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Tujuan penelitian ini adalah menganalisis karakteristik distribusi SUHI pada kawasan permukiman di Kota Yogyakarta. Analisis dilakukan menggunakan citra Landsat 8 yang memiliki band termal. Berdasarkan luas cakupan wilayah yang terdapat fenomena SUHI di Kota Yogyakarta mencapai +1.046,86 ha, sedangkan +2.232,1 ha merupakan non-SUHI karena nilainya LSTnya masih di bawah ambang batas. Kelas SUHI 1 dengan rentang nilai rentang 0,090 C-0,180C merupakan kelas SUHI yang paling besar cakupan wilayah terdampaknya yaitu +376,69 ha. Sedangkan kelas SUHI 5 dengan rentang >2,50C yang juga merupakan kelas SUHI tertinggi mencakup wilayah +5,62 ha dengan cakupan meliputi kawasan permukiman di Kelurahan Ngupasan, Prawirodirjan, Kadipaten, Panembahan, Klitren dan Kelurahan Demangan. Fenomena SUHI dapat terjadi secara temporal sehingga diperlukan penelitian panjang untuk mengetahui trend kejadiannya meliputi intensitas, sebaran lokasi, dan kaitannya dengan faktor klimatologi.

Perbedaan distribusi awan baik secara spasial maupun temporal mempengaruhi hujan yang terjadi. Secara umum pola curah hujan di Indonesia terbagi menjadi tiga pola umum yakni pola monsunal, pola ekuatorial serta pola lokal dengan puncak musim hujan serta kemarau yang berbeda. Penelitian ini mencoba mengevaluasi produk Cloud Type (Jenis Awan) Himawari-8 High-resolution Cloud Analysis Information (HCAI) dalam mengestimasi hujan. Analisis dilakukan di tiga lokasi untuk menggambarkan estimasi atau prakiraan kejadian hujan di beberapa daerah dengan tipe hujan berbeda. Data yang dipergunakan ialah data estimasi kategori hujan per-jam berdasarkan citra jenis awan Himawari-8 HCAI yang diverifikasi dengan data observasi Hellmann selama periode 48 jam di Stasiun Klimatologi Yogyakarta (Mlati, Sleman); Stasiun Meteorologi Supadio (Pontianak); dan Stasiun Meteorologi Amahai (Maluku Tengah). Evaluasi dilakukan dengan tabel kontingensi untuk mengidentifikasi ketepatan dan keandalan estimasi atau prakiraan berdasarkan nilai Percent Correct (PC) dan Frequency Bias Index (FBI). Berdasarkan nilai FBI dan PC ketepatan dan sifat teknik estimasi di tiga lokasi penelitian tidaklah sama namun secara umum dapat disimpulkan bahwa estimasi atau prakiraan hujan dari teknik prakiraan ini cenderung underestimate/underforecast dalam menduga kejadian hujan kategori “tidak hujan” dan “hujan ringan”. Sebaliknya, prakiraan cenderung bersifat overestimate/overforecast dalam menduga hujan kategori lebat dan sangat lebat. Ketepatan teknik estimasi hujan berdasarkan citra jenis awan Himawari-8 HCAI dalam menduga kejadian hujan kategori “hujan ringan”, “sedang” dan “sangat lebat” secara umum relatif lebih baik daripada untuk menduga hujan kategori “tidak hujan” dan “lebat”.

This study aims to analyze the potential of surface water to meet agricultural water needs in Kediri Regency, Indonesia. Data from government agencies (i.e., Indonesian Bureau of Meteorology, Climatology, and Geophysics and Kediri Agriculture Office) and fieldwork were analyzed to achieve the research objectives. The data obtained consisted of rainfall, temperature, infiltration capacity, soil texture, root depth, and agricultural land area. The potential of surface water resources was calculated by using the Thornthwaite–Mather water balance method. The water balance results were compared with agricultural water demands, which were calculated on the basis of the area of agricultural land and type of crop, particularly paddy fields. Critical and noncritical conditions for surface water resources were classified on the basis of the ratio between the availability of surface water resources and the demand for agricultural water. Results showed that the total surface water potential widely varied by season. The water balance calculation indicated that all subwatersheds (SWs) experienced a water surplus in the rainy season, whereas almost all SWs were deficient in surface water in the dry season, Overall, the surface water in Kediri was critical in the rainy season and more severely critical in the dry season. The results of this study indicated that the high demand for agricultural water can affect the availability of water resources in the tropics. The results are expected to be considered in determining regional planning related to the use and need of water resources and supporting infrastructures.

This paper discusses an analysis to obtain the optimal thermal sensor placement based on indoor thermal characteristics. The method relies on the Computational Fluid Dynamics (CFD) simulation by manipulating the outdoor climate and indoor air conditioning (AC) system. First, the alternative sensor's position is considered the optimum installation and the occupant's safety. Utilizing the Standardized Euclidean Distance (SED) analysis, these positions are then selected for the best position using the distribution of the thermal parameters' values data at the activity zones. Onsite measurement validated the CFD model results with the maximum root means square error, RMSE, between both data sets as 0.8°C for temperature, the relative humidity of 3.5%, and an air velocity of 0.08m/s, due to the significant effect of the building location. The Standardized Euclidean Distance (SED) analysis results are the optimum sensor positions that accurately, consistently, and have the optimum % coverage representing the thermal condition at 1,1m floor level. At the optimal positions, actual sensors are installed and proven to be valid results since sensors could detect thermal variables at the height of 1.1m with SED validation values of 2.5±0.3, 2.2±0.6, 2.0±1.1, for R15, R33, and R40, respectively.

Climate change has become a global issue over last decades. Its impact affects to various aspects of human life. Uncertainty of dry and wet seasons present a consequence to and create losses on agriculture sector. Therefore, resilience to climate change is necessary for farmers. This research aims to identify exposure, sensitivity, and adaptive capacity within the framework of community resilience to climate change in agricultural sector. Parameters used in this research include rainfall variability representing system exposure, landuse and topography representing sensitivity, and farmer’s knowledge and behavior representing adaptive capacity. Secondary data used in this research are daily rainfall data, land use and topographic maps, while primary data obtained by interview using purposive sampling method to measure adaptive capacity of farmers community. We employ trend, spatial, and descriptive analysis. The results show that Sentolo Subdistrict has a relatively high exposure to extreme events both in wet and dry seasons that occurred 5 times in 12 years. However, this high exposure did not affect agriculture sector on Sentolo significantly, both in terms of damages and losses to farmers. It indicates that the sensitivity to climate change in this area is low, while farmers’ community in Sentolo has a high level of adaptive capacity. They have sufficient level of knowledge to climate change, better adjustment to technology and well-managed assets. This interplay shows that the agricultural community in the study area has a relatively high resilience to climate change.

Productive agricultural areas in Kebumen, Central Java, Indonesia are potentially vulnerable to the adverse impacts of climate change. We surveyed small-scale farmers to assess climate change-related perceptions and adaptations in the agriculture sector. The majority of the respondents agreed that there were changes in climatological variables affecting their farming activities, especially in terms of precipitation and temperature. However, the results also revealed that only 13% of respondents believed that human activities play a significant role. Three forms of adaptations have been developed by the farmers, namely: (1) agricultural diversification, (2) agricultural intensification, and (3) socioeconomic adaptation. Changing crops to more climate-tolerant varieties was one of the most common agricultural diversification practices (implemented by 88% of farmers). Most of the farmers also tried to maintain agricultural productivity by adjusting a local planting calendar (implemented by 94% of farmers). The use of machinery to intensify farming practice was an uncommon strategy (implemented by only 30% of farmers) because of expensive maintenance and small cultivation areas. The results suggested the importance of increasing farmers’ knowledge and technological know-how related to climate change and its implications, developing effective adaptation and mitigation efforts, and constructing climate-resilient infrastructure in the agricultural sector.

Donorejo is one of the villages in Purworejo Regency, Central Java, Indonesia. This village is a unique place and famous for its tourism site, namely Goa Seplawan. Nevertheless, this tourist attraction has not provided significant income for local revenue, as the poverty rate in Donorejo is still quite high. The Office of Community Empowerment, Villages, Population and Civil Registry of Central Java stated that only 1, 630 residents of Donorejo were categorized as prosperous in their economy. It indicated that almost 50% of the population in Donorejo has not been economically prosperous and the development of Donorejo has not implemented optimally. To find out the proper development strategy, the Analytical Hierarchy Process was used as a method based on stakeholder assessment in the Donorejo. The used priorities were based on four aspects, namely human resource development, regional promotion, development of supporting infrastructure, and public services. The obtained results indicated that development of supporting infrastructure is a priority for the development of Donorejo. This outcome can be used as a reference to optimize the village development.

This research aims to compare precipitation data derived from satellite observation and ground measurements through a dense station network over Central Java, Indonesia. A precipitation estimate from the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 Version 7 are compared with precipitation data from interpolated rain gauge stations. Correlation analysis, mean bias error (MBE), and root mean square error (RMSE) were utilized in the analysis for each thee-monthly seasonal statistics. The result shows that the 3B42 products often estimate lower rainfall than observed from weather stations in the peak of the rainy season (DJF). Further, it is revealed that the 3B42 product are less robust in estimating rainfall at high elevation, especially when humid environment, which is typical during the rainy season peak, are involved.

&nbsp, Precipitation homogeneity is one of the main factors that contribute to the difference in the rain-rate estimation from meteorological satellites. Using the Tropical Rainfall Measuring Mission (TRMM) products, this paper aims to characterize the homogeneity of ice-scattering signals from TRMM Microwave Imagers (TMIs) as related to rain-rate estimation bias with TRMM Precipitation Radar (PR). Statistical information about the polarization-corrected brightness temperature (PCT) from the TMI 85 GHz band is obtained over the global ocean in the tropics. The characteristics are the fraction of PCT below a given threshold, the minimum value, and the standard deviation that are calculated at a 0.25° × 0.25°grid level. The average values of rain-rate estimation from TRMM PR and TMI in the same grid position and time are then compared. This result indicates that the rain-rate estimation bias is influenced by the homogeneity and organization of precipitation systems. Using the statistical signature of ice-scattering signals at the grid level, an adjustment was implemented for TMI rain-rate estimation. The results could produce rain-rate estimations that conform more to PR, particularly for the inhomogeneous precipitation system mostly affected by stratiform rain. The characterization of ice-scattering signals as a proxy to the precipitation homogeneity, as presented in this research, could be implemented in order to improve the accuracy of satellite rain-rate estimation in the future.&nbsp

Dieng Volcanic Highland is one of the most intensive potato agricultural land in Indonesia, as well as frost disaster prone area. Frost indicated by appearance of frozen dew on the ground or vegetation surface due to cold temperatures during dry season. Frost causes damage to leaf tissue in potato plants, resulting crop failure and losses of up to tens of millions. Disaster management needs to be assess in order to achieve Disaster Risk Reduction (DRR) on agricultural land. This research aims to identify frost hazard areas based on local physical characteristics, analyze frost impacts on agricultural land, and provide preparedness recommendation to reduce the impact of frost disasters in Dieng Volcanic Highland. Research was conducted in Dieng Village, Wonosobo and Dieng Kulon Village, Banjarnegara. Method to assess hazard level was performed by spatial mapping technology using ArcGIS and comprehensive analysis using frost assessment through combinations of geomorphology, land use, proximity to water bodies and weather aspects. Dieng Volcanic Highland has a 125.59 hectare frost hazard areas, as many as 58.4 hectares of hazard areas are dominated by high level, while 24.84 hectares are moderate level and 42.95 hectares are low level. Cropland dominated by potato commodity has the highest hazard level, frost incident causing agricultural commodities to wither to death so that farmers experience losses. Frost losses in Dieng have a range from 800 thousand rupiah to over 155 million rupiah and only destructive on potato farm. In order to encourage agricultural resilience and reduce the loss of frost disasters, effort of preparedness can be done by passively and actively methods. Passive methods includes site selection, early warning system, shifting commodities, cropland modification, and appropriate calendar planting. Active methods includes frost modification using heaters, blower and sprinkle irrigation, and cropland covering using mulch, plastic or nets.

Yogyakarta city has a problem of water resources management along with the rapid development in this region. Rainwater harvesting (RWH) can be an alternative choice in urban water resources management. This study aims to determine the best RWH scenario as a sustainable water supply to meet domestic water demand in Yogyakarta City. The method used is the Sustainability Index with 3 parameters including reliability, resilience and vulnerability. Each parameter is a derivative of a water balance simulation of the RWH system using the data range in the period 2006–2015. This study compares the percentage of roof usage in the RWH system and the level of domestic water demand. The results of this study indicate that the RWH scenario by utilizing 50 %–75 % of the roof area can be ideally meet up to 80 % of domestic water needs in Yogyakarta City. RWH scenario with 100 % roof usage can meet all domestic water needs well. This study shows that the RWH system can have a positive impact on the management and sustainability of water resources in Yogyakarta City.

Indonesia is among the most affected regions by climate variability and change. Located between the Pacific and the Indian Ocean, Indonesia is mostly influenced by some climate variabilities, such as the monsoon, El-Nino Southern Oscillation (ENSO), and Indian Ocean Dipole (IOD). These climate variabilities affect significantly on the Indonesian rainfall that further increase the chances of crop failure, specifically on the tobacco yield over Temanggung Regency which is known as the producer of good quality tobacco in Indonesia. Tobacco needs a sufficient dry condition prior to the harvest stage due to maintains its productivity and leaf quality. This ideal condition could be achieved when the dry season, typically in the mid of the year for Temanggung, is not affected by any wet climate variability. Moreover, based on this study, it was found that there was the most remarkable decline in tobacco productivity in 2016 since the required dry condition was interrupted by the prolonged significant rainfall which depicted by strong mid-year negative-IOD indices. The analysis utilized the dataset of tobacco productivity, daily rainfall intensity, and the indices of monsoon, ENSO, and IOD for the period of seven years, from 2010– 2016. This study concludes that the climate variabilities give a huge contribution to the profitable tobacco cultivation. Furthermore, efforts to adapt and to mitigate the impacts of the climate variability in Indonesia, specifically for the agriculture sector, is needed by way of increasing the various stakeholder's knowledge that involved in policy planning and decision-making as well as involving the farmers in the training on climate adaptation and mitigation.

Geographically, Indonesia has been subjected towards various climate change related phenomena. This research aim at evaluation of participatory implementation towards climate change related policy which has been set in Indonesia. The research method derived from qualitative framework developed by UNESCO. The research took RAN-API or National Action Plan upon Climate Change Adaptation which has been established since 2013. The document has been integrated within National Medium Term Plan launched at 2015 up to 2019. The research revealed that participation has been inclusive to many stakeholder involved within climate change adaptation program. Furthermore, encouragement needs to be carried out at all level especially in urbanized area. Local to national government has pivotal role to introduce many activities engaged to climate change adaptation. At different array, the research also revealed that many participation has been initiated independently by non-government organization as well as local stakeholder which need to be documented in order to ensure its merits.

Increased of the number of visitor at Gelatik Cave is a challenge in terms of cave management. In natural conditions, Caves are vulnerable with environmental changes especially microclimates condition. The change of microclimate inside the cave can destruct cave ornaments.Therefore, it is necessary to calculate the cave carrying capacity with microclimates as the main parameter. This research aims to (1) explore the daily variation of speleoclimate in Gelatik Cave Tourism and (2) analyze the cave tourism capacity in Gelatik Cave. Microclimate parameter that was measured in this research was temperature, relative humidity, and carbon dioxide inside the cave. Measurement of microlimate parameter was carried out automatically for 24 hours during peak season in December 2017 and low season in May 2018. Cave tourism capacity was measured using Lobo method (Lobo, 2015). The results showed that temperature, relative humidity, and carbon dioxide in the Gelatik Cave varry due to tourism activities. The most sensitive parameter is the carbon dioxide concentration inside the cave. The maximum of tourists allowed to visit Gelatik Cave is 76 visitors/ day during holidays and working days. Meanwhile, the maximum time of stay accepted for a particular area inside Gelatik Cave is 17 minutes 10 seconds during weekdays and 12 minutes 53 seconds during the holiday season.

Upper Progo watershed is one of the important agricultural areas in Temanggung Regency, Central Java. This research used the data obtained from Landsat 8 imagery to analyze the agricultural drought risk in the watershed. The hazard was analyzed using multi-temporal data every 16 days (to the Landsat 8’s temporal resolution) during the drought; from May to September 2015 combining the Landsat 8 imagery and the land’s physical condition. An agricultural drought hazard map was then created by summing the hazard class score in every recording time with overlay method. The crop’s vulnerability analyzed using NDVI difference, which indicates the crop’s ability to survive in dry conditions. The crop’s vulnerability was also analyzed every 16 days. A vulnerability map was then created by summing the vulnerability class of every recording time. The assessment of the drought risk was done by multiplying the hazard and the vulnerability scores. The result shows the high and very high classes of agricultural drought risk were located on the west research area which had a high class of hazard and vulnerability. Meanwhile, the moderate, low, and very low classes of agricultural risk were distributed evenly in the center and east area.

Gunungkidul Regency is known as an area that often experiences drought. On the other hand, Gunungkidul Regency is also the regency with the highest amount of rice production in the Special Region of Yogyakarta Province. Rainfed paddy farming is the most widely developed type of paddy in Gunungkidul Regency where irrigation needs are determined by rainfall. Decreased rainfall that triggers meteorological drought can disrupt rainfed-based agriculture. This study aims to analyze the distribution of meteorological drought and analyze the impact of meteorological drought on rainfed paddy productivity in Gunungkidul Regency during the period 2001 – 2019. Meteorological drought identification was carried out using the Standardized Precipitation Index (SPI). Results of the SPI classification was mapped using Spline-Tension interpolation for spatial analysis of the distribution of meteorological drought. Spatial analysis and comparison graphs were used to analyze the relationship between drought and rainfed paddy productivity. The widest meteorological drought in Gunungkidul Regency occurred in November 2006. The highest frequency of drought events occurred in Paliyan Sub-district for 50 months while the lowest occurred in Ponjong Sub-district for 30 months. Most sub-districts in Gunungkidul Regency have a positive relationship between meteorological drought. Most of rainfed paddy productivity decreased when El Nino occurred.

The diurnal cycle is a process that repeats daily due to earth rotation. This cycle could significantly affect the hydrological conditions and lithosphere conditions, including humans. This diurnal cycle is also likely to influence seasonal patterns in the region. The diurnal cycle has a close relationship with the time-series pattern and distribution of rainfall. It often affects hydrometeorological disasters in the form of floods and droughts. This paper provides an overview of early identification related to the diurnal cycle of rain in the Central Java region - Indonesia. Rainfall estimation data from The Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) is used as the primary input in the analysis. The research results show that there are differences in rainfall patterns between the northern, central, and southern parts of the study area

Synthetic rainfall simulation using weather generator models is commonly used as a substitute at locations with incomplete or short rainfall data. It incorporates a method that can be developed into forecasts of future rainfall. This study was designed to modify a rainfall prediction system based on the principles of weather generator models and to test the validity of the modelling results. It processed the data collected from eight rain stations in zones affected by El-Nino Southern Oscillation (ENSO). A large-scale predictor, that is, SST prediction data in the Nino 3.4 region over the Pacific Ocean was used as the influencing variable in projecting rainfall for the following six months after the predefined dates. Rainfall data from weather stations and SST in 1960-2000 were analyzed to identify the effects of ENSO and build a statistical model based on the regression function. Meanwhile, the model was validated using the data from 2001 to 2007 by backtesting six months in a row. The analysis results showed that the model could simulate both low rainfall in the dry season and high one in the rainy season. Validation by the student's t-test confirmed that the six-month synthetic rain data at nearly all observed stations was homogenous. For this reason, the developed model can be potentially used as one of the season prediction systems.

Sangiran Site is dominated by rainfed field. Climate parameters, especially rain intensity affects crop patterns. Farmers strongly depend on rain intensity to support productivity thus they need climate-based crop patterns. Sangiran Site is prone to drought hazard since the region has a limited access to groundwater, which is henced by deep well in the region. Drought becomes the main threat to agriculture within Sangiran. This study aims to analyse meteorological drought and crop pattern determination using the SPI and the Oldeman classification respectively. Rainfall data is derived from multi temporal CHIRPS data. A monthly time series with thirty consecutive years (1988–2017) was used to calculate the annual SPI. The annual SPI help to determine crop patterns which is suitable for the region. The results of the study show that angiran Site has monsoonal rainfall with one peak of dry season, and one peak of wet season. Rainfed field is at the highest risk when drought lasts for above four months. Climate based crop patterns with the Oldeman classification indicate that Sangiran Site is classified into type C2 which is adequate for two times palawija crops and one time paddy crops.

Predicted increasing climate variability and change in the future by the Intergovernmental Panel of Climate Change have significant impact towards agricultural sector in Indonesia.Local farm commodities in Indonesia, such as tobacco, are very sensitive to changing climate. This study aims to measure tobacco farmers perspective towards increasing climate riskin Indonesia. Tobacco plantationarea in Temanggung District is selected as a case study since it is well known for its tobacco production, particularly for cigarette.Focus Group Discussion (FGD) towards local tobacco farmers has been conducted to identify how the weather and climate affect the farmer activity, as well as the climate risk due to increasing unpredictability of weather and climate. The result shows that in farmers perspective, it becomes more difficult to manage the farmlands. For the case of tobacco, excessive rainfalls orinsufficient rainfall could cause crop failure. As a result, the tobacco productivity is not as large compared to the past. The farmers also have lower income compared to the past5 years due to lower tobacco quality and quantity.

Madden-Jullian Oscillation (MJO) has a strong influence towards rainfall over The Maritime Continent (MC). Due to possible impacts towards extreme precipitation in this area, a study is required to determine the influence of those processes. This research aims to investigate the influence of MJO on extreme precipitations over Indonesian Maritime Continent. To investigate the influence of those three processes, satellite precipitation data from The Tropical Rainfall Measuring Mission (TRMM) 3B42 product and Real time multivariate MJO (RMM) Index are used. Several extreme indices are calculated to identify magnitude of the extremes by calculating the area coverage of a specific precipitation threshold in each climate zone. Principal component analysis (PCA) is implemented to these indices to reduce large number of data into smaller number of information. Correlation analysis is implemented to the PCA and then matched to the MJO index to identify degree of influence of each process. Comparison of winds and mean sea level pressure data during each phenomenon is conducted to identify the key elements that control the generation of extreme precipitation. The result indicates extreme rain events in Indonesia could be triggered by the MJO, particularly during phase 4-6.

Even though climate change has a multisectoral impact on the agricultural country Indonesia, farming sector experiences the most significant adversity. The concomitant climate uncertainty potentially harms in particular traditional farmers. Current technology is now able to predict weather and climate conditions, and as such, it is useful for farmers as an input to their decision-making process in farmland management. This paper explains the design of a mobile application created by researchers to present information on seasonal weather prediction that fits adaptation measures in the agricultural sector to climate variability. The product can help to enhance the adaptation capacity of communities to erratic climate, particularly farmers and the Office of Agriculture in Temanggung District. Also, the application is expected to provide recommendations for both parties to be able to reduce crop failure and subsequent loss due to climate variability and increase the resilience of farmers to climate change impact, especially the persistent increase and decrease in rainfall each in the rainy and dry season.

Infrastructure plays an important role in the tourism sector as a provider of facilities to provide facilities to tourist sites. The study area is in the Donorejo village, Central Java. Donorejo village has one of the most famous caves in Central Java, namely Goa Seplawan. The study was conducted with in-depth interviews with local residents and tourist visitors, as well as measurements and direct examination of the paths that are on site. Quality assessment of road conditions is carried out qualitatively. The assessment is based on the experience and standardization of each respondent which is then re-matched with the results of the study at the location and the Road Condition Index Matrix (RCI). There are three main paths to Seplawan Cave, namely through Hamlet Rejosari, Denansri, and Katerban. The main road passes through Hamlet Rejosari in good condition, but very steep. On the other hand, Denansri and Katerban hamlets have poor conditions. Road improvements have increasing the number of visitors to Goa Seplawan. In 2018 there were 9, 889 and in 2019 became 13, 882. This number shows that road construction has an impact on increasing the number of visitors at tourism sites in the Donorejo village.

DAS Progo Hulu merupakan kawasan pertanian penting yang ada di Kabupaten Temanggung. Defisit curah hujan yang cukup panjang berdampak pada aktivitas pertanian di daerah ini. Tujuan dari penelitian ini adalah untuk menganalisis tingkat kerentanan tanaman secara multi-temporal di DAS Progo Hulu Kabupaten Temanggung. Metode yang digunakan adalah menganalisis data curah hujan, menghitung selisih NDVI pada setiap tempo 16 hari, dan melakukan validasi objek tanaman pertanian. Hasil penelitian menunjukkan Kerentanan kekeringan pertanian yang dideteksi menggunakan selisih NDVI menunjukkan bahwa lereng dan kaki vulkan Sindoro dan Sumbing memiliki kerentanan paling tinggi. Hal tersebut disebabkan karena daerah tersebut memiliki jenis tanaman semusim yang tidak tahan terhadap cengkaman air.

Kekeringan sering terjadi di Provinsi Jawa Tengah. Kekeringan tersebut dapat dipengaruhi oleh berbagai faktor dan dapat pula memberikan dampak terhadap berbagai aspek. Penelitian ini bertujuan untuk menganalisis distribusi kekeringan di Provinsi Jawa Tengah. Data yang diperlukan adalah data curah hujan bulanan. Data curah hujan tersebut merupakan data hasil pengukuran lapangan tahun 1981-2010 dan dilengkapi oleh data Tropical Rainfall Measuring Mission (TRMM). Metode yang digunakan meliputi metode Standardized Precipitation Index (SPI) dan interpolasi tension spline. Metode SPI digunakan untuk menentukan klasifikasi kekeringan. Hasil pengolahan SPI dipetakan menggunakan interpolasi tension spline. Kekeringan meteorologis di Provinsi Jawa Tengah terjadi setiap tahun (1981-2010). Kekeringan terluas terjadi pada bulan Setember-November 1982 di 96% wilayah Provinsi Jawa Tengah. Kekeringan ekstrim (golongan amat sangat kering) terluas terjadi pada bulan Setember-November 1997 di 39% wilayah Provinsi Jawa Tengah dengan pola membulat serta mengelilingi pusat-pusat wilayah normal di sekitar Kabupaten Banjarnegara, Kabupaten Wonogiri, dan Kabupaten Pati. Kata kunci: ENSO, Jawa Tengah, Kekeringan Meteorologis, Pola Tanam, SPI

Agricultural drought is alarmed by meteorological drought characterized by lower year-to-year rainfall. Under long period and continuous water deficits, plants may demonstrate stress symptoms and wilt or die. Furthermore, agricultural drought leads to crop failures and threaten the food security of an area. Progo Hulu sub-watershed is a major agricultural area in Temanggung Regency. Spatial-temporal pattern-based information about agricultural drought can be a basis for decision making in drought mitigation. This study aims to analyze spatial and temporal distribution patterns of drought, analyze the physical characteristics of land and their influence on drought pattern, and establish a prediction model of drought distribution patterns based on four physical characteristics of the land. Landsat 8 imagery is used to determine the spatial and temporal patterns of agricultural drought in Upper Progo watershed using an improved Temperature vegetation Dryness Index (iTVDI). Slope, land use, landform, and soil texture are the physical characteristics of land as the variables to determine the most influential factor of drought pattern. They are analyzed using multiple regression analysis techniques. Pixel samples are obtained through purposive sampling method based on land units. The results reveal that the spatial-temporal distribution of agricultural drought occurs rapidly on the slopes and foothills of Sumbing and Sindoro. These areas have the highest average value of the iTVDI index. Agricultural drought extends gradually in line with the number of days without rainfall. Landform is a physical characteristic that most influences the distribution of agricultural drought. The established model by utilizing four variables of physical characteristics generates an average value which almost similar to the iTVDI value produced by remote sensing data. The model can be useful to estimate drought distribution based on the number of days without rainfall.

Tropical Cyclone Cempaka occurred on November 27, 2017 in the Indian Ocean, just south of Central Java. This incident induced high rainfall leading to flash floods in the southern part of Central Java, including Gunungsewu Karst Area. The highest rainfall recorded on November 28, 2017, in this area was 239 mm/day (Automatic Rainfall Recorder/ARR Station in Pindul Cave) and 341 mm/day (ARR Station in Tepus). The extreme rainfall also caused groundwater flood in Ngreneng Karst Window. This study aimed to analyze the mechanism of this flood. The results of the analysis showed that it was caused by water filling up the conduit passage in the entire Bribin-Baron underground river system. The flow of the conduit pushed the diffuse flow into the surface fast, and the water that came out of Ngreneng Karst Window was thereby clear. The inundation lasted for ten days and submerged up to 26.4 ha of the study area.

Perubahan penggunaan lahan di Kota Semarang akibat pertumbuhan penduduk dan aktivitas ekonomi telah menyebabkan terjadinya urban sprawl. Banjir rob, land subsidence, intrusi air laut dan tercemarnya air tanah di Kota Semarang Bagian Utara menyebabkan terjadinya perkembangan Kota Semarang dominan ke arah selatan. Hal ini menyebabkan perubahan penggunaan lahan dari lahan non terbangun menjadi lahan terbangun sehingga jumlah air hujan yang langsung menjadi limpasan akan semakin banyak. Hal ini akan menyebabkan bahaya banjir bandang di Kota Semarang semakin besar. Penelitian ini bertujuan untuk: (1) mengetahui perubahan lahan yang terjadi di DAS Garang selama tahun 1994 dan 2001, dan (2) mengetahui dampak perubahan penggunaan lahan terhadap besarnya debit puncak yang terjadi di DAS Garang. Data yang digunakan dalam penelitian ini adalah Citra Landsat TM tahun 1994, Citra Landsat ETM tahun 2001, dan Citra Alos AVNIR 2008, peta tanah DAS Garang, peta kemiringan lereng DAS Garang, peta jaringan sungai DAS Garang, dan data curah hujan harian Stasiun Ungaran tahun 1952 sampai dengan tahun 2009. Ditemukan bahwa luas lahan terbangun bertambah lebih dari dua kali lipat dari tahun 2001 sampai dengan 2008, lahan pertanian meningkat hampir 50% dan luas hutan mengalami penurunan dari tahun ke tahun. Namun demikian, debit puncak di DAS Garang tidak bertambah secara ekstrem meskipun mengalami sedikit perubahan. Change due to land use in the city of Semarang as an impact of population growth and economic activity has led to urban sprawl. Rob flooding, land subsidence, seawater intrusion and contamination of ground water in the northern part of Semarang lead to the development of the southern part. Consequently, this leads to changes in land use so that the amount of rain water runoff will increase. This may cause the danger of flash floods in the greater city of Semarang. This study were aimed to: (1) determine the changes that occur in the Garang watershed lands during 1994 and 2001, and (2) determine the impact of land use changes on the size of the peak discharge occurring in the Garang watershed. The data used in this study were the 1994 Landsat TM, Landsat ETM 2001, and Citra Alos AVNIR 2008, Garang watershed soil map, slope map of Garang watershed stream network, and daily rainfall data at Ungaran Station of 1952 until 2009. It was found that developed land has been increasing more than doubled from 2001 to 2008, agricultural land increased by nearly 50% and the forest area were decreased from year to year. However, the peak discharge at the Garang watershed has not increased to the extreme though there was a slight change.

We consider the Empirical Orthogonal Function (EOF) to study the rainfall pattern in Daerah Istimewa Yogyakarta (DIY) Province, Indonesia. The EOF is one of the important methods to study the dominant pattern of the data using dimension reduction technique. EOF makes possible to reduce the huge dimension of observed data into a smaller one without losing its significant information in order to figures the whole data. The methods is also known as Principal Components Analysis (PCA) which is conducted to find the pattern of the data. DIY Province is one of the province in Indonesia which has special characteristics related to the rainfall pattern. This province has an active volcano, karst, highlands, and also some lower area including beach. This province is bounded by the Indonesian ocean which is one of the important factor to provide the rainfall. We use at least ten years rainfall monthly data of all stations in this area and study the rainfall characteristics based on the four regencies of the province. EOF analysis is conducted to analyze data in order to decide the station groups which have similar characters.