Hydrologic Response to Land Use and Land Cover Changes within the Context of Catchment-Scale Spatial Information
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».