Climate Variability and Climate Change Impacts on Land Surface, Hydrological Processes and Water Management

Abstract

During the last several decades, Earth´s climate has undergone significant changes due to anthropogenic global warming, and feedbacks to the water cycle. Therefore, persistent efforts are required to understand the hydrological processes and to engage in efficient water management strategies under changing environmental conditions. The twenty-four contributions in this Special Issue have broadly addressed the issues across four major research areas: (1) Climate and land-use change impacts on hydrological processes, (2) hydrological trends and causality analysis faced in hydrology, (3) hydrological model simulations and predictions, and (4) reviews on water prices and climate extremes. The substantial number of international contributions to the Special Issue indicates that climate change impacts on water resources analysis attracts global attention. Here, we give an introductory summary of the research questions addressed by the papers and point the attention of readers toward how the presented studies help gaining scientific knowledge and support policy makers.

A Method for Estimating Urban Flood-Carrying Capacity Using the VIS-W Underlying Surface Model: A Case Study from Wuhan, China

“…Compared to the self-container storage capacity in the sub-catchment, the seven waterlogged places located in No. 5,No.8,and No.20, and the three waterlogged places located in No.19, are not reasonable. The waterlogged places located in No.…”

“…Furthermore, the storage capacities in No. 5,No.8,and No.20 (in light purple colors) are much higher than the quantity of rainwater.…”

“…26), and the "important" group, for which the ratio is between 40% and 89% (including No. 5,No. 6,No.…”

“…The nationwide flood and waterlogging disasters caught the attention of researchers in the field of flood control and management [3]. Extreme rainstorms, the increasing ratio of impervious surface [4,5], and urbanization generated changes to transform original suburbs to semi-urban or urban land areas [6], which might affect the local original hydrological conditions [7][8][9]. Taking Wuhan as an example, the imperious surface increased from 903.45 km 2 to 3989.49 km 2 from 2010 to 2016 [10].…”

Wireless sensor networks and machine learning meet climate change prediction

“…Using an equation developed in the study, it was found that climate change awareness positively influences an individual's attitude and intention to reduce the waste that they produce. A fundamental review of the study problems discussed in this research is provided by Zhang and Reggiani, 23 which points out how the performed studies support the improvement of scientific understanding by policymakers. However, all of these solutions only provide theories for the prediction of climate change.…”