Using hydrological connectivity to detect transitions and degradation thresholds: Applications to dryland systems

Saco, Patricia M.; Rodríguez, J. F.; Heras, Mariano Moreno de las; Keesstra, Saskia; Azadi, Sama; Sandi, Steven G.; Baartman, Jantiene; Rodrigo‐Comino, Jesús; Rossi, M.

doi:10.1016/j.catena.2019.104354

Cited by 83 publications

(42 citation statements)

References 64 publications

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“…Continued research is needed to better describe variability in landscape morphology, precipitation, soil porosity, and vegetation structure, as these factors have been identified as key determinants of SMV in semi‐arid catchments. This new knowledge can be used to further improve landscape‐scale indices for the prediction of SMV in semi‐arid areas, like topographic wetness indices (Western, Grayson, Blöschl, Willgoose, & McMahon, 1999; Ding et al, 2018) and connectivity indices (Kim & Mohanty, 2016; Saco et al, 2020) by incorporating aspect‐controlled radiation differences in the development of soil moisture and vegetation patterns (Kumari et al, 2020; Yetemen, Istanbulluoglu, & Duvall, 2015).…”

Section: Discussionmentioning

confidence: 99%

The role of landscape morphology on soil moisture variability in semi‐arid ecosystems

Srivastava

Saco

Rodríguez

et al. 2020

Hydrological Processes

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Previous studies on semi‐arid ecosystems have shown high values of soil moisture variability (SMV) primarily induced by the combined effects of non‐uniform precipitation, incoming solar radiation, and soil and vegetation properties. However, the relative impact of these various factors on SMV has been difficult to evaluate due to limited availability of field data. In addition, only a limited number of studies have analysed the role of landscape morphology on SMV. Here we use numerical simulations of a simple hydrological model, the Bucket Grassland Model, to systematically analyse the effect of each contributing factor on SMV on two different landscape morphologies. The two different landform morphologies represent landscapes dominated respectively by either diffusive erosion or fluvial erosion processes. We conducted various simulations driven by a stochastically generated 100‐year climate time series, which is long enough to capture climatic fluctuations, in order to understand the effect of various soil moisture controlling factors on the spatiotemporal SMV. Our modelling results show that the fluvial dominated landscapes promote higher spatial SMV than the diffusive dominated ones. Further, the role of landform morphology on SMV is more pronounced in regions where the spatial variability of incoming solar radiation and precipitation is high.

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Section: Discussionmentioning

confidence: 99%

The role of landscape morphology on soil moisture variability in semi‐arid ecosystems

Srivastava

Saco

Rodríguez

et al. 2020

Hydrological Processes

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“…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]. It is generally realized that disturbances in hydrological connectivity due to either climatic or anthropogenic could trigger cascading effects on ecosystems, leading to ecosystem degradation [5]. Therefore, quantifying hydrological connectivity is of great importance for a number of reasons, such as establishing a baseline of measurable changes, making connectivity related to various eco-hydrological functions, and developing protection and restoration criteria [6].…”

Section: Introductionmentioning

confidence: 99%

Assessment of Surface Hydrological Connectivity in an Ungauged Multi-Lake System with a Combined Approach Using Geostatistics and Spaceborne SAR Observations

Chen

Lili

Zhang

et al. 2020

Water

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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.

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“…Water depth time series over the tidal flat are estima ted using a finite-differences quasi-2D hydrodynamic model (Ricca rdi, 2000) that has been successfully applied to coastal wetlands (Rodriguez et al, 2017;Sandi et al, 2018) and floodplains (Sandi et al, 2019;Sandi et al, 2020a;Sandi et al, 2020b;Saco et al, 2019). The model solves the shallow water equations using a…”

Section: Hydrodynamic Modelmentioning

confidence: 99%

“…Here, we investiga te how accretion and migration processes affect wetland response to SLR using a computational framework that includes all relevant hydrodynamic and sediment transport mechanisms that affect vegetation and landscape dynamics, yet it is efficient enough to allow the simulation of long time periods. The framework consists of a fast-performance quasi-2D hydrodynamic model (Riccardi, 2000;Rodriguez et al, 2017) that we have extensively tested in wetlands (Rodriguez et al, 70 2017;Saco et al, 2019;Sandi et al, 2018;Sandi et al, 2019;Sandi et al, 2020a;Sandi et al, 2020b) and a sediment advection transport model (Garcia et al, 2015) that we couple with vegetation formulations for preference to tidal conditions to obtain rea listic predictions of wetland accretion and migration under SLR. Our framework incorporates two vegetation species, mangrove and saltmarsh, and accounts for the effects of manmade features like inner channels, embankments and flow constrictions due to culverts.…”

Section: Introduction 35mentioning

confidence: 99%

Accretion, retreat and transgression of coastal wetlands experiencing sea-level rise

Breda¹,

Saco²,

Sandi³

et al. 2020

Preprint

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Abstract. The vulnerability of coastal wetlands to future sea-level rise (SLR) has been extensively studied in recent years, and models of coastal wetland evolution have been developed to assess and quantify the expected impacts. Coastal wetlands respond to SLR by vertical accretion and landward migration. Wetlands accrete due to their capacity to trap sediments and to incorporate dead leaves, branches stems and roots into the soil, and they migrate driven by the preferred inundation conditions in terms of salinity and oxygen availability. Accretion and migration strongly interact and they both depend on water flow and sediment distribution within the wetland, so wetlands under the same external flow and sediment forcing but with different configurations will respond differently to SLR. Analyses of wetland response to SLR that do not incorporate realistic consideration of flow and sediment distribution, like the bathtub approach, are likely to result in poor estimates of wetland resilience. Here, we investigate how accretion and migration processes affect wetland response to SLR using a computational framework that includes all relevant hydrodynamic and sediment transport mechanisms that affect vegetation and landscape dynamics, and it is efficient enough computationally to allow the simulation of long time periods. Our framework incorporates two vegetation species, mangrove and saltmarsh, and accounts for the effects of natural and manmade features like inner channels, embankments and flow constrictions due to culverts. We apply our model to simplified domains that represent four different settings found in coastal wetlands, including a case of a tidal flat free from obstructions or drainage features and three other cases incorporating an inner channel, an embankment with a culvert, and a combination of inner channel, embankment and culvert. We use conditions typical of SE Australia in terms of vegetation, tidal range and sediment load, but we also analyse situations with three times the sediment load to assess the potential of biophysical feedbacks to produce increased accretion rates. We find that all wetland settings are unable to cope with SLR and disappear by the end of the century, even for the case of increased sediment load. Wetlands with good drainage that improves tidal flushing are more resilient than wetlands with obstacles that result in tidal attenuation, and can delay wetland submergence by 20 years. Results from a bathtub model reveals systematic overprediction of wetland resilience to SLR: by the end of the century, half of the wetland survives with a typical sediment load, while the entire wetland survives with increased sediment load.

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Using hydrological connectivity to detect transitions and degradation thresholds: Applications to dryland systems

Cited by 83 publications

References 64 publications

The role of landscape morphology on soil moisture variability in semi‐arid ecosystems

The role of landscape morphology on soil moisture variability in semi‐arid ecosystems

Assessment of Surface Hydrological Connectivity in an Ungauged Multi-Lake System with a Combined Approach Using Geostatistics and Spaceborne SAR Observations

Accretion, retreat and transgression of coastal wetlands experiencing sea-level rise

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