hydrologic classification and allow greater confidence in results. We also apply the map results to the development of hydrologic landscape regions.     

Characterizing Runoff and Water Yield for Headwater Catchments in the Southern Sierra Nevada

In a Mediterranean climate where much of the precipitation falls during winter, snowpacks serve as the primary source of dry season runoff. Increased warming has led to significant changes in hydrology of the western United States. An important question in this context is how to best manage forested catchments for water and other ecosystem services? Answering this basic question requires detailed understanding of hydrologic functioning of these catchments. Here, we depict the differences in hydrologic response of 10 catchments. Size of the study catchments ranges from 50 to 475 ha, and they span between 1,782 and 2,373 m elevation in the rain‐snow transitional zone. Mean annual streamflow ranged from 281 to 408 mm in the low elevation Providence and 436 to 656 mm in the high elevation Bull catchments, resulting in a 49 mm streamflow increase per 100 m (R² = 0.79) elevation gain, despite similar precipitation across the 10 catchments. Although high elevation Bull catchments received significantly more precipitation as snow and thus experienced a delayed melt, this increase in streamflow with elevation was mainly due to a reduction in evapotranspiration (ET) with elevation (45 mm/100 m, R² = 0.65). The reduction in ET was attributed to decline in vegetation density, growing season, and atmospheric demand with increasing elevation. These findings suggest changes in streamflow in response to climate warming may likely depend on how vegetation responds to those changes in climate.     

Novel dimensionless index for physically based assessment of thermal refugia characterizes off-channel habitat on gravel bed river

In the Willamette River, OR, main channel temperatures can be too warm for cold water fishes, causing fish to concentrate in secondary channel features that provide thermal refugia. However, temperature regimes vary among and within features. Improved understanding of physical processes controlling thermal regimes is needed. This study developed a dimensionless index for assessment of thermal refugia on the upper Willamette River. The novel hyporheic insolation (HIN) index uses minimal field measurements to predict thermal refugia resulting from buffering. Continuous water temperature measurements at one side channel, eight alcoves, and six beaver ponds provided data to ground truth calculated ${ℍ}_{\text{in}}$ predictions. Water temperature records were first used to characterize stratification at sites. Calculation of the Richardson number, an index of stability, showed two well-mixed sites and 13 stratified sites. At stratified sites, calculated ${ℍ}_{\text{in}}$ values characterized the ratio of cooling flux from hyporheic discharge to heat flux from incoming solar radiation. As ${ℍ}_{\text{in}}$ increased, measured temperatures at sites decreased. Despite overall scatter, a logarithmic fit to bin-averaged ${ℍ}_{\text{in}}$ values showed R² = 0.91. Calculations suggest that secondary channel features characterized by stratification and cool hyporheic discharge can provide thermal refugia. Accordingly, the HIN index may serve as a practical tool grounded in physical processes governing temperature across a floodplain.     

PHYSICAL HYDROLOGY AND THE EFFECTS OF FOREST HARVESTING IN THE PACIFIC NORTHWEST: A REVIEW1

The Pacific Northwest encompasses a range of hydrologic regimes that can be broadly characterized as either coastal (where rain and rain on snow are dominant) or interior (where snowmelt is dominant). Forest harvesting generally increases the fraction of precipitation that is available to become streamflow, increases rates of snowmelt, and modifies the runoff pathways by which water flows to the stream channel. Harvesting may potentially decrease the magnitude of hyporheic exchange flow through increases in fine sediment and clogging of bed materials and through changes in channel morphology, although the ecological consequences of these changes are unclear. In small headwater catchments, forest harvesting generally increases annual runoff and peak flows and reduces the severity of low flows, but exceptions have been observed for each effect. Low flows appear to be more sensitive to transpiration from vegetation in the riparian zone than in the rest of the catchment. Although it appears that harvesting increased only the more frequent, geomorphically benign peak flows in several studies, in others the treatment effect increased with return period. Recovery to pre‐harvest conditions appeared to occur within about 10 to 20 years in some coastal catchments but may take many decades in mountainous, snow dominated catchments.     

Long‐Term Trends in Streamflow and Precipitation in Northwest California and Southwest Oregon, 1953‐2012

Using nonparametric Mann‐Kendall tests, we assessed long‐term (1953‐2012) trends in streamflow and precipitation in Northern California and Southern Oregon at 26 sites regulated by dams and 41 “unregulated” sites. Few (9%) sites had significant decreasing trends in annual precipitation, but September precipitation declined at 70% of sites. Site characteristics such as runoff type (groundwater, snow, or rain) and dam regulation influenced streamflow trends. Decreasing streamflow trends outnumbered increasing trends for most months except at regulated sites for May‐September. Summer (July‐September) streamflow declined at many sites, including 73% of unregulated sites in September. Applying a LOESS regression model of antecedent precipitation vs. average monthly streamflow, we evaluated the underlying streamflow trend caused by factors other than precipitation. Decreasing trends in precipitation‐adjusted streamflow substantially outnumbered increasing trends for most months. As with streamflow, groundwater‐dominated sites had a greater percent of declining trends in precipitation‐adjusted streamflow than other runoff types. The most pristine surface‐runoff‐dominated watersheds within the study area showed no decreases in precipitation‐adjusted streamflow during the summer months. These results suggest that streamflow decreases at other sites were likely due to more increased human withdrawals and vegetation changes than to climate factors other than precipitation quantity.     

Modeling the Spatially Varying Water Balance Processes in a Semiarid Mountainous Watershed of Idaho1

Stratton, Benjamin T., Venakataramana Sridhar, Molly M. Gribb, James P. McNamara, and Balaji Narasimhan, 2009. Modeling the Spatially Varying Water Balance Processes in a Semiarid Mountainous Watershed of Idaho. Journal of the American Water Resources Association (JAWRA) 45(6):1390‐1408. Abstract: The distributed Soil Water Assessment Tool (SWAT) hydrologic model was applied to a research watershed, the Dry Creek Experimental Watershed, near Boise Idaho to investigate its water balance components both temporally and spatially. Calibrating and validating SWAT is necessary to enable our understanding of the water balance components in this semiarid watershed. Daily streamflow data from four streamflow gages were used for calibration and validation of the model. Monthly estimates of streamflow during the calibration phase by SWAT produced satisfactory results with a Nash Sutcliffe coefficient of model efficiency 0.79. Since it is a continuous simulation model, as opposed to an event‐based model, it demonstrated the limited ability in capturing both streamflow and soil moisture for selected rain‐on‐snow (ROS) events during the validation period between 2005 and 2007. Especially, soil moisture was generally underestimated compared with observations from two monitoring pits. However, our implementation of SWAT showed that seasonal and annual water balance partitioning of precipitation into evapotranspiration, streamflow, soil moisture, and drainage was not only possible but closely followed the trends of a typical semiarid watershed in the intermountain west. This study highlights the necessity for better techniques to precisely identify and drive the model with commonly observed climatic inversion‐related snowmelt or ROS weather events. Estimation of key parameters pertaining to soil (e.g., available water content and saturated hydraulic conductivity), snow (e.g., lapse rates, melting), and vegetation (e.g., leaf area index and maximum canopy index) using additional field observations in the watershed is critical for better prediction.     

Observed Changes in Climate and Streamflow in the Upper Rio Grande Basin

Observed streamflow and climate data are used to test the hypothesis that climate change is already affecting Rio Grande streamflow volume derived from snowmelt runoff in ways consistent with model‐based projections of 21st‐Century streamflow. Annual and monthly changes in streamflow volume and surface climate variables on the Upper Rio Grande, near its headwaters in southern Colorado, are assessed for water years 1958–2015. Results indicate winter and spring season temperatures in the basin have increased significantly, April 1 snow water equivalent (SWE) has decreased by approximately 25%, and streamflow has declined slightly in the April–July snowmelt runoff season. Small increases in precipitation have reduced the impact of declining snowpack on trends in streamflow. Changes in the snowpack–runoff relationship are noticeable in hydrographs of mean monthly streamflow, but are most apparent in the changing ratios of precipitation (rain + snow, and SWE) to streamflow and in the declining fraction of runoff attributable to snowpack or winter precipitation. The observed changes provide observational confirmation for model projections of decreasing runoff attributable to snowpack, and demonstrate the decreasing utility of snowpack for predicting subsequent streamflow on a seasonal basis in the Upper Rio Grande Basin.     

Modes of Variability of Annual and Seasonal Rainfall in Mexico

The aim of this study is to identify temporal and spatial variability patterns of annual and seasonal rainfall in Mexico. A set of 769 weather stations located in Mexico was examined. The country was divided into 12 homogeneous rainfall regions via principal component analysis. A Pettitt test was conducted to perform a homogeneity analysis for detecting abrupt changes in mean rainfall levels, and a Mann‐Kendall test was conducted to examine the presence of monotonically increasing/decreasing patterns in the data. In total, 14.4% of the annual series was deemed nonstationary. Fourteen percent of the samples were nonstationary in the winter and summer, and 9% were nonstationary in the spring and autumn. According to the results, the nonstationarity of some seasonal rainfall series may be associated with the presence of atmospheric phenomena (e.g., El Niño/Southern Oscillation, Pacific Decadal Oscillation, Atlantic Multidecadal Oscillation, and North Atlantic Oscillation). A rainfall frequency analysis was performed for the nonstationary annual series, and significant differences in the return levels can be expected for the scenarios analyzed. The identification of areas that are more susceptible to changes in rainfall levels will improve water resource management plans in the country, and it is expected that these plans will take into account nonstationary theory.     

Evaluation of Ground‐Water and Surface‐Water Exchanges Using Streamflow Difference Analyses1

Abstract: In the karstic lower Flint River Basin, limestone fracturing, jointing, and subsequent dissolution have resulted in the development of extensive secondary permeability and created a system of major conduits that facilitate the exchange of water between the Upper Floridan aquifer and Flint River. Historical streamflow data from U.S. Geological Survey gaging stations located in Albany and Newton, Georgia, were used to quantify ground‐water and surface‐water exchanges within a 55.3 km section of the Flint River. Using data from 2001, we compared estimates of ground‐water flux using a time adjustment method to a water balance equation and found that these independent approaches yielded similar results. The associated error was relatively large during high streamflow when unsteady conditions prevail, but much lower during droughts. Flow reversals were identified by negative streamflow differences and verified with in situ data from temperature sensors placed inside large spring conduits. Long‐term (13 years) analysis showed negative streamflow differentials (i.e., a losing stream condition) coincided with high river stages and indicated that streamflow intrusion into the aquifer could potentially exceed 150 m³/s. Although frequent negative flow differentials were evident, the Flint River was typically a gaining stream and showed a large net increase in flow between the two gages when examined over the period 1989‐2003. Ground‐water contributions to this stream section averaged 2‐42 m³/s with a mean of 13 m³/s. The highest rate of ground‐water discharge to the Flint River occurred during the spring when regional ground‐water levels peaked following heavy winter and spring rains and corresponding rates of evapotranspiration were low. During periods of extreme drought, ground‐water contributions to the Flint River declined.     

Using SWAT to Model Streamflow in Two River Basins With Ground and Satellite Precipitation Data1

Abstract: Both ground rain gauge and remotely sensed precipitation (Next Generation Weather Radar – NEXRAD Stage III) data have been used to support spatially distributed hydrological modeling. This study is unique in that it utilizes and compares the performance of National Weather Service (NWS) rain gauge, NEXRAD Stage III, and Tropical Rainfall Measurement Mission (TRMM) 3B42 (Version 6) data for the hydrological modeling of the Middle Nueces River Watershed in South Texas and Middle Rio Grande Watershed in South Texas and northern Mexico. The hydrologic model chosen for this study is the Soil and Water Assessment Tool (SWAT), which is a comprehensive, physical‐based tool that models watershed hydrology and water quality within stream reaches. Minor adjustments to selected model parameters were applied to make parameter values more realistic based on results from previous studies. In both watersheds, NEXRAD Stage III data yields results with low mass balance error between simulated and actual streamflow (±13%) and high monthly Nash‐Sutcliffe efficiency coefficients (NS > 0.60) for both calibration (July 1, 2003 to December 31, 2006) and validation (2007) periods. In the Middle Rio Grande Watershed NEXRAD Stage III data also yield robust daily results (time averaged over a three‐day period) with NS values of (0.60‐0.88). TRMM 3B42 data generate simulations for the Middle Rio Grande Watershed of variable qualtiy (MBE = +13 to ?16%; NS = 0.38‐0.94; RMSE = 0.07‐0.65), but greatly overestimates streamflow during the calibration period in the Middle Nueces Watershed. During the calibration period use of NWS rain gauge data does not generate acceptable simulations in both watersheds. Significantly, our study is the first to successfully demonstrate the utility of satellite‐estimated precipitation (TRMM 3B42) in supporting hydrologic modeling with SWAT; thereby, potentially extending the realm (between 50°N and 50°S) where remotely sensed precipitation data can support hydrologic modeling outside of regions that have modern, ground‐based radar networks (i.e., much of the third world).     

Generation of Ensemble Streamflow Forecasts Using an Enhanced Version of the Snowmelt Runoff Model1

Harshburger, Brian J., Von P. Walden, Karen S. Humes, Brandon C. Moore, Troy R. Blandford, and Albert Rango, 2012. Generation of Ensemble Streamflow Forecasts Using an Enhanced Version of the Snowmelt Runoff Model. Journal of the American Water Resources Association (JAWRA) 48(4): 643‐655. DOI: 10.1111/j.1752‐1688.2012.00642.x Abstract: As water demand increases in the western United States, so does the need for accurate streamflow forecasts. We describe a method for generating ensemble streamflow forecasts (1‐15 days) using an enhanced version of the snowmelt runoff model (SRM). Forecasts are produced for three snowmelt‐dominated basins in Idaho. Model inputs are derived from meteorological forecasts, snow cover imagery, and surface observations from Snowpack Telemetry stations. The model performed well at lead times up to 7 days, but has significant predictability out to 15 days. The timing of peak flow and the streamflow volume are captured well by the model, but the peak‐flow value is typically low. The model performance was assessed by computing the coefficient of determination (R²), percentage of volume difference (Dv%), and a skill score that quantifies the usefulness of the forecasts relative to climatology. The average R² value for the mean ensemble is >0.8 for all three basins for lead times up to seven days. The Dv% is fairly unbiased (within ±10%) out to seven days in two of the basins, but the model underpredicts Dv% in the third. The average skill scores for all basins are >0.6 for lead times up to seven days, indicating that the ensemble model outperforms climatology. These results validate the usefulness of the ensemble forecasting approach for basins of this type, suggesting that the ensemble version of SRM might be applied successfully to other basins in the Intermountain West.     

Streamflow Response to Climate as Influenced by Geology and Elevation1

Mayer, Timothy D. and Seth W. Naman, 2011. Streamflow Response to Climate as Influenced by Geology and Elevation. Journal of the American Water Resources Association (JAWRA) 47(4):724‐738. DOI: 10.1111/j.1752‐1688.2011.00537.x Abstract: This study examines the regional streamflow response in 25 predominately unregulated basins to warmer winter temperatures and snowpack reductions over the last half century in the Klamath Basin of California and Oregon. Geologic controls of streamflow in the region result in two general stream types: surface‐dominated and groundwater‐dominated basins. Surface‐dominated basins were further differentiated into rain basins and snowmelt basins on the basis of elevation and timing of winter runoff. Streamflow characteristics and response to climate vary with stream type, as discussed in the study. Warmer winter temperatures and snowpack reductions have caused significantly earlier runoff peaks in both snowmelt and groundwater basins in the region. In the groundwater basins, the streamflow response to changes in snowpack is smoothed and delayed and the effects are extended longer in the summer. Our results indicate that absolute decreases in July‐September base flows are significantly greater, by an order of magnitude, in groundwater basins compared to surface‐dominated basins. The declines are important because groundwater basins sustain Upper Klamath Lake inflows and mainstem river flows during the typically dry summers of the area. Upper Klamath Lake April‐September net inflows have decreased an estimated 16% or 84 thousand acre‐feet (103.6 Mm³) since 1961, with the summer months showing proportionately more decline. These changes will exacerbate water supply problems for agriculture and natural resources in the region.     

Estimation of Daily Streamflow of Southeastern Coastal Plain Watersheds by Combining Estimated Magnitude and Sequence

Commonly used methods to predict streamflow at ungauged watersheds implicitly predict streamflow magnitude and temporal sequence concurrently. An alternative approach that has not been fully explored is the conceptualization of streamflow as a composite of two separable components of magnitude and sequence, where each component is estimated separately and then combined. Magnitude is modeled using the flow duration curve (FDC), whereas sequence is modeled by transferring streamflow sequence of gauged watershed(s). This study tests the applicability of the approach on watersheds ranging in size from about 25‐7,226 km² in Southeastern Coastal Plain (U.S.) with substantial surface storage of wetlands. A 19‐point regionalized FDC is developed to estimate streamflow magnitude using the three most selected variables (drainage area, hydrologic soil index, and maximum 24‐h precipitation with a recurrence interval of 100 years) by a greedy‐heuristic search process. The results of validation on four watersheds (Trent River, North Carolina: 02092500; Satilla River, Georgia: 02226500; Black River, South Carolina: 02136000; and Coosawhatchie River, South Carolina: 02176500) yielded Nash‐Sutcliffe efficiency values of 0.86‐0.98 for the predicted magnitude and 0.09‐0.84 for the predicted daily streamflow over a simulation period of 1960‐2010. The prediction accuracy of the method on two headwater watersheds at Santee Experimental Forest in coastal South Carolina was weak, but comparable to simulations by MIKE‐SHE.     

Assessing the Impact of Areal Precipitation Input on Streamflow Simulations Using the SWAT Model1

Masih Ilyas, Shreedhar Maskey, Stefan Uhlenbrook, and Vladimir Smakhtin, 2011. Assessing the Impact of Areal Precipitation Input on Streamflow Simulations Using the SWAT Model. Journal of the American Water Resources Association (JAWRA) 47(1):179‐195. DOI: 10.1111/j.1752‐1688.2010.00502.x Abstract: Reduction of input uncertainty is a challenge in hydrological modeling. The widely used model Soil Water Assessment Tool (SWAT) uses the data of a precipitation gauge nearest to the centroid of each subcatchment as an input for that subcatchment. This may not represent overall catchment precipitation conditions well. This paper suggests an alternative – using areal precipitation obtained through interpolation. The effectiveness of this alternative is evaluated by comparing its simulations with those based on the standard SWAT precipitation input procedure. The model is applied to mountainous semiarid catchments in the Karkheh River basin, Iran. The model performance is evaluated at daily, monthly, and annual scales by using a number of performance indicators at 15 streamflow gauging stations each draining an area in the range of 590‐42,620 km². The comparison suggests that the use of areal precipitation improves model performance particularly in small subcatchments in the range of 600‐1,600 km². The modified areal precipitation input results in increased reliability of simulated streamflows in the areas of low rain gauge density. Both precipitation input methods result in reasonably good simulations for larger catchments (over 5,000 km²). The use of areal precipitation input improves the accuracy of simulated streamflows with spatial resolution and density of rain gauges having significant impact on results.     

STREAMFLOW DEPLETION: MODELING OF REDUCED BASEFLOW ANI INDUCED STREAM INFILTRATION FROM SEASONALLY PUMPED WELLS1

ABSTRACT: Numerical modeling techniques are used to analyze streamflow depletion for stream‐aquifer systems with baseflow. The analyses calculated two flow components generated by a pumping well located at a given distance from a river that is hydraulically connected to an unconfined aquifer. The two components are induced stream infiltration and reduced baseflow; both contribute to total streamflow depletion. Simulation results suggest that the induced infiltration, the volume of water discharged from the stream to the aquifer, has a shorter term impact on streamflow, while the reduced baseflow curves show a longer term effect. The peak impacts of the two hydrologic processes on streamflow occur separately. The separate analysis helps in understanding the hydrologic interactions between stream and aquifer. Practically, it provides useful information about contaminant transport from stream to aquifer when water quality is a concern, and for areas where water quantity is an issue, the separate analysis offers additional information to the development of water resource management plan.     

Hydrologic Calibration and Validation of SWAT in a Snow‐Dominated Rocky Mountain Watershed,Montana, U.S.A.1

Abstract: The Soil and Water Assessment Tool (SWAT) has been applied successfully in temperate environments but little is known about its performance in the snow‐dominated, forested, mountainous watersheds that provide much of the water supply in western North America. To address this knowledge gap, we configured SWAT to simulate the streamflow of Tenderfoot Creek (TCSWAT). Located in central Montana, TCSWAT represents a high‐elevation watershed with ～85% coniferous forest cover where more than 70% of the annual precipitation falls as snow, and runoff comes primarily from spring snowmelt. Model calibration using four years of measured daily streamflow, temperature, and precipitation data resulted in a relative error (RE) of 2% for annual water yield estimates, and mean paired deviations (Dv) of 36 and 31% and Nash‐Sutcliffe (NS) efficiencies of 0.90 and 0.86 for monthly and daily streamflow, respectively. Model validation was conducted using an additional four years of data and the performance was similar to the calibration period, with RE of 4% for annual water yields, Dv of 43% and 32%, and NS efficiencies of 0.90 and 0.76 for monthly and daily streamflow, respectively. An objective, regression‐based model invalidation procedure also indicated that the model was validated for the overall simulation period. Seasonally, SWAT performed well during the spring and early summer snowmelt runoff period, but was a poor predictor of late summer and winter base flow. The calibrated model was most sensitive to snowmelt parameters, followed in decreasing order of influence by the surface runoff lag, ground water, soil, and SCS Curve Number parameter sets. Model sensitivity to the surface runoff lag parameter reflected the influence of frozen soils on runoff processes. Results indicated that SWAT can provide reasonable predictions of annual, monthly, and daily streamflow from forested montane watersheds, but further model refinements could improve representation of snowmelt runoff processes and performance during the base flow period in this environment.