Development of a Water Management Framework for Upper Yamuna River Basin using WEAP
Bibliographic record
Abstract
Dinesh Kumar1, C. T. Dhanya1, and Saman Razavi21 Department of Civil Engineering, Indian Institute of Technology Delhi, New Delhi-110016, India2 Department of Civil and Geological Engineering, University of Saskatchewan, SaskatoonSK S7N 3H5, CanadaAbstract: The regime of water quantity and quality in Upper Yamuna River Basin (UYRB), a tributary of Yamuna Basin that originates from the Himalayan region, has been affected by anthropogenic activities, climate extremes, and changing climate. The fresh water resources of UYRB is shared by six Indian states through the Memorandum of Agreement-1995. The river supplies domestic and agricultural water for more than 40 million people and 2 billion kg of crop yield per year. The significant increase in population, new hydrological extremes, changing climate, and unsustainable practices are expected to affect the fresh water resource, e-flow and agricultural activities of the basin. Hence, there is a need for a basin scale hydrological model in order to understand the human-water interactions in this basin in terms of both water quantity and quality, and to support the sustainable and economic use of water across the basin. This model needs to accommodate the storage and diversion structures, ecosystem requirements, water import (export) from (to) riparian areas, etc. This study focuses on the development of a framework to manage the water resources of this basin for present and future scenarios using Water Evaluation And Planning (WEAP) model. Quantitative statistics are used to assess the performance of the model, and the results indicate that the model successfully captures the system dynamics well. Nash-Sutcliffe coefficient (calibration/validation) value at Hathikund Barrage and Wazirabad Barrage are 0.84/0.79 and 0.77/0.61, respectively. \soutEven though the model simulates monthly and monsoon flows well, \soutsignificant difference is observed in the non-monsoon flows, especially at Wazirabad Barrage. The model simulates monsoon flows (i.e. peak flows) very well. Though the significant difference is observed in between the simulated and natural flow during the non-monsoon flow (i.e. low flows) in the downstream river gauge stations, especially at Wazirabad station.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".