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Simulation of runoff and recharge and estimation of constituent loads in runoff, Edwards aquifer recharge zone (outcrop) and catchment area, Bexar County, Texas, 1997-2000

The U.S. Geological Survey developed a watershed model (Hydrological Simulation Program—FORTRAN) to simulate runoff and recharge and to estimate constituent loads in surface-water runoff in the Edwards aquifer recharge zone (outcrop) and catchment area in Bexar County, Texas. Rainfall and runoff data collected during 1970–98 from four gaged basins in the outcrop and catchment area were used to calibrate and test the model. The calibration parameters were applied in simulations of the four calibration basins and six ungaged basins that compose the study area to obtain runoff and recharge volumes for 4 years, 1997–2000. In 1997, simulated runoff from the study area was 5.62 inches. Simulated recharge in the study area was 7.85 inches (20 percent of rainfall). In 1998, simulated runoff was 11.05 inches; simulated recharge was 10.99 inches (25 percent of rainfall). In 1999, simulated runoff was 0.66 inch; simulated recharge was 3.03 inches (19 percent of rainfall). In 2000, simulated runoff was 5.29 inches; simulated recharge was 7.19 inches (21 percent of rainfall). During 1997– 2000, direct infiltration of rainfall accounted for about 56 percent of the total Edwards aquifer recharge in Bexar County. Streamflow losses contributed about 37 percent of the recharge; flood impoundment contributed 7 percent. The simulated runoff volumes were used with event-mean-concentration data from basins in the study area and from other Bexar County basins to compute constituent loads and yields for various land uses. Annual loads for suspended solids, dissolved solids, dissolved nitrite plus nitrate nitrogen, and total lead were consistently largest from undeveloped land and smallest from commercial land or transportation corridors. Annual loads and yields varied with rainfall, with the maximum loads produced in the wettest year (1998) and the minimum loads produced in the driest year (1999).

Texas↗

Evaluation and modification of five techniques for estimating stormwater runoff for watersheds in west-central Florida

Several traditional techniques have been used for estimating stormwater runoff from ungaged watersheds. Applying these techniques to watersheds in west-central Florida requires that some of the empirical relations be extrapolated beyond tested ranges. As a result, there is uncertainty as to the accuracy of these estimates. Sixty-six storms occurring in 15 west-central Florida watersheds were initially modeled using the Rational Method, the U.S. Geological Survey Regional Regression Equations, the Natural Resources Conservation Service TR-20 model, the U.S. Army Corps of Engineers HEC-1 model, and the U.S. Environmental Protection Agency Storm Water Management Model. The techniques were applied according to the guidelines specified in the user manuals or standard engineering textbooks as though no field data were available and the selection of input parameters was not influenced by observed data. Computed estimates were compared with observed runoff to evaluate the accuracy of the techniques. One watershed was eliminated from further evaluation when it was determined that the area contributing runoff to the stream varies with the amount and intensity of rainfall. Therefore, further evaluation and modification of the input parameters were made for only 62 storms in 14 watersheds. Runoff ranged from 1.4 to 99.3 percent of rainfall. The average runoff for all watersheds included in this study was about 36 percent of rainfall. The average runoff for the urban, natural, and mixed land use watersheds was about 41, 27, and 29 percent of rainfall, respectively. Initial estimates of peak discharge using the Rational Method produced average watershed errors that ranged from an underestimation of 50.4 percent to an overestimation of 767 percent. The coefficient of runoff ranged from 0.20 to 0.60. Calibration of the technique produced average errors that ranged from an underestimation of 3.3 percent to an over estimation of 1.5 percent. The average calibrated coefficient of runoff for each watershed ranged from 0.02 to 0.72. The average values of the coefficient of runoff necessary to calibrate the urban, natural, and mixed land use watersheds were 0.39, 0.16, and 0.08, respectively. The U.S. Geological Survey regional regression equations for determining peak discharge produced errors that ranged from an underestimation of 87.3 percent to an overestimation of 1,140 percent. The regression equations for determining runoff volume produced errors that ranged from an underestimation of 95.6 percent to an overestimation of 324 percent. Regression equations developed from data used for this study produced errors that ranged between an underestimation of 82.8 percent and an overestimation of 328 percent for peak discharge and from an underestimation of 71.2 percent to an overestimation of 241 percent for runoff volume. Use of the equations developed for west-central Florida streams produced average errors for each type of watershed that were lower than errors associated with use of the U.S. Geological Survey regional equations. Initial estimates of peak discharges and runoff volumes using the Natural Resources Conservation Service TR-20 model, produced average errors of 44.6 and 42.7 percent, respectively, for all the watersheds. Curve numbers and times of concentration were adjusted to match estimated and observed peak discharges and runoff volumes. The average change in the curve number for all the watersheds was a decrease of 2.8 percent. The average change in the time of concentration was an increase of 59.2 percent. The shape of the input dimensionless unit hydrograph also had to be adjusted to match the shape and peak time of the estimated and observed flood hydrographs. Peak rate factors for the modified input dimensionless unit hydrographs ranged from 162 to 454. The mean errors for peak discharges and runoff volumes were reduced to 18.9 and 19.5 percent, respectively, using the average calibrated input parameters for each watershed. Initial estimates of peak discharges and runoff volumes using the U.S. Army Corp of Engineers Hydrologic Engineering Center-1 model, produced average errors of 105 and 26.8 percent respectively, for all the watersheds. Curve numbers and lag times were adjusted to match estimated and observed peak discharges and runoff volumes. The average change in the curve number for all the watersheds was a decrease of 2.5 percent. The average change in the lag time was an increase of 169 percent. The mean errors for peak discharges and runoff volumes were reduced to 5.8 and 1.4 percent, respectively, using the average calibrated input parameters for each watershed. The observed and estimated peak discharges and runoff volumes could be matched by adjusting curve numbers and lag time using the U.S. Army Corp of Engineers Hydrologic Engineering Center-1 model; however, the shape of the estimated flood hydrograph and timing of the peak could not be matched. The input dimensionless unit hydrograph must also be changed to increase the accuracy of the Hydrologic Engineering Center-1 model for watersheds in west-central Florida. The source code has to be modified and recompiled to enter different dimensionless unit hydrographs into the HEC-1 program. During application of the U.S. Environmental Protection Agency Storm Water Management Model, two separate infiltration methods were evaluated. Initial estimates of peak discharges and runoff volumes produced mean errors of 46.5 and 6.8 percent, respectively, for all watersheds using the Green-Ampt infiltration method, and 48.8 and 9.5 percent, respectively, using the Horton infiltration method. The mean errors were reduced to 18 and 0.3 percent for the Green-Ampt method and 20.9 and 7.2 percent for the Horton method using the average calibrated input parameters for each watershed. Estimates of peak discharges and runoff volumes were initially made for watersheds in west-central Florida using recommended procedures, then compared to observed peak discharges and runoff volumes. Subsequently, the procedures were modified to increase accuracy for this area. The same methods used during the study could be used in other parts of the world to evaluate the accuracy of standard methods for estimating stormwater runoff.

Florida↗

Estimated ground-water discharge by evapotranspiration from Death Valley, California, 1997-2001

The U.S. Geological Survey, in cooperation with the National Park Service and Inyo County, Calif., collected field data from 1997 through 2001 to accurately estimate the amount of annual ground-water discharge by evapotranspiration (ET) from the floor of Death Valley, California. Multispectral satellite-imagery and National Wetlands Inventory data are used to delineate evaporative ground-water discharge areas on the Death Valley floor. These areas are divided into five general units where ground-water discharge from ET is considered to be significant. Based upon similarities in soil type, soil moisture, vegetation type, and vegetation density; the ET units are salt-encrusted playa (21,287 acres), bare-soil playa (75,922 acres), low-density vegetation (6,625 acres), moderate-density vegetation (5,019 acres), and high-density vegetation (1,522 acres). Annual ET was computed for ET units with micrometeorological data which were continuously measured at six instrumented sites. Total ET was determined at sites that were chosen for their soil- and vegetated-surface conditions, which include salt-encrusted playa (extensive salt encrustation) 0.17 feet per year, bare-soil playa (silt and salt encrustation) 0.21 feet per year, pickleweed (pickleweed plants, low-density vegetation) 0.60 feet per year, Eagle Borax (arrowweed plants and salt grass, moderate-density vegetation) 1.99 feet per year, Mesquite Flat (mesquite trees, high-density vegetation) 2.86 feet per year, and Mesquite Flat mixed grasses (mixed meadow grasses, high-density vegetation) 3.90 feet per year. Precipitation, flooding, and ground-water discharge satisfy ET demand in Death Valley. Ground-water discharge is estimated by deducting local precipitation and flooding from cumulative ET estimates. Discharge rates from ET units were not estimated directly because the range of vegetation units far exceeded the five specific vegetation units that were measured. The rate of annual ground-water discharge by ET for each ET unit was determined by fitting the annual ground-water ET for each site with the variability in vegetation density in each ET unit. The ET rate representing the midpoint of each ET unit was used as the representative value. The rate of annual ground-water ET for the playa sites did not require scaling in this manner. Annual ground-water discharge by ET was determined for all five ET units: salt-encrusted playa (0.13 foot), bare-soil playa (0.15 foot), low-density vegetation (1.0 foot), moderate-density vegetation (2.0 feet), and high-density vegetation (3.0 feet), and an area of vegetation or bare soil not contributing to ground-water discharge unclassified (0.0 foot). The total ground-water discharge from ET for the Death Valley floor is about 35,000 acre-feet and was computed by summing the products of the area of each ET unit multiplied by a corresponding ET rate for each unit.

Water-Resources Investigations Report↗

Streamflow conditions in the Guadalupe River Basin, south-central Texas, water years 1987-2006— An assessment of streamflow gains and losses and relative contribution of major springs to streamflow

The U.S. Geological Survey, in cooperation with the Edwards Aquifer Authority, assessed available streamflow data in the Guadalupe River Basin to determine streamflow gains and losses and the relative contribution of flow from major springs - Comal Springs, San Marcos Springs, and Hueco Springs - to streamflow in reaches of the Guadalupe River and its tributaries. The assessment is based primarily on long-term (1987-2006) and short-term (January 1999, August 1999, August 2000, and August 2006) streamflow conditions. For each analysis period, the ratio of flow from the major springs (measured at the spring source) to the sum of inflows (measured at the source of inflow to the river system) is computed for reaches of the Comal River and San Marcos River that include springflows from major springs, and for Guadalupe River reaches downstream from Canyon Dam. The ratio of springflow to the sum of inflows to the reach is an estimate of the contribution of flows from major springs to streamflow. For 1987-2006, the ratio of springflow from the major springs to the sum of inflows for the most upstream reach that includes inflow from all three major springs, Guadalupe River - above Comal River to Gonzales, is 27 percent. At the lowermost downstream reach, Guadalupe River - Bloomington to the San Antonio River, the percentage of the sum of inflows attributed to springflow is 18 percent. At that lowermost reach, the ratio of Canyon Lake releases to the sum of inflows was 20 percent. For the short-term periods August 2000 and August 2006 (periods of relatively low flow), springflow in the reach Guadalupe River - above Comal River to Gonzales accounted for 77 and 78 percent, respectively, of the sum of inflows in that reach. At the lowermost reach Guadalupe River - Bloomington to San Antonio River, springflow was 52 and 53 percent of the sum of inflows, respectively, during August 2000 and August 2006 (compared with 18 percent during 1987-2006); and during August 2000 and August 2006, the ratios of Canyon Lake releases to the sum of inflows were less than 10 percent (compared with 20 percent during 1987-2006)

Texas↗

Evaluating external nutrient and suspended-sediment loads to Upper Klamath Lake, Oregon, using surrogate regressions with real-time turbidity and acoustic backscatter data

Executive Summary Suspended-sediment and total phosphorus loads were computed for two sites in the Upper Klamath Basin on the Wood and Williamson Rivers, the two main tributaries to Upper Klamath Lake. High temporal resolution turbidity and acoustic backscatter data were used to develop surrogate regression models to compute instantaneous concentrations and loads on these rivers. Regression models for the Williamson River site showed strong correlations of turbidity with total phosphorus and suspended-sediment concentrations (adjusted coefficients of determination [Adj R 2 ]=0.73 and 0.95, respectively). Regression models for the Wood River site had relatively poor, although statistically significant, relations of turbidity with total phosphorus, and turbidity and acoustic backscatter with suspended sediment concentration, with high prediction uncertainty. Total phosphorus loads for the partial 2014 water year (excluding October and November 2013) were 39 and 28 metric tons for the Williamson and Wood Rivers, respectively. These values are within the low range of phosphorus loads computed for these rivers from prior studies using water-quality data collected by the Klamath Tribes. The 2014 partial year total phosphorus loads on the Williamson and Wood Rivers are assumed to be biased low because of the absence of data from the first 2 months of water year 2014, and the drought conditions that were prevalent during that water year. Therefore, total phosphorus and suspended-sediment loads in this report should be considered as representative of a low-water year for the two study sites. Comparing loads from the Williamson and Wood River monitoring sites for November 2013–September 2014 shows that the Williamson and Sprague Rivers combined, as measured at the Williamson River site, contributed substantially more suspended sediment to Upper Klamath Lake than the Wood River, with 4,360 and 1,450 metric tons measured, respectively. Surrogate techniques have proven useful at the two study sites, particularly in using turbidity to compute suspended-sediment concentrations in the Williamson River. This proof-of-concept effort for computing total phosphorus concentrations using turbidity at the Williamson and Wood River sites also has shown that with additional samples over a wide range of flow regimes, high-temporal-resolution total phosphorus loads can be estimated on a daily, monthly, and annual basis, along with uncertainties for total phosphorus and suspended-sediment concentrations computed using regression models. Sediment-corrected backscatter at the Wood River has potential for estimating suspended-sediment loads from the Wood River Valley as well, with additional analysis of the variable streamflow measured at that site. Suspended-sediment and total phosphorus loads with a high level of temporal resolution will be useful to water managers, restoration practitioners, and scientists in the Upper Klamath Basin working toward the common goal of decreasing nutrient and sediment loads in Upper Klamath Lake.

Oregon↗

Barrier island vulnerability to breaching: a case study on Dauphin Island, Alabama

Breaching of barrier islands can adversely impact society by severing infrastructure, destroying private properties, and altering water quality in back bays and estuaries. This study provides a scheme that assesses the relative vulnerability of a barrier island to breach during storms. Dauphin Island, Alabama was selected for this study because it has a well documented history of island breaches and extensive geological and geomorphic data. To assess the vulnerability of the island, we defined several variables contributing to the risk of breaching: island geology, breaching history, and island topography and geomorphology. These variables were combined to form a breaching index (BI) value for cross island computational bins, each bin every 50 m in the alongshore direction. Results suggest the eastern section of Dauphin Island has the lowest risk of breaching with the remaining portion of the island having a moderate to high risk of breaching. Two reaches in the western section of the island were found to be particularly vulnerable due primarily to their minimal cross-sectional dimensions.

Alabama↗

PESTools – A Python toolkit for processing PEST-related information

PESTools is an open-source Python package for processing and visualizing information associated with the parameter estimation software PEST and PEST++. While PEST output can be reformatted for post- processing in spreadsheets or other menu-driven software packages, that approach can be error-prone and time-consuming. Managing information from highly parameterized models with thousands of parameters and observations presents additional challenges. PESTools consists of a set of Python object classes to facilitate efficient processing and visualization of PEST-related information. Processing and visualization of observation residuals, objective function contributions, parameter and observation sensitivities, parameter correlation and identifiability, and other common PEST outputs have been implemented. PESTools is integrated with the pyemu software package for linear-based computer model uncertainty analyses, allowing for efficient computations using the Jacobian Matrix without any external utilities or files. The use of dataframe objects (pandas Python package) facilitates rapid subsetting and querying of large datasets, as well as the incorporation of ancillary information such as observation locations, times, measurement types, and other associated information. PESTools’ object methods can be easily scripted with concise code, or alternatively, the use of IPython notebooks allows for live interaction with the information. PESTools is designed to streamline workflows and provide deeper insight into model behavior, enhance troubleshooting, and improve transparency in the calibration process.

Conference Paper↗

Simulating transport of volatile organic compounds in the unsaturated zone using the computer model R-UNSAT

Subsurface spills of gasoline and other petroleum products are a common environmental problem throughout the industrialized world. The U.S. Environmental Protection Agency has estimated that 40 percent of the more than 200,000 retail service stations in the United States have had accidental releases of petroleum hydrocarbons to the subsurface (U.S. Environmental Protection Agency, 1991). Restoration of a contaminated aquifer to regulatory standards is a technically difficult problem even when best engineering strategies are applied. Natural attenuation, a remediation strategy that relies on intrinsic physical, chemical, and biological processes to decrease contaminant concentrations, is gaining widespread acceptance in aquifer restoration efforts (Tremblay and others, 1995). The potential for successful remediation by natural attenuation depends on the fate of the organic constituents of the spilled product, which may include additives such as methyl tert-butyl ether (MTBE). These compounds can dissolve in ground water, adsorb to subsurface sediments, volatilize and diffuse through the unsaturated zone, or undergo chemical and biological reactions (fig. 1). Volatilization and biodegradation near the water table are two processes that can contribute significantly to the natural attenuation of volatile organic compounds (VOCs) in shallow ground water (McAllister and Chiang, 1994). To date, quantitative information on the rates at which these processes occur has been limited. R-UNSAT, a computer model designed for quantifying rates of volatilization and biodegradation of organic compounds near the water table, was developed and documented by the U.S. Geological Survey (USGS) and is now available to the public. R-UNSAT also can be applied, however, to other unsaturated-zone transport problems that involve gas diffusion, such as radon migration, and the deposition of compounds from the atmosphere to shallow ground water. This fact sheet describes the transport model and demonstrates its capabilities through applications to point- and nonpoint-source contamination.

Fact Sheet↗

Spatial and temporal variation of stream chemistry associated with contrasting geology and land-use patterns in the Chesapeake Bay watershed—Summary of results from Smith Creek, Virginia; Upper Chester River, Maryland; Conewago Creek, Pennsylvania; and Difficult Run, Virginia, 2010–2013

Despite widespread and ongoing implementation of conservation practices throughout the Chesapeake Bay watershed, water quality continues to be degraded by excess sediment and nutrient inputs. While the Chesapeake Bay Program has developed and maintains a large-scale and long-term monitoring network to detect improvements in water quality throughout the watershed, fewer resources have been allocated for monitoring smaller watersheds, even though water-quality improvements that may result from the implementation of conservation practices are likely to be first detected at smaller watershed scales. In 2010, the U.S. Geological Survey partnered with the U.S. Environmental Protection Agency and the U.S. Department of Agriculture to initiate water-quality monitoring in four selected small watersheds that were targeted for increased implementation of conservation practices. Smith Creek watershed is an agricultural watershed in the Shenandoah Valley of Virginia that is dominated by cattle and poultry production, and the Upper Chester River watershed is an agricultural watershed on the Eastern Shore of Maryland that is dominated by row-cropping activities. The Conewago Creek watershed is an agricultural watershed in southeastern Pennsylvania that is characterized by mixed agricultural activities. The fourth watershed, Difficult Run, is a suburban watershed in northern Virginia that is dominated by medium density residential development. The objective of this study was to investigate spatial and temporal variations in water chemistry and suspended sediment in these four relatively small watersheds that represent a range of land-use patterns and underlying geology to (1) characterize current water-quality conditions in these watersheds, and (2) identify the dominant sources, sinks, and transport processes in each watershed. The general study design involved two components. The first included intensive routine water-quality monitoring at an existing streamgage within each study area (including continuous water-quality monitoring as well as discrete water-quality sampling) to develop a detailed understanding of the temporal and hydrologic variability in stream chemistry and sediment transport in each watershed. The second component involved extensive water-quality monitoring at various sites throughout each watershed to develop a detailed understanding of spatial patterns. Both components were used to improve understanding of sources and transport processes affecting stream chemistry, including nutrients and suspended sediments, and their implications for detecting long-term trends related to best management practices. This report summarizes the results of monitoring that was performed from April 2010 through September 2013. Individual Small Watershed Summaries Summaries for each of the four small watersheds are presented below. Each watershed has a more descriptive and detailed section in the report, but these summaries may be particularly useful for some watershed managers and stakeholders desiring slightly less technical detail. Smith Creek Smith Creek is a 105.39-mi 2 watershed within the Shenandoah Valley that drains to the North Fork Shenandoah River. The long-term Smith Creek base-flow index is 72.3 percent, indicating that on average, approximately 72 percent of Smith Creek flow was base flow, which suggests that Smith Creek streamflow is dominated by groundwater discharge rather than stormwater runoff. A series of cluster and principal components analyses demonstrated that the majority of the variability in Smith Creek water quality could be attributed to hydrologic and seasonal variability. Statistically significant positive correlations with flow were observed for turbidity, suspended sediments, total nitrogen, ammonium, orthophosphate, iron, total phosphorus, and the ratio of calcium to magnesium. Statistically significant inverse correlations with flow were observed for specific conductance, magnesium, δ 15 N of nitrate, pH, bicarbonate, calcium, and δ 18 O of nitrate. Of particular note, flow and nitrate were not statistically significantly correlated, likely because of the relatively complex concentration-discharge relationship observed in continuous and discrete datasets. Statistically significant seasonal patterns were observed for numerous water-quality constituents: water temperature, turbidity, orthophosphate, total phosphorus, suspended-sediment concentration, and silica were higher during the warm season, but pH, dissolved oxygen, and sulfate were higher during the cool season. Surrogate regression models were developed to compute sediment and nutrient loads in Smith Creek using the continuous water-quality monitors. The mean Smith Creek in-stream sediment load was approximately 6,900 tons per year, with nearly 90 percent of the sediment load over the 3-year study period contributed during the eight largest storm events during that period. The Smith Creek total phosphorus load was approximately 21,000 pounds of phosphorus per year, with the majority of the load contributed during stormflow periods, although a substantial phosphorus load still occurs during base-flow conditions. The Smith Creek total nitrogen load was approximately 400,000 pounds per year, with total nitrogen accumulation less dominated by stormflow contributions (as was the case for sediment and total phosphorus) and strongly affected by base-flow export of nitrogen from the basin. Extensive water-quality monitoring throughout the Smith Creek watershed revealed how the complex geology and hydrology interacted to result in variable water chemistry. During relatively dry and low base-flow periods, much of the discharge in Smith Creek was contributed by a single dominant spring—Lacey Spring. During wetter base-flow periods, the flows in Smith Creek were largely generated by a mixture of headwater springs and forested mountain tributaries with very different geochemical composition. The headwater springs generally issued from limestone bedrock and were characterized as having relatively high nitrate, specific conductance, calcium, and magnesium, as well as relatively low concentrations of phosphorus, ammonium, iron, and manganese. The undeveloped, high-gradient, forested mountain sites were generally characterized by low ionic strength waters with low nutrient concentrations. Nitrate isotope data from the limestone springs generally were consistent with manure-derived nitrogen sources (such as cattle and poultry), although the possibility of other mixed sources cannot be excluded. Nitrate isotope data from the undeveloped, high-gradient forested mountain sites were more consistent with nitrogen from undisturbed soils, atmospheric deposition, or nitrogen fixation. Regardless of the nitrogen source, oxygen isotope data indicate that the nitrate was largely a result of nitrification. Land-use data indicate that manure sources of nitrogen dominated watershed nitrogen inputs. Phosphorus sources were less well studied. The presence of a single point-source discharge near the town of New Market contributed the majority of the phosphorus to Smith Creek under base-flow conditions, but nonpoint sources of phosphorus dominated the loading to Smith Creek during stormflow periods. Implementation of conservation practices increased in the Smith Creek watershed during the study period, and even though a broad range of practice types was implemented, the most common practices included stream fencing (for cattle exclusion), the development of nutrient management plans, conservation crop rotation, and the planting of cover crops. While the implementation of these conservation practices is encouraging, results indicate small increases in nitrate concentrations at the streamgage over the last 29 years, concurrent with small decreases in nitrate fluxes. It will likely be years before the cumulative effect of these practices can be detected in the Smith Creek water quality, and the magnitude of the effect of these conservation practices detected in Smith Creek will depend largely on whether nutrient loading (of manure and commercial fertilizer) is reduced over time. Upper Chester River The Upper Chester River watershed includes the 36-square-mile (mi 2 ) watershed area around several nontidal tributaries that drain into the tidal Chester River. The streamgage is on Chesterville Branch, the largest nontidal tributary (approximately 6.12 mi 2 ) and is the site for continuous water-quality monitoring for this project. The base-flow index at Chesterville Branch is about 72 percent and indicates that, as in most of the Coastal Plain, groundwater is the greatest contributor to streamflow. As such, more than 90 percent of the nitrogen in the stream is in the form of nitrate from groundwater. Continuous and discrete data collected at Chesterville Branch show the effects of streamflow and season on water quality. Significantly positive correlations with flow were observed for ammonium, dissolved and total phosphorus, sediment, and turbidity as runoff carried these constituents from the land surface into Chesterville Branch. Other constituents that increased significantly with flow include potassium, sulfate, iron, and manganese, which are likely contributed from near-stream areas and ponds with high organic-matter content. Total nitrogen, pH, and specific conductance, along with chemical constituents associated with groundwater inputs including nitrate, calcium, ratio of calcium to magnesium, silica, bicarbonate, and sodium, were negatively correlated with flow because concentrations of these constituents were diluted by runoff. Seasonal differences in water chemistry, which are most likely related to increased biologic effects on the uptake and release of chemicals in the stream and near-stream areas, also were observed. Water temperature, orthophosphate, δ 15 N of nitrate, bicarbonate, sodium, and the ratio of sodium to chloride were higher during the warm season, and dissolved oxygen, total nitrogen, nitrate, magnesium, sulfate, and manganese were higher during the cool season. Surrogate-regression models developed by using continuous water-quality data showed that the annual sediment load for the 2013 water year was about 2,600 tons, with more than 90 percent of this sediment contributed during two storms. The total phosphorus load in 2013 was about 13,000 pounds with more than 90 percent contributed during the same two storms as sediment. The load of total nitrogen, 140,000 pounds, accumulated steadily throughout the 2013 water year as nitrate in groundwater continuously discharged into the stream. The same two large storms that contributed 90 percent of the suspended-sediment and total phosphorus load only contributed about 20 percent of the annual total nitrogen load. Extensive water-quality monitoring of stream base flow throughout the Upper Chester River watershed identified how differences in land use and hydrogeology affected water chemistry. In parts of the watershed with well-drained soil and thick sandy aquifer sediments, concentrations of nitrate and other chemicals associated with fertilizer and lime application increased in streams as agricultural land use increased. More than 90 percent of the nitrogen in streams from these areas was in the form of nitrate, and concentrations ranged from about 5 milligrams per liter (mg/L) to 8 mg/L as nitrogen in the two largest tributaries. Stream nitrate concentrations were about 1 mg/L as nitrogen where soils were more poorly drained, the surficial aquifer sediments were thinner, and forests and wetlands were more widespread than agriculture. Nitrate isotope data were consistent with inorganic fertilizers ± atmospheric deposition and N 2 fixation as sources of nitrogen, and with nitrification as the dominant nitrate-forming process. Nitrate reduction was indicated by elevated δ 15 N and δ 18 O values in some samples from streams draining watersheds with poorly drained soils. An analysis of land-use data and SPARROW modeling input data attributed almost 90 percent of the nitrogen sources in the Upper Chester River watershed to inorganic fertilizer and fixation of atmospheric nitrogen by legumes, which is in agreement with the isotopic characteristics of nitrate in this watershed. Local sources of manure are limited in this area. Total phosphorus concentrations during base flow ranged from below detection to about 0.2 mg/L. Stream phosphorus concentrations during base flow were generally lower than those measured during storms because most phosphorus transport likely occurs as phosphorus attached to sediment particles during runoff. Because manure is not widely used in this area, the major source of phosphorus is likely fertilizer. The implementation of conservation practices in the Upper Chester River watershed increased substantially during the study period, with a total implementation of 1,194 U.S. Department of Agriculture-compliant practices. The most frequently used practices were oriented towards nutrient and sediment control, including cover crops, nutrient management planning, conservation crop rotation, conservation tillage, and irrigation management. The current Chesapeake Bay model for this area predicts that implementation of best management practices should result in a 13-percent decrease in overall delivery of nitrogen to the Upper Chester River. Because most nitrogen travels through the groundwater system for years to decades before being discharged to streams, the time period of monitoring was not sufficient to see the effects of these practices on water quality. The magnitude of the effect that may eventually be detected will depend on the degree to which nitrate leaching into the groundwater system is reduced over time. Loadings of phosphorus and sediment are primarily transported during large runoff events and are difficult to control and analyze for trends because of their timing and episodic nature. Conewago Creek Conewago Creek has two primary monitoring locations—one near the middle of the 47-mi 2 watershed and the other near the outlet just upstream of the Susquehanna River. The base-flow index was 47.3 percent for 2012–2013, indicating that on average, approximately 53 percent of the streamflow in Conewago Creek exited the watershed as surface flow, which suggests that the stormwater runoff was somewhat greater than groundwater discharge (base flow). A series of cluster and principal components analyses demonstrated that the majority of the variability in the Conewago Creek water quality could be attributed to hydrologic and seasonal variability. Statistically significant positive correlations with flow were observed at both monitoring sites for ammonium, total phosphorus, orthophosphate, iron, and manganese; additionally, at the upstream monitoring station, total nitrogen demonstrated a statistically significant positive correlation with flow. Statistically significant inverse correlations with flow were observed at both sites for water temperature, specific conductance (at the downstream site only), sulfate, chloride, calcium, and magnesium. Statistically significant seasonal patterns were observed for several water-quality constituents. Water temperature, phosphorus (upstream site only), and orthophosphate were higher during the warm season, and nitrate and total nitrogen (upstream site only) were higher during the cool season. Surrogate regression models were developed to compute sediment and nutrient load in Conewago Creek by using the continuous water-quality monitors and water-quality samples. Conewago Creek sediment load was approximately 9,900 tons in 2012 and approximately 18,900 tons in 2013, with nearly 80 percent of the sediment load in 2013 contributed by the three largest storm events. Annual total nitrogen loads could not be estimated due to poor model performance. The addition of continued monitoring or a continuously recording nitrate sensor could improve estimates of total nitrogen loads. During 2012 and 2013, phosphorus loads in Conewago Creek were approximately 50,000 pounds in each year. Combining data from one high-flow synoptic sampling with the data from routine sampling revealed how the geology and hydrology interact to result in variable water chemistry throughout the Conewago Creek watershed. The areas above the upstream gage in the headwaters are generally underlain by forested non-carbonate bedrock and are characterized by relatively low nitrate, specific conductance, calcium, and magnesium, as well as relatively low concentrations of phosphorus, ammonium, iron, and manganese. The more developed, agricultural areas below the upstream site were generally characterized by higher ionic strength waters with higher nutrient and metal concentrations. An analysis of land-use data and SPAtially Referenced Regressions On Watershed (SPARROW) modeling data indicates that manure sources of nitrogen dominate the input of nitrogen to the watershed. Implementation of conservation practices increased in the Conewago Creek watershed during the study period, and while a broad range of practice types were implemented, the most common practices included residue and tillage management, cover crops, nutrient management, terracing, and stream fencing (for animal exclusion or bank restoration). While the implementation of these conservation practices is encouraging, the cumulative effects of these practices probably will not be detected in Conewago Creek water quality for several years. The magnitude of the effects of these conservation practices on water quality in Conewago Creek will depend largely on the extent to which nutrient loading (septic, manure, and commercial fertilizer) and sediment-producing activities are reduced over time. Difficult Run The Difficult Run watershed is a 57.82-mi 2 watershed that drains to the Potomac River. The long-term Difficult Run base-flow index (from 1936 to 2010) was 57.9, indicating that approximately 58 percent of streamflow exited the watershed as base flow and 42 percent as stormflow; however, with continued development and urbanization of the watershed, the base-flow index has decreased to 50 percent during the last 20 years. This base-flow index was less than those of the other watersheds evaluated in this study, likely because the Difficult Run watershed largely is underlain by crystalline piedmont metamorphic rocks and has a greater proportion of impervious urban land cover. A series of cluster and principal components analyses indicated that most of the variability in Difficult Run water quality could be attributed to hydrologic variability and seasonality. Statistically significant positive correlations with flow were observed for turbidity, dissolved oxygen, suspended sediments, ammonium, orthophosphate, iron, and total phosphorus. Statistically significant inverse correlations with flow were observed for water temperature, pH, specific conductance, bicarbonate, calcium, magnesium, nitrate, δ 15 N of nitrate, and silica. Statistically significant seasonal patterns were observed for numerous water-quality constituents: water temperature, ammonium, orthophosphate, and δ 15 N of nitrate were higher during the warm season, and dissolved oxygen, nitrate, and manganese were higher during the cool season. Surrogate regression models were developed to compute sediment and nutrient loading rates. The Difficult Run sediment load was approximately 8,000 tons per year, with greater than 95 percent of the sediment load in the 2013 water year contributed by the seven largest storm events. The total phosphorus load in Difficult Run was approximately 14,000 pounds of phosphorus per year, with the majority of the load contributed during stormflow periods. The total nitrogen load in Difficult Run is estimated to have been approximately 140,000 pounds per year, with total nitrogen accumulation less dominated by stormflow contributions than that of phosphorus and strongly affected by base-flow export of nitrogen from the basin. Extensive water-quality monitoring throughout the Difficult Run watershed revealed relatively uniform generation of flow per unit of watershed area, as well as spatial variation in water quality that is strongly related to land-use activities. Elevated nitrate concentrations were observed in a subset of monitoring sites that are inversely correlated with population density and positively correlated to the septic system density within each subwatershed. The majority of the elevated nitrate concentrations for these sites are hypothesized to be caused by nitrate leaching from septic systems, more so than homeowner fertilizer usage among these subwatersheds that have lower population densities than other parts of the watershed. Nitrate isotope data, temporal patterns in the water-quality data, mass-balance computations, and a separate land-use analysis all generally indicate that leachate from septic systems was the likely source of the elevated nitrate. Another group of water-quality sites have relatively low nitrogen concentrations, are located in areas that are served by city sewer lines, and have experienced stream restoration activities. A final group of sites drained the areas with the highest imperviousness and had strongly elevated specific conductance, chloride, and sodium, which were likely caused by a combination of road salting and other anthropogenic sources draining these urbanized areas in the watershed. A fourth group of sites represents a mixture of water sources and had water quality similar to that at the Difficult Run streamgage. Analysis of the nitrate isotope data generally indicates a broad range of composition indicative of mixed natural and anthropogenic nitrogen sources. Implementation of conservation practices increased in the Difficult Run watershed during the study period, and while a broad range of practice types was implemented, the most common practices included stream restoration. While the implementation of these conservation practices is encouraging, the cumulative effect of these practices probably will not be detected in Difficult Run water quality for several years.

Maryland, Pennsylvania, Virginia↗

Evaluation of development options for Alaska North Slope viscous and heavy oil

Current estimates of discovered viscous and heavy oil in Alaska’s North Slope are 12 billion barrels of oil-in-place and 12–18 billion barrels of oil-in-place, respectively (see Appendix 1 for conversion to SI units). Since the early 1990s to the end of 2010, cumulative viscous oil production has amounted to 150 million barrels, and there has been no commercial production of heavy oil. During the last three decades, the industry has been challenged to develop technologies to commercially produce these untapped oil resources in this Arctic environment. In this paper, the general locations and geologic properties of the viscous oil-bearing West Sak/Schrader Bluff and heavy oil-bearing Ugnu stratigraphic intervals are described first. The geologic variability within these deposits and the evolution of technology have forced an incremental development approach, requiring costly field testing at the pilot scale of innovative extraction techniques. Although viscous oil is currently produced, its development is not mature, and firms appear to be still spending large sums on new approaches to improve recovery. The analysis specifies a representative viscous oil project and then applies a “real options” framework using simulation to determine whether the risked expected project value is sufficient to fund required expenditures on extraction process research and field testing. Computations show available field test funds to be highly sensitive to the operator’s hurdle rate of return as well as the range in magnitude of potential State revenues. The contribution of the paper is solving this problem using an approach where the extreme low return and high scenarios need only be specified, and where the uncertainties are modeled with beta distributions based on historical data or expert opinion.

Alaska↗

Morphology and paleohydrology of intracrater alluvial fans north of Hellas Basin, Mars

Alluvial fans and sinuous ridges are both important records of the history of fluvial activity on Mars, and they often occur together. We present observations of alluvial fans, many of which exhibit inverted relief, in five craters in the region north of Hellas basin. The observed fans ranged in size from ~10 to 820 km 2 . We identified three primary fan surface morphology classes (chute, degraded, and Inverted) as well as many instances where the morphology transitions from proximal chutes (or, rarely, a cratered degraded surface) to distal ridges corresponding to increasing thermal inertia. Clear superposition relationships at contacts between adjacent fans are rarely observed, suggesting interfingered deposits and concurrent fan development across the region. Localized factors appear to influence fan development as there is no systematic trend in the azimuth range of fan location, size of fan or catchment, as well as the degree of crater filling. Water and sediment availability may be controlled by lithology differences and weather patterns. Many of the fans had a mismatch between catchment and fan volume, corresponding to significant amounts of erosion perhaps due to windblown stripping of fine sediment. However, several notable fans exhibited volumes greater than their corresponding catchments. This may reflect uncertainty in the accuracy of the estimated paleosurface, or it may indicate sediment contributions to the fan from outside the mapped catchment. Ridges, inferred to be the resistant remnants of fluvially transported deposits, were used to estimate flow magnitude in fan construction with computed discharges of 60–400 m 3 /s and corresponding supply rate runoff values ~1–20 mm/h. Acknowledging that width-derived discharge values may overestimate flow conditions due to the likelihood of amalgamated channel deposits, this quantification provides important climate constraints. The upper range of runoff values and discharge rates are quite high, and would require either intense rain storms to generate immediate runoff, or longer-term snow accumulation and subsequent melt-runoff, potentially enhanced by rain-on-snow events. Minimum continuous formation time scales of less than a century are computed, but are incompatible with fan morphology (e.g., superposition relationships, embedded craters) and mechanisms to sustain flows. More realistic lower-limit fan construction times, accounting for modeled precipitation rates from the literature, are tens to hundreds of thousands of years. Fans were active in multiple events spanning the Hesperian to Amazonian periods, requiring transient climate conditions to support the fan aggradation.

Icarus↗

Regression models of discharge and mean velocity associated with near-median streamflow conditions in Texas: utility of the U.S. Geological Survey discharge measurement database

A database containing more than 16,300 discharge values and ancillary hydraulic attributes was assembled from summaries of discharge measurement records for 391 USGS streamflow-gauging stations (streamgauges) in Texas. Each discharge is between the 40th- and 60th-percentile daily mean streamflow as determined by period-of-record, streamgauge-specific, flow-duration curves. Each discharge therefore is assumed to represent a discharge measurement made for near-median streamflow conditions, and such conditions are conceptualized as representative of midrange to baseflow conditions in much of the state. The hydraulic attributes of each discharge measurement included concomitant cross-section flow area, water-surface top width, and reported mean velocity. Two regression equations are presented: (1) an expression for discharge and (2) an expression for mean velocity, both as functions of selected hydraulic attributes and watershed characteristics. Specifically, the discharge equation uses cross-sectional area, water-surface top width, contributing drainage area of the watershed, and mean annual precipitation of the location; the equation has an adjusted R-squared of approximately 0.95 and residual standard error of approximately 0.23 base-10 logarithm (cubic meters per second). The mean velocity equation uses discharge, water-surface top width, contributing drainage area, and mean annual precipitation; the equation has an adjusted R-squared of approximately 0.50 and residual standard error of approximately 0.087 third root (meters per second). Residual plots from both equations indicate that reliable estimates of discharge and mean velocity at ungauged stream sites are possible. Further, the relation between contributing drainage area and main-channel slope (a measure of whole-watershed slope) is depicted to aid analyst judgment of equation applicability for ungauged sites. Example applications and computations are provided and discussed within a real-world, discharge-measurement scenario, and an illustration of the development of a preliminary stage-discharge relation using the discharge equation is given.

Texas↗

Beating effect identified from seismic responses of instrumented buildings

Beating effects observed in the recorded responses of buildings are examined in this paper. Beating is a periodic, resonating and prolonged vibrational behavior caused by distinctive close coupling of translational and torsional modes of a lightly damped structure. Repetitively stored potential energy during the coupled translational and torsional deformations turns into repetitive vibrational energy causing the ensuing prolonged motions. Beating, if a dominant response characteristic, may impact the instantaneous and long-term shaking performances of the buildings during earthquakes. In many cases, it is noted that resonance caused by site effects also contributes to accentuating the beating effect. Records from the buildings exhibit structural responses with beating effects. Spectral analyses and system identification techniques are used to quantify dynamic characteristics used in computing beating periods. The beat frequency generally known in acoustical physics is denoted by the absolute value of the differences in frequencies that cause the phenomenon. Engineering implications of the beating may be summarized as (a) prolonged cyclic shaking due to beating effect may take its toll on the structural system, (b) repetitive shaking can accentuate fatigue and low-cycle fatigue, and (c) resonating beating cycles can and do cause discomfort to occupants. Identification of beating effects is the key to find remedial action in modification of dynamic characteristics in order to attenuate or eliminate such effects.

Conference Paper↗

Constraining source and path effects of large magnitude earthquakes using ground motion simulations

The purpose of this study is to use ground‐motion simulations to investigate ways in which source and path effects for large‐magnitude earthquakes can be represented in nonergodic ground‐motion models (GMMs). To achieve this, we designed a ground‐motion study in the San Francisco Bay Area that includes earthquakes with a broad range of magnitudes distributed uniformly on a fault plane, and sites covering a large range of rupture distances and azimuths. After running a large suite of kinematic simulations (magnitude 4–7), we then develop a nonergodic GMM with the simulated data. We find that trends in the within‐site residuals are affected significantly by the earthquake radiation pattern, rupture directivity, and slip patterns. Next, we modify an existing rupture directivity model to fit and remove the observed radiation pattern and rupture directivity from the residuals. We also minimize the contributions of slip patterns by averaging the within‐site residuals among multiple source realizations. Finally, after removing the source effects from the within‐site residuals, we compare the path effects computed with different magnitude groups using two approaches. The first approach only considers the small events that have the same shortest path to a site as the large events, whereas the second approach considers all small events on the fault plane. The results indicate that it is difficult to satisfactorily approximate the path effects of large events with those of small events using either approach, at least in the case of simulations.

California↗

Effects of land use on water quality and transport of selected constituents in streams in Mecklenburg County, North Carolina, 1994–98

Transport rates for total solids, total nitrogen, total phosphorus, biochemical oxygen demand, chromium, copper, lead, nickel, and zinc during 1994–98 were computed for six stormwater-monitoring sites in Mecklenburg County, North Carolina. These six stormwater-monitoring sites were operated by the Mecklenburg County Department of Environmental Protection, in cooperation with the City of Charlotte, and are located near the mouths of major streams. Constituent transport at the six study sites generally was dominated by nonpoint sources, except for nitrogen and phosphorus at two sites located downstream from the outfalls of major municipal wastewater-treatment plants. To relate land use to constituent transport, regression equations to predict constituent yield were developed by using water-quality data from a previous study of nine stormwater-monitoring sites on small streams in Mecklenburg County. The drainage basins of these nine stormwater sites have relatively homogeneous land-use characteristics compared to the six study sites. Mean annual construction activity, based on building permit files, was estimated for all stormwater-monitoring sites and included as an explanatory variable in the regression equations. These regression equations were used to predict constituent yield for the six study sites. Predicted yields generally were in agreement with computed yields. In addition, yields were predicted by using regression equations derived from a national urban water-quality database. Yields predicted from the regional regression equations generally were about an order of magnitude lower than computed yields. Regression analysis indicated that construction activity was a major contributor to transport of the constituents evaluated in this study except for total nitrogen and biochemical oxygen demand. Transport of total nitrogen and biochemical oxygen demand was dominated by point-source contributions. The two study basins that had the largest amounts of construction activity also had the highest total solids yields (1,300 and 1,500 tons per square mile per year). The highest total phosphorus yields (3.2 and 1.7 tons per square mile per year) attributable to nonpoint sources also occurred in these basins. Concentrations of chromium, copper, lead, nickel, and zinc were positively correlated with total solids concentrations at most of the study sites (Pearson product-moment correlation >0.50). The site having the highest median concentrations of chromium, copper, and nickel also was the site having the highest computed yield for total solids.

North Carolina↗

Simulation of the regional groundwater-flow system of the Menominee Indian Reservation, Wisconsin

A regional, two-dimensional, steady-state groundwater-flow model was developed to simulate the groundwater-flow system and groundwater/surface-water interactions within the Menominee Indian Reservation. The model was developed by the U.S. Geological Survey (USGS), in cooperation with the Menominee Indian Tribe of Wisconsin, to contribute to the fundamental understanding of the region’s hydrogeology. The objectives of the regional model were to improve understanding of the groundwater-flow system, including groundwater/surface-water interactions, and to develop a tool suitable for evaluating the effects of potential regional water-management programs. The computer code GFLOW was used because of the ease with which the model can simulate groundwater/surface-water interactions, provide a framework for simulating regional groundwater-flow systems, and be refined in a stepwise fashion to incorporate new data and simulate groundwater-flow patterns at multiple scales. Simulations made with the regional model reproduce groundwater levels and stream base flows representative of recent conditions (1970–2013) and illustrate groundwater-flow patterns with maps of (1) the simulated water table and groundwater-flow directions, (2) probabilistic areas contributing recharge to high-capacity pumped wells, and (3) estimation of the extent of infiltrated wastewater from treatment lagoons. The groundwater-flow model described in this report simulates the major hydrogeologic features of the modeled area, including surficial unconsolidated aquifers, groundwater/surface-water interactions, and groundwater withdrawals from existing high-capacity production wells. Areas contributing recharge to pumped high-capacity wells on the Menominee Indian Reservation were delineated by tracking simulated water particles from the water table to wells in combination with Monte Carlo techniques, and maps of the probability of capture for each well nest were produced. Groundwater-agebased areas contributing recharge to wells were simulated by using the calibrated set of parameters and porosity values adjusted to account for bias in simulated saturated thickness. Simulations were performed for current (2013) pumping rates. The simulations show a range in sensitivity of the simulated areas contributing recharge to wells given the parameters evaluated through the Monte Carlo analysis. The areas contributing recharge to supply wells for the villages of Zoar and Neopit are long and narrow, with a sharp gradation from high to low probability of capture. The areas contributing recharge to supply wells for Middle Village and the village of Keshena exhibit a sharp gradation from high to low probability over a relatively small area between the well and a local groundwater mound. The highest probability areas contributing recharge to the supply wells for the Villages of Onekewat and Redwing are in the immediate vicinity of the wells. These wells also have an extensive area with low probability for capturing water that is likely due to a locally low hydraulic gradient and the large degree of uncertainty associated with the lakebed resistance parameters that control interaction between groundwater and local lakes. Additional field investigations and associated local model refinements would facilitate further reductions in uncertainty associated with simulated areas contributing recharge to the wells. The likely extent of the Neopit wastewater plume was simulated by using the groundwater-flow model and Monte Carlo techniques to evaluate the sensitivity of predictive simulations to a range of model parameter values. Wastewater infiltrated from the currently operating lagoons flows predominantly south toward Tourtillotte Creek. Some of the infiltrated wastewater is simulated as having a low probability of flowing beneath Tourtillotte Creek to the nearby West Branch Wolf River. Results for the probable extent of the wastewater plume are considered to be qualitative because the method only considers advective flow and does not account for processes affecting contaminant transport in porous media. Therefore, results for the probable extent of the wastewater plume are sensitive to the number of particles used to represent flow from the lagoon and the resolution of a synthetic grid used for the analysis. Nonetheless, it is expected that the qualitative results may be of use for identifying potential downgradient areas of concern that can then be evaluated using the quantitative “area contributing recharge to wells” method or traditional contaminant-transport simulations.

Wisconsin↗

An Automated Cropland Classification Algorithm (ACCA) for Tajikistan by combining Landsat, MODIS, and secondary data

The overarching goal of this research was to develop and demonstrate an automated Cropland Classification Algorithm (ACCA) that will rapidly, routinely, and accurately classify agricultural cropland extent, areas, and characteristics (e.g., irrigated vs. rainfed) over large areas such as a country or a region through combination of multi-sensor remote sensing and secondary data. In this research, a rule-based ACCA was conceptualized, developed, and demonstrated for the country of Tajikistan using mega file data cubes (MFDCs) involving data from Landsat Global Land Survey (GLS), Landsat Enhanced Thematic Mapper Plus (ETM+) 30 m, Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m time-series, a suite of secondary data (e.g., elevation, slope, precipitation, temperature), and in situ data. First, the process involved producing an accurate reference (or truth) cropland layer (TCL), consisting of cropland extent, areas, and irrigated vs. rainfed cropland areas, for the entire country of Tajikistan based on MFDC of year 2005 (MFDC2005). The methods involved in producing TCL included using ISOCLASS clustering, Tasseled Cap bi-spectral plots, spectro-temporal characteristics from MODIS 250 m monthly normalized difference vegetation index (NDVI) maximum value composites (MVC) time-series, and textural characteristics of higher resolution imagery. The TCL statistics accurately matched with the national statistics of Tajikistan for irrigated and rainfed croplands, where about 70% of croplands were irrigated and the rest rainfed. Second, a rule-based ACCA was developed to replicate the TCL accurately (∼80% producer’s and user’s accuracies or within 20% quantity disagreement involving about 10 million Landsat 30 m sized cropland pixels of Tajikistan). Development of ACCA was an iterative process involving series of rules that are coded, refined, tweaked, and re-coded till ACCA derived croplands (ACLs) match accurately with TCLs. Third, the ACCA derived cropland layers of Tajikistan were produced for year 2005 (ACL2005), same year as the year used for developing ACCA, using MFDC2005. Fourth, TCL for year 2010 (TCL2010), an independent year, was produced using MFDC2010 using the same methods and approaches as the one used to produce TCL2005. Fifth, the ACCA was applied on MFDC2010 to derive ACL2010. The ACLs were then compared with TCLs (ACL2005 vs. TCL2005 and ACL2010 vs. TCL2010). The resulting accuracies and errors from error matrices involving about 152 million Landsat (30 m) pixels of the country of Tajikistan (of which about 10 million Landsat size, 30 m, cropland pixels) showed an overall accuracy of 99.6% (k hat = 0.97) for ACL2005 vs. TCL2005. For the 3 classes (irrigated, rainfed, and others) mapped in ACL2005, the producer’s accuracy was >86.4% and users accuracy was >93.6%. For ACL2010 vs. TCL2010, the error matrix showed an overall accuracy on 96.2% (k hat = 0.96). For the 3 classes (irrigated, rainfed, and others) mapped in ACL2010, the producer’s and user’s accuracies for the irrigated areas were ≥82.9%. Any intermixing was overwhelmingly between irrigated and rainfed croplands, indicating that croplands (irrigated plus rainfed areas) as well as irrigated areas were mapped with high levels of accuracies (∼90% or higher) even for the independent year. The ACL2005 and ACL2010, each, were produced using ACCA algorithm in ∼30 min using a Dell Precision desktop T7400 computer for the entire country of Tajikistan once the MFDCs for the years were ready. The ACCA algorithm for Tajikistan is made available through US Geological Survey’s ScienceBase: http://www.sciencebase.gov/catalog/folder/4f79f1b7e4b0009bd827f548 or at: https://powellcenter.usgs.gov/globalcroplandwater/content/models-algorithms . The research contributes to the efforts of global food security through research on global croplands and their water use (e.g., https://powellcenter.usgs.gov/globalcroplandwater/ ). The above results clearly demonstrated the ability of a rule-based ACCA to rapidly and accurately produce cropland data layer year after year (hindcast, nowcast, forecast) for the country it was developed using MFDCs that consist of combining multiple sensor data and secondary data. It needs to be noted that the ACCA is applicable to the area (e.g., country, region) for which it is developed. In this case, ACCA is applicable for the Country of Tajikistan to hindcast, nowcast, and forecast agricultural cropland extent, areas, and irrigated vs. rainfed. The same fundamental concept of ACCA applies to other areas of the World where ACCA codes need to be modified to suite the area/region of interest. ACCA can also be expanded to compute other crop characteristics such as crop types, cropping intensities, and phenologies.

Remote Sensing↗

A bibliography of terrain modeling (geomorphometry), the quantitative representation of topography: Supplement 4.0

Terrain modeling, the practice of ground-surface quantification, is an amalgam of Earth science, mathematics, engineering, and computer science. The discipline is known variously as geomorphometry (or simply morphometry), terrain analysis, and quantitative geomorphology. It continues to grow through myriad applications to hydrology, geohazards mapping, tectonics, sea-floor and planetary exploration, and other fields. Dating nominally to the co-founders of academic geography, Alexander von Humboldt (1808, 1817) and Carl Ritter (1826, 1828), the field was revolutionized late in the 20th Century by the computer manipulation of spatial arrays of terrain heights, or digital elevation models (DEMs), which can quantify and portray ground-surface form over large areas (Maune, 2001). Morphometric procedures are implemented routinely by commercial geographic information systems (GIS) as well as specialized software (Harvey and Eash, 1996; Köthe and others, 1996; ESRI, 1997; Drzewiecki et al., 1999; Dikau and Saurer, 1999; Djokic and Maidment, 2000; Wilson and Gallant, 2000; Breuer, 2001; Guth, 2001; Eastman, 2002). The new Earth Surface edition of the Journal of Geophysical Research, specializing in surficial processes, is the latest of many publication venues for terrain modeling. This is the fourth update of a bibliography and introduction to terrain modeling (Pike, 1993, 1995, 1996, 1999) designed to collect the diverse, scattered literature on surface measurement as a resource for the research community. The use of DEMs in science and technology continues to accelerate and diversify (Pike, 2000a). New work appears so frequently that a sampling must suffice to represent the vast literature. This report adds 1636 entries to the 4374 in the four earlier publications1. Forty-eight additional entries correct dead Internet links and other errors found in the prior listings. Chronicling the history of terrain modeling, many entries in this report predate the 1999 supplement. Coverage is representative from about 1800 through early–mid 2002. Papers increasingly are published exclusively or in duplicate on the Internet's World Wide Web; the dates given here for Web addresses (URLs) that lack a print publication indicate a Web site's last update or my last access of it. The bibliography is arranged alphabetically and thus is not readily summarized. This introduction cites about 500 entries, a third of them grouped under 24 morphometric topics, as a guide to the listing's contents. Continuing the practice of previous bibliographies in the series to provide more information on a few applications (see summary of past topics in Pike, 2000a), this report elaborates further on topographic data, putative new parameters, tectonic geomorphology/neo-orometry, biogeography, ice-cap morphometry, results from the Mars Global DEM, landslide-hazard mapping, terrain modeling as physics, Hack's law, and broad-scale computer visualization. The literature of some of these subjects is large, and none of the summaries is intended to more than introduce the topic and comment on some of the current contributions of terrain modeling. Closing the essay is a discussion of pre-1900 papers that trace the evolution of ridge-line and watercourse quantification by descriptive geometry, as well as comments on some new books and an on-line bulletin board.

Open-File Report↗