ELSEVIER | Journal of Hydrology: Regional Studies
Friso Holwerda a, Diego Salazar-Martínez b, Thomas R.H. Holmes c, Christopher R. Haind, Martha C. Andersone
- a Instituto de Ciencias de la Atmósfera y Cambio Climático, Universidad Nacional Autónoma de México, Circuito de la Investigación Científica, Ciudad Universitaria, Coyoacán, 04510, Ciudad de Mexico, Mexico
- b Sustainable Agricultural Water Systems Unit, USDA-ARS, Davis, CA, United States
- c NASA Goddard Space Flight Center, Greenbelt, MD, United States
- d NASA Marshall Space Flight Center, Huntsville, AL, United States
- e Hydrology and Remote Sensing Laboratory, USDA-ARS, Beltsville, MD, United States
Abstract
Study region
Central Plateau of Mexico
Study focus
This study investigated the relationships between yield anomalies of rainfed crops and six drought indices: evaporative stress indices (ESIs) derived from the ALEXI, MOD16, and GLEAM evapotranspiration products; the MODIS NDVI anomaly; the standardized precipitation index (SPI) based on spatially interpolated rain gauge data; and the Mexico Drought Monitor (MDM). Drought indices were calculated as a function of calendar time (all indices) and time from MODIS-derived green-up onset (all indices except MDM). To evaluate the effects of spatial resolution, indices were analyzed both at their native spatial resolutions and at a common 0.1° grid.
New hydrological insights for the region
Significant delays in satellite-derived green-up onset were observed during drought years, likely due to postponed sowing. Aligning drought variables to green-up onset improved temporal synchronization of crop growth stages across years. For corn, this alignment revealed that the strongest relationships between yield anomalies and cumulative NDVI anomaly/evaporative stress indices occurred during the mid-season growth stage. Degrading the spatial resolution generally weakened the drought index-yield anomaly relationships, particularly for the NDVI anomaly. The ALEXI-based ESI and MODIS NDVI anomaly showed the strongest relationships with crop yield anomalies. Mixed results were obtained for ESIMODIS, while the performance of ESIGLEAM was likely affected by its lower spatial resolution. Both the SPI and the MDM showed the weakest relationships.
