Attribution analyses on streamflow variation to changing climate and land surface characteristics are critical in studies of watershed hydrology. However, attribution results may differ greatly on different spatial and temporal scales, which has not been extensively studied previously. This study aims to investigate the spatial-temporal contributions of climate change and underlying surface variation to streamflow alteration using Budyko framework. Jiangling River Watershed (JRW), a typical landform transitional watershed in Southwest China, was chosen as the study area. The watershed was firstly divided into eight sub-basins by hydrologic stations, and hydrometeorological series (1954–2015) were divided into sub-intervals to discriminate spatial-temporal features. The results showed that long-term tendencies of hydrometeorological variables, i.e., precipitation (P), potential evapotranspiration (E₀), and runoff depth (R), exhibited clear spatial patterns, which were highly related to topographic characteristics. Additionally, sensitivity analysis, which interpreted the effect of one driving factor by unit change, showed that climate factors P and E₀, and catchment characteristics (land surface parameter n) played positive, negative, and negative roles in R, according to elastic coefficients (ε), respectively. The spatial distribution of ε illustrated a greater sensitivity and heterogeneity in the plateau and semi-humid regions (upstream). Moreover, the results from attribution analysis showed that the contribution of the land surface factor accounted for approximately 80% of the R change for the entire JRW, with an obvious spatial variation. Furthermore, tendencies of the contribution rates demonstrated regulations across different sub-regions: a decreasing trend of land surface impacts in trunk stream regions and increasing tendencies in tributary regions, and vice versa for climate impacts. Overall, both hydrometeorological variables and contributions of influencing factors presented regularities in long-term tendencies across different sub-regions. More particularly, the impact of the primary influencing factor on all sub-basins exhibited a decreasing trend over time. The evidence that climate and land surface change act on streamflow in a synergistic way, would complicate the attribution analysis and bring a new challenge to attribution analysis.

The effect of artificial island on the geomorphologic processes in the coastal area under the coupled hydrodynamics, wave, and sediment transport system is a complicated and multi-scale problem. Studying these dynamic processes will suggest how coastal ecological restoration should be conducted. In this study, a unified, unstructured, gridded coupled hydrodynamics, wave, and sediment transport model and a topographic evolution model were adopted. Based on the field observations of water depth, velocity, suspended sediment concentration, bed sand, and quaternary thickness, a high-spatiotemporal-resolution numerical simulation of the offshore dynamic environment under the disturbance of artificial island was performed, and the accuracy of the calculation was verified. The research showed that the coupling system with an unstructured mesh was able to reproduce the flow and sediment transport processes with acceptable accuracy. The contracted flow zone between the artificial island and the coastline, the runoff and alongshore current from the river, as well as the tidal flow from the ocean, worked together to mold the local complex morphology around the artificial island. The coupled modeling system, supported with parallel computation, can be used to study coastal environments with small-scale wading structures.

The railway-road-inland waterway (IWW) transportation network in the Yangtze River Basin was extracted using ArcGIS software and the triangular mesh covered the simulated region was generated using Quantum_GIS software. The population density and gross domestic product were chosen as the characteristic economic variables, which were interpolated spatially into the mesh to analyze the origin-destination (OD) matrix of the coal transport network. Then, the multimodal transportation cost model was developed considering the detailed cost functions of railway, road, and IWW in an open source code programed by Python language. Finally, the coal transportation cost under different transportation allocation scenarios were calculated and compared to investigate the advantages and potential of the multimodal transportation mode in the Yangtze River Basin. The cost analysis about the multimodal transportation system showed that the IWW mode has great potential to decrease the transportation cost of the coal within the OD matrix although the railway mode took at least 80% of the total transportation load.