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Assessment of Livelihood Vulnerability to Climate Change Using Three Index Methods
Full text linkVulnerability assessment based on composite indices such as Livelihood Vulnerability Index (LVI) or Sistem Informasi Data Indeks Kerentanan (SIDIK) is widely used, and it is practically known as the initial step to determine the adaptation policies for climate change. Various vulnerability assessment methods that have been developed including LVI and SIDIK raise the possibility that different methods can lead to different conclusions. This research aimed to assess whether the results of vulnerability analysis using different methods on the same data offer consistent results. Comparative studies on this topic based on the different indexing methods may also provide a beneficial insight for stakeholders. We tested LVI, LVI-IPCC, and SIDIK methods in Tanah Merah and Lobuk villages in Sumenep Regency, East Java. We collected the primary data based on interviews with households in the field. Climate data (monthly rainfall, maximum, and minimum air temperature) with 0.05o spatial resolution from 2001-2020 was obtained from CHIRPS and TerraClimate. Our results showed that both villages were consistently categorized as vulnerable according to LVI, LVI-IPCC, and SIDIK methods. This result is also consistent at village and household levels. The findings showed difference in the key indicators driving the vulnerability in both villages. The key indicators in Tanah Merah Village were households without waste management, training from government, and no early warning system. In contrast, the key indicators driving the vulnerability for Lobuk were households with small land ownership and households with debt. Further, action recommendations for Tanah Merah are providing waste banks and waste sorting facility, upgrading public capacity through workshops, and adopting social media to share climate-related information. For Lobuk, the recommendations are the determination of regulatory instruments related to space utilization in the coastal area, mapping area affected by climate change, and financial literacy improvement especially promoting savings in the community
Evaluation of Flood Hazard Potency in Jakarta based on Multi-criteria Analysis
Full text linkThe 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
Fire Danger on Jambi Peatland Indonesia based on Weather Research and Forecasting Model
Full text linkMonitoring drought related to peat fire danger is becoming essentials due to the adverse impacts of peat fires. However, the current monitoring is mostly based on station data and has not yet covered all parts of peatlands. This research was carried out to initiate a spatial monitoring for peat fire, particularly in Jambi province. Our approach was simple by integrating Weather Research Forecasting (WRF) output with a drought-fire model. This research aims to: (i) calibrate rainfall, air temperature and soil moisture data from WRF output; and (ii) analyze temporal drought related to fire danger. A drought-fire model known as Peat Fire Vulnerability Index was applied with daily inputs of WRF output at 5km resolution, which were comprised of rainfall, air temperature, and soil moisture. The results showed that calibration reduced rainfall magnitude, and slightly increased the maximum air temperature and soil moisture. The calibration performance was good as shown by a very low percent bias (less than ±5%), and lower error (RMSE=16.5; MAE=9.5). Our analysis showed that drought triggered by El Niño in 2015 had escalated extreme fire danger class by 38% compared to normal year (2018). This has been confirmed by a low variation of proportion of extreme class during July-August 2015. The results suggested that integrating spatial global climate data will benefit to the improved drought-fire model by providing spatial data. The results are expected to be a reference on drought and peat fires mitigation action
Drought Events in Western Part of Timor Island Indonesia
Full text linkDrought 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
Potential of Sorghum Varieties as Biofuel
Full text linkThe downside of fossil fuels as non-renewable energy resources in Indonesia has led to invent alternative energy resources. One of alternative sources is biofuels, which are derived from organic compound that originated from plants and living creatures. Here, we used sorghum as a source of biofuels, but current knowledge of sorghum cultivation on dry land is limited. This study aims to determine the influence of sorghum genotypes on their growth and yield in a dry land, and to analyze the potential of sorghum as biofuels. This research was carried out in low land, on vertisol soil, from August to November 2020. We applied a completely randomized block design with one factor and 3 replications. Seven sorghum varieties were identified namely Numbu, Super 1, Suri 3, Keller, Kawali, Black Sorghum, and Bioguma-2. The results showed that each variety had different genetical properties leading to various growth rates in both vegetative and generative phases. Our finding revealed that Keller variety was the most productive sorghum plant as it produced the highest sugar content (20°Brix). Also, Keller was the tallest plants (>300 cm) compared to other varieties. Bioguma-2 was the second, which was proven by its longest stem (307 cm) and high stem sap content (18°Brix). Thus, we recommended the Keller and Bioguma-2 as the suitable sorghum variety to be utilized in biofuels manufacturing
Optimization of Newly Opened Rice Fields on Tidal Swamp Through Superior Rice Varieties in Bulungan District
No full textThe potential of swamps in Indonesia is quite extensive but has not been used optimally to support food availability. In order to take advantage of the large swamp potential, the government has opened a new paddy field on the land. Various obstacles faced in the program of developing new openings, especially land biophysical problems, climate change and social economic problems. The purpose of this study was to determine the region\u27s performance, constraints and efforts to optimize new openings of swamps for the development of agricultural food crops, especially rice. The study was conducted in new openings of tidal swamps in Bulungan District in 2017-2018. The research method is a survey followed by a field assessment. The results showed that in accordance with regional conditions, optimization of new openings in Bulungan can be done through: (1) land management, (2) water management, (3) the use of adaptive superior varieties, (4) amelioration and location-specific fertilization, (5) planting on time and together and in accordance with the planting calendar (KATAM) on swamp.Indonesian swamp has a high potency to provide areas for agricultural expansion, which means to raise food security. To optimize its utilization, government has developed new rice fields in the tidal swamp. This research was carried out in a new rice field from the tidal swamp in Bulungan District. The research aimed to optimize the new rice fields by implementing superior rice varieties (NSV). The study used a randomized block design (RBD) with three replicates. Benefit Cost Ratio (BCR) analysis was performed to determine the feasibility of rice farming in the new field. The NSV consisted of six varieties of rice, namely Inpara-1, Inpara-2, Inpara-3, Inpara-4, Inpara-5, and a local variety. The planting pattern implemented was jajar legowo (jarwo) 2:1, and seedlings were planted three stems per clump at the age of 20-25 days. Each planting treatment was given the same dose of limestone and fertilizer, namely dolomite 1,000 kg ha-1, NPK fertilizer 250 kg ha-1, and Urea 100 kg ha-1. The results showed that all varieties were able to adapt tidal swamp condition, and Inpara varieties productivity was higher than that of local variety. The productivity of superior varieties rice in a newly opened rice reached 2.6–5.75 tons milled dry grain ha-1. The findings also revealed that superior rice varieties have BCR>1, while the local variety had BCR<1. The productivity of Inpara-1 and Inpara-2 was the highest compared to other varieties and was also feasible to be cultivated on newly opened rice fields in Bulungan District
Adaptive Garlic Farming to Climate Change and Variability in Lombok
Full text linkClimate change impact in Indonesia is generally characterized by changes in daily temperature, rainfall patterns, and sea level rise. These changes mainly influence agricultural practices for various crops, including garlic (Alium sativum L.). Current knowledge on climate vulnerability related to agricultural impact in Indonesia is limited. This study aims to identify the level of vulnerability of garlic farmer households to climate change and provide recommendations for adaptation activities for garlic farmers. The household vulnerability profile was assessed using Livelihood Vulnerability Index (LVI) and LVI-IPCC approaches. We carried out interviews for 100 respondents in four villages in Lombok to obtain primary data related to agricultural practices. Relation between climate variables and garlic productivity was determined using linear regression approach. The results showed that rainfall and temperature had a negative correlation with garlic productivity as indicated statistical indicators used, namely R2. According to LVI and LVI-IPCC approach, Sembalun Timba Gading and Sajang have the highest level of vulnerability (0.60) and Sajang Village has the lowest level of vulnerability (0.55) among all villages. The findings suggested that climate information should be considered in agricultural sector for climate change mitigation and adaptation
Identification of Global Warming Contribution to the El Niño Phenomenon Using Empirical Orthogonal Function Analysis
Full text linkSea surface temperature (SST) is identified as one of the essential climate/ocean variables. The increased SST levels worldwide is associated with global warming which is due to excessive amounts of greenhouse gases being released into the atmosphere causing the multi-decadal tendency to warmer SST. Moreover, global warming has caused more frequent extreme El Niño Southern Oscillation (ENSO) events, which are the most dominant mode in the coupled ocean-atmosphere system on an interannual time scale. The objective of this research is to calculate the contribution of global warming to the ENSO phenomenon. SST anomalies (SSTA) variability rosed from several mechanisms with differing timescales. Therefore, the Empirical Orthogonal Function in this study was used to analyze the data of Pacific Ocean sea surface temperature anomaly. By using EOF analysis, the pattern in data such as precipitation and drought pattern can be obtained. The result of this research showed that the most dominant EOF mode reveals the time series pattern of global warming, while the second most dominant EOF mode reveals the El Niño Southern Oscillation (ENSO). The modes from this EOF method have good performance with 95.8% accuracy rate
Evaluation of Different Runoff Curve Number (CN) Approaches on Water Regulation Services Assessment in Intermittent Micro Catchment Dominated by Oil Palm Plantation
Full text linkSurface runoff is a primary driving factor for water regulation services on oil palm plantations as it determines the hydrological components and other biogeochemical process. Therefore, understanding on their interaction and contribution within the watershed system is important to support decision-making system. Here, we applied Soil and Water Assessment Tools (SWAT) model to simulate water regulation services for an intermittent micro-catchment dominated by oil palm plantation in Harapan Landscapes, Batanghari Regency, Jambi Province. In this study, we used two different runoff curve number (CN) approaches in the SWAT model, namely the soil moisture curve number (CN-SM) and the plant evaporation curve number (CN-ET), to evaluate their applicability and uncertainty for assessing water regulation services. SWAT was automatically calibrated and validated against daily observed streamflow data. The results showed that the model performed well as indicated by hydrograph visual interpretation and statistical indicators. The performance was good for calibration and validation for both approaches with high R2 and Nash-Sutcliffe Efficiency (NSE). Also, the uncertainty was acceptable with P-factor >70% and R-factor <1. Differences in CN-SM and CN-ET\u27s conceptual structure have caused variations in the calibrated parameters\u27 best-fit value and their sensitivity to streamflow simulations, which implicated for other components\u27 output water regulation services. However, CN-ET approach was less responsive to area\u27s biophysical conditions for runoff generation than CN-SM one. This implicated that CN-ET generated low soil water storage and an overestimated actual evapotranspiration. This modeling exercise showed selection of a runoff CN approach by considering biophysical characteristics is important for calculating and simulating water balance component in such watershed. The accuracy of the simulation will significantly influence watershed management recommendations to improve water regulation\u27s sustainability
The Use of Weather Research and Forecasting Model to Predict Rainfall in Tropical Peatland: 1. Model Parameterization
Full text linkRainfall 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