Many watersheds in Hawai‘i are flash flood prone due to their small contributing areas and frequent intense rainfall. Motivated by the possibility of developing an operational flood forecasting system, this study evaluated the performance of the National Weather Service (NWS) model, the Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM) in simulating the hydrology of the flood-prone Hanalei watershed in Kaua‘i, Hawai‘i. Application of HL-RDHM to Hanalei watershed required i) modifying the Hydrologic Rainfall Analysis Project (HRAP) coordinate system; ii) generating precipitation grids from rain gauge data, and iii) generating parameters for Sacramento Soil Moisture Accounting Model (SAC-SMA) and routing parameter grids for the modified HRAP coordinate system. For selected time periods, the performance of HL-RDHM was satisfactory even without calibration for basin-averaged and distributed a priori parameter grids. The model reasonably matched the observed peak discharges and time to peak during calibration and validation periods suggesting that HL-RDHM may be suitable for flood forecasting applications in Hawai‘i. This presentation will also discuss on Irrigation Water Requirement Estimation Decision Support System (IWREDSS) Model for Texas. The quantity of water required for different agricultural crops at different locations under different irrigation system is required for the planning of agricultural water-supply development. GIS-based model for estimating irrigation water requirement for different crops is becoming more popular in recent years due to availability of spatially distributed data (e.g. soil, rain, evapotranspiration etc.). Among different models, IWREDSS was developed to estimate crop irrigation requirements for consumptive use permitting in Hawai‘i in 2008 and updated in 2013. This presentation will highlight the capability of IWREDSS for the state of Texas.