Luis E. Peña’s research while affiliated with University of Ibagué and other places

Frequency analysis has been the most widely used tool worldwide to dimension water-related infrastructures and evaluate flood risks. The concept of stationarity has been a common and practical hypothesis in hydrology for many years. However, in recent decades due to climate change pressure and changes in land use, it has been related to the presence of time-series trends that in hydrology indicate non-stationary effects. In this sense, the need to comprehensively address non-stationary frequency analysis has been identified. This study proposes to incorporate the non-stationary flood frequency analysis into the dimensioning process of road structures with the following objectives: i) evaluate the effect of land use on peak flow in a simulated period of 129 years, ii) evaluate covariates related to land use, and iii) evaluate covariates related to climate change. To this end, road drainage simulation exercises were carried out in three sections of the Ibagué-Cajamarca road located in Colombia. Likewise, the Generalized Additive Models for Location, Scale and Shape was implemented for the non-stationary analysis, and covariates related to climate variability were included, such as El Niño-Southern Oscillation indices (ONI12, ONI3.4, MEI, and SOI), and the Pacific Decadal Oscillation (PDO) index, as well as some related to the evolution of land use such as hydraulic conductivity, soil water storage in the root zone, and infiltration capacity represented in the curve number. The results indicate that the non-stationary analysis improves the prediction of maximum flows, and it is possible to obtain road drainage dimensioning that adjusts to climate and land-use variations.

Rainwater harvesting has proven to be a valuable strategy for mitigating the effects of global climate change. However, most of the techniques reported in the academic literature are based on capturing surface runoff generated by rainfall, and therefore, ponds are located close to surface currents, implying investments in infrastructure to conduct water to the place where it is utilized. The aims of this research are the following: i) develop a methodology for the detection of ponds for rainwater harvesting through hydrological and geospatial analyses based on terrain curvature, and ii) identify relevant variables to establish the potential storage volume in ponds. For this purpose, the study was performed in the Tolima region of Colombia with an area of 23,663 km², where 32% corresponds to arid and semi-arid areas. The detection of ponds from the terrain curvature was carried out using geographic information systems and the estimation of daily storage in the rainwater harvesting pond (RWHP) system. Likewise, the principal component analysis identified key variables in the process of detecting and selecting ponds. The results show that the proposed methodology allows the detection of potential ponds for rainwater harvesting near cultivation and water demanding zones for various uses, which could introduce relevant variables in decision-making processes and, decrease water supply distribution costs in semi-arid areas.

This investigation proposes the use of the analytic hierarchy process (AHP) to evaluate potential sites for stream monitoring and broadcast of flood warnings. The methodology adopts variables established by the World Meteorological Organization (WMO) for the selection of stream-monitoring sites and incorporates new variables associated with the stream morphometry and hydraulics. The proposed approach quantifies subjective valuations through pairwise comparisons of judgements within the selection criteria. The uncertainty of expert judgement was assessed via Monte Carlo simulations and its effects on the resulting priority vector were analysed. This approach was applied on three main mountain watershed streams at which 11 alternative stream-gauging sites were evaluated and scored. According to our findings, six variables explain 0.711 of the total weight in the priority vector for the evaluation of a candidate site. Our approach is suitable for selecting the most stable alternative location based on a multi-criteria analysis in an inter-comparison arrangement.

Changes in land use within a catchment are among the causes of non-stationarity in the flood regime, as they modify the upper soil physical structure and its runoff production capacity. This paper analyzes the relation between the variation of the upper soil hydraulic properties due to changes in land use and its effect on the magnitude of peak flows: (1) incorporating fractal scaling properties to relate the effect of the static storage capacity (the sum of capillary water storage capacity in the root zone, canopy interception and surface puddles) and the upper soil vertical saturated hydraulic conductivity on the flood regime; (2) describing the effect of the spatial organization of the upper soil hydraulic properties at catchment scale; (3) examining the scale properties in the parameters of the Generalized Extreme Value (GEV) probability distribution function, in relation to the upper soil hydraulic properties. This study considered the historical changes of land use in the Combeima River catchment in South America, between 1991 and 2007, using distributed hydrological modeling of daily discharges to describe the hydrological response. Through simulation of land cover scenarios, it was demonstrated that it is possible to quantify the magnitude of peak flows in scenarios of land cover changes through its Wide-Sense Simple Scaling with the upper soil hydraulic properties.