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Influence of El Niño 2015/2016 on Climate Variability and Production of Main Crops in Langkat Regency
Full text linkEl Niño Southern Oscillation (ENSO) is a global phenomenon that drives local and regional climate variability. It also affects various sectors in daily life, including agriculture. Influence of El Niño is well documented in literatures and generally it gives detrimental effects on agriculture. But, our understanding on local impact to main crops in Langkat Regency, North Sumatra is limited. This study explored the influence of the 2015/16 El Niño in Langkat Regency particularly on local climate variability, and production of on rice, corn, and soybean. We used daily climate data for 1981-2016 combined with agricultural production for 2010-2016. The onset of rainy season was determined using climate data, and we divided the analysis based on the seasonal zone (ZOM). Then we statistically compared agricultural production of each main crops (rice, corn, soybean) annually to the annual mean production for 2010-2016. The results showed that El Niño shorten a wet season in 2015/16 for all ZOMs, with a decreased rainfall between 7% to 30% compared to the normal year. In contrast, agricultural production had risen for 6%-16% due to human interventions during El Niño period. The interventions were comprised of two activities: the use of climate information for agricultural management and expansion of planting area. The findings suggested that climate information will be benefit to society when it is properly used
Validasi Waktu Tanam dan Pupuk Berdasarkan Kalender Tanam Banyudono Kabupaten Boyolali
Full text linkTeknologi informasi tentang waktu tanam dan dosis pupuk merupakan hal yang baru bagi pengguna teknologi pertanian (penyuluh lapang dan petani). Salah satu manfaat yang telah dirasakan oleh pengguna dengan adanya KATAM terpadu adalah menjadi dasar ajuan untuk kebutuhan benih dan pupuk. Kegiatan validasi KATAM terpadu dilaksanakan di Desa Bangak Kecamatan Banyudono Kabupaten Boyolali dengan luasan sekitar 6100 m2. Waktu tanam yang direkomendasikan KATAM terpadu adalah April II - III atau sekitar 11 april sd 30 April 2016. Perlakuan yang diterapkan adalah a. waktu tanam (setelah rekomendasi KATAM terpadu 27 Mei-27 Agustus 2016 dan 14 Juni-14 September 2017) dan dosis pupuk yaitu rekomendasi KATAM terpadu dan dosis petani. Varietas yang ditanam adalah Situ Begendit. Waktu tanam padi di Kecamatan Banyudono tidak serempak dan hanya sekitar 40 % yang sesuai dengan KATAM terpadu (April II-III). . Luasan tanam yang sesuai waktu tanam KATAM sekitar 42 %, sebelum KATAM 42 % dan setelah KATAM 16 %.Pola tanam dalam setahun yang diterapkan oleh responden adalah padi-padi-padi sebanyak 80% dan padi-padi-palawija sebanyak 20%. Penggunaan varietas Situ Bagendit pada musim tanam kedua dan ketiga karena tanaman lebih tahan terhadap kekeringan dan hasil yang tinggi. Rata rata produktivitas padi yang ditanam sesuai KATAM 3.5 ton/ha, yang ditanam sebelum KATAM 3.2 ton/ha dan yang ditanam setelah KATAM sekitar 5.2 ton/ha. Hasil validasi rekomendasi yang bias dterapkan di tingkat petani adalah dosis pupuk dan varietas. Waktu tanam yang direkomendasikan KATAM tidak sesuai dengan produktivitas yang diharapkan petani. Hasil pengamatan di lapang menunjukkan bahwa produktivitas padi yang ditanam setelah waktu tanam KATAM tinggi dengan varietas Situ Bagendit yaitu sekitar 8 ton GKP/ha.Nowadays, information technology on planting calendar and fertilizer dosage remains research challenges, in Indonesia, especially for end user farmers. Integration of the planting calendar (then called as KATAM – ‘Kalender Tanam’), has raised many benefits for users since it provides the basic recommendations for seed and fertilizer needs. This research aims to validate the benefit of using Integrated KATAM as guidance for rice planting and fertilizing in Bangak Village, Banyudono Sub-district, with an area of around 6,100 m2. Two different approaches was performed: (i) interviewing farmers about planting date, variety, growth phase, water resource, and their technology to anticipate climate change, and (ii) calculating the rice productivity under different planting date, planting pattern, fertilizer dosage, and variety. Two treatments were used simultaneously on the field within the same planting calendar based on KATAM. The first treatment was a combination of planting date and fertilizer dosage for Situ Bagendit variety, while the second was two fertilizer dosages applied on two rice varieties (Ciherang and Situ Bagendit). Field activity was held on May-August and June-September 2016. The results found that around 60% of the farmers in Banyudono Sub-district did not applied the integrated KATAM recommendation on planting time. During a year of validation period (2016), 80% of the farmers applied the rice-rice-rice pattern, and the remaining applied rice-rice-palawija. Our findings revealed that most farmers preferred to use Situ Bagendit variety as its higher tolerance to drought and higher potential yield. By applying KATAM recommendation, Situ Bagendit rice variety gave the highest productivity up to 8.89 ton/ha compared to other rice varieties. Further the research highlights the use of KATAM recommendation may increase rice productivity especially when Situ Bagendit is applied
Acute Respiratory Infections (Pneumonia) Incidence Rate in Children due to Climate Variables and Air Quality in Bogor
Full text linkPneumonia is the respiratory infection disease, which is influenced by climatic variables and air quality. However, little is known how rainfall and air humidity influence on the disease situated in a high traffic density such as in Bogor, Indonesia. The research aims to analyze the influences of rainfall, air humidity, and air pollution on the incidence rate of pneumonia under 5-year old children in Bogor. We used statistical approaches namely correlation and principal component analysis and combined with chart analysis to identify the influences. Our results revealed that high rainfall (high relative humidity) improved air quality by lowering the concentration of particulate matter. But, the indoor microorganism growth would increase, therefore it affects the incidence rate of pneumonia under 5-year old children, especially in transition season from wet to dry. In dry season, high concentration of particulate matter in the air would increase the incidence rate of pneumonia. Other findings showed that climate (through humidity) and particulate matters have regulated the pneumonia incidence rate in Bogor. The rate was higher under high humidity. On other hand, in transition from dry to wet season, concentration of particulate matters was more dominant to influence the incident rate
Frost Predictions in Dieng using the Outputs of Subseasonal to Seasonal (S2S) Model
Full text linkDieng 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
Spatial and Temporal Analysis of El Niño Impact on Land and Forest Fire in Kalimantan and Sumatra
Full text linkLand and forest fires in Kalimantan and Sumatra, Indonesia occurred annually at different magnitude and duration. Climate and sea interaction, like El Niño, influences the severity of dry seasons preceding the fires. However, research on the influence of El Niño intensity to fire regime in Kalimantan and Sumatra is limited. Therefore, this study aims to analyze the spatial and temporal patterns of the effects of El Niño intensity on land and forest fires in fire-prone provinces in Indonesia. Here, we applied the empirical orthogonal function analysis based on singular value decomposition to determine the dominant patterns of hotspots and rainfall data that evolve spatially and temporally. For analysis, the study required the following data: fire hotspots, dry-spell, and rainfall for period 2001-2019. This study revealed that El Niño intensity had a different impacts for each province. Generally, El Niño will influence the severity of forest fire events in Indonesia. However, we found that the impact of El Niño intensity varied for Kalimantan, South Sumatra, and Riau Province. Kalimantan was the most sensitive province to the El Niño event. The duration and number of hotspots in Kalimantan increased significantly even in moderate El Niño event. This was different for South Sumatra, where the duration and number of hotspots only increased significantly when a strong El Niño event occurred.Land and forest fires in Kalimantan and Sumatra, Indonesia occurred annually at different magnitude and duration. Climate and sea interaction, like El Niño, influences the severity of dry seasons preceding the fires. However, research on the influence of El Niño intensity to fire regime in Kalimantan and Sumatra is limited. Therefore, this study aims to analyze the spatial and temporal patterns of the effects of El Niño intensity on land and forest fires in fire-prone provinces in Indonesia. Here, we applied the empirical orthogonal function analysis based on singular value decomposition to determine the dominant patterns of hotspots and rainfall data that evolve spatially and temporally. For analysis, the study required the following data: fire hotspots, dry-spell, and rainfall for period 2001-2019. This study revealed that El Niño intensity had a different impacts for each province. Generally, El Niño will influence the severity of forest fire events in Indonesia. However, we found that the impact of El Niño intensity varied for Kalimantan, South Sumatra, and Riau Province. Kalimantan was the most sensitive province to the El Niño event. The duration and number of hotspots in Kalimantan increased significantly even in moderate El Niño event. This was different for South Sumatra, where the duration and number of hotspots only increased significantly when a strong El Niño event occurred
Non-linear Routing Scheme at Grid Cell Level for Large Scale Hydrologic Models: A Review
Full text linkNew tools and concepts in the form of mathematical models, remote sensing and Geographic Information System (GIS), communication and telemetering have been developed for the complex hydrologic systems that permit a different analysis of processes and allow watershed to be considered as an integrated planning and management unit. Hydrological characteristics can be generated through spatial analysis, and ready for input into a distributed hydrologic models to define adequately the hydrological response of a watershed that can be related back to the specific environmental, climatic, and geomorphic conditions. In the present paper, some recent development in hydrologic modeling will be reviewed with recognition of the role of horizontal routing scheme in large scale hydrologic modeling. Among others, these developments indicated the needs of alternative horizontal routing models at grid scale level that can be coupled to land surface parameterization schemes that presently still employed the linear routing model. Non-linear routing scheme will be presented and discussed in this paper as possible extension
The Impact of El Niño and La Nina on Fluctuation of Rice Production in Banten Province
Full text linkRice 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
Influence of Land Use and Rainfall on Carbon Stock Dynamics for Oil Palm and Rubber
Full text linkThe 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
The Potency of the Rice Crop Index Development through Adjustment of Agroclimate and Water Management Situated in Rainfed Field Gunungkidul
Full text linkOne of the strategies to increase the rice self-sufficiency is by improving the rice crop index (IP) in rainfed field areas. This paper aims to obtain the areas for IP development based on agroclimate information on the rainfed fields in Gunungkidul. The methodology of research was based on descriptive analysis, surveys and interviews involving farmers, researchers, agricultural officers, and village officials. We performed field surveys and interviews in 2016 and 2017. The surveys were carried out by identification and verification of the water sources for agriculture, determination of the appropriate water infrastructure, and determination of the areas affected by rice cultivation development. The results showed that the determination of the beginning of planting season could refer the Modern Integrated Planting Calendar (KATAM) and the estimation of the start of the rainy season by the local meteorological office (BMKG). We estimated that as many of 2,111 ha was suitable for IP 200 development, which may raise the potency of rice production to 10,058 tons (increased by 5.10%). On other hand, the IP 300 only covers the rainfed field areas of 687 ha, which has a potential rice production of 3,294 tons (increased by 1.67%). Further identification and verification are needed regarding the potency of water sources. This will determine which types of proper water infrastructure that must be provided for support the development of IP, hence the national rice self-sufficiency
Dynamics Modeling of CO2 in Oil Palm
Full text linkOil 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.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