scholarly journals Evaluation of JULES-crop performance against site observations of irrigated maize from Mead, Nebraska

2016 ◽  
Author(s):  
Karina Williams ◽  
Jemma Gornall ◽  
Anna Harper ◽  
Andy Wiltshire ◽  
Debbie Hemming ◽  
...  
Keyword(s):  
Input Parameter ◽  
Model Development ◽  
Crop Productivity ◽  
Crop Model ◽  
Test Model ◽  
Area Index ◽  
Crop Varieties ◽  
Weather And Climate ◽  
Set Up ◽  
The Impact

Abstract. The JULES-crop model (Osborne et al., 2015) is a parameterisation of crops within the Joint UK Land Environment Simulator (JULES), which aims to simulate both the impact of weather and climate on crop productivity and the impact of crop-lands on weather and climate. In this evaluation paper, observations of maize at three FLUXNET sites in Nebraska (US-Ne1, US-Ne2, US-Ne3) are used to test model assumptions and make appropriate input parameter choices. JULES runs are performed for the irrigated sites (US-Ne1 and US-Ne2) both with the crop model switched off (prescribing leaf area index (LAI) and canopy height) and with the crop model switched on. These are compared against GPP and carbon pool FLUXNET observations. We use the results to point to future priorities for model development and describe how our methodology can be adapted to set up model runs for other sites and crop varieties. The implications of our results on the choice of parameters and settings to be used in global runs of JULES-crop are also discussed.

scholarly journals Evaluation of JULES-crop performance against site observations of irrigated maize from Mead, Nebraska

2017 ◽  
Vol 10 (3) ◽  
pp. 1291-1320 ◽  
Author(s):  
Karina Williams ◽  
Jemma Gornall ◽  
Anna Harper ◽  
Andy Wiltshire ◽  
Debbie Hemming ◽  
...  
Keyword(s):  
Input Parameter ◽  
Model Development ◽  
Crop Productivity ◽  
Crop Model ◽  
Test Model ◽  
Area Index ◽  
Crop Varieties ◽  
Weather And Climate ◽  
Set Up ◽  
The Impact

Abstract. The JULES-crop model (Osborne et al., 2015) is a parametrisation of crops within the Joint UK Land Environment Simulator (JULES), which aims to simulate both the impact of weather and climate on crop productivity and the impact of croplands on weather and climate. In this evaluation paper, observations of maize at three FLUXNET sites in Nebraska (US-Ne1, US-Ne2 and US-Ne3) are used to test model assumptions and make appropriate input parameter choices. JULES runs are performed for the irrigated sites (US-Ne1 and US-Ne2) both with the crop model switched off (prescribing leaf area index (LAI) and canopy height) and with the crop model switched on. These are compared against GPP and carbon pool FLUXNET observations. We use the results to point to future priorities for model development and describe how our methodology can be adapted to set up model runs for other sites and crop varieties.

scholarly journals Using the Soil and Water Assessment Tool to Simulate the Pesticide Dynamics in the Data Scarce Guayas River Basin, Ecuador

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 696 ◽  
Author(s):  
Naomi Cambien ◽  
Sacha Gobeyn ◽  
Indira Nolivos ◽  
Marie Anne Eurie Forio ◽  
Mijail Arias-Hidalgo ◽  
...  
Keyword(s):  
River Basin ◽  
Assessment Tool ◽  
Model Development ◽  
Model Performance ◽  
Water Quality Monitoring ◽  
Freshwater Ecosystem ◽  
Set Up ◽  
The Impact ◽  
Water Assessment ◽  
Soil And Water

Agricultural intensification has stimulated the economy in the Guayas River basin in Ecuador, but also affected several ecosystems. The increased use of pesticides poses a serious threat to the freshwater ecosystem, which urgently calls for an improved knowledge about the impact of pesticide practices in this study area. Several studies have shown that models can be appropriate tools to simulate pesticide dynamics in order to obtain this knowledge. This study tested the suitability of the Soil and Water Assessment Tool (SWAT) to simulate the dynamics of two different pesticides in the data scarce Guayas River basin. First, we set up, calibrated and validated the model using the streamflow data. Subsequently, we set up the model for the simulation of the selected pesticides (i.e., pendimethalin and fenpropimorph). While the hydrology was represented soundly by the model considering the data scare conditions, the simulation of the pesticides should be taken with care due to uncertainties behind essential drivers, e.g., application rates. Among the insights obtained from the pesticide simulations are the identification of critical zones for prioritisation, the dominant areas of pesticide sources and the impact of the different land uses. SWAT has been evaluated to be a suitable tool to investigate the impact of pesticide use under data scarcity in the Guayas River basin. The strengths of SWAT are its semi-distributed structure, availability of extensive online documentation, internal pesticide databases and user support while the limitations are high data requirements, time-intensive model development and challenging streamflow calibration. The results can also be helpful to design future water quality monitoring strategies. However, for future studies, we highly recommend extended monitoring of pesticide concentrations and sediment loads. Moreover, to substantially improve the model performance, the availability of better input data is needed such as higher resolution soil maps, more accurate pesticide application rate and actual land management programs. Provided that key suggestions for further improvement are considered, the model is valuable for applications in river ecosystem management of the Guayas River basin.

scholarly journals Calibration of the Crop model in the Community Land Model

2013 ◽  
Vol 6 (1) ◽  
pp. 379-398 ◽  
Author(s):  
X. Zeng ◽  
B. A. Drewniak ◽  
E. M. Constantinescu
Keyword(s):  
Net Ecosystem Exchange ◽  
Crop Productivity ◽  
Crop Model ◽  
Biofuel Production ◽  
Community Land Model ◽  
Terrestrial Carbon Cycle ◽  
Crop Development ◽  
Choose Parameter ◽  
Parameter Values ◽  
The Impact

Abstract. Farming is using more terrestrial ground with increases in population and the expanding use of agriculture for non-nutritional purposes such as biofuel production. This agricultural expansion exerts an increasing impact on the terrestrial carbon cycle. In order to understand the impact of such processes, the Community Land Model (CLM) has been augmented with a CLM-Crop extension that simulates the development of three crop types: maize, soybean, and spring wheat. The CLM-Crop model is a complex system that relies on a suite of parametric inputs that govern plant growth under a given atmospheric forcing and available resources. CLM-Crop development used measurements of gross primary productivity and net ecosystem exchange from AmeriFlux sites to choose parameter values that optimize crop productivity in the model. In this paper we calibrate these values in order to provide a faithful projection in terms of both plant development and net carbon exchange, using a Markov chain Monte Carlo technique.

Multiobjective Optimization for Duct and Strut Design of an Annular Exhaust Diffuser

2012 ◽  
Author(s):  
Philipp Schaefer ◽  
Willy H. Hofmann ◽  
Peter-Anton Gieß
Keyword(s):  
Experimental Data ◽  
Multiobjective Optimization ◽  
Evolutionary Strategies ◽  
Test Model ◽  
Heavy Duty ◽  
Aerodynamic Optimization ◽  
Inlet Conditions ◽  
Heavy Duty Gas Turbine ◽  
Set Up ◽  
The Impact

This paper describes the aerodynamic optimization of a typical exhaust diffuser for a heavy duty gas turbine. The objective is to maximize diffuser performance and, in this way, pressure recovery by optimizing the geometry for two given inlet conditions. To validate and adjust the numerical set-up, experimental data from measurements on the test model is used. The numerical results obtained by using TRACE compares with the experimental results. An optimization process is applied using the framework AutoOpti developed by DLR, which combines evolutionary strategies with surrogate models in order to select optimal geometric parameters. Finally, the differences between the baseline and several optimized designs are discussed and the impact of different parameters on diffuser performance is demonstrated.

scholarly journals Lime and Organic Manure Amendment: A Potential Approach for Sustaining Crop Productivity of the T. Aman-Maize-Fallow Cropping Pattern in Acidic Piedmont Soils

2021 ◽  
Vol 13 (17) ◽  
pp. 9808
Author(s):  
Mohammad Rafiqul Islam ◽  
Afsana Akter ◽  
Mohammad Anamul Hoque ◽  
Sumaiya Farzana ◽  
Shihab Uddin ◽  
...  
Keyword(s):  
Acid Soil ◽  
Poultry Manure ◽  
Acid Soils ◽  
Crop Productivity ◽  
Organic Manure ◽  
Cow Dung ◽  
Cropping Pattern ◽  
Yield Increase ◽  
Set Up ◽  
The Impact

Acid soil is a hindrance to agricultural productivity and a threat to food and environmental security. Research was carried out to assess the impact of lime and organic manure (OM) amendments on yield and nutrient uptake by using the T. Aman-Maize-Fallow cropping pattern in acid soils. The experiment was set up in an RCBD design and used nine treatments and three replications. The treatments, comprising of various doses of lime, OM (cow dung and poultry manure), and a lime-OM combination, were applied to the first crop, T. Aman (Binadhan 7), and in the next crop, maize (BARI Hybrid Maize-9), the residual impacts of the treatments were assessed. Results demonstrate that the highest grain yield, 4.84 t ha−1 (13.61% increase over control) was recorded for T. Aman and 8.38 t ha−1 (58.71% increase over control) for maize, was achieved when dololime was applied in combination with poultry manure. The total rice equivalent yield increase over the control ranged from 20.5% to 66.1%. The application of lime with cow dung or poultry manure considerably enhanced N, P, K, and S content and uptake in both crops, compared to the control. Thus, it may be inferred that using dololime in association with poultry manure can increase crop productivity in acid soils.

scholarly journals Evaluation of photosynthetic photon flux in lettuce cultivation at different shading levels

2020 ◽  
Vol 38 (1) ◽  
pp. 65-70
Author(s):  
Nilton Nélio Cometti ◽  
Josimar V da Silva ◽  
Everaldo Zonta ◽  
Raphael MA Cessa
Keyword(s):  
Flux Measurement ◽  
Crop Productivity ◽  
Photon Flux ◽  
Ambient Conditions ◽  
Photosynthetic Photon Flux ◽  
Transparent Plastic ◽  
Limit Value ◽  
Protected Cultivation ◽  
Set Up ◽  
The Impact

ABSTRACT Protected cultivation has grown in Brazil. Generally, greenhouses are covered with transparent plastic film and shading screen. The plastic, over time, loses its transparency due to pollution residues, dust and other debris. The loss of transparency reduces lightness, photosynthesis and leads to losses of productivity and product quality. The losses are not always detectable by the farmer. Additionally, internal shading screens are used to reduce heating transmission to the ground. The objective of this study was to evaluate the impact of shading on lettuce crop productivity and to determine the optimum shading to reach the highest productivity. Plots were set up inside and outside the greenhouse, with four shading levels with black screens (0, 35, 50 and 75%). The treatments were converted to real shading from the photosynthetic photon flux measurement. The results of fresh and dry phytomass were treated and analyzed by regression as a function of the real shading. In ambient conditions of photosynthetic photon fluxes around 1000 μmol m-2 s-1, reaching up to 2000 μmol m-2 s-1 at some hours of the day, typical of tropical environment, lettuce may support a shading of up to 50% without risk of productivity reduction; under these conditions, shading between 20 and 35% is beneficial, and can guarantee its maximum productivity in lettuce cultivation. It is recommended that the lettuce producer in protected cultivation monitors the shelf life of the plastic, avoiding that the shading exceeds 50%. In order to compare shading experiments, one should use the incident photon flux (FFI) for the whole crop cycle, indicating the minimum limit value of FFI = 600 mol m-2 cycle-1 for the crispy lettuce at an average temperature close to 21oC.

scholarly journals Wheat Varietal Diversification Increases Ethiopian Smallholders’ Food Security: Evidence from a Participatory Development Initiative

2021 ◽  
Vol 13 (3) ◽  
pp. 1029 ◽  
Author(s):  
Elisabetta Gotor ◽  
Muhammed Abdella Usman ◽  
Martina Occelli ◽  
Basazen Fantahun ◽  
Carlo Fadda ◽  
...  
Keyword(s):  
Food Security ◽  
Development Program ◽  
Crop Productivity ◽  
Participatory Development ◽  
Wheat Crop ◽  
Robust Estimator ◽  
Crop Varieties ◽  
Effective Role ◽  
Doubly Robust ◽  
The Impact

This study assesses the impact of a participatory development program called Seeds For Needs, carried out in Ethiopia to support smallholders in addressing climate change and its consequences through the introduction, selection, use, and management of suitable crop varieties. More specifically, it analyzes the program’s role of boosting durum wheat varietal diversification and agrobiodiversity to support higher crop productivity and strengthen smallholder food security. The study is based on a survey of 1008 households across three major wheat-growing regional states: Amhara, Oromia, and Tigray. A doubly robust estimator was employed to properly estimate the impact of Seeds For Needs interventions. The results show that program activities have significantly enhanced wheat crop productivity and smallholders’ food security by increasing wheat varietal diversification. This paper provides further empirical evidence for the effective role that varietal diversity can play in improving food security in marginal environments, and also provides clear indications for development agencies regarding the importance of improving smallholders’ access to crop genetic resources.

scholarly journals Estimation of Forest LAI Using Discrete Airborne LiDAR: A Review

2021 ◽  
Vol 13 (12) ◽  
pp. 2408
Author(s):  
Luo Tian ◽  
Yonghua Qu ◽  
Jianbo Qi
Keyword(s):  
Forest Canopy ◽  
Input Parameter ◽  
3D Structure ◽  
Tree Height ◽  
Heterogeneous Data ◽  
Airborne Lidar ◽  
Area Index ◽  
Cloud Data ◽  
Time Space ◽  
The Impact

The leaf area index (LAI) is an essential input parameter for quantitatively studying the energy and mass balance in soil-vegetation-atmosphere transfer systems. As an active remote sensing technology, light detection and ranging (LiDAR) provides a new method to describe forest canopy LAI. This paper reviewed the primary LAI retrieval methods using point cloud data (PCD) obtained by discrete airborne LiDAR scanner (DALS), its validation scheme, and its limitations. There are two types of LAI retrieval methods based on DALS PCD, i.e., the empirical regression and the gap fraction (GF) model. In the empirical model, tree height-related variables, LiDAR penetration indexes (LPIs), and canopy cover are the most widely used proxy variables. The height-related proxies are used most frequently; however, the LPIs proved the most efficient proxy. The GF model based on the Beer-Lambert law has been proven useful to estimate LAI; however, the suitability of LPIs is site-, tree species-, and LiDAR system-dependent. In the local validation in previous studies, poor scalability of both empirical and GF models in time, space, and across different DALS systems was observed, which means that field measurements are still needed to calibrate both types of models. The method to correct the impact from the clumping effect and woody material using DALS PCD and the saturation effect for both empirical and GF models still needs further exploration. Of most importance, further work is desired to emphasize assessing the transferability of published methods to new geographic contexts, different DALS sensors, and survey characteristics, based on figuring out the influence of each factor on the LAI retrieval process using DALS PCD. In addition, from a methodological perspective, taking advantage of DALS PCD in characterizing the 3D structure of the canopy, making full use of the ability of machine learning methods in the fusion of multisource data, developing a spatiotemporal scalable model of canopy structure parameters including LAI, and using multisource and heterogeneous data are promising areas of research.

scholarly journals Modulating Drought Stress Response of Maize by a Synthetic Bacterial Community

2021 ◽  
Vol 12 ◽  
Author(s):  
Jaderson Silveira Leite Armanhi ◽  
Rafael Soares Correa de Souza ◽  
Bárbara Bort Biazotti ◽  
Juliana Erika de Carvalho Teixeira Yassitepe ◽  
Paulo Arruda
Keyword(s):  
Drought Stress ◽  
Crop Productivity ◽  
Temporal Variations ◽  
Plant Responses ◽  
Temporal Data ◽  
Water Usage ◽  
Flow Modulation ◽  
Non Invasive ◽  
Set Up ◽  
The Impact

Plant perception and responses to environmental stresses are known to encompass a complex set of mechanisms in which the microbiome is involved. Knowledge about plant physiological responses is therefore critical for understanding the contribution of the microbiome to plant resilience. However, as plant growth is a dynamic process, a major hurdle is to find appropriate tools to effectively measure temporal variations of different plant physiological parameters. Here, we used a non-invasive real-time phenotyping platform in a one-to-one (plant–sensors) set up to investigate the impact of a synthetic community (SynCom) harboring plant-beneficial bacteria on the physiology and response of three commercial maize hybrids to drought stress (DS). SynCom inoculation significantly reduced yield loss and modulated vital physiological traits. SynCom-inoculated plants displayed lower leaf temperature, reduced turgor loss under severe DS and a faster recovery upon rehydration, likely as a result of sap flow modulation and better water usage. Microbiome profiling revealed that SynCom bacterial members were able to robustly colonize mature plants and recruit soil/seed-borne beneficial microbes. The high-resolution temporal data allowed us to record instant plant responses to daily environmental fluctuations, thus revealing the impact of the microbiome in modulating maize physiology, resilience to drought, and crop productivity.

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