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DWBmodelUN: an R-package for the hydrological model Dynamic Water Balance

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<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. </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  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. </p><p>In addition, this package includes a practical example of application in Sogamoso River Basin, located at the Oriental mountain range of Colombia.  Therefore, data sets with hydrological, meteorological and setup information were incorporated within the package.</p><p>This tool intents to spread  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>Rodríguez, E., Sánchez, I., Duque, N., Arboleda, P., Vega, C., Zamora, D., … 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 – Colombia. Water Resources Management. </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 – Model development and testing. Journal of Hydrology, 360(1–4), 117–131. </p>
Title: DWBmodelUN: an R-package for the hydrological model Dynamic Water Balance
Description:
<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.
 </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  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.
 </p><p>In addition, this package includes a practical example of application in Sogamoso River Basin, located at the Oriental mountain range of Colombia.
  Therefore, data sets with hydrological, meteorological and setup information were incorporated within the package.
</p><p>This tool intents to spread  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>Rodríguez, E.
, Sánchez, I.
, Duque, N.
, Arboleda, P.
, Vega, C.
, Zamora, D.
, … 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 – Colombia.
Water Resources Management.
 </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 – Model development and testing.
Journal of Hydrology, 360(1–4), 117–131.
 </p>.

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