Predicting phosphorus dynamics in complex terrains using a variable source area hydrology model

Phosphorus (P) loss from agricultural watersheds has long been a critical water quality problem, the control of which has been the focus of considerable research and investment. Preventing P loss depends on accurately representing the hydrological and chemical processes governing P mobilization and transport. The Soil and Water Assessment Tool (SWAT) is a watershed model commonly used to predict run‐off and non‐point source pollution transport. SWAT simulates run‐off employing either the curve number (CN) or the Green and Ampt methods, both assume infiltration‐excess run‐off, although shallow soils underlain by a restricting layer commonly generate saturation‐excess run‐off from variable source areas (VSA). In this study, we compared traditional SWAT with a re‐conceptualized version, SWAT‐VSA, that represents VSA hydrology, in a complex agricultural watershed in east central Pennsylvania. The objectives of this research were to provide further evidence of SWAT‐VSA's integrated and distributed predictive capabilities against measured surface run‐off and stream P loads and to highlight the model's ability to drive sub‐field management of P. Thus, we relied on a detailed field management database to parameterize the models. SWAT and SWAT‐VSA predicted discharge similarly well (daily Nash–Sutcliffe efficiencies of 0.61 and 0.66, respectively), but SWAT‐VSA outperformed SWAT in predicting P export from the watershed. SWAT estimated lower P loss (0.0–0.25 kg ha^?1) from agricultural fields than SWAT‐VSA (0.0–1.0+ kg ha^?1), which also identified critical source areas – those areas generating large run‐off and P losses at the sub‐field level. These results support the use of SWAT‐VSA in predicting watershed‐scale P losses and identifying critical source areas of P loss in landscapes with VSA hydrology. Copyright © 2014 John Wiley & Sons, Ltd.     

Improving the spatial representation of soil properties and hydrology using topographically derived initialization processes in the SWAT model

Topography exerts critical controls on many hydrologic, geomorphologic and biophysical processes. However, many watershed modelling systems use topographic data only to define basin boundaries and stream channels, neglecting opportunities to account for topographic controls on processes such as soil genesis, soil moisture distributions and hydrological response. Here, we demonstrate a method that uses topographic data to adjust spatial soil morphologic and hydrologic attributes: texture, depth to the C‐horizon, saturated conductivity, bulk density, porosity and the water capacities at field (33 kpa) and wilting point (1500 kpa) tensions. As a proof of concept and initial performance test, the values of the topographically adjusted soil parameters and those from the Soil Survey Geographic Database (SSURGO; available at 1 : 20 000 scale) were compared with measured soil pedon pit data in the Grasslands Soil and Water Research Lab watershed in Riesel, TX. The topographically adjusted soils were better correlated with the pit measurements than were the SSURGO values. We then incorporated the topographically adjusted soils into an initialization of the Soil and Water Assessment Tool model for 15 Riesel research watersheds to investigate how changes in soil properties influence modelled hydrological responses at the field scale. The results showed that the topographically adjusted soils produced better runoff predictions in 50% of the fields, with the SSURGO soils performing better in the remainder. In addition, the a priori adjusted soils result in fewer calibrated model parameters. These results indicate that adjusting soil properties based on topography can result in more accurate soil characterization and, in some cases, improve model performance. Copyright © 2016 John Wiley & Sons, Ltd.     

Estimating forest biomass using small footprint LiDAR data: An individual tree-based approach that incorporates training data

A new individual tree-based algorithm for determining forest biomass using small footprint LiDAR data was developed and tested. This algorithm combines computer vision and optimization techniques to become the first training data-based algorithm specifically designed for processing forest LiDAR data. The computer vision portion of the algorithm uses generic properties of trees in small footprint LiDAR canopy height models (CHMs) to locate trees and find their crown boundaries and heights. The ways in which these generic properties are used for a specific scene and image type is dependent on 11 parameters, nine of which are set using training data and the Nelder–Mead simplex optimization procedure. Training data consist of small sections of the LiDAR data and corresponding ground data. After training, the biomass present in areas without ground measurements is determined by developing a regression equation between properties derived from the LiDAR data of the training stands and biomass, and then applying the equation to the new areas. A first test of this technique was performed using 25 plots (radius = 15 m) in a loblolly pine plantation in central Virginia, USA (37.42N, 78.68W) that was not intensively managed, together with corresponding data from a LiDAR canopy height model (resolution = 0.5 m). Results show correlations (r) between actual and predicted aboveground biomass ranging between 0.59 and 0.82, and RMSEs between 13.6 and 140.4 t/ha depending on the selection of training and testing plots, and the minimum diameter at breast height (7 or 10 cm) of trees included in the biomass estimate. Correlations between LiDAR-derived plot density estimates were low (0.22 ≤ r ≤ 0.56) but generally significant (at a 95% confidence level in most cases, based on a one tailed test), suggesting that the program is able to properly identify trees. Based on the results it is concluded that the validation of the first training data-based algorithm for determining forest biomass using small footprint LiDAR data was a success, and future refinement and testing are merited.     

Hydrogeology of desert springs in the Panamint Range,California, USA: Identifying the sources and amount of recharge that support spring flow

Despite its location in the rain shadow of the southern Sierra Nevada, the Panamint Range hosts a complex mountain groundwater system supporting numerous springs which have cultural, historical, and ecological importance. The sources of recharge that support these quintessential desert springs remain poorly quantified since very little hydrogeological research has been completed in the Panamint Range. Here we address the following questions: (i) what is the primary source of recharge that supports springs in the Panamint Range (snowmelt or rainfall), (ii) where is the recharge occurring (mountain-block, mountain-front, or mountain-system) and (iii) how much recharge occurs in the Panamint Range? We answer questions (i) and (ii) using stable isotopes measured in spring waters and precipitation, and question (iii) using a chloride mass-balance approach which is compared to a derivation of the Maxey–Eakin equation. Our dataset of the stable isotopic composition (δ¹⁸O and δ²H) of precipitation is short (1.5 years), but analyses on spring water samples indicate that high-elevation snowmelt is the dominant source of recharge for these springs, accounting for 57 (±9) to 79 (±12) percent of recharge. Recharge from rainfall is small but not insignificant. Mountain-block recharge is the dominant recharge mechanism. However, two basin springs emerging along the western mountain-front of the Panamint Range in Panamint Valley appear to be supported by mountain-front and mountain-system recharge, while Tule Spring (a basin spring emerging at the terminus of the bajada on the eastern side of the Panamint Range) appears to be supported by mountain-front recharge. Calculated recharge rates range from 19 mm year⁻¹ (elevations < 1000 mrsl) to 388 mm year⁻¹ (elevations > 1000 mrsl). The average annual recharge is approximately 91 mm year⁻¹ (equivalent to 19.4 percent of total annual precipitation). We infer that the springs in the Panamint Range (and their associated ecosystems) are extremely vulnerable to changes in snow cover associated with climate change. They are heavily dependent on snowmelt recharge from a relatively thin annual snowpack. These findings have important implications for the vulnerability of desert springs worldwide.     

Resonance behaviour and partial averaging in a three-body system with gravitational radiation damping

In a previous investigation, a model of three-body motion was developed which included the effects of gravitational radiation reaction. The aim was to describe the motion of a relativistic binary pulsar that is perturbed by a third mass and look for resonances between the binary and third-mass orbits. Numerical integration of an equation of relative motion that approximates the binary gives evidence of such resonances. These ( m : n ) resonances are defined for the present purposes by the resonance condition,   m ω= 2 n Ω  , where m and n are relatively prime integers and ω and Ω are the angular frequencies of the binary orbit and third-mass orbit (around the centre of mass of the binary), respectively. The resonance condition consequently fixes a value for the semimajor axis a of the binary orbit for the duration of the resonance because of the Kepler relationship  ω= a ^−3/2  . This paper outlines a method of averaging developed by Chicone, Mashhoon and Retzloff, which renders a non-linear system that undergoes resonance capture into a mathematically amenable form. This method is applied to the present system and one arrives at an analytical solution that describes the average motion during resonance. Furthermore, prominent features of the full non-linear system, such as the frequency of oscillation and antidamping, accord with their analytically derived formulae.     

Development and application of a physically based landscape water balance in the SWAT model

Watershed scale hydrological and biogeochemical models rely on the correct spatial‐temporal prediction of processes governing water and contaminant movement. The Soil and Water Assessment Tool (SWAT) model, one of the most commonly used watershed scale models, uses the popular curve number (CN) method to determine the respective amounts of infiltration and surface runoff. Although appropriate for flood forecasting in temperate climates, the CN method has been shown to be less than ideal in many situations (e.g. monsoonal climates and areas dominated by variable source area hydrology). The CN model is based on the assumption that there is a unique relationship between the average moisture content and the CN for all hydrologic response units (HRUs), and that the moisture content distribution is similar for each runoff event, which is not the case in many regions. Presented here is a physically based water balance that was coded in the SWAT model to replace the CN method of runoff generation. To compare this new water balance SWAT (SWAT‐WB) to the original CN‐based SWAT (SWAT‐CN), two watersheds were initialized; one in the headwaters of the Blue Nile in Ethiopia and one in the Catskill Mountains of New York. In the Ethiopian watershed, streamflow predictions were better using SWAT‐WB than SWAT‐CN [Nash–Sutcliffe efficiencies (NSE) of 0·79 and 0·67, respectively]. In the temperate Catskills, SWAT‐WB and SWAT‐CN predictions were approximately equivalent (NSE > 0·70). The spatial distribution of runoff‐generating areas differed greatly between the two models, with SWAT‐WB reflecting the topographical controls imposed on the model. Results show that a water balance provides results equal to or better than the CN, but with a more physically based approach. Copyright © 2010 John Wiley & Sons, Ltd.     

Web-based service of a visualization package “Amira” for the geosciences

Amira is a powerful three-dimensional visualization package that has been employed recently by the science and engineering communities to gain insight into their data. We discuss a new paradigm for the use of Amira in the Earth sciences that relies on the client-server paradigm. We have developed a module called WEB-IS2, which provides web-based access to Amira. This tool allows Earth scientists to manipulate Amira controls remotely and to analyze, render and view large datasets through the Internet without regard for time or location. This could have important ramifications for GRID computing.     

Understanding fen hydrology across multiple scales

Fens, which are among the most biodiverse of wetland types in the USA, typically occur in glacial landscapes characterized by geo‐morphologic variability at multiple spatial scales. As a result, the hydrologic systems that sustain fens are complex and not well understood. Traditional approaches for characterizing such systems use simplifying assumptions that cannot adequately capture the impact of variability in geology and topography. In this study, a hierarchical, multi‐scale groundwater modelling approach coupled with a geologic model is used to understand the hydrology of a fen in Michigan. This approach uses high‐resolution data to simulate the multi‐scale topographic and hydrologic framework and lithologic data from more than 8500 boreholes in a statewide water well database to capture the complex geology. A hierarchy of dynamically linked models is developed that simulates groundwater flow at all scales of interest and to delineate the areas that contribute groundwater to the fen. The results show the fen receiving groundwater from multiple sources: an adjacent wetland, local recharge, a nearby lake and a regional groundwater mound. Water from the regional mound flows to an intermediate source before reaching the fen, forming a ‘cascading’ connection, while other sources provide water through ‘direct’ connections. The regional mound is also the source of water to other fens, streams and lakes in this area, thus creating a large, interconnected hydrologic system that sustains the entire ecosystem. In order to sustainably manage such systems, conservation efforts must include both site‐based protection and management, as well as regional protection and management of groundwater source areas. Copyright © 2016 John Wiley & Sons, Ltd.     

Microphysics and Optical Attenuation in Fog: Observations from Two Coastal Sites

Boundary-Layer Meteorology - A total of 15 fog events from two field campaigns are investigated: the High Energy Laser in Fog (HELFOG) project (central California) and the Toward Improving Coastal...     

Incorporating variable source area hydrology into a curve-number-based watershed model

Many water quality models use some form of the curve number (CN) equation developed by the Soil Conservation Service (SCS; U.S. Depart of Agriculture) to predict storm runoff from watersheds based on an infiltration-excess response to rainfall. However, in humid, well-vegetated areas with shallow soils, such as in the northeastern USA, the predominant runoff generating mechanism is saturation-excess on variable source areas (VSAs). We reconceptualized the SCS–CN equation for VSAs, and incorporated it into the General Watershed Loading Function (GWLF) model. The new version of GWLF, named the Variable Source Loading Function (VSLF) model, simulates the watershed runoff response to rainfall using the standard SCS–CN equation, but spatially distributes the runoff response according to a soil wetness index. We spatially validated VSLF runoff predictions and compared VSLF to GWLF for a subwatershed of the New York City Water Supply System. The spatial distribution of runoff from VSLF is more physically realistic than the estimates from GWLF. This has important consequences for water quality modeling, and for the use of models to evaluate and guide watershed management, because correctly predicting the coincidence of runoff generation and pollutant sources is critical to simulating non-point source (NPS) pollution transported by runoff. Copyright © 2007 John Wiley & Sons, Ltd.