Changes in bioclimatic indicators can provide valuable information on how global warming induced climate change can affect humans, ecology and the environment. Trends in thermal bioclimatic indicators over the diverse climate of Iran were assessed in this study to comprehend their spatio-temporal changes in different climates. The gridded temperature data of Princeton Global Meteorological Forcing with a spatial resolution of 0.25° and temporal extent of 1948–2010 was used for this purpose. Autocorrelation and wavelets analyses were conducted to assess the presence of self-similarity and cycles in the data series. The modified version of the Mann–Kendall (MMK) test was employed to estimate unidirectional trends in 11 thermal bioclimatic indicators through removing the influence of natural cycles on trend significance. A large decrease in the number of grid points showing significant trends was noticed for the MMK in respect to the classical Mann–Kendall (MK) test which indicates that the natural variability of the climate should be taken into consideration in bioclimatic trend analyses in Iran. The unidirectional trends obtained using the MMK test revealed changes in almost all of the bioclimatic indicators in different parts of Iran, which indicates rising temperature have significantly affected the bioclimate of the country. The semi-dry region along the Persian Gulf in the south and mountainous region in the northeast were found to be more affected in terms of the changes in a number of bioclimatic indicators.

A fully analytical 1-D salt intrusion model which is simple to implement and requiring minimal data, was tested in six previously un-surveyed Malaysian estuaries (Kurau, Perak, Bernam, Selangor, Muar and Endau). The data required for this method can be collected during a single day of observations. Site measurements were conducted in these estuaries during the dry season (June-August 2012 and February-March 2013) near spring tide. Data on cross-sections (by echosounding), water levels (by pressure loggers) and salinity (by moving boat) were collected as input to the 1-D salt intrusion model. This paper demonstrates a good fit between the simulated and observed salinity distribution for all six estuaries. Additionally, the two calibration parameters (the Van der Burgh’s coefficient and the boundary condition for the dispersion) were compared with the existing predictive equations. Since gauging stations were only present in some nested catchments in the drainage basins, the river discharge had to be up-scaled to represent the total discharge contribution of the catchments. Subsequently, the correspondence between the calibration coefficients and the predictive equations was good, particularly in view of the uncertainty in the river discharge data used. This confirms that the predictive salt intrusion model is valid for the cases studied in Malaysia. The model provides a reliable predictive instrument which the water authority of Malaysia can use for making decisions on water abstractions or dredging