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Agronomy
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Simulating the Impacts of Climate Change on Hydrology and Crop...
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Simulating the Impacts of Climate Change on Hydrology and Crop Production

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Water Use and Irrigation".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 18108

Special Issue Editors

Dr. Benjamin D Duval

E-Mail Website
Guest Editor
Biology Department, New Mexico Institute of Mining and Technology, Socorro, NM 87801, USA
Interests: ecology; climate change; soil; soil science; ecosystems; biomass; carbon cycle; nitrogen cycle
Special Issues, Collections and Topics in MDPI journals
Dr. Sarah C. Davis

E-Mail Website
Guest Editor
Environmental Studies Program, Voinovich School of Leadership and Public Affairs, Ohio University, The Ridges, Building 22, Athens, OH 45701, USA
Interests: renewable technologies; ecosystem ecology; carbon sequestration; biofuels; greenhouse gases; ecosystem modeling; bioenergy; Ethanol
Dr. Darren Drewry

E-Mail Website
Guest Editor
Department of Food, Agricultural, and Biological Engineering, The Ohio State University, Columbus, OH, USA
Interests: ecohydrology; vegetation biophysics; land surface remote sensing; data assimilation

Special Issue Information

Dear Colleagues,

Climate change and increased climate variability exert significant impacts on agricultural outputs, with some of the most profound impacts occurring at the intersection of crop production and water dynamics. Changes in hydrological dynamics can pose challenges for agricultural management in the future. The impacts of changes in hydrological forcing have the potential to be amplified or dampened by other projected changes to future growth environments (e.g., temperature, humidity and CO2 concentration). To highlight the importance of these challenges and the state-of-the-art in our understanding of agro-ecosystem responses to climate change, we are soliciting articles for a Special Issue of the journal Agronomy, titled “Simulating the Impacts of Climate Change on Hydrology and Crop Production”. We are generally interested in papers that address the intersection of climate change, hydrology and agro-ecosystem dynamics. Specific topics of interest include, but are not limited to: climate impacts on water use in agro-ecosystems, hydrological fluxes of agro-ecosystems as modulated by climate variability, the ecohydrology of agro-ecosystems, and changes to crop production and resource utilization as driven by hydroclimatic variability. We encourage submissions that report results from either empirical or modeling studies, and will also consider syntheses such as quantitative research reviews and formal meta-analyses.

* Submissions will undergo formal peer review, and authors should select the Special Issue title “Simulating the Impacts of Climate Change on Hydrology and Crop Production” at the time of submission.

Dr. Benjamin D Duval
Prof. Dr. Sarah C. Davis
Dr. Darren Drewry
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agronomy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (6 papers)

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Research

18 pages, 1574 KiB  
Article
Machine Learning Approach to Simulate Soil CO2 Fluxes under Cropping Systems
by Toby A. Adjuik and Sarah C. Davis
Agronomy 2022, 12(1), 197; https://doi.org/10.3390/agronomy12010197 - 14 Jan 2022
Cited by 14 | Viewed by 3385
Abstract
With the growing number of datasets to describe greenhouse gas (GHG) emissions, there is an opportunity to develop novel predictive models that require neither the expense nor time required to make direct field measurements. This study evaluates the potential for machine learning (ML) [...] Read more.
With the growing number of datasets to describe greenhouse gas (GHG) emissions, there is an opportunity to develop novel predictive models that require neither the expense nor time required to make direct field measurements. This study evaluates the potential for machine learning (ML) approaches to predict soil GHG emissions without the biogeochemical expertise that is required to use many current models for simulating soil GHGs. There are ample data from field measurements now publicly available to test new modeling approaches. The objective of this paper was to develop and evaluate machine learning (ML) models using field data (soil temperature, soil moisture, soil classification, crop type, fertilization type, and air temperature) available in the Greenhouse gas Reduction through Agricultural Carbon Enhancement network (GRACEnet) database to simulate soil CO2 fluxes with different fertilization methods. Four machine learning algorithms—K nearest neighbor regression (KNN), support vector regression (SVR), random forest (RF) regression, and gradient boosted (GB) regression—were used to develop the models. The GB regression model outperformed all the other models on the training dataset with R2 = 0.88, MAE = 2177.89 g C ha−1 day−1, and RMSE 4405.43 g C ha−1 day−1. However, the RF and GB regression models both performed optimally on the unseen test dataset with R2 = 0.82. Machine learning tools were useful for developing predictors based on soil classification, soil temperature and air temperature when a large database like GRACEnet is available, but these were not highly predictive variables in correlation analysis. This study demonstrates the suitability of using tree-based ML algorithms for predictive modeling of CO2 fluxes, but no biogeochemical processes can be described with such models. Full article
(This article belongs to the Special Issue Simulating the Impacts of Climate Change on Hydrology and Crop Production)
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20 pages, 11538 KiB  
Article
Spring Precipitation Deficiency in Poland and Its Temporal and Spatial Variability in the Context of Agricultural Needs
by Robert Kalbarczyk and Eliza Kalbarczyk
Agronomy 2022, 12(1), 158; https://doi.org/10.3390/agronomy12010158 - 10 Jan 2022
Cited by 3 | Viewed by 1612
Abstract
Deficient precipitation (dPr) in the growing season, especially in critical periods, affects plant condition and determines the quality and quantity of obtained yields. Knowledge about the variability and distribution of dPr is essential to mitigate its effect on agricultural soils and on crop [...] Read more.
Deficient precipitation (dPr) in the growing season, especially in critical periods, affects plant condition and determines the quality and quantity of obtained yields. Knowledge about the variability and distribution of dPr is essential to mitigate its effect on agricultural soils and on crop and livestock production. The goal of the work is to determine the spatial and temporal distribution of spring precipitation deficiency and also to indicate the zones of risk and variability of its occurrence in Poland. It was assumed that dPr occurred when total monthly precipitation in a given year accounted for ≤75% of the total multi-year mean (1951–2018). In the spring season, the multi-year mean of the area covered by deficient precipitation (ACDP) amounted to 33% and fluctuated between approximately 31% in May and approximately 35% in March. The study distinguished four zones in Poland that vary in terms of the risk and variability of spring precipitation deficiency. The obtained results may be used, for example, to assess the needs for irrigation in the changing climate conditions, to model the growing season and yields of cultivated plants, and to select adaptation measures for agriculture in response to climate change. Full article
(This article belongs to the Special Issue Simulating the Impacts of Climate Change on Hydrology and Crop Production)
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11 pages, 2234 KiB  
Article
Expanded Potential Growing Region and Yield Increase for Agave americana with Future Climate
by Sarah C. Davis, John T. Abatzoglou and David S. LeBauer
Agronomy 2021, 11(11), 2109; https://doi.org/10.3390/agronomy11112109 - 21 Oct 2021
Cited by 5 | Viewed by 2171
Abstract
Rising crop risk for farmers and greater subsidy costs for governments are both associated with changing climatic conditions, including increased water scarcity. The resilience of Agave spp. in both hot and dry conditions, combined with their wide range of uses, position these plants [...] Read more.
Rising crop risk for farmers and greater subsidy costs for governments are both associated with changing climatic conditions, including increased water scarcity. The resilience of Agave spp. in both hot and dry conditions, combined with their wide range of uses, position these plants as novel high-yielding crops suitable for both (i) a warming climate and (ii) agricultural regions with finite water resources. A simple model of the physiological response of Agave americana to variations in solar radiation, temperature, and precipitation was used to predict A. americana yields globally at a 4 km spatial resolution for both contemporary climate and high-end warming scenarios. The potential growing region for A. americana expanded by 3–5% (up to 3 million ha) and potential biomass production increased by 4–5% (up to 4 Gt of additional biomass) with climate warming scenarios. There were some declines in biomass with the climate warming projected in smaller dispersed locations of tropical South America, Africa, and Australia. The amount of water required for optimal A. americana yield is less than half of the current water required for other crops grown in semi-arid agricultural regions of the southwestern US, and a similar low water demand can be expected in other semi-arid regions of the world. Rock mulching can further reduce the need for irrigation and increase suitable cropland area for A. americana by 26–30%. We show that >10 Mg ha−1 y−1 of A. americana biomass could be produced on 27 million ha of cropland without requiring irrigation. Our results suggest that cultivation of A. americana can support resilient agriculture in a future with rising temperatures and water scarcity. Full article
(This article belongs to the Special Issue Simulating the Impacts of Climate Change on Hydrology and Crop Production)
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20 pages, 5849 KiB  
Article
Water-Centric Nexus Approach for the Agriculture and Forest Sectors in Response to Climate Change in the Korean Peninsula
by Chul-Hee Lim
Agronomy 2021, 11(8), 1657; https://doi.org/10.3390/agronomy11081657 - 20 Aug 2021
Cited by 4 | Viewed by 2395
Abstract
Climate change has inherent multidisciplinary characteristics, and predicting the future of a single field of work has a limit. Therefore, this study proposes a water-centric nexus approach for the agriculture and forest sectors for improving the response to climate change in the Korean [...] Read more.
Climate change has inherent multidisciplinary characteristics, and predicting the future of a single field of work has a limit. Therefore, this study proposes a water-centric nexus approach for the agriculture and forest sectors for improving the response to climate change in the Korean Peninsula. Two spatial models, i.e., Environmental Policy Integrated Climate and Integrated Valuation of Ecosystem Services and Tradeoffs, were used to assess the extent of changes in agricultural water demand, forest water supply, and their balance at the watershed level in the current and future climatic conditions. Climate changed has increased the agricultural water demand and forest water supply significantly in all future scenarios and periods. Comparing the results with RCP8.5 2070s and the baseline, the agricultural water demand and forest water supply increased by 35% and 28%, respectively. Water balance assessment at the main watershed level in the Korean Peninsula revealed that although most scenarios of the future water supply increases offset the demand growth, a risk to water balance exists in case of a low forest ratio or smaller watershed. For instance, the western plains, which are the granary regions of South and North Korea, indicate a higher risk than other areas. These results show that the land-use balance can be an essential factor in a water-centric adaptation to climate change. Ultimately, the water-centric nexus approach can make synergies by overcoming increasing water demands attributable to climate change. Full article
(This article belongs to the Special Issue Simulating the Impacts of Climate Change on Hydrology and Crop Production)
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18 pages, 9570 KiB  
Article
Impact of El Niño Southern Oscillation on Rainfall and Rice Production: A Micro-Level Analysis
by Shilpa Cherian, Shankarappa Sridhara, Konapura Nagaraja Manoj, Pradeep Gopakkali, Nandini Ramesh, Abdullah A. Alrajhi, Ahmed Z. Dewidar and Mohamed A. Mattar
Agronomy 2021, 11(6), 1021; https://doi.org/10.3390/agronomy11061021 - 21 May 2021
Cited by 4 | Viewed by 3219
Abstract
Monsoon fluctuation due to El Niño Southern Oscillation (ENSO) has a reflective influence on rice production, which is the major food grain crop in India. The impact of ENSO on the spatial variability of summer monsoon rainfall was analyzed from 1950 to 2018 [...] Read more.
Monsoon fluctuation due to El Niño Southern Oscillation (ENSO) has a reflective influence on rice production, which is the major food grain crop in India. The impact of ENSO on the spatial variability of summer monsoon rainfall was analyzed from 1950 to 2018 and that on Kharif rice production for the period of 1998–2016. It was clear from the analysis that ENSO had varied influences on rainfall and rice production over different rice-growing districts of Karnataka. During El Niño (strong, moderate, and weak) years, southwest (S-W) monsoon rainfall was below normal in all the districts of Karnataka, wherein the highest negative deviation from normal was recorded in the Mysore district (−21.43%). In contrast, the rice production was higher in 15 districts out of 25, and the deviation from normal ranged from −39.73% in Bidar to 42.11% in Gulbarga district. During the La Niña (strong, moderate, and weak) years, S-W monsoon rainfall was above normal in 12 districts in which Bidar and Bengaluru urban districts have shown the highest positive deviation (19.93 and 19.82%, respectively). However, except for Udupi, Dakshina Kannada, Bidar, Davanagere, and Hassan districts, all the other major rice-growing districts have shown a positive deviation in rice production with the highest deviation of 62.39% in Tumkur district. Additionally, correlation coefficient values indicated the influence of southwest monsoon rainfall on Kharif rice production during El Niño years with a major contribution from September month rainfall. This kind of ENSO impact analysis on spatial rice production could be useful for formulating the farm-level site-specific management, planning, and policy decisions during ENSO periods in advance. Full article
(This article belongs to the Special Issue Simulating the Impacts of Climate Change on Hydrology and Crop Production)
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19 pages, 4098 KiB  
Article
Influence of the Water Source on the Carbon Footprint of Irrigated Agriculture: A Regional Study in South-Eastern Spain
by Bernardo Martin-Gorriz, Victoriano Martínez-Alvarez, José Francisco Maestre-Valero and Belén Gallego-Elvira
Agronomy 2021, 11(2), 351; https://doi.org/10.3390/agronomy11020351 - 16 Feb 2021
Cited by 18 | Viewed by 3880
Abstract
Curbing greenhouse gas (GHG) emissions to combat climate change is a major global challenge. Although irrigated agriculture consumes considerable energy that generates GHG emissions, the biomass produced also represents an important CO2 sink, which can counterbalance the emissions. The source of the [...] Read more.
Curbing greenhouse gas (GHG) emissions to combat climate change is a major global challenge. Although irrigated agriculture consumes considerable energy that generates GHG emissions, the biomass produced also represents an important CO2 sink, which can counterbalance the emissions. The source of the water supply considerably influences the irrigation energy consumption and, consequently, the resulting carbon footprint. This study evaluates the potential impact on the carbon footprint of partially and fully replacing the conventional supply from Tagus–Segura water transfer (TSWT) with desalinated seawater (DSW) in the irrigation districts of the Segura River basin (south-eastern Spain). The results provide evidence that the crop GHG emissions depend largely on the water source and, consequently, its carbon footprint. In this sense, in the hypothetical scenario of the TSWT being completely replaced with DSW, GHG emissions may increase by up to 50% and the carbon balance could be reduced by 41%. However, even in this unfavourable situation, irrigated agriculture in the study area could still act as a CO2 sink with a negative total and specific carbon balance of −707,276 t CO2/year and −8.10 t CO2/ha-year, respectively. This study provides significant policy implications for understanding the water–energy–food nexus in water-scarce regions. Full article
(This article belongs to the Special Issue Simulating the Impacts of Climate Change on Hydrology and Crop Production)
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