Livestock Early Warning System for Africa’s Rangelands - Monitoring and Predicting Agricultural Drought: A Global Study - page 292

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Line
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-0.0
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Norm
PgEn

Figure 22.4 The deviation in forage standing crop for cattle compared to 30-year means of
da ily standing crop for a rangeland community in southeastern Kenya, as estimated by the
Li vestock Early Warning System. The dotted lines show the upper and lower 66% confidence
limits of 10- to 90-day projections.

and improved training of local extension officers. Issues of literacy, tradi-
tional pastoral decision-making processes, water availability, disease inci-
dence, and conflict must be considered in devising effective communication
instruments in pastoral communities.

[292

Re flections on the Future
Agricultural practitioners, regardless of the decision environment, have
not had access to reliable production estimates relative to long-term data
in a spatially coherent manner. The emergence of geo-referenced weather
data, offered on-line in near-real time, coupled with automated modeling
environments, is ushering in a new suite of tools for the agricultural and
natural resource decision-maker. These tools could easily be integrated into
a suite of new tools that allow the emergence of highly integrated precision
landscape analysis systems, allowing decision-makers to explore issues of
crop production, disease risk, drought, hydrology, and market conditions
in a manner not experienced before.
Adapting models to the new realities of weather data systems (satellite-
based, radar, distributed ground-satellite-web linked systems) needs to be
considered in the near future. Higher resolution imagery, greater comput-
ing power, and stronger institutional collaboration on data sharing are go-
ing to make drought monitoring a more routine process that a wide array
of decision-makers can access.