SOIL-SOILN simulations of water drainage and nitrate nitrogen transport from soil core lysimeters

Water resources protection from nitrate nitrogen (NO3-N) contamination is an important public concern and a major national environmental issue. The abilities of the SOIL-SOILN model to simulate water drainage and nitrate N fluxes from orchardgrass (Dactylis glomerata L.) were evaluated using data from a 3-yr field experiment. The soil is classified as a Hagerstown silt loam soil (fine, mixed, semiactive, mesic Typic Hapludalf). Nitrate losses below the 1-m depth from N-fertilized grazed orchardgrass were measured with intact soil core lysimeters. Five N-fertilizer treatments consisted of a control, urine application in the spring, urine application in the summer, urine application in the fall, and feces application in the summer. The SOIL-SOILN models were evaluated using water drainage and nitrate flux data for 1993-1994, 1994-1995, and 1995-1996. The N rate constants from a similar experiment with inorganic fertilizer and manure treatments under corn (Zea mays L.) were used to evaluate the SOILN model under orchardgrass sod. Results indicated that the SOIL model accurately simulated water drainage for all three years. The SOILN model adequately predicted nitrate losses for three urine treatments in each year and a control treatment in 1994-1995. However, it failed to produce accurate simulations for two control treatments in 1993-1994 and 1995-1996, and feces treatments in all three years. The inaccuracy in the simulation results for the control and feces treatments seems to be related to an inadequate modeling of N transformation processes. In general, the results demonstrate the potential of the SOILN model to predict NO3-N fluxes under pasture conditions using N transformation rate constants determined through the calibration process from corn fields on similar soils.     

Monitoring, modelling and environmental exposure assessment of industrial chemicals in the aquatic environment

Monitoring and laboratory data play integral roles alongside fate and exposure models in comprehensive risk assessments. The principle in the European Union Technical Guidance Documents for risk assessment is that measured data may take precedence over model results but only after they are judged to be of adequate reliability and to be representative of the particular environmental compartments to which they are applied. In practice, laboratory and field data are used to provide parameters for the models, while monitoring data are used to validate the models' predictions. Thus, comprehensive risk assessments require the integration of laboratory and monitoring data with the model predictions. However, this interplay is often overlooked. Discrepancies between the results of models and monitoring should be investigated in terms of the representativeness of both. Certainly, in the context of the EU risk assessment of existing chemicals, the specific requirements for monitoring data have not been adequately addressed. The resources required for environmental monitoring, both in terms of manpower and equipment, can be very significant. The design of monitoring programmes to optimise the use of resources and the use of models as a cost-effective alternative are increasing in importance. Generic considerations and criteria for the design of new monitoring programmes to generate representative quality data for the aquatic compartment are outlined and the criteria for the use of existing data are discussed. In particular, there is a need to improve the accessibility to data sets, to standardise the data sets, to promote communication and harmonisation of programmes and to incorporate the flexibility to change monitoring protocols to amend the chemicals under investigation in line with changing needs and priorities.     

The Use of Carbon and Nitrogen Isotopes to Study Watershed Erosion Processes1

Abstract:  Tracer studies are needed to better understand watershed soil erosion and calibrate watershed erosion models. For the first time, stable nitrogen and carbon isotopes (δ¹⁵N and δ¹³C) and the carbon to nitrogen atomic ratio (C/N) natural tracers are used to investigate temporal and spatial variability of erosion processes within a sub‐watershed. Temporal variability was assessed by comparing δ¹⁵N, δ¹³C, and C/N of eroded‐soils from a non‐equilibrium erosion event immediately following freezing and thawing of surface soils with two erosion events characterized by equilibrium conditions with erosion downcutting. Spatial variability was assessed for the equilibrium events by using the δ¹⁵N and δ¹³C signatures of eroded‐soils to measure the fraction of eroded‐soil derived from rill/interrill erosion on upland hillslopes as compared to headcut erosion on floodplains. In order to perform this study, a number of tasks were carried out including: (1) sampling source‐soils from upland hillslopes and floodplains, (2) sampling eroded‐soils with an in situ trap in the stream of the sub‐watershed, (3) isotopic and elemental analysis of the samples using isotope ratio mass spectrometry, (4) fractioning eroded‐soil to its upland rill/interrill and floodplain headcut end‐members using an unmixing model within a Bayesian Markov Chain Monte Carlo framework, and (5) evaluating tracer unmixing model results by comparison with process‐based erosion prediction models for rill/interrill and headcut erosion processes. Results showed that finer soil particles eroded during the non‐equilibrium event were enriched in δ¹⁵N and δ¹³C tracers and depleted in C/N tracer relative to coarser soil particles eroded during the equilibrium events. Correlation of tracer signature with soil particle size was explainable based on known biogeochemical processes. δ¹⁵N and δ¹³C were also able to distinguish between upland rill/interrill erosion and floodplain headcut erosion, which was due to different plant cover at the erosion sources. Results from the tracer unmixing model highlighted future needs for coupling rill/interrill and headcut erosion prediction models.     

Estimating Watershed Level Nonagricultural Pesticide Use From Golf Courses Using Geospatial Methods1

Abstract: Limited information exists on pesticide use for nonagricultural purposes, making it difficult to estimate pesticide loadings from nonagricultural sources to surface water and to conduct environmental risk assessments. A method was developed to estimate the amount of pesticide use on recreational turf grasses, specifically golf course turf grasses, for watersheds located throughout the conterminous United States (U.S.). The approach estimates pesticide use: (1) based on the area of recreational turf grasses (used as a surrogate for turf associated with golf courses) within the watershed, which was derived from maps of land cover, and (2) from data on the location and average treatable area of golf courses. The area of golf course turf grasses determined from these two methods was used to calculate the percentage of each watershed planted in golf course turf grass (percent crop area, or PCA). Turf‐grass PCAs derived from the two methods were used with recommended application rates provided on pesticide labels to estimate total pesticide use on recreational turf within 1,606 watersheds associated with surface‐water sources of drinking water. These pesticide use estimates made from label rates and PCAs were compared to use estimates from industry sales data on the amount of each pesticide sold for use within the watershed. The PCAs derived from the land‐cover data had an average value of 0.4% of a watershed with minimum of 0.01% and a maximum of 9.8%, whereas the PCA values that are based on the number of golf courses in a watershed had an average of 0.3% of a watershed with a minimum of <0.01% and a maximum of 14.2%. Both the land‐cover method and the number of golf courses method produced similar PCA distributions, suggesting that either technique may be used to provide a PCA estimate for recreational turf. The average and maximum PCAs generally correlated to watershed size, with the highest PCAs estimated for small watersheds. Using watershed specific PCAs, combined with label rates, resulted in greater than two orders of magnitude over‐estimation of the pesticide use compared to estimates from sales data.     

Development of the Spatial Rainfall Generator (SRGEN) for the Agricultural Policy/Environmental Extender Model

Accurate spatial representation of climatic patterns is often a challenge in modeling biophysical processes at the watershed scale, especially where the representation of a spatial gradient in rainfall is not sufficiently captured by the number of weather stations. The spatial rainfall generator (SRGEN) is developed as an extension of the “weather generator” (WXGEN), a component of the Agricultural Policy/Environmental eXtender (APEX) model. SRGEN generates spatially distributed daily rainfall using monthly weather statistics available at multiple locations in a watershed. The spatial rainfall generator as incorporated in APEX is tested on the Cowhouse watershed (1,178 km²) in central Texas. The watershed presented a significant spatial rainfall gradient of 2.9 mm/km in the lateral (north‐south) directions based on four rainfall gages. A comparative analysis between SRGEN and WXGEN indicates that SRGEN performs well (PBIAS = 2.40%). Good results were obtained from APEX for streamflow (NSE = 0.99, PBIAS = 8.34%) and NO₃‐N and soluble P loads (PBIAS ≈ 6.00% for each, respectively). However, APEX underpredicted sediment yield and organic N and P loads (PBIAS: 24.75‐27.90%) with SRGEN, although its uncertainty in output was lower than WXGEN results (PBIAS: ?13.02 to ?46.13%). The overall improvement achieved in rainfall generation by SRGEN is demonstrated to be effective in the improving model performance on flow and water quality output.     

CONJUNCTIVE SURFACE AND GROUND WATER MANAGEMENT IN THE JAKARTA REGION,INDONESIA1

ABSTRACT: This study investigates the degree of economic inefficiency of the current institutional arrangements for surface and ground water management in meeting urban water demand in the Jakarta region. A numerical model of integrated surface and ground water management is developed using GAMS (General Algebraic Modelling System) software. The model maximizes the net present value of social benefits from piped water and ground water consumption across all users over time from 1999 to 2025. Four policy scenarios are examined: the status quo, the social planner's solution, and two ground water pumping quota scenarios: an aggregate ground water pumping quota and a partial quota applied to commercial and industrial users. Three variations in each policy scenario are considered: investment in water infrastructure of the Jakarta water enterprise (PAM Jaya), water demand growth, and discount rates. The status quo, depending on the investment option, the growth of water demand, and the discount rate, results in a 7.4 to 47.8 percent loss in economic efficiency relative to the social planner's solution. The partial quota is the most feasible, applicable, and manageable scenario. The optimal investment option could increase the volume of piped water supply and reduce the cost of water production. The volume of water delivery could increase by up to 156 percent, but it implies only a 35 percent increase in the surface raw water demands above the current level. However, it does not significantly reduce cumulative ground water extraction over the time period considered.     

Life from an orderly cosmos

Recent astrophysical studies suggest a high degree of order in the inanimate universe, stemming from cosmic beginnings. This state is consistent with the nonrandomness observed experimentally in the thermal polymers of amino acids that figure as an early inanimate stage in organic evolution. The various stages in inanimate matter, protocells, and evolved cells and the degree of order that they represent comport with the second law of thermodynamics on a cosmic scale.