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Record W2104312679 · doi:10.14796/jwmm.r220-01

Urbanization Impacts on Houston Rainstorms

2004· article· en· W2104312679 on OpenAlexvenueno aff
Steven J. Burian, J. Marshall Shepherd

Bibliographic record

VenueJournal of Water Management Modeling · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsnot available
FundersAmerican Society for Engineering EducationNational Aeronautics and Space Administration
KeywordsUrbanizationEnvironmental scienceHydrology (agriculture)Water resource managementGeologyGeotechnical engineeringEconomicsEconomic growth

Abstract

fetched live from OpenAlex

During urbanization the natural landscape is altered by removal of indigenous vegetation, stripping of topsoil, modification of the soil profile, importation of fill material, compaction of soil layers, and the introduction of impervious surfaces. These actions alter the hydrologic response at the regional and catchment scales, decreasing travel time of overland flow, infiltration, soil water content, and groundwater recharge, and increasing surface runoff volumes, discharge rates, and pollutant loadings. Thesearedirectandquantifiable impacts to the hydrologic cycle manifested at and below the land surface, but there are other impacts not as well understood or quantifiable that occur through the land surface-atmosphere interface. One such impact is the influence of urban development on mesoscale circulations and resulting convection. Hypothesized mechanisms for urban enhancement of convective rainfall include enhanced convergence caused by the urban heat island, drag effects of the built-up surface, and modified microphysical and dynamical processes caused by the introduction of water and cloud condensation nuclei from automobiles and industry. Decades of accumulated observational and modeling evidence has shown that major cities may indeed be influencing convective activity causing modified precipitation patterns. This chapter seeks to corroborate these findings by summarizing evidence that the urbanization of a major coastal city in the United States has resulted in modified rainstorm characteristics within the urbanized area and in the seasonally variant downwind urban-affected

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.

How this classification was reachedexpand

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.504
Threshold uncertainty score0.612

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.210
Teacher spread0.196 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2004
Admission routes1
Has abstractyes

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