Statistical Assessment of High-Resolution Climate Model Rainfall Data in the Ciliwung Watershed, Indonesia

The impact of climate change on hydrometeorological hazards pointed out the necessity for information on rainfall data. Using Climate Hazard Group InfraRed Precipitation with Station (CHIRPS) data could solve the problem of the scarcity of observed rainfall data at a finer spatial resolution. This paper examines the performance of high-resolution rainfall climate model data called CORDEX SEA and NEXGDPP in the Ciliwung watershed, Indonesia. We used CHIRPS data as observed data, which was separately divided for calibration (1981-2005) and validation (2006-2020) of the climate models. Totally 14 climate models were used, comprised of 4 CORDEX and 10 NEXGDPP. The models accuracy was assessed based on three statistical indicators: bias, mean absolute percentage error (MAPE), and mean square error (MSE). We determined the best model based on Taylor Diagram. The results showed that the bias value in the dry season was smaller than in the wet and transitional seasons. All models performed well as shown by the low bias values except for the ACCESS1-0 RCP8.5 model. The findings revealed that MRI-CGCM was the best model for calibration, whereas EC-Earth was the best model in the validation period for both RCP4.5 and RCP8.5 scenarios. Further, the choice of climate model may influence water resource management over watershed scale

APPLICATION OF CMORPH DATA FOR FOREST/LAND FIRE RISK PREDICTION MODEL IN CENTRAL KALIMANTAN

Central Kalimantan Province is a region with high level of forest/land fire, especially during dry season. Forest/land fire is a dangerous ecosystem destroyer factor, so it needs to be anticipated and prevented as early as possible. CMORPH rainfall data have good potential to overcome the limitations of rainfall data observation. This research is aimed to obtain relationship model between burned acreage and several variables of rainfall condition, as well as to develop risk prediction model of fire occurrence and burned acreage by using rainfall data. This research utilizes information on burned acreage (Ha) and CMORPH rainfall data. The method applied in this research is statistical analysis (finding correlation and regression of two phases), while risk prediction model is generated from the resulting empirical model from relationship of rainfall variables using Monte Carlo simulation based on stochastic spreadsheet. The result of this study shows that precipitation accumulation for two months prior to fire occurrence (CH2Bl) has correlation with burned acreage, and can be estimated by using following formula (if rainfall ≤ 93 mm): Burnt Acreage (Ha) = 5.13 – 21.7 (CH2bl – 93) (R2 = 67.2%). Forest fire forecasts can be determined by using a precipitation accumulation for two months prior to fire occurrence and Monte Carlo simulation. Efforts to anticipate and address fire risk should be carried out as early as possible, i.e. two months in advance if the probability of fire risk had exceeded the value of 40%

Assessment of Livelihood Vulnerability to Climate Change Using Three Index Methods

Vulnerability 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

ANALISIS KESESUAIAN IKLIM UNTUK PENGEMBANGAN CENDANA (Santalum album L.) DI NUSA TENGGARA TIMUR

Land suitability analysis method is introduced for sandalwood (Santalum album L.) in Nusa Tenggara Timur. It includes analysis on its (I) agro ecological suitability based on crop requirement for climate and soil characteristic, (2) ecological suitability, and (3) social-economic requirement for sustainable and profitable production. Approach to these three components is conducted through desk study/survey and on site research. All information collected and analyzed is combined together in GIS (Geographical Information System) for further use

PENILAIAN RISIKO IKLIM PADA SISTEM PERTANIAN EKOSISTEM LAHAN RAWA PASANG SURUT (STUDI KASUS DI DELTA TELANG I, DELTA TELANG II DAN DELTA AIR SALEH, BANYUASIN, SUMATERA SELATAN) (CLIMATE RISK ASSESMENT ON AGRICULTURAL SYSTEM IN SWAMP AREAS ...

The characteristics of swampland areas are different from agricultural land of Java, mainly in water availability. In swampland ecosystems there are unique environmental conditions. To assess risks of climate, mainly in climate change, we must assess about capacity and adaptation strategy. From treasure of related institution and interview with farmers,its had been known about climate impact on farming systems application, rainfall pattern and water availability. This paper aims to assess risks of climate on farming systems, application of adaptation strategy to reduce risks of climate and probability to provide of planting pattern alternative in the future in swampland areas (tidal marsh) in Delta Telang I, Delta Telang II and Delta Air Saleh, Banyuasin, South Sumatera

Analisis Jejak Karbon Agribisnis Sawit Untuk Menyusun Arahan Strategi Dan Program Corporate Social Responsibility (CSR)

Palm oil agribusiness include on-farm activities (plantation) and off-farm activities (palm oil mill) are exposed to environmental issues as one of the contributors to greenhouse gas (GHG) emission. The purpose of this study is to assess the carbon footprint of palm oil agribusiness as an input to formalize Corporate Social Responsibility (CSR) strategy and program, particularly in efforts to reduce CO2 emission. The boundary of emission sources are: 1) diesel for transporting seed; 2) diesel of pump water; 3) fertilizer (N); 4) diesel for transporting FFB to mill; 5) diesel consumption at mill; 6) electricity consumption at mill; 7) POME; and 8) diesel for transporting CPO to harbour. Data to estimate CO2 emissions during 20 year of life cycle (period 1991-2011). Total emissions of palm oil agribusiness is 3904511 tonCO2, where diesel for transporting FFB (79 %) and CPO (11.12 %) as the largest emitters. It is influenced by the considerable distance between the location of estate SA, estate AB, mill and harbor. The accumulation of carbon stocks is 5713697 ton C / ha. initial carbon stocks was higher compared to carbon stocks in peat and mineral., Tree planting, forest conservation, waste utilization, and the Clean Development Mechanism (CDM) project is an effort in the company\u27s environmental management, especially reducing GHG emissions. Strategic and programs that was formulated in the form of: 1) system integration palm oil agribusiness and cattle breeding; 2) alternative energy as a impact of CDM project; 3) participatory tree planting; and 4) socialization upon mitigation of GHG emissions

Prediksi Awal Musim Hujan di Jawa Menggunakan Data Luaran Regional Climate Model Version 3.1 (RegCM3)

Monsoon onset information plays an important role in setting up planting strategy for achieving optimum yield. This study aimed to develop forecasting model for the monsoon onset in main rice growing area of Java used Regional Climate Model Version 3.1 (RegCM3). The forecasting models of the monsoon onset and September-Oktober-November (SON) rainfall data were developed using regression model that have the highest coefficient determination and the models were tested using likelihood ratio test. It was found that the forecasting models of the monsoon onset and September-Oktober-November rainfall data were polynomial orde 2 or cuadratic that have coefficient determination 69%, 74%, 80% and 86%. Likelihood ratio test found that RegCM3 rainfall data was not significantly different with observation rainfall data (α = 0.05). Onset in Java between 25th until 34th of 10-days period (early September until early December)