scholarly journals Water pricing and irrigation across Europe: opportunities and constraints for adopting irrigation scheduling decision support systems

2015 ◽  
Vol 16 (1) ◽  
pp. 245-252 ◽  
Author(s):  
Elias Giannakis ◽  
Adriana Bruggeman ◽  
Hakan Djuma ◽  
Jerzy Kozyra ◽  
Jürg Hammer
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Irrigation Scheduling ◽  
Water Pricing ◽  
Farm Size ◽  
Small Farm ◽  
Farm Population ◽  
Irrigation Technologies ◽  
Southern European Countries

Despite the plethora of irrigation scheduling decision support systems that have been developed over the past decades, there is little evidence of widespread adoption by farmers. This paper investigates the structural, institutional and political rigidities that affect the adoption of irrigation scheduling technologies in southern European countries and highlights the corresponding opportunities. The recent implementation of water pricing policies, as required under the European Water Framework Directive, could motivate farmers to invest in technologies for improving water management. A review of irrigation water prices in southern Europe found a large range of prices both within and between countries, from 0.054–0.645 €/m3 (Greece) to 0.23–1.50 €/m3 (France). However, inadequate monitoring infrastructure and a lack of political will to impose the new water prices are giving a mixed signal to farmers. An ageing and poorly trained farm population, small farm size and low level of farm investment also impede the uptake of irrigation technologies. Within this context, European-funded research needs to consider these constraints and pay closer attention to the conversion of knowledge and innovation into successful commercial products.

scholarly journals Assessing the Impact of Reference Evapotranspiration Models on Decision Support Systems for Irrigation

Horticulturae ◽  
2018 ◽  
Vol 4 (4) ◽  
pp. 49 ◽  
Author(s):  
Matthias Olberz ◽  
Katrin Kahlen ◽  
Jana Zinkernagel
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Reference Evapotranspiration ◽  
Irrigation Scheduling ◽  
Vegetable Crops ◽  
Crop Water ◽  
Local Climate ◽  
Climate Conditions ◽  
The Impact

Reference evapotranspiration (E T 0) is a major estimator for crop water requirements predicted by decision support systems for irrigation. However, the impact of different E T 0s on the predicted amount of water supply and counts of irrigation events has not been evaluated. Simulations of the Geisenheim Irrigation Scheduling (GS) for vegetable crops with two different E T 0s, P2-E T 0 and FAO56-E T 0, were evaluated to assess exemplarily the impact of E T 0s. The sensitivity of both E T 0s to local climate conditions was characterized through a random forest analysis, and a linear regression model was used to adjust the original GS by adapting K c-values to the exchange E T 0. For assessing the outcomes of GS irrigation decision, simulations of 173 individual cropping cycles including six vegetable crops over eight years were conducted. After adjusting P2-E T 0 K c-values to FAO56-E T 0 K c-values, there was no impact of the E T 0-model on the practical irrigation scheduling with GS. Finally, we discuss that any E T 0-model, if adjusted accordingly, might have little impact on similar irrigation systems and provide a method to exchange E T 0s.

scholarly journals Dynamic Crop Models and Remote Sensing Irrigation Decision Support Systems: A Review of Water Stress Concepts for Improved Estimation of Water Requirements

2020 ◽  
Vol 12 (23) ◽  
pp. 3945
Author(s):  
Massimo Tolomio ◽  
Raffaele Casa
Keyword(s):  
Remote Sensing ◽  
Decision Support ◽  
Water Stress ◽  
Decision Support Systems ◽  
Growth And Development ◽  
Support Systems ◽  
Irrigation Scheduling ◽  
Crop Growth ◽  
Plant Water ◽  
Crop Models

Novel technologies for estimating crop water needs include mainly remote sensing evapotranspiration estimates and decision support systems (DSS) for irrigation scheduling. This work provides several examples of these approaches, that have been adjusted and modified over the years to provide a better representation of the soil–plant–atmosphere continuum and overcome their limitations. Dynamic crop simulation models synthetize in a formal way the relevant knowledge on the causal relationships between agroecosystem components. Among these, plant–water–soil relationships, water stress and its effects on crop growth and development. Crop models can be categorized into (i) water-driven and (ii) radiation-driven, depending on the main variable governing crop growth. Water stress is calculated starting from (i) soil water content or (ii) transpiration deficit. The stress affects relevant features of plant growth and development in a similar way in most models: leaf expansion is the most sensitive process and is usually not considered when planning irrigation, even though prolonged water stress during canopy development can consistently reduce light interception by leaves; stomatal closure reduces transpiration, directly affecting dry matter accumulation and therefore being of paramount importance for irrigation scheduling; senescence rate can also be increased by severe water stress. The mechanistic concepts of crop models can be used to improve existing simpler methods currently integrated in irrigation management DSS, provide continuous simulations of crop and water dynamics over time and set predictions of future plant–water interactions. Crop models can also be used as a platform for integrating information from various sources (e.g., with data assimilation) into process-based simulations.

Decision Support Systems and Informatics for Child Welfare Administrative Data to Inform Practice and Policy

2012 ◽  
Author(s):  
Hye-Chung Kum ◽  
Joy Stewart ◽  
Terry Moore ◽  
Michael Dineen
Keyword(s):  
Decision Support ◽  
Child Welfare ◽  
Decision Support Systems ◽  
Administrative Data ◽  
Support Systems

Decision support systems in dentistry.

1999 ◽  
Vol 28 (1) ◽  
pp. 59-60 ◽  
Author(s):  
S C White
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems

Assigning Value to Clinical Information – A Major Limiting Factor in the Implementation of Decision-Support Systems

1996 ◽  
Vol 35 (01) ◽  
pp. 1-4 ◽  
Author(s):  
F. T. de Dombal
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Clinical Information ◽  
Limiting Factor ◽  
Major Difficulty ◽  
Computer Aided ◽  
Computer Aided Decision

AbstractThis paper deals with a major difficulty and potential limiting factor in present-day decision support - that of assigning precise value to an item (or group of items) of clinical information. Historical determinist descriptive thinking has been challenged by current concepts of uncertainty and probability, but neither view is adequate. Four equations are proposed outlining factors which affect the value of clinical information, which explain some previously puzzling observations concerning decision support. It is suggested that without accommodation of these concepts, computer-aided decision support cannot progress further, but if they can be accommodated in future programs, the implications may be profound.

Architectures for Architects

1993 ◽  
Vol 32 (01) ◽  
pp. 12-13 ◽  
Author(s):  
M. A. Musen
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Design And Development

Abstract:Response to Heathfield HA, Wyatt J. Philosophies for the design and development of clinical decision-support systems. Meth Inform Med 1993; 32: 1-8.

Characterizing Decision Support Telemedicine Systems

2006 ◽  
Vol 45 (05) ◽  
pp. 523-527 ◽  
Author(s):  
A. Abu-Hanna ◽  
B. Nannings
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Literature Search ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Problem Dimension ◽  
Process Dimension

Summary Objectives: Decision Support Telemedicine Systems (DSTS) are at the intersection of two disciplines: telemedicine and clinical decision support systems (CDSS). The objective of this paper is to provide a set of characterizing properties for DSTSs. This characterizing property set (CPS) can be used for typing, classifying and clustering DSTSs. Methods: We performed a systematic keyword-based literature search to identify candidate-characterizing properties. We selected a subset of candidates and refined them by assessing their potential in order to obtain the CPS. Results: The CPS consists of 14 properties, which can be used for the uniform description and typing of applications of DSTSs. The properties are grouped in three categories that we refer to as the problem dimension, process dimension, and system dimension. We provide CPS instantiations for three prototypical applications. Conclusions: The CPS includes important properties for typing DSTSs, focusing on aspects of communication for the telemedicine part and on aspects of decisionmaking for the CDSS part. The CPS provides users with tools for uniformly describing DSTSs.

Integration of Decision-Support Systems and Signal Interpretation

1994 ◽  
Vol 33 (01) ◽  
pp. 143-143
Author(s):  
A. Rosenfalck
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems
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