The rapid development of Satellite Precipitation Products (SPPs) has heightened the need for a hydro-meteorological assessment of the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) products in different climate and geographical regions. Reliability of the IMERG early (IMERG_E), late (IMERG_L) and final (IMERG_F) run products in precipitation estimations was evaluated over the Kelantan River Basin, Malaysia from 12 March 2014 to 31 December 2016. The three IMERG products were then incorporated into a calibrated Soil and Water Assessment Tool (SWAT) model to assess their reliability in streamflow simulations. Overall, monthly precipitation variability is well captured by the three SPPs. The IMERG_F exhibited a smaller systematic bias (RB = 7.14%) compared to the IMERG_E (RB = −10.42%) and IMERG_L (RB = −17.92%) in daily precipitation measurement. All the three SPPs (NSE = 0.66~0.71 and R² = 0.73~0.75) performed comparably well as precipitation gauges (NSE = 0.74 and R² = 0.79) in the daily streamflow simulation. However, the IMERG_E and IMERG_L showed a significant underestimation of daily streamflow by 27.6% and 36.3%, respectively. The IMERG_E and IMERG_F performed satisfactory in streamflow simulation during the 2014–2015 flood period, with NSE and R² values of 0.5~0.51 and 0.62~0.65, respectively. With a better peak flow capture ability, the IMERG_F outperformed the near real-time products in cumulative streamflow measurement. The study has also shown that the point-to-pixel or pixel-to-pixel comparison schemes gave comparable conclusions. Future work should focus on the development of a standardized GPM hydro-meteorological assessment framework, so that a fair comparison among IMERG validation studies can be conducted.

Trends in precipitation and temperature extremes of the Muda River Basin (MRB) in north-western Peninsular Malaysia were analyzed from 1985 to 2015. Daily climate data from eight stations that passed high quality data control and four homogeneity tests (standard normal homogeneity test, Pettitt test, Buishand range test, and von Neumann ratio test) were used to calculate 22 Expert Team on Climate Change Detection and Indices (ETCCDI) extreme indices. Non-parametric Mann–Kendall, modified Mann–Kendall and Sens’ slope tests were applied to detect the trend and magnitude changes of the climate extremes. Overall, the results indicate that monthly precipitation tended to increase significantly in January (17.01 mm/decade) and December (23.23 mm/decade), but decrease significantly in May (26.21 mm/decade), at a 95% significance level. Monthly precipitation tended to increase in the northeast monsoon, but decrease in the southwest monsoon. Mann–Kendall test detected insignificant trends in most of the annual climate extremes, except the extremely wet days (R99p), mean of maximum temperature (TXmean), mean of minimum temperature (TNmean), cool days (TX10p), cool nights (TN10p), warm days (TX90p) and warm nights (TN90p) indices. The number of heavy (R10mm), very heavy (R20mm), and violent (R50mm) precipitation days changed at magnitudes of 0~2.73, −2.14~3.33, and −1.67~1.29 days/decade, respectively. Meanwhile, the maximum 1-day (Rx1d) and 5-day (Rx5d) precipitation amount indices changed from −10.18 to 3.88 mm/decade and −21.09 to 24.69 mm/decade, respectively. At the Ampangan Muda station, TNmean (0.32 °C/decade) increased at a higher rate compared to TXmean (0.22 °C/decade). The number of the cold days and nights tended to decrease, while an opposite trend was found in the warmer days and nights.

Drastic growth of urban populations has caused expansion of peri-urban areas—the transitional zone between a city and its hinterland. Although urbanisation may bring economic opportunities and improve infrastructure in an area, uncontrolled urban expansion towards peri-urban areas will negatively impact the environment and the community living within the area. Malaysia, for example, has become one of the most urbanised countries in East Asia. However, cities in Malaysia are relatively small and less densely populated compared with other cities in East Asia. This indicates that urban expansion has been sprawling towards peri-urban areas, and not being controlled and properly managed. To ensure urban expansions occur sustainably, urban growth boundary (UGB) can potentially be used as a mechanism to contain and limit urban expansion, and allow urban growth to be planned to achieve sustainable development. A scientific approach is essential to determine an UGB that allows future growth to be predicted and taken into consideration. Potentially, urban spatial models have been widely used to plan and predict future urban expansions. George Town Conurbation, the second largest urban conurbation in Malaysia, has been chosen as the study area in this study. This study aims to demonstrate the application of a GIS-Cellular Automata model, known as FutureSim, which was developed to simulate land cover changes and generate a designated UGB for this area. The model was developed based on the transition rule derived from land cover changes, from 2010 to 2018, and then used to predict future land cover changes under two different planning scenarios—compact growth and urban sprawl scenarios. With the accuracy of the model exceeding 74%, FutureSim was used to predict land cover change until 2030. The model can potentially be used to assist planners and policymakers to make decisions on the allocation of sustainable land use and planning for rapidly developing regions.

This study introduces a hydro-climatic extremes assessment framework that combines the latest climate simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6) HighResMIP with the Soil and Water Assessment (SWAT) model, and examines the influence of the different climate model resolutions. Sixty-six hydrological and environmental flow indicators from the Indicators of Hydrologic Alteration (IHA) were computed to assess future extreme flows in the Kelantan River Basin (KRB), Malaysia, which is particularly vulnerable to flooding. Results show that the annual precipitation, streamflow, maximum and minimum temperatures are projected to increase by 6.9%, 9.9%, 0.8 °C and 0.9 °C, respectively, by the 2021–2050 period relative to the 1985–2014 baseline. Monthly precipitation and streamflow are projected to increase especially for the Southwest Monsoon (June–September) and the early phase of the Northeast Monsoon (December) periods. The magnitudes of the 1-, 3-, 7-, 30- and 90-day minima flows are projected to increase by 7.2% to 8.2% and the maxima flows by 10.4% to 28.4%, respectively. Lastly, changes in future hydro-climatic extremes are frequently quite different between the high-resolution and low-resolution models, e.g., the high-resolution models projected an increase of 11.8% in mean monthly flow in November-December-January compared to 3.2% for the low-resolution models.