**1\. Introduction**

##  1.1. Moses project

The background of the project, its concepts and the technologies are described
into the document in [AD1], “ _**Moses Project Grant Agreement and Annexes** _
”, Horizon 2020 Grant Agreement No. 642258\.

The main objective of Moses is “to put in place and demonstrate at the real
scale of application an information platform devoted to water procurement and
management agencies to facilitate planning of irrigation water resources **”**
. To achieve these goals, the MOSES project combines in an innovative and
integrated platform a wide range of data and technological resources: EO data,
probabilistic seasonal forecasting and numerical weather prediction, crop
water requirement and irrigation modelling and online GIS Decision Support
System. The following entities composes the Moses project Consortium:

  1. Esri Italia Spa (Esri), Italy 

  

  2. Agenzia Regionale per la Prevenzione, l'Ambiente e l'Energia dell'Emilia-Romagna (ArpaeER), Italy 

  

  3. Agencia Estatal de Meteorologia (AEMET), Spain 

  

  4. Institutul National de Hidrologie Si Gospodarire a Apelor (INHGA), Romania 

  

  5. Administratia Nationala de Meteorologie R.A. (ANM), Romania 

  

  6. Alma Mater Studiorum - Università Di Bologna (UNIBO), Italy 

  

  7. Asociacion Feragua de Comunidades de Regantes de Andalucia (FER), Spain 

  

  8. Serco Belgium Sa (SERCO), Belgium 

  

  9. Technische Universiteit Delft (DUT), Netherlands 

  

  10. Universidad de Castilla - La Mancha (UCLM), Spain 

  

  11. Universite Chouaib Doukkali (UCD), Morocco 

  

  12. Agromet Srl (AM), Italy 

  

  13. Consorzio di Bonifica di Secondo Grado per il Canale Emiliano Romagnolo (CER), Italy 

  

  14. Aliara Agrícola Sl (ALI), Spain 

  

  15. Aryavarta Space Organization (ASO), India 

  

  16. Consorzio di Bonifica della Romagna (CBR), Italy  1 

  

  

The project started on July 1, 2015, while the Kick-Off meeting took place in
Rome on July 14 and 15, 2015.

##  1.2. Purpose of the document

The purpose of the Data Management Plan (DMP) is to provide an analysis of the
main elements of the data management policy implemented by the members of the
consortium with regard to all the datasets generated within the project.

The document is organized as follows:

  * Chapter 2 provides a brief description of the Release Candidate version of the MOSES DSS (web-site and platform); 

  

  * Chapter 3 describes in details the main points about datasets management required by Annex 1 of [RD3]. Both data sets used as input for the processing platform and outputs of the system (MOSES products) will be analyzed. We will exploit a dataset by dataset approach, as suggested in [RD3]; 

  

  * Chapter 4 describes in details the structure of the web services which exposes REST interfaces to the datasets in Chapter 3; 

  

  * Finally, Chapter 5 provides details about the management of scientific publications resulting from the project, including the exploited datasets and tools. 

  

This document has evolved during the lifespan of the project. New releases of
this document have been delivered in case new dataset types and data
structures changes in order to comply with raising design issues.

##  1.3. Definitions, acronyms and abbreviations

The following table lists acronyms and abbreviations used in this document.  
  
<table>  
<tr>  
<th>

AD

</th>  
<th>

Applicable Document

</th> </tr>  
<tr>  
<td>

CMS

</td>  
<td>

Content Management System

</td> </tr>  
<tr>  
<td>

DA

</td>  
<td>

Demonstration Area

</td> </tr>  
<tr>  
<td>

DSS

</td>  
<td>

Decision Support System

</td> </tr>  
<tr>  
<td>

EASME

</td>  
<td>

European Agency for Small and Medium Enterprises

</td> </tr>  
<tr>  
<td>

ECM

</td>  
<td>

Early Season Crop Maps

</td> </tr>  
<tr>  
<td>

EO

</td>  
<td>

Earth Observation

</td> </tr>  
<tr>  
<td>

GIS

</td>  
<td>

Geographical Information System

</td> </tr>  
<tr>  
<td>

ISCM

</td>  
<td>

In-Season Crop Maps

</td> </tr>  
<tr>  
<td>

IT

</td>  
<td>

Information Technology

</td> </tr>  
<tr>  
<td>

LAI

</td>  
<td>

Leaf Area Index

</td> </tr>  
<tr>  
<td>

NA

</td>  
<td>

Not Applicable

</td> </tr>  
<tr>  
<td>

RD

</td>  
<td>

Reference Document

</td> </tr>  
<tr>  
<td>

SF

</td>  
<td>

Seasonal Forecast

</td> </tr>  
<tr>  
<td>

SWS

</td>  
<td>

Synthetic Weather Series

</td> </tr>  
<tr>  
<td>

SYGMA

</td>  
<td>

System for Grant MAnagement

</td> </tr>  
<tr>  
<td>

UAA

</td>  
<td>

Utilized Agricultural Area

</td> </tr>  
<tr>  
<td>

WBS

</td>  
<td>

Work Breakdown Structure

</td> </tr>  
<tr>  
<td>

WP

</td>  
<td>

Work Package

</td> </tr> </table>

##  1.4. Applicable and reference documents

The following documents are applicable:

[AD1] “ _**Moses Project Grant Agreement and Annexes** _ ”, Horizon 2020 Grant
Agreement No. 642258

[AD2] _**“AMENDMENT to Moses Project Grant Agreement and Annexes** _ ”,
Horizon 2020 Reference No. AMD-642258-5

The following documents are used as references:

[RD1] Moses Consortium Agreement, version 2, 2015-05-18

[RD2] Guidelines on Open Access to Scientific Publications and Research Data
in Horizon 2020, Version 2.1, 15 February 2016

[RD3] Guidelines on Data Management in Horizon 2020, Version 2.1, 15 February
2016

[RD4] Moses Deliverable D2.2 (Design Definition File)

[RD5] Moses Deliverable D3.1 (Crop Mapping Package)

#  2\. Integrated Exploitation Platform

##  MOSES website

The MOSES project website is available at the link  _http://www.moses-
project.eu/_ .  The website has been developed using the well-known CMS
Wordpress, and is hosted by the company Webfaction. A screenshot of the
welcome page of the website is shown in the following Figure 1.

**Figur**

**e**

**1**

**-**

**Screenshot of the MOSES**

**public web site**

##  MOSES platform

All data coming from the MOSES platform have been centralized into a webGIS
portal. The public URL of the project’s portal is the following:
_https://moses.esriitalia.it/portal_ .  The portal is also accessible from the
link “Portal” of the project’s official website:  _www.moses-project.eu/_ A
screenshot of the welcome page of the portal is shown in the following Figure
2.

**Figure**

**2**

**-**

**Screenshot of the MOSES web**

**GIS**

**portal**

As the WebGIS portal is a tool mainly for GIS-expert users, during the Beta
and Release Candidate phase of the project has been developed a specific web
application for the final user. Such application has been designed according
to the feedbacks of MOSES Demonstration Area partners, and a very fine work of
tailoring and customization has been performed.

The web application has been deployed for every DA, and the URL is:
_https://moses.esriitalia.it/mosesviewer_rc_xx/_ , where xx = {it, sp, mo, ro}
is the identifier of the DA. Web applications are profiled and users can
access with their credentials of MOSES portal. A screenshot of the web
application is shown in the following Figure 3.

**Figure 3 - Screenshot of the MOSES front-end web application**

#  3\. Datasets generated by MOSES platform

During the activities of the project, several datasets have been generated by
the MOSES platform. In the following there is a list of the high-level
products (refer to [RD3] for more details).  
  
<table>  
<tr>  
<th>

**ID**

</th>  
<th>

**Product Name**

</th>  
<th>

**Brief Description**

</th> </tr>  
<tr>  
<td>

1

</td>  
<td>

Crop raster maps

</td>  
<td>

Raster images showing the crop classification in the demonstration areas. Two
kinds of dataset will be produced each year for each demonstration area: an

“early season” classification of macro-classes and an in-season crop
classification, updated on weekly or fortnightly basis

</td> </tr>  
<tr>  
<td>

2

</td>  
<td>

Seasonal probabilistic forecast

</td>  
<td>

XML files containing the seasonal probabilistic forecast of 6 climatological
indices (expressed as anomalies with respect to the climatological averages).
Each file refers to a cell of the downscaling grid on the demonstration area.
The frequency of generation depends on the length of the irrigation season and
it ranges from once per year to once per month.

</td> </tr> </table>  
<table>  
<tr>  
<th>

**ID**

</th>  
<th>

**Product Name**

</th>  
<th>

**Brief Description**

</th> </tr>  
<tr>  
<td>

3

</td>  
<td>

Synthetic weather series generated from seasonal probabilistic forecasts

</td>  
<td>

Comma separated value files of synthetic daily weather data (minimum and
maximum temperature, precipitation) computed by a weather generator fed by
climate data and seasonal probabilistic forecast. Each file refers to a cell
of the local meteo grid on the demonstration area. The frequency of emission
depends on the length of the irrigation season and it ranges from once for
year to once for month.

</td> </tr>  
<tr>  
<td>

4

</td>  
<td>

Phenological stage data

</td>  
<td>

Raster images and statistical tables of the phenological stage of the
monitored crops in the demonstration areas, computed by the “crop water demand
processor”. During crop growing season, these datasets will be updated on a
weekly basis

</td> </tr>  
<tr>  
<td>

5

</td>  
<td>

Short-term forecasts of crop water demand

</td>  
<td>

Raster images and statistic tables containing the short-term forecasts of crop
water demand, computed by the “crop water demand processor”. During crop
season, these datasets will be updated on a weekly basis

</td> </tr>  
<tr>  
<td>

6

</td>  
<td>

Crop water demand monitoring data

</td>  
<td>

Raster images and statistical tables of current crop water demand, computed by
the “crop water demand processor”. During crop season, these datasets will be
updated on a weekly basis

</td> </tr>  
<tr>  
<td>

7

</td>  
<td>

Seasonal irrigation forecasts

</td>  
<td>

This product is composed by two comma separated value files: seasonal
irrigation climate and seasonal irrigation forecast, where season means a
3month period.

Both the outputs are the statistical distribution of irrigations estimated by
the soil water balance processor and expressed as percentiles for each
computational unit.

The frequency of emission depends on the length of the irrigation season and
it ranges from once for year to once for month.

</td> </tr>  
<tr>  
<td>

8

</td>  
<td>

Short-term irrigation forecasts

</td>  
<td>

Comma separated value files containing the status of crop water availability,
forecasts of rainfall and crop water needs for the next 7 days and model
assessment of previous irrigations, for each computational unit of the
demonstration area. This product is updated on a daily basis.

</td> </tr>  
<tr>  
<td>

9

</td>  
<td>

In field measures of water balance components

</td>  
<td>

Tables containing direct (in field) measurements of water balance components,
collected in the Demonstration Area during crop season.

</td> </tr> </table>

The following paragraphs reports, for each product, the datasets generated
with their main characteristics.

##  3.1. Crop raster maps

This product consists in the two following datasets, which are described in
details in subsequent paragraphs:

  * Early crop map 

  

  * In season crop map 

  

###  3.1.1 Early Season Crop Maps (ECM)  
  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

ECM

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Early (Functional) Crop Map

</td> </tr>  
<tr>  
<td>

Purpose

</td>  
<td>

_Mapping of broad crop classes at a very early stage in the irrigation season
used to estimate crop water requirements from mid spring to summer season in
combination with seasonal probabilistic forecasts and a soil water balance
model._

</td> </tr>  
<tr>  
<td>

Description (Content Specification):

</td>  
<td>

_Early season crop classification mapping relies on the possibility to
discriminate irrigated crops prior to the growing season start; it is based on
a few satellite images, selected at given time windows: classes are aggregated
crops, also indicated as “Crop Functional Groups”; it is intended that if such
mapping is not feasible the seasonal irrigation forecast module will derive
such information from alternative sources (Land Use/Land cover maps,
statistics, ground surveys, etc.)._

</td> </tr>  
<tr>  
<td>

Output Layers  2  :

</td>  
<td>

  1. _Vector: EARLY_CROP_CLASS_

  

  2. _Raster: EARLY_CROP_CLASS_

  

  

_Id of the crop map class (integer value)._

</td> </tr>  
<tr>  
<td>

Measurement Unit:

</td>  
<td>

_N/A_

</td> </tr>  
<tr>  
<td>

Temporal/spatial applicable domains:

</td>  
<td>

_Yearly/District area (TBC)_

</td> </tr>  
<tr>  
<td>

Temporal coverage

</td>  
<td>

_One year_

</td> </tr>  
<tr>  
<td>

Spatial Coverage / Area:

</td>  
<td>

_Demonstration area_

</td> </tr>  
<tr>  
<td>

Spatial Resolution / Scale (Data Grid):

</td>  
<td>

  1. _Vector derived from the EO input data / 1:10000 scale_

  

  2. _Raster derived from the EO input data / 20x20m_

  

  

</td> </tr>  
<tr>  
<td>

Geographic projection / Reference system:

</td>  
<td>

_UTM WGS84_

</td> </tr> </table>  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

ECM

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Early (Functional) Crop Map

</td> </tr>  
<tr>  
<td>

Input Data/Sources:

</td>  
<td>

_EO data:_

  * _L8 from USGS_

  

  * _S2 from DHUS No EO DATA:_

  

  * _Agronomic scheme [RD5]_

  

  * _Orchards and vineyards mask [RD5]_

  

  * _AOI mask [RD5]_

  

  * _Agricultural mask (UAA Utilized Agricultural Area) [RD5]_

  

  * _Verification data: Ground true from three ground surveys (selected crop fields Shapefile)_

  

</td> </tr>  
<tr>  
<td>

Input Data Archiving and rolling policies

</td>  
<td>

_5 GB / rolling policy one year_

</td> </tr>  
<tr>  
<td>

Frequency of update (refresh rate):

</td>  
<td>

_One year_

</td> </tr>  
<tr>  
<td>

Format:

</td>  
<td>

_Vector/Raster_

</td> </tr>  
<tr>  
<td>

Naming convention:

</td>  
<td>

_MOSES_ECM_YYYYMMDD_SSyyyyddd_SSyyyyddd_SSyyyddd.shp where:_

  * _MOSES_ECM is the product identifier_

  

  * _yyyyddd is the sensing day of the tree images used in input in format year/doy_

  

  * _SS satellite ID (S2 or L8)_

  

  * _YYYYMMDD is the generation time of the early crop map_

  

</td> </tr>  
<tr>  
<td>

Product ID.

</td>  
<td>

ECM

</td> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Early (Functional) Crop Map

</td> </tr>  
<tr>  
<td>

Archiving and preservation

</td>  
<td>

_Amount of data generated: 1 GB per year_

_Given the demonstration purpose of the alpha release of the MOSES platform,
all Early Crop Maps generated (as like as all other outputs generated during
the project) are saved on a storage server set up in Esri Italia premises._

_In details, the storage server has been implemented as a virtual disk (with
1TB capacity) inside the private Storage Area Network (SAN) owned by Esri
Italia._

_The system is managed with VMware HA Clusters e VMware DRS technologies,
which ensure a high degree of redundancy and availability. Virtual disks are
distributed on shared arrays on the SAN, and every array implements RAID-5
(rotating parity) level, plus a spare-disk that comes into operation in case
of malfunctioning of each single unit._

_The storage server will be kept available for the whole duration of the
project. Procedures for maintenance of data after the end of the project will
be defined during the development of the beta release of the system._

</td> </tr>  
<tr>  
<td>

Data sharing:

</td>  
<td>

_Access to the storage server is possible through FTP protocol, exploiting any
FTP client application with the following parameters:_

_IP: 84.253.153.145_

_Username: client_

_Password: mosesClient_

_Port: 21_

_Early Crop Maps can be found in the server folder:_

_DA_XX/YYYY/ECM/_

_Where XX represents the demonstration area code (currently only "IT", namely
the "Consorzio di Bonifica di Romagna") and YYYY is the year (currently only
data belonging to crop season 2016 are available)._

_Inside this folder, it is possible to find two subfolders, named “RASTER” and
“VECTOR”, which contain the product in the two formats._

</td> </tr>  
<tr>  
<td>

Standards and metadata:

</td>  
<td>

</td> </tr> </table>

**3.1.2 In-Season Crop Maps (ISCM)**  
  
<table>  
<tr>  
<th>

**Product ID.**

</th>  
<th>

</th> </tr>  
<tr>  
<td>

**Product Name**

</td>  
<td>

**In-Season Crop Map**

</td> </tr>  
<tr>  
<td>

**Purpose**

</td>  
<td>

\- _Mapping the extent of specific crop at quarterly /monthly frequency using
satellite observed multispectral data._

</td> </tr>  
<tr>  
<td>

**Description (Content Specification):**

</td>  
<td>

\- _Layer of segments/fields containing information about the presence of
specific crops._

</td> </tr>  
<tr>  
<td>

**Output Layers:**

</td>  
<td>

\- Id_icm : ID of the crop map class (integer value).

</td> </tr>  
<tr>  
<td>

**Measurement Unit:**

</td>  
<td>

\- _N/A_

</td> </tr>  
<tr>  
<td>

**Temporal/spatial applicable domains:**

</td>  
<td>

\- _Quarterly/District area_

</td> </tr>  
<tr>  
<td>

**Temporal coverage**

</td>  
<td>

\- _Quarterly_

</td> </tr>  
<tr>  
<td>

**Spatial Coverage / Area:**

</td>  
<td>

\- _Demonstration area_

</td> </tr>  
<tr>  
<td>

**Spatial Resolution / Scale (Data Grid):**

</td>  
<td>

\- _Vectorial derived from the EO input data / 1:10000_

</td> </tr>  
<tr>  
<td>

**Geographic projection /** **Reference system:**

</td>  
<td>

\- _UTM WGS84_

</td> </tr>  
<tr>  
<td>

**Input Data/Sources:**

</td>  
<td>

  * _EO data:_

  

  * _S2 Bottom of Atmosphere (BOA) reflectance from satellite images downloaded in the pre-processing module. Other data:_

  

  * _Training set/ground truth [RD5]_

  

  * _Orchards and vineyards mask [RD5]_

  

\-

</td> </tr>  
<tr>  
<td>

**Input Data Archiving and rolling policies**

</td>  
<td>

  * _EO data:_

  

  * _7 GB / 2 months (forecast considering all four DA, satellite image acquisition every 5 days and 12 bands) Other data:_

  

  * _Less than 50 MB/yearly_

  

</td> </tr>  
<tr>  
<td>

**Frequency of update (refresh rate):**

</td>  
<td>

\- _15-30 days_

</td> </tr>  
<tr>  
<td>

**Format:**

</td>  
<td>

\- _Vector/Raster_

</td> </tr>  
<tr>  
<td>

**Naming convention:**

</td>  
<td>

  * _MOSES_ICM_SSYYYYMMDD1_ SSYYYYMMDD2_YYYYMMDD:_

  

_Where:_

  * _MOSES_ICM is the product identifier_

  

  * _YYYYMMDD1 is the sensing day of the first image used in input in format year/doy_

  

  * _YYYYMMDD2 is the sensing day of the second image used in input in format year/doy_

  

  * _SS satellite ID (S2)_

  

  * _YYYYMMDD is the generation time of the crop map_

  

</td> </tr>  
<tr>  
<td>

**Product ID.**

</td>  
<td>

</td> </tr>  
<tr>  
<td>

**Product Name**

</td>  
<td>

**In-Season Crop Map**

</td> </tr>  
<tr>  
<td>

**Archiving and preservation**

</td>  
<td>

_Amount of data generated: less than 1GB per year_

_Same solution adopted for storage of Early Crop Maps (see paragraph 3.1.1)_

</td> </tr>  
<tr>  
<td>

**Data sharing:**

</td>  
<td>

_Data access through FTP protocol (connection parameters reported in “data
sharing” section of paragraph 3.1.1)_

_In Season Crop Maps can be found in the server folder:_

_DA_XX/YYYY/ISCM/_

_Where XX represents the demonstration area code and YYYY is the year._

_Inside this folder, it is possible to find a subfolder named “VECTOR” which
contain the product._

</td> </tr>  
<tr>  
<td>

**Standards and metadata:**

</td>  
<td>

</td> </tr> </table>

##  3.2. Seasonal probabilistic weather forecast  
  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

Seasonal Forecast (SF)

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Seasonal probabilistic forecast

</td> </tr>  
<tr>  
<td>

**Purpose**

</td>  
<td>

Seasonal probabilistic forecast includes the multi-model ensembles of seasonal
anomalies forecast, with respect to the reference climate, for 6 climate
indices, needed as input of the weather generator.

</td> </tr>  
<tr>  
<td>

**Description (Content Specification):**

</td>  
<td>

This product provides specific information on the output of the statistical
calibration processor, needed as input of the weather generator processor.

The statistical downscaling processor is meant to remove all systematic biases
at local scale from the multi-model seasonal forecast EUROSIP outputs and to
calibrate the predictions of local climate indices on the observed local
climate using the same reference period.

For each cell of the local analysis meteo grid the forecasts are produced as
anomalies with respect to the climate for the 6 indices needed as input by the
Weather Generator processor, namely: o total precipitation (Prec3M); o
probability of wet days (WetDaysFrequency) ; o probability of a wet day after
a wet day

(WetWetDaysFrequency); o average minimum temperature (Tmin); o average maximum
temperature (Tmax);

o average difference of maximum temperature between dry and wet days
(DeltaTmaxDryWet).

</td> </tr> </table>  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

Seasonal Forecast (SF)

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Seasonal probabilistic forecast

</td> </tr>  
<tr>  
<td>

**Layers(*):**

</td>  
<td>

The XML files contain the following elements (full dots) and corresponding
attributes (rings):·

◦ point: description of the computation area to which forecasts refers

◦ name – geographical name of location

◦ code – conventional point code

◦ lon – WGS84 longitude of center of computation area

◦ lat – WGS84 latitude of center of computation area

◦ info – other information

climate: description of reference climate

◦ from – year in which reference climate begins

◦ to – year in which the reference climate ends

models: description of the systems contributing to the multi-model

ensemble

◦ number – number of systems contributing to the ensemble

◦ name – acronym for all the systems contributing to the ensemble

◦ members – number of ensemble members for each system

◦ repetitions – number of repetitions (typically 1)

◦ year – year to which the seasonal forecast refers

◦ season – acronym of the season to which the seasonal forecast refers

forecast: includes all ensemble member forecast values for the 6 climate index
anomalies

◦ var – describe each forecast field including:

▪ type – acronym of the field

▪ attribute – full field or anomaly (anomalies in our case)

▪ value – all ensemble member values for the field

</td> </tr>  
<tr>  
<td>

**Measurement Unit:**

</td>  
<td>

lon,lat: decimal degrees PREC3M: mm

WetDaysFrequency: %

WetWetDaysFrequency: %

Tmin: °C

Tmax: °C

DeltaTmaxDryWet: °C

</td> </tr> </table>  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

Seasonal Forecast (SF)

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Seasonal probabilistic forecast

</td> </tr>  
<tr>  
<td>

**Field of Applicability (Temporal/Spatial):**

</td>  
<td>

Seasonal / District area

</td> </tr>  
<tr>  
<td>

**Temporal coverage**

</td>  
<td>

3-months

</td> </tr>  
<tr>  
<td>

**Spatial Coverage / Area:**

</td>  
<td>

Computation area

</td> </tr>  
<tr>  
<td>

**Spatial Resolution / Scale (Data Grid):**

</td>  
<td>

Depending on the resolution of the local analysis grid (e.g.: for Italy, ERG5
analysis : 5 Km)

</td> </tr>  
<tr>  
<td>

**Geographic projection /** **Reference system:**

</td>  
<td>

WGS84

</td> </tr>  
<tr>  
<td>

**Input Data/Sources:**

</td>  
<td>

The ensemble multi-model seasonal forecast anomalies over the computation area
are extracted from the calibrated multi-model seasonal prediction produced
over the corresponding national domain.

These calibrated predictions are obtained by applying a MOS (Model Output
Statistics) statistical downscaling scheme using as input the multi-model
operational EUROSIP seasonal predictions (for more details see D3.2 - Seasonal
probabilistic forecasting).

An Identities table of the cells belonging to the analysis grid in .csv format
is needed to feed this processor. The table has to contain the following
fields:

  * Id_meteo: identifier of the cell (5 digits) 

  

  * Table_name: name of the datatable in the meteo db (tipically: GRD_XXXXX where XXXXX is the id_meteo) 

  

  * Meteo_name: name of the location 

  

  * Longitude: longitude of the central point of the cell in decimal degrees 

  

  * Latitude: latitude of the central point of the cell in decimal degrees 

  

  * Height: height in meters of the central point of the cell 

  

</td> </tr>  
<tr>  
<td>

**Input Data Archiving and rolling policies**

</td>  
<td>

The inputs are not archived in the system

</td> </tr>  
<tr>  
<td>

**Frequency of update (refresh rate):**

</td>  
<td>

Monthly

</td> </tr> </table>  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

Seasonal Forecast (SF)

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Seasonal probabilistic forecast

</td> </tr>  
<tr>  
<td>

**Format:**

</td>  
<td>

Extensible Markup Language file (.xml) with the following elements (full dots)
and corresponding attributes (rings): point

◦ name – alphanumeric string

◦ code – integer 4 digit

◦ lon – float, 6 digit, precision 3 digits

◦ lat – float, 6 digit, precision 3 digits

◦ info – alphanumeric string

climate -

◦ from – integer 4 digit

</td> </tr>  
<tr>  
<td>

</td>  
<td>

◦

</td>  
<td>

to – integer 4 digit

</td> </tr>  
<tr>  
<td>

</td>  
<td>

models

◦

</td>  
<td>

number – integer 1 digit

</td> </tr>  
<tr>  
<td>

</td>  
<td>

◦

</td>  
<td>

name – alphanumeric 4 digit array with dimension ‘number’

</td> </tr>  
<tr>  
<td>

</td>  
<td>

◦

</td>  
<td>

member – integer 2 digit array with dimension ‘number’

</td> </tr>  
<tr>  
<td>

</td>  
<td>

◦

</td>  
<td>

repetition – integer 1 digit

</td> </tr>  
<tr>  
<td>

</td>  
<td>

◦

</td>  
<td>

year – integer 4 digit

</td> </tr>  
<tr>  
<td>

</td>  
<td>

◦

</td>  
<td>

season – alphanumeric 3 digit

</td> </tr>  
<tr>  
<td>

</td>  
<td>

forecast ◦

</td>  
<td>

var

▪ type – alphanumeric string

▪ attribute – alphanumeric string

▪ value – float array with dimension nrModels * nrMembers

</td> </tr>  
<tr>  
<td>

**Naming convention:**

</td>  
<td>

**File name convention:** **GRD_XXXXX.csv** where:

● **XXXXX** is the identifier of the cell that refers to the local meteo
analysis grid

**Folder name convention:**

see “Data Sharing” section of this table

</td> </tr>  
<tr>  
<td>

Product ID.

</td>  
<td>

Seasonal Forecast (SF)

</td> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Seasonal probabilistic forecast

</td> </tr>  
<tr>  
<td>

**Archiving and preservation**

</td>  
<td>

About 10 kb for each XML file (corresponding to each cell on the local climate
observational analysis grid).

Example for a DA with 100 weather grid cells (12 forecasts): Annual storage:
100 * 12 * 10 kb = 12 Mb

All files and folder are archived on a storage server made available on Esri
Italia premises (same solution adopted for storage of Early Crop Maps
described in paragraph 3.1.1).

</td> </tr>  
<tr>  
<td>

**Data sharing:**

</td>  
<td>

Data access is possible through FTP protocol (connection parameters reported
in “data sharing” section of paragraph 3.1.1)

Weather forecasts are saved in folders that can be found in the server folder:

DA_XX/YYYY/SF/MMM/

Where XX represents the demonstration area code, YYYY the year and MMM the
acronym of the 3-months forecast period.

</td> </tr>  
<tr>  
<td>

**Standards and metadata:**

</td>  
<td>

</td> </tr> </table>

##  3.3. Synthetic weather series generated from seasonal probabilistic
forecasts  
  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

Synthetic Weather Series (SWS)

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Synthetic weather series generated from seasonal probabilistic forecasts

</td> </tr>  
<tr>  
<td>

**Purpose**

</td>  
<td>

The synthetic series of seasonal forecasts of daily temperature, precipitation
and, if available, potential evapotranspiration are one the input data sources
that feed the seasonal version of soil water balance processor in order to
produce seasonal irrigation forecasts.

</td> </tr>  
<tr>  
<td>

**Description (Content Specification):**

</td>  
<td>

The SyntheticSeries are an intermediate product between two different MOSES
processors: it is the output of the Weather Generator processor and it is one
of the input of the Seasonal irrigation forecast processor. It provides, for
each cell of the weather grid on the computation area, a synthetic series of
daily data of temperature and precipitation that represents the probabilistic
seasonal forecast.

In more details, the number _n_ of years of the synthetic series depends on
the number of _members_ and _repetitions_ of each _models_ of the
probabilistic seasonal anomalies forecast (see XML file description). Each
year of the series is composed by observed data of the previous 9months and a
synthetic series generated by the weather generator processor for the 3-months
forecast period.

The weather generator processor is fed by climate data and a probabilistic
seasonal anomalies forecast XML file (see the SeasonalForecasts description).

For instance, if the seasonal forecast refers to the summer season JJA (June,
July and August), each 12-months period of the SyntheticSeries is composed by
9 months of observed daily data (from the 1  st  of September of the year
before the forecast until the 31  st  of May of the forecast year) and 3
months of generated daily data (June, July and August).

</td> </tr>  
<tr>  
<td>

**Layers(*):**

</td>  
<td>

Each record is composed by the following fields:

  1. **date** : date of generated year 

  

  2. **tmin** : daily minimum air temperature 

  

  3. **tmax** : daily maximum air temperature 

  

  4. **tavg** : daily average air temperature 

  

  5. **prec** : total daily precipitation 

  

  6. **etp** : total daily evapotranspiration (not mandatory, to be implemented) 

  

  

</td> </tr> </table>  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

Synthetic Weather Series (SWS)

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Synthetic weather series generated from seasonal probabilistic forecasts

</td> </tr>  
<tr>  
<td>

**Measurement Unit:**

</td>  
<td>

  * tmin: °C 

  

  * tmax: °C 

  

  * tavg: °C 

  

  * prec: mm 

  

  * etp: mm 

  

</td> </tr>  
<tr>  
<td>

**Field of Applicability (Temporal/Spatial):**

</td>  
<td>

Seasonal / District area

</td> </tr>  
<tr>  
<td>

**Temporal coverage**

</td>  
<td>

3-months

</td> </tr>  
<tr>  
<td>

**Spatial Coverage / Area:**

</td>  
<td>

Each file cover one cell of the weather grid

</td> </tr>  
<tr>  
<td>

**Spatial Resolution / Scale (Data Grid):**

</td>  
<td>

Same resolution of the weather grid

</td> </tr>  
<tr>  
<td>

**Geographic projection /** **Reference system:**

</td>  
<td>

UTM WGS84

</td> </tr>  
<tr>  
<td>

**Input Data/Sources:**

</td>  
<td>

This product is the output of the Weather generator processor fed by:

  * probabilistic seasonal forecast anomalies XML file (see the Seasonal Forecasts description) 

  

  * climate data (daily temperature and precipitation, at least 20 years) (for more details see D3.3 - Irrigation forecasting package) 

  

  * observed weather data (daily temperature and precipitation, at least the last 9 months before the forecast until the first day of seasonal forecast) 

  

</td> </tr>  
<tr>  
<td>

**Input Data Archiving and rolling policies**

</td>  
<td>

  * Seasonal forecast anomalies XML: about 10 kb for file 

  

  * Climate data: about 300 kb for each weather grid cell 

  

  * Observed data: about 20 kb for each weather grid cell Rolling policy: year 

  

</td> </tr>  
<tr>  
<td>

**Frequency of update (refresh rate):**

</td>  
<td>

monthly (when seasonal irrigation forecast is requested)

</td> </tr>  
<tr>  
<td>

**Format:**

</td>  
<td>

Comma separated value file (.csv), with the following fields:

  * date, ISO8601 format (YYYY-MM-DD) 

  

  * tmin, float, precision: 1 digit 

  

  * tmax, float, precision: 1 digit 

  

</td> </tr>  
<tr>  
<td>

Product ID.

</td>  
<td>

Synthetic Weather Series (SWS)

</td> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Synthetic weather series generated from seasonal probabilistic forecasts

</td> </tr>  
<tr>  
<td>

</td>  
<td>

  * tavg, float, precision: 1 digit 

  

  * prec, float, precision: 1 digit 

  

  * etp, float, precision: 1 digit 

  

</td> </tr>  
<tr>  
<td>

**Naming convention:**

</td>  
<td>

**File name convention:** **GRD_XXXXX.csv** where:

  * **XXXXX** is the identifier of the cell that refers to the local meteo analysis grid 

  

**Folder name convention:**

  * see “Data Sharing” section of this table 

  

</td> </tr>  
<tr>  
<td>

**Archiving and preservation**

</td>  
<td>

Each synthetic series requires about 1 Mb of storage.

Example of annual storage for a DA with 100 weather grid cells and three
seasonal irrigation forecast for year:

Annual storage: 100 * 3 * 1 Mb = 300 Mb

All files and folder are archived on a storage server made available on Esri
Italia premises (same solution adopted for storage of Early Crop Maps
described in paragraph 3.1.1).

</td> </tr>  
<tr>  
<td>

**Data sharing:**

</td>  
<td>

Data access is possible through FTP protocol (connection parameters reported
in “data sharing” section of paragraph 3.1.1)

Synthetic weather series are saved in folders that can be found in the server
folder:

DA_XX/YYYY/SWS/MMM

Where XX represents the demonstration area code, YYYY is the year and MMM the
acronym of the 3-months forecast period.

</td> </tr>  
<tr>  
<td>

**Standards and metadata:**

</td>  
<td>

</td> </tr> </table>

##  3.4. Phenological stage data

This MOSES product consists in the two following datasets, which are described
in details in subsequent tables:

  * Leaf Area Index (LAI) 

  

  * Normalized Difference Vegetation Index (NDVI) 

  

###  3.4.1 Leaf Area Index (LAI)  
  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

LAI

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Leaf Area Index

</td> </tr>  
<tr>  
<td>

Purpose

</td>  
<td>

_Mapping and monitoring of Leaf Area Index (LAI) biophysical variable by means
of remote sensing multispectral data. The monitoring is performed at 5 days
temporal resolution or more depending on the availability of remote sensing
multispectral observations._

</td> </tr>  
<tr>  
<td>

Description (Content Specification):

</td>  
<td>

_The LAI is the amount of one-sided leaf area per unit area of ground.
Different plant functional types will possess a different amount, range and
temporal evolution of leaf area, leaf biomass and leaf area density. The
product includes also layers containing zonal statistics (mean and standard
deviation) over segments/fields (=unit map defined in the “in season crop map
module”)._

</td> </tr>  
<tr>  
<td>

Output Layers:

</td>  
<td>

_Vector layers:_

  1. _LAI_mean_DOYaa_

  

  2. _LAI_std_DOYaa Raster:_

  

  

_1\. LAI_DD_MM_AA_

</td> </tr>  
<tr>  
<td>

Measurement Unit:

</td>  
<td>

_m 2/m 2_

</td> </tr>  
<tr>  
<td>

Temporal/spatial applicable domains:

</td>  
<td>

_Daily/District area_

</td> </tr>  
<tr>  
<td>

Temporal coverage

</td>  
<td>

_Daily_

</td> </tr>  
<tr>  
<td>

Spatial Coverage / Area:

</td>  
<td>

_Demonstration area_

</td> </tr>  
<tr>  
<td>

Spatial Resolution / Scale (Data Grid):

</td>  
<td>

_Vectorial derived from the EO input data / 1:10000_

_Raster derived from the EO input data / from 10x10m (Sentinel) to 30 x 30m
(Landsat 8)_

</td> </tr>  
<tr>  
<td>

Geographic projection / Reference system:

</td>  
<td>

_UTM WGS84_

</td> </tr> </table>  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

LAI

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Leaf Area Index

</td> </tr>  
<tr>  
<td>

Input Data/Sources:

</td>  
<td>

_EO data:_

  * _L8 TOA or S2 BOA reflectance (rf,: DD 3.4). No EO DATA:_

  

  * _csv file of input crop parameters and others (rf,:D3.4)_ ● _UCM vector_

  

</td> </tr>  
<tr>  
<td>

Input Data Archiving and rolling policies

</td>  
<td>

_EO data_

_2 GB / quarterly_

_NO EO data:_

_10 MB / rolling policy 1 time_

</td> </tr>  
<tr>  
<td>

Frequency of update (refresh rate):

</td>  
<td>

_Daily_

</td> </tr>  
<tr>  
<td>

Format:

</td>  
<td>

_Vector /Raster_

</td> </tr>  
<tr>  
<td>

Naming convention:

</td>  
<td>

_Raster_

_MOSES_LAI_YYYYMMDD_ SS_yyyyDOY.tif where:_

  * _MOSES_LAI is the product identifier_

  

  * _YYYYMMDD is the generation time of the LAI_

  

  * _SS satellite ID (S2 or L8)_

  

  * _yyyyDOY is the sensing day used in input in format year/doy_

  

</td> </tr>  
<tr>  
<td>

Archiving and preservation

</td>  
<td>

_Amount of data generated: 1,5 GB per 15 days_

Raster images and vector data are archived on a storage server made available
on Esri Italia premises (same solution adopted for storage of Early Crop Maps
described in paragraph 3.1.1).

</td> </tr> </table>  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

LAI

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Leaf Area Index

</td> </tr>  
<tr>  
<td>

Data sharing:

</td>  
<td>

Data access is possible through FTP protocol (connection

parameters reported in “data sharing” section of paragraph 3.1.1)

Raster images of LAI parameter are saved in the following folder on the
server:

DA_XX/YYYY/CWD/RASTER/LAI/

Where XX represents the demonstration area code and YYYY is the year.

“CWD” folder contains all outputs of the Crop Water Demand processor, divided
into “raster” and “vector” products. Inside the “RASTER” sub-folder it is then
possible to find specific directories of each product. Finally, inside the
“LAI” folder user can find the “tiff” files named according to the above
mentioned convention.

LAI in vector format is available as a field of the “Unit Crop Map” shapefile,
that can be found in the directory:

DA_XX/YYYY/CWD/VECTOR/

Inside this directory, files are named according to the following convention:

UCM_DA_YYYY_SEA_DOY

Where DA is identifier of Demo Area, e.g. “SP”; SEA is identifier of
irrigation season (initial of reference month, e.g. “JJA” for JuneJuly-
August); YYYY refers to the current year and DOY is the Day Of Year of the
computation. A unique file contains LAI indices, as like as NDVI, KC, CWD and
CWDF data described in the following paragraphs, since they are all computed
with the same processor. A unique file contains LAI indices, as like as NDVI,
KC, CWD and CWDF data described in the following paragraphs.

</td> </tr>  
<tr>  
<td>

Standards and metadata:

</td>  
<td>

</td> </tr> </table>

###  3.4.2. Normalized Difference Vegetation Index (NDVI)  
  
<table>  
<tr>  
<th>

**Product ID.**

</th>  
<th>

**NDVI**

</th> </tr>  
<tr>  
<td>

**Product Name**

</td>  
<td>

**Normalized Difference Vegetation Index**

</td> </tr>  
<tr>  
<td>

**Purpose**

</td>  
<td>

_Mapping and monitoring of Normalized Difference Vegetation index (NDVI) by
means of remote sensing multispectral data. The monitoring is performed at 5
days temporal resolution or more depending on the availability of remote
sensing multispectral observations._

</td> </tr>  
<tr>  
<td>

**Description (Content Specification):**

</td>  
<td>

_The NDVI is an index of plant “greenness” or photosynthetic activity, and is
one of the most commonly used vegetation indices. The product includes also
layers containing zonal statistics (mean and standard deviation) over
segments/fields (=unit map defined in the “in season crop map module”)._

</td> </tr>  
<tr>  
<td>

**Output Layers:**

</td>  
<td>

_Vector layers:_

  1. _NDVI_mean_DOYaa_

  

  2. _NDVI_std_DOYaa_

  

  

_Raster:_

_1\. NDVI_DD_MM_AA_

</td> </tr>  
<tr>  
<td>

**Measurement Unit:**

</td>  
<td>

_adimensional_

</td> </tr>  
<tr>  
<td>

**Temporal/spatial applicable domains:**

</td>  
<td>

_Daily /District Area_

</td> </tr>  
<tr>  
<td>

**Temporal coverage**

</td>  
<td>

_Daily_

</td> </tr>  
<tr>  
<td>

**Spatial Coverage / Area:**

</td>  
<td>

_Demonstration Area_

</td> </tr>  
<tr>  
<td>

**Spatial Resolution / Scale (Data Grid):**

</td>  
<td>

_Vectorial derived from the EO input data / 1:10000_

_Raster derived from the EO input data / from 10x10m (Sentinel) to 30 x 30m
(Landsat 8)_

</td> </tr>  
<tr>  
<td>

**Geographic projection /** **Reference system:**

</td>  
<td>

_UTM WGS84_

</td> </tr>  
<tr>  
<td>

**Input Data/Sources:**

</td>  
<td>

_EO data:_

_L8 TOA or S2 TOC reflectance (rf,: DD 3.4)._

_UCM vector_

</td> </tr>  
<tr>  
<td>

**Input Data Archiving and rolling policies**

</td>  
<td>

_EO data_

_2 GB / quarterly_

</td> </tr>  
<tr>  
<td>

**Frequency of update (refresh rate):**

</td>  
<td>

_Daily_

</td> </tr>  
<tr>  
<td>

**Format:**

</td>  
<td>

_Vector/raster_

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Product ID.**

</th>  
<th>

**NDVI**

</th> </tr>  
<tr>  
<td>

**Product Name**

</td>  
<td>

**Normalized Difference Vegetation Index**

</td> </tr>  
<tr>  
<td>

**Naming convention:**

</td>  
<td>

_Raster_

_MOSES_NDVI_YYYYMMDD_ SS_yyyyDOY.tif where:_

_MOSES_NDVI is the product identifier_

_YYYYMMDD is the generation time of the NDVI_

_SS satellite ID (S2 or L8)_

_yyyyDOY is the sensing day used in input in format year/doy_

</td> </tr>  
<tr>  
<td>

**Archiving and preservation**

</td>  
<td>

_Amount of data generated: 1,5 GB per 15 days_

Raster images and vector data (shapefiles) are archived on a storage server
made available on Esri Italia premises (same solution adopted for storage of
Early Crop Maps described in paragraph 3.1.1).

</td> </tr>  
<tr>  
<td>

**Data sharing:**

</td>  
<td>

Data access is possible through FTP protocol (connection parameters reported
in “data sharing” section of paragraph

3.1.1)

**Raster images** of NDVI parameter are saved in the following folder on the
server:

DA_XX/YYYY/CWD/RASTER/NDVI/

Where XX represents the demonstration area code and YYYY is the year.

Inside the “NDVI” folder user can find the “tiff” files named according to the
above mentioned convention.

NDVI in **vector format** is available as a field of the “Unit Crop Map”
shapefile, that can be found in the directory:

DA_XX/YYYY/CWD/VECTOR/

Inside this directory, files are named according to the following convention:

UCM_DA_YYYY_SEA_DOY

Where DA is identifier of Demo Area, e.g. “SP”; SEA is identifier of
irrigation season (initial of reference month, e.g. “JJA” for June-July-
August); YYYY refers to the current year and DOY is the Day Of Year of the
computation. The same file contains NDVI, LAI, KC, CWD and CWDF data described
in these paragraphs.

</td> </tr>  
<tr>  
<td>

**Standards and metadata:**

</td>  
<td>

</td> </tr> </table>

##  3.5. Short term forecast of crop water demand  
  
<table>  
<tr>  
<th>

**Product ID.**

</th>  
<th>

**CWDF**

</th> </tr>  
<tr>  
<td>

**Product Name**

</td>  
<td>

**Short term forecast of Crop Water Demand**

</td> </tr>  
<tr>  
<td>

**Purpose**

</td>  
<td>

_Seven days forecast of the crop water demand by combining remote sensing
multispectral data and short term forecast meteorological data._

</td> </tr>  
<tr>  
<td>

**Description (Content Specification):**

</td>  
<td>

_The crop water demand forecast is an estimate of the amount of water required
for optimal growth of a plant in the following 7 days. It is the cumulative 7
days values of the forecasted maximum crop evapotranspiration ETmax. CWDF
product includes forecast using two different estimates of forecasted ETmax
(cf. 3.4). The product includes also layers containing zonal statistics (mean
and standard deviation) of 7 days ETmax forecast over segments/fields (=unit
map defined in the “in season crop map module”)._

</td> </tr>  
<tr>  
<td>

**Output Layers:**

</td>  
<td>

_Vector layers:_

  1. _CWDF_an_mean_

  

  2. _CWDF_an_std_

  

  3. _CWDF_emp_mean_

  

  4. _CWDF_emp_std_

  

  

_Raster:_

  1. _CWDF_analytical_DD_MM_AA_

  

  2. _CWDF_empirical_DD_MM_AA_

  

  

</td> </tr>  
<tr>  
<td>

**Measurement Unit:**

</td>  
<td>

_mm/week_

</td> </tr>  
<tr>  
<td>

**Temporal/spatial applicable domains:**

</td>  
<td>

_Weekly /District area_

</td> </tr>  
<tr>  
<td>

**Temporal coverage**

</td>  
<td>

_weekly_

</td> </tr>  
<tr>  
<td>

**Spatial Coverage / Area:**

</td>  
<td>

_Demonstration Area_

</td> </tr>  
<tr>  
<td>

**Spatial Resolution / Scale (Data Grid):**

</td>  
<td>

_Vectorial derived from the EO input data / 1:10000_

_Raster derived from the EO input data / from 10x10m to 30 x 30m_

</td> </tr>  
<tr>  
<td>

**Geographic projection /** **Reference system:**

</td>  
<td>

_UTM WGS84_

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Product ID.**

</th>  
<th>

**CWDF**

</th> </tr>  
<tr>  
<td>

**Product Name**

</td>  
<td>

**Short term forecast of Crop Water Demand**

</td> </tr>  
<tr>  
<td>

**Input Data/Sources:**

</td>  
<td>

_EO data:_

  * _L8 TOA or S2 TOC (rf,: DD 3.4)_

  

_No EO DATA:_

  * _csv file of short term meteorological forecast (rf,:D3.4)_

  

  * _Fruit mask if available_

  

  * _UCM vector_

  

</td> </tr>  
<tr>  
<td>

**Input Data Archiving and rolling policies**

</td>  
<td>

_EO data_

_2 GB / quarterly_ _NO EO data:_

_10 MB / daily_

</td> </tr>  
<tr>  
<td>

**Frequency of update (refresh rate):**

</td>  
<td>

_Daily_

</td> </tr>  
<tr>  
<td>

**Format:**

</td>  
<td>

_Vector/Raster_

</td> </tr>  
<tr>  
<td>

**Naming convention:**

</td>  
<td>

_Raster_

_MOSES_CWDF_ME _YYYYMMDD_ SS_yyyyDOY.tif where:_

  * _MOSES_CWDF is the product identifier_

  

  * _YYYYMMDD is the generation time of the CWD_

  

  * _SS satellite ID (S2 or L8)_

  

  * _yyyyDOY is the sensing day used in input in format year/doy_

  

  * _ME is the method used to estimate CWDF:analytical (an) or empirical (em)_

  

</td> </tr>  
<tr>  
<td>

**Archiving and preservation**

</td>  
<td>

_Amount of data generated: 1,5 GB per 15 days_

Raster images and vector data (shapefiles) are archived on a storage server
made available on Esri Italia premises (same solution adopted for storage of
Early Crop Maps described in paragraph 3.1.1).

</td> </tr>  
<tr>  
<td>

**Product ID.**

</td>  
<td>

**CWDF**

</td> </tr>  
<tr>  
<td>

**Product Name**

</td>  
<td>

**Short term forecast of Crop Water Demand**

</td> </tr>  
<tr>  
<td>

**Data sharing:**

</td>  
<td>

Data access is possible through FTP protocol (connection parameters reported
in “data sharing” section of paragraph

3.1.1)

**Raster images** of CWDF parameter are saved in the following folder on the
server:

DA_XX/YYYY/CWD/RASTER/CWDF/

Where XX represents the demonstration area code and YYYY is the year.

The folder contains the “tiff” files of both “analytical” and

“empirical” CWDF, named according to the above-mentioned convention.

CWDFs in **vector format** are available as fields of the “Unit Crop Map”
shapefile, that can be found in the directory:

DA_XX/YYYY/CWD/VECTOR/

Inside this directory, files are named according to the following convention:

UCM_DA_YYYY_SEA_DOY

Where DA is identifier of Demo Area, e.g. “SP”; SEA is identifier of
irrigation season (initial of reference month, e.g. “JJA” for June-July-
August); YYYY refers to the current year and DOY is the Day Of Year of the
computation. The same file contains CWDF, NDVI, LAI, KC and CWD data described
in these paragraphs.

</td> </tr>  
<tr>  
<td>

**Standards and metadata:**

</td>  
<td>

</td> </tr> </table>

##  3.6. Short term forecast of Gross irrigation water requirements  
  
<table>  
<tr>  
<th>

**Product ID.**

</th>  
<th>

**GIWRF**

</th> </tr>  
<tr>  
<td>

**Product Name**

</td>  
<td>

**Short term forecast of Gross Irrigation Water Requirements**

</td> </tr>  
<tr>  
<td>

**Purpose**

</td>  
<td>

_Seven days forecast of the gross irrigation water requirements (GIWR) by
combining remote sensing multispectral data and short term forecast
meteorological data._

</td> </tr>  
<tr>  
<td>

**Description (Content Specification):**

</td>  
<td>

_The gross irrigation water requirements forecast is an estimate of the amount
of irrigation water required for optimal growth of a plant in the following 7
days. It is defined as the crop water demand minus precipitation. GIWRF
product includes forecast using two different estimates of forecasted ETmax
(cf. 3.4). The product includes also layers containing zonal statistics (mean
and standard deviation) of 7 days GIWR forecast over segments/fields (=unit
map defined in the “in season crop map module”)._

</td> </tr>  
<tr>  
<td>

**Output Layers:**

</td>  
<td>

_Vector layers:_

  1. _GIWRF_an_mean_

  

  2. _GIWRF_an_std_

  

  3. _GIWRF_emp_mean_

  

  4. _GIWRF_emp_std_

  

  

_Raster:_

  1. _GIWRF_analytical_DD_MM_AA_

  

  2. _GIWRF_empirical_DD_MM_AA_

  

  

</td> </tr>  
<tr>  
<td>

**Measurement Unit:**

</td>  
<td>

_mm/week_

</td> </tr>  
<tr>  
<td>

**Temporal/spatial applicable domains:**

</td>  
<td>

_Weekly /District area_

</td> </tr>  
<tr>  
<td>

**Temporal coverage**

</td>  
<td>

_weekly_

</td> </tr>  
<tr>  
<td>

**Spatial Coverage / Area:**

</td>  
<td>

_Demonstration Area_

</td> </tr>  
<tr>  
<td>

**Spatial Resolution / Scale (Data Grid):**

</td>  
<td>

_Vectorial derived from the EO input data / 1:10000_

_Raster derived from the EO input data / from 10x10m to 30 x 30m_

</td> </tr>  
<tr>  
<td>

**Geographic projection /** **Reference system:**

</td>  
<td>

_UTM WGS84_

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Product ID.**

</th>  
<th>

**GIWRF**

</th> </tr>  
<tr>  
<td>

**Product Name**

</td>  
<td>

**Short term forecast of Gross Irrigation Water Requirements**

</td> </tr>  
<tr>  
<td>

**Input Data/Sources:**

</td>  
<td>

_EO data:_

  * _L8 TOA or S2 TOC reflectance from Pre-processing module (rf,: DD 3.4)_

  

_No EO DATA:_

  * _csv file of short term meteorological forecast (rf,:D3.4)_

  

  * _Fruit mask if present_

  

  * _UCM vector_

  

</td> </tr>  
<tr>  
<td>

**Input Data Archiving and rolling policies**

</td>  
<td>

_EO data_

_2 GB / quarterly NO EO data:_

_10 MB / daily_

</td> </tr>  
<tr>  
<td>

**Frequency of update (refresh rate):**

</td>  
<td>

_Daily_

</td> </tr>  
<tr>  
<td>

**Format:**

</td>  
<td>

_Vector/Raster_

</td> </tr>  
<tr>  
<td>

**Naming convention:**

</td>  
<td>

_Raster_

_MOSES_GIWRF_ME _YYYYMMDD_ SS_yyyyDOY.tif where:_

  * _MOSES_GIWR is the product identifier_

  

  * _YYYYMMDD is the generation time of the CWD_

  

  * _SS satellite ID (S2 or L8)_

  

  * _yyyyDOY is the sensing day used in input in format year/doy_

  

  * _ME is the method used to estimate GIWR:analytical (an) or empirical (em)_

  

</td> </tr>  
<tr>  
<td>

**Archiving and preservation**

</td>  
<td>

_Amount of data generated: 1,5 GB per 15 days_

Raster images and vector data (shapefiles) are archived on a storage server
made available on Esri Italia premises (same solution adopted for storage of
Early Crop Maps described in paragraph 3.1.1).

</td> </tr>  
<tr>  
<td>

**Product ID.**

</td>  
<td>

**GIWRF**

</td> </tr>  
<tr>  
<td>

**Product Name**

</td>  
<td>

**Short term forecast of Gross Irrigation Water Requirements**

</td> </tr>  
<tr>  
<td>

**Data sharing:**

</td>  
<td>

Data access is possible through FTP protocol (connection parameters reported
in “data sharing” section of paragraph

3.1.1)

**Raster images** of GIWRF parameter are saved in the following folder on the
server:

DA_XX/YYYY/CWD/RASTER/GIWRF/

Where XX represents the demonstration area code and YYYY is the year.

The folder contains the “tiff” files of both “analytical” and

“empirical” GIWRF, named according to the above-mentioned convention.

GIWRFs in **vector format** are available as fields of the “Unit Crop Map”
shapefile, that can be found in the directory:

DA_XX/YYYY/CWD/VECTOR/

Inside this directory, files are named according to the following convention:

UCM_DA_YYYY_SEA_DOY

Where DA is identifier of Demo Area, e.g. “SP”; SEA is identifier of
irrigation season (initial of reference month, e.g. “JJA” for June-July-
August); YYYY refers to the current year and DOY is the Day Of Year of the
computation. The same file contains CWDF, NDVI, LAI, KC and CWD data described
in these paragraphs.

</td> </tr>  
<tr>  
<td>

**Standards and metadata:**

</td>  
<td>

</td> </tr> </table>

##  3.7. Crop water demand monitoring data

This MOSES product consists in the two following datasets, which are described
in details in subsequent tables:

  * Crop Coefficient(Kc) 

  

  * Crop Water Demand (CWD) 

  

  * Gross Irrigation Water Requirement (GIWR) 

  

###  3.7.1 Crop Coefficient (Kc)  
  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

Kc

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Crop Coefficient

</td> </tr>  
<tr>  
<td>

Purpose

</td>  
<td>

_Mapping and monitoring of the crop coefficient by means of remote sensing
multispectral data. The monitoring is performed at 5 days temporal resolution
or more depending on the availability of remote sensing multispectral
observations._

</td> </tr>  
<tr>  
<td>

Description (Content Specification):

</td>  
<td>

_Crop coefficient is a crop property used to predict evapotranspiration and
corresponds to the ratio between crop evapotranspiration (ET c  ) _ 3  _and
reference evapotranspiration (ET 0  ) _ 4

_Product includes crop coefficients estimated by two different methods
(empirical and analytical). The product includes also layers containing zonal
statistics (mean and standard deviation) over segments/fields (=unit map
defined in the “in season crop map module”)._

</td> </tr> </table>  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

Kc

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Crop Coefficient

</td> </tr>  
<tr>  
<td>

Output Layers:

</td>  
<td>

_Vector layers:_

  1. _Kc_an_mean_

  

  2. _Kc_an_std_

  

  3. _Kc_emp_mean_

  

  4. _Kc_emp_std_

  

  

_Raster:_

  1. _Kc_analytical_DD_MM_AA_

  

  2. _Kc_empirical_DD_MM_AA_

  

  

</td> </tr>  
<tr>  
<td>

Measurement Unit:

</td>  
<td>

_mm/mm_

</td> </tr>  
<tr>  
<td>

Temporal/spatial applicable domains:

</td>  
<td>

_Daily/District Area_

</td> </tr>  
<tr>  
<td>

Temporal coverage

</td>  
<td>

_Daily_

</td> </tr>  
<tr>  
<td>

Spatial Coverage / Area:

</td>  
<td>

_Demonstration Area_

</td> </tr>  
<tr>  
<td>

Spatial Resolution / Scale (Data Grid):

</td>  
<td>

_Vectorial derived from the EO input data / 1:10000_

_Raster derived from the EO input data / from 10x10m to 30 x 30m_

</td> </tr>  
<tr>  
<td>

Geographic projection / Reference system:

</td>  
<td>

_UTM WGS84_

</td> </tr>  
<tr>  
<td>

Input Data/Sources:

</td>  
<td>

_EO data:_

_1) L8 TOA or S2 TOC reflectance data (rf,: DD 3.4)._

_No EO DATA:_

  1. _csv file of input crop parameters and miscellaneous (rf,:D3.4)_

  

  2. _csv file of observed meteorological data_

  

  

_3)Fruit mask if present_

_4) UCM vector_

</td> </tr> </table>  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

Kc

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Crop Coefficient

</td> </tr>  
<tr>  
<td>

Input Data Archiving and rolling policies

</td>  
<td>

_EO data_

_1) 4 GB / quarterly_

_NO EO data:_

  1. _10 MB / rolling policy 1 time_

  

  2. _10 MB/Daily_

  

  

</td> </tr>  
<tr>  
<td>

Frequency of update (refresh rate):

</td>  
<td>

_Daily_

</td> </tr>  
<tr>  
<td>

Format:

</td>  
<td>

_Vector/Raster_

</td> </tr>  
<tr>  
<td>

Naming convention:

</td>  
<td>

_Raster_

_MOSES_KC_ME _YYYYMMDD_ SS_yyyyDOY.tif where:_

  * _MOSES_KC is the product identifier_

  

  * _YYYYMMDD is the generation time of the Kc_

  

  * _SS satellite ID (S2 or L8)_

  

  * _yyyyDOY is the sensing day used in input in format year/doy_

  

  * _ME is the method used to estimate Kc:analytical (an) or empirical (em)_

  

</td> </tr>  
<tr>  
<td>

Archiving and preservation

</td>  
<td>

_Amount of data generated: 3GB per 15 days_

Raster images and vector data (shapefiles) are archived on a storage server
made available on Esri Italia premises (same solution adopted for storage of
Early Crop Maps described in paragraph 3.1.1).

</td> </tr>  
<tr>  
<td>

Product ID.

</td>  
<td>

Kc

</td> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Crop Coefficient

</td> </tr>  
<tr>  
<td>

Data sharing:

</td>  
<td>

Data access is possible through FTP protocol (connection

parameters reported in “data sharing” section of paragraph 3.1.1)

Raster images of KC parameter are saved in the following folder on the server:

DA_XX/YYYY/CWD/RASTER/KC/

Where XX represents the demonstration area code and YYYY is the year.

The folder contains the “tiff” files of both “analytical” and “empirical” KCs,
named according to the above-mentioned convention.

KCs in vector format are available as fields of the “Unit Crop Map” shapefile,
that can be found in the directory:

DA_XX/YYYY/CWD/VECTOR/

Inside this directory, files are named according to the following convention:

UCM_DA_YYYY_SEA_DOY

Where DA is identifier of Demo Area, e.g. “SP”; SEA is identifier of
irrigation season (initial of reference month, e.g. “JJA” for JuneJuly-
August); YYYY refers to the current year and DOY is the Day Of Year of the
computation. The same file contains KC, NDVI, LAI, KC and CWDF data described
in these paragraphs.

</td> </tr>  
<tr>  
<td>

Standards and metadata:

</td>  
<td>

</td> </tr> </table>

###  3.7.2 Crop Water Demand (CWD)  
  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

CWD

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Crop water demand

</td> </tr>  
<tr>  
<td>

Purpose

</td>  
<td>

_Mapping and monitoring of the crop water demand and irrigation water
requirements by means of remote sensing multispectral data. The monitoring is
performed at 7 days temporal resolution or more depending on the availability
of remote sensing multispectral observations._

</td> </tr>  
<tr>  
<td>

Description (Content Specification):

</td>  
<td>

_The crop water demand is an estimate of the amount of water required for
optimal growth of a plant and it is equal to the maximum crop
evapotraspiration ETmax. CWD product includes two different estimates of ETmax
, both employing FAO56 method but using 2 crop coefficients estimated by two
different methods (empirical and analytical). The product includes also layers
containing zonal statistics (mean and standard deviation) over segments/fields
(=unit map defined in the “in season crop map module”)._

</td> </tr>  
<tr>  
<td>

Output Layers:

</td>  
<td>

_Vector layers:_

  1. _CWD_an_mean_

  

  2. _CWD_an_std_

  

  3. _CWD_emp_mean_

  

  4. _CWD_emp_std_

  

  

_Raster:_

  1. _CWD_analytical_DD_MM_AA_

  

  2. _CWD_empirical_DD_MM_AA_

  

  

</td> </tr>  
<tr>  
<td>

Measurement Unit:

</td>  
<td>

_mm/day_

</td> </tr>  
<tr>  
<td>

Temporal/spatial applicable domains:

</td>  
<td>

_Daily/District area_

</td> </tr>  
<tr>  
<td>

Temporal coverage

</td>  
<td>

_Daily_

</td> </tr>  
<tr>  
<td>

Spatial Coverage / Area:

</td>  
<td>

_Demonstration area_

</td> </tr>  
<tr>  
<td>

Spatial Resolution / Scale (Data Grid):

</td>  
<td>

_Vectorial derived from the EO input data / 1:10000_

_Raster derived from the EO input data / from 10x10m to 30 x 30m_

</td> </tr>  
<tr>  
<td>

Geographic projection / Reference system:

</td>  
<td>

_UTM WGS84_

</td> </tr> </table>  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

CWD

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Crop water demand

</td> </tr>  
<tr>  
<td>

Input Data/Sources:

</td>  
<td>

_EO data:_

  1. _L8 TOA or S2 TOC reflectance data (rf,: DD 3.4)._

  

  

_No EO DATA:_

  2. _csv file of input crop parameters and miscellaneous (rf,:D3.4)_

  

  3. _csv file of observed meteorological data_

  

  4. _Fruit mask if present_

  

  5. _UCM vector_

  

  

</td> </tr>  
<tr>  
<td>

Input Data Archiving and rolling policies

</td>  
<td>

_EO data_

_1) 4 GB / quarterly_

_NO EO data:_

  1. _10 MB / 1 time per year_

  

  2. _10 MB/daily_

  

  3. _less than 50 MB/ quarterly_

  

  

</td> </tr>  
<tr>  
<td>

Frequency of update (refresh rate):

</td>  
<td>

_Daily_

</td> </tr>  
<tr>  
<td>

Format:

</td>  
<td>

_Vector/Raster_

</td> </tr>  
<tr>  
<td>

Naming convention:

</td>  
<td>

_Raster_

_MOSES_CWD_ME _YYYYMMDD_ SS_yyyyDOY.tif where:_

  * _MOSES_CWD is the product identifier_

  

  * _YYYYMMDD is the generation time of the CWD_

  

  * _SS satellite ID (S2 or L8)_

  

  * _yyyyDOY is the sensing day used in input in format year/doy_

  

  * _ME is the method used to estimate CWD:analytical (an) or empirical (em)_

  

</td> </tr>  
<tr>  
<td>

Product ID.

</td>  
<td>

CWD

</td> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Crop water demand

</td> </tr>  
<tr>  
<td>

Archiving and preservation

</td>  
<td>

_Amount of data generated: 3GB per 15 days_

Raster images and vector data (shapefiles) are archived on a storage server
made available on Esri Italia premises (same solution adopted for storage of
Early Crop Maps described in paragraph 3.1.1).

</td> </tr>  
<tr>  
<td>

Data sharing:

</td>  
<td>

Data access is possible through FTP protocol (connection

parameters reported in “data sharing” section of paragraph 3.1.1)

Raster images of CWD parameter are saved in the following folder on the
server:

DA_XX/YYYY/CWD/RASTER/CWD/

Where XX represents the demonstration area code and YYYY is the year.

The folder contains the “tiff” files of both “analytical” and

“empirical” CWDs, named according to the above-mentioned convention.

CWDs in vector format are available as fields of the “Unit Crop Map”
shapefile, that can be found in the directory:

DA_XX/YYYY/CWD/VECTOR/

Inside this directory, files are named according to the following convention:

UCM_DA_YYYY_SEA_DOY

Where DA is identifier of Demo Area, e.g. “SP”; SEA is identifier of
irrigation season (initial of reference month, e.g. “JJA” for JuneJuly-
August); YYYY refers to the current year and DOY is the Day Of Year of the
computation. The same file contains CWD, NDVI, LAI, KC and CWDF data described
in these paragraphs.

</td> </tr>  
<tr>  
<td>

Standards and metadata:

</td>  
<td>

</td> </tr> </table>

###  3.7.3 Gross Irrigation Water Requirement (GIWR)  
  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

GIWR

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Gross Irrigation Water Requirement

</td> </tr>  
<tr>  
<td>

Purpose

</td>  
<td>

_Mapping and monitoring of the irrigation water requirements by means of
remote sensing multispectral data. The monitoring is performed at 7 days
temporal resolution or more depending on the availability of remote sensing
multispectral observations._

</td> </tr>  
<tr>  
<td>

Description (Content Specification):

</td>  
<td>

_The Gross water requirements is an estimate of the amount of irrigation water
required for optimal growth of a plant. It is defined as the crop water demand
minus precipitation. GIWR product includes estimates using two different
estimates of ETmax (cf. 3.4). The product includes also layers containing
zonal statistics (mean and standard deviation) over segments/fields (=unit map
defined in the “in season crop map module”)._

</td> </tr>  
<tr>  
<td>

Output Layers:

</td>  
<td>

_Vector layers:_

  1. _GIWR_an_mean_

  

  2. _GIWR_an_std_

  

  3. _GIWR_emp_mean_

  

  4. _GIWR_emp_std_

  

  

_Raster:_

  1. _GIWR_analytical_DD_MM_AA_

  

  2. _GIWR_empirical_DD_MM_AA_

  

  

</td> </tr>  
<tr>  
<td>

Measurement Unit:

</td>  
<td>

_mm/day_

</td> </tr>  
<tr>  
<td>

Temporal/spatial applicable domains:

</td>  
<td>

_Daily/District area_

</td> </tr>  
<tr>  
<td>

Temporal coverage

</td>  
<td>

_Daily_

</td> </tr>  
<tr>  
<td>

Spatial Coverage / Area:

</td>  
<td>

_Demonstration area_

</td> </tr>  
<tr>  
<td>

Spatial Resolution / Scale (Data Grid):

</td>  
<td>

_Vectorial derived from the EO input data / 1:10000_

_Raster derived from the EO input data / from 10x10m to 30 x 30m_

</td> </tr>  
<tr>  
<td>

Geographic projection / Reference system:

</td>  
<td>

_UTM WGS84_

</td> </tr> </table>  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

GIWR

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Gross Irrigation Water Requirement

</td> </tr>  
<tr>  
<td>

Input Data/Sources:

</td>  
<td>

_EO data:_

  1. _L8 TOA or S2 TOC reflectance data (rf,: DD 3.4)._

  

  

_No EO DATA:_

  2. _csv file of input crop parameters and miscellaneous (rf,:D3.4)_

  

  3. _csv file of observed meteorological data_

  

  4. _Fruit mask if present_

  

  5. _UCM vector_

  

  

</td> </tr>  
<tr>  
<td>

Input Data Archiving and rolling policies

</td>  
<td>

_EO data_

_1) 4 GB / quarterly_

_NO EO data:_

  1. _10 MB / 1 time per year_

  

  2. _10 MB/daily_

  

  3. _less than 50 MB/ quarterly_

  

  

</td> </tr>  
<tr>  
<td>

Frequency of update (refresh rate):

</td>  
<td>

_Daily_

</td> </tr>  
<tr>  
<td>

Format:

</td>  
<td>

_Vector/Raster_

</td> </tr>  
<tr>  
<td>

Naming convention:

</td>  
<td>

_Raster_

_MOSES_GIWR_ME _YYYYMMDD_ SS_yyyyDOY.tif where:_

  * _MOSES_GIWR is the product identifier_

  

  * _YYYYMMDD is the generation time of the CWD_

  

  * _SS satellite ID (S2 or L8)_

  

  * _yyyyDOY is the sensing day used in input in format year/doy_

  

  * _ME is the method used to estimate CWD:analytical (an) or empirical (em)_

  

</td> </tr>  
<tr>  
<td>

Product ID.

</td>  
<td>

GIWR

</td> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Gross Irrigation Water Requirement

</td> </tr>  
<tr>  
<td>

Archiving and preservation

</td>  
<td>

_Amount of data generated: 3GB per 15 days_

Raster images and vector data (shapefiles) are archived on a storage server
made available on Esri Italia premises (same solution adopted for storage of
Early Crop Maps described in paragraph 3.1.1).

</td> </tr>  
<tr>  
<td>

Data sharing:

</td>  
<td>

Data access is possible through FTP protocol (connection

parameters reported in “data sharing” section of paragraph 3.1.1)

Raster images of CWD parameter are saved in the following folder on the
server:

DA_XX/YYYY/CWD/RASTER/GIWR/

Where XX represents the demonstration area code and YYYY is the year.

The folder contains the “tiff” files of both “analytical” and

“empirical” CWDs, named according to the above-mentioned convention.

CWDs in vector format are available as fields of the “Unit Crop Map”
shapefile, that can be found in the directory:

DA_XX/YYYY/CWD/VECTOR/

Inside this directory, files are named according to the following convention:

UCM_DA_YYYY_SEA_DOY

Where DA is identifier of Demo Area, e.g. “SP”; SEA is identifier of
irrigation season (initial of reference month, e.g. “JJA” for JuneJuly-
August); YYYY refers to the current year and DOY is the Day

Of Year of the computation. The same file contains CWD, GIWR, NDVI, LAI, KC,
GIWRF and CWDF data described in these paragraphs.

</td> </tr>  
<tr>  
<td>

Standards and metadata:

</td>  
<td>

</td> </tr> </table>

##  3.8. Seasonal irrigation forecast

This MOSES product consists in the two following datasets, which are described
in details in following tables:

  * Seasonal irrigation climate 

  

  * Seasonal irrigation forecast 

  

###  3.8.1. Seasonal irrigation climate  
  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

SeasonalIrriClimate

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Seasonal irrigation climate

</td> </tr>  
<tr>  
<td>

Purpose

</td>  
<td>

Seasonal irrigation climate is the 3-months crop irrigation assessment
computed by the MOSES soil water balance processor for the climatic period,
e.g. for the Italy Demonstration area, from 1991 until the year of seasonal
forecast.

</td> </tr>  
<tr>  
<td>

Description (Content Specification):

</td>  
<td>

This product provides, for each distinct combination of the unit map,
information about the total crop water needs for the analyzed season of the
climate series. In more details, the data provided are the irrigation
statistical distribution in millimeters expressed as percentiles for each unit
map. This information has to be integrated with the seasonal irrigation
forecast output (see the specific table of the product SeasonalIrriForecasts)
in order to compare the seasonal irrigation forecast and the irrigation
climate and to evaluate the signal of the forecast with respect to the
climate.

</td> </tr>  
<tr>  
<td>

Layers(*):

</td>  
<td>

  1. ID_CASE: identifier of the distinct combination of crop map, soil map and meteo grid. 

  

  2. CROP: identifier of the crop for the water balance processor 

  

  3. SOIL: identifier of the soil type for the water balance processor 

  

  4. METEO: identifier of the meteo cell that refers to the meteo grid of the demonstration area 

  

  5. p5: the 5  th  percentile of total seasonal irrigation quantity for the crop computed from climate data 

  

  6. p25: the 25  th  percentile of total seasonal irrigation quantity for the crop computed from climate data 

  

  7. p50: the 50  th  percentile of total seasonal irrigation quantity for the crop computed from climate data 

  

  8. p75: the 75  th  percentile of total seasonal irrigation quantity for the crop computed from climate data 

  

  9. p95: the 95  th  percentile of total seasonal irrigation quantity for the crop computed from climate data 

  

  

</td> </tr> </table>  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

SeasonalIrriClimate

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Seasonal irrigation climate

</td> </tr>  
<tr>  
<td>

Measurement Unit:

</td>  
<td>

Millimeters

</td> </tr>  
<tr>  
<td>

Field of Applicability (Temporal/Spatial):

</td>  
<td>

Monthly / District area

</td> </tr>  
<tr>  
<td>

Temporal coverage

</td>  
<td>

3-months

</td> </tr>  
<tr>  
<td>

Spatial Coverage / Area:

</td>  
<td>

Computation area

</td> </tr>  
<tr>  
<td>

Spatial Resolution / Scale (Data Grid):

</td>  
<td>

Vectorial, the same resolution of the unit map

</td> </tr>  
<tr>  
<td>

Geographic projection / Reference system:

</td>  
<td>

UTM WGS84

</td> </tr>  
<tr>  
<td>

Input Data/Sources:

</td>  
<td>

This product is the results of the integration between the following input
data: - early crop map

  * soil information 

  

  * climate series of observed weather data (e.g. 20 years of daily temperature and precipitation data) 

  

</td> </tr>  
<tr>  
<td>

Input Data Archiving and rolling policies

</td>  
<td>

  * Climate data archiving: about 300 kb for each weather grid cell 

  

  * Rolling policies: annual update if possible 

  

</td> </tr>  
<tr>  
<td>

Frequency of update (refresh rate):

</td>  
<td>

monthly (when requested)

</td> </tr>  
<tr>  
<td>

Format:

</td>  
<td>

Comma separated value file (.csv) with the following fields:

  * ID_CASE, integer with 5 digits 

  

  * CROP, alphanumeric string 

  

  * SOIL, alphanumeric string 

  

  * METEO, integer of 5 digits 

  

  * p5 (mm), float, precision: 2 digits 

  

  * p25 (mm), float, precision: 2 digits 

  

  * p50 (mm), float, precision: 2 digits 

  

  * p75 (mm), float, precision: 2 digits 

  

  * p95 (mm), float, precision: 2 digits 

  

</td> </tr>  
<tr>  
<td>

Product ID.

</td>  
<td>

SeasonalIrriClimate

</td> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

Seasonal irrigation climate

</td> </tr>  
<tr>  
<td>

Naming convention:

</td>  
<td>

MOSES_SeasonalIrriClimate_AAAAA _MMM.csv where:

  * MOSES_ SeasonalIrriClimate is the product identifier 

  

  * AAAAA is the computation area name, composed by 5 characters in capital letters (e.g. ITALY, SPAIN, MAROC, ROMAN) 

  

  * MMM is the 3-month period of the seasonal forecasts, composed by the initial letters of the forecast month 

  

</td> </tr>  
<tr>  
<td>

Archiving and preservation

</td>  
<td>

Values for the DA Italy:

About 100 kb for each .csv monthly emission.

About 8 Mb for the corresponding shapefile (see data sharing).

The files are archived on a storage server made available on Esri Italia
premises (same solution adopted for storage of Early Crop Maps described in
paragraph 3.1.1).

</td> </tr>  
<tr>  
<td>

Data sharing:

</td>  
<td>

Data access is possible through FTP protocol (connection parameters reported
in “data sharing” section of paragraph 3.1.1)

Seasonal irrigation climate data are saved in folders that can be found in the
server folder:

DA_XX/YYYY/SWB/SEASONAL/MMM

Where XX represents the demonstration area code YYYY is the year and MMM the
acronym of the 3-months forecast period.

This dataset, together with the corresponding SeasonalIrriForecast, is
automatically processed on the MOSES geoDataBase, using the Unit Crop Map of
the corresponding DA.

A copy of the resulting maps is saved as shapefile (zipped) in the same
directory, with this naming convention:

swbSeasonal_YYY_MMM.zip

Where YYYY is the year and MMM the 3-months forecast period.

</td> </tr>  
<tr>  
<td>

Standards and metadata:

</td>  
<td>

</td> </tr> </table>

###  3.8.2. Seasonal irrigation forecast  
  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

**SeasonalIrriForecast**

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

**Seasonal irrigation forecast**

</td> </tr>  
<tr>  
<td>

**Purpose**

</td>  
<td>

Seasonal irrigation forecast are the 3-months probabilistic forecasts of crop
water needs computed by the MOSES soil water balance processor.

</td> </tr>  
<tr>  
<td>

**Description (Content Specification):**

</td>  
<td>

This product provides, for each distinct combination of the unit map,
information about the total crop water needs for the forecast season. In more
details, the data provided are the irrigation statistical distribution in
millimeters expressed as percentiles for each unit map.

This information has to be integrated with the seasonal irrigation climate
output (see the specific table of the product SeasonalIrriClimate) in order to
compare the seasonal irrigation forecast and the irrigation climate and to
evaluate the signal of the forecast with respect to the climate.

</td> </tr>  
<tr>  
<td>

**Layers(*):**

</td>  
<td>

  1. **ID_CASE** : identifier of the distinct combination of crop map, soil map and meteo grid. 

  

  2. **CROP:** identifier of the crop for the water balance processor 

  

  3. **SOIL:** identifier of the soil type for the water balance processor 

  

  4. **METEO:** identifier of the meteo cell that refers to the meteo grid of the computation area 

  

  5. **p5** : the 5  th  percentile of total seasonal irrigation quantity for the crop 

  

  6. **p25** : the 25  th  percentile of total seasonal irrigation quantity for the crop 

  

  7. **p50** : the 50  th  percentile of total seasonal irrigation quantity for the crop 

  

  8. **p75** : the 75  th  percentile of total seasonal irrigation quantity for the crop 

  

  9. **p95** : the 95  th  percentile of total seasonal irrigation quantity for the crop 

  

  

</td> </tr>  
<tr>  
<td>

**Measurement Unit:**

</td>  
<td>

Millimeters

</td> </tr>  
<tr>  
<td>

**Field of Applicability (Temporal/Spatial):**

</td>  
<td>

Monthly / District area

</td> </tr>  
<tr>  
<td>

**Temporal coverage**

</td>  
<td>

3-months

</td> </tr>  
<tr>  
<td>

**Spatial Coverage / Area:**

</td>  
<td>

Computation area

</td> </tr> </table>  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

**SeasonalIrriForecast**

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

**Seasonal irrigation forecast**

</td> </tr>  
<tr>  
<td>

**Spatial Resolution / Scale (Data Grid):**

</td>  
<td>

Vectorial, the same resolution of the unit map

</td> </tr>  
<tr>  
<td>

**Geographic projection /** **Reference system:**

</td>  
<td>

UTM WGS84

</td> </tr>  
<tr>  
<td>

**Input Data/Sources:**

</td>  
<td>

This product is the results of the integration between the following input
data:

  * early crop map 

  

  * soil information 

  

  * synthetic series of daily temperature and precipitation generated by seasonal probabilistic forecast 

  

(for more details see SyntheticSeries description and the D3.2 - Seasonal
probabilistic forecasting)

</td> </tr>  
<tr>  
<td>

**Input Data Archiving and rolling policies**

</td>  
<td>

Archiving: each synthetic series requires about 1 Mb of storage (to be

multiplied for the number of cells of the meteo grid) Rolling policy: year

</td> </tr>  
<tr>  
<td>

**Frequency of update (refresh rate):**

</td>  
<td>

monthly (when requested).

</td> </tr>  
<tr>  
<td>

**Format:**

</td>  
<td>

Comma separated value file (.csv) with the following fields:

  * ID_CASE, integer with 5 digits 

  

  * CROP, alphanumeric string 

  

  * SOIL, alphanumeric string 

  

  * METEO, integer of 5 digits 

  

  * p5 (mm), float, precision: 2 digits 

  

  * p25 (mm), float, precision: 2 digits 

  

  * p50 (mm), float, precision: 2 digits 

  

  * p75 (mm), float, precision: 2 digits 

  

  * p95 (mm), float, precision: 2 digits 

  

</td> </tr>  
<tr>  
<td>

Product ID.

</td>  
<td>

**SeasonalIrriForecast**

</td> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

**Seasonal irrigation forecast**

</td> </tr>  
<tr>  
<td>

**Naming convention:**

</td>  
<td>

**MOSES_SeasonalIrriForecast_AAAAA_YYYY_MMM.csv** where:

  * **MOSES_ SeasonalIrriForecast** is the product identifier 

  

  * **AAAAA** is the computation area name, composed by 5 characters in capital letters (e.g. ITALY, SPAIN, MAROC, ROMAN) 

  

  * **YYYY** is the year of emission of the seasonal forecast 

  

  * **MMM** is the 3-month period of the seasonal forecast, composed by the initial letters of the forecast months 

  

</td> </tr>  
<tr>  
<td>

**Archiving and preservation**

</td>  
<td>

Values for the DA Italy:

About 100 kb for each .csv monthly emission.

About 8 Mb for the corresponding shapefile (see data sharing).

The files are archived on a storage server made available on Esri Italia
premises (same solution adopted for storage of Early Crop Maps described in
paragraph 3.1.1).

</td> </tr>  
<tr>  
<td>

**Data sharing:**

</td>  
<td>

Data access is possible through FTP protocol (connection parameters reported
in “data sharing” section of paragraph 3.1.1)

Seasonal irrigation climate data are saved in folders that can be found in the
server folder:

DA_XX/YYYY/SWB/SEASONAL/MMM

Where XX represents the demonstration area code YYYY is the year and MMM the
acronym of the 3-months forecast period.

This dataset, together with the corresponding SeasonalIrriClimate, is
automatically processed on the MOSES geoDataBase, using the Unit Crop Map of
the corresponding DA.

A copy of the resulting maps is saved as zipped shapefile, in the same
directory, with this naming convention:

**swbSeasonal_YYY_MMM.zip**

Where YYYY is the year and MMM the 3-months forecast period.

</td> </tr>  
<tr>  
<td>

**Standards and metadata:**

</td>  
<td>

</td> </tr> </table>

##  3.8. Short term irrigation forecast  
  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

**ShortTermIrriForecast**

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

**Short-term irrigation forecast**

</td> </tr>  
<tr>  
<td>

**Purpose**

</td>  
<td>

Short-term irrigation forecasts are the 7-days forecasts of crop water needs
computed by the MOSES soil water balance module.

</td> </tr>  
<tr>  
<td>

**Description (Content Specification):**

</td>  
<td>

This product provides, for each distinct combination of the unit map
(intersection of the crop, soil and meteo map), information about the status
of crop water availability, forecasts of rainfall and crop water needs for the
next 7 days and model assessment of irrigation for the previous 14 days.

This set of information provides a framework about the irrigation needed by
crops for the next week, taking into account the actual irrigation carried out
in the previous 14 days (e.g. if the model computes 40 mm in the previous 14
days, whereas the farmer has irrigated 60 mm, it is possible to decrease the
short term irrigation forecast of 20 mm).

</td> </tr>  
<tr>  
<td>

**Layers(*):**

</td>  
<td>

  1. **dateForecast** : date of the last observed weather data; 

  

  2. **ID_CASE** : identifier of the distinct combination of crop map, soil map and meteo grid; 

  

  3. **CROP:** identifier of the crop for the water balance module; 

  

  4. **SOIL:** identifier of the soil type for the water balance; 

  

  5. **METEO:** identifier of the meteo cell that refers to the meteo grid of the demonstration area; 

  

  6. **readilyAvailableWater** : current readily available water for the crop [mm]. 

  

  7. **soilWaterDefici** t: difference between field capacity and the actual quantity of water, summed on all the layers of the rooting depth [mm]. 

  

  8. **forecast7daysPrec** : 7-days forecast of precipitation (sum) [mm]. 

  

  9. **forecast7daysMaxTransp** : 7-days forecast of maximum crop transpiration (sum) [mm]. 

  

  10. **forecast7daysIRR** : 7-days forecast of irrigation needs (sum). 

  

  11. **previousAllSeasonIRR** : Summed irrigation simulated by means of observed weather data during the all irrigation season, until the date of forecast [mm]. 

  

  

</td> </tr>  
<tr>  
<td>

**Measurement Unit:**

</td>  
<td>

Millimeters

</td> </tr> </table>  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

**ShortTermIrriForecast**

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

**Short-term irrigation forecast**

</td> </tr>  
<tr>  
<td>

**Field of Applicability (Temporal/Spatial):**

</td>  
<td>

Daily / District area

</td> </tr>  
<tr>  
<td>

**Temporal coverage**

</td>  
<td>

7-days

</td> </tr>  
<tr>  
<td>

**Spatial Coverage / Area:**

</td>  
<td>

Demonstration area

</td> </tr>  
<tr>  
<td>

**Spatial Resolution / Scale (Data Grid):**

</td>  
<td>

Vectorial, same resolution of the unit map

</td> </tr>  
<tr>  
<td>

**Geographic projection /** **Reference system:**

</td>  
<td>

UTM WGS84

</td> </tr>  
<tr>  
<td>

**Input Data/Sources:**

</td>  
<td>

This product is the results of the integration between several data sources:

  * early crop map and in-season crop map 

  

  * soil information 

  

  * observed weather data (daily temperature and precipitation) 

  

  * 7-days weather forecast data (daily temperature and precipitation) 

  

(for more details see D3.3 - Irrigation forecasting package)

</td> </tr>  
<tr>  
<td>

**Input Data Archiving and rolling policies**

</td>  
<td>

(Values for the DA Italy)

Weather input: about 20 Mb / rolling policy: everyday

Soil and parameters input: about 1 Mb / rolling policy: stable

Crop map: see crop map product (paragraph 3.1)

</td> </tr>  
<tr>  
<td>

**Frequency of update (refresh rate):**

</td>  
<td>

Daily

</td> </tr> </table>  
<table>  
<tr>  
<th>

Product ID.

</th>  
<th>

**ShortTermIrriForecast**

</th> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

**Short-term irrigation forecast**

</td> </tr>  
<tr>  
<td>

**Format:**

</td>  
<td>

Comma separated value file (.csv) with the following fields:

  * dateForecast, ISO8601 (YYYY-MM-DD) 

  

  * ID_CASE, integer with 5 digits 

  

  * CROP, alphanumeric string 

  

  * SOIL, alphanumeric string 

  

  * METEO, integer of 5 digits 

  

  * readilyAvailableWater (mm), float, precision: 1 digit 

  

  * soilWaterDeficit (mm), float, precision: 1 digit 

  

  * forecast7daysPrec (mm), float, precision: 1 digit 

  

  * forecast7daysMaxTransp (mm), float, precision: 1 digit 

  

  * forecast7daysIRR (mm), integer 

  

  * previousAllSeasonIRR (mm), integer 

  

</td> </tr>  
<tr>  
<td>

**Naming convention:**

</td>  
<td>

**MOSES_ShortTermIrriForecasts_AAAAA_YYYYMMDD.csv**

where:

  * **MOSES_ShortTermIrriForecasts** is the product identifier 

  

  * **AAAAA** is the demonstration area name, composed by 5 characters in capital letters (e.g. ITALY, SPAIN, MAROC, ROMAN) 

  

  * **YYYYMMDD** is the emission date of the short term forecasts 

  

</td> </tr>  
<tr>  
<td>

**Archiving and preservation:**

</td>  
<td>

Values for the DA Italy:

About 400 kb for each .csv daily emission.

About 8 Mb for the corresponding shapefile (see data sharing).

The files are archived on a storage server made available on Esri Italia
premises (same solution adopted for storage of Early Crop Maps described in
paragraph 3.1.1).

</td> </tr>  
<tr>  
<td>

Product ID.

</td>  
<td>

**ShortTermIrriForecast**

</td> </tr>  
<tr>  
<td>

Product Name

</td>  
<td>

**Short-term irrigation forecast**

</td> </tr>  
<tr>  
<td>

**Data sharing:**

</td>  
<td>

Data access is possible through FTP protocol (connection parameters reported
in “data sharing” section of paragraph 3.1.1)

Short-term irrigation forecast data are saved in folders that can be found in
the server folder:

DA_XX/YYYY/SWB/INSEASON/

Where XX represents the demonstration area code and YYYY is the year.

This dataset is automatically processed on the MOSES geoDataBase, using the
Unit Crop Map of the corresponding DA.

A copy of the resulting maps is saved as zipped shapefile, in the same
directory, with this naming convention:

swbShotTerm_YYYYMMDD.zip

Where YYYYMMDD is the date of emission of the forecast.

</td> </tr>  
<tr>  
<td>

**Standards and metadata:**

</td>  
<td>

</td> </tr> </table>

##  3.9. In-field measures of water balance components and IRRINET water
balance data

Canale Emiliano Romagnolo (CER) provides the following datasets to the MOSES
platform: ● IRRINET data (irrigation requirement data of the crops in the
Italian DA) ● DA-IT database with data collected during in-field measurement
campaigns.

The two datasets are detailed in the following tables.

###  3.9.1 IRRINET  
  
<table>  
<tr>  
<th>

**Product ID.**

</th>  
<th>

</th> </tr>  
<tr>  
<td>

**Product Name**

</td>  
<td>

**IRRINET**

</td> </tr>  
<tr>  
<td>

**Purpose**

</td>  
<td>

_Irrigation scheduling & water balance data _

</td> </tr>  
<tr>  
<td>

**Description (Content Specification):**

</td>  
<td>

_The product provides information related to irrigation requirements of the
crops for a specific day within the irrigation season:_

  * _ET 0  : reference evapotranspiration _

  

  * _ET max  : evapotranspiration of the crop in optimal condition _

  

  * _ET act  : actual evapotranspiration of the crop _

  

  * _IrriDate: forecasted date of the next irrigation for the crop_

  

  * _IrriAmount: irrigation amount of the next irrigation gift_

  

  * _SoilMoisture: soil moisture content_

  

  * _RootDepth: depth of crop roots_

  

  * _DegDay: sum of the growing degrees day_

  

  * _IrriNeeds: sum of the irrigation requirements of the crop_

  

</td> </tr>  
<tr>  
<td>

**Layers(*):**

</td>  
<td>

_POINT layer: the above information are provided as point attributes_

</td> </tr>  
<tr>  
<td>

**Measurement Unit:**

</td>  
<td>

  * _ET 0  : mm/ha of the day _

  

  * _ET max  : mm/ha of the day _

  

  * _ET act  : mm/ha of the day _

  

  * _IrriDate: date in American format_

  

  * _IrriAmount: mm/ha_

  

  * _SoilMoisture: mm/ha_

  

  * _RootDepth: mm_

  

  * _DegDay: integer_

  

  * _IrriNeeds: mm/ha_

  

</td> </tr>  
<tr>  
<td>

**Field of Applicability (Temporal/Spatial):**

</td>  
<td>

_Daily based values for the required date within crop life cycle_

</td> </tr>  
<tr>  
<td>

**Temporal coverage**

</td>  
<td>

_Daily_

</td> </tr>  
<tr>  
<td>

**Spatial Coverage / Area:**

</td>  
<td>

_Area covered by the service_

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Product ID.**

</th>  
<th>

</th> </tr>  
<tr>  
<td>

**Product Name**

</td>  
<td>

**IRRINET**

</td> </tr>  
<tr>  
<td>

**Spatial Resolution / Scale (Data Grid):**

</td>  
<td>

_Free_

</td> </tr>  
<tr>  
<td>

**Geographic projection /** **Reference system:**

</td>  
<td>

_WGS84 projection in decimal degree_

</td> </tr>  
<tr>  
<td>

**Input Data/Sources:**

</td>  
<td>

_Query parameter: specific date within the crop life cycle_

_Inputs to be stored before the call for each plot/crop_

  * _Plot coordinates_

  

  * _Irrigation system (category)_

  

  * _Crop type_

  

  * _Start date of the crop_

  

  * _Harvesting date_

  

  * _Kind of rootstock_

  

  * _Planting density_

  

  * _Inter rows management: weeds/tillage_

  

  * _Planting year_

  

</td> </tr>  
<tr>  
<td>

**Input Data Archiving and rolling policies**

</td>  
<td>

_Around 10Kb per plot_

</td> </tr>  
<tr>  
<td>

**Frequency of update (refresh rate):**

</td>  
<td>

_Daily_

</td> </tr>  
<tr>  
<td>

**Format:**

</td>  
<td>

_JSON/XML stream_

</td> </tr>  
<tr>  
<td>

**Naming convention:**

</td>  
<td>

_No files_

</td> </tr>  
<tr>  
<td>

**Archiving and preservation**

</td>  
<td>

</td> </tr>  
<tr>  
<td>

**Data sharing:**

</td>  
<td>

_HTTP API calls free available for the project members. Authentication may be
needed. An XML/JSON parser is needed to pick up each piece of information from
the stream._

_API documentation will be made available_

</td> </tr>  
<tr>  
<td>

**Standards and metadata:**

</td>  
<td>

_Int. Metereological Standards, FAO ID56. Metadata: crop water requirement,
seasonal water stress/replenishment,_

</td> </tr> </table>

###  3.9.2 DA-IT database  
  
<table>  
<tr>  
<th>

**Product ID.**

</th>  
<th>

</th> </tr>  
<tr>  
<td>

**Product Name**

</td>  
<td>

**DA-IT Database**

</td> </tr>  
<tr>  
<td>

**Purpose**

</td>  
<td>

Collections of data coming from various measurements made on DA-

IT

</td> </tr>  
<tr>  
<td>

**Description (Content Specification):**

</td>  
<td>

The product contains the measured data collected in the DA-IT during the
measurement campaigns (ground truth) for the following classes and parameters:

Soil Moisture

EM38: apparent EC, soil moisture volumetric content

TDR : soil moisture volumetric content

Gravimetric samples : soil moisture volumetric content

Crop biometrics

Plant Height : height of the plant canopy

Plant Width : width of the plant canopy

Plant Length: length of the plant canopy

Canopy Cover: spatial arrangement of the aboveground plant vegetation

Canopy Volume: volume of the plant aboveground vegetation

FAPAR = Fraction adsorbed of photosynthetically active radiation LSW = Leaf
Specific Weight, dry matter weight per leaf area unit at full maturity

LAI = Leaf Area Index, one-sided green leaf area per unit ground surface area

Phenology = plant development stage

Crop Yield

Yield: commercial production

Irrigation

Irr. Volume = volume of irrigation water supplied

Irr. Method = irrigation technology applied (Sprinkler =1; Drip = 2; Mini-
Sprinkler = 3; Surface =4)

</td> </tr>  
<tr>  
<td>

**Layers(*):**

</td>  
<td>

POINT layer: the above information are provided as point attributes

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Product ID.**

</th>  
<th>

</th> </tr>  
<tr>  
<td>

**Product Name**

</td>  
<td>

**DA-IT Database**

</td> </tr>  
<tr>  
<td>

**Measurement Unit:**

</td>  
<td>

EM38 = mS/m, m3/m3

TDR = m3/m3

Gravimetric sample = m3/m3

Plant Height = m

Plant Width = m

Plant Length = m

Canopy Cover = % or fraction of the ground area

Canopy volume = m3

FAPAR = % or fraction of PAR

LSW = DM g/cm2

LAI = m2/m2

Phenology = BBCH scale or other applicable

Yield = t/ha

Irr. Volume = m3/ha

Irr. Method = code (1-4)

</td> </tr>  
<tr>  
<td>

**Field of Applicability (Temporal/Spatial):**

</td>  
<td>

3 or 4 times during the crop growth cycle at specific growth stages (early
vegetation, rapid development, full vegetative growth, senescence) , 10x10 m
pixel

</td> </tr>  
<tr>  
<td>

**Temporal coverage**

</td>  
<td>

The data are collected during the growing season from March/April to the end
of October.

</td> </tr>  
<tr>  
<td>

**Spatial Coverage / Area:**

</td>  
<td>

DA-IT area

</td> </tr>  
<tr>  
<td>

**Spatial Resolution / Scale (Data Grid):**

</td>  
<td>

Variable with parameters from less than 1 m2 to 10x10 m

</td> </tr>  
<tr>  
<td>

**Geographic projection /** **Reference system:**

</td>  
<td>

WGS84 projection in decimal degree

</td> </tr>  
<tr>  
<td>

**Input Data/Sources:**

</td>  
<td>

Measurement instruments

</td> </tr>  
<tr>  
<td>

**Input Data Archiving and rolling policies**

</td>  
<td>

N.A.

</td> </tr>  
<tr>  
<td>

**Frequency of update (refresh rate):**

</td>  
<td>

Approx. every 5 weeks from April to October

</td> </tr>  
<tr>  
<td>

**Format:**

</td>  
<td>

CSV file and Shape file

</td> </tr>  
<tr>  
<td>

**Naming convention:**

</td>  
<td>

DA-IT MOSES Database

</td> </tr>  
<tr>  
<td>

**Archiving and preservation**

</td>  
<td>

About 25kb per parameter and per data, totalizing approx. 3000 Kb

</td> </tr>  
<tr>  
<td>

**Data sharing:**

</td>  
<td>

Data are available for MOSES internal uses until publication.

</td> </tr>  
<tr>  
<td>

**Product ID.**

</td>  
<td>

</td> </tr>  
<tr>  
<td>

**Product Name**

</td>  
<td>

**DA-IT Database**

</td> </tr>  
<tr>  
<td>

**Standards and metadata:**

</td>  
<td>

No standards available

</td> </tr> </table>

#  4\. Structure of Web Services

The datasets generated by the MOSES processors are organized in hierarchic
layer structures in order to be published by ArcGIS Server and to be made
available through WebGIS interface. The web services structures is replicated
for each Demonstration Area in order to coherently separate and secure data
for the different users.

In the following tables, we list the available web services and, for each one,
the public URL of the service, a description and the structure of layers
inside the service. The Demonstration Area the products refer to is specified
in the URL, and it is identified by two alphanumeric characters (the DA short
name specified in the global configuration file). We report in the following,
as examples, the URLs with the products computed in the Italian Demonstration
Areas. Identical services are being realized for the other DAs in order to
publish the products generated in the 2018 irrigation season.  
  
<table>  
<tr>  
<th>

**Early Crop Map**

</th>  
<th>

</th> </tr>  
<tr>  
<td>

URL

</td>  
<td>

https://moses.esriitalia.it/adminarcgis/rest/services/RCDAIT/earlyCropMap/MapServer

</td> </tr>  
<tr>  
<td>

Description

</td>  
<td>

The REST web service publishes one layer (id = 0), with the output of the
Early Crop Map processor for the current irrigation season and DA (Italy, in
the example URL reported above), namely maps of broad crop classes at a very
early stage in the irrigation season.

</td> </tr>  
<tr>  
<td>

Layer structure

</td>  
<td>

Layer 0: **sde.SDE.BETA_ECM_IT**

</td> </tr> </table>

**Table 1 - Early Crop Map web service description**  
  
<table>  
<tr>  
<th>

**Unit (in-season) Crop Map**

</th> </tr>  
<tr>  
<td>

URL

</td>  
<td>

https://moses.esriitalia.it/adminarcgis/rest/services/RCDAIT/unitCropMap/MapServer

</td> </tr>  
<tr>  
<td>

Description

</td>  
<td>

The REST web service publishes one layer (id = 0) with the output of the Unit
Crop Map processor, namely the processor that extracts the soil units of the
DA that are uniform according to a set of characteristics such as cultivated
crop, soil composition, belonging to the same meteorological observation and
forecast grid, type of exploited irrigation system, etc.

</td> </tr>  
<tr>  
<td>

Layer structure

</td>  
<td>

Layer 0: **UnitCropMap**

</td> </tr> </table>

**Table 2 - In season Crop Map web service description**  
  
<table>  
<tr>  
<th>

**Seasonal irrigation forecast**

</th> </tr>  
<tr>  
<td>

URL

</td>  
<td>

https://moses.esriitalia.it/adminarcgis/rest/services/RCDAIT/seasonalIrrigationForecast/MapServer

</td> </tr>  
<tr>  
<td>

**Seasonal irrigation forecast**

</td> </tr>  
<tr>  
<td>

Description

</td>  
<td>

The REST web service publishes the output of the Soil Water Balance processor
in “Seasonal” configuration on the reference DA, which produces the
statistical distribution of irrigations, expressed as percentiles, for each
computational unit. It contains three layers, named “mean of irrigation
forecasts [mm]” (layer ID = 0), “mean of seasonal irrigation climate [mm]”
(layer ID = 1) and “seasonal irrigation anomaly forecast [mm]” (layer ID = 2),
whose content is described in the following tables.

</td> </tr>  
<tr>  
<td>

Layer structure

</td>  
<td>

Layer 0: **median of seasonal irrigation forecast [mm]**

Layer 1: **median of seasonal irrigation climate [mm]**

Layer 2: **seasonal irrigation anomaly forecast [mm]**

</td> </tr> </table>

**Table 3 - Seasonal irrigation forecast web service description**  
  
<table>  
<tr>  
<th>

**In-season irrigation forecast**

</th> </tr>  
<tr>  
<td>

URL

</td>  
<td>

https://moses.esriitalia.it/adminarcgis/rest/services/RCDAIT/inSeasonIrrigationForecast/MapServer

</td> </tr>  
<tr>  
<td>

Description

</td>  
<td>

The REST web service publishes the output of the Soil Water Balance processor
in “InSeason” configuration, which produces the short-term (seven days)
irrigation forecasts of crop water needs. It publishes data referred to daily
forecasts since the beginning of the current crop season.

</td> </tr>  
<tr>  
<td>

Layer structure

</td>  
<td>

Layer 0: **Irrigation forecast (7 days)**

Layer 1: **Previous irrigation assessment (all season)**

Layer 2: **Precipitation forecast (7 days)**

Layer 3: **ET crop (7 days) [mm]**

Layer 4: **Previous irrigation assessment (14 days)**

Layer 5: **Readily available water**

Layer 6: **current soil water deficit [mm]**

Layer 7: **root depth [m]**

</td> </tr> </table>

**Table 4 - In-season irrigation forecast web service description**  
  
<table>  
<tr>  
<th>

**Current In-season irrigation forecast**

</th> </tr>  
<tr>  
<td>

URL

</td>  
<td>

https://moses.esriitalia.it/adminarcgis/rest/services/RCDAIT/currentInSeasonIrrigationForecast/MapServer

</td> </tr>  
<tr>  
<td>

Description

</td>  
<td>

The REST web service publishes the last available output generated by the Soil
Water Balance processor in “In-Season” configuration on the DA specified in
the URL. Every day, as soon as the SWB processor generates new output, the
content of the feature class published by the service is overwritten. Unlike
the previous one, this web service may be easily used in order to visualize
the current irrigation forecasts through web maps or applications.

</td> </tr>  
<tr>  
<td>

**Current In-season irrigation forecast**

</td> </tr>  
<tr>  
<td>

Layer structure

</td>  
<td>

Same layers and content of the “in-season irrigation forecast” service

</td> </tr> </table>

**Table 5 – Current In-season irrigation forecast web service description**  
  
<table>  
<tr>  
<th>

**Weather forecast on the meteorological grid covering the DA**

</th> </tr>  
<tr>  
<td>

URL

</td>  
<td>

https://moses.esriitalia.it/adminarcgis/rest/services/RCDAIT/WeatherForecast/MapServer

</td> </tr>  
<tr>  
<td>

Description

</td>  
<td>

The REST web service publishes last available 7-days weather forecasts
computed on the meteorological grid covering the DA specified in the URL.
Weather forecasts are updated every day, i.e. at each execution of the Soil
Water Balance processor. Actually, short term weather forecasts represent an
input of that processor, but they are also published as a product since they
can be useful to potential MOSES clients.

The web service publishes a single layer (ID = 0) containing all weather data.

</td> </tr>  
<tr>  
<td>

Layer structure

</td>  
<td>

Layer 0: **precipitation forecast [mm]**

</td> </tr> </table>

**Table 6 - Weather forecast web service description**  
  
<table>  
<tr>  
<th>

**Crop Water Demand processor products**

</th> </tr>  
<tr>  
<td>

URL

</td>  
<td>

https://moses.esriitalia.it/adminarcgis/rest/services/RC
-DAIT/cropWaterDemand/MapServer

</td> </tr>  
<tr>  
<td>

Description

</td>  
<td>

The REST web service publishes the outputs of the Crop Water Demand processor
generated during the current irrigation season on the DA specified in the URL.
It allows the access to data generated since the beginning of the current
irrigation season.

</td> </tr>  
<tr>  
<td>

Layer structure

</td>  
<td>

Layer 0: **NDVI**

Layer 1: **LAI**

Layer 2: **Crop coefficient analytical**

Layer 3: **Crop coefficient empirical**

Layer 4: **CWD empirical [mm/day]**

Layer 5: **CWD analytical [mm/day]**

Layer 6: **CWD forecast empirical [mm/week]**

Layer 7: **CWD forecast analytical [mm/week]**

Layer 8: **Gross irrigation requirement emp [mm/day]**

Layer 9: **Gross irrigation requirement analytical [mm/day]**

</td> </tr> </table>

**Table 7 - Crop Water Demand web service description**

Data published by all web services may be accessed by means of standard
queries. The server supports both HTTP GET and POST methods for request-
responses.

#  5\. Scientific publications

According to the requirements set by [RD2], MOSES consortium will provide an
open access to all scientific publications resulting from the project. Open
access will be guaranteed to the datasets exploited in the publications, too.

The consortium will realize a specific section of the project website, called
Publications, where all scientific papers will be listed and a “machine
readable copy” of the final version of the article will be linked (green open
access approach). In order to guarantee reliability and continuous access to
the publications, the full text articles linked by our website will be
physically stored on a public online repository, such as Zenodo  (
_http://zenodo.org/_ )  .

List of publication on the website and uploads of the full-text articles in
the public repository will be updated whenever needed.

Furthermore, the complete list of the publications produced by project’s
partners and access modes will be included in Deliverable 6.2 (Communication
and Dissemination Report).