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INDONESIA
Agromet
Published by Institut Pertanian Bogor
ISSN : 01263633     EISSN : 2655660X     DOI : -
Core Subject : Agriculture,
Agriculture, Biological Sciences & Forestry
Agromet publishes original research articles or reviews that have not been published elsewhere. The scope of publication includes agricultural meteorology/climatology (the relationships between a wide range of agriculture and meteorology/climatology aspects). Articles related to meteorology/climatology and environment (pollution and atmospheric conditions) may be selectively accepted for publication. This journal is published twice a year by Indonesian Association of Agricultural Meteorology (PERHIMPI) in collaboration with Department of Geophysics and Meteorology, Faculty of Mathematics and Natural Sciences, IPB University.
Arjuna Subject : -
Articles 289 Documents
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Propagation Characteristics of Madden Julian Oscillation in the Indonesian Maritime Continent: Case Studies for 2020-2022 Istiqomah, Fadhilatul; Yulihastin, Erma; Wiratmo, Joko; Hermawan, Eddy; Trilaksono, Nurjanna Joko; Irawan, Dasapta Erwin; Yohanes, Kristy Natasha; Ayunina, Amalia Qurrotu
Agromet Vol. 38 No. 1 (2024): JUNE 2024
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.38.1.1-12

Abstract

Madden-Julian Oscillation (MJO) can affect weather and climate variability in the Indonesian Maritime Continent. MJO propagation is not always the same, previous research has classified MJO into 4 categories: slow, fast, stand, and jump. The objective of this study is to investigate the differences in MJO propagation and the factors that impact it. Daily data for variables such as Outgoing Longwave Radiation (OLR), zonal wind, and sea surface temperature are utilized in this research. The collected data is processed using composite methods based on the 8 MJO phases, with a specific focus on the years 2020, 2021, and 2022. The research findings suggest that warm sea surface temperatures in the Pacific Ocean and zonal winds dominated by Kelvin waves are favorable for MJO propagation. Conversely, cooling sea surface temperatures in the Pacific Ocean and zonal winds dominated by equatorial Rossby waves can hinder MJO propagation. Future researchers are expected to examine the impact of MJO propagation during extreme rainfall occurrences in several regions of Indonesia, as well as the application of machine learning and deep learning methods to predict MJO propagation in the future.
Climate Influences on Latex Yield in South Sumatra, Indonesia Sahuri
Agromet Vol. 38 No. 1 (2024): JUNE 2024
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.38.1.13-18

Abstract

This study addresses the impact of climate variability on latex yield. Field research was carried out in the Indonesian Rubber Research Institute Experimental Field, located in South Sumatra, Indonesia for 2020 to 2022. The study used mature IRR 118 clones of rubber (Hevea brasiliensis) planted in clay loam soil. Latex yields for dry and rainy seasons were compared to obtain the effects of climatic factors. A purposive sampling of latex clone IRR 118 was applied in the field. The results showed that declined rainfall and soil moisture content contributed to the low latex yield during dry season. A declined water availability acts as a limiting factor resulting in decreased latex yield. Latex yield consistently decreased when soil moisture content fell below 21.5%. Based on statistical analysis, the correlation between latex yield and climate factor was 0.36, 0.42, and 0.52 for rainfall, soil moisture content, and evapotranspiration, respectively. Our findings highlight the crucial influence of climatic factors, emphasizing the significance of optimal water availability for latex production.
A Comparison of the Performance of the Weighted Ensembles Means in CORDEX-SEA Precipitation Simulations Aminoto, Tugiyo; Faqih, Akhmad; Perdinan; Koesmaryono, Yonny; Dwi Dasanto, Bambang
Agromet Vol. 38 No. 1 (2024): JUNE 2024
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.38.1.19-35

Abstract

Numerous studies stated that the performance of ensemble mean derived from multiple climate models generally surpassed the individual member model, and applying weighting factors potentially increase the ensemble mean of performance. This study aims to assess the performance of unweighted and weighted ensemble means of 9-modelled precipitation datasets in the CORDEX-SEA multi-model simulations for 1981-2005. The 9 datasets included: CNRM_a, ECE_b, GFDL_b, IPSL_b, HadGEM2_a, HadGEM2_c, HadGEM2_d, MPI_c, and NorESM1_d. The weighting factors were derived from the models' skill scores measured using five statistical-based metrics, namely Taylor, Pierce (SS), Tian skill score (Tian), Climate prediction index (CPI), and Performance and Independence (PI). The ERA5 and GPCP precipitation datasets were used as the references for comparison. Then, reliable metrics will be used to determine the weighting factor. The results found that three metrics namely Taylor, SS, and Tian were more reliable than the other two metrics (CPI and PI). Spatially, the weighted ensemble mean based on a random method was superior to other ensemble mean methods and individual models. We found that the CNRM_a and GFDL_b models were spatially performed best. In contrast, most the ensemble means was temporally less performed compared to the individual model. Our findings suggested that by removal of low performance models will significantly influence on the overall ensemble model performance. Further, the research may provide valuable considerations of climate models selection for climate projection assessments, especially in the Southeast Asia region.
Extreme Rainfall Analysis in the Bengawan Solo Watershed, Java Perdinan; Hapsari, Indri; Mudzakir Setiawan, Amsari
Agromet Vol. 38 No. 1 (2024): JUNE 2024
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.38.1.36-48

Abstract

As the largest watershed in Java Island, the Bengawan Solo watershed has experienced recurrent hydrometeorological hazards, leading to infra-structure damage, casualties, and environmental degradation. Research on extreme rainfall causing the hazards in the Bengawan Solo watershed is still limited. This study examines extreme rainfall events by analyzing daily rainfall data (1991-2020) at three observation stations namely Musuk, Tinap, and Lowayu, which represent the upstream, middle, and downstream of the Bengawan Solo watershed. The Extreme Value Theory (EVT) using the Block Maxima approach with a Generalized Extreme Value (GEV) method was used to determine the rainfall return period of 5, 10, 20, 30, and 50-year. We applied the Mann-Kendall test to assess the annual trends of extreme rainfall indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI). The results found that the highest estimated annual maximum of daily rainfall was in Musuk station (226.7 mm), followed by Tinap station (159.3 mm) and Lowayu station (149.4 mm). While no significant trend was observed for Musuk, other stations showed a significant trend for the decrease of the daily rainfall intensity, the increase of the number of annual rainy days, the decrease of the annually maximum amount of five consecutive precipitation days, and the increase of the annually number of consecutive wet days. There is also an increase in the maximum amount of annual rainfall for one day (Rx1day) at Lowayu station, which indicates a higher risk of disaster due to high rainfall. Additionally, an increasing trend in the total annual rainfall (PRCPTOT) at Musuk, Tinap, and Lowayu stations suggests a greater potential for water storage to meet water needs in these areas.
A Preliminary Study on the Parameter Configuration of Weather Research Forecasting in Tropical Peatland, Central Kalimantan Taufik, Muh.; Haikal, Mudrik
Agromet Vol. 38 No. 1 (2024): JUNE 2024
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.38.1.49-57

Abstract

Hydrometeorological variables are sensitively regulated by atmospheric dynamics and variability. Weather research and forecasting (WRF) model is the cutting-edge tool for studying and investigating the dynamics of physical atmospheric conditions, but the configuration scheme of WRF parameters remains a research challenge for topical peatland situated in the maritime continent. Here, we evaluated WRF parametrization based on three kalibration configuration schemes, which influence rainfall, temperature, and soil moisture dynamics. We tested the WRF evaluation for Sebangau-Kahayan peatland for a wet-dry season in August 2020. The best configuration was determined based on three statistical metrics namely mean absolute error, percent bias, and coefficient of correlation. Our results showed that WRF forecasts were greatly depend on a bias correction to improve the model performance, in which it was consistently found in all configurations. Rainfall was barely predicted in station level with a low performance in term of weekly spatial distribution. Other findings revealed that all configurations showed a good performance for temperature and soil moisture forecasts. Further, our findings emphasize the important physical parameter of WRF that control rainfall formation and dynamics. Last, we highlight an urgent need of more ground stations in term of spatial distribution to validate the weather forecast.
Identification of Peatland Burned Area based on Multiple Spectral Indices and Adaptive Thresholding in Central Kalimantan Pratikasiwi, Hilda Ayu; Taufik, Muh.; Santikayasa, I Putu; Domiri, Dede Dirgahayu
Agromet Vol. 38 No. 2 (2024): DECEMBER 2024
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.38.2.68-77

Abstract

Nowadays, spectral index has become popular as a tool to identify fire-burned areas. However, the use of a single index may not be universally applicable to region with diverse landscape and vegetation as peatlands. Here, we propose to develop a procedure that integrates multiple spectral indices with an adaptive thresholding method to enhance the performance of burned area detection. We combined the Normalized Difference Vegetation Index (NDVI) and the Normalized Burn Ratio (NBR) using MODIS imagery from 2002 to 2022 to calculate (Confirmed Burned Pixel) by filtering dNDVI and dNBR. The mean and standard deviation of serve as inputs for image thresholding. We tested our approach in Sebangau peatland, Central Kalimantan, where fires occur annually. The results showed that the model performed well with overall accuracy > of 91%, indicating that the model is effective and reliable for identifying burned areas. The findings also revealed that the frequency of fire is below 2 times/year, with the southeastern is the most fire prone regions. Further, our findings provide an alternative approach for identifying burned areas in locations with diverse vegetation cover and different geographical regions.
ENSO and IOD Influence on Extreme Rainfall in Indonesia: Historical and Future Analysis Hanifa, Risyda; Wiratmo, Joko
Agromet Vol. 38 No. 2 (2024): DECEMBER 2024
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.38.2.78-87

Abstract

Indonesia, as a maritime continent, is vulnerable to environmental disasters such as floods and landslides due to extreme rainfall. This study aims to identify changes in the influence of ENSO and IOD on extreme rainfall across Indonesia, specifically during the September-October-November period. We used rainfall and sea surface temperature data from the CMIP6 climate model for the historical period (1985-2014), near-future (2031-2060), and far-future (2061-2090) projections under SSP2-4.5 and SSP 5-8.5 climate scenarios. The relation between rainfall dan ENSO/IOD was simply defined by linear regression approach. We analyzed the change of influence by comparing the historical and the future condition. The results indicated that the changes in the teleconnection of ENSO and IOD to extreme rainfall in future is consistently negative, except for Java (near-future) and Kalimantan and southern Sumatra (far-future). Our finding revealed that significant changes in the teleconnection varied throughout maritime continent. The maximum change was found in Northern Kalimantan, which reached values of -80 mm/°C due to ENSO and -180 mm/°C due to IOD for near future. These findings highlight the spatial variability in teleconnection changes across Indonesia, underscoring the need for region-specific climate adaptation measures in response to evolving extreme rainfall patterns.
Rainfall and Temperature Change Analysis and their Correlation on Maize Productionin Karawang, West Java Ruminta; Fiky Yulianto, Wicaksono; Grace Ananda, Napitupulu
Agromet Vol. 38 No. 2 (2024): DECEMBER 2024
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.38.2.88-96

Abstract

Maize is an important food commodity and its yields can be threatened by changes in climate variables, such as increasing air temperature and decreasing rainfall. The research identifies and detect the change in climate variables and analyze their correlation with maize production. Quantitative and descriptive methods were used namely trend analysis, correlation, and regression. We utilized climate data (temperature and rainfall) and maize production for 1991-2022, with tested study area in Karawang, West Java. We divided the climate data into two periods to analyze any change in climate variables. The results indicated a change in temperature (+0.56 °C) and rainfall (-47.34 mm) per year, but there is no change in the agroclimatic zone. Our findings showed a moderate correlation between rainfall and maize production and productivity, with the mean correlation coefficients of 0.31 and 0.35, respectively. Similarly, air temperature showed a moderate correlation with maize production and productivity, with the mean correlation coefficients of 0.30 and 0.32, respectively. Appropriate anticipatory and adaptation efforts are needed to maintain maize production in rainfed agriculture such as in Karawang Regency.
The Use of Artificial Neural Networks to Estimate Reference Evapotranspiration Haris, Abdul; Marimin; Wahjuni, Sri; Setiawan, Budi Indra
Agromet Vol. 39 No. 1 (2025): JUNE 2025
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.39.1.1-7

Abstract

Evapotranspiration is defined as the loss of water from soil and vegetation to the atmosphere, driven by weather conditions. It reduces the availability of water for agricultural purposes, which affects the amount of irrigation water, particularly during the dry season. The objective of this paper is to present a comparative analysis of the estimated reference evapotranspiration value based on artificial neural networks (ANN) with backpropagation bias 1 (BP-1) and backpropagation bias 0 (BP-0) architectures. The model was fed with data of air temperature, relative humidity, and solar radiation. The model is utilized to calculate the evapotranspiration using the Hargreaves method as the training data. The performance of ANN model was evaluated using the mean square error (MSE), root mean square error (RMSE), and coefficient determination (R2). Our results showed that both ANN models performed well as indicated by low error (MSE < 0.01) and high R2 (>0.99). Also, we found that air temperature and relative humidity determine the optimal prediction. Further, this proposed model can serve as a reference for other models seeking to determine the most appropriate computational model for evapotranspiration value estimation.
Assessment of Rice Crop Water Requirements for Planting Season in Moderate Agroclimatic Area of West Sumatra Saputra, Rizky Armei; Yulianti, Via; Hermansah
Agromet Vol. 39 No. 1 (2025): JUNE 2025
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.39.1.40-47

Abstract

In changing climate, uncertainty in rice production becomes more frequent leading to threat of food security. However, research on rice cultivation in the rainfed agricultural areas of West Sumatra remains limited. The objectives of the study are to analyze the crop water requirements of rainfed rice and to determine rice planting patterns. The study was conducted in a moderate agro-climate area of West Sumatra based on oldeman agroclimate zone that experienced changes in planting patterns. We used climate data for 1991 – 2020 obtained from TerraClimate, which were utilized for monthly water balance computation based on the Thornwhite and Matter approach. The analysis focused on four major rice production centers, namely: Panti in Pasaman, Lima Kaum in Tanah Datar, Luak in Lima Puluh Kota and Sijunjung. The results showed change in water deficit periods across the study sites have changed planting season. Based on our analysis site in Lima Kaum, Tanah Datar experienced the longest deficit period, which lasted 5 months from May to September. This situation may not suitable to plant rice throughout the year without additional irrigation. Further, adjusting to the secondary crop may be considered to optimize agricultural productivity. These findings can serve as a reference for determining planting seasons and improving water use and distribution strategies in rainfed agricultural systems.

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