Human activities have led to changes in land use, environmental conditions and climate. Land use change has significant impacts on hydrology and other water related problems. In this study, the assessment of land use change is used to explore the effects of human activities on hydrologic response under the paleo-environment and the present conditions by using a grid-based distributed hydrologic model. According to the results of land use change analysis, forest area decreased, but the areas of building types A and B increased from 1843 to 1902. Due to increasing building area and decreasing forest area and rice fields, the peak discharge is increasing and arriving earlier. Projected rainfall-runoff hydrographs suggest that rainfall may peak early (in the third hour) leading to earlier peak discharge or rainfall could peak later (in the eighth hour), leading to larger and later peak discharge. This study offers guidance for future urban planning and flood risk management.

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 Menjer lake is the main source for Hydroelectric Power Plant of the PLTA Garung. Information about the water balance and the potential of existing water resources in the Menjer Catchment Area (DTA) is needed to obtain an efficient operating pattern, the sustainability of the Garung hydropower plant, and good management of the Menjer Lake. The purpose of this study was to estimate the inflow of three main rivers in the Menjer catchment area using HEC-HMS hydrological and water balance approach. Simulated results of the HEC-HMS model shows that the average of total the inflows of three main rivers to the Menjer lake in 2017, 2018 and 2019 during rainy season are 0.954 m3/s, 0.944 m3/s, and 1.017 m3/s, and during dry season are 0.820 m3/s, 0.783 m3/s, and 0.80 m3/s, respectively. While the prediction results of the discharge with the equation of the water balance shows that the average of total river inflows to the Menjer lake during rainy season is 2017 is 1.628 m3/s, in 2018 it is 1.579 m3/s, and in 2019 it is 3.296 m3/s and during dry season is 1.893 m3/s in 2017, 1.176 m3/s tahun 2018, and 1.893 m3/s in 2019. These results indicate that the results of discharge modeling with HEC-HMS are smaller than those predicted by the water balance equation. The study concluded that HEC-HMS could be used to predict daily inflows. However, further calibration and validation need to be carried out by recommending installing a river flow monitoring station at each river outlet.Keywords: water balance HEC-HMS, inflow prediction

Many flood modelings use geovisualization techniques but are very complicated and can only be understood by researchers or practitioners. There is a need for modelings that are informative and can be understood by ordinary people for the purpose of disaster mitigation. This research analyzed a flood modeling geovisualization sample to find out the extent to which aesthetic values are used in that modeling. For breaking down the modeling, an analytical approach was used as well as physioplastic, ideoplastic, and judgment analyses. Then, the modeling was evaluated through a questionnaire that was distributed using Google Forms to 40 respondents with a background as visual communication design students. The questionnaire was presented using closed questions and a visual analogue scale. The aesthetic parameters used for measuring were: lighting, color, two-dimensional field, three-dimensional field, time/motion, and sound. The evaluation results showed that the flood modeling geovisualization sample did not use aesthetics effectively. Modeling representations need to be simplified into visualizations using a well-planned aesthetic concept to make them more informative. Hopefully, the result of this research will make flood modeling more impactful and easier to understand by ordinary people through the application of aesthetic values such as those addressed in the questionnaire.