Agromet
type: channel
description: Agromet is published twice a year by the Indonesian Association of Agricultural Meteorology (PERHIMPI) in collaboration with Department of Geophysics and Meteorology, Faculty of Mathematics and Natural Sciences, IPB University. Agromet publishes original research articles or reviews that have not been published elsewhere. The scope of publication related to weather and climate issues (agriculture, forestry, water resources, environment, ecology, and health as affected by weather and climate variability and change).
publisher: PERHIMPI (Indonesian Association of Agricultural Meteorology)
language: en
publication name: Agromet
issn: 0126-3633
items: Water Use Efficiency and Adaptive Responses of Oil Palm under El Niño-Induced Drought and Haze
items: Transboundary Trajectory Patterns of PM2.5 in The Lower Troposphere of Jakarta Region
items: Spatiotemporal Patterns of Meteorological Drought in the National Food Barn Region: A Case Study of South Sulawesi Province
items: Bias Correction of CMIP6 Models for Assessment of Wet and Dry Conditions Over Sumatra
items: Assessing the Influence of Climate Services and Climate Change Adaptation Strategies on Smallholder Agriculture: A Systematic Literature Review
items: Water Use Efficiency in Pineapple Plants Fertilization Based on Water Balance Analysis
items: ECMWF SEAS5 Seasonal Rainfall Assessment: A Study Case in Papua
items: Flood Management Strategy Based on Analysis of Regional Characteristics and Causal Factors in Kendari City
items: Climate Change Impact On Rice Productivity Using FAO AquaCrop Model: A Case Study in Lampung
items: Assessment of Rice Crop Water Requirements for Planting Season in Moderate Agroclimatic Area of West Sumatra
items: Land Management of Tidal Swamp Type B with Surjan System as Climate Change Anticipation
items: Contribution of Small Rainwater Reservoirs to Performance Off-season Vegetable Farming
items: The Use of Artificial Neural Networks to Estimate Reference Evapotranspiration
items: Canopy Microclimate Modification with Reflective Mulches Under Oil Palm and Its Role to Soybean Growth
items: Effect of Rainfall Intensity on Glyphosate Herbicide Effectiveness in Controlling Ageratum conyzoides, Rottboellia exaltata, and Cyperus rotundus Weeds
items: Implementation of Bayesian Model Averaging Method to Calibrate Monthly Rainfall Ensemble Prediction over Java Island
items: The Impact of El Niño and La Nina on Fluctuation of Rice Production in Banten Province
items: Dynamics Modeling of CO2 in Oil Palm
items: Modeling of Heavy Rainfall Triggering Landslide Using WRF Model
items: Rainfall and Temperature Change Analysis and their Correlation on Maize Productionin Karawang, West Java
items: ENSO and IOD Influence on Extreme Rainfall in Indonesia: Historical and Future Analysis
items: Identification of Peatland Burned Area based on Multiple Spectral Indices and Adaptive Thresholding in Central Kalimantan
items: Extreme Rainfall Analysis in the Bengawan Solo Watershed, Java
items: Correlation between Climate Data and Yields of Some Prominent Food Crops in Manokwari, West Papua, Indonesia
items: A Preliminary Study on the Parameter Configuration of Weather Research Forecasting in Tropical Peatland, Central Kalimantan
items: A Comparison of the Performance of the Weighted Ensembles Means in CORDEX-SEA Precipitation Simulations
items: Climate Influences on Latex Yield in South Sumatra, Indonesia
items: Propagation Characteristics of Madden Julian Oscillation in the Indonesian Maritime Continent: Case Studies for 2020-2022
items: Analysis of Carbon Dioxide Emission from Forest Fires based on Fire Radiative Power in Riau
items: Climate influence on Diarrhea Disease in Tropical Regions based on Systematic Literature Review

Water Use Efficiency and Adaptive Responses of Oil Palm under El Niño-Induced Drought and Haze
type: item
description: Oil palm plays an important role in the tropical carbon cycle but is highly sensitive to climatic variability. Understanding the coupled dynamics of carbon and water fluxes in such ecosystems essential for sustainable management under variable climatic conditions. This study analyses the Water Use Efficiency (WUE) and coupled carbon–water fluxes of an 18-year-old oil palm plantation in Jambi, Indonesia, during the 2015 El Niño event using data from an eddy covariance flux tower. The analysis focused on the diurnal variations of Net Ecosystem Production (NEP), evapotranspiration (ET), and water use efficiency (WUE) during wet, dry, and dry with haze periods, which were determined based on rainfall data. Our results show that WUE reached its highest value during the dry-with-haze period (7,484 g CO₂ kg⁻¹ H₂O), more than double that of the wet (3,440) and dry (3,347) periods. This increase resulted from reduced evapotranspiration (ET) due to stomatal regulation, despite lower Net Ecosystem Production (NEP) caused by light limitation from haze. Diurnal analyses showed WUE peaking in the morning and declining at midday as the Vapor Pressure Deficit (VPD) increased (up to 0.88 kPa under haze). These findings highlight oil palm’s adaptive strategy to conserve water under stress while maintaining productivity. However, severe haze markedly weakens carbon sequestration. The results provide critical insights for optimizing irrigation and water management in the face of increasing climate variability.
subject: Articles
  topic: section
subject: evapotranspiration
  topic: keywords
subject: net ecosystem production
  topic: keywords
subject: oil palm
  topic: keywords
subject: vapor pressure deficit
  topic: keywords
subject: water use efficiency
  topic: keywords
creator: Kharisma Rinandyta
creator: Tania June
rights: Copyright (c) 2025 Kharisma Rinandyta, Prof. Dr. Ir. Tania June, MSc https://creativecommons.org/licenses/by-nc/4.0
date: 2025-11-12
publication date: 2025-11-12
starting page: 86
ending page: 94
doi: 10.29244/j.agromet.39.2.86-94

Transboundary Trajectory Patterns of PM2.5 in The Lower Troposphere of Jakarta Region
type: item
description: PM2.5 is a key indicator of air quality and poses serious environmental and health concern, especially in Jakarta where air quality frequently exceeds recommended standards. But researches mainly focus on surface-level pollutant, underscoring transboundary emission. This study aims to analyze the transboundary trajectory patterns of PM2.5 pollutants, and to estimate the contribution of emissions to air quality in the Jakarta for 2024. Meteorological data and PM2.5 concentrations from five air quality monitoring stations were analyzed during non-rainfall periods. Potential emission sources analysis was simulated using HYSPLIT Concentration Weighted Trajectory (CWT). Our results show PM2.5 concentrations during the wet season were ~40% lower than dry season, with an average concentration of 27.11 μg/m3 and were strongly influenced by monsoonal wind patterns in both seasons. During the west monsoon, pollutant transport was predominantly from the southwest to northeast, whereas during the east monsoon it shifted from the northwest to northeast. The trajectory patterns exhibited no substantial differences across all layers (15, 50, 100, and 200 m), although seasonal atmospheric stability influenced pollutant dispersion. In the wet season, PM2.5 primarily originated from western regions of Jakarta, while in the dry season sources were predominantly from the east, which is consistent with prevailing monsoonal winds. Several monitoring stations also indicated potential contributions from North Jakarta due to curved airflow patterns. These findings highlight the dominant role of monsoonal wind in controlling PM2.5 concentrations and transboundary transport in Jakarta within the lower troposphere.
subject: Articles
  topic: section
subject: air quality
  topic: keywords
subject: emission sources
  topic: keywords
subject: HYSPLIT
  topic: keywords
subject: monsoon
  topic: keywords
subject: wind direction
  topic: keywords
creator: Sifa Istiqomah
creator: I Putu Santikayasa
creator: Ana Turyanti
rights: Copyright (c) 2025 Sifa Istiqomah, I Putu Santikayasa, Ana Turyanti https://creativecommons.org/licenses/by-nc/4.0
date: 2025-12-30
publication date: 2025-12-30
starting page: 107
ending page: 119
doi: 10.29244/j.agromet.39.2.107-119

Spatiotemporal Patterns of Meteorological Drought in the National Food Barn Region: A Case Study of South Sulawesi Province
type: item
description: Hydrometeorological disasters, particularly droughts, pose a significant threat to food crop productivity. South Sulawesi, one of Indonesia’s major rice-producing regions outside Java, is highly vulnerable to drought impacts. This study analyzes the spatiotemporal patterns of meteorological drought in South Sulawesi during 1981–2020 using the Standardized Precipitation Index (SPI) and applies run theory to characterize drought events. Monthly rainfall data were obtained from the Climate Hazards Center InfraRed Precipitation (CHIRP) dataset and complemented with ground-based observations from the BMKG rainfall observation network. Principal Component Analysis (PCA) with varimax rotation was employed to identify dominant spatial patterns of meteorological drought variability. The results identify three principal regions explaining more than 65% of the total variance: Region 1 (R1; 56%) in northern South Sulawesi, Region 2 (R2; 10%) in the central to eastern areas, and Region 3 (R3; 10%) in the western region. R1 exhibits the highest drought frequency and intensity but relatively short durations, whereas R3 shows the lowest frequency but the longest durations and largest magnitudes. A positive correlation between drought duration and magnitude is observed across all regions, along with a significant drying trend in the southern part of R2. Overall, these findings provide important insights into the spatial and temporal variability of meteorological drought in South Sulawesi and offer a scientific basis for strengthening drought risk management and regional food security strategies.
subject: Articles
  topic: section
subject: drought
  topic: keywords
subject: principal component analysis
  topic: keywords
subject: regionalization
  topic: keywords
subject: standardized precipitation index
  topic: keywords
subject: trend
  topic: keywords
creator: Nastiti Andini
creator: I Putu Santikayasa
creator: Amsari Mudzakir Setiawan
rights: Copyright (c) 2025 Nastiti Andini, I Putu Santikayasa, Amsari Mudzakir Setiawan https://creativecommons.org/licenses/by-nc/4.0
date: 2025-12-31
publication date: 2025-12-31
starting page: 120
ending page: 130
doi: 10.29244/j.agromet.39.2.121-130

Bias Correction of CMIP6 Models for Assessment of Wet and Dry Conditions Over Sumatra
type: item
description: The performance of CMIP6 models in capturing local and regional precipitation patterns often requires refinement due to inherent biases. This study evaluates eleven CMIP6 models for their applicability over Sumatra Island and applies two bias correction methods namely Linear Scaling (LS) and Quantile Delta Mapping (QDM). We used ERA5 precipitation datasets as a reference bias correction during 1981-2014. The performance was assessed using MAE, correlation, and PBIAS. Results reveals that raw model of CMIP6 generally underestimate precipitation, particularly during the DJF and SON seasons, with the largest errors over the mountainous western Sumatra. LS tends to overcorrect and shift precipitation estimates toward a wetter bias, while QDM significantly improves the accuracy and seasonal consistency of the simulations. The multi-model ensemble mean (CMIP6-avg) outperforms individual models, and its performance is further enhanced with QDM, yielding higher correlation and lower error metrics. Spatial and seasonal analyses demonstrate that QDM more effectively reduces both dry and wet biases, especially during peak rainfall seasons. These findings underscore the importance of robust bias correction techniques to improve climate projections for hydrological and climate impact studies in Sumatra and other tropical regions with complex terrain.
subject: Articles
  topic: section
subject: linear scaling
  topic: keywords
subject: model evaluation
  topic: keywords
subject: precipitation
  topic: keywords
subject: topography
  topic: keywords
subject: quantile delta mapping
  topic: keywords
creator: Rahmat Hidayat
creator: Muh Taufik
rights: Copyright (c) 2025 Rahmat Hidayat, Muh Taufik
date: 2025-06-05
publication date: 2025-06-05
starting page: 33
ending page: 39
doi: 10.29244/j.agromet.39.1.33-39

Assessing the Influence of Climate Services and Climate Change Adaptation Strategies on Smallholder Agriculture: A Systematic Literature Review
type: item
description: Climate services and climate change adaptation practices are increasingly recognized as essential for supporting smallholder farmers. Despite numerous studies on climate impacts and adaptation strategies, limited systematic evidence exists on how climate services and adaptation interventions influence farming practices across regions. This study addresses the gap through a systematic literature review of Scopus-indexed publications over the past decade. Using the PRISMA approach, 1981 articles were screened, with 31 meeting the eligibility criteria. Of these, 23 focused on adaptation interventions and 8 on climate services. Geographically, 30 studies were concentrated in tropical regions Africa (n =16) and in Asia (n=14), while one study was outside the tropics. Findings show that climate information strongly supports the adoption of adaptation strategies (>60%), especially in technological interventions such as Climate-Smart Agriculture, ecosystem management, irrigation, and climate risk reduction. In terms of service delivery, basic climate service provision demonstrated greater effectiveness (80%) compared to advisory-based agricultural services (40%). Socio-demographic factors, particularly education and age, consistently influenced farmers’ decision-making in adopting both climate services and adaptation practices. Overall, this review highlights the need for more integrated approaches that explicitly connect climate services with adaptation interventions. Strengthening these linkages is especially critical in tropical regions, where smallholder farmers remain highly vulnerable to climate variability and long-term climate change risks.
subject: Articles
  topic: section
subject: climate risk
  topic: keywords
subject: decision making
  topic: keywords
subject: intervention model
  topic: keywords
subject: PRISMA
  topic: keywords
subject: socio-demography
  topic: keywords
creator: Marjuki Marjuki
creator: Yonny Koesmaryono
creator: I Putu Santikayasa
creator: Ardhasena Sopaheluwakan
rights: Copyright (c) 2025 Marjuki Marjuki, Yonny Koesmaryono, I Putu Santikayasa, Ardhasena Sopaheluwakan https://creativecommons.org/licenses/by-nc/4.0
date: 2025-09-01
publication date: 2025-09-01
starting page: 75
ending page: 85
doi: 10.29244/j.agromet.39.2.75-85

Water Use Efficiency in Pineapple Plants Fertilization Based on Water Balance Analysis
type: item
description: Most fertilization in pineapple cultivation occurs through foliar application, which involves dissolving fertilizers in water and spraying them on the pineapple plants. The provision of irrigated water to plants refers to water balance analysis, which corresponds to the available water supply. The research aims to determine the effect of various foliar volumes on the growth and production of pineapple plants. The research was carried out in April 2022 - July 2023 at PT. Great Giant Pineapple Lampung using a Completely Randomized Block Design (CRBD). We applied four treatments of foliar water, which comprised of 1500 l/ha, 2000 l/ha, 3000 l/ha (as control), and based on water balance analysis. The treatment has three replication each. The results showed there was not significant different of growth and yield between treatments of water balance approach and the 3000 l/ha foliar water volume (control), in which both have reduced water usage by 22% for one cycle of pineapple cultivation. The findings provide a more efficient water manage-ment strategy for foliar fertilization, reducing water usage without affecting plant performance, and supporting sustainable agricultural practices in pineapple cultivation. Further, the findings can serve as a reference for optimizing irrigation scheduling and input costs in large-scale plantations.
subject: Articles
  topic: section
subject: efficiency plant growth
  topic: keywords
subject: foliar
  topic: keywords
subject: irrigation
  topic: keywords
subject: water volume effect
  topic: keywords
creator: Nungki Kusuma Astuti
creator: Rinaldi Nur Rahman Putra
creator: Yuni Arda Br Saragih
rights: Copyright (c) 2025 Nungki Kusuma Astuti, Rinaldi Nur Rahman Putra, Yuni Arda Br Saragih https://creativecommons.org/licenses/by-nc/4.0
date: 2025-11-08
publication date: 2025-11-08
starting page: 67
ending page: 74
doi: 10.29244/j.agromet.39.2.67-74

ECMWF SEAS5 Seasonal Rainfall Assessment: A Study Case in Papua
type: item
description: Papua, Indonesia’s easternmost island, is prone to seasonal hydrometeorological disasters, necessitating high-quality climate forecasts for effective risk management. This study evaluates the performance of the European Centre for Medium-Range Weather Forecasts (ECMWF) Seasonal Forecast System 5 (SEAS5) in predicting seasonal (3-monthly) rainfall across Papua from 1982 to 2016, using the blended Climate Hazards group InfraRed Precipitation with in-situ rainfall data (CHIRP+Pos) as the observational reference. SEAS5 forecasts at 1 to 3 month lead times were assessed across seasons which defined as July-August-September (JAS), August-September-October (ASO), September-October-November (SON), and December-January-February (DJF), and El Niño-Southern Oscillation (ENSO) phases (El Niño, La Niña, Neutral), using Pearson correlation coefficient (Corr), root mean square error (RMSE), and Kling-Gupta Efficiency (KGE) metrics. Results show stronger SEAS5 skill in JAS–SON (Corr up to 0.939) compared to DJF-JFM (Corr as low as -0.208), with a robust ENSO-rainfall relationship in JJA-SON. SEAS5 performed best during El Niño, particularly in lowlands and exhibited greater variability skill during La Niña and Neutral phases. Benchmarking against a linear regression baseline showed SEAS5’s superior Corr in 76.2% of grids but higher RMSE in 60.6%. Despite limitations in mountainous regions and at longer lead times, SEAS5 offers reliable forecasts for lowland areas during JAS-SON under El Niño, supporting operational applications like drought preparedness and agricultural planning in the regions.
subject: Articles
  topic: section
subject: climate extreme
  topic: keywords
subject: ENSO
  topic: keywords
subject: model evaluation
  topic: keywords
subject: topography
  topic: keywords
subject: seasonal prediction
  topic: keywords
creator: Steven Andika
creator: I Putu Santikayasa
creator: Permana Donaldi Sukma
rights: Copyright (c) 2025 Steven Andika, I Putu Santikayasa, Permana Donaldi Sukma https://creativecommons.org/licenses/by-nc/4.0
date: 2025-12-10
publication date: 2025-12-10
starting page: 95
ending page: 106
doi: 10.29244/j.agromet.39.2.%p

Flood Management Strategy Based on Analysis of Regional Characteristics and Causal Factors in Kendari City
type: item
description: Flooding is a disaster that causes environmental damage, economic losses, and social problem. Kendari City is one of the Indonesian cities that frequently experiences floods due to various factors, including high rainfall, land use changes, poor drainage conditions, and improper spatial management. This study aims to (1) assess the factors contributing to flooding, (2) analyze government governance and community participation in flood management, and (3) formulate an integrated flood management strategy. The methods used were descriptive analysis, spatial approach, SWOT analysis, and Quantitative Strategic Planning Matrix (QSPM). The results showed that there is evidence of land use changes between 2013 – 2023 based on spatial image analysis. We found there were three sub-districts, which is categorized on high flood vulnerability namely Baruga, Kadia, and Kambu sub-districts. Based on the level of community preparedness parameters including knowledge and attitudes, emergency plans, early warning, and resource mobilization, Baruga belongs to the medium category (74.60%), while Kambu (57.42%) and Kadia (59.58%) were in low category. QSPM analysis recommends two priority strategies to reduce flood vulnerability namely accelerating drainage system improvements and replicating the Baruga model in other areas. Future research should focus on climate change-induced flood modeling, gender-sensitive vulnerability assessments, and economic loss estimation to enhance the effectiveness of flood management strategies.
subject: Articles
  topic: section
subject: community readiness
  topic: keywords
subject: flood management
  topic: keywords
subject: flood-prone areas
  topic: keywords
subject: QSPM
  topic: keywords
subject: SWOT
  topic: keywords
creator: Wandira Agus Sakawuna
creator: Budi Indra Setiawan
creator: Perdinan
rights: Copyright (c) 2025 wandira agus sakawuna, Budi Indra Setiawan, Perdinan
date: 2025-06-26
publication date: 2025-06-26
starting page: 56
ending page: 66
doi: 10.29244/j.agromet.39.1.56-66

Climate Change Impact On Rice Productivity Using FAO AquaCrop Model: A Case Study in Lampung
type: item
description: Climate change impacts global food productions, but its local effect on rice production, particularly on monsoon dominated regions remain less understood. Here, we assess climate change impact on rice production situated on Lampung Province, as one of the largest rice productions in Indonesia. The FAO AquaCrop model was used to predict rice productivity, incorporating climate projections from the CMIP5 model under medium (RCP 4.5) and high (RCP 8.5) emission scenarios. We simulated the model for fifteen locations representing districts in Lampung Province. Our results show that by 2050, the decreased rainfall is projected during the dry season and early rainy season, but the average monthly temperatures and evapotranspiration rates are expected to increase across all districts. AquaCrop simulated an increased rice productivity by +0.25 and +0.74 tons/ha for both scenarios in April planting season, but it decreased by -0.41 and -0.75 tons/ha in November planting season due to water stress. This research is important to provide a deeper understanding of the impact of climate change on rice productivity in Lampung Province. These findings highlight the need for adaptive strategies to sustain rice production under future climate conditions.
subject: Articles
  topic: section
subject: adaptation strategies
  topic: keywords
subject: evapotranspiration
  topic: keywords
subject: marksim weather generator
  topic: keywords
subject: RCP 4.5
  topic: keywords
subject: RCP 8.5
  topic: keywords
creator: Rizki Priatama
creator: Tumiar Katarina Manik
creator: Paul Benyamin Timotiwu
creator: Eko Pramono
creator: Alimuddin
rights: Copyright (c) 2025 Rizki Priatama, Tumiar Katarina Manik, Paul Benyamin Timotiwu, Eko Pramono, Alimuddin
date: 2025-06-19
publication date: 2025-06-19
starting page: 48
ending page: 55
doi: 10.29244/j.agromet.39.1.48-55

Assessment of Rice Crop Water Requirements for Planting Season in Moderate Agroclimatic Area of West Sumatra
type: item
description: 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.
subject: Articles
  topic: section
subject: climate variability
  topic: keywords
subject: crop production
  topic: keywords
subject: planting pattern
  topic: keywords
subject: rainfed agriculture
  topic: keywords
subject: water balance
  topic: keywords
creator: Rizky Armei Saputra
creator: Via Yulianti
creator: Hermansah
rights: Copyright (c) 2025 Via Yulianti, Rizky Armei Saputra, Hermansah
date: 2025-06-16
publication date: 2025-06-16
starting page: 40
ending page: 47
doi: 10.29244/j.agromet.39.1.40-47

Land Management of Tidal Swamp Type B with Surjan System as Climate Change Anticipation
type: item
description: Agriculture is one of the most vulnerable sectors to climate change, which can significantly impact national food security. In addition to climate change, agricultural development faces challenges, including the conversion of agricultural land for non-agricultural purposes. As a result, agricultural extensification has expanded into marginal lands, such as tidal swamplands. This paper presents a literature review on the characteristics of tidal swamplands, the principles of the surjan system, and its relevance in addressing climate change, particularly in the context of food security and ecosystem sustainability. Various literature sources were analyzed to assess the advantages, challenges, and sustainable management strategies of tidal swamplands. The review highlights the importance of effective land management to create suitable soil conditions for optimal plant growth and increased productivity. The surjan system, a land management approach practiced by tidal swampland farmers, demonstrates high adaptability in mitigating the impacts of climate change. This system integrates cultural, ecological, and economic perspectives by combining local knowledge with technological advancements. Key components of the surjan system include a one-way water management system with flap-gates and stoplogs, as well as the use of climate-adaptive crop varieties on tidal swamplands.
subject: Articles
  topic: section
subject: adaptive cropping
  topic: keywords
subject: food security
  topic: keywords
subject: resilience
  topic: keywords
subject: sustainable agriculture
  topic: keywords
subject: water management
  topic: keywords
creator: Ani Susilawati
creator: Lutfi Izhar
creator: Achmad Adi Surya Sustama
rights: Copyright (c) 2025 Ani Susilawati, Lutfi Izhar, Achmad Adi Surya Sustama
date: 2025-05-05
publication date: 2025-05-05
starting page: 8
ending page: 20
doi: 10.29244/j.agromet.39.1.8-20

Contribution of Small Rainwater Reservoirs to Performance Off-season Vegetable Farming
type: item
description: Climate Smart Agriculture (CSA) has become essential in ensuring sustainable agricultural production amidst ongoing climate change. This study aims to analyze the impact of small rainwater reservoirs (SRRs) on the performance of off-season vegetable farming in Netpala Village, East Nusa Tenggara, Indonesia. The SRRs, constructed using plastic tarpaulin with storage capacities of 3.6 m³ and 4.3 m³, were applied to support the cultivation of mustard greens, Chinese cabbage, cabbage, carrots, and eggplant during the December 2017 to April 2018 growing season. An on-farm research (OFR) approach was used to assess the effects of SRR implementation compared to traditional water management practices. Key performance indicators include cultivated land area, planting index, crop diversification, and farmer income. Results revealed that SRRs expanded the cultivated area by 21.07%, increased the planting index by 0.52 for mustard greens and 0.64 for cabbage, and boosted farmer income by 29.38%. Income levels were also influenced by factors such as market absorption, commodity prices, and land availability. These findings demonstrate that SRRs can enhance the resilience and productivity of smallholder vegetable farming systems by improving water availability during the rainy or off-season. SRRs offer a practical and scalable solution to address water scarcity and promote sustainable intensification in vulnerable agricultural regions.
subject: Articles
  topic: section
subject: climate smart agriculture
  topic: keywords
subject: irrigation
  topic: keywords
subject: planting index
  topic: keywords
subject: water storage
  topic: keywords
subject: water use efficiency
  topic: keywords
creator: Tony Basuki
creator: Bernard deRosari
creator: Debora Kana Hau
creator: Jacob Nulik
creator: Yiyi Sulaeman
creator: Apolinaris S Geru
rights: Copyright (c) 2025 Tony Basuki, Bernard deRosari, Debora Kana Hau, Jacob Nulik, Yiyi Sulaeman, Apolinaris S Geru
date: 2025-06-03
publication date: 2025-06-03
starting page: 21
ending page: 32
doi: 10.29244/j.agromet.39.1.21-32

The Use of Artificial Neural Networks to Estimate Reference Evapotranspiration
type: item
description: 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.
subject: Articles
  topic: section
subject: agriculture
  topic: keywords
subject: computational models
  topic: keywords
subject: error evaluation
  topic: keywords
subject: Hargreaves method
  topic: keywords
subject: water requirements
  topic: keywords
creator: Abdul Haris
creator: Marimin
creator: Sri Wahjuni
creator: Budi Indra Setiawan
rights: Copyright (c) 2025 Abdul Haris, Marimin, Sri Wahjuni, Budi Indra Setiawan
date: 2025-04-29
publication date: 2025-04-29
starting page: 1
ending page: 7
doi: 10.29244/j.agromet.39.1.1-7

Canopy Microclimate Modification with Reflective Mulches Under Oil Palm and Its Role to Soybean Growth
type: item
description: Land utilization under oil palm plantation is constrained by the condition of low light intensities. Modification of the microclimate through the use of reflective mulch, as a reflector, will increase its ability to reflect the land surface radiation under the tree stand. This modification may suitable for intercropping system between soybean and oil palm. The study aimed to determine the effect of microclimate modification, using reflective mulch, under the stand of oil palm, and to evaluate its effect on soybean productivity. The research was conducted at PTPN-VIII Cimarga Banten using a nested random design with two factors and three replications each. The first factor is the oil palm age, which consists of: (i) control (open land), (ii) 4 years, (iii) 5 years, and (iv) 8 years age of oil palm. The second factor is the reflective mulch, as a solar radiation reflector, which consists of three levels: (i) without mulch (control), (ii) inorganic reflective mulch/silver black plastic mulch, and (iii) organic reflective mulch/dried oil palm leaves. The application of inorganic and organic reflective mulch increased the distribution of reflected land surface radiation (59%-157%), reduced the soil temperature fluctuation (0.30C-1.20C), and maintained soil water content (45.2%-45.8%). An increased of plant growth rates (56%-86%), relative growth rates (16%-21%), and seed weight production per plant (74.8%-86.2%) also reported, as well as the reduction of the etiolation ratio (9.6%-12.5%). The use of organic and inorganic reflective mulches can improve the microclimate and increase the production of soybean under intercopping system with oil palm.
subject: Articles
  topic: section
creator: Taufan Hidayat
creator: Yonny Koesmaryono
creator: Impron Impron
creator: Munif Ghulamahdi
rights: Copyright (c)
date: 2020-03-11
publication date: 2020-03-11
starting page: 1
ending page: 10
doi: 10.29244/j.agromet.34.1.1-10

Effect of Rainfall Intensity on Glyphosate Herbicide Effectiveness in Controlling Ageratum conyzoides, Rottboellia exaltata, and Cyperus rotundus Weeds
type: item
description: Glyphosate is one of herbicide active ingredient which is mostly used to control weeds in crops. However, in rain season herbicide effectiveness decreases as it is washed by rain. This research aimed to study effect of rainfall intensity on the effectiveness of herbicide (Round up 486 SL 2.5 l/ha.) with isopropilamina glyphosate as the active ingredient in controlling specific weeds Ageratum conyzoides, Rottboellia exaltata, and Cyperus rotundus. The experiment was consisted of six treatments and arranged in randomized block design with 8 replications. The treatments were level of rain intensity which were 5 mm/hour, 10 mm/hour, 20 mm/hour, 40 mm/hour, no rain and control (no herbicide no rain). Rainfall intensity was determined by conducting simulation trials prior to the treatments and applied 30 minutes after herbicide applications. The results showed that herbicide effectiveness decreased as the rainfall intensity incresed, even though with longer time the herbicide was still able to control the weeds. The effect of rainfall intensity on herbicide effectiveness was different for different weeds. Up to intensity 40 mm/hour herbicide was capable to control weeds but with level of weeds destruction 20-60%.
subject: Articles
  topic: section
creator: Tumiar Katarina Manik
creator: Dad Resiworo Jekti Sambodo
creator: Dwi Saputra
rights: Copyright (c)
date: 2020-04-14
publication date: 2020-04-14
starting page: 11
ending page: 19
doi: 10.29244/j.agromet.34.1.11-19

Implementation of Bayesian Model Averaging Method to Calibrate Monthly Rainfall Ensemble Prediction over Java Island
type: item
description: Bayesian Model Averaging (BMA) is a statistical post-processing method for producing probabilistic forecasts from an ensemble prediction in the form of predictive Probability Density Function (PDF). BMA is commonly used to calibrate Ensemble Prediction System (EPS) in a shorter-range forecast. Here, we applied the BMA for a longer forecast at a seasonal interval. This study aimed to develop the implementation of the BMA method to calibrate the seasonal forecast (long range) of monthly rainfall from the RAW output of the EPS European Center for Medium-Range Weather Forecasts (ECMWF) system 4 model (ECS4). This model was calibrated with observational data from 26 stations over Java Island in 1981-2018. BMA predictive PDF was generated with a gamma distribution, which was obtained based on two training schemes, namely sequential (BMA-JTS) and conditional (BMA-JTC) training windows. Generally, both of BMA-JTS and BMA-JTC were able to produce better distribution characteristics of ensemble prediction than that of RAW model ECS4. Both BMA methods showed a good performance as indicated by a high accuracy, small bias, and small uncertainty to the observed rainfall. Our findings revealed that BMA-JTC was able to improve the quality of probabilistic forecasts of below and above normal events. The improvement was shown in most stations over Java Island, in which the model was a good skill forecast based on Brier Skill Score (BSS).
subject: Articles
  topic: section
creator: Robi Muharsyah
creator: Tri Wahyu Hadi
creator: Sapto Wahyu Indratno
rights: Copyright (c)
date: 2020-04-20
publication date: 2020-04-20
starting page: 20
ending page: 33
doi: 10.29244/j.agromet.34.1.20-33

The Impact of El Niño and La Nina on Fluctuation of Rice Production in Banten Province
type: item
description: Rice production in Indonesia is facing serious problem, in which the production is fluctuated causing the unstability in the food supply. One factor influencing the rice productions is climate extreme. Here, we analysed rice production in Banten Province for 2002-2015. The objective of this reasearh was to analyse the effect of climate variability on the fluctuation of rice production in Banten. We relied on data from BPS Banten, which provided timeseries of rice production for 2002-2015. We used four statistical approaches namely linear, quadratic, exponential, and moving average models to detect trend in rice production. Our results showed that Rice Production fluctuated every year indicating an increased trend for the observartion period. Based on the trend analysis, the growth rate for rice production was 1,66% per year. Climate extreme has affected on rice production, with El Niño resulted in the decreasing on rice production, whereas La Nina caused an increased of rice production. Further, to adapt climate extreme events, the government needs to encourage farmers to join the Rice Farming Insurance (AUTP) program to protect rice farming from economic losses due to the climate extreme impacts.
subject: Articles
  topic: section
creator: Tian Mulyaqin
rights: Copyright (c)
date: 2020-05-18
publication date: 2020-05-18
starting page: 34
ending page: 41
doi: 10.29244/j.agromet.34.1.34-41

Dynamics Modeling of CO2 in Oil Palm
type: item
description: Oil palm plantation has a high potency to absorb carbon. Limited observed data and expensive instrumentations to measure the absorbed carbon have caused an inaccurate estimation of carbon storage from oil palm. The objectives of this research were to develop a CO2 absorption model, and to calculate the carbon cycle based on climate factors and plant age. CO2 absorption was derived from gross primary production (GPP) and net primary production (NPP), which were ​​based on solar radiation. From NPP we derived net ecosystem exchange (NEE) by calculating the difference between NPP and soil respiration. Our results showed that age of oil palm has influenced the CO2 absorption from 9.8 (1 year) to 117 tons ha-1 year-1 (19 years), with average of 86.5 tons ha-1 year-1 (over 25-year life cycle). We validated our NPP model with biomass that indicated a very good performance of the model with R2 0.95 and RMSE 1.81. Meanwhile, the performance of NEE model was slightly lower (R2 0.71 and 0.72, for wet and dry conditions), but the model had a similar pattern with the measured NEE. Based on the model performance, the findings imply that the model is useful to estimate CO2 absorption, where there is no eddy covariance measurement. This research suggests that carbon modeling will contribute to global terrestrial carbon modeling.
subject: Articles
  topic: section
creator: Meriana Ina Kii
creator: Tania June
creator: I Putu Santikayasa
rights: Copyright (c)
date: 2020-06-05
publication date: 2020-06-05
starting page: 42
ending page: 54
doi: 10.29244/j.agromet.34.1.42-54

Modeling of Heavy Rainfall Triggering Landslide Using WRF Model
type: item
description: This study revealed the behavior of heavy rainfall before landslide event based on the Weather Research Forecasting (WRF) model. Simulations were carried out to capture the heavy rainfall patterns on 27 November 2018 in Kulonprogo, Yogyakarta. The modeling was performed with three different planetary boundary layer schemes, namely: Yonsei University (YSU), Sin-Hong (SH) and Bougeault and Lacarrere (BL). Our results indicated that the variation of rainfall distribution were small among schemes. The finding revealed that the model was able to capture the radar’s rainfall pattern. Based on statistical metric, WRF-YSU scheme was the best outperforming to predict a temporal pattern. Further, the study showed a pattern of rainfall development coming from the southern coastal of Java before 13:00 LT (Local Time=WIB=UTC+7) and continued to inland after 13:00 LT. During these periods, the new clouds were developed. Based on our analysis, the cloud formation that generated rainfall started at 10:00 LT, and hit a peak at 13:00 LT. A starting time of cloud generating rainfall may be an early indicator of landslide.
subject: Articles
  topic: section
subject: Heavy Rainfall
  topic: keywords
subject: Kulonprogo
  topic: keywords
subject: Landslide
  topic: keywords
subject: Planetary Boundary Layer
  topic: keywords
subject: Weather Research Forecasting (WRF)
  topic: keywords
creator: Danang Eko Nuryanto
creator: Yuaning Fajariana
creator: Radyan Putra Pradana
creator: Rian Anggraeni
creator: Imelda Ummiyatul Badri
creator: Ardhasena Sopaheluwakan
rights: Copyright (c)
date: 2020-06-09
publication date: 2020-06-09
starting page: 55
ending page: 65
doi: 10.29244/j.agromet.34.1.55-65

Rainfall and Temperature Change Analysis and their Correlation on Maize Productionin Karawang, West Java
type: item
description: 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.
subject: Articles
  topic: section
subject: correlation
  topic: keywords
subject: climograph shift
  topic: keywords
subject: dryland
  topic: keywords
subject: productivity
  topic: keywords
subject: rainfall variability
  topic: keywords
subject: trend
  topic: keywords
creator: Ruminta
creator: Wicaksono Fiky Yulianto
creator: Napitupulu Grace Ananda
rights: Copyright (c) 2024 Ruminta Roem, Wicaksono Fiky Yulianto, Napitupulu Grace Ananda
date: 2024-12-31
publication date: 2024-12-31
starting page: 88
ending page: 96
doi: 10.29244/j.agromet.38.2.88-96

ENSO and IOD Influence on Extreme Rainfall in Indonesia: Historical and Future Analysis
type: item
description: 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.
subject: Articles
  topic: section
subject: climate projection
  topic: keywords
subject: linear regression
  topic: keywords
subject: maritime continent
  topic: keywords
subject: teleconnection
  topic: keywords
subject: variability
  topic: keywords
creator: Risyda Hanifa
creator: Joko Wiratmo
rights: Copyright (c) 2024 Risyda Hanifa, Joko Wiratmo
date: 2024-12-16
publication date: 2024-12-16
starting page: 78
ending page: 87
doi: 10.29244/j.agromet.38.2.78-87

Identification of Peatland Burned Area based on Multiple Spectral Indices and Adaptive Thresholding in Central Kalimantan
type: item
description: 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.
subject: Articles
  topic: section
subject: Accuracy
  topic: keywords
subject: Fire Frequency
  topic: keywords
subject: Normalized Burn Ratio
  topic: keywords
subject: Normalized Difference Vegetation Index
  topic: keywords
subject: Peat Fire
  topic: keywords
creator: Hilda Ayu Pratikasiwi
creator: Muh. Taufik
creator: I Putu Santikayasa
creator: Dede Dirgahayu Domiri
rights: Copyright (c) 2024 Hilda Ayu Pratikasiwi, Muh. Taufik, I Putu Santikayasa, Dede Dirgahayu Domiri
date: 2024-10-03
publication date: 2024-10-03
starting page: 68
ending page: 77
doi: 10.29244/j.agromet.38.2.68-77

Extreme Rainfall Analysis in the Bengawan Solo Watershed, Java
type: item
description: 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.
subject: Articles
  topic: section
subject: climate index
  topic: keywords
subject: generalized extreme value
  topic: keywords
subject: hydrometeorological hazards
  topic: keywords
subject: return period
  topic: keywords
subject: watershed management
  topic: keywords
creator: Perdinan
creator: Indri Hapsari
creator: Amsari Mudzakir Setiawan
rights: Copyright (c) 2024 Indri Hapsari, Perdinan, Amsari Mudzakir Setiawan
date: 2024-06-20
publication date: 2024-06-20
starting page: 36
ending page: 48
doi: 10.29244/j.agromet.38.1.36-48

Correlation between Climate Data and Yields of Some Prominent Food Crops in Manokwari, West Papua, Indonesia
type: item
description: Environmental factors, particularly climate conditions, play a crucial role in influencing the growth and yield of cultivated crops. Although knowledge on their influence has been revealed in many records, our understanding of their relationship in West Papua is limited due to lack of data. This research leveraged data of monthly climate variables (temperature, rainfall, and radiation intensity) and crop yields from West Papua, Indonesia for period 2011-2020. The Analysis revealed varying trends in the highest average monthly air temperature, humidity, rainfall, and radiation intensity across different months. Despite these fluctuations, there was a general tendency towards increased harvested area and rice, maize, and soybeans production. While the overall impact of climate variables on crop productivity appeared insignificant, certain nuances emerge. Specifically, air humidity demonstrated a notable influence on rice productivity, while air temperature has a stronger effect on maize productivity than other climate variables. However, correlation tests indicated that the relationship between climate variables (air temperature, humidity, rainfall, and radiation intensity) and crop productivity, particularly maize, rice, and soybeans, did not reach statistical significance. This underscores the complexity of the interplay between climate dynamics and agricultural outcomes.
subject: Articles
  topic: section
subject: correlation
  topic: keywords
subject: decadal
  topic: keywords
subject: food sources
  topic: keywords
subject: weather variability
  topic: keywords
subject: sustainable yield
  topic: keywords
creator: Siska Syaranamual
creator: Yaved Muyan
rights: Copyright (c) 2024 Siska Syaranamual, Yaved Muyan
date: 2024-06-28
publication date: 2024-06-28
starting page: 58
ending page: 67
doi: 10.29244/j.agromet.38.1.58-67

A Preliminary Study on the Parameter Configuration of Weather Research Forecasting in Tropical Peatland, Central Kalimantan
type: item
description: 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.
subject: Articles
  topic: section
subject: parameterization
  topic: keywords
subject: rainfall
  topic: keywords
subject: soil moisture
  topic: keywords
subject: spatial distribution
  topic: keywords
subject: temperature
  topic: keywords
creator: Muh. Taufik
creator: Mudrik Haikal
rights: Copyright (c) 2024 Muh. Taufik, Mudrik Haikal
date: 2024-06-24
publication date: 2024-06-24
starting page: 49
ending page: 57
doi: 10.29244/j.agromet.38.1.49-57

A Comparison of the Performance of the Weighted Ensembles Means in CORDEX-SEA Precipitation Simulations
type: item
description: 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.
subject: Articles
  topic: section
subject: climate models
  topic: keywords
subject: model skill score
  topic: keywords
subject: performance evaluation
  topic: keywords
subject: statistical-based metrics
  topic: keywords
subject: weighting factors
  topic: keywords
creator: Tugiyo Aminoto
creator: Akhmad Faqih
creator: Perdinan
creator: Yonny Koesmaryono
creator: Bambang Dwi Dasanto
rights: Copyright (c) 2024 Tugiyo Aminoto, Akhmad Faqih, Perdinan, Yonny Koesmaryono, Bambang Dwi Dasanto
date: 2024-03-19
publication date: 2024-03-19
starting page: 19
ending page: 35
doi: 10.29244/j.agromet.38.1.19-35

Climate Influences on Latex Yield in South Sumatra, Indonesia
type: item
description: 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.
subject: Articles
  topic: section
subject: dry season
  topic: keywords
subject: evapotranspiration
  topic: keywords
subject: IRR118 clone
  topic: keywords
subject: rubber
  topic: keywords
subject: soil moisture content
  topic: keywords
creator: Sahuri
rights: Copyright (c) 2024 Sahuri Sahuri
date: 2024-02-05
publication date: 2024-02-05
starting page: 13
ending page: 18
doi: 10.29244/j.agromet.38.1.13-18

Propagation Characteristics of Madden Julian Oscillation in the Indonesian Maritime Continent: Case Studies for 2020-2022
type: item
description: 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.
subject: Articles
  topic: section
subject: Madden Julian Oscillation
  topic: keywords
subject: Indonesian Maritime Continent
  topic: keywords
subject: propagation characteristics
  topic: keywords
subject: weather phenomena
  topic: keywords
subject: sea surface temperature
  topic: keywords
creator: Fadhilatul Istiqomah
creator: Erma Yulihastin
creator: Joko Wiratmo
creator: Eddy Hermawan
creator: Nurjanna Joko Trilaksono
creator: Dasapta Erwin Irawan
creator: Kristy Natasha Yohanes
creator: Amalia Qurrotu Ayunina
rights: Copyright (c) 2024 Fadhilatul Istiqomah, Erma Yulihastin, Joko Wiratmo, Eddy Hermawan, Nurjanna Joko Trilaksono, Dasapta Erwin Irawan, Kristy Natasha Yohanes, Amalia Qurrotu Ayunina
date: 2024-02-02
publication date: 2024-02-02
starting page: 1
ending page: 12
doi: 10.29244/j.agromet.38.1.1-12

Analysis of Carbon Dioxide Emission from Forest Fires based on Fire Radiative Power in Riau
type: item
description: Riau is one of the susceptible regions in Indonesia, which faces frequent land and forest fires. Fires occur in various land covers and soil types, both peat and mineral soils, which emitted huge carbon to the atmosphere. Forest fires emit greenhouse gases, including carbon dioxide (CO2). The objective of the research was to quantify CO2 from land and forest fires. The quantification emission was for 2016 – 2018 based on the fire radiant power (FRP) dataset along with the buffer methodology for assessing fire-affected land extents across different land covers. The FRP dataset we used to be only at a confidence level of 70% or higher, which represents hotspots. The results revealed large numbers of FRP focal points (> 1000) that can be identified as fires for 2016 and 2018, whereas only small numbers (121) were identified for 2017. Then we quantified the area burned of 95,396 Ha in Riau for 2016, which was double to the 2018’s area burned. Further, this burning contributed to CO2 emission equal to 313,456 tCO2 for 2016. Emission in 2017 was a relatively low as not many observed fires detected.
subject: Articles
  topic: section
subject: burned area
  topic: keywords
subject: emissions
  topic: keywords
subject: hotspot
  topic: keywords
subject: land cover
  topic: keywords
subject: soil types
  topic: keywords
creator: Mochamad Afif Derma Kusuma
creator: Fithriya Y Rohmawati
creator: Idung Risdiyanto
rights: Copyright (c) 2023 Mochamad Afif Derma Kusuma, Fithriya Y Rohmawati, Idung Risdiyanto
date: 2023-11-15
publication date: 2023-11-15
starting page: 108
ending page: 116
doi: 10.29244/j.agromet.37.2.108-116

Climate influence on Diarrhea Disease in Tropical Regions based on Systematic Literature Review
type: item
description: Diarrhea disease presents a significant public health concern due to its impact on mortality, and research showed that climate plays an important role on diarrhea prevalence. However, effect of climate on diarrhea incidence was inconsistent among climate factors. Here, we investigated this inconsistency thorough systematic literature review. Our review encompassed the formulation of research questions, development of literature search strategies, and the establishment of inclusion/exclusion criteria for systematic data extraction. We carried out an extensive search from peer-review literature databases including Scopus, Pubmed, and Proquest for articles published between January 2000 to March 2023. We found that 74 studies focusing on diarrhea diseases and climate influencing factors met our inclusive criteria. Climate factors that affected diarrhea were rainfall, temperature, humidity, and climate seasonality. Our findings revealed that a positive association between diarrhea and rainfall was consistently observed. Other climate factors (temperature and humidity) indicated a positive correlation as well, although viral diarrhea exhibited a negative correlation with temperature. Further, bacterial and parasitic diarrhea diseases were more prevalent in the rainy season, whereas viral diarrhea occurred more frequently during the dry season with lower temperatures.
subject: Articles
  topic: section
subject: association
  topic: keywords
subject: diarrhea
  topic: keywords
subject: inconsistent
  topic: keywords
subject: rainfall
  topic: keywords
subject: temperature
  topic: keywords
creator: Dela Arinda
creator: Rini Hidayati
creator: Muh. Taufik
rights: Copyright (c) 2023 Dela Arinda, Rini Hidayati, Muh. Taufik
date: 2023-11-10
publication date: 2023-11-10
starting page: 99
ending page: 107
doi: 10.29244/j.agromet.37.2.99-107