Climate change, as a consequence of global warming, has been a threat for a very long time, however, the recent socio-economic, environmental, and health crisis caused by the COVID-19 pandemic have led us to a point where prompt actions are needed to be taken. Water resources management (WRM) has become a major global concern due to rising population, unplanned urbanization, deforestation, frequent extreme floods and drought events, and the unequal distribution of water resources.
To mitigate the effects of climate change, it is essential to maintain the water-energy-food nexus. Water availability is highly dependent on natural resources from sapphire-blue oceans to glacier-capped mountains.
Remote Sensing and Geographic Information System (GIS) techniques provide a platform where one can relate the attributes (spatial and non-spatial) to analyze the data efficiently. It represents the landscape in the form of geo-referenced data, defining the characteristic geometry of the geographic attributes. While stepping into the corridor of the 21st century, the utility of remote sensing and GIS-techniques in various fields has made things understandable, thus enhancing the ways of investigation for better decision-making and management.
For a long time, extrapolation of data of hydrological processes were performed manually; that included hydrographs and other manual hydrological charts. Technological advancements have made people adopt and maintain new soft structures. Now, the modelers can simulate the river runoff and its pattern around the globe with the help of GIS data structures using a “spatial hydrological model”.
Integrating Satellite Remote Sensing and GIS with hydro-climatology provides an appropriate tool for managing the large and complex databases and provides a digital depiction of catchment features for the modeling approach. It is a supportive tool to attain higher accuracy from hydrological models, thus giving reliable outcomes for betterment.
Many researchers and scientists have assessed the capabilities of satellite-based products, such as Global Climate Models or Regional Climate Models. These datasets include weather parameters like precipitation, temperature, wind speed, and humidity at a coarse to fine spatiotemporal resolution compared to gauge observations on both, pixel, and basin scales globally.
The main element of the terrestrial hydrological cycle is the generation of river discharge and the movement of water, which flows in the river channels. The prime zone that hosts this process is the river catchment, watershed, or basin. The hydrological response of watersheds to precipitation events depends on the mechanisms of runoff generation.
As the climate and land use change, the movement of water (on the surface & underground) is also affected. It also increases the risks of extreme events like flash floods. In such hydrological zones, various spatial differences in vegetation, topography, soil properties, geology, land use/land cover, and meteorological conditions are observed and can be well understood even on a small scale.
Thus, the heterogeneity in land cover and land use surface may be affected and strengthened by anthropogenic activities that can have an impact on the characteristics of natural landscapes. Therefore, it is important not only to consider the prime processes occurring, but also the terrestrial ones capturing the relevant factors that govern the runoff generation scenarios, and provide a chance to represent the land surface heterogeneity to describe the hydrological cycle.
Pakistan comes in the Hindukush Karakoram Himalaya (HKH) region.The region is well known as the “Water Tower of Asia”, and the “Third Pole”, as it hosts snow and glacier-capped peaks. Pakistan is a developing country that has been affected by climate change. According to Germanwatch, a German think-tank advocating for the prevention of climate change impacts has ranked Pakistan as the seventh nation most affected by events related to climate change (Climate Risk Index 2018 report). Hence, the use of data and integrating technologies to increase precision in prediction of events can help us plan to manage the problem beforehand.
Masood, Muhammad, et al. “Assessment of Real-Time, Multi-Satellite Precipitation Products under Diverse Climatic and Topographic Conditions.” Asia-Pacific Journal of Atmospheric Sciences (2019): 1-15.
Anjum, M. N., Ding, Y., Shangguan, D., Ijaz, M. W., & Zhang, S. (2016). Evaluation of high-resolution satellite-based real-time and post-real-time precipitation estimates during 2010 extreme flood event in Swat River Basin, Hindukush region. Advances in Meteorology, 2016.