scholarly journals Farmers Try to Improve Their Irrigation Practices by Using Daily Irrigation Recommendations—The Vipava Valley Case, Slovenia

Agronomy ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 1238
Author(s):  
Rozalija Cvejić ◽  
Majda Černič-Istenič ◽  
Luka Honzak ◽  
Urša Pečan ◽  
Špela Železnikar ◽  
...  
Keyword(s):  
Climate Change ◽  
Decision Support ◽  
Soil Water ◽  
Water Reservoir ◽  
Irrigation Scheduling ◽  
Learning And Development ◽  
Climate Change Projections ◽  
High Exposure ◽  
Agricultural Innovation ◽  
Irrigation Volume

Based on the latest climate change projections for the 21st century, high exposure to climate change is expected in Vipava Valley, Slovenia’s sub-Mediterranean agricultural area. An irrigation-decision support system was developed and implemented on 35 farms in the period of 2016–2020 to increase agricultural climate-change resilience. Farmers have shifted from irrigation scheduling based on experience and assumptions to irrigation scheduling based on real-time soil-water monitoring to partially implement irrigation based on irrigation-decision support systems. Simulations show that if farmers continue to practice justified irrigation applications and gradually transition to replenishing soil water reservoir content to 85%, they will achieve a 25% reduction in total irrigation-volume consumption, a 24% reduction in energy requirements and a 24% reduction in CO2 emissions. Future agricultural innovation policies should extend actions beyond the financial to those facilitating the establishment of multidisciplinary agricultural innovation teams with corresponding infrastructures to better enable the mutual exchange of knowledge, learning and development of a transparent institutional framework.

scholarly journals Grapevine Phenology of cv. Touriga Franca and Touriga Nacional in the Douro Wine Region: Modelling and Climate Change Projections

Agronomy ◽  
2019 ◽  
Vol 9 (4) ◽  
pp. 210 ◽  
Author(s):  
Ricardo Costa ◽  
Helder Fraga ◽  
André Fonseca ◽  
Iñaki García de Cortázar-Atauri ◽  
Maria C. Val ◽  
...  
Keyword(s):  
Climate Change ◽  
Decision Support ◽  
Performance Metrics ◽  
Strategic Decision ◽  
Future Climate Change ◽  
Growing Degree Days ◽  
Climate Change Scenarios ◽  
Degree Days ◽  
Climate Change Projections ◽  
Wine Region

Projections of grapevine phenophases under future climate change scenarios are strategic decision support tools for viticulturists and wine producers. Several phenological models are tested for budburst, flowering, and veraison and for two main grapevine varieties (cv. Touriga Franca and Touriga Nacional) growing in the Douro Demarcated Region. Four forcing models (Growing degree-days, Richardson, Sigmoid, and Wang) and three dormancy models (Bidabe, Smoothed Utah and Chuine), with different parameterizations and combinations, are used. New datasets, combing phenology with weather station data, widespread over the Douro wine region, were used for this purpose. The eight best performing models and parameterizations were selected for each phenophase and variety, based on performance metrics. For both cultivars, results revealed moderate performances (0.4 < R2 < 0.7) for budburst, while high performances (R2 > 0.7) were found for flowering and veraison, particularly when Growing degree-days or Sigmoid models are used, respectively. Climate change projections were based on a two-member climate model ensemble from the EURO-CORDEX project under RCP4.5. Projections depicted an anticipation of phenophase timings by 6, 8 or 10–12 days until the end of the century for budburst, flowering, and veraison, respectively. The inter-model variability is of approximately 2–4 days for flowering and veraison and 4–6 days for budburst. These results establish grounds for the implementation of a decision support system for monitoring and short-term prediction of grapevine phenology, thus promoting a more efficient viticulture.

Irrigator Pro: Progression of a Peanut Irrigation Scheduling Decision Support System

2020 ◽  
Vol 36 (5) ◽  
pp. 785-795
Author(s):  
Christopher L Butts ◽  
Ronald B Sorensen ◽  
Marshall C Lamb
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Soil Temperature ◽  
Water Potential ◽  
Soil Water ◽  
Support System ◽  
Soil Water Potential ◽  
Irrigation Scheduling ◽  
List Type ◽  
Web Based

HighlightsThe logic used in developing a decision support system for irrigating peanut based on max/min soil temperature is describedLogic to transform decision support system from peanut to irrigate corn and cotton with and without soil sensors.Progression of a decision support system from a desktop program to a web/mobile applicationAbstract. Irrigator Pro is a decision support tool for scheduling irrigation events in peanut. It was deployed in 1995 as a rule-based system using crop history, yield potential, soil type, in-season irrigation/rainfall and maximum/minimum soil temperature. As computing platforms have progressed from desktop personal computers to mobile web-based platforms, Irrigator Pro has been updated and is now deployed as a web-based program and an application for mobile devices. Irrigator Pro not only works for peanuts but has been modified to irrigate both corn and cotton. The irrigation decisions are now based on in-field soil water potential measurements in addition to the traditional checkbook with max/min soil temperatures. Users are individual growers, extension agents, and agronomic consultants. The objective of this manuscript is to document the initial development of Irrigator Pro as an expert system combining data and experiential knowledge and the progression from a checkbook-based decision support system to a hybrid system using observed weather data and soil moisture measurement. The background knowledge, equations, and thresholds for triggering irrigation recommendations are included. Keywords: Decision support system, Irrigation scheduling, Irrigator Pro, Mobile app, Peanut, Soil water potential.

scholarly journals A robust multiple-objective decision-making paradigm based on the water–energy–food security nexus under changing climate uncertainties

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Maedeh Enayati ◽  
Omid Bozorg-Haddad ◽  
Elahe Fallah-Mehdipour ◽  
Babak Zolghadr-Asli ◽  
Xuefeng Chu
Keyword(s):  
Climate Change ◽  
Decision Making ◽  
Food Security ◽  
Decision Support ◽  
Multiple Objective ◽  
Decision Making Process ◽  
Climate Change Projections ◽  
Decision Support Framework ◽  
The Impact

AbstractFrom the perspective of the water–energy–food (WEF) security nexus, sustainable water-related infrastructure may hinge on multi-dimensional decision-making, which is subject to some level of uncertainties imposed by internal or external sources such as climate change. It is important to note that the impact of this phenomenon is not solely limited to the changing behavior patterns of hydro-climatic variables since it can also affect the other pillars of the WEF nexus both directly and indirectly. Failing to address these issues can be costly, especially for those projects with long-lasting economic lifetimes such as hydropower systems. Ideally, a robust plan can tolerate these projected changes in climatic behavior and their associated impacts on other sectors, while maintaining an acceptable performance concerning environmental, socio-economic, and technical factors. This study, thus, aims to develop a robust multiple-objective decision-support framework to address these concerns. In principle, while this framework is sensitive to the uncertainties associated with the climate change projections, it can account for the intricacies that are commonly associated with the WEF security network. To demonstrate the applicability of this new framework, the Karkheh River basin in Iran was selected as a case study due to its critical role in ensuring water, energy, and food security of the region. In addition to the status quo, a series of climate change projections (i.e., RCP 2.6, RCP 4.5, and RCP 8.5) were integrated into the proposed decision support framework as well. Resultantly, the mega decision matrix for this problem was composed of 56 evaluation criteria and 27 feasible alternatives. A TOPSIS/Entropy method was used to select the most robust renovation plan for a hydropower system in the basin by creating a robust and objective weighting mechanism to quantify the role of each sector in the decision-making process. Accordingly, in this case, the energy, food, and environment sectors are objectively more involved in the decision-making process. The results revealed that the role of the social aspect is practically negligible. The results also unveiled that while increasing the power plant capacity or the plant factor would be, seemingly, in favor of the energy sector, if all relevant factors are to be considered, the overall performance of the system might resultantly become sub-optimal, jeopardizing the security of other aspects of the water–energy–food nexus.

IrrigaSys – a decision support system for irrigation management in the Sorraia Valley region, Portugal

2020 ◽  
Author(s):  
Lucian Simionesei ◽  
Tiago B. Ramos ◽  
Jorge Palma ◽  
Ana R. Oliveira ◽  
Ramiro Neves
Keyword(s):  
Decision Support ◽  
Water Balance ◽  
Decision Support System ◽  
Soil Water ◽  
Support System ◽  
Weather Forecast ◽  
Irrigation Scheduling ◽  
Mobile App ◽  
Soil Water Balance ◽  
Sentinel 2

&lt;p&gt;IrrigaSys is a decision support system (DSS) for irrigation water management based on online, open&lt;br&gt;access tools. The system includes remote access to local meteorological stations for weather&lt;br&gt;conditions, a MM5 model for weather forecast, the MOHID-Land model for the computation of the&lt;br&gt;soil water balance and irrigation scheduling, and a MySQL database for data repository. Despite its&lt;br&gt;complexity, the data necessary to run IrrigaSys is minimal, and include the location of the agricultural&lt;br&gt;field, crop type, sowing and harvest dates, soil texture, irrigation method, and daily/weekly irrigation&lt;br&gt;depths applied by the farmer. Based on this information, the system automatically downloads the&lt;br&gt;weather data from the meteorological station located closest to the agricultural plot, as well as the&lt;br&gt;weather forecast for the seven days following the current date. The soil water balance is then&lt;br&gt;computed for the previous and following week as well as the crop irrigation needs using the MOHIDLand&lt;br&gt;model. Results are made available via a web interface, a mobile app, SMS, and email. Besides the&lt;br&gt;model outputs, the IrrigaSys further provides the Normalized Difference Vegetation Index (NDVI) for&lt;br&gt;the agricultural field. The NDVI is computed from Sentinel 2 spectral bands with a resolution of 10m,&lt;br&gt;and is updated every time new Sentinel 2 imagery data (with cloud cover &lt; 10%) is available. The&lt;br&gt;IrrigaSys has been developed in close cooperation with the Water Board Association of the Sorraia&lt;br&gt;Valley irrigation district (15360 ha), southern Portugal, over the last 5 years, supporting 103 plots of&lt;br&gt;30 farmers during the last irrigation season. As a result, the main limitation is naturally associated to&lt;br&gt;the difficulty in providing reliable estimates for all field plots based on calibrated model data. As the&lt;br&gt;next step, the service should start automatically identifying the culture status based on satellite&lt;br&gt;information as well as providing fertigation recommendations to farmers.&lt;/p&gt;

Uncertainty in CMIP6 climate change projections for the Australian monsoon is tied to hemispheric-scale changes

2020 ◽  
Author(s):  
Sugata Narsey ◽  
Josephine R. Brown ◽  
Robert A. Colman ◽  
Francois Delage ◽  
Scott Brendan Power ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Change Projections ◽  
Australian Monsoon

Modelling impacts of different climate change scenarios on soil water regime of a Mollisol

2005 ◽  
Vol 33 (1) ◽  
pp. 185-188 ◽  
Author(s):  
Csilla Farkas ◽  
Roger Randriamampianina ◽  
Juraj Majerčak
Keyword(s):  
Climate Change ◽  
Soil Water ◽  
Water Regime ◽  
Climate Change Scenarios ◽  
Soil Water Regime

Evapotranspiration Measurement and Irrigation Scheduling for Several Tropical Fruit Crops Using the EnviroScan System

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 549f-550
Author(s):  
Mongi Zekri ◽  
Bruce Schaffer ◽  
Stephen K. O'Hair ◽  
Roberto Nunez-Elisea ◽  
Jonathan H. Crane
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Water Use ◽  
National Parks ◽  
Quantitative Information ◽  
Irrigation Scheduling ◽  
Management Tool ◽  
Fruit Crops ◽  
Tropical Fruit

In southern Florida, most tropical fruit crops between Biscayne and Everglades National Parks are irrigated at rates and frequencies based on experience and observations of tree growth and fruit yield rather than on reliable quantitative information of actual water use. This approach suggests that irrigation rates may be excessive and could lead to leaching of agricultural chemicals into the groundwater in this environmentally sensitive area. Therefore, a study is being conducted to increase water use efficiency and optimize irrigation by accurately scheduling irrigation using a very effective management tool (EnviroScan, Sentek Environmental Innovations, Pty., Kent, Australia) that continuously monitors soil water content with highly accurate capacitance multi-sensor probes installed at several depths within the soil profile. The system measures crop water use by monitoring soil water depletion rates and allows the maintenance of soil water content within the optimum range (below field capacity and well above the onset of plant water stress). The study is being conducted in growers' orchards with three tropical fruit crops (avocado, carambola, and `Tahiti' lime) to facilitate rapid adoption and utilization of research results.

scholarly journals Characterizing Growing Season Length of Subtropical Coniferous Forests with a Phenological Model

Forests ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 95
Author(s):  
Yuan Gong ◽  
Christina L. Staudhammer ◽  
Susanne Wiesner ◽  
Gregory Starr ◽  
Yinlong Zhang
Keyword(s):  
Climate Change ◽  
Soil Water ◽  
Prescribed Fire ◽  
Water Availability ◽  
Longleaf Pine ◽  
Growing Season ◽  
Soil Water Availability ◽  
Future Climate Change ◽  
Short Term ◽  
Phenological Model

Understanding plant phenological change is of great concern in the context of global climate change. Phenological models can aid in understanding and predicting growing season changes and can be parameterized with gross primary production (GPP) estimated using the eddy covariance (EC) technique. This study used nine years of EC-derived GPP data from three mature subtropical longleaf pine forests in the southeastern United States with differing soil water holding capacity in combination with site-specific micrometeorological data to parameterize a photosynthesis-based phenological model. We evaluated how weather conditions and prescribed fire led to variation in the ecosystem phenological processes. The results suggest that soil water availability had an effect on phenology, and greater soil water availability was associated with a longer growing season (LOS). We also observed that prescribed fire, a common forest management activity in the region, had a limited impact on phenological processes. Dormant season fire had no significant effect on phenological processes by site, but we observed differences in the start of the growing season (SOS) between fire and non-fire years. Fire delayed SOS by 10 d ± 5 d (SE), and this effect was greater with higher soil water availability, extending SOS by 18 d on average. Fire was also associated with increased sensitivity of spring phenology to radiation and air temperature. We found that interannual climate change and periodic weather anomalies (flood, short-term drought, and long-term drought), controlled annual ecosystem phenological processes more than prescribed fire. When water availability increased following short-term summer drought, the growing season was extended. With future climate change, subtropical areas of the Southeastern US are expected to experience more frequent short-term droughts, which could shorten the region’s growing season and lead to a reduction in the longleaf pine ecosystem’s carbon sequestration capacity.

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