Assessment of land use and land cover changes in association with hydrometeorological parameters in the Upper Indus Basin

• Main Authors: Bilal, Hazrat, Siwar, Chamhuri, Mokhtar, Mazlin, Kanniah, Kasturi Devi, Govindan, Rajesh, Al-Ansari, Tareq
• Format: Article
• Published: National Centre of Excellence in Geology 2021
• Subjects: HD Industries. Land use. Labor
• Online Access: http://eprints.utm.my/id/eprint/96364/; http://nceg.uop.edu.pk/GeologicalBulletin/Vol-54(2)-2021/Vol-54(2)-2021-Paper1.pdf

The Upper Indus river basin (UIB) is not only significant because of its freshwater supply for agriculture and hydropower electricity generation but also for its contribution to maintaining ecosystem services. Land cover and land-use changes (LULC) are linked to socio-economic, and local climatic and hydrological conditions. Annual LULC changes in the UIB between 2001 and 2016 are studied using Moderate Resolution Imaging Spectroradiometer (MODIS) land cover product. The LULC data from MODIS is correlated to ground-based runoff (1984-2016), precipitation and temperature data (1960-2016). Mann Kendall and Pearson's correlation tests are used for data analysis. The overall accuracy of the MODIS land product is 87% with the kappa coefficient value of 0.82. The mainland cover types in terms of area coverage are barren land 53%, grassland 31% and permanent snow and ice 15%. Vegetation like forestland, grassland, cropland and savanna increased significantly during the period of observation. Most of the barren land is replaced by permanent snow and ice and a reduction was observed from 55.29% in 2001 to 52.78% in 2016. On the other hand, annual total precipitation and annual river flow exhibit significant increasing trends while the annual mean temperature was observed to be slightly increasing. A strong correlation exists between snow and icecovered area, vegetation and annual total precipitation. These results might be helpful to the concerned departments dealing with land planning, climate change, water resources and power generation.