Adaptive Garlic Farming on Climate Change and Variability in Lombok

Climate 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.

Potential of Sorghum Varieties as Biofuel

The 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

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.

Evaluation of Different Runoff Curve Number (CN) Approaches on Water Regulation Services Assessment in Intermittent Micro Catchment Dominated by Oil Palm Plantation

Surface 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's conceptual structure have caused variations in the calibrated parameters' best-fit value and their sensitivity to streamflow simulations, which implicated for other components' output water regulation services. However, CN-ET approach was less responsive to area's 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's sustainability.

Non-linear Routing Scheme at Grid Cell Level for Large Scale Hydrologic Models: A Review

New 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 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.

Accute Respiratory Infections (Pneumonia) Incidence Rate in Children due to Climate Variables and Air Quality in Bogor

Pneumonia 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

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.

Planting Time and Fertilizer Validation Based on Banyudono Planting Calendar in Boyolali Regency

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.

Identification of Global Warming Contribution to the El Niño Phenomenon Using Empirical Orthogonal Function Analysis

Sea 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.