| Development of reliable monitoring and prediction indices and tools are fundamental to
drought preparedness, management, and response decision making. This presentation
provides an overview of the Global Integrated Drought Monitoring and Prediction System
(GIDMaPS) which offers near real-time drought information using both remote sensing
observations and model simulations. Designed as a cyberinfrastructure system,
GIDMaPS provides drought information based on a wide range of model simulations
and satellite observations from different space agencies. Numerous indices have
been developed for drought monitoring based on various indicator variables (e.g.,
precipitation, soil moisture, water storage). Defining droughts based on a single variable
(e.g., precipitation, soil moisture or runoff) may not be sufficient for reliable risk
assessment and decision making. GIDMaPS provides drought information based on
multiple indices including Standardized Precipitation Index (SPI), Standardized Soil
Moisture Index (SSI) and the Multivariate Standardized Drought Index (MSDI) which
combines SPI and SSI probabilistically. In other words, MSDI incorporates the
meteorological and agricultural drought conditions for overall characterization of
droughts, and better management and distribution of water resources among and across
different users. The seasonal prediction component of GIDMaPS is based on a
persistence model which requires historical data and near-past observations. The seasonal
drought prediction component is designed to provide drought information for water
resource management, and short-term decision making. In this presentation, both
monitoring and prediction components of GIDMaPS will be discussed, and the results
from several major droughts including the 2013 Namibia, 2012-2013 United States,
2011-2012 Horn of Africa, and 2010 Amazon Droughts will be presented. The
presentation will highlight how this drought cyberinfrastructure system can be used to
improve water resource management in California. Furthermore, the presentation
provides an overview of the information farmers need for better decision making and
how GIDMaPS can be used to improve decision making and reducing drought
impacts.
Further Reading
Hao Z., AghaKouchak A., Nakhjiri N., Farahmand A., 2014, Global Integrated
Drought Monitoring and Prediction System, Scientific Data, 1:140001, 1-10, doi:
10.1038/sdata.2014.1.
Momtaz F., Nakhjiri N., AghaKouchak A., 2014, Toward a Drought Cyberinfrastructure
System, Eos, Transactions American Geophysical Union, 95(22), 182-183,
doi:10.1002/2014EO220002.
AghaKouchak A., 2014, A Baseline Probabilistic Drought Forecasting Framework Using
Standardized Soil Moisture Index: Application to the 2012 United States Drought,
Hydrology and Earth System Sciences, 18, 2485-2492, doi: 10.5194/hess-18-2485-2014. |