Spatial Technologies: An Effective Tool to Overcome Data Scarcity for Disaster Risk Analysis in High Mountain Environment

Transcription

1 Spatial Technologies: An Effective Tool to Overcome Data Scarcity for Disaster Risk Analysis in High Mountain Environment Muhammad Yasir (PhD Research Scholar) SKL 水资源与水电工程科学国家重点实验室 STATE KEY LABORATORY OF WATER RESOURCES AND HYDROPOWER ENGINEERING SCIENCE Wuhan University 武汉大学水利水电学院 School of Water Resources and Hydropower Engineering swrh.whu.edu.cn

2 INTRODUCTION: General Context of the study /11/22

3 General Context of the study Varying discharge in Upper Indus River Basin (UIB) may result in the form of floods and droughts in mountainous regions Developing understanding of the hydrological regime and the impact of climate variability on Indus River catchments is extremely significant for flood prediction and water resource management Impact of changing climate on snow and glaciers results in extreme variation in stream flow which effects the water resource management in the downstream areas by causing Floods and Droughts etc /11/22

4 Primary Focus To simulate and forecast stream flow in the Shyok River Basin under different future climate change scenarios for flood and drought risk analysis /11/22

5 Methodology/Strategy Upper Indus Basin 1. Gilgit 2. Hunza 3. Astore 4. Shigar 5. Shyok 6. Shingo 7. Zanskar /11/22

6 Datasets Used Remote Sensing Satellite data ASTER GDEM (30m x 30 m) for catchment area delimitation MODIS (MOD10A2) (1680 images) snow cover products (500m x 500m) ( ) for snow cover area and total area estimation Meteorological Data (Skardu PMD) Precipitation (daily) ( ) Temperature (daily) ( ) Stream Flow Data (WAPDA) Daily stream flow data ( ) /11/22

7 ASTER: Study area GDEM /11/22

8 ASTER: Shyok Glacier Cover /11/22

9 MODIS: Annual Snow Cover Variation /11/22

10 Zonal Features of Study Area (from hypsometry) Zone A B C D E Elevation Band (m) Mean Elevation (m) % Area 2.1% 12.4% 61.8% 23.5% 0.2% Area in Km Climate Station Skardu (Installed by PMD) /11/22

11 Ø Snowmelt models Snowmelt Runoff Model (SRM) Ø Energy balance models (TOPKAPI, SNAP, ISNOBAL etc.) Ø Degree-day models (HBV, HEC-1, SRM, Cemaneige etc.) ØSnowmelt Runoff Model, SRM (Martinec, 1975) Ø Degree-day model Ø Simulation, forecasting and to study the climate change impact on river discharge in high mountaineous catchments Ø Satellite remote-sensing cryosphere data as basic input Ø Worldwide application. Ø Tested by WMO (1986; 1992) for simulation and forecasting Ø Zone-wise & basin-wide application /11/22

12 Zone-wise Snow Cover Area (SCA) /11/22

13 Zone-wise SRM application (2003) /11/22

14 2. Basin-wide SRM Application Basin-wide application: Input data (SCA) /11/22

15 Basin-wide SRM application (2004) /11/22

16 Climate change scenarios: Shyok River Basin 1. Cryosphere (Snow & ice cover) area change: 20% until year2075, 10% until year 2050, due to increasing precipitation (keeping mean temperature constant). 2. Mean temperature change: 4 C increase until year 2100, 3 C until year 2075, 2 C until year 2050 and 1 C until year 2025 (keeping other variables constant). 3. Scenario 1+2: 3 C increase in altitudinal zones & 20% increase in cryosphere area until year /11/22

17 Impact of Climate Variability on Shyok River Runoff Scenario (1): Snow cover area (SCA) change /11/22

18 Impact of Climate Variability on Shyok River Runoff Scenario (2): Change in mean temperature /11/22

19 Impact of Climate Variability on Shyok River Runoff Scenario (3): +20% SCA & T+3 C /11/22

20 Conclusion The snowmelt runoff model (SRM) is proven to be efficient Linear relationship between SCA, Temperature and Simulated River Discharge Climate change impact on basin s hydrology; +1 C = +25% summer Q +10% SCA = +11% summer Q The snowmelt runoff modeling of Shyok River discharge for flood risk assessment can prove very significant for the hydrologists and risk managers for necessary planning and infra-structure development in the area Spatial Technologies are a viable tool in predicting and assessing disaster risk and its effective analysis for future times /11/22

21 Thank You! /11/22