Huang W.,Peking UniversityBeijing China |
Dupont-Nivet G.,CNRS Geosciences Laboratory of Rennes |
Guo Z.,Key Laboratory of Orogenic Belts and Crustal EvolutionMinistry of Education
Geochemistry, Geophysics, Geosystems | Year: 2015
The Tibetan Himalaya represents the northernmost continental unit of the Indian plate that collided with Asia in the Cenozoic. Paleomagnetic studies on the Tibetan Himalaya can help constrain the dimension and paleogeography of "Greater India," the Indian plate lithosphere that subducted and underthrusted below Asia after initial collision. Here we present a paleomagnetic investigation of a Jurassic (limestones) and Lower Cretaceous (volcaniclastic sandstones) section of the Tibetan Himalaya. The limestones yielded positive fold test, showing a prefolding origin of the isolated remanent magnetizations. Detailed paleomagnetic analyses, rock magnetic tests, end-member modeling of acquisition curves of isothermal remanent magnetization, and petrographic investigation reveal that the magnetic carrier of the Jurassic limestones is authigenic magnetite, whereas the dominant magnetic carrier of the Lower Cretaceous volcaniclastic sandstones is detrital magnetite. Our observations lead us to conclude that the Jurassic limestones record a prefolding remagnetization, whereas the Lower Cretaceous volcaniclastic sandstones retain a primary remanence. The volcaniclastic sandstones yield an Early Cretaceous paleolatitude of 55.5°S [52.5°S, 58.6°S] for the Tibetan Himalaya, suggesting it was part of the Indian continent at that time. The size of "Greater India" during Jurassic time cannot be estimated from these limestones. Instead, a paleolatitude of the Tibetan Himalaya of 23.8°S [21.8°S, 26.1°S] during the remagnetization process is suggested. It is likely that the remagnetization, caused by the oxidation of early diagenetic pyrite to magnetite, was induced during 103-83 or 77-67 Ma. The inferred paleolatitudes at these two time intervals imply very different tectonic consequences for the Tibetan Himalaya. © 2014. American Geophysical Union. All Rights Reserved.
Wu B.,Peking UniversityBeijing China |
Zheng Y.,Peking UniversityBeijing China |
Wu X.,Peking UniversityBeijing China |
Tian Y.,Peking UniversityBeijing China |
And 3 more authors.
Water Resources Research | Year: 2015
Integrated surface water-groundwater modeling can provide a comprehensive and coherent understanding on basin-scale water cycle, but its high computational cost has impeded its application in real-world management. This study developed a new surrogate-based approach, SOIM (Surrogate-based Optimization for Integrated surface water-groundwater Modeling), to incorporate the integrated modeling into water management optimization. Its applicability and advantages were evaluated and validated through an optimization research on the conjunctive use of surface water (SW) and groundwater (GW) for irrigation in a semiarid region in northwest China. GSFLOW, an integrated SW-GW model developed by USGS, was employed. The study results show that, due to the strong and complicated SW-GW interactions, basin-scale water saving could be achieved by spatially optimizing the ratios of groundwater use in different irrigation districts. The water-saving potential essentially stems from the reduction of nonbeneficial evapotranspiration from the aqueduct system and shallow groundwater, and its magnitude largely depends on both water management schemes and hydrological conditions. Important implications for water resources management in general include: first, environmental flow regulation needs to take into account interannual variation of hydrological conditions, as well as spatial complexity of SW-GW interactions; and second, to resolve water use conflicts between upper stream and lower stream, a system approach is highly desired to reflect ecological, economic, and social concerns in water management decisions. Overall, this study highlights that surrogate-based approaches like SOIM represent a promising solution to filling the gap between complex environmental modeling and real-world management decision-making. © 2015. American Geophysical Union. All Rights Reserved.