Javier Houspanossian

Groundwater level fluctuations play a critical role in shaping hydrological extremes in flat sedimentary landscapes, where shallow water table depth (WTD) and strong surface-subsurface connectivity modulate the impacts of floods and droughts. The Western Pampean Plain (Argentina) exemplifies these dynamics; however, accurate modeling is often hindered by the lack of continuous in situ monitoring. In this context, manual WTD measurements collected by local farmers represent an underexploited source of information for modeling. In this study, we developed a Random Forest framework integrating farmer-operated observations with climatic and satellite-derived data and evaluated its ability to reconstruct and predict WTD. We tested seven modeling strategies, integrating: (i) climatic variables (including effects up to 15 months); (ii) high-resolution satellite-derived Surface Water Cover Index (SWCI) from Landsat; and (iii) coarse-resolution Terrestrial Water Storage Anomalies (TWSA) from GRACE. The best-performing model integrated climatic variables and SWCI, yielding strong reconstruction (R² = 0.861, RMSE = 0.266 m) and robust prediction (R² = 0.752, RMSE = 0.344 m) performances under cross-validation and rolling-origin validation, respectively. Model interpretation revealed SWCI as the dominant predictor, reflecting the strong surface-subsurface connectivity that characterizes this environment. This study provides a practical framework that integrates farmer-operated groundwater monitoring with freely available satellite observations to support agricultural decision-making in flood and drought risk management across flat sedimentary landscapes.

El Oeste de la región Pampeana es conocido por su alternancia entre ciclos de inundación y sequías, enfrentando importantes desafíos relacionados a la gestión del agua. En este sentido, comprender la relación entre los fenómenos hidrológicos extremos y los excesos y déficits de precipitación acumulados resulta relevante para la planificación y gestión territorial. En este estudio se analizó la relación entre la variabilidad hidrológica y la variabilidad climática en el Oeste de la región Pampeana, desde el año 2000 hasta el 2023. Para este análisis se construyeron series temporales mensuales de anomalías de almacenamiento de agua terrestre (GRACE/GRACE-FO), de cobertura superficial de agua (Landsat) y del índice estandarizado de precipitación-evapotranspiración (SPEI) a múltiples escalas temporales (1 a 48 meses). A partir del método de nivel de umbral se identificaron tres episodios de inundación y dos de sequías. Se evidenció que las condiciones acumuladas extremadamente húmedas conjuntamente con niveles altos de almacenamiento de agua terrestre pueden generar inundaciones severas. Por otra parte, las altas correlaciones entre SPEI de 36 y 48 meses con el almacenamiento de agua terrestre (r = 0.85; p < 0,01) demostraron la importancia de los excesos y déficits de precipitación acumulados en el tiempo para comprender la sucesión de episodios de inundaciones y sequías, así como también la alta capacidad de los índices para monitorear el estado hidrológico de la región. Estos hallazgos resaltan la relevancia de las observaciones satelitales para mejorar la gestión y reducción de los riesgos asociados a las inundaciones y sequías.

Regional effects of farming on hydrology are associated mostly with irrigation. In this work, we show how rainfed agriculture can also leave large-scale imprints. The extent and speed of farming expansion across the South American plains over the past four decades provide an unprecedented case of the effects of rainfed farming on hydrology. Remote sensing analysis shows that as annual crops replaced native vegetation and pastures, floods gradually doubled their coverage, increasing their sensitivity to precipitation. Groundwater shifted from deep (12 to 6 meters) to shallow (4 to 0 meters) states, reducing drawdown levels. Field studies and simulations suggest that declining rooting depths and evapotranspiration in croplands are the causes of this hydrological transformation. These findings show the escalating flooding risks associated with rainfed agriculture expansion at subcontinental and decadal scales.

Las rastrilladas suelen ser conceptualizadas como caminos indígenas que representan el tránsito de los pueblos originarios por sus territo rios. En tanto expresiones materiales de circulación en el paisaje, creemos que reflejan un conjunto de tramas de relaciones y territorialida des desarrolladas en el tiempo. Para este trabajo nos concentramos en el área donde está la mayor parte de las rastrilladas utilizadas por Mansilla en su viaje a Leuvucó, fines del siglo XIX, la cual incluye partes de la denominada Frontera Sur y del MamüllMapu. Además de sus escritos, realizamos un análisis cartográfico mediante el uso de Sistema de Información Geográfica como metodología para profundizar en los lugares que son articulados en conexiones directas o aquellos que son evitados. Los resultados muestran diferencias significativas entre los caminos de la Frontera Sur (sector norte) y los del Mamüll Mapu (sector sur). Entendemos esas diferencias como parte de la te rritorialidad y cosmovisión rankülche, específicamente en relación a la conformación de los territorios de ocupación efectiva, los territorios dominados y al desarrollo de prácticas consuetudinarias. En este sentido, el estudio de las rastrilladas constituye una interesante vía de análisis para pensar, a nivel regional, diferentes dimensiones de la territorialidad indígena.

In this paper, we explored how aridity influences the regional deforestation and land-use patterns (i.e. crops/pastures) in South American Dry Chaco. To do this, we contrasted land use during last decade (2001–2012) with a spatially explicit aridity index, which we complemented with a crop water balance model. Land-use classifications were performed by considering the temporal variability of NDVI from MODIS satellites, showing that 40 and 60% of deforested land was assigned to crops and pastures, respectively. Results indicate that although the regional deforestation pattern was not associated with the aridity gradient, with drier areas similarly deforested as wetter areas, contrasting differences were observed in the use of this land, with crops mostly located (90%) in wetter areas and pastures evenly distributed across the whole aridity gradient. This research highlighted the strong effect of water limitations on the land-use option after deforestation and may help to set the basis for future land-use planning policies.

Land cover changes may affect climate and the energy balance of the Earth through their influence on the greenhouse gas composition of the atmosphere (biogeochemical effects) but also through shifts in the physical properties of the land surface (biophysical effects). We explored how the radiation budget changes following the replacement of temperate dry forests by crops in central semiarid Argentina and quantified the biophysical radiative forcing of this transformation. For this purpose, we computed the albedo and surface temperature for a 7‐year period (2003–2009) from MODIS imagery at 70 paired sites occupied by native forests and crops and calculated the radiation budget at the tropopause and surface levels using a columnar radiation model parameterized with satellite data. Mean annual black‐sky albedo and diurnal surface temperature were 50% and 2.5 °C higher in croplands than in dry forests. These contrasts increased the outgoing shortwave energy flux at the top of the atmosphere in croplands by a quarter (58.4 vs. 45.9 W m⁻²) which, together with a slight increase in the outgoing longwave flux, yielded a net cooling of −14 W m⁻². This biophysical cooling effect would be equivalent to a reduction in atmospheric CO₂ of 22 Mg C ha⁻¹, which involves approximately a quarter to a half of the typical carbon emissions that accompany deforestation in these ecosystems. We showed that the replacement of dry forests by crops in central Argentina has strong biophysical effects on the energy budget which could counterbalance the biogeochemical effects of deforestation. Underestimating or ignoring these biophysical consequences of land‐use changes on climate will certainly curtail the effectiveness of many warming mitigation actions, particularly in semiarid regions where high radiation load and smaller active carbon pools would increase the relative importance of biophysical forcing.