Implementing CGMS in Morocco

and the Huaibei/Juanghuai plains

Allard de Wit & Raymond van der Wijngaart

Workshop contents

Introduction MARS Crop Yield Forecasting System (MCYFS) and Crop Growth Monitoring System (CGMS): What is it and what is needed to set it up Strengths and limitations How to sustain it in the future

Discuss with partners INRA and APEI Collection of necessary inputs (weather, experimental data, soil

data, irrigation, regional statistics, etc.) – Deliverable 2.1 Usability of CGMS for pilot areas: main drivers of yield level and

variability, identify missing elements and improvements. Take into account synergies with WP3

Information chain in the MCYFS

MeteorologicalMeteorologicalinformation information AgrometeoAgrometeo

informationinformation

Analysts

On-demandOn-demandelaborationelaboration(extreme events(extreme events

&&critical condition)critical condition)

YieldYieldestimateestimate

StatisticalStatistical

informationinformation

SatelliteSatellite

informationinformation

Domain of CGMS

Level 1 Level 2 Level 3CGMS overview and levels of operation

CGMS.exe program

Daily estimates at grid level: Precipitation (daily total) Temperature (daily maximum, daily minimum) Global radiation (daily total) or a proxy (sunshine duration,

cloud cover) Vapour pressure Wind speed (daily average) Reference evapotranspiration (derived from the above)

Potential evaporation of water surface Potential evaporation of wet bare soil Potential evapotranspiration of a crop canopy

Level1: Weather data requirements in CGMS

Level1: How to get weather data

Use station observations: CGMS can process, store, make quality checks

and substitute missing data. CGMS can interpolate to a regular grid

Use output from numerical weather prediction models: Often easier to obtain Beware for strong biases for some variables

and/or regions!

Level 2: WOFOST Crop Model in CGMS

Level2: WOFOST profile

WOFOST is a semi-deterministic crop simulation model of physiological processes (daily time steps), phenology (sowing- flowering- maturity) Light interception Photosynthesis Respiration Assimilate partitioning Leaf area dynamics Senescence of canopy Evapotranspiration Soil water balance

Level2: daily flow of dry matter in WOFOST

light interception

potential gross photosynthesis

actual gross photosynthesisTa/Tp

radiation leaf area

maintenance respiration growth

respiration

crop growth(dry matter)

roots stems storage organs

leaves

partitioningdvs

temp

Production ecological principles of yield levels

Production level (t/ha) Van Ittersum and Rabbinge, 1997

CO2

Radiation

Temperature

Crop features

Rainfall

Irrigation

Nutrients

Weeds/Pests

Critical periods

Diseases

Pollutants/salt

Defining factors

Reducing factors

Limiting factorsAttainable yield

Actual yield

WOFOST 7.1

Level2: Output variables of WOFOST in CGMS

Crop development stage Crop total biomass and yield under

potential & water-limited conditions Crop leaf area index under potential &

water-limited conditions Soil moisture, transpiration

Level2: Limitations of WOFOST

Multi-parameter model, difficult to calibrate and validate

Sensitive for initial state of soil and crop Processes not simulated: Irrigation,

nutrients, winter-kill, cold stress, heat stress, damage from excess water, flooding

No recovery mechanisms

Level2: Implementing WOFOST

Needed for setting up CGMS Level2 (WOFOST) Spatial information about soil type and

parameters Regional crop calendars and crop masks for

winter-wheat Winter-wheat experimental data for calibration:

1. phenology (sowing, emergence, flowering, maturity).2. Crop total biomass, maximum LAI.3. Time-series of crop biomass (roots, stems, leaves,

organs), LAI, yield under potential conditions.4. As point 3, under water-limited conditions.

Level3: Actual yield forecasting

Statistical infrastructure to forecast crop yield/production in the current year using: Time-series of historic reported crop yield and

area Time-series of crop yield indicators (e.g. CGMS

output, meteorology or remote sensing indicators)

Needed for setting up: Time-series of historic crop yield & area at

national, provincial and (if possible) district level

How to sustain CGMS A clear political mandate for agricultural monitoring with a stable

source of funding and a clear entry into the political decision making process.

Institutional arrangements to operate the system and a stable project organization with clear functional delegation of responsibilities to the various partners;

Long term dedication of key personnel to the project not only at the institution with the political mandate, but also with supporting institutions (research institutes, universities). In this way, knowledge can be build up and shared across a pool of personnel;

Good technical know-how: particularly with regard to the management of database system, the handling of spatial information layers, statistical analysis of system results and visualization;

A stable stream of input data consisting of weather data, but also historical regional crop yield statistics and crop experimental data;

WP2: Adapting CGMS for winter-wheat monitoringin Huaibei/Juanghuai and Morocco

WP2.1: Data collection WP2.2/2.3: Evaluation of usability, strategy

development, system adaptation for target regions

WP2.4/2.5: System testing and piloting in target regions

WP2 data collection activities - China (D2.1)Huaibei plains

What Description Who When Backup solution

Station weather data      ECMWF data from MO3

Soil map and parameters       FAO 1:5.000.000

Crop masks      SAGE crop masks at 0.05 degrees

Regional crop calendars      FAO or MO3 calendars

Crop experimental data       None

winter-wheat regional statistics       None

WP2.1 data collection activities - Morocco (D2.1)Morocco

What Description Who WhenBackup solution

Station weather data      ECMWF data from MO3

Soil map and parameters  50,000 soil map    

FAO 1:5.000.000

Crop masks      

SAGE crop masks at 0.05 degrees

Regional crop calendars      

FAO or MO3 calendars

Crop experimental data       None

winter-wheat regional statistics  Province level statistics Riad   15 april None

WP2.2/2.3: Evaluation of usability What are main driving factors of yield level

and inter-annual variability at regional scale? What are missing components in the current

CGMS for the target regions? Are there special requirements for system

output? How to answer these questions:

Analyze time-series of crop yield at regional level in combination with weather, model output.

Design questionnaire to be circulated with local experts in the target regions.

Conclusion

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