Annual Estimates of Recharge,Quick‐Flow Runoff,and Evapotranspiration for the Contiguous U.S. Using Empirical Regression Equations

This study presents new data‐driven, annual estimates of the division of precipitation into the recharge, quick‐flow runoff, and evapotranspiration (ET) water budget components for 2000‐2013 for the contiguous United States (CONUS). The algorithms used to produce these maps ensure water budget consistency over this broad spatial scale, with contributions from precipitation influx attributed to each component at 800 m resolution. The quick‐flow runoff estimates for the contribution to the rapidly varying portion of the hydrograph are produced using data from 1,434 gaged watersheds, and depend on precipitation, soil saturated hydraulic conductivity, and surficial geology type. Evapotranspiration estimates are produced from a regression using water balance data from 679 gaged watersheds and depend on land cover, temperature, and precipitation. The quick‐flow and ET estimates are combined to calculate recharge as the remainder of precipitation. The ET and recharge estimates are checked against independent field data, and the results show good agreement. Comparisons of recharge estimates with groundwater extraction data show that in 15% of the country, groundwater is being extracted at rates higher than the local recharge. These maps of the internally consistent water budget components of recharge, quick‐flow runoff, and ET, being derived from and tested against data, are expected to provide reliable first‐order estimates of these quantities across the CONUS, even where field measurements are sparse.     

Effects of Land‐Use and Land‐Cover Change on Evapotranspiration and Water Yield in China During 1900‐20001

Abstract: China has experienced a rapid land‐use/cover change (LUCC) during the 20th Century, and this process is expected to continue in the future. How LUCC has affected water resources across China, however, remains uncertain due to the complexity of LUCC‐water interactions. In this study, we used an integrated Dynamic Land Ecosystem Model (DLEM) in conjunction with spatial data of LUCC to estimate the LUCC effects on the magnitude, spatial and temporal variations of evapotranspiration (ET), runoff, and water yield across China. Through comparisons of DLEM results with other model simulations, field observations, and river discharge data, we found that DLEM model can adequately catch the spatial and seasonal patterns of hydrological processes. Our simulation results demonstrate that LUCC led to substantial changes in ET, runoff, and water yield in most of the China’s river basins during the 20th Century. The temporal and spatial patterns varied significantly across China. The largest change occurred during the second half century when almost all of the river basins had a decreasing trend in ET and an increasing trend in water yield and runoff, in contrast to the inclinations of ET and declinations of water yield in major river basins, such as Pearl river basin, Yangtze river basin, and Yellow river basin during the first half century. The increased water yield and runoff indicated alleviated water deficiency in China in the late 20th Century, but the increased peak flow might make the runoff difficult to be held by reservoirs. The continuously increasing ET and decreasing water yield in Continental river basin, Southwest river basin, and Songhua and Liaohe river basin implied regional water deficiency. Our study in China indicates that deforestation averagely increased ET by 138 mm/year but decreased water yield by the same amount and that reforestation averagely decreased ET by 422 mm/year since most of deforested land was converted to paddy land or irrigated cropland. In China, cropland‐related land transformation is the dominant anthropogenic force affecting water resources during the 20th Century. On national average, cropland expansion was estimated to increase ET by 182 mm/year while cropland abandonment decreased ET by 379 mm/year. Our simulation results indicate that urban sprawl generally decreased ET and increased water yield. Cropland managements (fertilization and irrigation) significantly increased ET by 98 mm/year. To better understand LUCC effects on China’s water resources, it is needed to take into account the interactions of LUCC with other environmental changes such as climate and atmospheric composition.     

Estimating Evapotranspiration for Dryland Cropping Systems in the Semiarid Texas High Plains Using SWAT

The Soil and Water Assessment Tool (SWAT) is one of the most widely used watershed models for simulating hydrology in response to agricultural management practices. However, limited studies have been performed to evaluate the SWAT model's ability to estimate daily and monthly evapotranspiration (ET) in semiarid regions. ET values were simulated using ArcSWAT 2012 for a lysimeter field managed under dryland conditions at the USDA‐ARS Conservation and Production Research Laboratory at Bushland, Texas, and compared with measured lysimeter values from 2000 to 2010. Two scenarios were performed to compare SWAT's performance: (1) use of default plant leaf area index (LAI) values in the embedded plant database and (2) adjusted LAI values. Scenario 1 resulted in an “unsatisfactory” Nash‐Sutcliffe efficiency (NSE) of 0.42 and 0.38 for the calibration and validation periods, respectively. Scenario 2 resulted in a “satisfactory” NSE value for the calibration period while achieving a “good” NSE of 0.70 for the validation period. SWAT generally underestimated ET at both the daily and monthly levels. Overestimation during fallow years may be due to the limitations of the pothole function used to simulate furrow diking. Users should be aware of potential errors associated with using default LAI parameters. Inaccuracies in ET estimation may also stem from errors in the plant stress functions, particularly when evaluating water management practices for dryland watersheds.     

Modeling the Spatially Varying Water Balance Processes in a Semiarid Mountainous Watershed of Idaho1

Stratton, Benjamin T., Venakataramana Sridhar, Molly M. Gribb, James P. McNamara, and Balaji Narasimhan, 2009. Modeling the Spatially Varying Water Balance Processes in a Semiarid Mountainous Watershed of Idaho. Journal of the American Water Resources Association (JAWRA) 45(6):1390‐1408. Abstract: The distributed Soil Water Assessment Tool (SWAT) hydrologic model was applied to a research watershed, the Dry Creek Experimental Watershed, near Boise Idaho to investigate its water balance components both temporally and spatially. Calibrating and validating SWAT is necessary to enable our understanding of the water balance components in this semiarid watershed. Daily streamflow data from four streamflow gages were used for calibration and validation of the model. Monthly estimates of streamflow during the calibration phase by SWAT produced satisfactory results with a Nash Sutcliffe coefficient of model efficiency 0.79. Since it is a continuous simulation model, as opposed to an event‐based model, it demonstrated the limited ability in capturing both streamflow and soil moisture for selected rain‐on‐snow (ROS) events during the validation period between 2005 and 2007. Especially, soil moisture was generally underestimated compared with observations from two monitoring pits. However, our implementation of SWAT showed that seasonal and annual water balance partitioning of precipitation into evapotranspiration, streamflow, soil moisture, and drainage was not only possible but closely followed the trends of a typical semiarid watershed in the intermountain west. This study highlights the necessity for better techniques to precisely identify and drive the model with commonly observed climatic inversion‐related snowmelt or ROS weather events. Estimation of key parameters pertaining to soil (e.g., available water content and saturated hydraulic conductivity), snow (e.g., lapse rates, melting), and vegetation (e.g., leaf area index and maximum canopy index) using additional field observations in the watershed is critical for better prediction.     

Watershed Evapotranspiration Increased due to Changes in Vegetation Composition and Structure Under a Subtropical Climate1

Abstract: Natural forests in southern China have been severely logged due to high human demand for timber, food, and fuels during the past century, but are recovering in the past decade. The objective of this study was to investigate how vegetation cover changes in composition and structure affected the water budgets of a 9.6‐km² Dakeng watershed located in a humid subtropical mountainous region in southern China. We analyzed 27 years (i.e., 1967‐1993) of streamflow and climate data and associated vegetation cover change in the watershed. Land use/land cover census and Normalized Difference of Vegetation Index (NDVI) data derived from remote sensing were used to construct historic land cover change patterns. We found that over the period of record, annual streamflow (Q) and runoff/precipitation ratio did not change significantly, nor did the climatic variables, including air temperature, Hamon’s potential evapotranspiration (ET), pan evaporation, sunshine hours, and radiation. However, annual ET estimated as the differences between P and Q showed a statistically significant increasing trend. Overall, the NDVI of the watershed had a significant increasing trend in the peak spring growing season. This study concluded that watershed ecosystem ET increased as the vegetation cover shifted from low stock forests to shrub and grasslands that had higher ET rates. A conceptual model was developed for the study watershed to describe the vegetation cover‐streamflow relationships during a 50‐year time frame. This paper highlighted the importance of eco‐physiologically based studies in understanding transitory, nonstationary effects of deforestation or forestation on watershed water balances.     

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.     

Spatiotemporal Evaluation of Simulated Evapotranspiration and Streamflow over Texas Using the WRF‐Hydro‐RAPID Modeling Framework

This study assesses a large‐scale hydrologic modeling framework (WRF‐Hydro‐RAPID) in terms of its high‐resolution simulation of evapotranspiration (ET) and streamflow over Texas (drainage area: 464,135 km²). The reference observations used include eight‐day ET data from MODIS and FLUXNET, and daily river discharge data from 271 U.S. Geological Survey gauges located across a climate gradient. A recursive digital filter is applied to decompose the river discharge into surface runoff and base flow for comparison with the model counterparts. While the routing component of the model is pre‐calibrated, the land component is uncalibrated. Results show the model performance for ET and runoff is aridity‐dependent. ET is better predicted in a wet year than in a dry year. Streamflow is better predicted in wet regions with the highest efficiency ~0.7. In comparison, streamflow is most poorly predicted in dry regions with a large positive bias. Modeled ET bias is more strongly correlated with the base flow bias than surface runoff bias. These results complement previous evaluations by incorporating more spatial details. They also help identify potential processes for future model improvements. Indeed, improving the dry region streamflow simulation would require synergistic enhancements of ET, soil moisture and groundwater parameterizations in the current model configuration. Our assessments are important preliminary steps towards accurate large‐scale hydrologic forecasts.     

Streamflow Changes in the South Atlantic,United States During the Mid‐ and Late 20th Century1

Abstract: Repeated severe droughts over the last decade in the South Atlantic have raised concern that streamflow may be systematically decreasing, possibly due to climate variability. We examined the monthly and annual trends of streamflow, precipitation, and temperature in the South Atlantic for the time periods: 1934‐2005, 1934‐1969, and 1970‐2005. Streamflow and climate (temperature and precipitation) trends transitioned ca. 1970. From 1934 to 1969, streamflow and precipitation increased in southern regions and decreased in northern regions; temperature decreased throughout the South Atlantic. From 1970 to 2005, streamflow decreased, precipitation decreased, and temperature increased throughout the South Atlantic. It is unclear whether these will be continuing trends or simply part of a long‐term climatic oscillation. Whether these streamflow trends have been driven by climatic or anthropogenic changes, water resources management faces challenging prospects to adapt to decadal‐scale persistently wet and dry hydrologic conditions.     

A Hydrologic Drying Bias in Water‐Resource Impact Analyses of Anthropogenic Climate Change

For water‐resource planning, sensitivity of freshwater availability to anthropogenic climate change (ACC) often is analyzed with “offline” hydrologic models that use precipitation and potential evapotranspiration (E_p) as inputs. Because E_p is not a climate‐model output, an intermediary model of E_p must be introduced to connect the climate model to the hydrologic model. Several E_p methods are used. The suitability of each can be assessed by noting a credible E_p method for offline analyses should be able to reproduce climate models’ ACC‐driven changes in actual evapotranspiration in regions and seasons of negligible water stress (E_w). We quantified this ability for seven commonly used E_p methods and for a simple proportionality with available energy (“energy‐only” method). With the exception of the energy‐only method, all methods tend to overestimate substantially the increase in E_p associated with ACC. In an offline hydrologic model, the E_p‐change biases produce excessive increases in actual evapotranspiration (E), whether the system experiences water stress or not, and thence strong negative biases in runoff change, as compared to hydrologic fluxes in the driving climate models. The runoff biases are comparable in magnitude to the ACC‐induced runoff changes themselves. These results suggest future hydrologic drying (wetting) trends likely are being systematically and substantially overestimated (underestimated) in many water‐resource impact analyses.     

Error Autocorrelation and Linear Regression for Temperature‐Based Evapotranspiration Estimates Improvement1

Medeiros, Patrick Valverde, Francisco Fernando Noronha Marcuzzo, Cristián Youlton, and Edson Wendland, 2012. Error Autocorrelation and Linear Regression for Temperature‐Based Evapotranspiration Estimates Improvement. Journal of the American Water Resources Association (JAWRA) 48(2): 297‐305. DOI: 10.1111/j.1752‐1688.2011.00614.x Abstract: Estimates of evapotranspiration on a local scale is important information for agricultural and hydrological practices. However, equations to estimate potential evapotranspiration based only on temperature data, which are simple to use, are usually less trustworthy than the Food and Agriculture Organization (FAO)‐Penman‐Monteith standard method. The present work describes two correction procedures for potential evapotranspiration estimates by temperature, making the results more reliable. Initially, the standard FAO‐Penman‐Monteith method was evaluated with a complete climatologic data set for the period between 2002 and 2006. Then temperature‐based estimates by Camargo and Jensen‐Haise methods have been adjusted by error autocorrelation evaluated in biweekly and monthly periods. In a second adjustment, simple linear regression was applied. The adjusted equations have been validated with climatic data available for the Year 2001. Both proposed methodologies showed good agreement with the standard method indicating that the methodology can be used for local potential evapotranspiration estimates.     

Effects of Rainfall and Ground‐Water Pumping on Streamflow in Mākaha,O’ahu,Hawai’i1

Abstract: Land‐use/land‐cover changes in Mākaha valley have included the development of agriculture, residential dwellings, golf courses, potable water supply facilities, and the introduction of alien species. The impact of these changes on surface water and ground water resources in the valley is of concern. In this study, streamflow, rainfall, and ground‐water pumping data for the upper part of the Mākaha valley watershed were evaluated to identify corresponding trends and relationships. The results of this study indicate that streamflow declined during the ground‐water pumping period. Mean and median annual streamflow have declined by 42% (135 mm) and 56% (175 mm), respectively, and the mean number of dry stream days per year has increased from 8 to 125. Rainfall across the study area appears to have also declined though it is not clear whether the reduction in rainfall is responsible for all or part of the observed streamflow decline. Mean annual rainfall at one location in the study area declined by 14% (179 mm) and increased by 2% (48 mm) at a second location. Further study is needed to assess the effect of ground‐water pumping and to characterize the hydrologic cycle with respect to rainfall, infiltration, ground‐water recharge and flow in the study area, and stream base flow and storm flow.     

Evaluating The National Land Cover Database Tree Canopy and Impervious Cover Estimates Across the Conterminous United States: A Comparison with Photo-Interpreted Estimates

The 2001 National Land Cover Database (NLCD) provides 30-m resolution estimates of percentage tree canopy and percentage impervious cover for the conterminous United States. Previous estimates that compared NLCD tree canopy and impervious cover estimates with photo-interpreted cover estimates within selected counties and places revealed that NLCD underestimates tree and impervious cover. Based on these previous results, a wall-to-wall comprehensive national analysis was conducted to determine if and how NLCD derived estimates of tree and impervious cover varies from photo-interpreted values across the conterminous United States. Results of this analysis reveal that NLCD significantly underestimates tree cover in 64 of the 65 zones used to create the NCLD cover maps, with a national average underestimation of 9.7% (standard error (SE) = 1.0%) and a maximum underestimation of 28.4% in mapping zone 3. Impervious cover was also underestimated in 44 zones with an average underestimation of 1.4% (SE = 0.4%) and a maximum underestimation of 5.7% in mapping zone 56. Understanding the degree of underestimation by mapping zone can lead to better estimates of tree and impervious cover and a better understanding of the potential limitations associated with NLCD cover estimates.     

A New Open‐Access HUC‐8 Based Downscaled CMIP‐5 Climate Model Forecast Dataset for the Conterminous United States

Watershed‐scale hydrologic simulation models generally require climate data inputs including precipitation and temperature. These climate inputs can be derived from downscaled global climate simulations which have the potential to drive runoff forecasts at the scale of local watersheds. While a simulation designed to drive a local watershed model would ideally be constructed at an appropriate scale, global climate simulations are, by definition, arbitrarily determined large rectangular spatial grids. This paper addresses the technical challenge of making climate simulation model results readily available in the form of downscaled datasets that can be used for watershed scale models. Specifically, we present the development and deployment of a new Coupled Model Intercomparison Project phase 5 (CMIP5) based database which has been prepared through a scaling and weighted averaging process for use at the level of U.S. Geological Survey (USGS) Hydrologic Unit Code (HUC)‐8 watersheds. The resulting dataset includes 2,106 virtual observation sites (watershed centroids) each with 698 associated time series datasets representing average monthly temperature and precipitation between 1950 and 2099 based on 234 unique climate model simulations. The new dataset is deployed on a HydroServer and distributed using WaterOneFlow web services in the WaterML format. These methods can be adapted for downscaled General Circulation Model (GCM) results for specific drainage areas smaller than HUC‐8. Two example use cases for the dataset also are presented.     

Assessing Satellite and Ground‐Based Potential Evapotranspiration for Hydrologic Applications in the Colorado River Basin

This study evaluates a remotely sensed and two ground‐based potential evapotranspiration (PET) products for hydrologic application in the Upper Colorado River Basin (UCRB). The remotely sensed Moderate Resolution Imaging Spectroradiometer product (MODIS‐PET) is a continuous, daily time series with 250 m resolution derived using the Priestley‐Taylor (P‐T) equation. The MODIS‐PET is evaluated against regional flux tower data as well as a synthetic pan product (Epan; 0.125°, daily) derived from the North American Land Data Assimilation System (NLDAS) and a Hargreaves PET derived from DAYMET variables (DAYMET‐PET; 1 km, daily). Compared to point‐scale PET computed using regional flux tower data, the MODIS‐PET had lower errors, with RMSE values ranging from 2.24 to 2.85 mm/day. Epan RMSE values ranged from 3.70 to 3.76 mm/day and DAYMET‐PET RMSE values ranged from 3.55 to 4.58 mm/day. Further investigation showed biases in temperature and radiation data contribute to uncertainty in the MODIS‐PET values, while bias in NLDAS temperature, downward shortwave (SW↓), and downward longwave (LW↓) propagate in the Epan estimates. Larger discrepancies between methods were observed in the warmer, drier regions of the UCRB, however, the MODIS‐PET was more responsive to landcover transitions and better captured basin heterogeneity. Results indicate the satellite‐based MODIS product can serve as a viable option for obtaining spatial PET values across the UCRB.     

Projections of 21st Century Sierra Nevada Local Hydrologic Flow Components Using an Ensemble of General Circulation Models1

Abstract: Sierra Nevada snowmelt and runoff is a key source of water for many of California’s 38 million residents and nearly the entire population of western Nevada. The purpose of this study was to assess the impacts of expected 21st Century climatic changes in the Sierra Nevada at the subwatershed scale, for all hydrologic flow components, and for a suite of 16 General Circulation Models (GCMs) with two emission scenarios. The Soil and Water Assessment Tool (SWAT) was calibrated and validated at 35 unimpaired streamflow sites. Results show that temperatures are projected to increase throughout the Sierra Nevada, whereas precipitation projections vary between GCMs. These climatic changes drive a decrease in average annual streamflow and an advance of snowmelt and runoff by several weeks. The largest streamflow reductions were found in the mid‐range elevations due to less snow accumulation, whereas the higher elevation watersheds were more resilient due to colder temperatures. Simulation results showed that decreases in snowmelt affects not only streamflow, but evapotranspiration, surface, and subsurface flows, such that less water is available in spring and summer, thus potentially affecting aquatic and terrestrial ecosystems. Declining spring and summer flows did not equally affect all subwatersheds in the region, and the subwatershed perspective allowed for identification for the most sensitive basins throughout the Sierra Nevada.     

Heterogeneity of Hydrologic Response in Urban Watersheds1

Meierdiercks, Katherine L., James A. Smith, Mary Lynn Baeck, and Andrew J. Miller, 2010. Heterogeneity of Hydrologic Response in Urban Watersheds. Journal of the American Water Resources Association (JAWRA) 46(6):1221–1237. DOI: 10.1111/j.1752-1688.2010.00487.x Abstract: The changing patterns of streamflow associated with urbanization are examined through analyses of discharge and rainfall records for the study watersheds of the Baltimore Ecosystem Study (BES). Analyses utilize a decade (1999-2008) of observations from a dense U.S. Geological Survey stream gaging network and Hydro-NEXRAD radar rainfall fields. The principal study watershed of the BES is Gwynns Falls (171 km²). Focus is given to two Gwynns Falls basins with contrasting patterns and histories of development, Dead Run and Upper Gwynns Falls. The sharp contrasts in streamflow properties between the basins reflect the differences in urban development prior to implementation of stormwater management regulations (much of Dead Run) and development for which stormwater management is an integral part of the hydrologic system (Upper Gwynns Falls). The mean annual runoff in Dead Run (558 mm) is 35% larger than that of Upper Gwynns Falls; larger contrasts in runoff properties typify the “warm season” and are linked to storm event hydrologic response. Spatial heterogeneities in storm event response are reflected in seasonal and diurnal properties of streamflow. Analyses of storm event response are presented for June 2006, during which monthly rainfall over the BES region ranged from less than 150 to more than 500 mm. Baisman Run, the BES forest reference watershed, and Moores Run, a highly urbanized watershed in Baltimore City, provide “end-member” representations of urban impacts on streamflow.     

Relationship of Land‐Use/Land‐Cover Patterns and Surface‐Water Quality in The Mullica River Basin1

Abstract: We describe relationships between pH, specific conductance, calcium, magnesium, chloride, sulfate, nitrogen, and phosphorus and land‐use patterns in the Mullica River basin, a major New Jersey Pinelands watershed, and determine the thresholds at which significant changes in water quality occur. Nonpoint sources are the main contributors of pollutants to surface waters in the basin. Using multiple regression and water‐quality data for 25 stream sites, we determine the percentage of variation in the water‐quality data explained by urban land and upland agriculture and evaluate whether the proximity of these land uses influences water‐quality/land‐use relationships. We use a second, independently collected water‐quality dataset to validate the statistical models. The multiple‐regression results indicate that water‐quality degradation in the study area is associated with basin‐wide upland land uses, which are generally good predictors of water‐quality conditions, and that both urban land and upland agriculture must be included in models to more fully describe the relationship between watershed disturbance and water quality. Including the proximity of land uses did not improve the relationship between land use and water quality. Ten‐percent altered‐land cover in a basin represents the threshold at which a significant deviation from reference‐site water‐quality conditions occurs in the Mullica River basin.     

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

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

Automated Calibration of the METRIC‐Landsat Evapotranspiration Process

A remaining challenge to applying satellite‐based energy‐balance algorithms for operational estimation of evapotranspiration (ET) is the calibration of the energy‐balance model. Customized calibration for each image date is generally required to overcome biases associated with radiometric accuracy of the image, uncertainties in aerodynamic features of the landscape, background thermal conditions, and model assumptions. The CIMEC process (calibration using inverse modeling at extreme conditions) is an endpoint calibration procedure where near extreme conditions in the image are identified where the ET can be estimated and assigned. In the Mapping EvapoTranspiration at high Resolution with Internalized Calibration (METRIC?) energy‐balance model, two endpoints represent the dry and wet ends of the ET spectrum. Generally, user‐intervention is required to select locations in the image to produce best accuracy. To bring the METRIC and similar processes into the domain of less experienced operators, a consistent, reproducible, and dependable statistics‐based procedure is introduced where relationships between vegetation amount and surface temperature are used to identify a subpopulation of locations (pixels) in an image that may best represent the calibration endpoints. This article describes the background and logic for the statistical approach, how the statistics were developed, area of interest requirements and assumptions, adjustment for dry conditions in desert climates, and implementation in a common image processing environment (ERDAS Imagine).     

Precipitation as the Primary Driver of Variability in River Nitrogen Loads in the Midwest United States

Nitrogen (N) losses from agricultural lands in the Midwest United States are contributing to the expansion of the hypoxic zone in the Gulf of Mexico. This study evaluated the importance of inter‐annual variability in precipitation, land cover, and N fertilizer use on NO₃ + NO₂‐N loads in seven United States Midwestern Rivers using the backward stepwise regression analysis. At the annual scale, fluctuations in the current and previous years’ precipitations explained much of the variation in streamflow, baseflow, and N‐load. Previous years precipitation effects were associated with fillable soil porosity. In some years, higher residual soil N from previous dry years also contributed to an increase in N‐load. Area under soybean production (SOY), a surrogate for replacement of prairies and small grains was generally not a significant explanatory variable. Fertilizer use from 1987 to 2012 was also not a significant explanatory variable in the annual analysis. Precipitation in both the current and previous months and previous year were important in explaining variation in monthly streamflow, baseflow, and N‐load. SOY was significant in one or two months from June to August, but had a higher p‐value than precipitation. We conclude recent increases in river N‐loads are primarily due to wet climate and minimally due to the changes in land cover or N fertilizer use. Under current cropping systems and agronomic N application rates, tile water remediation will be necessary to reduce river N‐loads.