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A soil block (1.5 m × 1.5 m × 1.5 m) was excavated at a footslope position on a hillslope underlain by a fragipan horizon. The block vertical faces were sealed on three sides using bentonite, sand, and lumber, with horizontal pressure exerted from basement jacks. The downslope face of the block

The accuracy of the Nitrogen and Carbon cycling in Soil, Water And Plant (NCSWAP) model to simulate (nitrate-nitrogen) NO 3 -N leaching from orchardgrass (Dactylis glomerata L.) pasture was evaluated using data collected from a 3-yr leaching experiment conducted in central Pennsylvania on Hagerstown silt loam soil (fine, mixed, mesic, Typic Hapludalf). Nitrate leaching losses below the 1-m depth from N-fertilized orchardgrass sod were measured with intact soil core lysimeters (0.6-m diam. by 1-m long). 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 were used to test the model. The model was calibrated using the data from 1993 to 1994 and then was validated using 1994 to 1995 and 1995 to 1996 water flow- and NO 3 -N leaching data. Statistical analysis indicated a good fit between field measured and predicted NO 3 -N leaching for most treatments in each year. The model simulations of water flow- and NO 3 -N leaching losses below the 1-m depth were compared with the mean of measured field data for these 3 yr. The results of this study showed that the NCSWAP model performed well and accurately simulated water flow and total annual NO 3 -N loss through leaching below the 1-m depth under orchardgrass pasture. However, the model failed to produce accurate simulations for the feces treatment in 1994 to 1995. The simulation error in the feces treatment seemed to be related to N mineralization process in the model. Generally, the results of this study suggest that the NCSWAP model can be used for predicting NO 3 -N leached annually from pastured orchardgrass.

This paper examines the efficiency and price effects of mergers by applying a frontier profit function to data on bank "megamergers." We find that merged banks experience a statistically significant 16 percentage point average increase in profit-efficiency rank relative to other large banks. Most of the improvement is from increasing revenues, including a shift in outputs from securities to loans, a higher-valued product. Improvements were greatest for the banks with the lowest efficiencies prior to merging, who therefore had the greatest capacity for improvement. By comparison, the effects on profits from merger-related changes in prices were found to be very small.

This paper examines the efficiency and price effects of mergers by applying a frontier profit function to data on bank ‘megamergers’. We find that merged banks experience a statistically significant 16 percentage point average increase in profit efficiency rank relative to other large banks. Most of the improvement is from increasing revenues, including a shift in outputs from securities to loans, a higher-valued product. Improvements were greatest for the banks with the lowest efficiencies prior to merging, who therefore had the greatest capacity for improvement. By comparison, the effects on profits from merger-related changes in prices were found to be very small.

This article develops a new method of estimating inefficiencies in joint production and shows that unlike the approaches utilized in the previous studies of inefficiency, this method maintains a consistent relationship between the error term of a profit function and the error terms of its price derivatives. A useful by-product of the method is a proof of a Hotelling-like lemma that relates stochastic input demand and output supply functions to stochastic profit functions. While the previous studies fit a single frontier to data on all firms, this paper estimates a frontier unique to every observed firm to allow each one to have a different potential of achieving maximal levels of profit. The new method is applied in the analysis of annual data, 1984–1989, for U.S. commercial banks. Both the analytical and numerical results of the paper show that the residual that the previous studies attribute to inefficiency includes the effects of excluded variables and of inaccuracies in the specified functional forms. Once accurate estimates of these effects are subtracted from the residual, the distortions in the measured inefficiencies should be considerably reduced. Consequently, this article considers how such estimates might be obtained.

The ability of the N submodel, LEACHN, of the Leaching Estimation And CHemical Model (LEACHM model) to simulate nitrate-nitrogen (NO 3 -N) leaching from orchardgrass (Dactylis glomerata L.) pasture was evaluated using field data from a 2-yr experiment. Leaching data were collected from an experiment conducted in central Pennsylvania on Hagerstown silt loam soil (fine, mixed, mesic, Typic Hapludalf). Nitrate losses below the 1-m depth from N-fertilized orchardgrass sod were measured with intact soil core lysimeters (0.6-m diam. by 1-m long). 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. Calibration N transformation rate constants from previous work with inorganic fertilizer and manure treatments under corn were used to evaluate the LEACHN model under pasture conditions. Statistical analysis indicated that the model accurately predicted annual NO 3 -N leaching below the 1-m depth for three to five of the five treatments in each year. The model failed to produce accurate predictions for the control and feces treatments in 1993 to 1994. The simulation error in these two treatments appeared to be related to soil N transformation rate constants in the model. Other reasons for discrepancies between measured and simulated NO 3 -N leaching for some months may have been due to restricted water flow associated with frozen soil or a heavy snowpack during winter. Results demonstrate the potential of the LEACHN model to predict NO 3 -N leaching under pasture conditions using N transformation rate constants determined through the calibration process from corn (Zea mays L.) fields on similar soils.

Field-saturated hydraulic conductivity (Kfs) is perhaps the single most important property for flow and transport-related phenomena in soils. Kfs is prone to variability because of swelling and shrinking of clay that results from differences in initial soil water content. The effects of initial soil water content on the variability of Kfs in a structured clayey soil were investigated in this study. The soil was classified as a Hagerstown silt loam (fine, mixed, mesic, Typic Hapludalf). The Kfs and initial water content were measured monthly from May 1994 to November 1995. The Guelph permeameter was used to measure Kfs. Three Kfs measurements were made in-situ on three corners of an equilateral triangle with sides of 3 m at a depth range of 0.35-0.40 m. The measurements were taken between the 23rd and 31st day of each month, depending on weather and soil conditions. A soil sample was collected from each hole at a depth of 0.35-0.40 m before making Kfs measurements in order to determine water content using the gravimetric method. Variations and fluctuations in Kfs values were observed throughout the duration of the study. Kfs values in June and July 1994 were about 4 to 15 times greater than in the spring, fall, and winter. In 1995, Kfs varied in the same manner as it did in 1994. Kfs values for the interval from June through September 1995 were much larger than in early spring, late fall, and winter. This variation in Kfs was attributed primarily to changes in soil structure and macroporosity caused by the swelling and shrinking of the clay associated with variations in soil water content throughout the year. A curvilinear logistic relationship (R 2 = 0.95) was found between the data of Kfs and initial soil water content.

Soil nitrogen mineralization kinetics were studied for eight treatments of two soils in an aerobic long-term (30 wk) incubation experiment. Soil mineral-N (NH 4 + and NO 3 − ) in the leachates was measured every week during the first 9 wk and every 2 or 3 wk thereafter. The NH 4 + percentage of the mineral-N ranged between 85 and 99% for all treatments in the first week of incubation and remained high (> 80%) in several treatments until the end of wk 4. Starting at wk 7, NH 4 + concentrations were negligible in all treatments. The net N mineralization rate was 15–24 mg N kg −1 wk −1 during the first 4–6 wk and 2–5 mg N kg −1 wk −1 from wk 8 until the end of the incubation. Four models, (i) a one-component, first-order exponential model (the single model), (ii) a two-component, first-order exponential model (the double model), (iii) a one-component, first-order exponential model including a constant term (the special model), and (iv) a hyperbolic model, were fit to the cumulative mineral-N vs time data using a non-linear regression procedure. The goodness of fit of the four models depended on the duration of incubation. With 30 wk data, the double and special models were significantly better than the other two models; with the first 15 wk data, the four models had essentially the same goodness of fit for seven out of eight treatments. The values of the regression parameters derived from each model also depended on the incubation duration. Results from this study show that the pool size and mineralization rate parameters in the different models are merely mathematically-defined quantities obtained from the kinetic analysis of the net N mineralization and do not represent any rigorously-defined pool sizes of potentially-mineralizable N and their mineralization rate constants in the soils.

A long standing puzzle in the Capital Asset Pricing Model (CAPM) has been the inability of empirical work to validate it. Roll (1977) was the first to point out this problem, and recently, Fama and French (1992, 1993) bolstered Roll's original critique with additional empirical results. Does this mean the CAPM is dead? This paper presents a new empirical approach to estimating the CAPM. This approach takes into account the differences between observable and expected returns for risky assets and for the market portfolio of all traded assets, as well as inherent nonlinearities and the effects of excluded variables. Using this approach, we provide evidence that the CAPM is alive and well.

The abilities of the Richards and convection-dispersion equations approach (LEACHNR) and the capacity model approach (LEACHNA) of the nitrogen version (LEACHN) of the LEACHM model to simulate nitrate leaching were evaluated using field data from a 5-year nitrate leaching experiment conducted in central Pennsylvania on Hagerstown silt loam soil (fine, mixed, mesic, Typic Hapludalf). Nitrate leaching losses from N-fertilized and manured corn below the 1.2-m depth were measured with zero-tension pan lysimeters. Three N-fertilized and manured treatments for 1988-1989, 1989-1990, and 1990-1991 and two N-fertilized treatments for 1991-1992 and 1992-1993 were used from the leaching experiment to evaluate both approaches of LEACHN. The individual monthly simulations of nitrate leaching were compared with the mean of pan efficiency corrected-measured data for these 5 years. Both approaches of the model were calibrated to the site conditions using the data of 1989-1990 and were then evaluated using 1988-1989, 1990-1991, 1991-1992 and 1992-1993 nitrate leaching data. Simulated results for the calibration year for both models were reasonably accurate (31 of 36 months simulated within the experimental 95% confidence limits). The statistical analysis used in this study indicated that both LEACHNA and LEACHNR adequately (91 to 120 months within the 95% confidence limits) predicted nitrate leaching below the 1.2-m depth for treatments in the refinement years. Much of the simulation error in some treatments in the refinement years seemed to be related to the sub-routine controlling soil nitrogen transformation processes and their rate constants in the model. The large deviations in NO 3 - -N leached in some winter months may be related, in part, to problems with simulated water flow associated with the frozen soil conditions and snow accumulation. The addition of a dual-pore water flow option (LEACHNA) to the nitrogen version of LEACHM did not improve prediction of nitrate leaching beyond the rooting zone of corn under Pennsylvania conditions.

Agricultural system models are useful tools to synthesize field experimental data and to extrapolate the results to longer periods of weather and other cropping systems. The objectives of this study were: 1) to quantify the effects of crop management practices and tillage on soil water and spring wheat production in a continuous spring wheat system using RZWQM2 model under a dryland condition, and 2) to extend the results to longer term weather conditions and alternate cropping systems and management practices. Measured soil water content, crop yield, and total above ground biomass under different tillage and plant management practices were used to calibrate and validate the RZWQM2 model. The model showed inevident impacts of tillage and significant reduction in grain yield and biomass under late planting, in agreement with observed differences among treatments. The hydrologic analysis under long-term climate variability showed a large water deficit (32.3 cm) for the spring wheat crop; Fallowing the dryland every other year conserved 4.2 cm water for the following wheat year, of which only 1.7 cm water was taken up by wheat, resulting in a yield increase of 249 kg ha-1 (13.7%). However, the annualized average total yield decreased 782 kg ha-1 (43.1%) due to one year fallow; thus the spring wheat-fallow rotation was not economical. Other long-term simulations showed that optimal planting dates ranged from March 1 to April 10, and the seeding rate with optimum economic return was 3.71 and 3.95 × 106 seeds ha-1 for conventional and ecological management treatments, respectively.

High NO 3 -N concentrations in groundwater resulting from agricultural production have increased the need for mathematical models to predict the concentration and mass of NO 3 -N leached from agricultural soils. Study objectives included evaluating the N version of LEACHM (LEACHMN) to predict mass of NO 3 -N leached from nonmanured and manured corn (Zea mays L.), and to test two methods of model validation. Four treatments (no manure with 0 and 200 kg N ha −1 and a manure treatment with 0 and 100 kg N ha −1 ) from a NO 3 leaching experiment were modeled for 1988, 1989, and 1990. Model calibration involved adjusting nitrification, denitrification, and volatilization rate constants to minimize differences between predicted and observed data

Leaching of agricultural chemicals from the root and vadose zones into groundwater is an important environmental concern. To procure a better understanding of the movement and transport of agricultural chemicals through the soil profile, a field research study was conducted to estimate bromide leaching losses under saturated conditions where preferential flow is occurring. The field data were then used to evaluate the LEACHM model. Eighteen double-ring infiltrometers were used to apply a pulse (100 mm depth) of bromide tracer on two previously saturated soils located in a karst region of southeastern Pennsylvania. Internal drainage over the next seven days resulted in nearly 51% of the applied Br − being leached to a depth below 0.80 m. The LEACHM model was used to simulate the amount of bromide leached in each infiltrometer. The model predicted, accurately, an average of 46% of the applied Br − leached below the 0.80 m depth. Mean values of bromide concentration in the soil profile were predicted within two standard deviations of the measured mean for all depths except for the 0.20–0.40 m depth increment where the model overpredicted the bromide concentration. The model predictions of Br − leached were tested against field measurements using several statistical tests. The LEACHM model performed adequately under preferential flow conditions, perhaps because the infiltration rate at each site was used as a model input. This, actually, is some measure of the macropore flow process and suggests that simple models such as LEACHM can be used in the field, as long as a distribution of infiltration rates is used as an input.

Management practices are needed to reduce dryland soil CO(2) emissions and to increase C sequestration. We evaluated the effects of tillage and cropping sequence combinations and N fertilization on dryland crop biomass (stems + leaves) and soil surface CO(2) flux and C content (0- to 120-cm depth) in a Williams loam from May to October, 2006 to 2008, in eastern Montana. Treatments were no-tilled continuous malt barley (Hordeum vulgaris L.) (NTCB), no-tilled malt barley-pea (Pisum sativum L.) (NTB-P), no-tilled malt barley-fallow (NTB-F), and conventional-tilled malt barley-fallow (CTB-F), each with 0 and 80 kg N ha(-1). Measurements were made both in Phase I (malt barley in NTCB, pea in NTB-P, and fallow in NTB-F and CTB-F) and Phase II (malt barley in all sequences) of each cropping sequence in every year. Crop biomass varied among years, was greater in the barley than in the pea phase of the NTB-P treatment, and greater in NTCB and NTB-P than in NTB-F and CTB-F in 2 out of 3 yr. Similarly, biomass was greater with 80 than with 0 kg N ha(-1) in 1 out of 3 yr. Soil CO(2) flux increased from 8 mg C m(-2) h(-1) in early May to 239 mg C m(-2) h(-1) in mid-June as temperature increased and then declined to 3 mg C m(-2) h(-1) in September-October. Fluxes peaked immediately following substantial precipitation (>10 mm), especially in NTCB and NTB-P. Cumulative CO(2) flux from May to October was greater in 2006 and 2007 than in 2008, greater in cropping than in fallow phases, and greater in NTCB than in NTB-F. Tillage did not influence crop biomass and CO(2) flux but N fertilization had a variable effect on the flux in 2008. Similarly, soil total C content was not influenced by treatments. Annual cropping increased CO(2) flux compared with crop-fallow probably by increasing crop residue returns to soils and root and rhizosphere respiration. Inclusion of peas in the rotation with malt barley in the no-till system, which have been known to reduce N fertilization rates and sustain malt barley yields, resulted in a CO(2) flux similar to that in the CTB-F sequence.

[1] Preferential flow path development in the field is the result of the complex interaction of multiple processes relating to the soil's structure, moisture condition, stress level, and biological activity. Visualizing and characterizing the cracking behavior and preferential paths evolution with soil depth has always been a key challenge and a major barrier against scaling up existing hydrologic concepts and models to account for preferential flows. This paper presents a new methodology to quantify soil preferential paths in the field using liquid latex. The evolution of the preferential flow paths at different soil depths and moisture conditions is assessed. Results from different soil series (Savage clay loam soil versus Chalmers clay loam) and different vegetation covers and soil managements (corn/tilled field versus soybean no-till field in the Chalmers soil series) are presented.

The LEACHM model was evaluated using data from a field experiment conducted in Lancaster County, Pennsylvania, U.S.A. Many of the parameter input values were the means of determinations for soil samples from the field site. Measured nitrogen (N) uptake and nitrate (NO3-N) storage in the soil profile, as well as mineralization and nitrification rates were higher in 1987 than in 1988. The measured N removal by crops was taken as the simulated N uptake. A reasonably good agreement between simulated and measured values was obtained for NO3-N storage. However, higher rate constants had to be used for 1987 than for 1988 in order to match simulated with measured storage. The simulated soil solution NO3-N concentrations at 1.2-m depth agreed quite well with those measured in porous cup water samples, except for the highest ammonium nitrate treatment. In general, the simulation results indicated that the LEACHM model described the nitrogen dynamics fairly well.

Since laboratory and field measurement of soil hydraulic properties is time consuming and subject to large error, numerous models have been proposed to predict soil hydraulic properties from easily measurable soil properties such as particle size distribution, bulk density, effective porosity and carbon content. In this study a multiple linear regression model was developed to predict the saturated hydraulic conductivity of soils from their particle size distribution and bulk density data. Published data from 350 soil core samples of varying soils from different sources were used to develop the model. Stepwise regression selected the best model for prediction of soil hydraulic conductivity (R2 = 0.68, P < 0.0001) from the independent parameters of silt, clay, and bulk density. Additional field measured data were collected to test and validate the model using several statistical evaluation procedures. Based on the statistical evaluation criteria, the model performed fairly well and gave a satisfactory validation versus the field measured data.

Management practices can influence soil CO(2) emission and C content in cropland, which can effect global warming. We examined the effects of combinations of irrigation, tillage, cropping systems, and N fertilization on soil CO(2) flux, temperature, water, and C content at the 0- to 20-cm depth from May to November 2005 at two sites in the northern Great Plains. Treatments were two irrigation systems (irrigated vs. non-irrigated) and six management practices that contained tilled and no-tilled malt barley (Hordeum vulgaris L.) with 0 to 134 kg N ha(-1), no-tilled pea (Pisum sativum L.), and a conservation reserve program (CRP) planting applied in Lihen sandy loam (sandy, mixed, frigid, Entic Haplustolls) in western North Dakota. In eastern Montana, treatments were no-tilled malt barley with 78 kg N ha(-1), no-tilled rye (Secale cereale L.), no-tilled Austrian winter pea, no-tilled fallow, and tilled fallow applied in dryland Williams loam (fine-loamy, mixed Typic Argiborolls). Irrigation increased CO(2) flux by 13% compared with non-irrigation by increasing soil water content in North Dakota. Tillage increased CO(2) flux by 62 to 118% compared with no-tillage at both places. The flux was 1.5- to 2.5-fold greater with tilled than with non-tilled treatments following heavy rain or irrigation in North Dakota and 1.5- to 2.0-fold greater with crops than with fallow following substantial rain in Montana. Nitrogen fertilization increased CO(2) flux by 14% compared with no N fertilization in North Dakota and cropping increased the flux by 79% compared with fallow in no-till and 0 kg N ha(-1) in Montana. The CO(2) flux in undisturbed CRP was similar to that in no-tilled crops. Although soil C content was not altered, management practices influenced CO(2) flux within a short period due to changes in soil temperature, water, and nutrient contents. Regardless of irrigation, CO(2) flux can be reduced from croplands to a level similar to that in CRP planting using no-tilled crops with or without N fertilization compared with other management practices.

Among greenhouse gases, carbon dioxide (CO(2)) is one of the most significant contributors to regional and global warming as well as climatic change. A field study was conducted to (i) determine the effect of soil characteristics resulting from changes in soil management practices on CO(2) flux from the soil surface to the atmosphere in transitional land from perennial forages to annual crops, and (ii) develop empirical relationships that predict CO(2) flux from soil temperature and soil water content. The CO(2) flux, soil temperature (T(s)), volumetric soil water content (theta(v)) were measured every 1-2 weeks in no-till (NT) and conventional till (CT) malt barley and undisturbed soil grass-alfalfa (UGA) systems in a Lihen sandy loam soil (sandy, mixed, frigid Entic Haplustoll) under irrigated and non-irrigated conditions in western North Dakota. Soil air-filled porosity (epsilon) was calculated from total soil porosity and theta(v) measurements. Significant differences in CO(2) fluxes between land management practices (irrigation and tillage) were observed on some measurement dates. Higher CO(2) fluxes were detected in CT plots than in NT and UGA treatments immediately after rainfall or irrigation. Soil CO(2) fluxes increased with increasing soil moisture (R(2)=0.15, P0.01) while an exponential relationship was found between CO(2) emission and T(s) (R(2)=0.59). Using a stepwise regression analysis procedure, a significant multiple regression equation was developed between CO(2) flux and theta(v), T(s) (CO(2) flux = e(-3.477+0.123T(s)+6.381theta)(v); R(2)=0.68, Por= 0.01). Not surprisingly, soil temperature was a driving factor in the equation, which accounted for approximately 59% in variation of CO(2) flux. It was concluded that less intensive tillage, such as no-till or strip tillage, along with careful irrigation management will reduce soil CO(2) evolution from land being converted from perennial forages to annual crops.

Simulation models can be used to predict N dynamics in a soil-water-plant system. The simulation accuracy and performance of three models: LEACHM (Leaching Estimation And CHemistry Model), NCSWAP (Nitrogen and Carbon cycling in Soil, Water And Plant), and SOILN to predict NO3-N leaching were evaluated and compared to field data from a 5-yr experiment conducted on a Hagerstown silt loam (fine, mixed, mesic Typic Hapludalf). Nitrate N losses past 1.2 m from N-fertilized and manured corn (Zea mays L.) were measured with zero-tension pan lysimeters for 5 yr. The models were calibrated using 1989-1990 data and validated using 1988-1989, 1990-1991, 1991-1992, and 1992-1993 NO3-N leaching data. Statistical analyses indicated that LEACHM, NCSWAP, and SOILN models were able to provide accurate simulations of annual NO3-N leaching losses below the 1.2-m depth for 8, 9, and 7 of 10 cases, respectively, in the validation years. The inaccuracy in the models' annual simulations for the control and manure treatments seems to be related to inadequate description of processes of N and C transformations in the models' code. The overall performance and accuracy of the SOILN model were worse than those of LEACHM and NCSWAP. The root mean square error (RMSE) and modeling efficiency (ME) were 10.7 and 0.9, 9.5 and 0.93, and 20.7 and 0.63 for LEACHM, NCSWAP, and SOILN, respectively. Overall, the three models have the potential to predict NO3-N losses below 1.2-m depth from fertilizer and manure nitrogen applied to corn without recalibration of models from year to year.

In this paper we examine the lending by small banks to small farms. We find that relationships, as measured by the length of tenure of farm operators, are positively related to bank lending. We also find that denovo banks have a positive tendency to lend to small farms, similar to the tendency of denovo banks to lend to small businesses generally. When existing relationships between borrowers and incumbent lenders are stronger, however, denovo banks have greater difficulties in lending to small farms. Finally, we find that, even within the category of small banks, lending to small farms (as a percentage of a bank's assets) tends to decrease as the bank increases in size. We believe that small farms are a category of small enterprises that have been under researched in the lending literature and that further study of these relationships would yield new and interesting results.

This document is one of two papers on Wharton's FDIC Research Database. Working paper #95-24 reviews the structure and data elements of the database. Supplement #95-24 facilitates its installation and use.