The structure and dynamics of groundwater systems in northwestern India

Transcription

1 The structure and dynamics of groundwater systems in northwestern India Indian team Rajiv Sinha, S. Joshi, Nibedita Nayak (IIT Kanpur) S.P. Rai (NIH Roorkee) Shashank Shekhar, Manoranjan Kumar (Delhi Univ.) Devashish Kumar (NGRI) UK team Alexander Densmore, Wout van Dijk (Durham Univ.) Sanjeev Gupta, Ajit Singh, Phillippa Mason (Imperial College)

2 India is the largest user of groundwater in the world (92% for agriculture) Wheat fields near Patiala, Punjab

3 but at a cost Total loss ~18-20 km 3 /yr in Punjab, Rajasthan, Haryana Likely 'the largest rate of groundwater loss in any comparable-sized region on Earth' (Tiwari et al. 2009) Change in water storage in northwestern India (based on GRACE data) Chen et al. (2014) Rodell et al. (2009) Nature

4 Project outcomes Sutlej R. Punjab Punjab Haryana Rajasthan Rajasthan Uttar Pradesh Haryana 1. The first integrated, detailed picture of water-level decline across northwestern India (CGWB + state groundwater board data)

5 Project outcomes Punjab Sutlej R. Lessons: Detail allows us to define specific areas for Punjab intervention and management Rajasthan Rajasthan Haryana Critical to integrate data across state/district Uttar Pradesh boundaries (but takes work) Haryana Same approach should be applied throughout the Indo-Gangetic basin 1. The first integrated, detailed picture of water-level decline across northwestern India (CGWB + state groundwater board data)

6 Project outcomes 2. Integrated summary of aquifer characteristics across the study area (CGWB aquifer-thickness logs)

7 Aquifer system consists of large sedimentary fans This shows that: 20 km Aquifer bodies are long, narrow channel deposits Aquifer bodies are not laterally extensive can t be correlated Typical dimensions 1-10 km across, 1-50 m thick

8 Fan areas: Thick, abundant aquifer bodies Ribbon-like long, narrow deposits that radiate from fan apex Low lateral connectivity Vertically stacked locally high connectivity Sutlej fan Yamuna fan

9 Inter-fan areas: Less aquifer material, thinner aquifer bodies No connectivity to major river systems no source of coarse sediment Low specific yield, even close to the Himalayas

10 Lessons: Geomorphic setting governs aquifer characteristics provides both guide and framework for integration Aquifers obey geomorphic rather than political boundaries critical for assessment & management Existing CGWB data provide raw material for very good understanding of aquifer properties Should be applied throughout the Indo-Gangetic basin

11 Project outcomes 3. Fine-scale characterisation of aquifer architecture based on drilling and coring

12 Project outcomes Lessons: New drilling and coring data allow us to check and extend CGWB aquifer-thickness logs Provide link to process understanding of aquifer deposition: stacked, multi-story sand bodies Closely-spaced logs provide information on aquifer heterogeneity good vertical connectivity, limited lateral connectivity 3. Fine-scale characterisation of aquifer architecture based on drilling and coring

13 Project outcomes Patiala Chandigarh Sirsa Delhi 4. Characterisation of groundwater movement and recharge using stable isotope analysis

14 Pre-monsoon groundwater samples - above 80 m Significant contribution of canal water to shallow aquifers Pre-monsoon groundwater samples - below 80 m GW samples (above 80 m) GW samples (below 80 m) Canal water samples River water samples Annual weighted avg. precipitation δ 18 O ( ) GW: δ 2 H = 6.37 x δ 18 O , r² = 0.95 δ 18 O ( ) δ 2 H ( ) δ 2 H ( )

15 Pre-monsoon groundwater samples - above 80 m Significant contribution of canal water to shallow aquifers δ 18 O ( ) GW: δ 2 H = 6.37 x δ 18 O , r² = δ 2 H ( ) Lessons: Pre-monsoon groundwater canal sources samples - below 80 m Shallow groundwater shows recharge δ 18 from O ( ) both meteoric and Deeper groundwater recharged only from meteoric source Stable isotopes (when systematically analysed across region) -40 GW samples (above 80 m) GW samples (below 80 m) Canal water samples River water samples Annual weighted avg. precipitation provide strong fingerprinting of groundwater sources δ 2 H ( )

16 Project outcomes Sutlej River Probability of finding aquifer material at m below ground level 5. First simple predictive model of aquifer-body occurrence

17 Project outcomes Sutlej River Lessons: Existing CGWB data plus simple geology-based rules provide an expectation of where to find aquifer material Model accuracy improves as more data are added easy to incorporate new wells Probability of finding aquifer material at m below ground level No proprietary algorithms or black-box approaches needed 4. First simple predictive model of aquifer-body occurrence

18 Training and knowledge transfer Bilateral student exchange India-UK 5 months Indian postdoc to UK 24 months Staff visits (weeks-months) Engagement with Dr Mihir Shah and GoI review of CWC and CGWB Training workshop for CGWB scientists: March 2016, Delhi

19 Recommendations Use geomorphic framework to guide data integration and interpretation Projects should encompass groundwater catchments across states Use probabilistic approaches rather than deterministic aquifer maps (with high uncertainties) Incorporate geomorphology, sedimentology, statistical analyses into aquifer mapping and characterisation Need for holistic view of surface and groundwater together