<p>Evapotranspiration (ET) is one of the most important factors for the water budget and physical processes in the tropical region. This variable affects the atmospheric water and it is important for its capacity to control precipitation, including its influence on absorption and reflection of solar and terrestrial radiation. In the tropical context ET is a relevant process, where the condensation of large amounts of water vapor leads to the release of latent heat energy. In order to understand ecohydrological and climatic synergies and interactions in the tropical basins, different models have tried to represent the hydrological processes in time and space. But most of these models depend on variables that should be measured in situ and are rarely available or limited in the tropical countries. This inevitably requires the model to be simple enough and the parameters can be estimated from climate and basin characteristics. In this regard, Zhang et al. (2008) developed a hydrological model Dynamic Water Balance (DWB). DWB is a semi-distributed model supported in the Budyko framework, which uses partition curves to distribute water to a number of components based on water availability and demand concepts. In general, the model assumes the control over the water balance is mostly dominated by the precipitation (P) and potential evapotranspiration.&#160;</p><p>The hydrologic structure of DWB consists of two tanks, soil moisture store and groundwater store, and adjust its mathematical relations through the optimization of four parameters. Due to its simplicity and strong concepts, DWB had been implemented successfully in several types of basins around the globe (Rodriguez et al., 2019).</p><p>This work presents DWBmodelUN, a hydrological R-package with the implementation of DWB in a regular mesh at a monthly time step. DWBmodelUN contains 12 functions related to data entry pre-processing, mathematical development of DWB, calibration algorithm Dynamical Dimension Search and an interactive graphical&#160; module. In overall terms, DWBmodelUN requires: (i) basin geographic data (defines the spatial resolution of the modelling), (ii) hydro-meteorological entry data (P, Temperatute, Streamflow) in raster format, (iii) initial values for the model parameters and (iv) setup data such as warm up, calibration and validation periods.&#160;</p><p>In addition, this package includes a practical example of application in Sogamoso River Basin, located at the Oriental mountain range of Colombia.&#160; Therefore, data sets with hydrological, meteorological and setup information were incorporated within the package.</p><p>This tool intents to spread&#160; the DWB model and facilitate its implementation in more basins. In this context, to execute DWBmodelUN users do not need extensive programming skills and the R-package was thought for easily adaptability.</p><p><strong>References</strong></p><p>Rodr&#237;guez, E., S&#225;nchez, I., Duque, N., Arboleda, P., Vega, C., Zamora, D., &#8230; Burke, S. (2019). Combined Use of Local and Global Hydro Meteorological Data with Hydrological Models for Water Resources Management in the Magdalena - Cauca Macro Basin &#8211; Colombia. Water Resources Management.&#160;</p><p>Zhang, L., Potter, N., Hickel, K., Zhang, Y., & Shao, Q. (2008). Water balance modeling over variable time scales based on the Budyko framework &#8211; Model development and testing. Journal of Hydrology, 360(1&#8211;4), 117&#8211;131.&#160;</p>
Droughts are a natural phenomenon of water deficit and represent one of the most dangerous natural hazards to human activities; accordingly, its understanding and monitoring are vital. For doing this, long historical series of precipitation and evapotranspiration are considered; however, the sources of this observed information on land are usually limited spatially and temporally. Consequently, the use of complementary sources of information, such as reanalysis, is appropriate in areas with scarce information. Thus, we have evaluated the use of the reanalysis databases of the eartH2Observe project (WFDEI & MSWEP) in the Magdalena-Cauca river basin in Colombia, through the calculation of three drought indicators (SPI, SPEI & WCI). The indices calculated with the in-situ data identified ten drought events of great affectation in the basin. Applying statistical and a Bootstrap uncertainty analysis, we evaluate the performance of the reanalysis, finding that the use of the MSWEP precipitation product has a good potential for the analysis of droughts in Colombia
The Magdalena-Cauca macro-basin (MCMB) in Colombia, by its tropical location, annually experiences the effects of movement of the Intertropical Convergence Zone, and it is highly affected by interannual macro-climatic phenomena, such as El Niño-Southern Oscillation (ENSO). With the aim of increasing the use of global reanalysis and remote sensing data for supporting water management decisions at the watershed scale and within the framework of the eartH2Observe research project, the aridity index (AI) was calculated with three different data sources. Precipitation products and AI results were compared with their corresponding in-situ national official data. The comparison shows high correlations between the AI derived from observed data and AI obtained from the reanalysis, with Pearson correlation coefficients above 0.8 for two of the products investigated. This shows the importance of using global reanalysis data in water availability studies on a regional scale for the MCMB and the potential of this information in others macrobasins in Colombia including the Orinoquia and Amazon regions, where in-situ data is scarce.Engineering
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