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All Journal Agromet IJEMS (Indonesian Journal of Environmental Management and Sustainability) Eksakta : Berkala Ilmiah Bidang MIPA
Resti Salmayenti
Department Of Geophysics And Meteorology, Faculty Of Mathematics And Natural Sciences, IPB University, Dramaga Campus, Bogor, Indonesia 16680
Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Energy Engineering Environmental Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health

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Journal : Agromet

 1 
Rainfall Prediction Using Artificial Neural Network Resti Salmayenti; Rahmat Hidayat; Aris Pramudia
Agromet Vol. 31 No. 1 (2017): JUNE 2017
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1176.878 KB) | DOI: 10.29244/j.agromet.31.1.11-21

Abstract

Artificial neural network (ANN) is widely used for modelling in environmental science including climate, especially in rainfall prediction. Current knowledge has used several predictors consisting of historical rainfall data and El Niño Southern Oscillation (ENSO). However, rainfall variability of Indonesian is not only driven by ENSO, but Indian Ocean Dipole (IOD) could also influence variability of rainfall. Here, we proposed to use Dipole Mode Index (DMI) as index of IOD as complementary for ENSO. We found that rainfall variability in region with a monsoonal pattern has a strong correlation with ENSO and DMI. This strong correlation occurred during June-November, but a weak correlation was found for region with rainfall’s equatorial pattern. Based on statistical criteria, our model has R2 0.59 to 0.82, and RMSE 0.04-0.09 for monsoonal region. This finding revealed that our model is suitable to be applied in monsoonal region. In addition, ANN based model likely shows a low accuracy when it uses for long period prediction.
Land Use Change Impact on Normalized Difference Vegetation Index, Surface Albedo, and Heat Fluxes in Jambi Province: Implications to Rainfall Siti Nadia Nurul Azizah; Tania June; Resti Salmayenti; Ummu Ma'rufah; Yonny Koesmaryono
Agromet Vol. 36 No. 1 (2022): JUNE 2022
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.36.1.51-59

Abstract

Jambi covers various land uses with different characteristics related to biogeophysical cycle. Land use plays an important role in the atmosphere-surface interaction and energy balance partition, which influenced rainfall pattern. Two proxies widely used to differentiate various land uses are albedo and normalized difference vegetation index (NDVI). However, study on albedo and NDVI relationship with rainfall in Jambi is still limited. This study aims to analyze the correlation of NDVI and albedo with rainfall and their distribution in Jambi and Muaro Jambi in 2013 and 2017. The research used Landsat 8 OLI TIRS satellite image data to derived NDVI and albedo, and CHIRPS data for rainfall. A simple linear regression was used to calculate the correlation of NDVI and albedo with rainfall. The results showed that the distribution of albedo for each land use class from the lowest to the highest was forest, plantation, cropland, shrubs, and settlements, respectively. On the contrary, the distribution of NDVI and rainfall is the inverse to albedo. Albedo and NDVI had a strong influence on rainfall through surface energy balance partition. This was indicated by the high R-square between albedo and rainfall (0.99) and between NDVI and rainfall (0.97). Increasing upward latent heat flux from the land surface to atmosphere leads to a rainfall increase. In other words, rainfall may also increase with the decrease in albedo, increase in NDVI, or land use change.
Estimation of Oil Palm Total Carbon Fluxes Using Remote Sensing Artika; Tania June; Resti Salmayenti; Yon Sugiarto; Handoko; Christian Stiegler; Alexander Knohl
Agromet Vol. 37 No. 1 (2023): JUNE 2023
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.37.1.12-20

Abstract

Net primary production (NPP) is one of the approaches used to estimate the amount of carbon sequestration by plants. This research aims to estimate the total carbon flux exchanged from different ages of oil palm using remote sensing. The study site was at the PTPN VI Batang Hari, Jambi, Sumatra, Indonesia. The amount of carbon sequestration by oil palm plantations at PTPN VI Batang Hari, Jambi can be estimated using remote sensing based on the light use efficiency (LUE) model. The results showed that the oil palm age affects the amount of carbon sequestrated. The lowest Net primary production value was found at one year of planting 4.28 gCm-2day-1, and the highest was 9.38 gCm-2day-1 at 20 years of planting. The model LUE output was validated using Eddy covariance data and the results showed a low error and a high accuracy rate with RMSE = 0.05 gCMJ-1, R2 = 92%, and p-value = 0.04. We concluded that the LUE model can be used with high accuracy to estimate the amount of carbon absorption of oil palm when direct measurement is unavailable.
Micrometeorological Method in Determining Plant Capacity to Absorb Pollutant: Oil Palm Case Study Za’immatul Mu’allimah; Tania June; Resti Salmayenti; Yon Sugiarto; Handoko; Christian Stiegler; Alexander Knohl
Agromet Vol. 37 No. 1 (2023): JUNE 2023
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.37.1.44-53

Abstract

The vegetation canopy's height and characteristics directly affect the turbulence that controls the exchange of mass and energy between the vegetation and the surrounding atmosphere. Turbulence also controls the momentum transfer towards the mass-carrying plant canopy and the accompanying atmospheric properties so that vegetation can contribute to pollutant deposition. This study aims to estimate the canopy capacity of oil palms to absorb pollutants based on their momentum transfer, the influence of atmospheric stability dynamics, and rainy and dry periods upon absorbed pollutants from PTPN VI in Jambi province for the period of January to December 2015 used micrometeorological observation data. The results showed that the dry deposition capacity value at the stable, neutral, and unstable atmospheric conditions were 2.06 x 10-3 kg/m2, 3.50 x 10-3 kg/m2, and 4.35 x 10-3 kg/m2, respectively. The stable or unstable conditions affected the momentum transfer through decreasing or increasing turbulence. In stable conditions, the cooling of the atmosphere impacts the turbulence to be restrained. The result also showed that the dry deposition capacity during the dry and rainy periods were 4.5 x 10-3 kg/m2 and 2.9 x 10-3 kg/m2, respectively. Further, atmospheric conditions tended to be unstable during the dry period, while the rainy period tended to be stable. This research showed that the momentum transfer method can estimate gas type pollutants by vegetation.
Co-Authors Aan Aryanti Sandra Alexander Knohl Alexander Knohl Aris Pramudia Artika Christian Stiegler Christian Stiegler Elham Sumarga Fauziah Nur Handoko Handoko Muhammad Sugihartono Putri Alya Mukti Ramadhanti Rahmat Hidayat Siti Nadia Nurul Azizah Tania June Ummu Ma'rufah Yon Sugiarto Yonny Koesmaryono Za’immatul Mu’allimah