Evaluation of Reference Evapotranspiration Methods in Arid,Semiarid, and Humid Regions

It is often necessary to find a simpler method in different climatic regions to calculate reference crop evapotranspiration (ET_o) since the application of the FAO‐56 Penman‐Monteith method is often restricted due to the unavailability of a comprehensive weather dataset. Seven ET_o methods, namely the standard FAO‐56 Penman‐Monteith, the FAO‐24 Radiation, FAO‐24 Blaney Criddle, 1985 Hargreaves, Priestley‐Taylor, 1957 Makkink, and 1961 Turc, were applied to calculate monthly averages of daily ET_o, total annual ET_o, and daily ET_o in an arid region at Aksu, China, in a semiarid region at Tongchuan, China, and in a humid region at Starkville, Mississippi, United States. Comparisons were made between the FAO‐56 method and the other six simple alternative methods, using the index of agreement D, modeling efficiency (EF), and root mean square error (RMSE). For the monthly averages of daily ET_o, the values of D, EF, and RMSE ranged from 0.82 to 0.98, 0.55 to 0.98, and 0.23 to 1.00 mm/day, respectively. For the total annual ET_o, the values of D, EF, and RMSE ranged from 0.21 to 0.91, ?43.08 to 0.82, and 24.80 to 234.08 mm/year, respectively. For the daily ET_o, the values of D, EF, and RMSE ranged from 0.58 to 0.97, 0.57 to 0.97, and 0.30 to 1.06 mm/day, respectively. The results showed that the Priestly‐Taylor and 1985 Hargreaves methods worked best in the arid and semiarid regions, while the 1957 Makkink worked best in the humid region.     

EXPERIMENTAL MARVIN WINDSHIELD EFFECTS ON PRECIPITATION RECORDS IN LEADVILLE,COLORADO1

ABSTRACT: An evaluation of the Leadville, Colorado, precipitation records that include a reported record-breaking storm (and flood) at higher elevations in the Rocky Mountains has indicated that the use of an experimental Marvin windshield (designed to decrease the effects of wind on precipitation-gage catchment of snow during winter) resulted in substantially overregistered summer precipitation for 1919 to 1938. The July monthly precipitation for these years was over-registered by an average of 157 percent of the long-term July monthly precipitation at Leadville. The cause of the overregistration of precipitation was the almost 4-foot-top-diameter cone-shaped windshield that had the effect of “funneling” hail and rain splash into the rain gage. Other nearby precipitation gages, which did not use this Marvin windshield, did not have this trend of increased precipitation for the same period. Streamflow records from the Leadville area also do not indicate an increase in streamfiow from 1919 to 1938. The storm of July 27, 1937, considered one of the few, large, intense rainstorms at higher elevations, had a recorded precipitation of total 4.34 inches (4.26 inches in 1 hour). Streamflow-gaging-station records indicate that only 0.09 inch of storm runoff occurred. Paleoflood investigations of channels in the Leadville area and old newspaper accounts also indicate no substantial flood from this storm. This study indicates that the 1937 storm probably totaled about 1.7 inches of precipitation, much of which occurred as hail.     

Improved Bankfull Channel Geometry Prediction Using Two‐Year Return‐Period Discharge1

He, Laien and Gregory V. Wilkerson, 2011. Improved Bankfull Channel Geometry Prediction Using Two‐Year Return‐Period Discharge. Journal of the American Water Resources Association (JAWRA) 47(6):1298–1316. DOI: 10.1111/j.1752‐1688.2011.00567.x Abstract:  Bankfull discharge (Q_bf) and bankfull channel geometry (i.e., width, W_bf; mean depth, D_bf; and cross‐section area, A_bf) are important design parameters in stream restoration, habitat creation, mined land reclamation, and related projects. The selection of values for these parameters is facilitated by regional curves (regression models in which Q_bf, W_bf, D_bf, and A_bf are predicted as a function of drainage area, A_da). This paper explores the potential for the two‐year return‐period discharge (Q₂) to improve predictions of W_bf, D_bf, and A_bf. Improved predictions are expected because Q₂ estimates integrate the effects of basin drainage area, climate, and geology. For conducting this study, 29 datasets (each representing one hydrologic region) spanning 14 states in the United States were analyzed. We assessed the utility of using Q₂ by comparing statistical measures of regression model performance (e.g., coefficient of determination and Akaike’s information criterion). Compared to using A_da, Q₂ is shown to be a “clearly superior” predictor of W_bf, D_bf, and A_bf, respectively, for 21, 13, and 25% of the datasets. By contrast, A_da yielded a clearly superior model for predicting W_bf, D_bf, and A_bf, respectively, for 0, 0, and 14% of the datasets. Our conclusion is that it alongside with developing conventional regional curves using A_da it is prudent to develop regional curves that use Q₂ as an independent variable because in some cases the resulting model will be superior.     

Assessment of Future Climate Change Impact on Water Quality of Chungju Lake,South Korea,Using WASP Coupled with SWAT

This study is to evaluate the future potential impact of climate change on the water quality of Chungju Lake using the Water Quality Analysis Simulation Program (WASP). The lake has a storage capacity of 2.75 Gm³, maximum water surface of 65.7 km², and forest‐dominant watershed of 6,642 km². The impact on the lake from the watershed was evaluated by the Soil and Water Assessment Tool (SWAT). The WASP and SWAT were calibrated and validated using the monthly water temperatures from 1998 to 2003, lake water quality data (dissolved oxygen, total nitrogen [T‐N], total phosphorus [T‐P], and chlorophyll‐a [chl‐a]) and daily dam inflow, and monthly stream water quality (sediment, T‐N, and T‐P) data. For the future climate change scenario, the MIROC3.2 HiRes A1B was downscaled for 2020s, 2050s, and 2080s using the Change Factor statistical method. The 2080s temperature and precipitation showed an increase of +4.8°C and +34.4%, respectively, based on a 2000 baseline. For the 2080s watershed T‐N and T‐P loads of up to +87.3 and +19.6%, the 2080s lake T‐N and T‐P concentrations were projected to be 4.00 and 0.030 mg/l from 2.60 and 0.016 mg/l in 2000, respectively. The 2080s chl‐a concentration in the epilimnion and the maximum were 13.97 and 52.45 μg/l compared to 8.64 and 33.48 μg/l in 2000, respectively. The results show that the Chungju Lake will change from its mesotrophic state of 2000 to a eutrophic state by T‐P in the 2020s and by chl‐a in the 2080s. Editor's note: This paper is part of a featured series on Korean Hydrology. The series addresses the need for a new paradigm of river and watershed management for Korea due to climate and land use changes.     

Decreased Runoff Response to Precipitation,Little Missouri River Basin,Northern Great Plains,USA

High variability in precipitation and streamflow in the semiarid northern Great Plains causes large uncertainty in water availability. This uncertainty is compounded by potential effects of future climate change. We examined historical variability in annual and growing season precipitation, temperature, and streamflow within the Little Missouri River Basin and identified differences in the runoff response to precipitation for the period 1976‐2012 compared to 1939‐1975 (n = 37 years in both cases). Computed mean values for the second half of the record showed little change (<5%) in annual or growing season precipitation, but average annual runoff at the basin outlet decreased by 22%, with 66% of the reduction in flow occurring during the growing season. Our results show a statistically significant (p < 0.10) 27% decrease in the annual runoff response to precipitation (runoff ratio). Surface‐water withdrawals for various uses appear to account for <12% of the reduction in average annual flow volume, and we found no published or reported evidence of substantial flow reduction caused by groundwater pumping in this basin. Results of our analysis suggest that increases in monthly average maximum and minimum temperatures, including >1°C increases in January through March, are the dominant driver of the observed decrease in runoff response to precipitation in the Little Missouri River Basin.     

Spatio-Temporal Variability of Soil Respiration of Forest Ecosystems in China: Influencing Factors and Evaluation Model

Understanding the influencing factors of the spatio-temporal variability of soil respiration (R _s) across different ecosystems as well as the evaluation model of R _s is critical to the accurate prediction of future changes in carbon exchange between ecosystems and the atmosphere. R _s data from 50 different forest ecosystems in China were summarized and the influences of environmental variables on the spatio-temporal variability of R _s were analyzed. The results showed that both the mean annual air temperature and precipitation were weakly correlated with annual R _s, but strongly with soil carbon turnover rate. R _s at a reference temperature of 0°C was only significantly and positively correlated with soil organic carbon (SOC) density at a depth of 20 cm. We tested a global-scale R _s model which predicted monthly mean R _s (R _s,monthly) from air temperature and precipitation. Both the original model and the reparameterized model poorly explained the monthly variability of R _s and failed to capture the inter-site variability of R _s. However, the residual of R _s,monthly was strongly correlated with SOC density. Thus, a modified empirical model (TPS model) was proposed, which included SOC density as an additional predictor of R _s. The TPS model explained monthly and inter-site variability of R _s for 56% and 25%, respectively. Moreover, the simulated annual R _s of TPS model was significantly correlated with the measured value. The TPS model driven by three variables easy to be obtained provides a new tool for R _s prediction, although a site-specific calibration is needed for using at a different region.     

Adequacy of Visually Classified Particle Count Statistics From Regional Stream Habitat Surveys1

Abstract: Streamlined sampling procedures must be used to achieve a sufficient sample size with limited resources in studies undertaken to evaluate habitat status and potential management‐related habitat degradation at a regional scale. At the same time, these sampling procedures must achieve sufficient precision to answer science and policy‐relevant questions with an acceptable and statistically quantifiable level of uncertainty. In this paper, we examine precision and sources of error in streambed substrate characterization using data from the Environmental Monitoring and Assessment Program (EMAP) of the U.S. Environmental Protection Agency, which uses a modified “pebble count” method in which particle sizes are visually estimated rather than measured. While the coarse (2?) size classes used in EMAP have little effect on the precision of estimated geometric mean (D_gm) or median (D₅₀) particle diameter, variable classification bias among observers can contribute as much as 0.3?, or about 15‐20%, to the root‐mean‐square error (RMSE) of D_gm or D₅₀ estimates. D_gm and D₅₀ estimates based on EMAP data are nearly equal when fine sediments (<2 mm) are excluded, but otherwise can differ by up to a factor of 2 or more, with D_gm < D₅₀ for gravel‐bed streams. The RMSE of reach‐scale particle size estimates based on visually classified particle count data from EMAP surveys, including variability associated with reoccupying unmarked sample reaches during revisits, is up to five to seven times higher than that reported for traditional measured pebble counts by multiple observers at a plot scale. Nonetheless, a variance partitioning analysis shows that the ratio of among site to revisit variance for several EMAP substrate metrics exceeds 8 for many potential regions of interest, suggesting that the data have adequate precision to be useful in regional assessments of channel morphology, habitat quality, or ecological condition.     

Characterizing Storm Hydrograph Rise and Fall Dynamics With Stream Stage Data1

Abstract: Storm‐flow transients (i.e., hydrograph rise and fall dynamics) may represent an important aspect of understanding streamflow dynamics. However, little is known about how temporal resolution of transient data and climate variability may color these potential indicators of hydrologic pattern or condition. Warm‐season stream stage and rainfall were monitored continuously (5 min) during the 2002 water year in eight tributaries of the Little Miami River (Ohio), which drain 17‐58 km² catchments. Rise rates generated using 5‐min data were different than those generated with mean daily data [calculated with the Indicators of Hydrologic Alteration (IHA) software], though fall rates were similar for fine and coarse temporal data. This result suggests that data with low temporal resolution may not be adequate to fully represent the dynamics of storm rise rates. Conversely, fall rates based on daily stage data (via IHA) were similar to those based on the 5‐min data, and so daily mean data may be appropriate for characterizing fall rates. We next analyzed the possible correlations between rainfall variability and storm‐flow stage dynamics. We derived rise and recession rates from storm stage hydrographs by assuming exponential rise and decay of a runoff peak. We found that raw rise rates (R_raw) were correlated with both the maximum rainfall rate and the time to the centroid of a rain event. We subsequently removed the trend based on these rainfall characteristics, which yielded new representations of rise rates abbreviated as R_rate and R_tcent, respectively, and that had lower variability than the uncorrected (raw) data. Fall rates were found to be independent of rainfall characteristics. Due to the predominant influence of stream hydrology upon aquatic biota and nutrient fluxes, our work suggests that these stage data analysis protocols can refine or otherwise reduce variability in these indices by accounting for relevant factors such as rainfall forcing. These protocols for derivation of transient indices should be tested for their potential to improve correlations between stream hydrology and temporally aligned biotic data and dissolved nutrient fluxes in streams.     

Sensitivity of Stream flow and Water Table Depth to Potential Climatic Variability in a Coastal Forested Watershed1

Dai, Zhaohua, Carl C. Trettin, Changsheng Li, Devendra M. Amatya, Ge Sun, and Harbin Li, 2010. Sensitivity of Streamflow and Water Table Depth to Potential Climatic Variability in a Coastal Forested Watershed. Journal of the American Water Resources Association (JAWRA) 1–13. DOI: 10.1111/j.1752-1688.2010.00474.x Abstract: A physically based distributed hydrological model, MIKE SHE, was used to evaluate the effects of altered temperature and precipitation regimes on the streamflow and water table in a forested watershed on the southeastern Atlantic coastal plain. The model calibration and validation against both streamflow and water table depth showed that the MIKE SHE was applicable for predicting the streamflow and water table dynamics for this watershed with an acceptable model efficiency (E > 0.5 for daily streamflow and >0.75 for monthly streamflow). The simulation results from changing temperature and precipitation scenarios indicate that climate change influences both streamflow and water table in the forested watershed. Compared to current climate conditions, the annual average streamflow increased or decreased by 2.4% with one percentage increase or decrease in precipitation; a quadratic polynomial relationship between changes in water table depth (cm) and precipitation (%) was found. The annual average water table depth and annual average streamflow linearly decreased with an increase in temperature within the range of temperature change scenarios (0-6°C). The simulation results from the potential climate change scenarios indicate that future climate change will substantially impact the hydrological regime of upland and wetland forests on the coastal plain with corresponding implications to altered ecosystem functions that are dependent on water.     

Hydrologic Effects of NDVI Time Series in a Context of Climatic Variability in an Upstream Catchment of the Minjiang River1

Abstract: Increasing regional vegetation activity has been frequently found especially in middle and high latitude and alpine areas, but the effects of which on regional hydrology is still highly uncertain. The Upstream Catchment of Minjiang River is a large mountainous catchment covering 22,919 km² with a diverse vegetation distribution pattern, including alpine group (A), subalpine group (SA), and temperate and subtropical group (T/ST). The Seasonal Mann‐Kendall test, a nonparametric trend test method, detected consistent upward trends in all groups in monthly accumulated growing degree days (AGDD_M) time series from 1982 to 2003, but no significant trend in mean monthly precipitation (MMP) time series in any group. The alpine group had a significant (p = 0.024) upward trend in monthly Normalized Difference of Vegetation Index (NDVI) time series from 1982 to 2003, in contrast, the SA and T/ST groups had decreasing (although not significant) trends. AGDD_M plays more important role than MMP in affecting NDVI change in alpine areas, indicating temperature was the main climatic driver. In contrast, water was the main driver for the T/ST group, as indicated by the significant correlation between NDVI and MMP and a weak correlation with AGDD_M. Correlation coefficients of NDVI and river flow varied with seasons, mostly negative, especially during the growing season (April to October). A significant (p = 0.025) correlation was found only in August, indicating that an increase in peak‐NDVI decreased high flow significantly. TI‐NDVI_c, which was developed in an attempt to track the vegetation change at the catchment scale, accounted for more than 40% of the evapotranspiration increase (r² = 0.43).     

Field Evaluation of DRAINMOD 5.1 Under a Cold Climate: Simulation of Daily Midspan Water Table Depths and Drain Outflows1

Abstract: The hydrologic performance of DRAINMOD 5.1 was assessed for the southern Quebec region considering freezing/thawing conditions. A tile drained agricultural field in the Pike River watershed was instrumented to measure tile drainage volumes. The model was calibrated using water table depth and subsurface flow data over a two‐year period, while another two‐year dataset served to validate the model. DRAINMOD 5.1 accurately simulated the timing and magnitude of subsurface drainage events. The model also simulated the pattern of water table fluctuations with a good degree of accuracy. The R² between the observed and simulated daily WTD for calibration was >0.78, and that for validation was 0.93. The corresponding coefficients of efficiency (E) were >0.74 and 0.31. The R² and E values for calibration/validation of subsurface flow were 0.73/0.48 and 0.72/0.40, respectively. DRAINMOD simulated monthly subsurface flow quite accurately (E > 0.82 and R² > 0.84). The model precisely simulated daily/monthly drain flow over the entire year, including the winter months. Thus DRAINMOD 5.1 performed well in simulating the hydrology of a cold region.     

SPATIAL VARIATIONS OF WATER LOSS DURING DROUGH A CASE STUDY1

ABSTRACT: A regional water conservation system for drought management involves many uncertain factors. Water received from precipitation may stay on the ground surface, evaporate back into the atmosphere, or infiltrate into the ground. Reliable estimates of the amount of evapotranspiration and infiltration are not available for a large basin, especially during periods of drought. By applying a geographic information system, this study develops procedures to investigate spatial variations of unavailable water for given levels of drought severity. Levels of drought severity are defined by truncated values of monthly precipitation and daily streamflow to reflect levels of water availability. The greater the truncation level, the lower the precipitation or streamflow. Truncation levels of monthly precipitation are recorded in depth of water while those of daily streamflow are converted into monthly equivalent water depths. Truncation levels of precipitation and streamflow treated as regionalized variables are spatially interpolated by the unbiased minimum variance estimation. The interpolated results are vector values of precipitation and streamflow at a grid of points covering the studied basin. They are then converted into raster‐based values and expressed graphically. The image subtraction operation is used to subtract the image of streamflow from that of precipitation at their corresponding level of drought severity. It is done on a cell‐by‐cell basis resulting in new attribute values to form the spatial image representing a spatial distribution of potential water loss at a given level of drought severity.     

Modeling Discharge Rates Using a Coupled Modeled Approach for the Merced River in Yosemite National Park

This study describes the application of the NASA version of the Carnegie‐Ames‐Stanford Approach (CASA) ecosystem model coupled with a surface hydrologic routing scheme previously called the Hydrological Routing Algorithm (HYDRA) to model monthly discharge rates from 2000 to 2007 on the Merced River drainage in Yosemite National Park, California. To assess CASA‐HYDRA's capability to estimate actual water flows in extreme precipitation years, the focus of this study is the 2007 water year, which was very dry, and the 2005 water year, which was a moderately wet year in the historical record. Prior to comparisons to gauge records, CASA‐HYDRA snowmelt algorithms were modified with equations from the U.S. Department of Agriculture Snowmelt‐Runoff Model (SRM), which has been designed to predict daily streamflow in mountain basins where snowmelt is a major runoff factor. Results show that model predictions closely matched monthly flow rates at the Pohono Bridge gauge station (USGS#11266500), with R² = 0.67 and Nash‐Sutcliffe (E) = 0.65. By subdividing the upper Merced River basin into subbasins with high spatial resolution in the gridded modeling approach, we were able to determine which biophysical characteristics in the Sierra differed to the largest degree in extreme low‐flow and high‐flow years. Average elevation and snowpack accumulation were found to be the most important explanatory variables to understand subbasin contributions to monthly discharge rates.     

Spatiotemporal Variability of Modeled Watershed Scale Surface‐Depression Storage and Runoff for the Conterminous United States

This study explores the viability of using simulated monthly runoff as a proxy for landscape‐scale surface‐depression storage processes simulated by the United States Geological Survey’s National Hydrologic Model (NHM) infrastructure across the conterminous United States (CONUS). Two different temporal resolution model codes (daily and monthly) were run in the NHM with the same spatial discretization. Simulated values of daily surface‐depression storage (treated as a decimal fraction of maximum volume) as computed by the daily Precipitation‐Runoff Modeling System (NHM‐PRMS) and normalized runoff (0 to 1) as computed by the Monthly Water Balance Model (NHM‐MWBM) were aggregated to monthly and annual values for each hydrologic response unit (HRU) in the CONUS geospatial fabric (HRU; n = 109,951) and analyzed using Spearman’s rank correlation test. Correlations between simulated runoff and surface‐depression storage aggregated to monthly and annual values were compared to identify where which time scale had relatively higher correlation values across the CONUS. Results show Spearman’s rank values >0.75 (highly correlated) for the monthly time scale in 28,279 HRUs (53.35%) compared to the annual time scale in 41,655 HRUs (78.58%). The geographic distribution of HRUs with highly correlated monthly values show areas where surface‐depression storage features are known to be common (e.g., Prairie Pothole Region, Florida).     

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.     

A System Dynamics Model for Conjunctive Management of Water Resources in the Snake River Basin

The Pacific Northwest is expected to witness changes in temperature and precipitation due to climate change. In this study, we enhance the Snake River Planning Model (SRPM) by modeling the feedback loop between incidental recharge and surface water supply resulting from surface water and groundwater extraction for irrigation and provide a case study involving climate change impacts and management scenarios. The new System Dynamics‐Snake River Planning Model (SD‐SRPM) is calibrated to flow at Box Canyon Springs located along a major outlet of the East Snake Plain Aquifer. A calibration of the model to flow at Box Canyon Springs, based on historic diversions (1950‐1995) resulted in an r² value of 0.74 and a validation (1996‐2005) r² value of 0.60. After adding irrigation entities to the model an r² value of 0.91, 0.88, and 0.87 were maintained for modeled vs. observed (1991‐2005) end‐of‐month reservoir content in Jackson Lake, Palisades, and American Falls, the three largest irrigation reservoirs in the system. The scenarios that compared the impacts of climate change were based on ensemble mean precipitation change scenarios and estimated changes to crop evapotranspiration (ET). Increased ET, despite increased precipitation, generally increased surface water shortages and discharge of springs. This study highlights the need to develop and implement models that integrate the human‐natural system to understand the impacts of climate change.     

Effect of Soils on Water Quantity and Quality in Piedmont Forested Headwater Watersheds of North Carolina1

Boggs, Johnny, Ge Sun, David Jones, and Steven G. McNulty, 2012. Effect of Soils on Water Quantity and Quality in Piedmont Forested Headwater Watersheds of North Carolina. Journal of the American Water Resources Association (JAWRA) 1‐19. DOI: 10.1111/jawr.12001 Abstract: Water quantity and quality data were compared from six headwater watersheds on two distinct soil formations, Carolina Slate Belt (CSB) and Triassic Basins (TB). CSB soils are generally thicker, less erodible, and contain less clay content than soils found in TB. TB generated significantly more discharge/precipitation ratio than CSB (0.33 vs. 0.24) in the 2009 dormant season. In the 2009 growing season, TB generated significantly less discharge/precipitation ratio than CSB (0.02 vs. 0.07). Over the entire monitoring period, differences in discharge/precipitation ratios between CSB and TB were not significantly different (0.17 vs. 0.20, respectively). Storm‐flow rates were significantly higher in TB than CSB in both dormant and growing season. Benthic macroinvertebrate biotic index scores were excellent for all streams. Nutrient concentrations and exports in CSB and TB were within background levels for forests. Low‐stream nitrate and ammonium concentrations and exports suggested that both CSB and TB were nitrogen limited. Soils appear to have had a significant influence on seasonal and storm‐flow generation, but not on long‐term total water yield and water quality under forested conditions. This study indicated that watersheds on TB soils might be more prone to storm‐flow generation than on CSB soils when converted from forest to urban. Future urban growth in the area should consider differences in baseline hydrology and effects of landuse change on water quantity and quality.     

Spatial and Seasonal Response of Municipal Water Use to Weather across the Contiguous U.S.

Weather variability has the potential to influence municipal water use, particularly in dry regions such as the western United States (U.S.). Outdoor water use can account for more than half of annual household water use and may be particularly responsive to weather, but little is known about how the expected magnitude of these responses varies across the U.S. This nationwide study identified the response of municipal water use to monthly weather (i.e., temperature, precipitation, evapotranspiration [ET]) using monthly water deliveries for 229 cities in the contiguous U.S. Using city‐specific multiple regression and region‐specific models with city fixed effects, we investigated what portion of the variability in municipal water use was explained by weather across cities, and also estimated responses to weather across seasons and climate regions. Our findings indicated municipal water use was generally well‐explained by weather, with median adjusted R² ranging from 63% to 95% across climate regions. Weather was more predictive of water use in dry climates compared to wet, and temperature had more explanatory power than precipitation or ET. In response to a 1°C increase in monthly maximum temperature, municipal water use was shown to increase by 3.2% and 3.9% in dry cities in winter and summer, respectively, with smaller changes in wet cities. Quantifying these responses allows urban water managers to plan for weather‐driven variability in water use.     

Calibration and Verification of SWMM for Low Impact Development

The Storm Water Management Model was used to simulate runoff and nutrient export from a low impact development (LID) watershed and a watershed using traditional runoff controls. Predictions were compared to observed values. Uncalibrated simulations underpredicted weekly runoff volume and average peak flow rates from the multiple subcatchment LID watershed by over 80%; the single subcatchment traditional watershed had better predictions. Saturated hydraulic conductivity, Manning's n for swales, and initial soil moisture deficit were sensitive parameters. After calibration, prediction of total weekly runoff volume for the LID and traditional watersheds improved to within 12 and 5% of observed values, respectively. For the validation period, predicted total weekly runoff volumes for the LID and traditional watersheds were within 6 and 2% of observed values, respectively. Water quality simulation was less successful, Nash–Sutcliffe coefficients >0.5 for both calibration and validation periods were only achieved for prediction of total nitrogen export from the LID watershed. Simulation of a 100‐year, 24‐h storm resulted in a runoff coefficient of 0.46 for the LID watershed and 0.59 for the traditional watershed. Results suggest either calibration is needed to improve predictions for LID watersheds or expanded look‐up tables for Green–Ampt infiltration parameter values that account for compaction of urban soil and antecedent conditions are needed.     

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.