Assessing Retrospective National Water Model Streamflow with Respect to Droughts and Low Flows in the Colorado River Basin

Streamflow monitoring in the Colorado River Basin (CRB) is essential to ensure diverse needs are met, especially during periods of drought or low flow. Existing stream gage networks, however, provide a limited record of past and current streamflow. Modeled streamflow products with more complete spatial and temporal coverage (including the National Water Model [NWM]), have primarily focused on flooding, rather than sustained drought or low flow conditions. Objectives of this study are to (1) evaluate historical performance of the NWM streamflow estimates (particularly with respect to droughts and seasonal low flows) and (2) identify characteristics relevant to model inputs and suitability for future applications. Comparisons of retrospective flows from the NWM to observed flows from the United States Geological Survey stream gage network over 22 years in the CRB reveal a tendency for underestimating low flow frequency, locations with low flows, and the number of years with low flows. We found model performance to be more accurate for the Upper CRB and at sites with higher precipitation, snow percent, baseflow index, and elevations. Underestimation of low flows and variable model performance has important implications for future applications: inaccurate evaluations of historical low flows and droughts, and less reliable performance outside of specific watershed/stream conditions. This highlights characteristics on which to focus future model development efforts.     

FOG DRIP IN THE BULL RUN MUNICIPAL WATERSHED,OREGON1

ABSTRACT: Net precipitation under old growth Douglas fir forest in the Bull Run Municipal Watershed (Portland, Oregon) totaled 1739 mm during a 4Cbweek period, 387 mm more than in adjacent clearcut areas. Expressing data on a full water year basis and adjusting gross precipitation for losses due to rainfall interception suggest fog drip could have added 882 mm (35 in) of water to total precipitation during a year when precipitation measured 2160 mm in a rain gage in a nearby clearing. Standard rain gages installed in open areas where fog is common may be collecting up to 30 percent less precipitation than would be collected in the forest. Long term forest management (Le., timber harvest) in the watershed could reduce annual water yield and, more importantly, summer stream flow by reducing fog drip.     

UNCERTAINTY OF EXTREME FLOOD ESTIMATES INCORPRATING HISTORICAL DATA1

ABSTRACT: The ability to predict extreme floods is an important part of the planning process for any water project for which failure will be very costly. The length of a gage record available for use in estimating extreme flows is generally much shorter than the recurrence interval of the desired flows, resulting in estimates having a high degree of uncertainty. Maximum likelihood estimators of the parameters of the three parameter lognormal (3PLN) distribution, which make use of historical data, are presented. A Monte Carlo study of extreme flows estimated from samples drawn from three hypothetical 3PLN populations showed that inclusion of historical flows with the gage record reduced the bias and variance of extreme flow estimates. Asymptotic theory approximations of parameter variances and covariances calculated using the second and mixed partial derivatives of the log likelihood function agreed well with Monte Carlo results. First order approximations of the standard deviations of the extreme flow estimates did not agree with the Monte Carlo results. An alternative method for calculating those standard deviations, the “asymptotic simulation” method, is described. The standard deviations calculated by asymptotic simulation agree well with the Monte Carlo results.     

UNCERTAINTIES IN ESTIMATING THE WATER BALANCE OF LAKES1

ABSTRACT: Evaluation of hydrologic methodology used in a number of water balance studies of lakes in the United States shows that most of these studies calculate one or more terms of the budget as the residual. A literature review was made of studies in which the primary purpose was error analysis of hydrologic measurement and interpretation. Estimates of precipitation can have a wide range of error, depending on the gage placement, gage spacing, and areal averaging technique. Errors in measurement of individual storms can be as high as 75 percent. Errors in short term averages are commonly in the 15-30 percent range, but decrease to about 5 percent or less for annual estimates. Errors in estimates of evaporation can also vary widely depending on instrumentation and methodology. The energy budget is the most accurate method of calculating evaporation; errors are in the 10–15 percent range. If pans are used that are located a distance from the lake of interest, errors can be considerable. Annual pan-to-lake coefficients should not be used for monthly estimates of evaporation because they differ from the commonly used coefficient of 0.7 by more than 100 percent. Errors in estimates of stream discharge are often considered to be within 5 percent. If the measuring section, type of flow profile, and other considerations, such as stage discharge relationship, are less than ideal errors in estimates of stream discharge can be considerably greater than 5 percent. Errors in estimating overland (nonchannelized) flow have not been evaluated, and in most lake studies this component is not mentioned. Comparison of several lake water balances in which the risdual consists solely of errors in measurement, shows that such a residual, if interpreted as ground water, can differ from an independent estimate of ground water by more than 100 percent.     

STREAM BASEFLOW PREDICTION BY CONVOLUTION OF ANTECEDENT RAINFALL EFFECTS1

ABSTRACT A method of stream baseflow prediction using a parallel drain theory and convolution techniques was developed. The infiltrating portions of several rain events were superimposed on the ground-water reserves and allowed to drain to the stream as individual baseflow responses. The convolution technique was used in summing the contributions from each rain event to the stream to give the total baseflow at any point in time. A single lumped parameter was adapted from a parallel drain analogy to represent the physical characteristics of a watershed. This parameter determines the time delay between a rainfall event and the resulting baseflow response. The procedure was applied to data from five watersheds. One year of records was used to find the best-fitting runoff delay coefficient, thus calibrating the response function which was subsequently applied to two test years to predict a dry weather low flow sequence. The agreement between predicted and observed flows was reasonably good, but marred by frequent minor rainfalls during the chosen dry periods. The application of the method should be much more successful in the western states where prolonged dry periods are common.     

COST REDUCTIONS DUE TO SEASONAL VARIATION IN MUNICIPAL WASTE WATER TREATMENT LEVELS1

ABSTRACT: Varying treatment levels to meet seasonal variation in assimilative capacity of streams can reduce total costs of treatment. A mathematical model of a Pennsylvania stream based on a theoretically sound approximation of the physical relationships underlying the distribution of DO in a river system was used to determine discharge constraints for an economic optimization model which produced estimates of sewage treatment cost savings. Increasing the number of flow periods during the year enhances cost reducing opportunities even when land application processes are considered. Also, the least cost treatment process for year around operation may not be the least costly under multiple flow period management.     

River Channel Geometry and Rating Curve Estimation Using Height above the Nearest Drainage

River channel geometry is an important input to hydraulic and hydrologic models. Traditional approaches to quantify river geometry have involved surveyed river cross sections, which cannot be extended to ungaged basins. In this paper, we describe a method for developing a synthetic rating curve to relate flow to water level in a stream reach based on reach‐averaged channel geometry properties developed using the Height above Nearest Drainage (HAND) method. HAND uses a digital elevation model (DEM) of the terrain and computes the elevation difference between each land surface cell and the stream bed cell to which it drains. Taking increments in water level in the stream, HAND defines the inundation zone and a water depth grid within this zone, and the channel characteristics are defined from this water depth grid. We apply our method to the Blanco River (Texas) and the Tar River (North Carolina) using 10‐m terrain data from the United States Geological Survey (USGS) 3D Elevation Program (3DEP) dataset. We evaluate the method's performance by comparing the reach‐average stage‐river geometry relationships and rating curves to those from calibrated Hydrologic Engineering Center's River Analysis System (HEC‐RAS) models and USGS gage observations. The results demonstrate that after some adjustment, the river geometry information and rating curves derived from HAND using national‐coverage datasets are comparable to those obtained from hydraulic models or gage measurements. We evaluate the inundation extent and show our approach is able to capture the majority of the Federal Emergency Management Agency (FEMA) 100‐year floodplain.     

APPLICATION OF THE RHESSys MODEL TO A CALIFORNIA SEMIARID SHRUBLAND WATERSHED1

ABSTRACT: Distributed hydrologic models which link seasonal streamflow and soil moisture patterns with spatial patterns of vegetation are important tools for understanding the sensitivity of Mediterranean type ecosystems to future climate and land use change. RHESSys (Regional Hydro‐Ecologic Simulation System) is a coupled spatially distributed hydroecological model that is designed to be able to represent these feedbacks between hydrologic and vegetation carbon and nutrient cycling processes. However, RHESSys has not previously been applied to semiarid shrubland watersheds. In this study, the hydrologic submodel of RHESSys is evaluated by comparing model predictions of monthly and annual streamflow to stream gage data and by comparing RHESSys behavior to that of another hydrologic model of similar complexity, MIKESHE, for a 34 km² watershed near Santa Barbara, California. In model intercomparison, the differences in predictions of temporal patterns in streamflow, sensitivity of model predictions to calibration parameters and landscape representation, and differences in model estimates of soil moisture patterns are explored. Results from this study show that both models adequately predict seasonal patterns of streamflow response relative to observed data, but differ significantly in terms of estimates of soil moisture patterns and sensitivity of those patterns to the scale of landscape tessellation used to derive spatially distributed elements. This sensitivity has implications for implementing RHESSys as a tool to investigate interactions between hydrology and ecosystem processes.     

Adaptation of Climate Model Projections of Streamflow to Account for Upstream Anthropogenic Impairments

A statistical procedure is developed to adjust natural streamflows simulated by dynamical models in downstream reaches, to account for anthropogenic impairments to flow that are not considered in the model. The resulting normalized downstream flows are appropriate for use in assessments of future anthropogenically impaired flows in downstream reaches. The normalization is applied to assess the potential effects of climate change on future water availability on the Rio Grande at a gage just above the major storage reservoir on the river. Model‐simulated streamflow values were normalized using a statistical parameterization based on two constants that relate observed and simulated flows over a 50‐year historical baseline period (1964–2013). The first normalization constant is a ratio of the means, and the second constant is the ratio of interannual standard deviations between annual gaged and simulated flows. This procedure forces the gaged and simulated flows to have the same mean and variance over the baseline period. The normalization constants can be kept fixed for future flows, which effectively assumes that upstream water management does not change in the future, or projected management changes can be parameterized by adjusting the constants. At the gage considered in this study, the effect of the normalization is to reduce simulated historical flow values by an average of 72% over an ensemble of simulations, indicative of the large fraction of natural flow diverted from the river upstream from the gage. A weak tendency for declining flow emerges upon averaging over a large ensemble, with tremendous variability among the simulations. By the end of the 21st Century the higher‐emission scenarios show more pronounced declines in streamflow.     

STREAM DISCHARGE PREDICTION VIA A GRID BASED SOIL WATER ROUTING WITH PADDY FIELDS1

ABSTRACT: A grid based daily hydrologic model for a watershed with paddy fields was developed to predict the stream discharge. ASCII formatted elevation, soil, and land use data supported by the GRASS Geographic Information System are used to generate distributed results such as surface runoff and subsurface flow, soil water content, and evapotranspiration. The model uses a single flow path algorithm and simulates a water balance at each grid element. A linear reservoir assumption was used to predict subsurface runoff components. The model was applied to a 75.6 km² watershed located in the middle of South Korea, and observed stream flow hydrographs from 1995 and 1996 were compared to model predictions. The stream flow predictions of 1995 and 1996 generally agreed with the observed flow, resulting in a Nash‐Sutcliffe efficiency R² of 0.60 and 0.62, respectively. The hydraulic conductivity for percolating water through the saturated layer affected baseflow generation. The levee height of the paddy influenced the time and magnitude of the surface runoff, depending on irrigation management. The model will be used for making low flow management decisions by evaluating the role of each land use to stream flow, especially in case of paddy decrease by gradual urbanization of a watershed.     

RUNOFF,EROSION, AND SOLUTES IN THE LOWER TRUCKEE RIVER,NEVADA, DURING 19691

The Truckee River heads in the Sierra Nevada at Lake Tahoe, and terminates in Pyramid Lake. During the 1969 water year, flow about 9 miles upstream from the mouth (974,000 acre-ft) was almost four times the long-term average, due mainly to heavy winter rains and spring snowmelt. A short period of low-altitude rainfall produced the highest concentrations of suspended sediment, whereas a much longer subsequent period of snowmelt yielded a much greater total quantity of material. The upper 90 percent of the basin yielded about 260 acre-feet (630,000 tons) of sediment at the Nixon gage, whereas an estimated 2,800 acre-feet (6.8 million tons) was contributed by erosion of about 200 acres of river bank below the gage. Solute content at the gage ranged from 80 to 450 mg/l, dominated by calcium, sodium, and bicarbonate, plus silica in the most dilute snowmelt and chloride in the most concentrated low flows. Solute load totaled about 130,000 tons, of which the principal constituents in Pyramid Lake-sodium plus equivalent bicarbonate and chloride-amounted to almost 40,000 tons. The total solute load during a year of average flow may be 45,000-55,000 tons, including 18,000-22,000 tons of principal lake constituents.     

IMPACTS OF CALIFORNIA'S CLIMATIC REGIMES AND COASTAL LAND USE CHANGE ON STREAMFLOW CHARACTERISTICS1

ABSTRACT: To investigate the impacts of urbanization and climatic fluctuations on stream flow magnitude and variability in a Mediterranean climate, the HEC‐HMS rainfall/runoff model is used to simulate stream flow for a 14‐year period (October 1, 1988, to September 30, 2002) in the Atascadero Creek watershed located along the southern coast of California for 1929, 1998, and 2050 (estimated) land use conditions (8, 38 and 52 percent urban, respectively). The 14‐year period experienced a range of climatic conditions caused mainly by El Nino‐Southern Oscillation variations. A geographic information system is used to delineate the watershed and parameterize the model, which is calibrated using data from two stream flow and eight rainfall gauges. Urbanization is shown to increase peak discharges and runoff volume while decreasing stream flow variability. In all cases, the annual and 14‐year distributions of stream flow are shown to be highly skewed, with the annual maximum 24 hours of discharge accounting for 22 to 52 percent of the annual runoff and the maximum ten days of discharge from an average El Nino year producing 10 to 15 percent of the total 14‐year discharge. For the entire period of urbanization (1929 to 2050), the average increase in annual maximum discharges and runoff was 45 m³/s (300 percent) and 15 cm (350 percent), respectively. Additionally, the projected increase in urbanization from 1998 to 2050 is half the increase from 1929 to 1998; however, increases in runoff (22 m³/s and 7 cm) are similar for both scenarios because of the region's spatial development pattern.     

CLIMATOLOGICAL WATERSHED CALIBRATION1

ABSTRACT: This study tests the hypothesis that climatic data can be used to develop a watershed model so that stream flow changes following forest harvest can be determined. Measured independent variables were precipitation, daily maximum and minimum temperature, and concurrent relative humidity. Computed variables were humidity deficit, saturated vapor pressure, and ambient vapor pressure. These climatic variables were combined to compute a monthly evaporation index. Finally, the evaporation index and monthly precipitation were regressed with measured monthly stream flow and the monthly estimates of stream flow were combined for the hydrologic year. A regression of predicted versus measured annual stream flow had a standard error of 1.5 inches (within 6.1 percent of the measured value). When 10, 15, and 20 years of data were used to develop the regression equations, predicted minus measured stream flow for the last 7 years of record (1972–1978) were within 16.8, 11.5, and 9.7 percent of the measured mean, respectively. Although single watershed calibration can be used in special conditions, the paired watershed approach is expected to remain the preferred method for determining the effects of forest management on the water resource.     

Stationarity of Streamflow Records and Their Influence on Bankfull Regional Curves1

Haucke, Jessica and Katherine A. Clancy, 2011. Stationarity of Streamflow Records and Their Influence on Bankfull Regional Curves. Journal of the American Water Resources Association (JAWRA) 47(6):1338–1347. DOI: 10.1111/j.1752‐1688.2011.00590.x Abstract: Bankfull regional curves, which are curves that establish relationships among channel morphology, discharge, drainage area, are used extensively for stream restoration. These curves are developed upon the assumption that streamflows maintain stationarity over the entire record. We examined this assumption in the Driftless Area of southwestern Wisconsin where agricultural soil retention practices have changed, and precipitation has increased since the 1970s. We developed a bankfull regional curve for this area using field surveys of bankfull channel performed during 2008‐2009 and annual series of peak streamflows for 10 rivers with streamflow records ranging from the 1930s to 2009. We found bankfull flows to correlate to a 1.1 return period. To evaluate gage data statistics, we used the sign test to compare our channel morphology to historic 1.5 return period discharge (Q_1.5) for five time periods: 1959‐1972, 1973‐1992, 1993‐2008, 1999‐2008, and the 1959‐2008 period of record. Analysis of the historic gage data indicated that there has been a more than 30% decline in Q_1.5 since 1959. Our research suggests that land conservation practices may have a larger impact on gaging station stationarity than annual precipitation changes do. Additionally, historic peak flow data from gages, which have records that span land conservation changes, may need to be truncated to represent current flow regimes.     

A SIMPLE METHOD FOR ESTIMATING BASEFLOW AT UNGAGED LOCATIONS1

ABSTRACT: Baseflow, or water that enters a stream from slowly varying sources such as ground water, can be critical to humans and ecosystems. We evaluate a simple method for estimating base‐flow parameters at ungaged sites. The method uses one or more baseflow discharge measurements at the ungaged site and longterm streamflow data from a nearby gaged site. A given baseflow parameter, such as the median, is estimated as the product of the corresponding gage site parameter and the geometric mean of the ratios of the measured baseflow discharges and the concurrent discharges at the gage site. If baseflows at gaged and ungaged sites have a bivariate lognormal distribution with high correlation and nearly equal log variances, the estimated baseflow parameters are very accurate. We tested the proposed method using long‐term streamflow data from two watershed pairs in the Driftless Area of southwestern Wisconsin. For one watershed pair, the theoretical assumptions are well met; for the other the log‐variances are substantially different. In the first case, the method performs well for estimating both annual and long‐term baseflow parameters. In the second, the method performs remarkably well for estimating annual mean and annual median baseflow discharge, but less well for estimating the annual lower decile and the long‐term mean, median, and lower decile. In general, the use of four measurements in a year is not substantially better than the use of two.     

ALTERNATIVE DEMAND MODEL ESTIMATORS FOR BLOCK RATE PRICING1

ABSTRACT: Three alternative demand model estimators for water sold under block rate tariffs are examined. The models are conceptually discussed and empirically estimated using cross-section and time-series data from Tucson, Arizona. While all three techniques produce plausible elasticity estimates, the ordinary least squares and censored sample techniques are shown to produce statistically biased results.     

VELOCITY DISTRIBUTIONS IN STREAMBED SIMULATION CULVERTS USED FOR FISH PASSAGE1

ABSTRACT: Stream crossings designed to simulate a natural streambed inside a culvert are commonly used to meet criteria where fish passage is required. Currently, there has been little research that quantitatively examines the flow patterns within these streambed simulation culverts. A model is presented that estimates the percent of a cross section that is within the swimming ability of juvenile fish developed from velocity measurements on first‐generation stream simulation culverts — those culverts with a continuous gravel bed. The model, developed with regression techniques, uses physical and hydraulic parameters including discharge, total cross sectional area, Froude number, and relative roughness, and was tested directly against velocity distributions computed from field measurements and in a culvert design mode. Results were favorable, although larger percentage errors exist, particularly at small flow depths. The model appears to underestimate the percent of channel cross section at or below a limiting velocity, hence it is generally conservative in design mode.     

PRECIPITATION MEASUREMENT BIASES IN THE UNITED STATES1

ABSTRACT: Gage-induced biases in monthly precipitation are estimated and removed at 1818 stations across the continental United States from 1950 through 1987. Deleterious effects of the wind and wetting losses on the interior walls of the gage were considered. These “corrected” estimates were obtained using site-specific information including wind speed, shelter-height air temperature, gage height, and sheltering. Wind speed and air temperature were interpolated at stations for which these data were not available using a spherically-based, nearest neighbor interpolation procedure. Results indicate that, as expected, biases are greater in the winter than the summer owing to the increased problems (particularly wind-induced) of measuring snowfall. In summer, percent errors range between 4 and 6 percent over nearly three-quarters of the United States with slightly larger errors over the Rocky Mountains. By contrast, winter biases are highly correlated with snowfall totals and percentage errors increase poleward, mimicking patterns of snowfall frequency. Since these biases are not trivial, they must be accounted for in order to obtain accurate and reliable time-series. If these biases are not properly addressed, serious errors can be introduced into climate change, hydrologic modeling, and environmental impact research.     

EVALUATING HSPF IN AN ARID,URBANIZED WATERSHED1

ABSTRACT: The Hydrologic Simulation Program‐FORTRAN (HSPF) is a powerful time variable hydrologic model that has rarely been applied in arid environments. Here, the performance of HSPF in southern California was assessed, testing its ability to predict annual volume, daily average flow, and hourly flow. The model was parameterized with eight land use categories and physical watershed characteristics. It was calibrated using rainfall and measured flow over a five‐year period in a predominantly undeveloped watershed and it was validated using a subsequent 4‐year period. The process was repeated in a separate, predominantly urbanized watershed over the same time span. Annual volume predictions correlated well with measured flow in both the undeveloped and developed watersheds. Daily flow predictions correlated well with measured flow following rain events, but predictions were poor during extended dry weather periods in the developed watershed. This modeling difficulty during dry‐weather periods reflects the large influence of, and the poor accounting in the model for, artificially introduced water from human activities, such as landscape overwatering, that can be important sources of water in urbanized arid environments. Hourly flow predictions mistimed peak flows, reflecting spatial and temporal heterogeneity of rainfall within the watershed. Model correlation increased considerably when predictions were averaged over longer time periods, reaching an asymptote after an 11‐hour averaging window.     

Estimation of Nonpoint Source Nitrate Concentrations in Indiana Rivers Based on Agricultural Drainage in the Watershed

Subsurface tile‐drained agricultural fields are known to be important contributors to nitrate in surface water in the Midwest, but the effect of these fields on nitrate at the watershed scale is difficult to quantify. Data for 25 watersheds monitored by the Indiana Department of Environmental Management and located near a U.S. Geological Survey stream gage were used to investigate the relationship between flow‐weighted mean concentration (FWMC) of nitrate‐N and the subsurface tile‐drained area (DA) of the watershed. The tile DA was estimated from soil drainage class, land use, and slope. Nitrate loads from point sources were estimated based on reported flows of major permitted facilities with mean nitrate‐N concentrations from published sources. Linear regression models exhibited a statistically significant relationship between annual/monthly nonpoint source (NPS) nitrate‐N and DA percentage. The annual model explained 71% of the variation in FWMC of nitrate‐N. The annual and monthly models were tested in 10 additional watersheds, most with absolute errors within 1 mg/l in the predicted FWMC. These models can be used to estimate NPS nitrate for unmonitored watersheds in similar areas, especially for drained agricultural areas where model performance was strongest, and to predict the nitrate reduction when various tile drainage management techniques are employed.