April 2013 Tanna DeRuyter and Laurel Saito University of Nevada Reno Michael Rosen US Geological Survey

1. Review of US Partner Projects April 2013 Tanna DeRuyter and Laurel Saito University of Nevada Reno Michael Rosen US Geological Survey

2. Food web and water quality in water bodies in Khorezm, Uzbekistan Additional collaborators: Arica Crootof, Lidstone and Associates Dilorom Fayzieva and Elena Ginatullina, Institute of Irrigation and Water Problems, Uzbekistan John Lamers, Center for Development Research, University of Bonn, Germany Nodir Mullabaev, Institute of Zoology, Uzbekistan BakhriddinNishonov, Hydrometeorological Research Institute, Uzbekistan Julian Scott, US Geological Survey Margaret Shanafield, National Centre for Groundwater Research and Training, Australia

3. ZEF (University of Bonn) UNESCO MarhaboBekchonova, Urgench State University Diana Shermetova, Urgench State University AkmalNigmadjanov, Institute of Water Problems Farida Kadirkhodjaeva, NIGMI Liliana Sinn, Natalia Shermetova, Christopher Martius Acknowledgements

4. NATO Science for Peace Project No. 982159 (2006-2010) • Using stable isotopes, passive organic samplers and modelling to assess environmental security in Khorezm, Uzbekistan • National Science Foundation Project 0838239 (2009-2014) • Investigating pesticide contamination in small lakes in Khorezm, Uzbekistan Previous projects

5. Agricultural economy UNESCO World Heritage Site (Khiva) Khorezm

6. Can these small lakes havesocio-economic benefit to the local population through fisheries/tourism? Courtesy of ZEF

7. Project objectives • Investigate water quality and aquatic ecosystems in irrigation runoff lakes in Khorezm • Develop aquatic food web and water quality models • Determine potential utility of irrigation runoff lakes for aquaculture, water supplies, and other uses • Train young Uzbek scientists at • Urgench State University (End-User) • State Committee for Nature Protection (End-User) • Hydrometeorological Research Institute (End-User) Urgench State University students collecting aquatic insect specimens

8. Goals and Milestones • Sample collection • Physical water quality • Aquatic food web • SPMDs • Bioassays • Lake cores • Sample analysis • Water quality (nutrients, metals, pesticides) • Stable isotope processing • Stable isotope analyses • SPMD extraction • SPMD analyses • Chlorophyll • Age-dating of lake cores • Data analysis and model parameterization • Food web modeling • Water quality modeling • Data synthesis and evaluation • Assessment of environmental security • Coordination with ZEF models/data • Model results • Assessment of suitability of water resources • Implementation at End-User • Training of young scientists • Final workshop of results, training, and hand over

9. Sites Sampled

10. Eshan Rabat (ESH) Tuyrekkul (TUY) Khodjababa (KHO) Shurkul (SHK)

11. Methods – sample collection water sampling evaporation fish SPMD zooplankton sediments lake cores in situ data water sampling

12. Methods - analysis

13. Evaporation dominates water balance Local groundwater table higher than lake level All water sampled was derived from evaporated Amu Darya water Hydrology – tuy and kho (summer 2008) Scott et al. (2011)

14. Fish, Macroinvertebrates, and Zooplankton • 16 species of fish • most common: carp, goldfish, snakehead • Species composition and fish body condition, length, and weight were different across lakes and years • ~30 zooplankton taxa • Zooplankton biomass peaks in spring to early summer and late summer to early fall • Highest zooplankton biomass observed in Tuyrekkul • Macroinvertebrates at all lakes

15. Stable isotopes • Looked at carbon (C) and nitrogen (N) isotopes • Fish • Zooplankton • Macroinvertebrates • Zooplankton differences may be due to species variability Zooplankton

17. In situ water quality

18. Nitrogen and Phosphorus

19. SPMDs Minimal impacts • All units are pg TEQ/mL • SPMD results are not significantly different from blanks, indicating very little organic contaminant presence

20. All HCH values were well below optimal limit of 0.98 mg/L Pesticides in water Optimal limit: 0.001 mg/L Tolerable limit: 1.1 mg/L

21. All values are well below optimal limits for HCH and DDT Lake core pesticides ESH KHO TUY SHK

22. Pesticides in fish USDA recommended DDT maximum: 5.0 mg/kg

23. Microbial experiments • Lindane (HCH) broke down very quickly • We were unable to complete the DDT experiments

24. 8 young scientists in Uzbekistan • NATO funding • 3 young scientists in US • Fulbright student fellowship • Teaching assistantships • National Science Foundation (NSF) • End-User training • NATO funding Education and training

25. Contributions of each partner • IWP – Dr. D. Fayzieva • Overall project coordination • Supervision of young scientists • Lead organizer of final workshop and training • UNR – Dr. L. Saito, Dr. S. Chandra • Lead for training on food web and water sampling and analysis and modeling • Lead for training on writing papers and theses • Sampling, analysis and modeling • NIGMI – Dr. B. Nishonov • Provide equipment for analyses • Perform water quality analyses • GOSSIAK and NIGMI (End-Users) • Participation in workshops and trainings • Application of methods into nation-wide monitoring practices • USGS – Dr. M. Rosen • Lead for training on SPMD deployment, retrieval, analysis, lake coring • Sampling and analysis • URDU (End-User) • Participation in sampling, analyzing, workshops, trainings • Application of innovative technology into education system • ZEF – Dr. J. Lamers • Provide equipment and facilities • Coordination of KEOM with project models

26. Training 1: stable isotope and limnological sampling (Khorezm, Uzbekistan) • June 2006 • Training 2: sediment sampling, SPMD (Khorezm, Uzbekistan) • June 2007 • Training 3: computer modelling and sampling (Reno, USA) • July 2007 • Trainings 4 and 5: theses, working with data (Reno, USA) • March 2008 and January 2009 • Closing workshop: present results and training in Russian (Tashkent, Uzbekistan) • June 2009 Trainings

27. NIGMI • BakhriddinNishonov • Yevgeniya Lee • Farida Kadirkhodjaeva • Urgench State University • MarhaboBekchonova • Diana Shermetova Uzbek Young Scientists

28. Institute of Water Problems • Elena Ginatullina • Nodirbek Mullabaev • AkmalNigmadjanov Uzbek Young Scientists

29. Held June 2009 (Tashkent) and October 2009 (Urgench) • 21 scientists in Tashkent, 12 students in Urgench • Training done by Uzbek young scientists • Trained on: • Water quality sampling • Food web sampling • Stable isotope processing • SPMD deployment and retrieval • Sediment sampling Young Scientists: End User Training

30. Margaret Shanafield Julian Scott Arica Crootof U.S. Young Scientists

31. Nutrient concentrations vary over time • Pesticide contamination appears to be low in lake waters and sediments • Lakes currently contain many fish, zooplankton, and macroinvertebratetaxa • Most lakes probably suitable for aquaculture • Sensitive to increased salinity and water management • Connections between young scientists in Uzbekistan and U.S. Conclusions

32. Modeling halophytic plants to improve agricultural production and environmental quality in arid and semi-arid regions Atriplexcanescens http://plants.usda.gov/java/profile?symbol=ATCA2 Funding source: Nevada Agricultural Experiment Station Project dates: July 2012 to June 2014

33. Background • Study addresses loss of agricultural production due to salinization of land • Almost 20% of irrigated land affected • Halophytes grow in saline soils or water • May be food for humans/livestock • May be useful for biofuel production • May be useful for managing/reducing soil and water salinity Distichlisspicata (saltgrass) http://plants.usda.gov/java/profile?symbol=DISP&photoID=disp_007_avp.jpg&format=print

34. Long-term goal: Assess potential for halophytic plants as an economic resource via food for humans or livestock, biofuel production, or by maintaining or restoring agricultural production of conventional crops on saline lands Objectives: Augment APEX model with halophytic plant data Develop salinity modules for APEX model Use APEX model to estimate feasibility of halophytes for food or biofuel production or reduction of salts in soils and water Project objectives

35. Parameterization of halophytic plants in APEX • Literature review • Plant physiology • Salt control mechanisms • Germination rates • Utility • Select 2-3 halophytes for which we have most data to model • Use data from Uzbekistan • Completion by May 2013 Tasks overview

36. Literature review of modeling approaches for modeling soil-plant-water salt movement • Many approaches are empirical/statistical • More mechanistic modeling approach has been selected • Task completed Tasks overview Jerusalem Artichoke

37. Add a salinity module to the APEX model • Dr. Cole Rossi at BLM is task lead • Dr. Rossi provided training on APEX model to team in Nov 2012 • Completion expected May 2013(?) • Assess halophytic plant potential • Set up models for Uzbek sites • Calibrate models • Set up scenarios • Work in progress Tasks overview Uzbek Suaeda plantation at Kyzylkesek

38. Coordinate project activities with coursework • NRES 725 Plant Physiological Ecology(Spring 2013) • NRES 730 Interdisciplinary Modeling (Summer 2014) • Outreach to Pyramid Lake Jr/Sr High School • Planned for Summer 2013 Tasks overview Tamarixramosissima (saltcedar)

39. Related project: NSF PEER project • Title: Utilization of low quality water for halophytic forage and renewable energy production • Two field sites: • Kyzylkesek: natural inland salinity • Khorezm: irrigation-induced salinity • Dr. Saito and Dr. Michael Rosen will travel to Uzbekistan in April 2013 • Dr. Kristina Toderich (PIon PEER project) willcome to US in May 2013 Other items Khorezm field site

40. Conference presentations • June 2013: UCOWR/NIWR conference, Lake Tahoe • December 2013: AGU conference, San Francisco • Jan/Feb 2014: NWRA conference, Las Vegas • March 2014: FIHMC conference, Reno • May 2014: EWRI conference, Location TBD Other items

41. QUESTIONS?