The Role of Climate and Human Influences in the Dry‐Up of the Jinci Springs,China1

Abstract: One of the largest karst springs in North China, the Jinci Springs, dried up and has remained dry since 1994. We develop a correlation analysis with time‐lag and a regression analysis with time‐lag to study the relation between spring flow and precipitation. This allows us to obtain a better understanding of karst hydrological processes by differentiating the contribution of variation in precipitation from anthropogenic impacts on the dry‐up of Jinci Springs. We divided the karstic hydrological processes into two phases: pre‐1961 and post‐1961. In the first phase (i.e., 1954‐1960) the groundwater recharge was affected by precipitation alone, and in the second phase (i.e., 1961‐1994) the groundwater recharge was influenced by both precipitation and human activities. Using precipitation and groundwater recharge data in the first phase, we set up a groundwater recharge model with time‐lags. By running the time‐lags model, we acquired the groundwater recharge likely to occur under the sole effect of precipitation in the second phase. Using a water‐balance calculation, we conclude that the groundwater recharge exhibited statistical stationarity, and the Jinci Springs dry‐up was the result of anthropogenic activities. At least three specific types of anthropogenic activities contributed to the drying‐up of Jinci Springs: (1) groundwater pumping accounts for 51%, (2) the dewatering from coal mining accounts for 33%, (3) and dam‐building 14%. The drying‐up of Jinci Springs meant that the groundwater drained from the aquifer’s fractures, and subsequently changed the structure of the karst aquifer. Although groundwater exploitation has been reduced, the flow at Jinci Springs has not reoccurred.     

Application of Wavelet Coherence Method to Investigate Karst Spring Discharge Response to Climate Teleconnection Patterns

The impact of climate teleconnections on the regional hydrometeorology has been well studied, but very little effort has been made to relate climate teleconnections with groundwater flow variation. In this study, we used a wavelet coherence method to analyze monthly climate indices, precipitation, and spring discharge data, and investigated the relation between major teleconnection patterns (the Arctic Oscillation, North Atlantic Oscillation, Pacific Decadal Oscillation, El Niño‐Southern Oscillation, and Indian Ocean Dipole) and karst hydrological process in Niangziguan Springs Basin, China. The results indicate precipitation and spring discharges correlate well with climate indices at intra‐ and inter‐annual time scales. Further, the climate indices are mainly correlated with precipitation at shorter periodicities, but correlated with spring discharge at longer scales. The difference reflects the modulation of karst aquifers on precipitation‐spring discharge during the processes of precipitation infiltration into the ground, and subsequent transformation into spring discharge. When teleconnection signals are transmitted into spring discharge via precipitation infiltration and groundwater propagation, some high‐frequency climatic signals are likely to be filtered, attenuated, and delayed, thus only low‐frequency climatic signals are preserved in spring discharge.     

WEST AFRICA: VOLTA DISCHARGE DATA QUALITY ASSESSMENT AND USE1

ABSTRACT: Water resource management in West Africa is often a complicated process due to inadequate resources, climatic extremes, and insufficient hydrological information. Insufficient data hinder sustainable watershed management practices, one of the top priorities in the Volta River Basin. This research properly fills in missing data by modeling the hydrological distribution in the Volta River Basin. On average, discharge gages across the basin are missing 20 percent of their monthly data over 20 years. Two methods were used to supplement missing data: a statistically linear model and a conceptual hydrological model. A linear equation, developed from the regression of precipitation and runoff, was used to evaluate the quality of existing data. The hydrological model separates the system into root and groundwater zones. Measured values were used to calibrate the hydrological model and to validate the statistical model. The quality of existing data was analyzed and organized for usability. Accuracy of the hydrological model was also evaluated for its effectiveness using R² and standard error. It was found that the hydrological model was an improvement from the linear model on a monthly basis; R² values improved by as much as 0.5 and monthly error decreased. Monthly predictions of the hydrological model were used to fill gaps of measured data sets.     

Estimating Water Budgets and Vertical Leakages for Karst Lakes in North‐Central Florida (United States) Via Hydrological Modeling1

Lin, Zhulu, 2011. Estimating Water Budgets and Vertical Leakages for Karst Lakes in North‐Central Florida (United States) Via Hydrological Modeling. Journal of the American Water Resources Association (JAWRA) 1‐16. DOI: 10.1111/j.1752‐1688.2010.00513.x Abstract: Newnans, Lochloosa, and Orange Lakes are closely hydrologically connected karst lakes located in north‐central Florida, United States. The complex karst hydrology in this region poses a great challenge to the hydrological modeling that is essential to the development of Total Maximum Daily Loads for these lakes. We used a Hydrological Simulation Program – Fortran model coupled with the parallel Parameter ESTimation model calibration and uncertainty analysis software to estimate effectively the hydrological interactions between the lakes and the underlying upper Floridan aquifer and the water budgets for these three lakes. The net results of the lake‐groundwater interactions in Newnans and Orange Lakes are that both lakes recharge the underlying upper Floridan aquifer, with the recharge rate of the latter one magnitude greater than that of the former. However, for Lochloosa Lake, the net lake‐groundwater interaction is that the lake gains water from groundwater in a significant amount, approximately 40% of its total terrestrial water input. The annual average vertical leakages estimated for Newnans, Lochloosa, and Orange Lakes are 6.0 × 10⁶, ?8.9 × 10⁶, and 44.4 × 10⁶ m³, respectively. The average vertical hydraulic conductance (K_v/b) of the units between a lake bottom and the underlying upper Floridan aquifer in this region are also estimated to be from 1.26 × 10^?4 to 1.01 × 10^?3 day^?1.     

Does the Temporal Resolution of Precipitation Input Influence the Simulated Hydrological Components Employing the SWAT Model?

This study aimed to evaluate the influence of sub‐daily precipitation time steps on model performance and hydrological components by applying the Green and Ampt infiltration method using the Soil and Water Assessment Tool (SWAT). Precipitation was measured at a resolution of 0.1 mm and aggregated to 5‐, 15‐, 30‐, and 60‐min time steps. Daily discharge data over a 10‐year period were used to calibrate and validate the model. Following a global sensitivity analysis, relevant parameters were optimized through an automatic calibration procedure using SWAT‐CUP for each time step. Daily performance statistics were almost equal among all four time steps (NSE ≈ 0.47). Discharge mainly consisted of groundwater flow (55%) and tile flow (42%), in reasonable proportions for the investigated catchment. In conclusion, model outputs were almost identical, showing simulations responded nearly independently of the chosen precipitation time step. This held true for (1) the selection of sensitive parameters, (2) performance statistics, (3) the shape of the hydrographs, and (4) flow components. However, a scenario analysis revealed that the precipitation time step becomes important when saturated hydraulic conductivities are low and curve numbers are high. The study suggests that there is no need in using precipitation time steps <1 h for lowland catchments dominated by soils with a low surface runoff potential if daily flow values are being considered. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Assessment of Groundwater Depletion and Implications for Management in the Denver Basin Aquifer System

The Denver Basin Aquifer System (DBAS) is a critical groundwater resource along the Colorado Front Range. Groundwater depletion has been documented over the past few decades due to the increased water use among users, presenting long‐term sustainability challenges. A spatiotemporal geostatistical analysis is used to estimate potentiometric surfaces and evaluate groundwater storage changes between 1990 and 2016 in each of the four DBAS aquifers. Several key depletion patterns and spatial water‐level changes emerge in this work. Hydraulic head changes are the largest in the west‐central side of the DBAS and have decreased in some areas by up to 180 m since 1990, while areas to the northwest show increases in hydraulic head by over 30.5 m. The Denver and Arapahoe aquifers show the largest groundwater storage losses, with the highest rates occurring in the 2000s. The results highlight uncertainty in the volumetric predictions under various storage coefficient calculations and emphasize the importance of representative aquifer characterization. The observed groundwater storage depletions are due to a combination of factors, which include population growth increasing the demand for water, variable precipitation, and drought influencing recharge, and increased groundwater pumping. The methods applied in this study are transferable to other groundwater systems and provide a framework that can help assess groundwater depletion and inform management decisions at other locations.     

Defining the Diurnal Pattern of Snowmelt Using a Beta Distribution Function

Snow is an important component of the hydrologic cycle for many regions worldwide. In addition to vital water resources, snowmelt can be important for forest ecosystem dynamics and flood risk. However, standard design events in the United States lack a design snowmelt event, including only precipitation events, though snowmelt has been shown to be larger than rainfall. In this article, we present a method using hourly snow water equivalent data to develop and test a function for representing the diurnal pattern of snowmelt. A two‐parameter beta distribution function is modified for the purposes of this study and found to fit the pattern of snowmelt well with a root mean squared error of 0.008. Soil moisture sensors were additionally utilized to assess the timing of the snowmelt water outflow from the base of the snowpack that supports the shape of the function, but suggests that the timing of losses recorded on snow pillows lag as much as 3 h. Further testing of the function showed the shape of the function to be accurate. The methods developed and tested in this paper can be applied for design purposes comparing snowmelt and rainfall events or to improve hydrological models investigating processes such as streamflow or groundwater recharge.     

How to Constrain Multi‐Objective Calibrations of the SWAT Model Using Water Balance Components

Accurate discharge simulation is one of the most common objectives of hydrological modeling studies. However, a good simulation of discharge is not necessarily the result of a realistic simulation of hydrological processes within the catchment. We propose an evaluation framework that considers both discharge and water balance components as evaluation criteria for calibration of the Soil and Water Assessment Tool (SWAT). In this study, we integrated average annual values of surface runoff, groundwater flow, and evapotranspiration in the model evaluation procedure to constrain the selection of good model runs for the Little River Experimental Watershed in Georgia, United States. For evaluating water balance and discharge dynamics, the Nash‐Sutcliffe efficiency (NSE) and percent bias (PBIAS) were used. In addition, the ratio of root mean square error and standard deviation of measured data (RSR) was calculated for individual segments of the flow duration curve to identify the best model runs in terms of discharge magnitude. Our results indicate that good statistics for discharge do not guarantee realistic simulations of individual water balance components. Therefore, we recommend constraining the ranges of water balance components to achieve a more realistic simulation of the entire hydrological system, even if tradeoffs between good statistics for discharge simulations and reasonable amounts of the water balance components are unavoidable. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

HYDROLOGIC ANALYSIS OF DISCHARGE SUSTAINABILITY FROM AN ABANDONED UNDERGROUND COAL MINE1

ABSTRACT: Discharge from flooded abandoned subsurface coal mines is considered a potential source for water supplies where other acceptable water sources are not available. The objective of this study was to develop procedures for determining sustainability of mine‐water discharge using rainfall and discharge data for a case study site. The study site is located in southwest Virginia where Late Paleozoic sequences of sandstone, coal, and shale predominate. A rain gauge and a flow rate monitoring system were installed at the site and data were collected for a period of 100 days. The recording period corresponded with one of the driest periods in recent years and, therefore, provided valuable information regarding the flow sustainability during baseflow conditions. From available data on underground mining patterns, geology, and ground water flow regimes, it was determined that a coal mine aquifer exhibits hydraulic characteristics very similar to the extremely heterogeneous systems observed in karst aquifers, and the mine discharge is analogous to springflow. Thus, techniques commonly used in karst‐water systems and springflow analysis were used to develop rainfall/mine‐discharge relationships. Springflow recession analysis was performed on five rainfall recessions and the coefficient for each recession was compared and interpreted in light of known geologic information. It was found that the recession coefficients described the mine discharge adequately and the mine aquifer response to a rainfall pulse was very similar to the response from certain types of karst aquifers. A cross‐correlation analysis was performed to verify the results of the recession analysis and to develop a “black box” statistical model for discharge data. The correlation analysis proved the validity of springflow recession analysis for mine discharge. The recorded data length was not adequate to create a statistical model, however, but a procedure was proposed for a statistical model that could be used with large flow records. For the study site, the mine discharge was found to be sustainable for a prolonged period of time.     

Testing and Improving Temperature Thresholds for Snow and Rain Prediction in the Western United States

The phase of precipitation at the land surface is critical to determine the timing and amount of water available for hydrological and ecological systems. However, there are few techniques to directly observe the precipitation phase and many prediction tools apply a single temperature threshold (e.g., 0°C) to determine phase. In this paper, we asked two questions: (1) what is the accuracy of default and station optimized daily temperature thresholds for predicting precipitation phase and (2) what are the regions and conditions in which typical temperature‐based precipitation phase predictions are most suited. We developed a ground truth dataset of rain vs. snow using an expert decision‐making system based on precipitation, snow depth, and snow water equivalent observations. This dataset was used to evaluate the accuracy of three temperature‐threshold‐based techniques of phase classification. Optimizing the temperature threshold improved the prediction of precipitation phase by 34% compared to using 0°C threshold. Developing a temperature threshold based on station elevation improved the error by 12% compared with using the 0°C temperature threshold. We also found the probability of snow as a function of temperature differed among ecoregions, which suggests a varied response to future climate change. These results highlight a current weakness in our ability to predict the effects of regional warming that could have uneven impacts on water and ecological resources.     

GROUND WATER/SURFACE WATER RESPONSES TO GLOBAL CLIMATE SIMULATIONS,SANTA CLARA‐CALLEGUAS BASIN,VENTURA, CALIFORNIA1

ABSTRACT: Climate variations can play an important, if not always crucial, role in successful conjunctive management of ground water and surface water resources. This will require accurate accounting of the links between variations in climate, recharge, and withdrawal from the resource systems, accurate projection or predictions of the climate variations, and accurate simulation of the responses of the resource systems. To assess linkages and predictability of climate influences on conjunctive management, global climate model (GCM) simulated precipitation rates were used to estimate inflows and outflows from a regional ground water model (RGWM) of the coastal aquifers of the Santa Clara‐Calleguas Basin at Ventura, California, for 1950 to 1993. Interannual to interdecadal time scales of the El Niño Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) climate variations are imparted to simulated precipitation variations in the Southern California area and are realistically imparted to the simulated ground water level variations through the climate‐driven recharge (and discharge) variations. For example, the simulated average ground water level response at a key observation well in the basin to ENSO variations of tropical Pacific sea surface temperatures is 1.2 m/°C, compared to 0.9 m/°C in observations. This close agreement shows that the GCM‐RGWM combination can translate global scale climate variations into realistic local ground water responses. Probability distributions of simulated ground water level excursions above a local water level threshold for potential seawater intrusion compare well to the corresponding distributions from observations and historical RGWM simulations, demonstrating the combination's potential usefulness for water management and planning. Thus the GCM‐RGWM combination could be used for planning purposes and — when the GCM forecast skills are adequate — for near term predictions.     

The Sensitivity of Northern Groundwater Recharge to Climate Change: A Case Study in Northwest Alaska1

Clilverd, Hannah M., Daniel M. White, Amy C. Tidwell, and Michael A. Rawlins, 2011. The Sensitivity of Northern Groundwater Recharge to Climate Change: A Case Study in Northwest Alaska. Journal of the American Water Resources Association (JAWRA) 47(6):1228–1240. DOI: 10.1111/j.1752‐1688.2011.00569.x Abstract: The potential impacts of climate change on northern groundwater supplies were examined at a fractured‐marble mountain aquifer near Nome, Alaska. Well water surface elevations (WSE) were monitored from 2004‐2009 and analyzed with local meteorological data. Future aquifer response was simulated with the Pan‐Arctic Water Balance Model (PWBM) using forcings (air temperature and precipitation) derived from fifth‐generation European Centre Hamburg Model (ECHAM5) global circulation model climate scenarios for extreme and modest increases in greenhouse gases. We observed changes in WSE due to the onset of spring snowmelt, low intensity and high intensity rainfall events, and aquifer head recession during the winter freeze period. Observed WSE and snow depth compared well with PWBM‐simulated groundwater recharge and snow storage. Using ECHAM5‐simulated increases in mean annual temperature of 4‐8°C by 2099, the PWBM predicted that by 2099 later freeze‐up and earlier snowmelt will decrease seasonal snow cover by one to two months. Annual evapotranspiration and precipitation are predicted to increase 27‐40% (55‐81 mm) and 33‐42% (81‐102 mm), respectively, with the proportion of snowfall in annual precipitation decreasing on average 9‐25% (p < 0.05). The amount of snowmelt is not predicted to change significantly by 2099; however, a decreasing trend is evident from 2060 in the extreme ECHAM5 greenhouse gas scenario. Increases in effective precipitation were predicted to be great enough to sustain sufficient groundwater recharge.     

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.     

Effect of Snow Cover Conditions on the Hydrologic Regime: Case Study in a Pluvial‐Nival Watershed,Japan1

Abstract: Hydrologic monitoring in a small forested and mountainous headwater basin in Niigata Prefecture has been undertaken since 2000. An important characteristic of the basin is that the hydrologic regime contains pluvial elements year‐round, including rain‐on‐snow, in addition to spring snowmelt. We evaluated the effect of different snow cover conditions on the hydrologic regime by analyzing observed data in conjunction with model simulations of the snowpack. A degree‐day snow model is presented and applied to the study basin to enable estimation of the basin average snow water equivalent using air temperature at three representative elevations. Analysis of hydrological time series data and master recession curves showed that flow during the snowmelt season was generated by a combination of ground water flow having a recession constant of 0.018/day and diurnal melt water flow having a recession constant of 0.015/hour. Daily flows during the winter/snowmelt season showed greater persistence than daily flows during the warm season. The seasonal water balance indicated that the ratio of runoff to precipitation during the cold season (December to May) was about 90% every year. Seasonal snowpack plays an important role in defining the hydrologic regime, with winter precipitation and snowmelt runoff contributing about 65% of the annual runoff. The timing of the snowmelt season, indicated by the date of occurrence of the first significant snowmelt event, was correlated with the occurrence of low flow events. Model simulations showed that basin average snow water equivalent reached a peak around mid‐February to mid‐March, although further validation of the model is required at high elevation sites.     

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

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

Controls on Temperature in Salmonid‐Bearing Headwater Streams in Two Common Hydrogeologic Settings,Kenai Peninsula,Alaska

Headwater streams are the most numerous in terms of both number and length in the conterminous United States and play important roles as spawning and rearing grounds for numerous species of anadromous fish. Stream temperature is a controlling variable for many physical, chemical, and biological processes and plays a critical role in the overall health and integrity of a stream. We investigated the controls on stream temperature in salmon‐bearing headwater streams in two common hydrogeologic settings on the Kenai Peninsula, Alaska: (1) drainage‐ways, which are low‐gradient streams that flow through broad valleys; and (2) discharge‐slopes, which are high gradient streams that flow through narrow valleys. We hypothesize local geomorphology strongly influences surface‐water and groundwater interactions, which control streamflow at the network scale and stream temperatures at the reach scale. The results of this study showed significant differences in stream temperatures between the two hydrogeologic settings. Observed stream temperatures were higher in drainage‐way sites than in discharge‐slope sites, and showed strong correlations as a continuous function with the calculated topographic metric flow‐weighted slope. Additionally, modeling results indicated the potential for groundwater discharge to moderate stream temperature is not equal between the two hydrogeologic settings, with groundwater having a greater moderating effect on stream temperature at the drainage‐way sites.     

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.     

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.     

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.     

Regional scale flood modeling using NEXRAD rainfall, GIS, and HEC-HMS/RAS: a case study for the San Antonio River Basin Summer 2002 storm event

This paper develops a framework for regional scale flood modeling that integrates NEXRAD Level III rainfall, GIS, and a hydrological model (HEC-HMS/RAS). The San Antonio River Basin (about 4000 square miles, 10,000 km2) in Central Texas, USA, is the domain of the study because it is a region subject to frequent occurrences of severe flash flooding. A major flood in the summer of 2002 is chosen as a case to examine the modeling framework. The model consists of a rainfall-runoff model (HEC-HMS) that converts precipitation excess to overland flow and channel runoff, as well as a hydraulic model (HEC-RAS) that models unsteady state flow through the river channel network based on the HEC-HMS-derived hydrographs. HEC-HMS is run on a 4 x 4 km grid in the domain, a resolution consistent with the resolution of NEXRAD rainfall taken from the local river authority. Watershed parameters are calibrated manually to produce a good simulation of discharge at 12 subbasins. With the calibrated discharge, HEC-RAS is capable of producing floodplain polygons that are comparable to the satellite imagery. The modeling framework presented in this study incorporates a portion of the recently developed GIS tool named Map to Map that has been created on a local scale and extends it to a regional scale. The results of this research will benefit future modeling efforts by providing a tool for hydrological forecasts of flooding on a regional scale. While designed for the San Antonio River Basin, this regional scale model may be used as a prototype for model applications in other areas of the country.