Capability of APSIM-Oryza to stimulate lowland rice-based farming systems under nitrogen treatments in a tropical climate

Rice is the most important crop in Asia and the staple food for most of the world’s population. Due to the overwhelming importance of this crop, modelling rice-based farming systems will provide valuable help to compare experimental research findings across regions, extrapolate field experimental data to wider environments, develop management recommendations and decision-support systems, explore effects of climate change and adaptation options, and prediction of crop yield. There is an increasing demand for the capability to simulate rice-based cropping systems, especially in Asia. Such a system capability will allow expanded investigation of nitrogen dynamics, crop sequencing, intercropping, crop residue management and soil and water management. Incorporation of the ORYZA2000 rice model(Bouman and van Laar, 2006) into APSIM (Agricultural Production Systems Simulator (APSIM-Oryza) together with recent work on carbon and nitrogen dynamics in transitional flooded/non-flooded systems(Gaydon et al., 2009) has facilitated long-term simulation of lowland rice-based farming systems scenarios. However, the capability of APSIM-Oryza to simulate rice-based crop sequences involving other crops has undergone limited testing to this point and under a variety of crop management practices and cropping systems. In this paper, we detail testing of the APSIM-Oryza simulation model against an experimental dataset involving lowland rice-rice-soybean crop rotation in West Nusa Tenggara Province(NTB) Indonesi

Risk management strategies using seasonal climate forecasting in irrigated cotton production: a tale of stochastic dominance

Decision‐making in agriculture is carried out in an uncertain environment with farmers often seeking information to reduce risk. As a result of the extreme variability of rainfall and stream‐flows in north‐eastern Australia, water supplies for irrigated agriculture are a limiting factor and a source of risk. The present study examined the use of seasonal climate forecasting (SCF) when calculating planting areas for irrigated cotton in the northern Murray Darling Basin. Results show that minimising risk by adjusting plant areas in response to SCF can lead to significant gains in gross margin returns. However, how farmers respond to SCF is dependent on several other factors including irrigators’ attitude towards risk.Crop Production/Industries, Risk and Uncertainty,

Water, health and early warnings

Water management is the focus in the first section, in which a number of projects are described whereby historical and forecast information is used directly in planning specific actions; in this case the forecaster-user chain is short and manageable at a personal level. Next is a detailed account of the steps required to establish climate services in the health area. Finally, Early Warning Systems are described. Early Warning Systems have not tended to use predictions until recently, traditionally having been built around historical observations. In that context Early Warning Systems provide an example of an application mainly designed for humanitarian benefit built solely using climate data alongside other information, but with growing use of predictions. A worked example is included establishing the impact of climate variability on disease incidence, the results of which provide a basis for incorporating seasonal climate forecasts into a Malaria Early Warning System in southern Africa

Responses of nitrogen utilization and apparent nitrogen loss to different control measures in the wheat and maize rotation sytsem

Nitrogen (N) is an essential macronutrient for plant growth and excessive application rates can decrease crop yield and increase N loss into the environment. Field experiments were carried out to understand the effects of N fertilizers on N utilization, crop yield and net income in wheat and maize rotation system of the North China Plain (NCP). Compared to farmers’ N rate (FN), the yield of wheat and maize in reduction N rate by 21–24% based on FN (RN) was improved by 451 kg ha-1, N uptakes improved by 17 kg ha-1 and net income increased by 1671 CNY ha-1, while apparent N loss was reduced by 156 kg ha-1. The controlled-release fertilizer with a 20% reduction of RN (CRF80%), a 20% reduction of RN together with dicyandiamide (RN80%+DCD) and a 20% reduction of RN added with nano-carbon (RN80%+NC) all resulted in an improvement in crop yield and decreased the apparent N losses compared to RN. Contrasted with RN80%+NC, the total crop yield in RN80%+DCD improved by 1185 kg ha-1, N uptake enhanced by 9 kg ha-1 and net income increased by 3929 CNY ha-1, while apparent N loss was similar. Therefore, a 37–39% overall decrease in N rate compared to farmers plus the nitrification inhibitor, DCD, was effective N control measure that increased crop yields, enhanced N efficiencies, and improved economic benefits, while mitigating apparent N loss. There is considerable scope for improved N use effieincy in the intensive wheat -maize rotation of the NCP

Developing ENSO-based irrigation water forecast system in a region with limited hydro-meteorological observations to mitigate the impacts of climate variability: a case study in Lombok, Indonesia

Uncertainty in water supplies due to climate variability is the major constraint for sustainable production of irrigated agricultural system in many countries like Indonesia. The paper describes how an integrated modelling approach is developed to simulate long-term streamflow and water allocation from limited observed hydro- meteorological data, which enables forecasting the streamflow based on the Southern Oscillation Index (SOI)

Performance of rice on a coarse sandy loam soil in response to water-saving irrigation practices in lowland eastern Indonesia

Rapid increase in world population and a corresponding increase in demand for water and land from industrial and municipal have forced the agricultural sector to use marginal land and irrigation water more efficiently by using less water to produce more food. Coarse-textured and porous soils of the tropical regions are increasingly used for growing both upland and lowland rice. In porous soils under rice, continuous flooding cannot be maintained due to high water percolation rates. Development of appropriate planning and management strategy to improve available water resources for the agricultural sector is a high national and global priority. Increased efficiency in water use is essential for future food security in Asia where rice production needs to increase by 70% over the current production by the year 2025 (Tuong and Bhuiyan 1999). However, experimental evidence for the hydrological and environmental conditions of coarse soils under which current rice-based cropping systems are practiced is limited. Such studies will become more important as porous soils are increasingly used for irrigated rice-based cropping systems. In this paper, we evaluate the effectiveness of alternately submerged and non-submerged (ASNS) over continuously submerged (CS) irrigation practices using three years of field experimental data on a coarse soil in the tropical region of eastern Indonesia

PENGGUNAAN INDEKS OSILASI SELATAN UNTUK MEMPRAKIRAKAN SIFAT HUJAN MUSIMAN GUNA MENENTUKAN STRATEGI TANAMAN DI LAHAN TADAH HUJAN DI PULAU LOMBOK SHOUTHERN OSCILLATION INDEX FOR FORCASTING SEOSONAL RAINFALL CHARACTERISTIC TO DETERMINE UPLAND ...

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ENSO-based streamflow forecasting and its application to water allocation and cropping decisions - an Australian experience

High climatic variability in northeast Australia, combined with limited water resources and increasing demand, makes the task of managing irrigation water and cropping decisions more complex. In this paper we explore the relationship between the El Niño-Southern Oscillation (ENSO) and the Inter-decadal Pacific Oscillation (IPO) on long-term streamflow. A functional relationship for forecasting streamflow and water availability will allow improved management of water resources and cropping decisions. Our results show that streamflow can be forecast during the peak irrigation demand period (October–January) using the Southern Oscillation Index (SOI) up to four months in advance. The impact of ENSO on streamflow is modulated by IPO phases with a substantial strengthening of La Niña episodes during the cold (negative) phase of IPO. Simulation of dam inflow and water allocation shows that the volume of irrigation water in La Niña years is significantly more than that in El Niño years; the resulting increase of some 20% in total crop area has a potential revenue of Au$40 million in the study catchment. Economic analysis using gross margin shows that SOI-based planting strategies would result in the best economic return for cotton growers in this region

Penggunaan Indeks Osilasi Selatan Untuk Memprakirakan Sifat Hujan Musiman Guna Menentukan Strategi Tanaman Di Lahan Tadah Hujan Di Pulau Lombok Shouthern Oscillation Index for Forcasting Seosonal Rainfall Characteristic to Determine Upland ...

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