Complex topography and wind characteristics play important roles in rising air masses and in daily spatial distribution of the precipitations in complex region. As a result, its spatial discontinuity and behaviour in complex areas can affect the spatial distribution of precipitation. In this work, a two-fold concept was used to consider both spatial discontinuity and topographic and wind speed in average daily spatial precipitation estimation using Inverse Distance Weighting (IDW) and Multiple Linear Regression (MLR) in tropical climates. First, wet and dry days were identified by the two methods. Then the two models based on MLR (Model 1 and Model 2) were applied on wet days to estimate the precipitation using selected predictor variables. The models were applied for month wise, season wise and year wise daily averages separately during the study period. The study reveals that, Model 1 has been found to be the best in terms of categorical statistics, R2 values, bias and special distribution patterns. However, it was found that sets of different predictor variables dominates in different months, seasons and years. Furthermore, necessities of other data for further enhancement of the results were suggested.

Topographic LIDAR can be used to estimate elevation values for dry areas down to the river water level during the extraction of river cross-sections (XS). However, LIDAR cannot accurately predict the submerged topography, which causes uncertainty in river XS area estimation. This uncertainty affects the channel water level and flood inundation depth estimation in in situ sparse data. Therefore, an alternative approach is presented to estimate unknown submerged topography (UST) using topographic LIDAR. The one dimension/two dimension Hydrologic Engineering Center River Analysis System (1D/2D HEC-RAS) model is used to simulate the estimated river XS with the help of in situ river water level and flow data which is later validated using in situ data. The results show that the proposed approach accurately estimates water level (error >0.5 m), channel flow areas, and floodplain water depths. Notably, the extent of the estimated floodplain overflow by UST models was in 94% agreement with the real XS.

Flooding is the most serious natural disaster and often happens in many countries around the world. Dabong Town which is located in the southern district of Kuala Krai, Kelantan was the case study of this research. Floods occur periodically at Kampung Dabong Hulu, Kampung Dabong Hilir and Kampung Chegar Lapan because of the heavy rainfall during the monsoon season. The main objective of this study is to determine which areas are exposed to floods and characterizing the flood zones in the Dabong Town by using Geographic Information System (GIS). Secondary data was gathered from the Department of Irrigation and Drainage while field investigations were conducted at the flooded area. Several questionnaires were distributed to the respondents in order to identify the extent of floods and depth of flooded areas. The results show that three parameters of flood hazards level which are low, medium and high have significant influences on the river flood hazard maps pattern. The area along the Galas River possessed high risk to flood and the total of the high hazard area is 378.39 hectares. Medium hazard area is shown as 57.11 hectares while low hazard area is 37.63 hectares.