Knowledge Priorities on Climate Change and Water in the Upper Indus Basin: A Horizon Scanning Exercise to Identify the Top 100 Research Questions in Social and Natural Sciences

River systems originating from the Upper Indus Basin (UIB) are dominated by runoff from snow and glacier melt and summer monsoonal rainfall. These water resources are highly stressed as huge populations of people living in this region depend on them, including for agriculture, domestic use, and energy production. Projections suggest that the UIB region will be affected by considerable (yet poorly quantified) changes to the seasonality and composition of runoff in the future, which are likely to have considerable impacts on these supplies. Given how directly and indirectly communities and ecosystems are dependent on these resources and the growing pressure on them due to ever-increasing demands, the impacts of climate change pose considerable adaptation challenges. The strong linkages between hydroclimate, cryosphere, water resources, and human activities within the UIB suggest that a multi- and inter-disciplinary research approach integrating the social and natural/environmental sciences is critical for successful adaptation to ongoing and future hydrological and climate change. Here we use a horizon scanning technique to identify the Top 100 questions related to the most pressing knowledge gaps and research priorities in social and natural sciences on climate change and water in the UIB. These questions are on the margins of current thinking and investigation and are clustered into 14 themes, covering three overarching topics of ‘governance, policy, and sustainable solutions’, ‘socioeconomic processes and livelihoods’, and ‘integrated Earth System processes’. Raising awareness of these cutting-edge knowledge gaps and opportunities will hopefully encourage researchers, funding bodies, practitioners, and policy makers to address them

Flood vulnerability assessment of the Upper Jhelum Basin using HEC-HMS model

The five watersheds of the Upper Jhelum Basin (UJB) in the Kashmir Himalaya, India has flood prone hydrographic features resulting in high-frequency of flooding in the basin. With this in mind, HEC-HMS was calibrated to estimate excess-runoff potential of five watersheds and the model results showed a good agreement with the observed streamflow. The study revealed that due to the presence of rocky-outcrops, precipitous-topography and impervious-surfaces, Vishav, Lidder and Sandran are the major contributors of the excess-runoff among the 5 watersheds as compared to Bringi and Kuthar. For the model-efficacy, the excess-runoff potential and the social-vulnerability of the region were compared to the floodwater-depth observed during the 2014-flooding event. The comparison reveals that the flood-vulnerability assessment of the UJB are well corroborated by the observed floodwater levels and the Vishav watershed is most vulnerable. The findings of this study are expected to inform flood management plans in the UJB

Impact of Land System Changes and Extreme Precipitation on Peak Flood Discharge and Sediment Yield in the Upper Jhelum Basin, Kashmir Himalaya

The Kashmir valley is prone to flooding due to its peculiar geomorphic setup compounded by the rapid anthropogenic land system changes and climate change. The scarcity of observations is one of the major challenges for understanding various land surface processes in the mountainous and mostly ungauged terrain. The study assesses the impact of land use and land cover (LULC) changes between 1980 and 2020 and extreme rainfall on peak discharge and sediment yield in the Upper Jhelum Basin (UJB), Kashmir Himalaya, India using KINEROS2 model. Analysis of LULC change revealed a notable shift from natural LULC to more intensive human-modified LULC, including a decrease in vegetative cover, deforestation, urbanization, and improper farming practices. The findings revealed a strong influence of the LULC changes on peak discharge, and sediment yield relative to the 2014 timeframe, which coincided with the catastrophic September 2014 flood event. The model predicted a peak discharge of 115,101 cubic feet per second (cfs) and a sediment yield of 56.59 tons/ha during the September 2014 flooding, which is very close to the observed peak discharge of 115,218 cfs indicating that the model is reliable for discharge prediction. The model predicted a peak discharge of 98,965 cfs and a sediment yield of 49.11 tons/ha in 1980, which increased to 118,366 cfs and, 58.92 tons/ha, respectively, in 2020, showing an increase in basin’s flood risk over time. In the future, it is anticipated that the ongoing LULC changes will make flood vulnerability worse, which could lead to another major flooding in the event of an extreme rainfall as predicted under climate change and, in turn, compromise achievement of sustainable development goals (SDG). Therefore, regulating LULC in order to modulate various hydrological and land surface processes would ensure stability of runoff and reduction in sediment yield in the UJB, which is critical for achieving many SDGs

Impact of Land System Changes and Extreme Precipitation on Peak Flood Discharge and Sediment Yield in the Upper Jhelum Basin, Kashmir Himalaya

The Kashmir valley is prone to flooding due to its peculiar geomorphic setup compounded by the rapid anthropogenic land system changes and climate change. The scarcity of observations is one of the major challenges for understanding various land surface processes in the mountainous and mostly ungauged terrain. The study assesses the impact of land use and land cover (LULC) changes between 1980 and 2020 and extreme rainfall on peak discharge and sediment yield in the Upper Jhelum Basin (UJB), Kashmir Himalaya, India using KINEROS2 model. Analysis of LULC change revealed a notable shift from natural LULC to more intensive human-modified LULC, including a decrease in vegetative cover, deforestation, urbanization, and improper farming practices. The findings revealed a strong influence of the LULC changes on peak discharge, and sediment yield relative to the 2014 timeframe, which coincided with the catastrophic September 2014 flood event. The model predicted a peak discharge of 115,101 cubic feet per second (cfs) and a sediment yield of 56.59 tons/ha during the September 2014 flooding, which is very close to the observed peak discharge of 115,218 cfs indicating that the model is reliable for discharge prediction. The model predicted a peak discharge of 98,965 cfs and a sediment yield of 49.11 tons/ha in 1980, which increased to 118,366 cfs and, 58.92 tons/ha, respectively, in 2020, showing an increase in basin’s flood risk over time. In the future, it is anticipated that the ongoing LULC changes will make flood vulnerability worse, which could lead to another major flooding in the event of an extreme rainfall as predicted under climate change and, in turn, compromise achievement of sustainable development goals (SDG). Therefore, regulating LULC in order to modulate various hydrological and land surface processes would ensure stability of runoff and reduction in sediment yield in the UJB, which is critical for achieving many SDGs

Assessing changes in the above ground biomass and carbon stocks of Lidder valley, Kashmir Himalaya, India

The changes in the land use and land cover (LULC), above ground biomass (AGB) and the associated above ground carbon (AGC) stocks were assessed in Lidder Valley, Kashmir Himalaya using satellite data (1980–2013), allometric equations and phytosociological data. Change detection analysis of LULC, comprising of eight vegetation and five non-vegetation types, indicated that 6% (74.5 km2) of the dense evergreen forest has degraded. Degraded forest and settlement increased by 20 and 52.8 km2, respectively. Normalized difference vegetation index was assessed and correlated with the field-based biomass estimates to arrive at best-fit models for remotely sensed AGB estimates for 2005 and 2013. Total loss of 1.018 Megatons of AGB and 0.5 Megatons of AGC was estimated from the area during 33-year period which would have an adverse effect on the carbon sequestration potential of the area which is already facing the brunt of climate change

Estimating Forest Biomass in Temperate Forests Using Airborne Multi-frequency Polarimetric SAR Data

We used multi-sensor, multi-frequency and multi-polarization SAR data for biophysical parameter retrieval in plantation forests of Northern Japan. The statistical relationships with different biophysical parameters are quite robust for certain frequencies-polarization combination. A combination of different frequencies and polarizations facilitate the retrieval of these parameters with R 2 of 0.95 and rms error of 15.19 tons ha-1. Further, a large sample of 186 stand age from coniferous species showed a robust relationship for all the three polarizations of the L-band data up to 40 years of age. L-band data provided very good retrieval accuracy for the dry biomass with the SEE = 22.52 tons ha-1. 1