=Paper=
{{Paper
|id=Vol-1498/HAICTA_2015_paper23
|storemode=property
|title=Main Features and Application of a Web-based Irrigation Management Tool for the Plain of Arta
|pdfUrl=https://ceur-ws.org/Vol-1498/HAICTA_2015_paper23.pdf
|volume=Vol-1498
|dblpUrl=https://dblp.org/rec/conf/haicta/MalamosTCAV15
}}
==Main Features and Application of a Web-based Irrigation Management Tool for the Plain of Arta==
https://ceur-ws.org/Vol-1498/HAICTA_2015_paper23.pdf
Main Features and Application of a Web-based
Irrigation Management Tool for the Plain of Arta
Nikolaos Malamos1, Ioannis L. Tsirogiannis2, Antonis Christofides3, Stavros
Anastasiadis4, Silvia Vanino5
1
Technological Educational Institute of Western Greece, Dept. of Agricultural Technology,
27200 Amaliada, Greece, e-mail: nmalamos@teimes.gr
2
Technological Educational Institute of Epirus, Dept. of Agricultural Technology, 47100
Kostakii, Arta, Greece, e-mail: itsirog@teiep.gr
3
National Technical University of Athens, Dept. of Water Resources and Environmental
Engineering, Iroon Politechniou 5, 15780 Zografou, Athens, Greece, e-mail:
anthony@itia.ntua.gr
4
Chios, Greece, e-mail: anastasiadis.st00@gmail.com
5
Consiglio per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria, 41 Nomentana St.,
00161, Rome, Italy, e-mail: vanino@inea.it
Abstract. Agriculture plays a key role in the management of water use.
Especially in Greece, irrigation is an essential element of agricultural
production and agricultural water use has a substantial share in total water use.
The presented study illustrates the key features of the IRMA_SYSTEM, a
regional, user-friendly computer/mobile-based, open and free modular
software for estimating site specific crop water requirements and irrigation
scheduling at multiple scales, from farm to water basin level. The estimation of
irrigation water requirements and irrigation scheduling is based on a
modification of the FAO 56 approach. The system takes into account historical
and forecast agrometeorological data, along with crop and soil-water data to
accomplish its tasks. Also, it is fully customizable, allowing the users to add
site and crop specific information taking advantage of additional data.
Feedback and evaluation procedures are already applied and expected to
contribute to the improvement of the system.
Keywords: irrigation scheduling, open source software, agrometeorological
information
1 Introduction
According to the EU Water Framework Directive WFD, 2000/60/EC (EU, 2000
(Greek law (GL) 3199; Govern. Gazette (GG) A'280 9-12-2003) and Presidential
Decree (PD) 51;GG Α΄54 8-3-2007)), action is needed to protect waters primary in
qualitative but also in quantitative terms. In the framework of the UN Environment
Program (UNEP, 2005) it was concluded that a challenge of water-related issues for
Mediterranean countries is to integrate water demand management in agriculture and
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to develop added value tools to optimize efficiency in irrigation. In 2012, the EU-
report on identifying water saving potentials in the EU countries mentioned that
improving water application efficiency would save 15 to 60% of water use (BIO
Intelligent Service, 2012). Also CMMC (2013) predicts a reduction up to 60% in
water availability for irrigation in extended Mediterranean areas of EU countries.
These facts make optimum irrigation water management a top priority goal. Beyond
these, the European Landscape Convention (which was adopted by the Greek state in
2010, GL 3827;GG A'30 25-2-2010) promotes protection, management and planning
of natural, rural, urban and peri-urban areas including land, inland water and marine
areas and must be also taken into account as an integral part of the environmental and
agricultural legislative framework. Among the various measures which member
states are proposed to adopt and develop are added value tools to optimize efficiency
in irrigation.
The purpose of the present study is to illustrate the key features of such a tool, the
IRMA_SYSTEM (http://arta.irrigation-management.eu/), which is a regional, user-
friendly computer/mobile-based, open and free modular software for estimating site
specific crop water requirements and irrigation scheduling at multiple scales, from
farm to water basin level, with high spatial resolution. The system takes into account
historical (from the system’s stations) and forecast agrometeorological data, along
with crop and soil-water data to accomplish the above mentioned tasks. Also, it is
fully customizable, allowing the users to add site specific information in order to
customize the output of the system, taking advantage of additional information.
Similar systems are: the California Irrigation Management Information System
(CIMIS, http://wwwcimis.water.ca.gov/), the Hydrotech-DSS (Todorovic et al. 2013)
and the ServiziAgronomici e Fitosanitari, Consiglio Irriquo
(http://www.agrometeopuglia.it) (AssocodiPuglia, 2008).
2 Materials and Methods
2.1 Study Area
The Region of Epirus (hydrological area GR05; Fig. 1) is located at the North-
West part of Greece, it has a total area of 9.203km2 (agricultural land corresponds to
the 14% of it) and a population of 353.820 p. The plain of Arta (45.329 ha, the
biggest of the region), is located at the south edge of Epirus, it is part of the Aracthos
and Louros hydrological basins (GR14 and GR46; WFD, 2013) and intersects with
Amvrakikos Wetlands National Park.
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Fig. 1. Hydrological basins of Greece, along with the hydrological basins of Epirus. (WFD,
2013)
2.2 Estimation of daily and hourly potential evapotranspiration, with the
Penman - Monteith equation
The Penman - Monteith (PM) equation for the estimation of reference
evapotranspiration was developed to describe potential evapotranspiration (PET) of a
reference grass crop, which is defined as the rate of evapotranspiration from a
hypothetical crop with an assumed fixed height (12 cm), surface resistance (70 sm–1)
and albedo (0.23), closely resembling the evapotranspiration from an extensive
surface of a disease free green grass cover of uniform height, actively growing,
completely shading the ground, and with adequate water and nutrient supply (Allen
et al., 1998, Eq. 1). To ensure the integrity of computations, the weather
measurements should be made at 2 m (or converted to that height) above an
extensive surface of green grass, shading the ground and not short of water. Standard
methods are proposed by Allen et al. (1998) to compute the parameters of Eq. 1 from
the observed climatic variables.
0,408Δ ( Rn − G ) + γ Τ900
+ 273 u 2 (es − ea )
PET = (1)
Δ + γ (1 + 0,34u 2 )
where PET is the grass reference evapotranspiration (mm day–1), Rn is the net
radiation at the crop surface (MJ m-2 day–1), G is soil heat flux density (MJ m–2 day–
1
), T is mean daily air temperature at 2m height (οC), u2 is wind speed at 2 m height
(m s–1), es is saturation vapor pressure (kPa), ea is actual vapor pressure (kPa), es–ea is
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saturation vapor pressure deficit (kPa), Δ is slope of the vapor pressure curve (kPa C-
1
), and γ is psychometric constant (kPa C–1). This equation uses standard
meteorological records of solar radiation (net, short wave, or sunshine duration) or
sunshine duration, minimum and maximum air temperature, air humidity (preferably
minimum and maximum relative humidity) or wet and dry bulb temperature, and
wind speed.
In areas where substantial changes in wind speed, dew point or cloudiness occur
during the day, calculation of the PET equation using hourly time steps is generally
better than using 24-hour calculation time steps. Such weather changes can cause 24-
hour means to misrepresent evaporative power of the environment during parts of the
day and may introduce error into the calculations. With the use of the
IRMA_SYSTEM, automated weather stations, weather data are available for hourly
periods. Therefore, the PM equation was applied on an hourly basis (Allen et al.,
1998).
2.3 Estimation of irrigation needs
The irrigation needs are estimated based on an approach that is called root zone
soil water depletion, which is a simplified soil water balance based on an initial soil
moisture condition and runs for a specified time period (start date, end date).
The basis for the calculation is the following ormula (Allen et al., 1998):
Dr,i = Dr,i-1 – (Pi – ROi) – IRn,i – CRi + ETc,i + DPi (2)
where: i is the current time period (i.e. the current day, or hour), Dr,i is the root
zone depletion at the end of the previous time period, Pi is the precipitation, ROi is
the runoff, IRn,i is the net irrigation depth, CRi is the capillary rise, ETc,i is the crop
evapotranspiration, DPi is the water loss through deep percolation.
The following limits were imposed on Dr,i:
Θs <= Dr,i <= ASM (3)
where Θs is the soil moisture at saturation and ASM is the total available soil
water, which is the difference between Field Capacity (FC) and Permanent Wilting
Point (PWP) as they are presented in Fig. 2. This approach is slightly different that
the one proposed by Allen et al., 1998, since they propose that Dr,i is always positive.
ROi equals the amount of water that exceeds soil moisture at saturation after heavy
rain, i.e.:
ROi = Pi + Θi–1 – Θs when (Pi + Θi–1 – Θs) > 0 (4)
where Θi–1 is the soil moisture at the previous time step. CRi and DPi are
considered zero, since in the case of the Arta plain there is a shallow water table and
equilibrium between them is considered.
The equation therefore becomes:
Dr,i = Dr,i-1 – Pi – IRn,i + ETc,i + ROi (5)
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(a) (b)
Fig. 2. Saturated water content (Θs) map (a) and Available soil moisture (ASM) map (b) of
IRMA_SYSTEM area at Arta plain.
ETc,i is calculated using crop coefficient approach by multiplying
evapotranspiration by crop coefficient Kc (Allen et al., 1998).
Each time the user irrigates, the initial depletion derives from the provided
irrigation water volume. An essential simplifying assumption of this method is that
each time we irrigate without providing the irrigation water volume, we assume that
enough water was applied in order for the soil moisture to reach FC (i.e. zero
depletion). Therefore, in this case we have i=1 and Dr,1=0.
The point i=1 is specified by start_date, which is a datetime object. The
initial_soil_moisture will usually equal FC (this, according to the essential
simplifying assumption, means that the crop was irrigated on start_date). However,
if the crop has not been irrigated recently, initial_soil_moisture will be set to another
value (such as a soil moisture measurement made at start_date).
Soil moisture (Θi) and depletion are related with this formula:
Θi = FC – Dr,i / Root depth (6)
So, since the initial_soil_moisture is given, Dr,1 is also known.
The method returns the root zone depletion for end_date in millimeters (mm).
Precipitation and ETc must have non-null records for all days from the day following
start_date to end_date.
2.4 System Implementation
The system is a product of cooperation between experts in the fields of
meteorological data acquisition, agricultural cultivation and landscapes water needs,
178
irrigation management, irrigation controllers manufacturing and software developers.
The general organisation of the system is presented in Fig. 3, while the flowchart of
the system modules is presented in Fig. 4.
Users
,
Other
data
(descriptive
fields
and
and
spatial)
of
the
area
irrigation
Third
party
meteorological
data
(DEM,
soil,
albedo
etc)
events
data
B
!
Alert
emails
Data
evaluation,
storage
and
analysis
for
production
of
data
C
series
of
measurements
and
Web
site
A
calculated
values
concerning
C
irrigation
water
balance
Generic
data,
advices
and
other
tools
IRMA
Meteorological
data
system
Internet
of
things
(stations
and
communication
center).
"Real
time"
NOA
weather
forecasts
Evaluation
meteorological
data
are
collected
and
transmitted
to
the
communication
center
Irrigation
controller
Fig. 3. IRMA_SYSTEM organisation plan
The IRMA_SYSTEM is a user-friendly computer/mobile-based, open and free
modular software, with its source available at: https://github.com/openmeteo/aira,
under the terms of the GNU General Public License as published by the Free
Software Foundation, written in Python and Django, along with NumPy
(http://www.numpy.org/) and GDAL - Geospatial Data Abstraction Library
(http://www.gdal.org/) modules.
Forecast
Stations data loggertodb
data
Download FAO PM PET FAO PM
Enhydris calculation PET
timeseries
Timeseries Spatial
Mapserver
Spatial PET
aggregation data
Hourly Spatial WMS and
WCS Irrigation
timeseries interpolation application
services
Soil water
data Desktop GIS
Fig. 4 Flowchart of IRMA system modules
179
The Enhydris database (http://system.irrigation-management.eu,
https://enhydris.readthedocs.org) web interface, with the available meteorological
stations is presented in Fig. 5. It includes a map that provides information about the
location of each station, together with the identification numbers, water basin, water
division, owner and type of the meteorological stations.
Agrometeorological data timeseries and crop water requirements estimations are
provided to users and visitors, while irrigation advices and a series of other utilities
will be available only to registered users. Users that want more precise results will
have to install meteorological and/or soil moisture sensors and dataloggers at their
fields.
Fig. 5. The Enhydris database web interface
Agriculturalists, green infrastructure managers, farmers and gardeners will be able
to use the system for setting up irrigation schedules, plan and record irrigation events
as well as self-training regarding irrigation management.
Figure 6 presents the home page of the system. The main feature is the map
presentation of the different variables, in daily time scale, that are involved in the
irrigation requirements methodology presented above, such as: Rainfall, Potential
Evapotranspiration, Humidity, Temperature, Wind speed and Solar Radiation, with
high spatial resolution of 70×70 m grid. The maps are produced by implementing the
Inverse Distance Weighting (Burrough and McDonnell, 1998) method for spatial
interpolation, found in the GDAL library.
The system provides this information of the study area, through the WMS service
provided by the Mapserver that was set for the purposes of the present project
(http://mapserver.org/). The historical data are kept from 1/1/2015 onwards, while
several maps produced by satellite images are also available.
Registered users can add their fields into the system (Fig. 7) using a map, in order
to pinpoint the geographic location of each field, with the help of the Hellenic
Cadaster orthophoto imagery basemap (http://gis.ktimanet.gr/wms/ktbasemap) that
allows zoom in scales up to 1 m. The user should provide information regarding the
180
field’s area, crop, irrigation type and strategy. Also, a list of the user’s already
register fields is available at the bottom of the page.
Fig. 6. IRMA_SYSTEM front page
If appropriate information is available to the registered users, they are able to
modify the properties of each field, based on this information, as shown in Fig. 7.
This information consists of parameters grouped in three major categories:
• Irrigation Management
• Crop Parameters
• Soil Parameters
Irrigation Management includes information regarding irrigation efficiency and
strategy. Crop includes information regarding the crop coefficient (Kc), the
maximum allowed depletion factor (MAD), the estimated maximum and minimum
root depth. Soil includes information regarding the FC, PWP and Θs. Appropriate
ranges and the system’s default values, according to literature, are available to the
user in order to provide guidance.
181
Fig. 7. The Update Field module of the IRMA_SYSTEM
Since the initial soil moisture is included in the initial conditions of the soil water
balance module of the IRMA_SYSTEM, register users should add the irrigations that
they have applied for each field, in order to get the appropriate irrigation advices. If
the user does not provide information about the applied irrigation water volume, the
system assumes that the applied water was enough in order for the soil to reach field
capacity. Figure 8 depicts the irrigation events list module of the IRMA_SYSTEM.
Fig. 8. The Irrigation Events list module of the IRMA_SYSTEM
182
Since the registered users provide the above information, the system produces
detailed irrigation advice estimates, in hourly basis, based on both historical and
forecast data as presented in Figures 9, 10.
Fig. 9. Irrigation advice module of the IRMA_SYSTEM
2.5 Evaluation and Feedback
A feedback procedure will be available for users that want to contribute to the
improvement and evolution of the system by evaluating it. A series of training
seminars for agriculturalists, which are expected to be the main type of users (in
order to analyze the provided information before make relevant suggestions to
farmers and green spaces managers) will follow the development. Also special
seminars for end users, in order to have a basic understanding of the system
operation will be made. Relevant training and help material will be available at the
tool's web site.
183
Field evaluation will be held for both agriculture and landscaping case studies,
against soil moisture readings from installed sensors at the agrometeorological
stations and irrigation water amount recordings.
Fig. 10. Detailed irrigation report module of the IRMA_SYSTEM.
3 Conclusions
The IRMA_SYSTEM is an added value regional management and planning tool
designed to contribute along with the other tools of IRMA project
(http://www.irrigation-management.eu/) to the improvement of efficiency in
irrigation techniques and irrigation scheduling from farm to water basin level, with
high spatial resolution.
It is a user-friendly computer/mobile-based, open and free modular software that
provides crop water requirements estimations and irrigation advices to users and
visitors, based on agrometeorological data timeseries and a modified FAO 56
approach.
The system is fully customizable, allowing the users to add site and crop specific
information in order to customize the output of the system, taking advantage of
additional information.
It is easily expandable, since the individual modules are independent of the
number of stations and accepts all kinds of forecast data.
184
The feedback and experimental evaluation procedures will contribute to the
further improvement and versatility of the system, aiming at increased experience
gain at regional level with different type of farms, crops and soil water information.
Acknowledgments. This work has been co-financed by EU / ERDF (75%) and
national funds of Greece and Italy (25%) in the framework of the European
Territorial Cooperation Programme (ETCP) GREECE-ITALY 2007-2013
(www.greece-italy.eu): IRMA project (www.irrigation-management.eu), subsidy
contract no: I3.11.06.
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