Satellite radar altimetry technology is used to monitor oceans and inland waters. However, inland monitoring is still in the development phase. New technologies and advanced algorithms are introduced to improve data accuracies at broader scales. Today's challenge is to ascertain altimetry usefulness at least at a regional level. This study compares satellite radar altimetry-derived inland water heights with in-situ data in Pakistan. Tarbela reservoir (mountainous region) and Guddu barrage (flat topography) on Pakistan's Indus River were selected, having extended altimetry and in-situ data time series. Gauge measurements from irrigation departments were acquired to evaluate altimetry products from the multi-satellite mission Database for Hydrological Time Series of Inland Waters (DAHITI). DAHITI includes data from satellites Jason 2 and 3 at Tarbela, Envisat, Saral, and Sentinel 3A at downstream Guddu barrage. The evaluation periods are 2013–2020 for Tarbela reservoir and 2002–2020 for Guddu barrage, depending on the common availability of datasets. Statistically higher correlations were found for both cases ranging from 0.98 to 0.88 except for one dataset $\mathrm{R}=0.45$ for Saral at Guddu). The root-mean-square error (RMSE) between in-situ and altimetry datasets at the Tarbela reservoir was much higher (340 to 531 cm) than the submeter errors (22–32 cm) at the Guddu barrage (Saral at Guddu gave a higher RMSE of 118 cm). Differences in satellite missions, data acquisition times, reference geoids, data processing methods, and topography may be the possible causes of these errors. While a more detailed investigation is required considering the inconsistencies of the datasets and the study sites (river vs. reservoir), it can be concluded that accuracies of altimetry derived Indus River water levels are better in flat areas than in the mountainous regions.

This study aims to assess the correlation between the satellite radar altimetry derived water level heights and in-situ gauges on the Indus River. The in-situ gauge data at Guddu Barrage was acquired from the Sindh Irrigation Department and its outliers were removed using the interquartile method. Altimetry derived water levels near the Guddu Barrage in Sindh, Pakistan were taken from various databases such as Database for Hydrological Time Series of Inland Waters (DAHITI), Hydroweb from 17 July 2008 to 20 Nov 2018, and SARvatore (SAR Versatile Altimetric Toolkit for Ocean Research & Exploitation) for Sentinel-3. The altimetry datasets were plotted against the in-situ gauge data and analysed visually as well as statistically. The regression analyses run yielded an R ² value of around 0.6 for DAHITI and Hydroweb whereas for SARvatore it was 0.1. RMSE values produced were 0.5m, 0.6m and 0.9m respectively for Hydroweb, DAHITI and SARvatore.

This study aims to assess the impact of the 2010–2011 flash floods on the crop production of Sanghar—an eastern district of Sindh. The population of almost two million is mainly dependent on agriculture. Cotton, sugarcane, and wheat are the main cash crops of the district. In 2010–2011 Sanghar was hit by flash floods after heavy rainfall. These floods adversely affected the crops standing at that time. However, on the other hand, they increased the fertility of agricultural lands. Satellite images, precipitation data, and geographical information system (GIS) tools were used to quantify floods’ effects by mapping pre- and post-flood vegetation cover. Supervised classification was applied on Landsat images from 2009 to 2013 to extract vegetation area. The temporal analysis unveils a significant increase in the vegetation cover in the post-flood years. Furthermore, the comparison between pre-and post-flood crop production data collected from the Pakistan Bureau of Statistics also validated the study results by revealing an increase in crop production.

The rising temperature due to climate change leads to glaciers melting, causing increased sea levels and sea surface temperatures (SST). The rising SST and glacier melting elevate sea levels around the globe. The rising sea level is hazardous for the coastal regions worldwide, and therefore, calls for continuous monitoring to manage this threat. Pakistan, with a coastline of 990 km long, is among those countries most vulnerable to sea-level rise (SLR). Around 10% of Pakistan's population lives near the coastal zones, which are most marginalized and dependent on fishing and small agricultural farms. An SLR of a few millimeters per year is a serious threat to Pakistan's coastal areas that can, directly and indirectly, cause land loss of low-lying areas and destruction of infrastructures, human settlements, agriculture lands, and coastal ecosystems and other resources. The coastal communities of developing countries such as Pakistan, lacking essential resources, are the most disadvantageous and adversely affected people of the world due to these disasters. To overcome resources and capacity constraints, remote sensing (RS) and GIS techniques can employ to monitor coastal zones at larger extents. In this study, SLR and SST around the coast of Karachi have been investigated using multi-mission satellite radar altimetry (SRA) and MODIS Terra L3 SST product. The SRA is used to monitor sea levels using data from 1993 to 2018. Similarly, monthly SST data from 2000 to 2019 have been acquired to monitor SST trends. The rises in sea levels and temperatures were estimated as 3.9 mm/year and 0.0138 °C/year respectively. Different extrapolation techniques can further be utilized to predict the potential of SLR and SST in the study area for developing future coastal zone management plans.

The most popular and beautiful spot of Urak valley— Hanna Lake, situated in the capital city Quetta (Balochistan, Pakistan), is shrinking affecting the surrounding environment and lake’s ecosystem. Lake completely dried thrice since 2001. One of the most stated reasons is a shortage of rainfalls due to climate change. Pakistan is ranked on 7th position in the list of most vulnerable countries to climate change with 141 extreme weather events. Linking lake drying to climate change seems to be an obvious connection in the absence of required historical records regarding temporal changes in the lake’s surface area and volume. Researching precise reasons is crucial to find appropriate solutions. This study took advantage of satellite-derived data to overcome the gap between recorded information. Changing lake surface areas from satellite images were compared with National Oceanic and Atmospheric Administration (NOAA) rainfall records since 1984 to study any interconnection between them. It was found that since 2002, rainfall trend increases, whereas, lake area decreases. This gives rise to the impression that climate change has not caused any drop in lakes and other water bodies.