Development of the Chesapeake Bay Watershed Total Maximum Daily Load Allocation

Nutrient load allocations and subsequent reductions in total nitrogen and phosphorus have been applied in the Chesapeake watershed since 1992 to reduce hypoxia and to restore living resources. In 2010, sediment allocations were established to augment nutrient allocations supporting the submerged aquatic vegetation resource. From the initial introduction of nutrient allocations in 1992 to the present, the allocations have become more completely applied to all areas and loads in the watershed and have also become more rigorously assessed and tracked. The latest 2010 application of nutrient and sediment allocations were made as part of the Chesapeake Bay total maximum daily load and covered all six states of the Chesapeake watershed. A quantitative allocation process was developed that applied principles of equity and efficiency in the watershed, while achieving all tidal water quality standards through an assessment of equitable levels of effort in reducing nutrients and sediments. The level of effort was determined through application of two key watershed scenarios: one where no action was taken in nutrient control and one where maximum nutrient control efforts were applied. Once the level of effort was determined for different jurisdictions, the overall load reduction was set watershed‐wide to achieve dissolved oxygen water quality standards. Further adjustments were made to the allocation to achieve the James River chlorophyll‐a standard.     

Cropland Riparian Buffers throughout Chesapeake Bay Watershed: Spatial Patterns and Effects on Nitrate Loads Delivered to Streams

We used statistical models to provide the first empirical estimates of riparian buffer effects on the cropland nitrate load to streams throughout the Chesapeake Bay watershed. For each of 1,964 subbasins, we quantified the 1990 prevalence of cropland and riparian buffers. Cropland was considered buffered if the topographic flow path connecting it to a stream traversed a streamside forest or wetland. We applied a model that predicts stream nitrate concentration based on physiographic province and the watershed proportions of unbuffered and buffered cropland. We used another model to predict annual streamflow based on precipitation and temperature, and then multiplied the predicted flows and concentrations to estimate 1990 annual nitrate loads. Across the entire Chesapeake watershed, croplands released 92.3 Gg of nitrate nitrogen, but 19.8 Gg of that was removed by riparian buffers. At most, 29.4 Gg more might have been removed if buffer gaps were restored so that all cropland was buffered. The other 43.1 Gg of cropland load cannot be addressed with riparian buffers. The Coastal Plain physiographic province provided 52% of the existing buffer reduction of Bay‐wide nitrate loads and 36% of potential additional removal from buffer restoration in cropland buffer gaps. Existing and restorable nitrate removal in buffers were lower in the other three major provinces because of less cropland, lower buffer prevalence, and lower average buffer nitrate removal efficiency.     

MODIS Biophysical States and NEXRAD Precipitation in a Statistical Evaluation of Antecedent Moisture Condition and Streamflow1

Abstract: The potential of remotely sensed time series of biophysical states of landscape to characterize soil moisture condition antecedent to radar estimates of precipitation is assessed in a statistical prediction model of streamflow in a 1,420 km² watershed in south‐central Texas, Moderate Resolution Imaging Spectroradiometer (MODIS) time series biophysical products offer significant opportunities to characterize and quantify hydrologic state variables such as land surface temperature (LST) and vegetation state and status. Together with Next Generation Weather Radar (NEXRAD) precipitation estimates for the period 2002 through 2005, 16 raw and deseasoned time series of LST (day and night), vegetation indices, infrared reflectances, and water stress indices were linearly regressed against observed watershed streamflow on an eight‐day aggregated time period. Time offsets of 0 (synchronous with streamflow event), 8, and 16 days (leading streamflow event) were assessed for each of the 16 parameters to evaluate antecedent effects. The model results indicated a reasonable correlation (r² = 0.67) when precipitation, daytime LST advanced 16 days, and a deseasoned moisture stress index were regressed against log‐transformed streamflow. The estimation model was applied to a validation period from January 2006 through March 2007, a period of 12 months of regional drought and base‐flow conditions followed by three months of above normal rainfall and a flood event. The model resulted in a Nash‐Sutcliffe estimation efficiency (E) of 0.45 for flow series (in log‐space) for the full 15‐month period, ?0.03 for the 2006 drought condition period, and 0.87 for the 2007 wet condition period. The overall model had a relative volume error of ?32%. The contribution of parameter uncertainties to model discrepancy was evaluated.     

Development and Application of the 2010 Chesapeake Bay Watershed Total Maximum Daily Load Model

The Phase 5.3 Watershed Model simulates the Chesapeake watershed land use, river flows, and the associated transport and fate of nutrient and sediment loads to the Chesapeake Bay. The Phase 5.3 Model is the most recent of a series of increasingly refined versions of a model that have been operational for more than two decades. The Phase 5.3 Model, in conjunction with models of the Chesapeake airshed and estuary, provides estimates of management actions needed to protect water quality, achieve Chesapeake water quality standards, and restore living resources. The Phase 5.3 Watershed Model tracks nutrient and sediment load estimates of the entire 166,000 km² watershed, including loads from all six watershed states. The creation of software systems, input datasets, and calibration methods were important aspects of the model development process. A community model approach was taken with model development and application, and the model was developed by a broad coalition of model practitioners including environmental engineers, scientists, and environmental managers. Among the users of the Phase 5.3 Model are the Chesapeake watershed states and local governments, consultants, river basin commissions, and universities. Development and application of the model are described, as well as key scenarios ranging from high nutrient and sediment load conditions if no management actions were taken in the watershed, to low load estimates of an all‐forested condition.     

Computing Atmospheric Nutrient Loads to the Chesapeake Bay Watershed and Tidal Waters

Application of integrated Chesapeake Bay models of the airshed, watershed, and estuary support air and water nitrogen controls in the Chesapeake. The models include an airshed model of the Mid‐Atlantic region which tracks the estimated atmospheric deposition loads of nitrogen to the watershed, tidal Bay, and adjacent coastal ocean. The three integrated models allow tracking of the transport and fate of nitrogen air emissions, including deposition in the Chesapeake watershed, the subsequent uptake, transformation, and transport to Bay tidal waters, and their ultimate influence on Chesapeake water quality. This article describes the development of the airshed model, its application to scenarios supporting the Chesapeake Total Maximum Daily Load (TMDL), and key findings from the scenarios. Key findings are that the atmospheric deposition loads are among the largest input loads of nitrogen in the watershed, and that the indirect nitrogen deposition loads to the watershed, which are subsequently delivered to the Bay are larger than the direct loads of atmospheric nitrogen deposition to Chesapeake tidal waters. Atmospheric deposition loads of nitrogen deposited in coastal waters, which are exchanged with the Chesapeake, are also estimated. About half the atmospheric deposition loads of nitrogen originate from outside the Chesapeake watershed. For the first time in a TMDL, the loads of atmospheric nitrogen deposition are an explicit part of the TMDL load reductions.     

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

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

Use of Hydrologic Landscape Classification to Diagnose Streamflow Predictability in Oregon

We implement a spatially lumped hydrologic model to predict daily streamflow at 88 catchments within the state of Oregon and analyze its performance using the Oregon Hydrologic Landscape (OHL) classification. OHL is used to identify the physio‐climatic conditions that favor high (or low) streamflow predictability. High prediction catchments (Nash‐Sutcliffe efficiency of (NS) > 0.75) are mainly classified as rain dominated with very wet climate, low aquifer permeability, and low to medium soil permeability. Most of them are located west of the Cascade Mountain Range. Conversely, most low prediction catchments (NS < 0.6) are classified as snow‐dominated with high aquifer permeability and medium to high soil permeability. They are mainly located in the volcano‐influenced High Cascades region. Using a subset of 36 catchments, we further test if class‐specific model parameters can be developed to predict at ungauged catchments. In most catchments, OHL class‐specific parameters provide predictions that are on par with individually calibrated parameters (NS decline < 10%). However, large NS declines are observed in OHL classes where predictability is not high enough. Results suggest higher uncertainty in rain‐to‐snow transition of precipitation phase and external gains/losses of deep groundwater are major factors for low prediction in Oregon. Moreover, regionalized estimation of model parameters is more useful in regions where conditions favor good streamflow predictability.     

STREAMFLOW TRENDS IN WISCONSIN'S DRIFTLESS AREA1

ABSTRACT: Trends in streamflow characteristics were analyzed for streams in southwestern Wisconsin's Driftless Area by using data at selected gaging stations. The analyses indicate that annual low flows have increased significantly, whereas annual flood peaks have decreased. The same trends were not observed for forested areas of northern Wisconsin. Streamflow trends for other streams in southeastern Wisconsin draining predominantly agricultural land were similar to trends for Driftless Area streams for annual low flows. The causes for the trends are not well understood nor are the effects. Trends in annual precipitation do not explain the observed trends in streamflow. Other studies have found that erosion rates decreased significantly in the Driftless Area, and have attributed this reduction to a change of agricultural practices, which increase infiltration, decrease flood peaks, and increase low flows.     

Towards Real‐Time Continental Scale Streamflow Simulation in Continuous and Discrete Space

The National Weather Service (NWS) forecasts floods at approximately 3,600 locations across the United States (U.S.). However, the river network, as defined by the 1:100,000 scale National Hydrography Dataset‐Plus (NHDPlus) dataset, consists of 2.7 million river segments. Through the National Flood Interoperability Experiment, a continental scale streamflow simulation and forecast system was implemented and continuously operated through the summer of 2015. This system leveraged the WRF‐Hydro framework, initialized on a 3‐km grid, the Routing Application for the Parallel Computation of Discharge river routing model, operating on the NHDPlus, and real‐time atmospheric forcing to continuously forecast streamflow. Although this system produced forecasts, this paper presents a study of the three‐month nowcast to demonstrate the capacity to seamlessly predict reach scale streamflow at the continental scale. In addition, this paper evaluates the impact of reservoirs, through a case study in Texas. Validation of the uncalibrated model using observed hourly streamflow at 5,701 U.S. Geological Survey gages shows 26% demonstrate PBias ≤ |25%|, 11% demonstrate Nash‐Sutcliffe Efficiency (NSE) ≥ 0.25, and 6% demonstrate both PBias ≤ |25%| and NSE ≥ 0.25. When evaluating the impact of reservoirs, the analysis shows when reservoirs are included, NSE ≥ 0.25 for 56% of the gages downstream while NSE ≥ 0.25 for 11% when they are not. The results presented here provide a benchmark for the evolving hydrology program within the NWS and supports their efforts to develop a reach scale flood forecasting system for the country.     

Sources of Suspended-Sediment Flux in Streams of the Chesapeake Bay Watershed: A Regional Application of the SPARROW Model1

Brakebill, John W., Scott W. Ator, and Gregory E. Schwarz, 2010. Sources of Suspended-Sediment Flux in Streams of the Chesapeake Bay Watershed: A Regional Application of the SPARROW Model. Journal of the American Water Resources Association (JAWRA) 46(4): 757-776. DOI: 10.1111/j.1752-1688.2010.00450.x Abstract: We describe the sources and transport of fluvial suspended sediment in nontidal streams of the Chesapeake Bay watershed and vicinity. We applied SPAtially Referenced Regressions on Watershed attributes, which spatially correlates estimated mean annual flux of suspended sediment in nontidal streams with sources of suspended sediment and transport factors. According to our model, urban development generates on average the greatest amount of suspended sediment per unit area (3,928 Mg/km²/year), although agriculture is much more widespread and is the greatest overall source of suspended sediment (57 Mg/km²/year). Factors affecting sediment transport from uplands to streams include mean basin slope, reservoirs, physiography, and soil permeability. On average, 59% of upland suspended sediment generated is temporarily stored along large rivers draining the Coastal Plain or in reservoirs throughout the watershed. Applying erosion and sediment controls from agriculture and urban development in areas of the northern Piedmont close to the upper Bay, where the combined effects of watershed characteristics on sediment transport have the greatest influence may be most helpful in mitigating sedimentation in the bay and its tributaries. Stream restoration efforts addressing floodplain and bank stabilization and incision may be more effective in smaller, headwater streams outside of the Coastal Plain.     

The Shallow‐Water Component of the Chesapeake Bay Environmental Model Package

The shallow‐water component of the Chesapeake Bay Environmental Model Package emphasizes the regions of the system inside the 2‐m depth contour. The model of these regions is unified with the system‐wide model but places emphasis on locally significant components and processes, notably submerged aquatic vegetation (SAV), sediment resuspension, and their interaction with light attenuation (Ke). The SAV model is found to be most suited for computing the equilibrium distribution of perennial species. Addition of plant structure and propagation are recommended to improve representation of observed trends in SAV area. Two approaches are taken to examining shallow‐water Ke. The first compares observed and computed differences between deep‐ and shallow‐water Ke. No consistent difference in observations is noted. In the preponderance of regions examined, computed shallow‐water Ke exceeds computed deep‐water Ke. The second approach directly compares Ke measured in shallow water with modeled results. Model values are primarily lower than observed, in contrast to results in deep water where model values exceed observed. The shortfall in computed Ke mirrors a similar shortfall in computed suspended solids. Improved model representation of Ke requires process‐based investigations into suspended solids dynamics as well as increased model resolution in shallow‐water regions.     

Temporal Changes in Streamflow and Attribution of Changes to Climate and Landuse in Wisconsin Watersheds

Previous historic trends analyses on 21st Century hydrologic data in the United States generally focus on annual flow statistics and have continued to use USGS hydro‐climatic data network (HCDN) stations, although post‐1988 diversions and runoff regulations are not reflected in the HCDN. Using a more recent dataset, Geospatial Attributes of Gages for Evaluating Streamflow, version II (GAGES II), compiled by Falcone (2012), which includes more watersheds with reference conditions, a comprehensive analysis of changes in seasonal, and annual streamflow in Wisconsin watersheds is demonstrated. Given the pronounced influence of seasonal hydrology in Wisconsin watersheds, the objective of this study is to elucidate the nature of temporal (annual, seasonal, and monthly) changes in runoff. Considerable temporal and regional variability was found in annual and seasonal streamflow changes between the two historic periods 1951‐1980 and 1981‐2010 considered in the study. For example, the northern watersheds show relatively small changes in streamflow discharge ranging from ?6.0 to 4.2%, while the southern watersheds show relatively large increases in streamflow discharge ranging from 13.1 to 18.2%. To apportion streamflow changes to climate and nonclimatic factors, a method based on potential evapotranspiration changes is demonstrated. Results show that nonclimatic factors account for more than 60% of changes in annual runoff in Wisconsin watersheds considered in the study.     

Water Quality Functions of Riparian Forest Buffers in Chesapeake Bay Watersheds

/ Maryland, Virginia, and Pennsylvania, USA, have agreed to reduce nutrient loadings to Chesapeake Bay by 40% by the year 2000. This requires control of nonpoint sources of nutrients, much of which comes from agriculture. Riparian forest buffer systems (RFBS) provide effective control of nonpoint source (NPS) pollution in some types of agricultural watersheds. Control of NPS pollution is dependent on the type of pollutant and the hydrologic connection between pollution sources, the RFBS, and the stream. Water quality improvements are most likely in areas of where most of the excess precipitation moves across, in, or near the root zone of the RFBS. In areas such as the Inner Coastal Plain and Piedmont watersheds with thin soils, RFBS should retain 50%-90% of the total loading of nitrate in shallow groundwater, sediment in surface runoff, and total N in both surface runoff and groundwater. Retention of phosphorus is generally much less. In regions with deeper soils and/or greater regional groundwater recharge (such as parts of the Piedmont and the Valley and Ridge), RFBS water quality improvements are probably much less. The expected levels of pollutant control by RFBS are identified for each of nine physiographic provinces of the Chesapeake Bay Watershed. Issues related to of establishment, sustainability, and management are also discussed.KEY WORDS: Riparian forest buffers; Chesapeake Bay; Nonpoint source pollution; Nitrogen; Phosphorus; Sediment     

Changes in Patterns of Streamflow From Unregulated Watersheds in Idaho,Western Wyoming,and Northern Nevada1

Clark, Gregory M., 2010. Changes in Patterns of Streamflow From Unregulated Watersheds in Idaho, Western Wyoming, and Northern Nevada. Journal of the American Water Resources Association (JAWRA) 46(3):486-497. DOI: 10.1111/j.1752-1688.2009.00416.x Abstract: Recent studies have identified a pattern of earlier spring runoff across much of North America. Earlier spring runoff potentially poses numerous problems, including increased risk of flooding and reduced summer water supply for irrigation, power generation, and migratory fish passage. To identify changing runoff patterns in Idaho streams, streamflow records were analyzed for 26 U.S. Geological Survey gaging stations in Idaho, western Wyoming, and northern Nevada, each with a minimum of 41 years of record. The 26 stations are located on 23 unregulated and relatively pristine streams that drain areas ranging from 28 to >35,000 km². Four runoff parameters were trend tested at each station for both the period of historical record and from 1967 through 2007. Parameters tested were annual mean streamflow, annual minimum daily streamflow, and the dates of the 25th and 50th percentiles of the annual total streamflow. Results of a nonparametric Mann-Kendall trend test revealed a trend toward lower annual mean and annual minimum streamflows at a majority of the stations, as well as a trend toward earlier snowmelt runoff. Significant downward trends over the period of historical record were most prevalent for the annual minimum streamflow (12 stations) and the 50th percentile of streamflow (11 stations). At most stations, trends were more pronounced during the period from 1967 through 2007. A regional Kendall test for water years 1967 through 2007 revealed significant regional trends in the percent change in the annual mean and annual minimum streamflows (0.67% less per year and 0.62% less per year, respectively), the 25th percentile of streamflow (12.3 days earlier), and the 50th percentile of streamflow (11.5 days earlier).     

Estimating Lag to Peak between Rainfall and Peak Streamflow with a Mixed‐Effects Model

We test the use of a mixed‐effects model for estimating lag to peak for small basins in Maine (drainage areas from 0.8 to 78 km²). Lag to peak is defined as the time between the center of volume of the excess rainfall during a storm event and the resulting peak streamflow. A mixed‐effects model allows for multiple observations at sites without violating model assumptions inherent in traditional ordinary least squares models, which assume each observation is independent. The mixed model includes basin drainage area and maximum 15‐min rainfall depth for individual storms as explanatory features. Based on a remove‐one‐site cross‐validation analysis, the prediction errors of this model ranged from ?42% to +73%. The mixed model substantially outperformed three published models for lag to peak and one published model for centroid lag for estimating lag to peak for small basins in Maine. Lag to peak estimates are a key input to rainfall–runoff models used to design hydraulic infrastructure. The improved accuracy and consistency with model assumptions indicates that mixed models may provide increased data utilization that could enhance models and estimates of lag to peak in other regions.     

Daily Updating of Operational Statistical Seasonal Water Supply Forecasts for the western U.S.1

Abstract: Official seasonal water supply outlooks for the western United States are typically produced once per month from January through June. The Natural Resources Conservation Service has developed a new outlook product that allows the automated production and delivery of this type of forecast year‐round and with a daily update frequency. Daily snow water equivalent and water year‐to‐date precipitation data from multiple SNOTEL stations are combined using a statistical forecasting technique (“Z‐Score Regression”) to predict seasonal streamflow volume. The skill of these forecasts vs. lead‐time is comparable to the official published outlooks. The new product matches the intra‐monthly trends in the official forecasts until the target period is partly in the past, when the official forecasts begin to use information about observed streamflows to date. Geographically, the patterns of skill also match the official outlooks, with highest skill in Idaho and southern Colorado and lowest skill in the Colorado Front Range, eastern New Mexico, and eastern Montana. The direct and frequent delivery of objective guidance to users is a significant new development in the operational hydrologic seasonal forecasting community.     

Twenty‐One‐Year Simulation of Chesapeake Bay Water Quality Using the CE‐QUAL‐ICM Eutrophication Model

The CE‐QUAL‐ICM (Corps of Engineers Integrated Compartment Water Quality Model) eutrophication model was applied in a 21‐year simulation of Chesapeake Bay water quality, 1985‐2005. The eutrophication model is part of a larger model package and is forced, in part, by models of atmospheric deposition, watershed flows and loads, and hydrodynamics. Results from the model are compared with observations in multiple formats including time series plots, cumulative distribution plots, and statistical summaries. The model indicates only one long‐term trend in computed water quality: light attenuation deteriorates circa 1993 through the end of the simulation. The most significant result is the influence of physical processes, notably stratification and associated effects (e.g., anoxic volume), on computed water quality. Within the application period, physical effects are more important determinants of year‐to‐year variability in computed water quality than external loads.     

A Streamflow Forecasting Framework using Multiple Climate and Hydrological Models1

Abstract: Water resources planning and management efficacy is subject to capturing inherent uncertainties stemming from climatic and hydrological inputs and models. Streamflow forecasts, critical in reservoir operation and water allocation decision making, fundamentally contain uncertainties arising from assumed initial conditions, model structure, and modeled processes. Accounting for these propagating uncertainties remains a formidable challenge. Recent enhancements in climate forecasting skill and hydrological modeling serve as an impetus for further pursuing models and model combinations capable of delivering improved streamflow forecasts. However, little consideration has been given to methodologies that include coupling both multiple climate and multiple hydrological models, increasing the pool of streamflow forecast ensemble members and accounting for cumulative sources of uncertainty. The framework presented here proposes integration and offline coupling of global climate models (GCMs), multiple regional climate models, and numerous water balance models to improve streamflow forecasting through generation of ensemble forecasts. For demonstration purposes, the framework is imposed on the Jaguaribe basin in northeastern Brazil for a hindcast of 1974‐1996 monthly streamflow. The ECHAM 4.5 and the NCEP/MRF9 GCMs and regional models, including dynamical and statistical models, are integrated with the ABCD and Soil Moisture Accounting Procedure water balance models. Precipitation hindcasts from the GCMs are downscaled via the regional models and fed into the water balance models, producing streamflow hindcasts. Multi‐model ensemble combination techniques include pooling, linear regression weighting, and a kernel density estimator to evaluate streamflow hindcasts; the latter technique exhibits superior skill compared with any single coupled model ensemble hindcast.     

Response of Nitrogen Loading to the Chesapeake Bay to Source Reduction and Land Use Change Scenarios: A SPARROW‐Informed Analysis

In response to concerns regarding the health of streams and receiving waters, the United States Environmental Protection Agency established a total maximum daily load for nitrogen in the Chesapeake Bay watershed for which practices must be in place by 2025 resulting in an expected 25% reduction in load from 2009 levels. The response of total nitrogen (TN) loads delivered to the Bay to nine source reduction and land use change scenarios was estimated using a Spatially Referenced Regression on Watershed Attributes model. The largest predicted reduction in TN load delivered to the Bay was associated with a scenario in which the mass of TN as fertilizer applied to agricultural lands was decreased. A 25% decrease in the mass of TN applied as fertilizer resulted in a predicted reduction in TN loading to the Bay of 11.3%, which was 2.5–5 times greater than the reductions predicted by other scenarios. Eliminating fertilizer application to all agricultural land in the watershed resulted in a predicted reduction in TN load to the Bay of 45%. It was estimated that an approximate 25% reduction in TN loading to the Bay could be achieved by eliminating fertilizer applied to the 7% of subwatersheds contributing the greatest fertilizer‐sourced TN loads to the Bay. These results indicate that management strategies aimed at decreasing loading from a small number of subwatersheds may be effective for reducing TN loads to the Bay, and similar analyses are possible in other watersheds.     

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.