Ignacio J. Lorite

Andalusian Institute of Agricultural and Fisheries Research and Training

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C. Santos

Andalusian Institute of Agricultural and Fisheries Research and Training

Elías Fereres

Consejo Superior de Investigaciones Científicas

Margarita Ruiz‐Ramos

Universidad Politécnica de Madrid

Clara Gabaldón‐Leal

University of Castilla-La Mancha

F. Orgaz

Instituto de Agricultura Sostenible

Luca Testi

Instituto de Agricultura Sostenible

Juan Miguel Ramírez-Cuesta

Centre d'Investigacions sobre Desertificació

Richard G. Allen

University of Idaho

Mónica Espadafor

University of Liège

Alfredo Rodríguez

University of Castilla-La Mancha

Cooperative Institutions

Finnish Environment Institute

Andalusian Institute of Agricultural and Fisheries Research and Training

Junta de Andalucía

University of Córdoba

Instituto de Agricultura Sostenible

Consejo Superior de Investigaciones Científicas

Natural Resources Institute Finland

Leibniz Centre for Agricultural Landscape Research

University of Bonn

Agriculture and Food

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Quantifying sustainable intensification of agriculture: The contribution of metrics and modelling

Ecological Indicators (2021)

Ioanna Mouratiadou Catharina Latka Floor van der Hilst Christoph Müller Regine Berges

Sustainable intensification (SI) of agriculture is a promising strategy for boosting the capacity of the agricultural sector to meet the growing demands for food and non-food products and services in a sustainable manner. Assessing and quantifying the options for SI remains a challenge due to its multiple dimensions and potential associated trade-offs. We contribute to overcoming this challenge by proposing an approach for the ex-ante evaluation of SI options and trade-offs to facilitate decision making in relation to SI. This approach is based on the utilization of a newly developed SI metrics framework (SIMeF) combined with agricultural systems modelling. We present SIMeF and its operationalization approach with modelling and evaluate the approach’s feasibility by assessing to what extent the SIMeF metrics can be quantified by representative agricultural systems models. SIMeF is based on the integration of academic and policy indicator frameworks, expert opinions, as well as the Sustainable Development Goals. Structured along seven SI domains and consisting of 37 themes, 142 sub-themes and 1128 metrics, it offers a holistic, generic, and policy-relevant dashboard for selecting the SI metrics to be quantified for the assessment of SI options in diverse contexts. The use of SIMeF with agricultural systems modelling allows the ex-ante assessment of SI options with respect to their productivity, resource use efficiency, environmental sustainability and, to a large extent, economic sustainability. However, we identify limitations to the use of modelling to represent several SI aspects related to social sustainability, certain ecological functions, the multi-functionality of agriculture, the management of losses and waste, and security and resilience. We suggest advancements in agricultural systems models and greater interdisciplinary and transdisciplinary integration to improve the ability to quantify SI metrics and to assess trade-offs across the various dimensions of SI.

Ex-ante

10.1016/j.ecolind.2021.107870

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Citations (30)

Analyzing the impact of extreme heat events and drought on wheat yield and protein concentration, and adaptation strategies using long-term cultivar trials under semi-arid conditions

Agricultural and Forest Meteorology (2022)

Ignacio J. Lorite A. Castilla José M. Cabezas José O. Alza C. Santos

10.1016/j.agrformet.2022.109279

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Citations (9)

Estimating actual irrigation application by remotely sensed evapotranspiration observations

Agricultural Water Management (2010)

P. Droogers Walter W. Immerzeel Ignacio J. Lorite

Irrigation scheduling

Irrigation district

10.1016/j.agwat.2010.03.017

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Citations (121)

Strategies for adapting maize to climate change and extreme temperatures in Andalusia, Spain

Climate Research (2015)

Clara Gabaldón‐Leal Ignacio J. Lorite M. Inés Mínguez JI Lizaso Alessandro Dosio

CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials CR 65:159-173 (2015) - DOI: https://doi.org/10.3354/cr01311 Contribution to the CR Special: 'Modelling climate change impacts for food security' Strategies for adapting maize to climate change and extreme temperatures in Andalusia, Spain C. Gabaldón-Leal1,*, I. J. Lorite1, M. I. Mínguez2, J. I. Lizaso2, A. Dosio3, E. Sanchez4, M. Ruiz-Ramos2 1IFAPA-Centro Alameda del Obispo, Junta de Andalucía, P.O. Box 3092, 14080 Córdoba, Spain 2AgSystems-CEIGRAM, Technical University of Madrid, 28040 Madrid, Spain 3European Commission Joint Research Centre, Institute for Environment and Sustainability, 21027 Ispra, Italy 4Faculty of Environmental Sciences and Biochemistry, University of Castilla-La Mancha, 45071 Toledo, Spain *‑Corresponding author: clara.gabaldon@juntadeandalucia.es ABSTRACT: Climate projections indicate that rising temperatures will affect summer crops in the southern Iberian Peninsula. The aim of this study was to obtain projections of the impacts of rising temperatures, and of higher frequency of extreme events on irrigated maize, and to evaluate some adaptation strategies. The study was conducted at several locations in Andalusia using the CERES-Maize crop model, previously calibrated/validated with local experimental datasets. The simulated climate consisted of projections from regional climate models from the ENSEMBLES project; these were corrected for daily temperature and precipitation with regard to the E-OBS observational dataset. These bias-corrected projections were used with the CERES-Maize model to generate future impacts. Crop model results showed a decrease in maize yield by the end of the 21st century from 6 to 20%, a decrease of up to 25% in irrigation water requirements, and an increase in irrigation water productivity of up to 22%, due to earlier maturity dates and stomatal closure caused by CO2 increase. When adaptation strategies combining earlier sowing dates and cultivar changes were considered, impacts were compensated, and maize yield increased up to 14%, compared with the baseline period (1981-2010), with similar reductions in crop irrigation water requirements. Effects of extreme maximum temperatures rose to 40% at the end of the 21st century, compared with the baseline. Adaptation resulted in an overall reduction in extreme Tmax damages in all locations, with the exception of Granada, where losses were limited to 8%. KEY WORDS: Climate change · Impact · Adaptation · Maize · Crop model · Regional climate model · Extreme temperature Full text in pdf format PreviousNextCite this article as: Gabaldón-Leal C, Lorite IJ, Mínguez MI, Lizaso JI, Dosio A, Sanchez E, Ruiz-Ramos M (2015) Strategies for adapting maize to climate change and extreme temperatures in Andalusia, Spain. Clim Res 65:159-173. https://doi.org/10.3354/cr01311 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in CR Vol. 65. Online publication date: September 28, 2015 Print ISSN: 0936-577X; Online ISSN: 1616-1572 Copyright © 2015 Inter-Research.

Peninsula

Representative Concentration Pathways

10.3354/cr01311

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Citations (24)

Evaluation of three simulation approaches for assessing yield of rainfed sunflower in a Mediterranean environment for climate change impact modelling

Climatic Change (2014)

J. Garcı́a López Ignacio J. Lorite R. García-Ruiz J. Domı́nguez

Empirical modelling

Rainfed agriculture

Mediterranean Basin

Representative Concentration Pathways

10.1007/s10584-014-1067-6

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Citations (50)

Almond responses to a single season of severe irrigation water restrictions

Irrigation Science (2021)

David Moldero Álvaro López‐Bernal Luca Testi Ignacio J. Lorite Elías Fereres

Orchard

Growing season

10.1007/s00271-021-00750-2

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Citations (13)

Regional calibration of Hargreaves equation for estimating reference ET in a semiarid environment

Agricultural Water Management (2005)

Pablo Jiménez‐Gavilán Ignacio J. Lorite S. Tornero J. Berengena

Penman–Monteith equation

Maxima

10.1016/j.agwat.2005.05.001

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Citations (305)

Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC)—Applications

Journal of Irrigation and Drainage Engineering (2007)

Richard G. Allen Masahiro Tasumi Anthony Morse Ricardo Trezza James L. Wright

Recent satellite image processing developments have provided the means to calculate evapotranspiration (ET) as a residual of the surface energy balance to produce ET "maps." These ET maps (i.e., images) provide the means to quantify ET on a field by field basis in terms of both the rate and spatial distribution. The ET images show a progression of ET during the year or growing season as well as its spatial distribution. The mapping evapotranspiration at high resolution with internalized calibration (METRIC) is a satellite-based image-processing procedure for calculating ET. METRIC has been applied with high resolution Landsat images in southern Idaho, southern California, and New Mexico to quantify monthly and seasonal ET for water rights accounting, operation of ground water models, and determination of crop coefficient populations and mean curves for common crops. Comparisons between ET by METRIC, ET measured by lysimeter, and ET predicted using traditional methods have been made on a daily and monthly basis for a variety of crop types and land uses. Error in estimated growing season ET was 4% for irrigated meadow in the Bear River basin of Idaho and 1% for an irrigated sugar beet crop near Kimberly, Id. Standard deviation of error for time periods represented by each satellite image averaged about 13 to 20% in both applications. The results indicate that METRIC and similar methods such as SEBAL hold substantial promise as efficient, accurate, and inexpensive procedures to estimate actual evaporation fluxes from irrigated lands throughout growing seasons.

Lysimeter

Growing season

Water balance

10.1061/(asce)0733-9437(2007)133:4(395)

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Citations (718)

Impact of spatial and temporal aggregation of input parameters on the assessment of irrigation scheme performance

Journal of Hydrology (2004)

Ignacio J. Lorite Luciano Mateos E. Fereres

Wet season

10.1016/j.jhydrol.2004.06.010

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