Robust estimates of soil moisture and latent heat flux coupling strength obtained from triple collocation

Land surface models (LSMs) are often applied to predict the one-way coupling strength between surface soil moisture (SM) and latent heat (LH) flux. However, the ability of LSMs to accurately represent such coupling has not been adequately established. Likewise, the estimation of SM/LH coupling strength using ground-based observational data is potentially compromised by the impact of independent SM and LH measurements errors. Here we apply a new statistical technique to acquire estimates of one-way SM/LH coupling strength which are nonbiased in the presence of random error using a triple collocation approach based on leveraging the simultaneous availability of independent SM and LH estimates acquired from (1) LSMs, (2) satellite remote sensing, and (3) ground-based observations. Results suggest that LSMs do not generally overestimate the strength of one-way surface SM/LH coupling

Changes In Nitrogen Use Efficiency And Soil Quality After Five Years Of Managing For High Yield Corn And Soybean

Average corn grain yields in the USA have increased linearly at a rate of 1.7 bu/acre over the past 35 years with a national yield average of 140 bu/acre. Corn yield contest winners and simulation models, however, indicate there is ~100 bu/a in exploitable corn yield gap. Four years (1999-2002) of plant development, grain yield and nutrient uptake were compared in intensive irrigated maize systems representing (a) recommended best management practices for a yield goal of 200 bu/acre (M1) and (b) intensive management aiming at a yield goal of 300 bu/acre (M2). For each management level, three levels of plant density (30000-P1, 37000-P2 and 44000-P3 seed/acre) were compared in a continuous corn and corn- soybean rotation. Over five years, the grain yields increased 11% as a function of management and this effect was manifest under higher plant densities. A high yield of 285 bu/acre was achieved at the M2, P2 treatment in 2003. Higher population resulted in greater demand for N and K per unit grain yield. Over the past five years, nitrogen use efficiency has steadily improved in the M2 treatment due to improvements in soil quality. Intensive management and population levels significantly increased residue carbon inputs with disproportionately lower soil respiration. Closing the yield gap requires higher plant population and improved nutrient management to maintain efficient and profitable improvement in maize production. Soil quality improvements and higher residue inputs under intensive management should make this task easier with time

Corn Yield Potential and Optimal Soil Productivity in Irrigated Corn/Soybean Systems

In 1999, an interdisciplinary research team at the University of Nebraska established a field experiment to (1) quantify and understand the yield potential of corn and soybean under irrigated conditions, (2) identify efficient crop management practices to achieve yields that approach potential levels, and (3) determine the energy use efficiency, global warming and soil C-sequestration potential of intensively managed corn systems. The experiment compares systems that represent different levels of management intensity expressed as combinations of crop rotation (continuous corn, corn-soybean), plant density (low, medium, high) and nutrient management (recommended best management vs. intensive management). Detailed measurements include soil nutrient dynamics and C balance, crop growth and development, nutrient uptake and components of yield of corn and soybean, radiation use efficiency, soil surface fluxes of greenhouse gases, root biomass, C inputs through crop residues, translocation of non-structural carbohydrates, and amount, composition and activity of the microbial biomass. Selected results for corn are presented

Corn Yield Potential and Optimal Soil Productivity in Irrigated Corn/Soybean Systems

In 1999, an interdisciplinary research team at the University of Nebraska established a field experiment to (1) quantify and understand the yield potential of corn and soybean under irrigated conditions, (2) identify efficient crop management practices to achieve yields that approach potential levels, and (3) determine the energy use efficiency, global warming and soil C-sequestration potential of intensively managed corn systems. The experiment compares systems that represent different levels of management intensity expressed as combinations of crop rotation (continuous corn, corn-soybean), plant density (low, medium, high) and nutrient management (recommended best management vs. intensive management). Detailed measurements include soil nutrient dynamics and C balance, crop growth and development, nutrient uptake and components of yield of corn and soybean, radiation use efficiency, soil surface fluxes of greenhouse gases, root biomass, C inputs through crop residues, translocation of non-structural carbohydrates, and amount, composition and activity of the microbial biomass. Selected results for corn are presented

Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites

Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements taken at individual eddy-covariance sites reflect model- or satellite-based grid cells? We evaluate flux footprints—the temporally dynamic source areas that contribute to measured fluxes—and the representativeness of these footprints for target areas (e.g., within 250–3000 m radii around flux towers) that are often used in flux-data synthesis and modeling studies. We examine the land-cover composition and vegetation characteristics, represented here by the Enhanced Vegetation Index (EVI), in the flux footprints and target areas across 214 AmeriFlux sites, and evaluate potential biases as a consequence of the footprint-to-target-area mismatch. Monthly 80% footprint climatologies vary across sites and through time ranging four orders of magnitude from 103 to 107 m2 due to the measurement heights, underlying vegetation- and ground-surface characteristics, wind directions, and turbulent state of the atmosphere. Few eddy-covariance sites are located in a truly homogeneous landscape. Thus, the common model-data integration approaches that use a fixed-extent target area across sites introduce biases on the order of 4%–20% for EVI and 6%–20% for the dominant land cover percentage. These biases are site-specific functions of measurement heights, target area extents, and land-surface characteristics. We advocate that flux datasets need to be used with footprint awareness, especially in research and applications that benchmark against models and data products with explicit spatial information. We propose a simple representativeness index based on our evaluations that can be used as a guide to identify site-periods suitable for specific applications and to provide general guidance for data use

Comparison and Hybridization of Two Approaches for Maize Simulation

Two approaches dominate simulation modeling of maize growth: (1) a generic approach, represented by the family of crop models developed by Dutch scientists at the Wageningen University, e.g. SUCROS (Spitters et al, 1989), WOFOST (Diepen et al, 1989) and INTERCOM (Kropff and van Laar, 1993), and (2) a maize-specific approach, represented by CERES-Maize (Jones and Kiniry, 1986) and its derivatives such as the maize module in DSSAT, and the MSB model developed by Muchow et al. (Muchow et al, 1990). These two approaches differ in three aspects. First, maize development in generic models is driven primarily by availability of assimilate from photosynthesis, while temperature is the primary driving force in the maize-specific models. Second, growth respiration and maintenance respiration are explicitly accounted for in the generic models to determine net dry matter production, while the maize-specific approach derives net dry matter production directly from intercepted solar radiation by means of a fixed value of radiation use efficiency (RUE) that implicitly accounts for respiration costs. Third, the generic approach requires phenology specification of growing degree days (GDD) to anthesis and does not consider hybrid differences in traits such as sensitivity to daytime length, potential number of kernels and potential grain filling rate, while the maize-specific approach requires specification or estimation of several phonological events and hybrid-specific parameters. A generic model (INTERCOM) and a maize-specific model (CERES-Maize, standard version) were evaluated with regard to their requirements for input parameters and their accuracy in predicting maize dry matter accumulation, leaf area expansion, and final grain and stover yields. Detailed field measurements from a 3-year study in which maize was grown with minimal possible stress were used for validation. Results suggest that CERES-Maize, in which temperature determines the potential leaf and stem growth, performed better than INTERCOM in which availability of assimilate is the primary driving force. In contrast, the separate routines for photosynthesis and respiration in INTERCOM provided greater sensitivity for crop response to temperature than CERES-Maize, which mostly relies on a fixed value of RUE for determining dry matter accumulation. Whereas INTERCOM requires specification of (GDD) to anthesis as an input parameter, CERES-Maize predicts anthesis from the GDD interval from emergence to end of the juvenile phase, and this ’juvenile-phase’ parameter is not readily available for most hybrids

Robust estimates of soil moisture and latent heat flux coupling strength obtained from triple collocation

Land surface models (LSMs) are often applied to predict the one-way coupling strength between surface soil moisture (SM) and latent heat (LH) flux. However, the ability of LSMs to accurately represent such coupling has not been adequately established. Likewise, the estimation of SM/LH coupling strength using ground-based observational data is potentially compromised by the impact of independent SM and LH measurements errors. Here we apply a new statistical technique to acquire estimates of one-way SM/LH coupling strength which are nonbiased in the presence of random error using a triple collocation approach based on leveraging the simultaneous availability of independent SM and LH estimates acquired from (1) LSMs, (2) satellite remote sensing, and (3) ground-based observations. Results suggest that LSMs do not generally overestimate the strength of one-way surface SM/LH coupling

Test of the Hybrid-Maize Model for Simulation of Soil Moisture Dynamics and Maize Response to Water Deficit

The Hybrid-Maize model (Yang et al, 2004), which has been validated under optimal water conditions, was evaluated for its ability to simulate soil moisture dynamics in the root zone and effects of water deficits on maize development and final yields (Fig. 1). The experimental data for this evaluation were obtained from ongoing field studies of the Carbon Sequestration Program (CSP) at the University of Nebraska. The studies include three cropping systems, each located in a quarter-section field (57 ha), two of which are irrigated by central-pivots and the third is rainfed. One irrigated field is in continuous maize and the other two are maize-soybean rotation. In each field, detailed micro-meteorological measurements were made, and soil moisture is continuously monitored at 10, 25, 50 and 100cm depths year around. Maize crop phenological development, leaf area expansion and aboveground biomass were measured nine times each growing season from 2001-2003, and final grain yield and stover biomass were measured at physiological maturity

Understanding and Managing Corn Yield Potential

Rainfed and irrigated systems in which corn is grown either in rotation with soybean or as a continuous monocrop are the predominant cropping systems in North America. About 30 million ha of corn are harvested annually for grain in the USA, of which eleven states in the Corn Belt produce more than 210 million tons or 35% of the global corn supply (Dobermann and Cassman, 2002). During the past 35 years, average corn yields have increased linearly at a rate of 1.7 bu/acre per year (109 kg ha-1 per year, Fig. 1). Average corn yields now approach 140 bu/acre (8.8 t ha-1), but progressive farmers routinely harvest 160 to 220 bu/acre (10 to 14 t ha--1)

Understanding Corn Yield Potential And Optimal Soil Productivity In Irrigated Corn Systems

In 1999, a field experiment was established to (I) quantify and understand the yield potential of corn and soybean under irrigated conditions, (2) identify efficient crop management practices to achieve yields that approach potential levels, and (3) determine the energy use efficiency, global warming and soil C-sequestration potential of intensively managed corn systems. The experiment compares systems that represent different levels of management intensity expressed as combinations of crop rotation (continuous corn, corn-soybean), plant density (low. medium. high) and nutrient management (recommended best management vs. intensive management). Detailed measurements include soil nutrient dynamics and C balance, crop growth and development, nutrient uptake and components of yield of corn and soybean, radiation use efficiency, soil surface fluxes of greenhouse gases, root biomass, C inputs through crop residues, translocation of non-structural carbohydrates, and amount, composition and activity of the microbial biomass. Data collected from 1999 to 2001 suggest that 0) current fertilizer recommendations do not allow expression of full attainable yield, (ii) high corn yields require higher plant density (37,000 to 44,000 plants/acre) and greater N and K uptake per unit yield, (iii) existing corn growth simulation models underestimate the actual dry matter production and yield measured at near-optimum growth conditions in the field, and (iv) the potential to increase C sequestration is greatest in continuous corn systems with intensive managemen