The drivers for coastal flooding may vary from extremely high intensity and persistent rainfall, morphological factors of the coastal area, to extreme waves from the ocean. This means that the flood ...vulnerability of a coastal area does not solely depend on a single driver but can be a combination with others. A national standard for coastal flooding based on rainfall drivers has been developed. As an evaluation, this study aimed to develop a method for coastal flood-prone mapping by combining rainfall with tidal waves. The steps included the assessment of the coastal flood-prone areas driven by rainfall (CFR) and the coastal flood-prone areas by combined drivers (CFC), which was developed by employing the analytic hierarchy process (AHP), spatial-overlaid, weighted-scored, and logical tests. The coastal area of Mataram City on the Island of Lombok in Indonesia was selected as the study area, since it is frequently affected by flooding. The findings determined the essentiality of the CFC method for identifying flood vulnerability areas. Thus, the minimum standard for CFC parameters can be defined with climatic and land characteristic factors. Further, the findings also identified the need for expert judgment in the development of the CFC weighted score-based method.
Critical watersheds that exceed their carrying capacity occur in many regions of the world; their formation is facilitated by a significant driving factor known as land use/land cover (LULC) changes. ...This study aims to identify the LULC changes in Cisadane Watershed, Indonesia, in 2010, 2015, 2021, and simulate future LULC for 2030 and 2050. Landsat 2010 and 2015 and Sentinel 2A images from 2020 were employed for deriving LULC maps using Random Forest. This study applied a Land change modeler (LCM) under the multi-layer perception Markov chain (MLP-MC) to predict the future LULC in three scenarios. The scenarios are business as usual (BAU), protecting paddy fields (PPF), and protecting forest areas (PFA). The results showed that all the LULC maps demonstrated excellent accuracy, indicated by >83% overall accuracy. Furthermore, BAU produces the worst effect of decreasing forest and paddy field areas. PPF tends to cause forest loss, while PFA is predicted to reduce the paddy fields. There is a trade-off between maintaining food security and conserving natural resources. The study reveals the importance of efficient land use planning in the future amidst increasing resource demand due to population growth while existing land resources are limited.
Ecosystem-based adaptation to climate change impacts, such as shoreline retreat, has been promoted at the international, national, and even local levels. However, among scientists, opinions about how ...to implement it in spatial-planning practices are varied. Science-based environmental factors, human wellbeing, and sustainable development can be strengthened by developing spatial-planning-based ecosystem adaptations (SPBEAs). Therefore, this article aims to assess how the SPBEA model can be developed within an area prone to shoreline retreat. A coastal area of the Sayung subdistrict in Central Java, Indonesia, was selected as a study area because it has experienced a massive shoreline retreat. A multicriteria analysis (MCA) method was employed for developing the model by using the geographic information system (GIS) technique of analysis, divided into three steps: the fishpond zone determination, which involved the analytical hierarchy process (AHP) method in the process of model development; the fishpond site determination; SPBEA fishpond site development. The results show that the SPBEA model is the best practice solution for combatting shoreline retreat because of tidal waves and/or sea-level rise. The spatial site management should empower the coastal protection zone and the sustainable fishpond zone by implementing a silvofishery approach.
Many countries, including Indonesia, face severe water scarcity and groundwater depletion. Monitoring and evaluation of water resources need to be done. In addition, it is also necessary to improve ...the method of calculating water, which was initially based on a biophysical approach, replaced by a socio-ecological approach. Water yields were estimated using the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model. The Ordinary Least Square (OLS) and geographic weighted regression (GWR) methods were used to identify and analyze socio-ecological variables for changes in water yields. The purpose of this study was: (1) to analyze the spatial and temporal changes in water yield from 2000 to 2018 in the Citarum River Basin Unit (Citarum RBU) using the InVEST model, and (2) to identify socio-ecological variables as driving factors for changes in water yields using the OLS and GWR methods. The findings revealed the overall annual water yield decreased from 16.64 billion m3 year-1 in the year 2000 to 12.16 billion m3 year-1 in 2018; it was about 4.48 billion m3 (26.91%). The socio-ecological variables in water yields in the Citarum RBU show that climate and socio-economic characteristics contributed 6% and 44%, respectively. Land use/Land cover (LU/LC) and land configuration contribution fell by 20% and 40%, respectively.The main factors underlying the recent changes in water yields include average rainfall, pure dry agriculture, and bare land at 28.53%, 27.73%, and 15.08% for the biophysical model, while 30.28%, 23.77%, and 10.24% for the socio-ecological model, respectively. However, the social-ecological model demonstrated an increase in the contribution rate of climate and socio-economic factors and vice versa for the land use and landscape contribution rate. This circumstance demonstrates that the socio-ecological model is more comprehensive than the biophysical one for evaluating water scarcity.
Many coastal areas and infrastructure suffered from unprecedented hazards such as storms, flooding, and erosion. Thus, it is increasing the vulnerability of urban coastal areas aggravated with the ...absence of coastal green infrastructure. Given the state of coastal environments, there is a genuine need to appraise the vulnerability of coastal cities on the basis of the latest projected climate scenarios and existing condition. Hence, to asses, the vulnerability level of Mataram coastal, the Coastal Vulnerability Index (CVI) accompanied by pre-assessment of readiness to climate disruption. The CVI used to map coastal into five classes of using GIS. As a case study, this approach applied to Mataram City: one of the tourism destinations in Lombok. Two of sub-districts in Mataram City, Ampenan and Sekarbela, laying in the shorelines have undergone coastal flooding and erosion. One of them, Ampenan sub-district, experienced flooding due to river-discharge and became the most severe location during inundation. Results indicated that along ±9000 meters of Mataram coast possess vulnerability level in moderate to very high-risk level. The assessment also showed that sea-level rise is not the only critical issue but also geomorphology and shoreline changes, the existence of green infrastructure, also human activity parameters took important part to be assessed.
Climate change has a greater effect on the long-term viability of coastal environments and people’s livelihood. The idea of using ecosystems to help people deal with the effects of climate change is ...becoming more common at the international, national, and local levels, especially when it comes to spatial planning. So, learning about spatial planning-based ecosystem adaptation (SPBEA) is important for early careers because they will be the ones who have to deal with the decisions made now. Coastal communities must also understand the steps they can take to lessen the effects of coastal disasters in their area. This study looks at how the SPBEA concept can be taught to early-career practitioners and coastal communities through training and workshops, and the effectiveness of online training in transferring knowledge. The method of training used the hybrid method for comparison. A hierarchical approach was taken, starting from the compilation of SPBEA teaching materials, followed by SPBEA training for early-career practitioners to generate SPBEA zoning and transferring the training results to the coastal communities. Online training is not as good as offline one, but it was advantageous for the participants. Indeed, the pond-farming community was excited about the implementation of SPBEA.
Abstract
Sayung Subdistrict, Demak Regency is a low-lying coastal area prone to coastal flooding. This coastal area’s flood susceptibility is not influenced by a single factor, but by the combined ...effect of excessive rainfall, the morphological characteristics of coastal areas, and tidal waves. As a reason, the objectives of this study were to (1) map coastal flood-prone areas using a combination of heavy rainfall and tidal waves; (2) determined the extent of inundation; and (3) provide feedback on potential flood-affected area management. The findings indicate inundation has increased by 2.4% per year. Therefore, the evaluation of the mitigation management has to be considered either on local communities’ perspective, regional and national government planning and non-government implementation. Local communities, with or without the assistance of NGO and regional governments, adapt their mitigation strategies to the changing environment, whether through physical, economical, or social approaches. Meanwhile, the regional and national governments’ management will be incorporated into the detailed spatial planning.
Changes in climate and land use land cover (LULC) are important factors that affect water yield (WY). This study explores which factors have more significant impact on changes in WY, spatially and ...temporally, within the Citarum River Basin Unit (RBU), West Java Province, Indonesia with an area of ±11.317 km2. The climate in the area of Citarum RBU belongs to the Am climate type, which is characterized by the presence of one or more dry months. The objectives of the study were: (1) To estimate a water yield model using integrated valuation of ecosystem services and tradeoffs (InVEST), and (2) to test the sensitivity of water yield (WY) to changes in climate variables (rainfall and evapotranspiration) and in LULC. The integration of remote sensing (RS), geographic information system (GIS), and the integrated valuation of ecosystem services and tradeoffs (InVEST) approach were used in this study. InVEST is a suite of models used to map and value the goods and services from nature that sustain and fulfill human life. The parameters used for determining the WY are LULC, precipitation, average annual potential evapotranspiration, soil depth, and plant available water content (PAWC). The results showed that the WY within the territory of Citarum RBU was 12.17 billion m3/year, with mean WY (MWY) of 935.26 mm/year. The results also show that the magnitude of MWY in Citarum RBU is lower than the results obtained in Lake Rawa Pening Catchment Areas, Semarang Regency and Salatiga City, Central Java (1.137 mm/year) and in the Patuha Mountain region, Bandung Regency, West Java (2.163 mm/year), which have the same climatic conditions. The WY volume decreased from 2006, to 2012, and 2018. Based on the results of the simulation, climatic parameters played a major role affecting WY compared to changes in LULC in the Citarum RBU. This model also shows that the effect of changes in rainfall (14.06–27.53%) is more dominant followed by the effect of evapotranspiration (10.97–23.86%) and LULC (10.29–12.96%). The InVEST model is very effective and robust for estimating WY in Citarum RBU, which was indicated by high coefficient of determination (R2) 0.9942 and the RSME value of 0.70.
One of data resources for hydrologic modelling is Digital Elevation Model (DEM). In hydrologic modelling, watershed delineation is an important step to create boundary of inundation area, so that DEM ...plays a significant role in watershed model. Nowadays, there are many sources of DEM data available in Indonesia that was provided by Geospatial Information Agency (BIG), including LiDAR and DEMNAS (National DEM). Based on its resolution, DEMNAS is classified as data for medium scale mapping, while LiDAR is used for large scale mapping. For hydrological modelling, medium scale data has been widely applied, while the large-scale hydrological modelling is still limited. The availability of large-scale data is quite large, including the City of Mataram, is a good source to examine its effect for hydrological modelling, so this research is conducted to see the effects of DEM sources, namely LiDAR and DEMNAS, for watershed model generation. Analysis is conducted by comparison to existing official watershed in that area. From seven watersheds, LiDAR produce better geometry in four areas, while DEMNAS is better in the rest. This research is expected to support a policy relating hydrological modelling at large scale.
Yuliana E, Hewindati YT, Winata A, Djatmiko WA, Rahadiati A. 2019. Diversity and characteristics of mangrove vegetation in Pulau Rimau Protection Forest, Banyuasin District, South Sumatra, Indonesia. ...Biodiversitas 20: 1215-1221. The purpose of the study was to analyze the flora diversity and characteristics of mangrove vegetation in Pulau Rimau Protection Forest, Banyuasin District, South Sumatra. Data collected were the number and girth diameter of mangrove tree species, and aquatic ecology parameters using transect method. The sample plots size were 2m×2 m; 5m×5 m; 10m×10 m; for seedling, sapling, and tree, respectively. The observation plots were arranged in a row of 120 m length on two sides of the forest edge, namely Calik Riverbank and Banyuasin Riverbank. Data were analyzed using importance value index (IVI), Simpson’s diversity index and Sørensen’s community similarity. The study revealed that there were differences in mangrove characteristics in two study sites. There were 57 plant species identified inside and outside sample plots, but only 15 species (26.32%) among them were categorized as true mangrove species. Inside the sample plots, there were 11 and 10 mangrove tree species recorded on the Calik Riverbank and Banyuasin Riverbank, respectively, but only 7 species among them were found in both sites. The mangroves on Calik Riverbank were dominated by Nypa (IVI 53.59%) and Bruguiera (51.12%), while those on Banyuasin Riverbank were dominated by Sonneratia (66.91%) and Avicennia (51.73%). The Simpson’s diversity index for Calik Riverbank and Banyuasin Riverbank was 0.82 and 0.78, respectively, whereas the Sørensen’s coefficient of community between the two sites was 0.67.
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