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Agromet

agromet
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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.

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Articles 289 Documents

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Climate Comfort in Nature-Based Tourism at Tropical Region Nofi Yendri Sudiar; Yonny Koesmaryono; . Perdinan; Hadi Susilo Arifin
Agromet Vol. 33 No. 2 (2019): DECEMBER 2019
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

This research reveals visitor perceptions of climate comfort in nature-based tourism areas in Indonesia. We combined a survey and modeling to calculate the comfort score based on Tourism Climate Index (TCI) and Holiday Climate Index (HCI) in three tourism sites of Ecopark Ancol, Bogor Botanical Garden, and Cibodas Botanical Garden. During the survey, we collected data on climate comfort perceptions and the role of the weather on the comfort. Totally, 793 respondents of tourism visitors participated in the study. Our results showed that almost all of visitors (>95%) stated that the weather affected the climate comfort. Interestingly, the weather condition did not influence on the decisions where the tourism site to visit. The level of perceived climate comfort for the sites were neutral (Ecopark, 57.3%), and comfortable (Bogor Botanical Garden, 60%; Cibodas Botanical Garden, 78.4%). Then by modeling we obtained the best method to calculate the comfort based on the following index: (i) TCI with Physiological Equivalent Temperature (PET) Tianjin for Ecopark (57.2), (ii) HCI for Bogor Botanical Garden (59), and (iii) HCI with PET Tianjin for Cibodas Botanical Garden (77.6). Further, perception on climate comfort was significantly difference among sex, age, and education level of the visitors. In warmer environmental condition, the older people and women feel more comfortable. Our finding revealed that topography was weak correlated with comfort perception. By understanding visitor perceptions, strategies and appropriate actions can be developed to increase comfort in the nature-based tourism industry.

Implementation of Bayesian Model Averaging Method to Calibrate Monthly Rainfall Ensemble Prediction over Java Island Muharsyah, Robi; Hadi, Tri Wahyu; Indratno, Sapto Wahyu
Agromet Vol. 34 No. 1 (2020): JUNE 2020
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

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).

Effect of Rainfall Intensity on Glyphosate Herbicide Effectiveness in Controlling Ageratum conyzoides, Rottboellia exaltata, and Cyperus rotundus Weeds Manik, Tumiar Katarina; Saputra, Dwi; Sambodo, Dad Resiworo Jekti
Agromet Vol. 34 No. 1 (2020): JUNE 2020
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

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%.

Long-term Monthly Discharge Prediction for Cimanuk Watershed Marliana Tri Widyastuti; Muh Taufik
Agromet Vol. 33 No. 2 (2019): DECEMBER 2019
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Although streamflow data is important for water resource planning, it’s long-term availability for Indonesian rivers is limited. One factor could be identified for example lack of observation. Here, we presented observation-based modeling to predict long-term discharge data for Cimanuk watershed in Indonesia. The watershed is categorized as one of the critical watersheds, meanwhile it supports to more than one million people. A well-known hydrological model called Soil and Water Assessment Tools (SWAT) was used to predict monthly discharge. The model was fed with monthly climate data, topography, land use and soil characteristics. We calibrated the model with the observed data from 1974 to 1994 (20 years). Our results showed that the model was a good performance in estimating monthly discharge as indicated by three statistical metrics used. Based on statistical evaluation, the calibration resulted a low percent bias (3.20%), strong correlation (0.73), and high Kling-Gupta Efficiency (0.78). Further, we did a sensitivity analysis for the model, and we found that hydrological response unit was the most influential parameters for the Cimanuk watershed. A long-term discharge data indicated a monsoonal pattern for this watershed.

Canopy Microclimate Modification with Reflective Mulches Under Oil Palm and Its Role to Soybean Growth Hidayat, Taufan; Koesmaryono, Yonny; Impron, Impron; Ghulamahdi, Munif
Agromet Vol. 34 No. 1 (2020): JUNE 2020
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

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.

The Impact of El Niño and La Nina on Fluctuation of Rice Production in Banten Province Mulyaqin, Tian
Agromet Vol. 34 No. 1 (2020): JUNE 2020
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

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.

Modeling of Heavy Rainfall Triggering Landslide Using WRF Model Nuryanto, Danang Eko; Fajariana, Yuaning; Pradana, Radyan Putra; Anggraeni, Rian; Badri, Imelda Ummiyatul; Sopaheluwakan, Ardhasena
Agromet Vol. 34 No. 1 (2020): JUNE 2020
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

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.

Pemodelan Dinamika CO2 Pada Tanaman Kelapa Sawit Kii, Meriana Ina; June, Tania; Santikayasa, I Putu
Agromet Vol. 34 No. 1 (2020): JUNE 2020
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

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.

The Efficiency of Water in Supporting Local Wisdom and Food Sustainability in Subak Sange, Bali Indonesia Ni Made Delly Resiani; I Wayan Sunanjaya
Agromet Vol. 34 No. 2 (2020): DECEMBER 2020
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.34.2.67-74

Subak is local wisdom in Bali that has been practiced for centuries in managing irrigation water. Here we present the uniqueness of Subak to manage water with an example of Subak Sange, Gianyar, Bali. The field activity was carried out from April-September 2019. The research objectives were to analyze: (i) the characteristics of local wisdom in Subak Sange, (ii) the effect of irrigation water frequency on pest and disease outbreaks on tobacco yield, and (iii) the efficiency of water use in chili-tobacco intercropping. We combined several approaches to achieve the objectives, including an interview with farmer, diversity analysis, Romijn method, and revenue cost ratio. The results showed that the harmony of relations between farmers was bound by a belief in three elements socio-agrarian-religious. The excessive irrigation gave more pest and disease outbreaks, as shown in 6-irrigation frequencies. In addition, the occurrence of rotten root outbreaks was the highest (29%). The optimal frequency irrigation for yield of tobacco was 4-times, which produced 11.5 tons of dry chopped tobacco per hectare, and this frequency irrigation was much more efficient water use by 79% than rice plants. Based on revenue cost ratio analysis, the chili-tobacco intercropping with four times irrigation was feasible. The findings indicate that management of irrigation water in Subak Sange is promising to support food sustainability in the region.

Frost Predictions in Dieng using the Outputs of Subseasonal to Seasonal (S2S) Model Erna Nur Aini; Akhmad Faqih
Agromet Vol. 35 No. 1 (2021): JUNE 2021
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.35.1.30-38

Dieng volcanic highland, where located in Wonosobo and Banjarnegara regencies, has a unique frost phenomenon that usually occurs in the dry season (July, August, and September). This phenomenon may attract tourism, but it has caused losses to farmers due to crop damage. Information regarding frost prediction is needed in order to minimize the negative impact of this extreme event. This study evaluates the potential use of the Subseasonal to Seasonal (S2S) forecast dataset for frost prediction, with a focus on two areas where frost usually occurs, i.e. the Arjuna Temple and Sikunir Hill. Daily minimum air temperature data used to predict frost events was from the outputs of the ECMWF model, which is one of the models contributed in the Subseasonal to Seasonal prediction project (S2S). The minimum air temperature observation data from the Banjarnegara station was used in conjunction with the Digital Elevation Model Nasional (DEMNAS) data to generate spatial data based on the lapse rate function. This spatial data was used as a reference to downscale the ECMWF S2S data using the bias correction approach. The results of this study indicated that the bias-corrected data of the ECMWF S2S forecast was able to show the spatial pattern of minimum air temperature from observations, especially during frost events. The S2S prediction represented by the bias-corrected ECMWF model has the potential for providing early warning of frost events in Dieng, with a lead time of more than one month before the event.

Page 23 of 29 | Total Record : 289

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