The study of the dynamics of anthropic disturbances that have an effect on the hydrological systems in plains requires integral simulation tools for their diagnosis. The objective of this article is, first, to analyse and reproduce the spatio‐temporal interactions between groundwater (GW) and surface water, net recharge, GW level, surface run‐off, and evapotranspiration in the upper creek basin of Del Azul, which is located in the centre of the province of Buenos Aires, Argentina, and second, to obtain insights to apply the methodology to other similar situations. For this purpose, a model coupling the semidistributed hydrological model (Soil and Water Assessment Tool [SWAT]) and the hydrogeological model (MODFLOW) has been used. A simulation was carried out for a period of 13 years (2003–2015) on a daily scale. The application of the SWAT–MODFLOW coupling gave good results based on the adjustment between the calculated flows and levels, reaching a Nash–Sutcliffe of 0.6 and R20.6 at the Seminario hydrometric station located at the watershed outlet point. According to the annual average balance, out of the total rainfall, evapotranspiration accounts for 85%, recharge accounts for 10.2%, and surface run‐off accounts for 4.8%. Annual and monthly trends of the stream–aquifer interaction were determined, obtaining on average an annual GW discharge of 34 mm and an annual average recharge of the stream to the aquifer of 1.4 mm. Monthly GW discharges are higher in winter–spring (July to December with an average of 3.3 mm) and lower in summer–autumn (January to June with an average of 2.8 mm). The monthly average recharge of the stream towards the aquifer varies from 0.02 to 0.36 mm and is higher in March, May, and August, when water excess is produced in the basin. Through the analysis of coupled modelling, it is possible to analyse and reproduce the spatio‐temporal transitions of flow existing between the stream, the hyporheic zone, and the aquifer.

No abstract

No abstract

Water movement modeling in plain areas requires digital elevation models (DEMs) adequately representing the morphological and geomorphological land patterns including the presence of civil structures that could affect water flow patterns. This has a direct effect on water accumulation and water flow direction. The objectives of this work were to analyze, compare and improve DEMs so surface water movement in plain areas could be predicted. In order to do that, we evaluated the accuracy of a digital elevation data set consisting in 4064 points measured with a differential global positioning system (GPS) in a plain Several topographic attributes (i.e., height, surface area, land slope, delimitation of geomorphological units, civil structures, basin boundaries and streams network) and different interpolation methods were analyzed. The results showed that both the SRTM and the ALOS PALSAR DEMs had a ± 4.4 m root mean square error (RMSE) in contrast to the ASTER DEM which had a ± 9 m RMSE. Our analysis proved that the best DEM representing the study area is the SRTM. The most suitable interpolation methods applied to the SRTM were the inverse distance weighting and the ANUDEM, whereas the spline method displayed the lowest vertical accuracy. With the proposed method we obtained a DEM for the study area with a ± 3.2 m RMSE, a 33% error reduction compared to the raw DEM.

: Due to the socioeconomical impact of water extremes in plain areas, there is a considerable demand for suitable strategies aiding in the management of water resources and rainfed crops. Numerical models allow for the modelling of water extremes and their consequences in order to decide on management strategies. Moreover, the integration of hydrologic models with hydraulic models under continuous or event-based approaches would synergistically contribute to better forecasting of water extreme consequences under different scenarios. This study conducted at the Santa Catalina stream basin (Buenos Aires province, Argentina) focuses on the integration of numerical models to analyze the hydrological response of plain areas to water extremes under different scenarios involving the implementation of an eco-efficient infrastructure (i.e., the integration of a green infrastructure and hydraulic structures). The two models used for the integration were: the Soil and Water Assessment Tool (SWAT) and the CELDAS8 (CTSS8) hydrologic-hydraulic model. The former accounts for the processes related to the water balance (e.g., evapotranspiration, soil moisture, percolation, groundwater discharge and surface runoff), allowing for the analysis of water extremes for either dry or wet conditions. Complementarily, CTSS8 models the response of a basin to a rainfall event (e.g., runoff volume, peak flow and time to peak flow, flooded surface area). A 10-year data record (2003–2012) was analyzed to test different green infrastructure scenarios. SWAT was able to reproduce the waterflow in the basin with Nash Sutcliffe (NS) efficiency coefficients of 0.66 and 0.74 for the calibration and validation periods, respectively. The application of CTSS8 for a flood event with a return period of 10 years showed that the combination of a green infrastructure and hydraulic structures decreased the surface runoff by 28%, increased the soil moisture by 10% on an average daily scale, and reduced the impact of floods by 21% during rainfall events. The integration of continuous and event-based models for studying the impact of water extremes under different hypothetical scenarios represents a novel approach for evaluating potential basin management strategies aimed at improving the agricultural production in plain areas.

In this paper we present several hydrological time series from Argentina that include, evapotranspiration, precipitation, and stream flow. We survey previous results and apply the 0-1 test for chaos to classify the sequences as regular or chaotic. Previous studies have shown evidence of chaos in several observables from hydrology using the traditional phase space reconstruction method and the computation of Lyapunov exponents. The 0-1 test for chaos can be used as a first step to identify the type of time series, that later can be subjected to the more detailed analysis of the phase space reconstruction. Assuming that the systems that generated these time series are deterministic, the 0-1 test for chaos classifies all of them as chaotic