Francesca Bassani

Climate change is increasingly challenging agricultural productivity and global food security. However, the extent to which changes in temperature and precipitation will translate into cropland suitability across crops and global warming levels remains poorly constrained. Here, we use a data-driven model linking climate and soil conditions to observed crop yields to assess future changes in global cropland suitability for twelve major crops. We project suitability responses under four Global Warming Levels (+1.5 to +4◦C), quantifying transitions among suitability classes and the climatic drivers associated with these changes. Our results show widespread future declines in cropland suitability compared to the baseline period (1985-2014), affecting between 36 and 52% of the currently harvested areas, depending on the warming level considered, particularly across low-to mid-latitude regions. Suitability increases are projected for a subset of crops at mid-to high latitudes. More than 75% of crops presently grown in semi-arid and tropical regions become less suitable as warming intensifies. By contrast, barley, maize, and wheat show increased suitability at higher latitudes, especially at the transition between the current humid continental and subarctic climate zones. These findings underscore the need to explicitly integrate spatially-explicit information on expected changes in climatic and soil conditions into crop adaptation planning to anticipate regional vulnerabilities and support sustainable agricultural development.

River networks play a central role in regulating biogeochemical transformations at the catchment scale, yet a general scaling theory linking network structure to integrated metabolic function is still lacking. By positing the fundamental differences between blue (fluvial) and green (terrestrial) metabolisms in river basins, we focus on the former and, inspired by allometric scaling in biology, we treat river networks as model organisms whose effective body size is given by the volume of water stored within the channelized system. Using finite‐size scaling theory for space‐filling dendritic networks we derive exact relationships linking universal geomorphic exponents, such as Hack's law, the Hurst exponent, and the probability distribution of the total contributing area to novel scaling laws for river network volume and for a broader class of capacity measures that represent geometric controls on material processing. The theoretical predictions are validated using both optimal channel networks and digital elevation models of real river basins, which display exponent convergence, collapse of rescaled distributions across nested subbasins, and robustness under coarse graining. By linking river network geometry to integrated metabolic capacity, our framework provides a direct, scale‐invariant bridge between geomorphic organization and catchment‐scale blue metabolism. The resulting allometric relations suggest Kleiber‐like scaling between metabolic interfaces and the network equivalent of body size, offering a unifying basis for predicting riverine biogeochemical function across scales and setting the stage for integrated blue‐green metabolic theories.

Rainfed crops account for approximately 40% of India’s food production and support 60% of its livestock. Although linked to oceanic monsoon rainfall, their productivity also depends on terrestrially-sourced rainfall, particularly in the non-monsoon season. The degree to which rainfed crops rely on moisture sourced from evaporation in upwind irrigated areas remains largely unknown. Using a combination of models and observations, we show that evaporation from upwind irrigated crops contributes 7% (mean) ± 5% (spread) of the rainfall over rainfed areas annually, rising to 15 ± 10% during the pre-monsoon months (averaged over the years 2000–2020). In the absence of this input, water stress experienced by rainfed crops can increase by 5%–10% during the crucial mid to late crop growth phases, potentially affecting yields. Our results reveal an unrecognized atmospheric link between irrigated and rainfed agriculture that is overlooked in current agricultural policies. Planning and managing these systems holistically can help strengthen regional food and water security under future climates.

Assessing crop water requirements and sustainability under future climates is crucial to concurrently address water scarcity, food security, and ecosystem preservation. Yet, global climate and hydrological models differ substantially in estimating precipitation, potential evapotranspiration, and renewable freshwater, challenging future crop water use and sustainability assessments. Here, we perform a multi-model analysis to quantify how model uncertainty propagates into crop water needs and sustainability estimates. Results show end-of-century global uncertainty spreads of ~ 18% and ~ 51% for green and blue water footprints, respectively, relative to ensemble means. Blue water sustainability exhibits even larger variability, from 250% to 451%, depending on scenario and model choices. These uncertainties further intensify at finer spatial scales. Hydrological model discrepancies dominate blue water assessments, whereas climate model variability primarily affects green water estimates, particularly under high-emission scenarios. Accounting for model uncertainty is essential for reliable crop water estimates and to inform agricultural water management under climate change.

Rainfed crops account for approximately 40% of India’s food production and support 60% of its livestock. Although linked to oceanic monsoon rainfall, their productivity also depends on terrestrial evaporation, particularly in the non-monsoon season. However, the degree to which rainfed crops also rely on moisture sourced from upwind irrigated areas, remains largely unknown. Using a combination of models and observations, we show that upwind irrigated crops contribute 7%±6% of the rainfall over rainfed areas, rising to 15%±10% during the pre-monsoon months. In the absence of this input, water stress experienced by rainfed crops can increase by 5–10% during the crucial mid to late crop growth phases, potentially affecting yields. Our results reveal an unrecognized atmospheric link between irrigated and rainfed agriculture, which is overlooked in current agricultural policies. Planning and managing these systems in an holistic manner can help strengthen regional food and water security under future climates.

The assessment of crop water sustainability under future climate scenarios is crucial for coping with predicted water scarcity and for devising strategies to ensure global food security. In this context, the evaluation of crop water indicators generally relies on global scale projections of climatic and hydrologic variables which often provide divergent estimates of precipitation, potential evapotranspiration, and renewable freshwater rates, thus affecting the final evaluation of crop water needs and associated risks. In this work, by performing a multi-model analysis (considering four climate models and six water models from the Inter-Sectoral Impact Model Intercomparison Project ISIMIP2b), we (i) evaluate and map crop water needs and sustainability under current and future climate scenarios, (ii) quantify the uncertainty associated with the climate and impact model selection, particularly focusing on how such uncertainties propagate both in time (from 2000 to 2090) and in space (ranging from global scale to the smallest grid cell unit), and (iii) assess the major sources of uncertainty (global climate or water models). Our results reveal a trend of increasing water unsustainability under future scenarios, despite significant uncertainties across models. Hotspots of unsustainable water use are identified in the Mideastern United States, Central Europe, and parts of South America, where blue water demands are projected to increase by over 150% by the end of the century relative to the year 2000. At the global scale, variations in green and blue water footprints from the average across all models are between ±10% and ±30%, respectively. Such uncertainties are highly amplified as the spatial scale of analysis is increased. For example, country-scale variations in green and blue water footprints of ±25% and ±100% relative to the multi-model average are observed in the United States. Disagreement across global water models dominates global uncertainty for blue crop water use and sustainability calculations, while variability across climate models contributes more prominently to green water footprint uncertainty under severe climate change scenarios. This study emphasizes the critical role of uncertainty quantification in understanding the variability of crop water requirements, offering key insights for managing agricultural water resources under changing climates.

India and China host ~45% of the world’s irrigated area, with irrigation accounting for 65–75% of the total water usage in these countries. The impact of intense irrigation on regional precipitation and even monsoonal dynamics is well acknowledged. However, the degree to which recycled irrigation water helps sustain rainfed crops, acting as an indirect source of water supply, remains unknown. This is especially important in India and China, where irrigated crops are grown in close proximity to rainfed ones. In this study, we quantify (a) the contribution of atmospherically recycled irrigation water to rainfall over rainfed regions, and (b) the importance of this contribution for satisfying the water demand of rainfed crops. The methodology involves 20 years of global Lagrangian atmospheric model (FLEXPART) simulations tracking 10 million air parcels. These simulations were constrained by ERA5 reanalysis data and satellite-based terrestrial evaporation data from GLEAM4. Evaporation from irrigated and rainfed crops was computed using the FAO-Penman method. Air parcels that contribute to rainfall over rainfed crops were tracked backward in time for a period of 15 days. Subsequently, the contribution of evaporation from irrigated crops to rainfall over rainfed crop regions was computed. Preliminary results show that, on average, ~15% of the rainfall over rainfed crops can be attributed to irrigation evaporation in upwind regions. The irrigation contribution to rainfall reaches as high as 50% in parts of the intensively irrigated Indo-Gangetic plain. Stark differences are observed between India and China, with irrigation contribution to rainfall over rainfed regions being substantially higher in India. Removal of this irrigation contribution would result in an average increase in evaporative stress of ~10%, with a maximum increase of 25%. With irrigation projected to expand to sustain crop production in a changing climate, it is likely to play an indirect yet significant role in supporting rainfed crops as well. Our results highlight the relevance of considering recycled irrigation as an essential source of water supply for rainfed crops.

The increasing impacts of climate change are causing serious challenges for global food security and sustainable agriculture. A key concern is how changing climate conditions, such as precipitation and temperature, might influence the suitability of croplands and agricultural systems, with significant consequences for future food production and related policies. This issue is particularly relevant in Switzerland, as mountainous regions and lowlands are especially vulnerable to foreseen climate changes, including rising temperatures and changes in precipitation patterns, characterized by reduced summer rainfall and increased winter precipitation. Furthermore, soil properties, such as pH and organic carbon, are also expected to change due to increased aridity and warming. In this study, by establishing relations between soil and climate factors and crop yield, we evaluate the suitability of five major crops produced in Switzerland (namely rye, wheat, barley, vines, and maize) via a data-driven model. We derive spatially explicit results for current and future scenarios. Findings for the reference year 2000 show that the leading drivers affecting the suitability are mostly related to climate rather than soil conditions. The relative effect of precipitation, temperature, and solar radiation varies depending on the crop and its geographic location, highlighting context-specific impacts of climate variations and their interlinkages. Regarding future projections, we assess how shifts in projected temperature and rainfall regimes under three Representative Concentration Pathways (RCPs 2.6, 4.5, and 8.5) translate into spatial variations in crop suitability compared to the year 2000. Regions facing the strongest warming by 2090 are projected to lose suitability for all the crops considered here, with temperature emerging, overall, as the dominant driver of such shifts, particularly in the Swiss lowlands.

Allometric scaling relations are widely used to link biological processes in nature. They are typically expressed as power laws, postulating that the metabolic rate of an organism scales as its mass to the power of an allometric exponent, which ranges between 2/3 and 3/4. Several studies have shown that such scaling laws hold also for natural ecosystems, including individual trees and forests, riverine metabolism, and river network organization. Here, we focus on allometric relations at watershed scale to investigate “catchment metabolism”, defined as the set of ecohydrological and biogeochemical processes through which the catchment maintains its structure and reacts to the environment. By revising existing plant size-density relationships and integrating them across large-scale domains, we show that the ecohydrological fluxes (representative of metabolic rates of a large and diverse vegetation assemblage) occurring at the catchment scale are invariant with respect to its average above-ground biomass, while they scale linearly with the basin size. We verify our theory with hyper-resolution ecohydrological simulations across the European Alps, which represent an ideal case study due to the large elevation gradient affecting the availability of energy and water resources. Deviations from the isometric scaling are observed and ascribable to energy limitations at high elevations. Remote sensing data from semiarid and tropical basins are also used to show that the observed scaling of water and carbon fluxes with size holds across a broad spectrum of climatic conditions.

This research explores the long-term impacts of intricate dynamics of fluvial corridors on the carbon cycle, focusing on the interaction with tropical meandering rivers during formative events and riparian vegetation, particularly large wood recruitment. A multidisciplinary approach – including satellite data analysis, deterministic modeling and stochastic processes – is employed to assess the magnitude of carbon exported by these rivers.Meandering rivers exhibit lateral migration, with continuous erosion and deposition shaping their dynamics. Riparian vegetation, impacted by flooding and cutoff events, plays a pivotal role in carbon recruitment. A satellite-guided methodology across the Amazon basin correlates river-induced forest cover loss with eroded areas to estimate carbon recruitment.To understand the long-term river dynamics, a stochastic toy model linking river evolution, sinuosity and carbon export is proposed. The model equation for sinuosity growth includes deterministic and noisy terms, accounting for river elongation and cutoff events, respectively. In particular, a compound Poisson process is used to describe the evolution of sinuosity over time, revealing the impact of cutoff events on long-term dynamics. The calibration of the parameters characterizing the Poisson process is performed through the results of numerical simulations for river planar evolution, based on Zolezzi and Seminara (2001) morphodynamic model.This study indicates a close relationship between the carbon sequestration and the dynamics of tropical rivers, emphasizing the negative impact of alterations like damming and mining on river morphodynamics and carbon storage. This research provides valuable insights into the complex interactions within fluvial corridors, contributing to our understanding of carbon cycling in these critical ecosystems.