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CREST meeting, Aug. 4, 2004

CREST meeting, Aug. 4, 2004. Previous research and some thinking about world water assessment. Yanjun Shen Oki/Kanae Lab., IIS, UT. The Outlines Brief introduction to my previous research About climatic zoning for world water assessment About data fusion.

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CREST meeting, Aug. 4, 2004

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  1. CREST meeting, Aug. 4, 2004 Previous research and some thinking about world water assessment Yanjun Shen Oki/Kanae Lab., IIS, UT

  2. The Outlines Brief introduction to my previous research About climatic zoning for world water assessment About data fusion

  3. Brief introduction to my previous research Water processes of land-atmosphere system Estimating surface ET by remote sensing

  4. Study area- North China Plain 北京 North China Plain 天津 渤　海　 石家荘 済南 In recent years：rainfall 400-500mm; actual ET ~800mm; irrigation＞300mm; groundwater is to be exhausted; most rivers dried up.

  5. Precipitation of NCP 900 Mean value of 456.7mm 800 10-year average: 481.2mm in 1970s 468.7mm in 1980s 420.3mm in 1990s 700 600 500 Annual precipitation (mm) 400 300 200 100 0 1971 1976 1981 1986 1991 1996 2001 Years * Data from Luancheng station, LESA. Precipitation of NCP

  6. Beijing　　北京 Shijiazhuang　石家荘 Handan邯鄲 Water level declination along Jing-Guang Line N S （河北省水文水資源管理局） （中国科学院欒城農業生態実験所）

  7. Groundwater of NCP 0m -20m 1959 1992 -40m 10m 20m 20m -20m -40m 30m -20m 0m 20m (after Sun et al., 1999)

  8. Wetland change 9000 km2 1950’s 1000 km2 in 2000 Rivers drying

  9. Part I: Field Experiments 北京 天津 簡易ボーエン比装置 渤　海　 石家荘 脈　山　行　太 38N 南皮 泊頭 楽城 辛集 黄　　　　　　　　河 脈 渦相関システム TDR (0-2m) Bo Sea 36mタワー温湿度観測 ボーエン比システム *: NOAA/AVHRR image of NCP.

  10. Part I: Observation items

  11. Precipitation and irrigation during the experimental period Totally, precipitation＝1100mmirrigation＝900mm

  12. Inter-annual variation of energy balance Net radiation （Rn） Soil heat flux （G） Sensible heat flux （H） Latent heat flux （LE） Leaf area index（LAI） Soil water storage （SW） Days from 1999/01/01

  13. 1.2 1.2 doy142 c a 1 1 doy269 0.8 0.8 EF 0.6 0.6 0.4 0.4 y = 0.164x + 0.2437 y = 0.127x + 0.1102 0.2 2 0.2 2 R = 0.916 doy190 R = 0.8666 doy70 0 0 0 1 2 3 4 5 6 0 1 2 3 4 5 1.2 1.2 Evaporative Fraction (LE/(Rn-G)) LAI d b LAI 1 1 doy212 0.8 0.8 doy110 EF 0.6 0.6 0.4 0.4 y = 0.1271x + 0.37 y = 0.1806x + 0.3411 doy68 2 2 0.2 R = 0.747 0.2 R = 0.7702 doy177 0 0 0 1 2 3 4 5 0 1 2 3 4 5 6 LAI LAI Part I: Dependence of energy partitioning on plant phenology Senescent stages . Maize 2000 . Wheat 1999 Before senescent . Maize 2001 . Wheat 2000 EF=a*LAI＋b This relation can be potentially used for regional estimation by remote sensing.

  14. Part I: Diurnal patterns of Bowen ratio in various seasons Wheat Maize Winter

  15. Part II: Effect of soil water condition on energy partitioning Relationship between ESW and Bowen ratio Transition period in spring （LAI<2) Wheat （LAI>4) Maize （LAI>3.5) Soil layer: 0~40cm Soil layer: 0~100cm Soil layer: 0~100cm ESW: Extractable soil water

  16. Part II: Influence of soil water on transpiration Heading Jointing 5x10m2の実験セル16個を5組に分け、灌漑による土壌水分をコントロールし、異なる水ストレスを与え、フィールド観測を行った。 maximum Milking Maturing Wheat stomatal conductance Extractable soil water The maximum stomatal conductance varies from growing stages.

  17. Part II: A conceptual model of soil water - transpiration relation 3-stages model of transpiration Incipient water stress Relative transpiration rate Wilting point threshold point

  18. T/Tp or E/Ep 1 0 Soil moisture θwθ*θ’ θf θ Part II: Dual-source ET model construction

  19. Part II: Adaptation of ET model with the concept of water deficit Vegetation Water Deficit Index Soil Water Deficit Index Integrated dual-source ET model (dual-source) (single-source)

  20. Part III: Introduction to the remote sensing algorithm Schematic flowchart Ancillary data: Ta, ea, U Radiance analysis of multi-spectral data NDVI, surf. temp. Albedo, Rn G WDI LEp LE=LEp*(1-WDI) 3-stage model as a theoretical base

  21. Part III: Determination of Water Deficit Index (WDI) (simplified VITT model for irrigated semiarid region) fv Warm edge (Tsmax) Wet edge (Tsmin) fv_max fv_m fv_x 0 water Ts_m Ts_x Ts Fractional cover Surface temperature Based on 3 assumptions : 1). at least one “well watered” and one “completely water stressed” point/pixel exist simultaneously 2). under a given vegetation condition, the surface temperature will linearly increase with the increase of WDI 3). under a given soil water condition, surface temperature linearly decrease with the increase of vegetation cover

  22. Warm edge WDI=1 Tsmax=-10.16*fv+30.10 A B C Wet edge WDI=0 Tsmin=-2.86*fv+12.69 Part III: An example of determination of WDIby TM data WDIB=BA/CA (Mar. 31, 2001)

  23. Examples of remotely estimated WDI (wheat season) Warm (dry), cold (wet) TM & ETM+ data 2000/10/14 pre-emerging 2001/03/31 pre-revival 2001/04/16 jointing 0 6Km 2001/06/19 post-harvest 2001/05/10 blooming 2001/05/26 milking Back

  24. Part III: Estimation of potential ET If fv > 0.5 then (single-source model) else (dual-source model) ETp=Ep+Tp (Penmen-Monteith Equ.) (Ritchie, 1974) (Jensen et al., 1989) with

  25. Part III: Estimated ET maps (wheat season) 2000/10/14 2001/03/31 2001/04/16 (pre-emerging) (pre-revival) (jointing) Histograms

  26. Part III: Estimated ET maps (wheat season) 2001/05/10 2001/05/26 2001/06/19 (blooming) (milking) (post-harvest) Histograms

  27. Part III: Energy and water fluxes: 正味放射 可能蒸発散 潜熱 顕熱 土壌熱流量

  28. Part III: Bowen ratio and Evaporative fraction: Bowen ratio Ground measurements of midday averaged value (10:00~15:00) Remotely estimated instantaneous value (~10:00) EF

  29. Part III: Estimated LAI and vegetation coverage coverage LAI LAI and vegetation coverage

  30. Part III: Validation: Soil water status Comparison of remotely estimated soil water status (blue line dots) and ground measured extractable soil water of 0~40 cm layer (green-yellow line) in 2001 Comparison of remotely estimated (1-WDI) with observed ESW of 0~40 cm layer ESW: extractable soil water.

  31. Part III: Validation: LE Comparison of the remotely estimated LE with ground measurements by Bowen ratio method Ground validation site is Luancheng Station, CAS

  32. The Outlines Brief introduction to my previous research About climatic zoning for world water assessment About data fusion

  33. Climatic zoning the earth with considering water resources river dry-up Land degradation Surface water Human-environment Water Competition Water deficit regions water table decline usable duration groundwater (e.g. ETp>P) In arid region, even 20mm rainfall can lead to disaster. (M. Yoshino) flood world Seasonal drought e.g. SW-India, S-China, N-SEAsia, etc. Water surplus regions flood Flood disaster will increase due to climate warming! (e.g. ETp<P) Different regions have different water issues, so, different strategies.

  34. Seasonal drought in water surplus regions Annual Rainfall map of India (cm) (India Meteorol. Dep.) Water woes in KeralaWith 44 rivers and India's highest annual rainfall, Kerala is in drought. Poor monsoons, inefficient water and land management practices are leading the state towards disaster ……(Down to Earth, May 31, 2004) http://www.downtoearth.org.in/cover.asp?foldername=20040531&filename=anal&sid=1&sec_id=7

  35. Seasonal drought in water surplus regions The case of S-China The drought in Zhejiang Province (July 2003) Too thirsty Pa=1400~1800mm Rice is dieing Dried river bed In the east part of Yangtze River basin, drought always occurs after the flood season of June and July. Dried river bed

  36. Tarim River Basin The Tarim River Basin, China The competing for limited water resources between human use and eco-environmental requirement is becoming the biggest water problem. Bosten Lake Tarim River Salinification Precipitation: 400-500mm in mountain range <50mm in plain Rivers are mainly recharged by snowmelt water river dry-up, vegetation dieing, desertification

  37. Eco-restoration in lower reach of Tarim River Bosten Lake Tarim river Optimal eco-waterlevel: 2~4m Stress water level: 4~9m Minimum water level: 9m (from: Chen Y., CAS) Due to land reclamation and water resources exploitation, the destination of Tarim River, Taitema Lake, has dried-up for long years, and the vegetation in lower reach has decreased also. The Government now want to recharge the groundwater and restore the ecosystem and conducted 4times water-transfer from the reservoirs or Bosten Lake. Plain reservoirs Dried-up Taitema Lake (dried)

  38. Tarim river Plain res. Dried-up Taitema Lake Enlargement of plain-reservoir Old dike New dike Enlarge for irrigation and water transfer Change function into eco-regulation

  39. Tarim river Plain res. Dried-up Taitema Lake Poplar windbreaks of the field

  40. Tarim river Plain res. Dried-up Taitema Lake Water canal in desert

  41. Tarim river Plain res. Dried-up Taitema Lake Vegetation at lower reach 胡楊 Hard skin of the soil surface

  42. Tarim river Plain res. Dried-up Taitema Lake The last gauge at lower reach (Arkan)

  43. The biggest issue in arid or semi-arid region is: How to balance the water requirement between human and environment for a sustainable utilization?

  44. The Outlines Brief introduction to my previous research About climatic zoning for world water assessment About data fusion

  45. Data Fusion: “Data fusion is a process dealing with the association, correlation, and combination of data and information from single and multiple sources to achieve refined position and identity estimates for observed entities, and to achieve complete and timely assessments of situations and threats, and their significance. The process is characterized by continuous refinements of its estimates and assessments, and by evaluation of the need for additional sources, or modification of the process itself, to achieve improved results”JDL DFG, 1992 To integrate various data source (e.g. different resolution, scale, format, etc.) into same format (or resolution, scale) for a comparable or computable purpose is one kind of data fusion.

  46. About the 0.5-deg Land cover map 4-min GLCD 4-min Global Land Cover Dataset areal aggregation 0.5-deg Percentage (purity) maps of some major cover types: Urban agricultural (irrigated and non-irr.) barren (including water) others 0.5-deg percentage maps

  47. 250 250 170 170 About rasterization of the country borders (make 0.5-deg gridded border) High resolution raster data (e.g. 4-min) Country-based data (GIS Vector data) convert resample 218 190 80 250 234 230 170 Country-based data (0.5-deg grid data) 239

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