Droughts

Brazil is widely recognized as a global hotspot for flash drought, which sets in over weeks rather than a season, yet events are often reported under other names, among them wet-season dry spells, leaving the evidence unconsolidated. We reviewed 92 articles from 2012 to September 2024. From these, 23 of them were Brazil-focused events. Only five of those explicitly examined flash drought, and at least 35 definitions were in use across the reviewed set, hampering cross-study comparison and early warning; the North, Center-West and South remain underrepresented.

About half the rain falling on the Amazon returns to the air from soil and plants, so its response to clearing and warming bears on rainfall across South America. Existing estimates are too coarse to detect fine-scale signal of deforestation. We used a surface energy balance model on satellite imagery resolved dry-season losses at 30 meters across Brazil’s 1.3 million square kilometer arc of deforestation, from 1990 to 2022. Over remaining forest ET rose 11 ± 1.5% while cleared land lost 41 ± 2.1%; since forest still covers most of the region, the area-wide trend was positive, 10 ± 2.1%. The ET rise is atritubeted to forest responding to warmer, drier air, though continued clearing could reverse it.

The Pantanal, the world’s largest tropical wetland, dried unusually over 2000-2021, with climate variability and land clearing in its headwaters both proposed as causes. Land-cover maps, gauged discharge and records of rainfall and evaporative demand back to 1951 were combined in a water balance analysis for the Upper Paraguay River Basin, reaching three decades further back than the land-cover record. We found that the runoff change across two wet and two dry periods, 96% traced to climate and only 4% to land cover, while wetland area shrank about 30% after 1985. The recent dry period was hotter and more arid than the 1965-1975 drought and may worsen rather than revert to humid conditions.

This study aims to better understand flash droughts worldwide and their varying characteristics and impacts. We surveyed the experiences of people affected by flash droughts and then examined a wide range of literature, including non-English and nonacademic sources. This helped us understand how flash droughts can differ from those commonly studied in the United States and China. We identified and described five types of flash droughts, some of which may not be detected by current drought measurement methods. It is crucial to include all types of flash droughts in drought monitoring systems and management plans, as they are expected to become more common due to global warming. We can then better prepare for and reduce the impacts of this growing threat.

Attributing a smallholder harvest to the farmer’s decisions rather than to soil and weather has been difficult, since field records are scarce. A process-based crop model simulated maize yields across all 72 of Zambia’s districts from 1979 to 2016, varying cultivar, fertilizer rate and planting date, which resolves those three choices separately for the first time nationally. Management explained 53% of yield variance overall, from 27% in the drier south to 82% in the wetter north, where fertilizer alone accounted for 72%.

Drought management is currently informed by a variety of approaches, mostly responding to drought crisis when it happens. Toward more effective and integrated drought management, we introduce a conceptual drought diagnosis framework inspired by diagnostic concepts from the field of medicine. This framework comprises five steps: 1. Initial diagnostic assessment; 2. Diagnostic testing; 3. Consultation; 4. Communication of the diagnosis; and 5. Treatment and prognosis. This framework can help drought managers to be more proactive in enabling drought-affected regions to become more drought resilient in the future.

We introduce SMAP-HydroBlocks (SMAP-HB), a high-resolution satellite-based surface soil moisture dataset at an unprecedented 30-m resolution (2015–2019) across the conterminous United States. SMAP-HB was produced by using a scalable cluster-based merging scheme that combines high-resolution land surface modeling, radiative transfer modeling, machine learning, SMAP satellite microwave data, and in-situ observations. We evaluated the resulting dataset over 1,192 observational sites. Its largest benefit of SMAP-HB is the high spatial detail and improved representation of the soil moisture spatial variability and spatial accuracy with respect to SMAP products.

Drought monitoring and yield prediction often rely on coarse-scale hydroclimate data or (infrequent) vegetation indexes that do not always indicate the conditions farmers face in the field. Consequently, decision-making based on these indices can often be disconnected from the farmer reality. Our study focuses on smallholder farming systems in data-sparse developing countries, and it shows how field-scale soil moisture can leverage and improve crop yield prediction and drought impact assessment.

Integrating computational models and hydroclimate data for actionable agriculture decision-making. Towards resilience and adaptability in a changing climate.