Hydrologic Model Framework for Water Resources Planning in the Santa Cruz River,Southern Arizona1

Abstract: The authors develop a model framework that includes a set of hydrologic modules as a water resources management and planning tool for the upper Santa Cruz River near the Mexican border, Southern Arizona. The modules consist of: (1) stochastic generation of hourly precipitation scenarios that maintain the characteristics and variability of a 45‐year hourly precipitation record from a nearby rain gauge; (2) conceptual transformation of generated precipitation into daily streamflow using varied infiltration rates and estimates of the basin antecedent moisture conditions; and (3) surface‐water to ground‐water interaction for four downstream microbasins that accounts for alluvial ground‐water recharge, and ET and pumping losses. To maintain the large inter‐annual variability of streamflow as prevails in Southern Arizona, the model framework is constructed to produce three types of seasonal winter and summer categories of streamflow (i.e., wet, medium, or dry). Long‐term (i.e., 100 years) realizations (ensembles) are generated by the above described model framework that reflects two different regimes of inter annual variability. The first regime is that of the historic streamflow gauge record. The second regime is that of the tree ring reconstructed precipitation, which was derived for the study location. Generated flow ensembles for these two regimes are used to evaluate the risk that the regional four ground‐water microbasins decline below a preset storage threshold under different operational water utilization scenarios.     

A PROPOSED METHOD FOR DROUGHT MONITORING1

ABSTRACT: Existing definitions of drought have focused on limited hydrologic indicators and are less effective for the purpose of drought monitoring. This study uses historical records of streamflow, precipitation, ground water, temperature, and lake elevation to define drought. Based on the method of truncation, drought durations and conditional probabilities of each indicator were estimated to define the drought severity levels, namely, 70 percent, 80 percent, 90 percent, and 95 percent. A drought monitoring method was developed by a combination of truncation level, duration, and conditional probabilities of five indicators. A six-month period of the 1988 drought in the central Ohio region was used to test the monitoring method. It was found that the developed method could effectively detect an occurrence of drought.     

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.     

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.     

GEOLOGICAL AND CLIMATIC CONTROLS ON STREAMFLOWS IN THE NEBRASKA SAND HILLS1

ABSTRACT: This paper presents hydrological characteristics of the streamflow of the Dismal, Middle Loup, North Loup, and Cedar Rivers in the Nebraska Sand Hills and their relation to climate and ground water variation. Time series of streamflow, precipitation, temperature, and ground water levels from 1976 to 1998 were used to analyze trends and fluctuations of streamflow and to determine relationships among streamflow, climate, and the ground water system. An increase of precipitation and a decrease of maximum temperature over the period resulted in higher ground water levels and increased streamflow in the region. The high permeability of the soil and the thick unsaturated zone enhance precipitation recharge, limit surface runoff, and prevent ground water losses through evapotranspiration. Thus, an abundance of ground water is stored, supplying more than 86 percent of streamflow in the four rivers. Streamflow is generally more constant in the Sand Hills than elsewhere in the region. The four rivers present different hydrologic characteristics because of the spatial heterogeneity in hydrogeologic conditions. Streamflow of the Dismal and Middle Rivers, which are less sensitive to climatic variation, is much steadier than that of the North Loup and Cedar Rivers.     

Historical Groundwater Trends in Northern New England and Relations with Streamflow and Climatic Variables

Water‐level trends spanning 20, 30, 40, and 50 years were tested using month‐end groundwater levels in 26, 12, 10, and 3 wells in northern New England (Maine, New Hampshire, and Vermont), respectively. Groundwater levels for 77 wells were used in interannual correlations with meteorological and hydrologic variables related to groundwater. Trends in the contemporary groundwater record (20 and 30 years) indicate increases (rises) or no substantial change in groundwater levels in all months for most wells throughout northern New England. The highest percentage of increasing 20‐year trends was in February through March, May through August, and October through November. Forty‐year trend results were mixed, whereas 50‐year trends indicated increasing groundwater levels. Whereas most monthly groundwater levels correlate strongly with the previous month's level, monthly levels also correlate strongly with monthly streamflows in the same month; correlations of levels with monthly precipitation are less frequent and weaker than those with streamflow. Groundwater levels in May through August correlate strongly with annual (water year) streamflow. Correlations of groundwater levels with streamflow data and the relative richness of 50‐ to 100‐year historical streamflow data suggest useful proxies for quantifying historical groundwater levels in light of the relatively short and fragmented groundwater data records presently available.     

DROUGHT,TREE RINGS,AND RESERVOIR DESIGN1

Droughts constitute one of the most important factors affecting the design and operation of water resources infrastructure. Hydrologists ascertain their duration, severity, and pattern of recurrence from instrumental records of precipitation or stream‐flow. Under suitable conditions, and with proper analysis, tree rings obtained from long living, climate sensitive species of trees can extend instrumental records of streamflow and precipitation over periods spanning several centuries. Those tree‐ring “reconstructions” provide a valuable insight about climate variability and drought occurrence in the Holocene, and yield long term hydrological data useful in the design of water infrastructure. This work presents a derivation of drought risk based on a renewal model of drought recurrence, a brief review of the basic theory of tree‐ring reconstructions, and a stochastic model for optimizing the design of water supply reservoirs. Examples illustrate the methodology developed in this work and the supporting role that tree‐ring reconstructed streamflow can play in characterizing hydrologic variability.     

GROUND WATER DROUGHT MANAGEMENT BY A FEEDFORWARD CONTROL METHOD1

ABSTRACT: Management of a regional ground water system to mitigate drought problems at the multi‐layered aquifer system in Collier County, Florida, is the main topic. This paper developed a feedforward control system that consists of system and control equations. The system equation, which forecasts ground water levels using the current measurements, was built based on the Kalman filter algorithm associated with a stochastic time series model. The role of the control equation is to estimate the pumping reduction rate during an anticipated drought. The control equation was built based on the empirical relationship between the change in ground water levels and the corresponding pumping requirement. The control system starts with forecasting one‐month‐ahead ground water head at each control point. The forecasted head is in turn used to calculate the deviation of ground water heads from the monthly target specified by a 2‐in‐10‐year frequency. When the forecasted water level is lower than the target, the control system computes spatially‐varied pumping reduction rates as a recommendation for ground water users. The proposed control system was tested using hypothetical droughts. The simulation result revealed that the estimated pumping reduction rates are highly variable in space, strongly supporting the idea of spatial forecasting and controlling of ground water levels as opposed to a lumped water use restriction method used previously in the model area.     

Characterization of Drought in the South Atlantic,United States

Drought has been less extensively characterized in the humid South Atlantic compared to the arid western United States. Our objective was to characterize drought in the South Atlantic and to understand whether drought has become more severe in this region over time. Here we used monthly streamflow to characterize hydrological drought. Hydrological drought occurred when streamflow fell below the 20th percentile over three consecutive months and terminated once streamflow remained above the 20th percentile for three consecutive months. We characterized the frequency, duration, magnitude, and severity of events using the above definition. Significant changes in drought characteristics were tested with Mann‐Kendall over three periods: 1930‐2010, 1930‐1969, and 1970‐2010. We show that 71% of drought events were shorter than six months, while 7% were multiyear events. There was little evidence of trends in drought characteristics to support the claim of drought becoming more severe in the South Atlantic over the 20th Century. The one exception was a significant increase in the joint probability of nearby basins being simultaneously in drought conditions in the southern portion of the study area from 1970 to 2010. While drought characteristics have changed little through time, decreasing average streamflow in non drought periods coupled with increasing water demand provide the context within which recent multiyear drought events have produced significant stress on existing water infrastructure.     

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.     

Five Hundred Years of Hydrological Drought in the Upper Colorado River Basin1

Abstract: This article evaluates drought scenarios of the Upper Colorado River basin (UCRB) considering multiple drought variables for the past 500 years and positions the current drought in terms of the magnitude and frequency. Drought characteristics were developed considering water‐year data of UCRB’s streamflow, and basin‐wide averages of the Palmer Hydrological Drought Index (PHDI) and the Palmer Z Index. Streamflow and drought indices were reconstructed for the last 500 years using a principal component regression model based on tree‐ring data. The reconstructed streamflow showed higher variability as compared with reconstructed PHDI and reconstructed Palmer Z Index. The magnitude and severity of all droughts were obtained for the last 500 years for historical and reconstructed drought variables and ranked accordingly. The frequency of the current drought was obtained by considering two different drought frequency statistical approaches and three different methods of determining the beginning and end of the drought period (annual, 5‐year moving, and ten year moving average). It was concluded that the current drought is the worst in the observed record period (1923‐2004), but 6th to 14th largest in terms of magnitude and 1st to 12th considering severity in the past 500 years. Similarly, the current drought has a return period ranging from 37 to 103 years based on how the drought period was determined. It was concluded that if the 10‐year moving average is used for defining the drought period, the current drought appears less severe in terms of magnitude and severity in the last 500 years compared with the results using 1‐ and 5‐year averages.     

Mid‐Range Streamflow Forecasts Based on Climate Modeling – Statistical Correction and Evaluation1

Abstract: Mid‐range streamflow predictions are extremely important for managing water resources. The ability to provide mid‐range (three to six months) streamflow forecasts enables considerable improvements in water resources system operations. The skill and economic value of such forecasts are of great interest. In this research, output from a general circulation model (GCM) is used to generate hydrologic input for mid‐range streamflow forecasts. Statistical procedures including: (1) transformation, (2) correction, (3) observation of ensemble average, (4) improvement of forecast, and (5) forecast skill test are conducted to minimize the error associated with different spatial resolution between the large‐scale GCM and the finer‐scale hydrologic model and to improve forecast skills. The accuracy of a streamflow forecast generated using a hydrologic model forced with GCM output for the basin was evaluated by forecast skill scores associated with the set of streamflow forecast values in a categorical forecast. Despite the generally low forecast skill score exhibited by the climate forecasting approach, precipitation forecast skill clearly improves when a conditional forecast is performed during the East Asia summer monsoon, June through August.     

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.     

WATER RESOURCES DEVELOPMENT IN THE MULLICA RIVER BASIN1

ABSTRACT: The potential withdrawal of water from the Mullica River-Great Bay Estuary is southern New Jersey prompted a joint study by biologists and engineers to determine the maximum supply of water that could be diverted from the basin without causing undue environmental impacts. The effect of removal of water from the basin over long periods of time was simulated by review of records of a severe drought. Based on analysis of streamflows and salinities during these drought conditions, minimum mean monthly streamflows were determined corresponding to the maximum salinities tolerable by the fish and shellfish communities, important sources of revenue and recreation in the region. A physically optimized, chance constrained linear programming model was developed for the conjunctive use of ground and surface waters. Adjusting water withdrawal from streamflow and groundwater sources according to physical and seasonal criteria would permit maximum use of the basin's resources, with no additional burden on the ecology of the estuary.     

Impact of Length of Dataset on Streamflow Calibration Parameters and Performance of APEX Model

Due to resource constraints, long‐term monitoring data for calibration and validation of hydrologic and water quality models are rare. As a result, most models are calibrated and, if possible, validated using limited measured data. However, little research has been done to determine the impact of length of available calibration data on model parameterization and performance. The main objective of this study was to evaluate the impact of length of calibration data (LCD) on parameterization and performance of the Agricultural Policy Environmental eXtender model for predicting daily, monthly, and annual streamflow. Long‐term (1984‐2015) measured daily streamflow data from Rock Creek watershed, an agricultural watershed in northern Ohio, were used for this study. Data were divided into five Short (5‐year), two Medium (15‐year), and one Long (25‐year) streamflow calibration data scenarios. All LCD scenarios were calibrated and validated at three time steps: daily, monthly, and annual. Results showed LCD affected the ability of the model to accurately capture temporal variability in simulated streamflow. However, overall average streamflow, water budgets, and crop yields were simulated reasonably well for all LCD scenarios.     

Soil moisture‐based drought monitoring at different time scales: a case study for the U.S. Great Plains

Short‐term agricultural drought and longer term hydrological drought have important ecological and socioeconomic impacts. Soil moisture monitoring networks have potential to assist in the quantification of drought conditions because soil moisture changes are mostly due to precipitation and evapotranspiration, the two dominant water balance components in most areas. In this study, the Palmer approach to calculating a drought index was combined with a soil water content‐based moisture anomaly calculation. A drought lag time parameter was introduced to quantify the time between the start of a moisture anomaly and the onset of drought. The methodology was applied to four shortgrass prairie sites along a North‐South transect in the U.S. Great Plains with an 18‐year soil moisture record. Short time lags led to high periodicity of the resulting drought index, appropriate for assessing short‐term drought conditions at the field scale (agricultural drought). Conversely, long time lags led to low periodicity of the drought index, being more indicative of long‐term drought conditions at the watershed or basin scale (hydrological drought). The influence of daily, weekly, and monthly time steps on the drought index was examined and found to be marginal. The drought index calculated with a short drought lag time showed evidence of being normally distributed. A longer data record is needed to assess the statistical distribution of the drought index for longer drought lag times.     

Assessment of Alternative Methods for Statistically Downscaling Daily GCM Precipitation Outputs to Simulate Regional Streamflow

This study applied three statistical downscaling methods: (1) bias correction and spatial disaggregation at daily time scale (BCSD_daily); (2) a modified version of BCSD which reverses the order of spatial disaggregation and bias correction (SDBC), and (3) the bias correction and stochastic analog method (BCSA) to downscale general circulation model daily precipitation outputs to the subbasin scale for west‐central Florida. Each downscaled climate input dataset was then used in an integrated hydrologic model to examine differences in ability to simulate retrospective streamflow characteristics. Results showed the BCSD_daily method consistently underestimated mean streamflow because the highly spatially correlated small precipitation events produced by this method resulted in overestimation of evapotranspiration. Highly spatially correlated large precipitation events produced by the SDBC method resulted in overestimation of the standard deviation of wet season daily streamflow and the magnitude/frequency of high streamflow events. BCSA showed better performance than the other methods in reproducing spatiotemporal statistics of daily precipitation and streamflow. This study demonstrated differences in statistical downscaling techniques propagate into significant differences in streamflow predictions, and underscores the need to carefully select a downscaling method that reproduces precipitation characteristics important for the hydrologic system under consideration.     

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.     

SIMULATING THE EFFECTS OF REDUCED PRECIPITATION ON GROUND WATER AND STREAMFLOW IN THE NEBRASKA SAND HILLS1

ABSTRACT: The Nebraska Sand Hills have a unique hydrologic system with very little runoff and thick aquifers that constantly supply water to rivers, lakes, and wetlands. A ground water flow model was developed to determine the interactions between ground water and streamflow and to simulate the changes in ground water systems by reduced precipitation. The numerical modeling method includes a water balance model for the vadose zone and MOD‐FLOW for the saturated zone. The modeling results indicated that, between 1979 and 1990, 13 percent of the annual precipitation recharged to the aquifer and annual ground water loss by evapotranspiration (ET) was only about one‐fourth of this recharge. Ground water discharge to rivers accounts for about 96 percent of the streamflow in the Dismal and Middle Loup rivers. When precipitation decreased by half the average amount of the 1979 to 1990 period, the average decline of water table over the study area was 0.89 m, and the streamflow was about 87 percent of the present rate. This decline of the water table results in significant reductions in ET directly from ground water and so a significant portion of the streamflow is maintained by capture of the salvaged ET.     

Groundwater Level Trends and Drivers in Two Northern New England Glacial Aquifers

We evaluated long‐term trends and predictors of groundwater levels by month from two well‐studied northern New England forested headwater glacial aquifers: Sleepers River, Vermont, 44 wells, 1992‐2013; and Hubbard Brook, New Hampshire, 15 wells, 1979‐2004. Based on Kendall Tau tests with Sen slope determination, a surprising number of well‐month combinations had negative trends (decreasing water levels) over the respective periods. Sleepers River had slightly more positive than negative trends overall, but among the significant trends (p < 0.1), negative trends dominated 67 to 40. At Hubbard Brook, negative trends outnumbered positive trends by a nearly 2:1 margin and all seven of the significant trends were negative. The negative trends occurred despite generally increasing trends in monthly and annual precipitation. This counterintuitive pattern may be a result of increased precipitation intensity causing higher runoff at the expense of recharge, such that evapotranspiration demand draws down groundwater storage. We evaluated predictors of month‐end water levels by multiple regression of 18 variables related to climate, streamflow, snowpack, and prior month water level. Monthly flow and prior month water level were the two strongest predictors for most months at both sites. The predictive power and ready availability of streamflow data can be exploited as a proxy to extend limited groundwater level records over longer time periods.