Crop Monitoring with Land Data Assimilation and Remote Sensing

Michael MarshallClimate Hazards Group (FEWSNET)

UC Santa Barbara001-8057555759 (office), 001-8058933146 (fax)

marshall@geog.ucsb.edu

2

Synopsis and Problem Statement More than 30% of people (primarily children) in sub-Saharan

Africa are undernourished Climatic shocks drive domestic food prices and production Crop monitoring and early warning is an effective mitigation

tool Remote sensing and surface reanalysis modeling techniques

enhance crop monitoring and early warning Crop stress (proportional to moisture in the root zone) can

lead to significant declines in crop yield

How can remotely sensed estimates of evapotranspiration (ET) be integrated with surface reanalysis data to augment crop monitoring?

3

Indices of Crop Stress

Precipitation– PDSE, PDSE-z, and CMI

(Palmer 1965)– SPI (McKee et al. 1993)

Vegetation– NDVI and VHI (Kogan 1995)

Evapotranspiration (ET)– WRSI (Doorenbos and Pruitt

1977)– ESI (Anderson 2007)

Soil Moisture (Koster and Suarez 1996)

4

Study Area

5

ET Model (Marshall et al. 2010)

fc = m2NDVI + b2

fg = m1EVI + b1 / m2NDVI + b2

ft =

fm = fAPAR / fAPARmx

fwet = RH10

Nwetmtgcc RfffffET

1 2

OPTMAX TT

e

pgs PETfET )1(f

wref

w

1

pc

gi PETS

WfET

5.0

(Betts et al. 1997)

(Chen et al. 1996)

(Fisher et al. 2008)

cc ETDPW

6

(NDVI, EVI): MODIS 16-day VI at 0.05° resolution (VPDmax, RHmin, RN, Tmax, PAR, LEs,i): GLDAS NOAH 3-hourly

surface reanalysis at 0.25° resolution (Crop production and area): Department of Resource Surveys

and Remote Sensing of the Ministry of Planning and National Development district-level maize statistics for the “long rains”

(Food security reports): FEWSNET annual online reports Spearmen’s rank correlation Qualitative analysis: SPI and MODIS LST in EWX

Data Handling and Processing

7

ρ = 0.55

ρ = 0.74

ρ = 0.74

8

Evaporative Stress Index (Canopy)

wetmtgc ffffESI 11

c

cc PET

ETESI 1

Crop stress is directly proportional to the amount of moisture in the root zone (transpiration). Therefore evaporation from the canopy and soil is negligible:

Assuming evaporation from the canopy and soil is negligible, ESI can be derived in terms of Fisher transpiration:

RN and PET (two highly uncertain ET terms) are eliminated.

9

2000

2003

10

2009

11

Implementation of ETa and ESIc in Crop Monitoring ESIc skewed- gamma or other standardization

Visualization of ESIc (post) with SPI (pre) in EWX

Forecast tool in semi-arid areas (Marsabit, Wajir, and West Pokot)

African Data Dissemination Service (ADDS)

Lagged vegetation/precipitation relationship and backcasting

Substitution of current ETa method in WRSI

12

THANK YOU