Abstract
Connectivity metrics for surface water are important for predicting floods and droughts, and improving water management for human use and ecological integrity at the landscape scale. The integrated use of synthetic aperture radar (SAR) observations and geostatistics approach can be useful for developing and quantifying these metrics and their changes, including geostatistical connectivity function (GCF), maximum distance of connection (MDC), surface water extent (SWE), and connection frequency. In this study, we conducted a geostatistical analysis based on 52 wet and dry binary state (i.e., water and non-water) rasters derived from Sentinel-1 A/B GRD products acquired from 2015 to 2019 for China’s Momoge National Nature Reserve to investigate applicability and dynamics of the hydrologic connectivity metrics in an ungauged (i.e., data such as flow and water level are scarce) multi-lake system. We found: (1) generally, the change of GCF in North–South and Northeast–Southwest directions was greater than that in the West–East and Northwest–Southeast directions; (2) MDC had a threshold effect, generally at most 25 km along the W–E, NW–SE and NE–SW directions, and at most 45 km along the N–S direction; (3) the flow paths between lakes are diverse, including channelized flow, diffusive overbank flow, over-road flow and “fill-and-merge”; (4) generally, the values of the three surface hydrological connectivity indicators (i.e., the MDC, the SWE, and the conneciton frequency) all increased from May to August, and decreased from August to October; (5) generally, the closer the distance between the lakes, the greater the connection frequency, but it is also affected by the dam and road barrier. The study demonstrates the usefulness of the geostatistical method combining Sentinel-1 SAR image analysis in quantifying surface hydrological connectivity in an ungagged area. This approach should be applicable for other geographical regions, in order help resource managers and policymakers identify changes in surface hydrological connectivity, as well as address potential impacts of these changes on water resources for human use and/or ecological integrity at the landscape level.
Highlights
The hierarchical nature and dynamic of lotic ecosystems may be conceptualized in a four-dimensional framework, namely the longitudinal connection between upstream and downstream, the lateral connection between the channel and the riparian/floodplain system, the vertical connection between the channel and contiguous groundwaters, and the time dimension that superimposes time hierarchy on three spatial dimensions [1]
The overall accuracy of the wet and dry binary state rasters derived from Sentinel-1 A/B GRD products ranges from 95.72% to 98.15%
We found that the geospatial connectivity function (GCF), maximum distance connection (MDC), and surface water extent (SWE)
Summary
The hierarchical nature and dynamic of lotic ecosystems may be conceptualized in a four-dimensional framework, namely the longitudinal connection between upstream and downstream, the lateral connection between the channel and the riparian/floodplain system, the vertical connection between the channel and contiguous groundwaters, and the time dimension that superimposes time hierarchy on three spatial dimensions [1]. Wetland hydrological connectivity can be divided into surface water connectivity and groundwater-surface water connectivity. Surface water connectivity refers to the movement of surface water from one area of the landscape to another [2], which is the key physical mechanism for nutrients, organic matter, sediment, pollutants and heat energe to move between watershed units [3,4]. The quantification of connectivity remains challenging due to the lack of high spatial-temporal resolution observational data, and the current consensus on the best metric for quantifying hydrological connectivity is limited
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