Hydrologic Response to Land Use and Land Cover Changes within the Context of Catchment-Scale Spatial Information
Why this work is in the frame
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Bibliographic record
Abstract
The Laohahe River basin, located in northeastern China, was selected as a case study to quantify the magnitude of changes in land use and land cover (LULC) during the period from the 1970s to the 2010s and its quantitative effects on surface hydrology, based on hydrologic modeling of a distributed Soil and Water Assessment Tool (SWAT) model and catchment-scale spatial information analyses from remotely sensed data. Land cover maps with 30-m resolution from 1979, 1989, 1999, and 2007, interpreted from Landsat images, were used to analyze LULC changes during the last decades. The observed daily hydro-meteorological data from 1970 to 2006 were divided into four periods: 1970–1979, 1980–1989, 1990–1999, and 2000–2006. The SWAT model was utilized for each period with four LULC scenarios, which were developed by using the four LULC maps. Annual and monthly surface runoff and actual evapotranspiration (AET) were selected as important hydrologic elements to indicate the hydrologic response to LULC changes. The results revealed that distinct land cover changes occurred in the basin; the most important change was the conversion among vegetation cover classes of cropland, forest land, and grassland. Surface runoff always decreased as the LULC scenarios changed from 1976 to 2007 during all periods, but AET did not change regularly following the present LULC changes. Multiple regression equations between quantitative changes of LULC and hydrologic elements were developed. The equations indicated that the changes in three vegetation cover classes of grassland, cropland, and forest areas significantly affected hydrological elements and the increases of vegetation cover class areas all led to decreases in surface runoff and increases in AET. Moreover, given the same quantitative area change, the effects of cropland on hydrologic elements were the strongest, the effects of forest land were the second strongest, and the effects of grassland were the third. The effects of LULC changes on the seasonal distribution of hydrologic elements were also investigated. The results demonstrated that LULC changes have less influence on surface runoff and AET in nonflood seasons, but more influence in flood seasons, especially in July, August, and September, when the crops grow best. The results of this study improved the understanding of hydrologic responses to LULC changes and provided needed knowledge for agricultural decisions and the management of land use and integrated water resources.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it