ABSTRACT:With the aim of improving the long-term mean annual surface water balance of Colombia, four new annual average precipitation fields are estimated at 4 km spatial resolution. To put in context, a concise literature review of rainfall in Colombia is presented. For estimation purposes, diverse multivariate geostatistical methods are implemented by combining information from 1180 raingauges covering the period 1950-2005, and satellite data from the tropical rainfall measuring mission (TRMM) for the period 1999-2005, used as a drift for the following geostatistical methods: (1) kriging with an external drift (KED), (2) standardized cokriging (SCK), (3) colocated cokriging (CCK), and (4) Markov regionalization CCK (CCKM). To ensure the reliability of the estimated precipitation fields, a detailed cross-validation procedure is performed, including univariate and bivariate analyses of residuals, which allows us to conclude that the best estimated rainfall field is obtained with KED, and the worst with SCK. Visual analyses are also performed in the search for consistency of the resulting precipitation fields. Furthermore, local (at-a-pixel) uncertainty modelling analysis is performed using the indicator approach. Conditional cumulative distribution functions (CCDF) are estimated using indicator CCK with Bayes-Markov hypothesis. Statistical descriptors for the pixel's CCDFs are estimated based on the resulting precipitation fields, including long-term mean, conditional variance and the coefficient of variation. These improved precipitation fields along with their estimated uncertainties are available (http://cancerbero.unalmed.edu.co/∼hidrosig/index.php) for the scientific community and constitute useful basic information for diverse applications in water resources, agriculture, hydropower generation, human health, risks and disaster prevention, and many other applied sectors in Colombia.

Distributed hydrological modeling has increased its popularity in the community, leading to the development of multiple models with different approaches. However, the rapid growth has also opened a gap between models, interfaces, and advanced users. User interfaces help to set up and pre-process steps. Nevertheless, they also limit the implementation of more complex experiments. This work presents the Watershed Modeling Framework (WMF) as a step forward in closing the interface–usage gap. WMF is a Fortran-Python module designed to provide tools to perform hydrological analysis and modeling that conceptualizes the watershed as an object with a defined topology, properties, and functions. WMF has a built-in hydrological model, geomorphological analysis functions, and a QGIS plugin. WMF interacts with other popular Python modules, making it dynamic and expandible. In this work, we describe the structure of WMF and its capabilities. We also provide some examples of its implementation and discuss its future development.

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Aquifers are ubiquitous, and their water is easy to obtain with low extraction costs. On many occasions, these characteristics lead to overexploitation due to important water level declines, reduction of river base flows, enhanced seawater intrusion, and wetland affection. The forecasted increase in water demands and global warming will impact the future availability of water resources. Conjunctive use of surface and subsurface waters can help in mitigating these impacts. There are two main conjunctive use strategies: artificial recharge (AR) and alternate conjunctive use (ACU). AR stores waters that are not to be used directly in aquifers. ACU utilizes groundwater in dry periods, while surface waters are preferred in wet ones; this allows the increase of water supply with lower dam storage, economic gains, and environmental advantages. Efficient conjunctive use can prevent soil salinization and waterlogging problems in semiarid countries due to excessive recharge from irrigation return flows or other origins. Groundwater is a neglected and generally misused resource to maintain environmental conditions. When considering the solution to a water resources problem, groundwater should always be part of the design as an alternative or a complementary resource. Aquifers have large inertia, and changes in their volumes are only noticeable after years of observations. Unfortunately, groundwater observation networks are much poorer than surface ones, something that should be changed if groundwater is to come to the rescue in these times of climate change. Human and material resources should be made available to monitor, control, analyze, and forecast groundwater.