Agriculture
; Climate models
; Decision making
; Decision support systems
; Drought
; Food supply
; Moisture
; Soil moisture
; Water resources
; Weather forecasting
; Agricultural drought
; Atmospheric observations
; Humanitarian assistances
; Hydrologic conditions
; Management decisions
; Posteriori estimates
; Streamflow prediction
; Variable infiltration capacities
; Forecasting
; agrometeorology
; crop yield
; decision support system
; early warning system
; ensemble forecasting
; famine
; food security
; growing season
; soil moisture
; vulnerability
; East Africa
英文摘要:
The increasing food and water demands of East Africa's growing population are stressing the region's inconsistent water resources and rain-fed agriculture. More accurate seasonal agricultural drought forecasts for this region can inform better water and agropastoral management decisions, support optimal allocation of the region's water resources, and mitigate socioeconomic losses incurred by droughts and floods. Here we describe the development and implementation of a seasonal agricultural drought forecast system for East Africa (EA) that provides decision support for the Famine Early Warning Systems Network's (FEWS NET) science team. We evaluate this forecast system for a region of equatorial EA (2° S-8° N, 36-46° E) for the March-April-May (MAM) growing season. This domain encompasses one of the most food-insecure, climatically variable, and socioeconomically vulnerable regions in EA, and potentially the world; this region has experienced famine as recently as 2011. To produce an "agricultural outlook", our forecast system simulates soil moisture (SM) scenarios using the Variable Infiltration Capacity (VIC) hydrologic model forced with climate scenarios describing the upcoming season. First, we forced the VIC model with high-quality atmospheric observations to produce baseline soil moisture (SM) estimates (here after referred as SM a posteriori estimates). These compared favorably (correlation Combining double low line 0.75) with the water requirement satisfaction index (WRSI), an index that the FEWS NET uses to estimate crop yields. Next, we evaluated the SM forecasts generated by this system on 5 March and 5 April of each year between 1993 and 2012 by comparing them with the corresponding SM a posteriori estimates. We found that initializing SM forecasts with start-of-season (SOS) (5 March) SM conditions resulted in useful SM forecast skill (> 0.5 correlation) at 1-month and, in some cases, 3-month lead times. Similarly, when the forecast was initialized with midseason (i.e., 5 April) SM conditions, the skill of forecasting SM estimates until the end-of-season improved (correlation > 0.5 over several grid cells). We also found these SM forecasts to be more skillful than the ones generated using the Ensemble Streamflow Prediction (ESP) method, which derives its hydrologic forecast skill solely from the knowledge of the initial hydrologic conditions. Finally, we show that, in terms of forecasting spatial patterns of SM anomalies, the skill of this agricultural drought forecast system is generally greater (> 0.8 correlation) during drought years (when standardized anomaly of MAM precipitation is below 0). This indicates that this system might be particularity useful for identifying drought events in this region and can support decision-making for mitigation or humanitarian assistance.
Climate Hazards Group, Department of Geography, University of California, Santa Barbara, CA, United States; University Corporation for Atmospheric Research, Boulder, CO, United States; U.S. Geological Survey, Earth Resources Observation and Science Center, Sioux Falls, United States; Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, United States; Hydrological Sciences Laboratory, NASA, Goddard Space Flight Center, Greenbelt, MD, United States
Recommended Citation:
Shukla S,, McNally A,, Husak G,et al. A seasonal agricultural drought forecast system for food-insecure regions of East Africa[J]. Hydrology and Earth System Sciences,2014-01-01,18(10)