Due to continuous problems of eutrophication, Lake Rawa Pening has been included into the 15 priority lakes in Indonesia to be saved from damage. This study aimed to clarify the current environmental conditions and trophic status of Lake Rawa Pening as a basis to control the eutrophication. Sediment loads, water quality, and nutrient concentrations were measured in the tributaries of lake inflow, within the lake, and at the point of lake outflow. The study was conducted in May, June, July, and August 2013. Water transparency, temperature, pH, turbidity, conductivity, and dissolved oxygen were measured in situ. Nitrogen, nitrate, total phosphorus, orthophosphate, TSS, and chlorophyll-a parameters were analyzed using standard method procedures. The Trophic State Index was used to determine the trophic state level. Hydroclimatological conditions showed that seasonally, fluctuation of water volume and discharge of lake followed the pattern of rainfall fluctuation. The sediment loads and nutrient concentration in the tributary inflow were more abundant than those in the lake  and  lake outflow. The results indicated that Lake Rawa Pening acts as sediment and nutrient sinks. Spatially and temporally, Lake Rawa Pening showed high variation of water quality. High concentration of nutrients observed during the wet and dry seasons indicated that the nutrients in the lake originated not only from external but also from internal sources. The overall results show that Lake Rawa Pening is a eutrophic lake, in which phosphorus seems to play a major role in causing eutrophication and massive growth of water hyacinth. <br /><br /><br />

Many scientists assume that RCM output is directly used as input for climate change impact models, while it consists of systematic errors. Consequently, RCM still requires bias correction to be used as an input model. The purpose of this study was to analyze the RCM performance before and after bias correction, its best performance from several models, as well as to clarify the importance of bias correction before it is used to analyze climate change. As a result of this, the method used for bias correction was Distribution Mapping method (for rainfall) and Average Ratio-method (for air temperature). While the Generalized Extrem Valuedistribution (GEV) was used to analysis extreme rainfall. To determine the performance of the model before and after bias correction, statistical analysis was used namelyR2, NSE, and RMSE. Furthermore, ranking for every single model and Taylor Diagram was used to determine the best model. The results showed that the RCMs performance improved with bias correction. However, CSIRO-Mk3-6-0, CCSM4, GFDL-ESM2M, and MPI-ESM-MR models can be ignored as ensemble models, because they demonstrated poor performance in simulating rainfall. From this study, it was suggested that the best model in simulating daily and monthly rainfall was ACCESS1-0, while MIROC-ESM-CHEM (daily air temperature) and ACCESS1-0 (monthly air temperature) were best models used in simulating air temperature. Key words: RCM, bias correction, performance, rainfall, air temperature

The Batanghari River flows from the province of West Sumatra into the West Coast of Jambi, with the main river extending up to 870 km. Also, the Batanghari watershed Land use changes have shown a decreasing forest cover and an increasing agricultural area. Therefore, this study aims to calculate the impact of land use and climate change on water and sediment yield using Soil and Water Assessment Tools (SWAT) hydrological modeling. Land-use change analysis was performed with projections in 2040 while, near future and future climate projections under Representative Concentration Pathway (R.C.P.) 4.5 and 8.5 were used for global climate change scenarios. The results show a changing pattern of growing agricultural area and decreasing forest area in 1990, 1997, 2005, 2015, and 2040. SWAT hydrological model used for the simulation was calibrated automatically with SWAT-CUP and the results were validated on good criteria. The sensitivity analysis results showed that effective hydraulic conductivity in main channel alluvium (CH_K2) and Base flow alfa factor (Alfa_BF) formed the most sensitive parameters for discharge. Furthermore, the model simulation showed an increase in surface runoff and a decrease in lateral flow and base flow due to land-use changes, which increased sediment loading over time. The impact of climate change on water and sediment yield increased the average flow discharge ratio, resulting in more frequent droughts and floods events.

Sustained lake functioning requires proper catchment land and water management. To address this, quantitative information and comprehensive understanding of the spatiotemporal dynamics and hydrological budget of the lake ecosystem are required. However, measuring hydrologic components such as groundwater discharge into a freshwater body is difficult, since its direct measurements are costly, time-consuming, and hardly implemented. Therefore, this study was intended to quantify groundwater inflow to the lake through an effective approach using the water balance modeling technique. Herein, groundwater discharge and contribution were calculated as the water balance residual in terms of net groundwater inflow. It can be considered a minimum estimate of groundwater inflow, as there the groundwater outflow maybe exists but not quantifiable. The approach has been applied for Lake Maninjau which is categorized as a deep, regulated, and tecto-volcanic lake located in West Sumatra Province, Indonesia. The result indicates that the groundwater inflow slightly moderately influences the fluxes of new water volume (the region between observed lowest and highest lake water level) at the upper layer of Lake Maninjau. Its contribution was equivalent to at least 20-28% according to the assessment for the years of 2013 and 2014. Annually, the new water volume recharged from the groundwater inflow corresponded to at least 182-281 million m3. Moreover, these findings enhance a previous study stated that the terrain system of Lake Maninjau is dominated by a rare groundwater aquifer.

Coastal areas have very important roles and benefits. Unfortunately, most of them in the world are experiencing the effects of climatic changes such as rising sea levels, increasing coastal erosion, and marine intrusion. Meanwhile, there have been many studies on coastal vulnerability from various aspects and perspectives. Therefore, it is necessary to study the trend on coastal vulnerability from past historical records of several decades ago and also from the aspects that have not been studied. This study aims to identify gaps and opportunities related to coastal vulnerability to provide solutions to sustainability themes in the future. Also, there is a need for this study since it is not monotonous and contains a novel element. The method used in this review article is Web of Science (WoS) as the database source, while VOSviewer is used to visualize and analyze the Bibliometric maps. WoS is a website that provides subscription-based access to multiple databases that provide comprehensive citation data for many different academic disciplines, while VOSviewer is a software tool for constructing and visualizing bibliometric networks. The analysis shows that for over 20 years, topics related to coastal vulnerability around the world are divided into four categories, each of which shows the most frequently occurring themes, namely climate change, coastal vulnerability, sea level, and vulnerability. Subsequently, there is a gap in coastal vulnerability, which is a topic on climate change that has been rarely studied in Indonesia since 2015. This bibliometric approach is used to identify key themes in each study or scope of knowledge that has been conducted so far, which is beneficialin determining novel future research.