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Record W4408349838 · doi:10.1016/j.qeh.2025.100061

Sedimentary records from human-made talavs reveal climate risks in semi-arid watersheds of India

2025· article· en· W4408349838 on OpenAlex
Soumyajit Sarkar, Jill Leonard‐Pingel, Andrew V. Michelson, Ambili Anoop, Praveen K. Mishra, Swagata Chakraborty, Kushank Bajaj, Uma Shankar Singh, Victoria A. Petryshyn, R.K. Ray, Pandurang Sabale, Atmadeep Bhattacharya, M. Kirby, Amir Bazaz

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueQuaternary Environments and Humans · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture, Water, and Health
Canadian institutionsUniversity of British Columbia
FundersUniversity of Colorado BoulderIndian Institute of Science Education and Research MohaliIndian Institute of Science Education and Research PuneDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsAridSedimentary rockHydrology (agriculture)Climate changeGeologyWater resource managementEnvironmental sciencePhysical geographyEarth scienceGeographyOceanographyPaleontologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Assessing climate impacts in semi-arid watersheds, which are home to populous semi-arid regions of South Asia, are becoming increasingly critical as these regions emerge as climate hotspots. Century-scale records of climate impacts, preserved in terrestrial sedimentary archives, are some of only kinds of investigations that can provide the necessary insights into how local climate variations impact these watersheds. Here, we investigate sedimentary records preserved in a unique type of human-made water bodies, which are commonly present in arid and semi-arid regions of south Asia. Known as ‘ talavs ’, human-made water bodies are ubiquitous in south Asia and have been historically constructed by damming seasonal rain-fed distributaries to conserve rainwater for the purposes of sustenance and agriculture in water-stressed regions. Integrating a multidisciplinary approach comprising remote sensing, lake geophysics, lithostratigraphic (sedimentological, mineralogical & geochemical measurements), and radiometric dating, we reconstruct century-scale records of landscape erosion & resultant run-off and in water-stressed catchments in one of the most climatologically threatened watersheds of western India, namely the Bhima watershed. Our reconstructions show that land erosion and subsequent sediment deposition in talavs are tied to the regional expressions of the Indian summer monsoon (ISM). We also find that while the landscape evolution is sensitive to divisional expressions of hydroclimate variability (associated with the ISM), the intensity of run-off and erosion is not a simple function of rainfall intensity; in fact, we find that land-surface erodibility is impacted by land-use patterns and incidence of prior climate events (e.g. flooding) and that these effects are more prominent in drier catchments (which also experience more extreme climate events) than in wetter parts of the watersheds. Based on our investigation, we conclude that drier catchments of watersheds in semi-arid regions are at an elevated risk of direct climate impacts than the wetter catchments in the same watershed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.261
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it