Influence of Land Use and Rainfall on Carbon Stock Dynamics for Oil Palm and Rubber

The expansion of agricultural commodities including oil palm plantations potentially causes an increase of greenhouse gas emissions by amplifying carbon dioxide (CO2) in the atmosphere. In the long term, this amplification will alter climate change. However, oil palm also has the potency to reduce greenhouse gas emissions by absorbing CO2 through photosynthesis. This study aims to determine the carbon stock that can be absorbed by oil palm and rubber plants, and to determine the relationship of rainfall with carbon stock in oil palm plants. The study used satellite image data based on Landsat and combined with rainfall data from near Perbaungan District, North Sumatra.  Three Landsat data (acquisition date: (i) 12 February 2000, (ii) 8 March 2009, and (iii) 11 August 2019) were processed to estimate carbon stock. The procedure for estimating carbon stock was as follows: determining the sample and digitizing the sampling points, converting the digital value of the numbers into the spectral spectrum, calculating the albedo values, calculating the long-wave and short-wave radiations, computing biomass, and the absorbed carbon stock. The results showed that the carbon stock in oil palm was greater than that of rubber plants as oil palm has a greater biomass. The greater the plant biomass, the bigger the carbon stock absorbed. Further, the findings revealed that rainfall in dry season has a contribution to carbon stock in oil palm and rubber. The higher the total rainfall during dry season will increase the absorbed carbon stocks.The expansion of agricultural commodities including oil palm plantations potentially causes an increase of greenhouse gas emissions by amplifying carbon dioxide (CO2) in the atmosphere. In the long term, this amplification will alter climate change. However, oil palm also has the potency to reduce greenhouse gas emissions by absorbing CO2 through photosynthesis. This study aims to determine the carbon stock that can be absorbed by oil palm and rubber plants, and to determine the relationship of rainfall with carbon stock in oil palm plants. The study used satellite image data based on Landsat and combined with rainfall data from near Perbaungan District, North Sumatra.  Three Landsat data (acquisition date: (i) 12 February 2000, (ii) 8 March 2009, and (iii) 11 August 2019) were processed to estimate carbon stock. The procedure for estimating carbon stock was as follows: determining the sample and digitizing the sampling points, converting the digital value of the numbers into the spectral spectrum, calculating the albedo values, calculating the long-wave and short-wave radiations, computing biomass, and the absorbed carbon stock. The results showed that the carbon stock in oil palm was greater than that of rubber plants as oil palm has a greater biomass. The greater the plant biomass, the bigger the carbon stock absorbed. Further, the findings revealed that rainfall in dry season has a contribution to carbon stock in oil palm and rubber. The higher the total rainfall during dry season will increase the absorbed carbon stocks

Analisis Pola Unsur Meteorologi dan Konsentrasi Polutan di Udara Ambien Studi Kasus : Jakarta dan Bandung (Analysis Of Pattern Of Meteorology Variable And Ambient Polutant Concentration Case Study : Bandung And Jakarta)

Meteorological conditions are the important factors that influence tranformation and tranportation process of the polutant in the atmosphere. The aim of this research is to study correlation between local meteorology condition with ambient polutant concentration. Case study has been done in Jakarta and Bandung. Research method is secondary data analysis by plot meteorology component (radiation, temperature, hummidity and wind velocity) and polutant consentration, to gain fluctuation pattern from both component and than do correlation analysis. Result of the analysis show that the influence of each meteorology component differ to each polutant component and depend on local condition. In Bandung and Jakarta, radiation fluctuation has negative correlation with CO, NO2, Nox and PM10. The most negative correlation in Bandung is wind velocity with CO which has correlation value -0.74, and correlation between humidity and O3 which has value -0.8. While the most positive correlation is correlation between temperature and radiation with O3 which has value 0.7 – 0.8. Humidity has positive correlation with several polutant. In Jakarta, in general, coefisien correlation value both positive and negative correlation less than coefisien correlation in Bandung, except for O3. The influence of amount and kind of emition also contribute to them. The unique matter has been found that meteorology component fluctuation in both Jakarta and Bandung has high correlation positive and negative with O3, up to the value -0.8 to +0.7. The other polutant component has small in both negative and positive cerrelation (±0.5)

The Use of Weather Research and Forecasting Model to Predict Rainfall in Tropical Peatland: 1. Model Parameterization

Rainfall dynamics play a vital role in tropical peatland by providing sufficient water to keep peat moist throughout the year. Therefore, information of rainfall data either historical or forecasting data has risen in recent decades especially for an alert system of fire. Here the Weather and Research Forecasting (WRF) model may act as a tool to provide forecasting weather data. This study aims to do parameterization on WRF parameters for peatland in Sumatra, and to perform bias correction on the WRF’s rainfall output with observed data. We performed stepwise calibration to choose the best five physical schemes of WRF for use in the study area. The output WRF’s rainfall was bias corrected by spatially observed rainfall data for 2019 at day resolution. Our results showed the following schemes namely (i) Eta scheme for cloud microphysical parameters; (ii) GD scheme for cumulus cloud parameters, (iii) MYJ scheme for planetary boundary layer parameters; (iv) RRTM for longwave radiation; and (v) New Goddard schemes for shortwave radiation are best combination for being used to predict rainfall in maritime continent. The spatially interpolated observed rainfall with the Inverse Distance Weighting (IDW) was outperformed for calibration process of WRF’s rainfall as shown by statistical indicators used in this study. Further, the findings have contributed to advance knowledge of rainfall forecasting in maritime continent, particularly in providing data to support the development of fire danger rating system for Indonesian peatland

Identifikasi Lokasi Potensial Panen Air Hujan Menggunakan Indeks Kesesuaian Embung dan Sistem Informasi Geografi di Provinsi Jawa Timur Indonesia: Identification of Locations for Potential Rainwater Harvesting Using the Conformity Index of Embankments and Geographic Information Systems in East Java Province, Indonesia

Increasing population has an impact on increasing  food supply to fulfil the requirement of the community. Increasing in food supply is able to be achieved by increasing the agricultural productive area. Low-water agricultural technology is one of technology can be applied in the development of agricultural areas with sufficient water availability. But on the other hand, water harvesting technology using pond is one approach in the development of agricultural land in dry areas. This study uses a geographic information system (GIS) approach to identify areas that have high potential for the development of water harvesting ponds in  East Java Province, Indonesia. GIS approaches is used for spatial analysis in calculating the area potential index for the ponds deveopment based on climate, physical surface and vegetation indicators. This index is calculated based on indicators, each of which is obtained from the surface parameter data. The results of the study show that the East Java Province is categorized as the "very suitable" and "appropriate" areas on water harvesting ponds suitability by 55% and 23%, respectively. This results show that the potential of the East Java area for developing water harvesting pond is very high about 78% compared with the entire region. On the other hand, locations that is categorized as "not suitable" and "very inappropriate" are about 8.7% and 9.2% compared with total area of ​​East Java Province. Iit can be concluded that climate, physical surface and vegetation indicators are very important  in determining the locations of water harvesting ponds development in East Java Province

The Use of Dam Environmental Vulnerability Index (DEVI) for Assessing Vulnerability of Bengawan Solo Watershed, Indonesia

Bengawan Solo is the longest river in Java, but current conditions show that its watershed is in a critical condition. Deforestation was very intensive in the last three decades that contributed to degradation of the watershed. Other factor contributing to the degradation is dam construction. However, our knowledge on the impact of dam construction on the environment and its vulnerability is poorly understood. Here, we assessed vulnerability of the watershed based on physical properties such as existing dams, morpho-dynamic activities, and deforested area. The study aims to identify the vulnerability of the Bengawan Solo watershed based on dam environmental vulnerability index (DEVI) approach, and to analyse the dominant variable contributing to DEVI. For calculating DEVI, several data were needed including land cover, rainfall, stream water stage, soil type, stream network, and dams. The results showed that Bengawan Solo watershed had moderate to high vulnerability (60%). Moderate level was identified for Madiun and Wonogiri sub-watershed, while high level was in Cepu and Babat sub-watershed. Our findings revealed that morpho-dynamic activities as represented by sediment rate and stream water stage had contributed to the high DEVI value as in Cepu and Babat sub-watershed. Further, influence of dams in this research was not dominant implying that any improvement to the DEVI approach remains research challenges. The improvement of the approach is expected to better identify the impact of dam construction on environment, situated in other regions than Amazon, where it was firstly developed

Analisis Indeks Pencemaran Airtanah di DKI Jakarta dengan Interpolasi Spasial: Analysis of Groundwater Pollution Index in DKI Jakarta using Spatial Interpolation

Everyone needs water to his life and his activity. Groundwater pollution is one of the problems in Indonesia. The increasing number of the show an increase water needs. They were filled with groundwater needs. There has been decreasing groundwater that is occupied in quantity and quality. The research was done in Jakarta, consisting of 42 sub-district. Research takes into account the condition of the dry season. Uses index research quality of groundwater pollution. Monitoring parameter groundwater consisting of physics, chemical and biology paramater. The research consists of determining the pollution index in Jakarta, analysis of groundwater pollution, and predicted entanglement with an index pollution population density. The research uses spatial interpolation to determine locations. Pollution index calculation used calculation storet. The measurement results in the rate used in the analysis index groundwater pollution. The research results obtained index value has increased pollution are on the north and central of Jakarta. The research results obtained East Jakarta having the condition geology that porous. The value of the groundwater pollution index was in north Jakarta. The results of the study indicated by a map pollution index the quality of groundwater during three periods. Index pollution in Jakarta consisting of pollution until the same as the quality standard. Research shows the absence of correlation with the population with the pollution groundwater quality

Water Availability Under Future Climate Change: A Study of Citarum River Basin, Indonesia

This study assessed the impact of climate change on future water availability in the Citarum river basin, Indonesia. Future climate was projected based on the output of HadCM3 GCM under A2 and B2 scenarios and downscaled using SDSM package application. The hydrological processes were modelled using WEAP application. The result suggested an increase of temperature as well as precipitation in the period of the 2020s, 2050s and 2080s. The water availability is projected to increase in the future.

Evaluation of Flood Hazard Potency in Jakarta based on Multi-criteria Analysis

The frequency of flood events in Indonesia has increased since 1990, especially in the capital city of Jakarta. Flood events have affected socio-economic activities, and have threaten community health in flood prone areas. Although many efforts have been performed to reduced flood impacts, research on flood hazard remains a research challenge. This study aims to map level of flood hazard in Jakarta and to determine the most affected factors that cause flood. First, we defined factors that influence flood, and combined an analytical hierarchy process (AHP) to determine their weighted values and GIS approach to determine their score values. The combination of weight and score value determined the flood hazard index (FHI). The sensitivity analysis and validation then were applied to determine the robustness of the approaches. Our results show that the most influenced factors determining flood hazard were rainfall intensity, land use, and slope, whereas geology is the less factor. Based on the sensitivity analysis and FHI validation, our approaches were able to represent 59% flood disaster in Jakarta. The pattern of FHI value was high in north areas and low in south areas. The findings indicated that north areas are more flood prone than south areas. Further, this research contributes to the improved approach of flood mitigation in Jakart

Drought Events in Western Part of Timor Island Indonesia

Drought is a below-averaged condition of water availability, which has detrimental impacts on many sectors. Many studies have been performed on drought analysis in Indonesia, yet knowledge about drought in western Timor is still limited. This research carried out a historical meteorological drought analysis based on a 3-month Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) using global climate data for 1989-2018. The index value was then categorized into three groups: moderate, severe, and extreme. We assessed: (i) the influence of El Niño phenomena to drought events, (ii) drought class frequency, and (iii) drought trend. Based on historical data, western Timor had a monsoonal pattern with dominant dry period, which occurred in April to November. The results showed that the drought events were mostly influenced by El Niño. Seasonally, El Niño not only increased the drought frequency in July-August (JJA) season, but also in other seasons. In El Niño year of 2015, drought covered most parts of study area during September-November (SON) season, especially in the western part. Dry conditions increased in June, reached maximum in September-November, and decreased in December. Other findings show that an extreme drought consistently had a downtrend, while the moderate drought had upward trends. Spatiotemporal drought analysis using SPI and SPEI showed similar patterns, SPEI detected a higher frequency of drought classes compared to SPI. This study suggests that knowledge on drought-related El Niño will benefit on drought mitigation action in the future

Sea Surface Temperature Anomaly Characteristics Affecting Rainfall in Western Java, Indonesia

Western Java is densely populated with high socio-economic activity. Climate-related disasters can be mitigated with the support of an understanding of systems that produce reliable climate predictions. One of the climate variables included in hydrometeorological disasters is rainfall. The characteristics of rainfall in Western Java cannot be separated from the sea surface temperature (SST) around the area. This study compares the relationship between SST and rainfall with singular value decomposition (SVD) and compares it with Pearson's correlation. SVD Model performance was evaluated using square covariance fraction (SCF) and Pearson correlation. The results showed that rainfall has a higher correlation with SST Anomaly (SSTA) by using SVD, with a correlation of about 0.63 in 6 to 9 months without lag time. Rainfall in western Java was closely related to the positive SSTA anomaly in southern Indonesia, especially the waters south of Java Island, and negative anomalies in other areas. Furthermore, atmospheric dynamic analysis showed that the positive coefficient expansion is followed by warmer SST, lower surface air pressure, higher water vapor, and higher rainfall, all were respective to their normal conditions around western Java. This study concludes that warmer SSTA around Western Java causes increased rainfall in western Java than normal and potentially impacts the hydrological disaster in West Java