Hydrological models are reliable tools that have been extensively used for hydrological studies. However, the complexity of some of these models has been a major setback, which affects their performance. This study compared Hydrologic Engineering Corps Hydrologic Modeling System (HEC-HMS) with most widely applied Soil Water Assessment Tool (ArcSWAT) model and used to assess impacts of climate change on streamflow at Bernam Basin, Malaysia for 2010-2039, 2040-2069 and 2070-2099 to the baseline period (1976- 2005) using an ensemble of ten GCMs under three RCP scenarios (RCPs 4.5, 6.0 and 8.5). The models performed satisfactorily. However, HEC-HMS performed better compared to ArcSWAT with 0.74, 0.71, 4.21 and 0.37; and 0.71, 0.69, 5.32 and 0.31 for R2 , NSE, PBIAS and RSR, respectively, during the calibration and validation periods. Future periods suggest a decreasing pattern in streamflow, with a higher percentage (−5.94%) expected for the RCP 8.5 scenario in the late century (2080s) during dry season period. In the wet season, streamflow decreases in all future periods except for RCP4.5 where it is expected to increase (0.36%). Therefore, the Basin may likely experience tremendous pressure in the late century due to low streamflow, particularly in dry season months.
In order to ensure the optimum quality of palm oil, oil palm fruit needs to be harvested at the optimum maturity to avoid free fatty acid (FFA) accumulation. The high content of FFA not only reduces the quality of palm oil but also increases the refining cost. Optimum maturity based on plantation standard operating procedure (SOP) is determined by identifying the tree with loose fruit on the ground. The matured bunch is further identified based on the colour of the bunch. This paper presents a research work on formulation and validation of mathematical equations to estimate the maturity stages (age in weeks) of fresh fruit bunch (FFB) based on FFB position in oil palm phyllotaxis (spiral leaves arrangement) as an additional feature to confirm the maturity level of oil palm FFB. Regression analysis showed that the proposed method was able to estimate the maturity stages of oil palm FFB with the coefficient of determination R2 = 0.9 and a root mean square error (RMSE) of 1.58 weeks. The FFB yield estimation model and harvesting can be created based on the extracted data using the formula which will help in the planning of harvesting operation. Plantation manager can use this information to generate yield variability map and estimate the appropriate number of workers and machine. Planned harvesting operation can save a significant amount of time in site harvesting operation.