Modelling and Forecasting of Rice Yield in support of Crop Insurance

W. van Verseveld; Albrecht Weerts; P. Trambauer; S.C. de Vries; J.G. Conijn; E. van Valkengoed; Dirk Hoekman; H. Hengsdijk; A. Schrevel

Abstract

The Government of Indonesia has embarked on a policy to bring crop insurance to all of Indonesia’s farmers. To support the Indonesian government, the G4INDO project (www.g4indo.org) is developing/constructing an integrated platform for judging and handling insurance claims. The platform consists of bringing together remote sensed data (both visible and radar) and hydrologic and crop modelling and forecasting to improve predictions in one forecasting platform (i.e. Delft-FEWS, Werner et al., 2013). The hydrological model and crop model (LINTUL) are coupled on time stepping basis in the OpenStreams framework (see https://github.com/openstreams/wflow) and deployed in a Delft-FEWS forecasting platform to support seasonal forecasting of water availability and crop yield. First we will show the general idea about the project, the integrated platform (including Sentinel 1 & 2 data) followed by first (reforecast) results of the coupled models for predicting water availability and crop yield in the Brantas catchment in Java, Indonesia.

Original language	English
Publication status	Published - 2016
Event	AGU Fall Meeting 2016 - San Francisco, United States Duration: 12 Dec 2016 → 16 Dec 2016

Conference

Conference	AGU Fall Meeting 2016
Country/Territory	United States
City	San Francisco
Period	12/12/16 → 16/12/16

Cite this

@conference{30908c1acd9446f1ba03415fbd1ce48c,

title = "Modelling and Forecasting of Rice Yield in support of Crop Insurance",

abstract = "The Government of Indonesia has embarked on a policy to bring crop insurance to all of Indonesia{\textquoteright}s farmers. To support the Indonesian government, the G4INDO project (www.g4indo.org) is developing/constructing an integrated platform for judging and handling insurance claims. The platform consists of bringing together remote sensed data (both visible and radar) and hydrologic and crop modelling and forecasting to improve predictions in one forecasting platform (i.e. Delft-FEWS, Werner et al., 2013). The hydrological model and crop model (LINTUL) are coupled on time stepping basis in the OpenStreams framework (see https://github.com/openstreams/wflow) and deployed in a Delft-FEWS forecasting platform to support seasonal forecasting of water availability and crop yield. First we will show the general idea about the project, the integrated platform (including Sentinel 1 & 2 data) followed by first (reforecast) results of the coupled models for predicting water availability and crop yield in the Brantas catchment in Java, Indonesia. ",

author = "{van Verseveld}, W. and Albrecht Weerts and P. Trambauer and {de Vries}, S.C. and J.G. Conijn and {van Valkengoed}, E. and Dirk Hoekman and H. Hengsdijk and A. Schrevel",

year = "2016",

language = "English",

note = "AGU Fall Meeting 2016 ; Conference date: 12-12-2016 Through 16-12-2016",

}

TY - CONF

T1 - Modelling and Forecasting of Rice Yield in support of Crop Insurance

AU - van Verseveld, W.

AU - Weerts, Albrecht

AU - Trambauer, P.

AU - de Vries, S.C.

AU - Conijn, J.G.

AU - van Valkengoed, E.

AU - Hoekman, Dirk

AU - Hengsdijk, H.

AU - Schrevel, A.

PY - 2016

Y1 - 2016

N2 - The Government of Indonesia has embarked on a policy to bring crop insurance to all of Indonesia’s farmers. To support the Indonesian government, the G4INDO project (www.g4indo.org) is developing/constructing an integrated platform for judging and handling insurance claims. The platform consists of bringing together remote sensed data (both visible and radar) and hydrologic and crop modelling and forecasting to improve predictions in one forecasting platform (i.e. Delft-FEWS, Werner et al., 2013). The hydrological model and crop model (LINTUL) are coupled on time stepping basis in the OpenStreams framework (see https://github.com/openstreams/wflow) and deployed in a Delft-FEWS forecasting platform to support seasonal forecasting of water availability and crop yield. First we will show the general idea about the project, the integrated platform (including Sentinel 1 & 2 data) followed by first (reforecast) results of the coupled models for predicting water availability and crop yield in the Brantas catchment in Java, Indonesia.

AB - The Government of Indonesia has embarked on a policy to bring crop insurance to all of Indonesia’s farmers. To support the Indonesian government, the G4INDO project (www.g4indo.org) is developing/constructing an integrated platform for judging and handling insurance claims. The platform consists of bringing together remote sensed data (both visible and radar) and hydrologic and crop modelling and forecasting to improve predictions in one forecasting platform (i.e. Delft-FEWS, Werner et al., 2013). The hydrological model and crop model (LINTUL) are coupled on time stepping basis in the OpenStreams framework (see https://github.com/openstreams/wflow) and deployed in a Delft-FEWS forecasting platform to support seasonal forecasting of water availability and crop yield. First we will show the general idea about the project, the integrated platform (including Sentinel 1 & 2 data) followed by first (reforecast) results of the coupled models for predicting water availability and crop yield in the Brantas catchment in Java, Indonesia.

M3 - Abstract

T2 - AGU Fall Meeting 2016

Y2 - 12 December 2016 through 16 December 2016

ER -

Modelling and Forecasting of Rice Yield in support of Crop Insurance

Abstract

Conference

Fingerprint

Cite this