water & energy exchange

Transcription

1 GRAPEX- A project to measure and model water & energy exchange

2 Many researchers are contributing to the GRAPEX project GRAPEX: Grape Remote sensing Atmospheric Profile Evapotranspiration experiment William Kustas 1, Martha Anderson 1, Kyle Knipper 1, Feng Gao 1, Joe Alfieri 1, Lynn McKee 1, John Prueger 2, Jerry Hatfield 2, Chris Parry 3, Andrew McElrone 3, Larry Hipps 4, Alfonso F Torres-Rua 5, Mac McKee 5, Luis Sanchez 6, Maria Mar Alsina 6, Nick Dokoozlian 6, Forrest Melton 7,8, Kirk Post 7, Christopher Hain 9 Héctor Nieto 10, Nurit Agam 11, Ting Xia 12 1 USDA-Agricultural Research Service, Hydrology and Remote Sensing Laboratory, Beltsville, MD 2 USDA-ARS National Laboratory for Agriculture and the Environment, Ames, IA 3 USDA-ARS Crops Pathology and Genetics Research Unit, Davis, CA 4 Plants, Soils and Climate Department, Utah State University, Logan UT 5 Department of Civil and Environmental Engineering, Utah State University, Logan, UT 6 Viticulture Research, Ernest & Julio Gallo Winery, Modesto, CA 7 School of Natural Resources California State University of Monterey Bay, Marina CA 8 NASA Ames Research Center, Moffett Field, CA 9 NASA Marshall Space Flight Center, Huntsville AL 10 IRTA (Institute for Food and Agricultural Research and Technology) LLIEDA Spain 11 Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of Negev, Israel 12 Department of Hydraulic Engineering, Tsinghua University, Beijing, China USDA is an equal opportunity provider and employer.

3 Context: Specialty Crop Industry in California Grapes ~ 1 million acres ( ha) Valued at ~$6 B Fruit & Nut Orchards ~ 2.6 million acres ( ha) Valued at ~$10 B ~80% of fresh water used for irrigation

4 GRAPEX Goal GRAPEX goal: to apply a multi-scale remote sensing evapotranspiration (ET) toolkit for improved irrigation scheduling and water management in vineyards in California, a region of endemic periodic drought. While this work focus on vineyards, the tools apply to fruit and nut orchards and other crops with highlystructured canopies.

5 Monitoring Water Use in U.S. Vineyards Current Operational ET Estimates for Irrigation Scheduling ET = K c (ET 0 ) Crop Coefficient (~ NDVI) Reference ET

6 Controlling Vine & Berry Development via Irrigation Irrigation Scheduling in Viticulture

7 Approaches for Monitoring ET

8 Overview of Data Fusion Approach for Obtaining daily ET

9 A Multi-Scale Modeling framework for TSEB GOES - West Developing a Multi-Scale Modeling Framework to Bridge from Field to Continental, Daily to Seasonal/Annual NOAA Geostationary Operational Environmental Satellites Low ET High ET Landsat Landsat Aircraft

10 GRAPEX Study in U.S. Vineyards The measurements were collected in two vineyards located approximately 32 km (~20 mi) northeast of Lodi, CA (38.29 N, W). East-West Rows spaced ~3.3 m (11 ft). Vines spaced ~1.5 m (5 ft). North Vineyard (site 1): ~ 34.4 ha (85 ac). Mature vines. South Vineyard (site 2): ~21 ha (52 acre). Young vines. GRAPEX Study site North Vineyard (site 1) South Vineyard (site 2)

11 Bare soil, cover crop & vine canopy: 3 sources GRAPEX Study site

12 GRAPEX site measurements

13 GRAPEX Episodic Measurements GRAPEX Measurements During IOPs Below canopy wind & water vapor turbulence Spectral & LAI Canopy T & CO2 Aircraft/UAV based high resolution Vis/NIR and thermal-ir UAV solar radiation divergence Tower-based Thermal/Optical Scanner Scintillometry

14 GRAPEX Episodic Measurements Additional GRAPEX Measurements During IOPs IRT sensor network Leaf & Canopy Hyperspectral Micro-Bowen ratio systems

15 GRAPEX Intensive Observation Periods (IOPs) IOP 1 ~April/May LAI ~ 0.5 to 2 LAI ~ 0.5 to 2 GRAPEX IOPs IOP 2 ~June/July LAI ~ 1.5 North Vineyard LAI ~ 1 South Vineyard IOP 3 ~August LAI ~ 2 LAI ~ 1.5 IOP 1 Flowering IOP 2 Fruit Set/Veraison IOP 3 Veraison

16 Leaf Area Index transects for GRAPEX GRAPEX LAI Measurements During IOPs ( )

17 Results with Data Fusion

18 Refinements to TSEB

19 Modification of radiation extinction for vine canopy architecture Measurements Model validation Radiation Modeling in Vineyards Refined radiation algorithm

20 Modeling Below Canopy Winds in Vineyards Modification of wind profile in the canopy air space for vine canopy for canopy architecture Original wind extinction algorithm Revised wind extinction algorithm

21 TSEB-derived ET and T Using UAV Imagery ET ET ET T T T

22 Shadow Detection Algorithm GRAPEX UAV Shadow Detection True Color Image Shadowed areas highlighted = shadowed pixels Impacts of Shadows on Surface Energy Balance

23 PhoDAR (LIDAR-like) data GRAPEX UAV canopy Volume Automatic soil / vegetation discrimination, canopy volume relate to yield

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25 Data Assim Water Balance Energy Balance

26 Water Balance Estimated Root Zone Soil Moisture Assimilated versus Non-Assimilated with ET Data Fusion Non Assim Early June Assim Non Assim Mid July Assim

27 Preliminary Conclusions from GRAPEX Crop coefficient-based techniques have limited utility for estimating ET and stress in vineyards. Conclusions The TSEB land surface scheme combined with the multi-scale ALEXI/DisALEXI/Data Fusion approach is providing reliable daily ET and is being used to assess seasonal water use and impacts on yield and detect ET anomalies Refinements to TSEB model parameterizations for unique canopy structure, architecture and row spacing/orientation using the data collected from GRAPEX is improving model performance. Very high resolution imagery from UAVs can provide valuable information on landscape features and vine conditions not detectable at satellite resolutions. Combining water balance and energy balance modeling approaches via data assimilation has the potential of providing more reliable spatial mapping of root zone soil moisture at 30 m resolution

28 Expanding GRAPEX Study Sites GRAPEX Sites Expanded: to New Climate Zones & Varieties

29 GRAPEX 2018: Application of ET Toolkit to a Variable Rate Drip Irrigation System

30 The Challenge..