MODELING OF AGRICULTURAL SYSTEMS

The authors present an overview of agricultural systems models. Beginning with why systems are modeled and for what purposes, the paper examines types of agricultural systems and associated model types. The broad categories range from pictorial (iconic) models to descriptive analogue models to symbolic (usually mathematical) models. The uses of optimization versus non-optimizing mechanistic models are reviewed, as are the scale and aggregation challenges associated with scaling up from the plant cell to the landscape or from a farm enterprise to a world market supply-demand equilibrium Recent modeling developments include the integration of formerly stand-alone biophysical simulation models, increasingly with a unifying spatial database and often for the purpose of supporting management decisions. Current modeling innovations are estimating and incorporating environmental values and other system interactions. At the community and regional scale, sociological and economic models of rural community structure are being developed to evaluate long-term community viability. The information revolution is bringing new challenges in delivering agricultural systems models over the internet, as well as integrating decision support systems with the new precision agriculture technologies.Farm Management,

Modelling soil water conent in a tomato field: proximal gamma ray spectroscopy and soil-crop system models

Proximal soil sensors are taking hold in the understanding of soil hydrogeological processes involved in precision agriculture. In this context, permanently installed gamma ray spectroscopy stations represent one of the best space-time trade off methods at field scale. This study proved the feasibility and reliability of soil water content monitoring through a seven-month continuous acquisition of terrestrial gamma radiation in a tomato test field. By employing a 1 L sodium iodide detector placed at a height of 2.25 m, we investigated the gamma signal coming from an area having a ~25 m radius and from a depth of approximately 30 cm. Experimental values, inferred after a calibration measurement and corrected for the presence of biomass, were corroborated with gravimetric data acquired under different soil moisture conditions, giving an average absolute discrepancy of about 2%. A quantitative comparison was carried out with data simulated by AquaCrop, CRITeRIA, and IRRINET soil-crop system models. The different goodness of fit obtained in bare soil condition and during the vegetated period highlighted that CRITeRIA showed the best agreement with the experimental data over the entire data-taking period while, in presence of the tomato crop, IRRINET provided the best results.Comment: 18 pages, 9 Figures, 3 Table

Optimizing the bioenergy water footprint by selecting SRC willow canopy phenotypes: regional scenario simulations

© The Author(s) 2019. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.Background and Aims: Bioenergy is central for the future energy mix to mitigate climate change impacts; however, its intricate link with the water cycle calls for an evaluation of the carbon–water nexus in biomass production. The great challenge is to optimize trade-offs between carbon harvest and water use by choosing cultivars that combine low water use with high productivity. Methods: Regional scenarios were simulated over a range of willow genotype × environment interactions for the major UK soil × climate variations with the process-based model LUCASS. Soil available water capacity (SAWC) ranged from 51 to 251 mm and weather represented the north-west (wet, cool), north-east (dry, cool), south-west (wet, warm) and south-east (dry, warm) of the UK. Scenario simulations were evaluated for small/open narrow-leaf (NL) versus large/closed broad-leaf (BL) willow canopy phenotypes using baseline (1965–89) and warmer recent (1990–2014) weather data. Key Results: The low productivity under baseline climate in the north could be compensated by choosing BL cultivars (e.g. ‘Endurance’). Recent warmer climate increased average productivity by 0.5–2.5 t ha−1, especially in the north. The modern NL cultivar ‘Resolution’ had the smallest and most efficient water use. On marginal soils (SAWC <100 mm), yields remained below an economic threshold of 9 t ha−1 more frequently under baseline than recent climate. In the drought-prone south-east, ‘Endurance’ yielded less than ‘Resolution’, which consumed on average 17 mm year−1 less water. Assuming a planting area of 10 000 ha, in droughty years between 1.3 and 4.5 × 106 m3 of water could be saved, with a small yield penalty, for ‘Resolution’. Conclusions: With an increase in air temperature and occasional water scarcities expected with climate change, high-yielding NL cultivars should be the preferred choice for sustainable use of marginal lands and reduced competition with agricultural food crops.Peer reviewedFinal Published versio

OPTIMIZING COMPLEX BIOECONOMIC SIMULATIONS USING AN EFFICIENT SEARCH HEURISTIC

For simulation to be truly useful for investigating many problems in agricultural economics, non-simplifying optimization techniques need to be employed. General methods for simulation optimization that do not inhibit system characterization or analysis are available, and they would appear to provide much of the mathematical and optimizing rigor demanded by economists. This paper describes the theory and algorithm of a robust and efficient simulation optimization approach, the Complex Method. An example of implementing the algorithm is illustrated using a pest management problem.simulation, optimization, Complex Method, hill-climbing, Research Methods/ Statistical Methods,

A BIOTIC CONTROL PERSPECTIVE ON NITRATE CONTAMINATION OF GROUNDWATER FROM AGRICULTURAL PRODUCTION

Agronomists consider the continuity and nutrient capturing properties of cover crops as important determinants of nutrient cycling in agricultural systems. Managing for these biotic control functions can help limit nutrient loss and groundwater contamination between main crop harvests. This simulation study highlights the potential role of cover crop management in a welfare economics framework. The objective is to find the optimal combination of nutrient input to the main crop, the extent of off-season cover crops, and crop functional diversity to maximize the sum of benefits from agricultural production and groundwater protection.Crop Production/Industries,

Climate Services for Resilient Development (CSRD) Partnership’s work in Latin America

The Climate Services for Resilient Development (CSRD) Partnership is a private-public collaboration led by USAID, which aims to increase resilience to climate change in developing countries through the development and dissemination of climate services. The partnership began with initial projects in three countries: Colombia, Ethiopia, and Bangladesh. The International Center for Tropical Agriculture (CIAT) was the lead organization for the Colombian CSRD efforts – which then expanded to encompass work in the whole Latin American region

Effect of crop management practices on the sustainability and environmental impact of organic and low input food production systems

While organic farming can reduce many of the environmental problems caused by agriculture, organic farming also includes some practices which are questionable in terms of environmental effects. Organic farming practices (rotations, fertilisation regimes, cover crop use) can differ significantly and this leads to large differences in its environmental effects. This leaves considerable scope to improve the environmental effects of organic farming. The environmental aspects of organic farming are discussed, and model simulations are used to illustrate how even moderate changes in organic rotations can have large effects on sustainability, here measured by a simple index of nitrogen lost by leaching relative to nitrogen harvested by the crops. In WP3.3.4 we are working to improve model simulation of organic rotations, and in WP7.1 we are making environmental assessment of organic cropping practices tested in the QLIF project, using model simulations and other approaches

A MAS model for optimizing the spatial aspects of livestock production and manure abatement

As a consequence of the EU Nitrates Directive many countries have developed policies to regulate manure production and manure emission on land. Farmers have three allocation options: spreading manure on own land, transporting manure to other farmers’ land and processing manure. To better understand the manure problem as an allocation problem a spatial mathematical programming multi-agent model has been developed. The model is applied for Flanders (Belgium), a highly concentrated livestock area. Using this model, policy alternatives and their cost efficiency can be evaluated. These simulations result in advice on location and type of manure processing and an indicator which creates transparency in the manure and processing market

Crop Rotations and Dynamic Analysis of Southeastern Peanut Farms

Agricultural policy objectives provide green payment incentives for farmers to initiate practices with environmental benefits. Velvet beans planted as a cover crop offer an alternative for southeastern peanut farmers to control nematodes without chemicals, while increasing soil fertility. Commodity programs provide government payments that are essential to rural economies of the southeast.Environmental Economics and Policy,