Pakistan is vulnerable to a range of climate hazards, including sea-level rise. The Indus Delta region, situated in the coastal Sindh province, is particularly at risk of sea-level rise due to low-lying land and fragile ecosystems. In this article, expertise is drawn together from the newly established Pakistan Sea-Level Working Group, consisting of policy experts, scientists, and practitioners, to provide recommendations for future research, investment, and coastal risk management. An assessment of the current scientific understanding of sea-level change and coastal climate risks in Pakistan highlights an urgent need to improve the availability and access to sea-level data and other coastal measurements. In addition, reflecting on the policy environment and the enablers needed to facilitate effective responses to future sea-level change, recommendations are made to integrate coastal climate services into the National Adaptation Plan and develop a National Framework for Climate Services. Such a framework, alongside collaboration, co-production, and capacity development, could help support required improvements in coastal observations and monitoring and continuously deliver useful, usable, and accessible sea-level information for use by practitioners and decision-makers.

In this study, the analysis of the extreme sea level was carried out by using 10 years (2007–2016) of hourly tide gauge data of Karachi port station along the Pakistan coast. Observations revealed that the magnitudes of the tides usually exceeded the storm surges at this station. The main observation for this duration and the subsequent analysis showed that in June 2007 a tropical Cyclone “Yemyin” hit the Pakistan coast. The joint probability method (JPM) and the annual maximum method (AMM) were used for statistical analysis to find out the return periods of different extreme sea levels. According to the achieved results, the AMM and JPM methods erre compatible with each other for the Karachi coast and remained well within the range of 95% confidence. For the JPM method, the highest astronomical tide (HAT) of the Karachi coast was considered as the threshold and the sea levels above it were considered extreme sea levels. The 10 annual observed sea level maxima, in the recent past, showed an increasing trend for extreme sea levels. In the study period, the increment rates of 3.6 mm/year and 2.1 mm/year were observed for mean sea level and extreme sea level, respectively, along the Karachi coast. Tidal analysis, for the Karachi tide gauge data, showed less dependency of the extreme sea levels on the non-tidal residuals. By applying the Merrifield criteria of mean annual maximum water level ratio, it was found that the Karachi coast was tidally dominated and the non-tidal residual contribution was just 10%. The examination of the highest water level event (13 June 2014) during the study period, further favored the tidal dominance as compared to the non-tidal component along the Karachi coast.

Algal bloom is a condition in which there is a massive growth of algae in a certain region and it is said to be harmful when the bloom causes damage effects. Due to the tremendous impact of harmful algal bloom (HAB) on some aspects, this research proposes the mathematical modelling of an HAB model to describe the process of HAB together with population dynamics. This research considers the delay terms in the modelling since the liberation of toxic chemicals by toxin-producing phytoplankton (TPP) is not an instantaneous process in which the species need to achieve their maturity. A model of fish interaction is also being studied to show the effect of HAB on fish species. Time delay is incorporated for the mortality of fish due to the consumption of toxic zooplankton. Stability analysis is conducted and numerical simulations are applied to obtain the analytical results which highlight the critical values for the delay parameters. The existence of Hopf bifurcation is established when the delay passes the threshold value. The results of both models show that the inclusion of the delay term affects the model by stabilizing and destabilizing the model. Therefore, this research shows the effect of an inclusion delay term on the model and also gives knowledge and an understanding of the process of HAB occurrence as well as the effect of HAB on fish populations.