Abstract. An analysis of hydrologic variability in Colombia shows different seasonal effects associated with E1 Nifio/Southern Oscillation (ENSO) phenomenon. Spectral and cross-correlation analyses are developed between climatic indices of the tropical Pacific Ocean and the annual cycle of Colombia's hydrology: precipitation, river flows, soil moisture, and the Normalized Difference Vegetation Index (NDVI). Our findings indicate stronger anomalies during December-February and weaker during March-May. The effects of ENSO are stronger for streamflow than for precipitation, owing to concomitant effects on soil moisture and evapotranspiration. We studied time variability of 10-day average volumetric soil moisture, collected at the tropical Andes of central Colombia at depths of 20 and 40 cm, in coffee growing areas characterized by shading vegetation ("shaded coffee"), forest, and sunlit coffee. The annual and interannual variability of soil moisture are highly intertwined for the period 1997-1999, during strong E1 Nifio and La Nifia events. Soil moisture exhibited greater negative anomalies during 1997-1998 E1 Nifio, being strongest during the two dry seasons that normally occur in central Colombia. Soil moisture deficits were more drastic at zones covered by sunlit coffee than at those covered by forest and shaded coffee. Soil moisture responds to wetter than normal precipitation conditions during La Nifia 1998-1999, reaching maximum levels throughout that period. The probability density function of soil moisture records is highly skewed and exhibits different kinds of multimodality depending upon land cover type. NDVI exhibits strong negative anomalies throughout the year during E1 Nifios, in particular during September-November (year 0) and June-August (year 0). The strong negative relation between NDVI and E1 Nifio has enormous implications for carbon, water, and energy budgets over the region, including the tropical Andes and Amazon River basin.

The Iowa Flood Center (IFC), established following the 2008 record floods, has developed a real-time flood forecasting and information dissemination system for use by all Iowans. The system complements the operational forecasting issued by the National Weather Service, is based on sound scientific principles of flood genesis and spatial organization, and includes many technological advances. At its core is a continuous rainfall–runoff model based on landscape decomposition into hillslopes and channel links. Rainfall conversion to runoff is modeled through soil moisture accounting at hillslopes. Channel routing is based on a nonlinear representation of water velocity that considers the discharge amount as well as the upstream drainage area. Mathematically, the model represents a large system of ordinary differential equations organized to follow river network topology. The IFC also developed an efficient numerical solver suitable for high-performance computing architecture. The solver allows the IFC to update forecasts every 15 min for over 1,000 Iowa communities. The input to the system comes from a radar-rainfall algorithm, developed in-house, that maps rainfall every 5 min with high spatial resolution. The algorithm uses Level II radar reflectivity and other polarimetric data from the Weather Surveillance Radar-1988 Dual-Polarimetric (WSR-88DP) radar network. A large library of flood inundation maps and real-time river stage data from over 200 IFC “stream-stage sensors” complement the IFC information system. The system communicates all this information to the general public through a comprehensive browser-based and interactive platform. Streamflow forecasts and observations from Iowa can provide support for a similar system being developed at the National Water Center through model intercomparisons, diagnostic analyses, and product evaluations.

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We present evidence that the El Niño phenomenon intensifies the annual cycle of malaria cases for Plasmodium vivax and Plasmodium falciparum in endemic areas of Colombia as a consequence of concomitant anomalies in the normal annual cycle of temperature and precipitation. We used simultaneous analyses of both variables at both timescales, as well as correlation and power spectral analyses of detailed spatial (municipal) and temporal (monthly) records. During "normal years," endemic malaria in rural Colombia exhibits a clear-cut "normal" annual cycle, which is tightly associated with prevalent climatic conditions, mainly mean temperature, precipitation, dew point, and river discharges. During historical El Niño events (interannual time scale), the timing of malaria outbreaks does not change from the annual cycle, but the number of cases intensifies. Such anomalies are associated with a consistent pattern of hydrological and climatic anomalies: increase in mean temperature, decrease in precipitation, increase in dew point, and decrease in river discharges, all of which favor malaria transmission. Such coupling explains why the effect appears stronger and more persistent during the second half of El Niño's year (0), and during the first half of the year (+1). We illustrate this finding with data for diverse localities in Buenaventura (on the Pacific coast) and Caucasia (along the Cauca river floodplain), but conclusions have been found valid for multiple localities throughout endemic regions of Colombia. The identified coupling between annual and interannual timescales in the climate-malaria system shed new light toward understanding the exact linkages between environmental, entomological, and epidemiological factors conductive to malaria outbreaks, and also imposes the coupling of those timescales in public health intervention programs.