The shoreline of Malaysia is exposed to threats of coastal erosion and a rise of sea level. The National Coastal Erosion Study, 2015 reported that 15% of an 8840 km shoreline is currently eroding, where one-third of those falls under the critical and significant categories that require structural protection. The Study of Sea Level Rise in Malaysia, 2017 presented a sea-level increase of 0.67–0.74 mm on average yearly. This study reviewed selected coastal protection structures along the shoreline of Malaysia as an erosion control and sea-level rise adaptation based on coastal management strategies. Hard structures such as rock revetment and breakwater are commonly used as erosion protection systems in the “hold the line” strategy. Increased platform level of seawalls and earth bunds, considered as an “adaptation” approach, are effective in erosion protection and are adaptive to sea-level rise. Mangrove replanting is suitable as a “limited intervention” approach in minimizing the long-term impact of both threats. However, offshore breakwater, groyne, and geotextile tubes are solely for protection purposes and are not as effective for sea-level rise adaptation. As the sea level is continuously increasing, their function as coastal protection will also become less effective. In summary, this comprehensive review on coastal protection in Malaysia will benefit the related agencies on the future assessment.

The hydrological regimes of watersheds might be drastically altered by climate change, a majority of Pakistan's watersheds are experiencing problems with water quality and quantity as a result precipitation changes and temperature, necessitating evaluation and alterations to management strategies. In this study, the regional water security in northern Pakistan is examined about anthropogenic climate change on runoff in the Kunhar River Basin (KRB), a typical river in northern Pakistan using Soil and Water Assessment tool (SWAT) and flow durarion curve (FDC). Nine general circulation models (GCMs) were successfully utilized following bias correction under two latest IPCC shared socioeconomic pathways (SSPs) emission scenarios. Correlation coefficients (R²), Nash-Sutcliffe efficiency coefficients (NSE), and the Percent Bias (PBIAS) are all above 0.75. The conclusions demonstrate that the SWAT model precisely simulates the runoff process in the KRB on monthly and daily timescales. For the two emission scenarios of SSP2-4.5 and SSP5-8.5, the mean annual precipitation is predicted to rise by 3.08 % and 5.86 %, respectively, compared to the 1980–2015 baseline. The forecasted rise in mean daily high temperatures is expected to range from 2.08 °C to 3.07 °C, while the anticipated increase in mean daily low temperatures is projected to fall within the range of 2.09 °C–3.39 °C, spanning the years 2020–2099. Under the two SSPs scenarios, annual runoff is estimated to increase by 5.47 % and 7.60 % due to climate change during the same period. Future socioeconomic growth will be supported by a sufficient water supply made possible by the rise in runoff. However, because of climate change, there is a greater possibility of flooding because of increases in both rainfall and runoff. As a result, flood control and development plans for KRB must consider the climate change's possible effects. There is a chance that the peak flow will move backwards relative to the baseline.

The empirical models commonly employed as alternatives for estimating evapotranspiration provide constraints and yield inaccurate results when applied to Nigeria. This study aims to develop novel empirical models to enhance evapotranspiration (ET0) estimation accuracy in Nigeria. The coefficients of non-linear equations were optimised using the particle swarm optimisation (PSO) algorithm for the development of the two new ET0 models for Nigeria, Awhari1 (temperature-based) and Awhari2 (mass transfer-based). ERA5 reanalysis data with a 0.1° × 0.1° resolution was used. The models were rigorously assessed against the FAO-56 Penman–Monteith method, resulting in Kling–Gupta efficiency (KGE) and percentage bias (Pbias) values of 0.75, 6.49, and 0.92, 5.67, respectively. The spatial distribution analysis of performance metrics showed both equations exhibited superior accuracy in estimating ET0 across diverse climatic zones in Nigeria. The incorporation of PSO in model development, coupled with spatial analysis, highlights the study's multidimensional approach. The spatial performance of the models indicates that they can be valuable tools for water resource management, irrigation planning, and sustainable agriculture practices in Nigeria.