Stream power index for networks (SPIN) toolbox for decision support in urbanizing watersheds

Ghunowa, Kimisha; MacVicar, Bruce; Ashmore, Peter

doi:10.1016/j.envsoft.2021.105185

Cited by 24 publications

(16 citation statements)

References 101 publications

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“…SPI values indicate if area is potentially erosive or relatively flat, which influences the susceptibility to floods. SPI was determined using SPIN toolbox in ArcGIS environment [ 48 ].…”

Section: Methodsmentioning

confidence: 99%

Vegetation Affecting Water Quality in Small Streams: Case Study in Hemiboreal Forests, Latvia

Saklaurs

Dubra

Liepa

et al. 2022

Plants

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Riparian forests are important ecosystems located along the margins of freshwaters. Riparian zones provide many ecosystem services, such as nutrient modification, erosion and temperature control, leading to improvements in water quality in adjacent water ecosystems. In many areas, riparian forest management is restricted to improve adjacent water quality. The potential influence of forest management on water quality of small streams was assessed by analysing species composition and structural diversity in riparian forests. We collected data in riparian forests along 15 streams in the eastern Baltics (Latvia) with different water quality classes. We used detrended correspondence analysis and indicator species’ analysis to determine relationships between woody plants and understory vegetation. We also used ADONIS and ANOSIM analysis to determine possible factors that affect species composition. Our results suggested that water quality is affected by ground vegetation, which in turn was altered by stand density and total yield. Site-specific decision making in management is required in riparian forests to ensure the required conditions in the streams, because species composition differs between sites, dominant tree species and stand parameters (density, total yield, stand age). Introduction of Betula pubescens Ehrh. in coniferous stands is favourable to ensure litter fall quality and provide shade for streams during summer.

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“…SPI values indicate if area is potentially erosive or relatively flat, which influences the susceptibility to floods. SPI was determined using SPIN toolbox in ArcGIS environment [ 48 ].…”

Section: Methodsmentioning

confidence: 99%

Vegetation Affecting Water Quality in Small Streams: Case Study in Hemiboreal Forests, Latvia

Saklaurs

Dubra

Liepa

et al. 2022

Plants

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“…The DEM was also used to compute the hydrology datasets of stream power index (SPI) and topographic wetness index (TWI). The SPI is estimated along the stream network to assess the change in magnitude of stream power between pre-and post-development scenarios [42]. Basically, TWI defines the effect of topography on the location and size of saturated source areas of runoff generation [43,44].…”

Section: Data Acquisitionmentioning

confidence: 99%

Impacts of the Urmia Lake Drought on Soil Salinity and Degradation Risk: An Integrated Geoinformatics Analysis and Monitoring Approach

et al. 2022

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Recent improvements in earth observation technologies and Geographical Information System (GIS) based spatial analysis methods require us to examine the efficiency of the different data-driven methods and decision rules for soil salinity monitoring and degradation mapping. The main objective of this study was to analyze the environmental impacts of the Lake Urmia drought on soil salinity and degradation risk in the plains surrounding the hyper-saline lake. We monitored the impacts of the lake drought on soil salinity by applying spatiotemporal indices to time-series satellite images (1990–2020) in Google Earth Engine environment. We also computed the soil salinity ratio to validate the results and determine the most efficient soil salinity monitoring techniques. We then mapped the soil degradation risk based on GIS spatial decision-making methods. Our results indicated that the Urmia Lake drought is leading to the formation of extensive salt lands, which impact the fertility of the farmlands. The land affected by soil salinity has increased from 2.86% in 1990 to 16.68% in 2020. The combined spectral response index, with a performance of 0.95, was the most efficient image processing method to assess soil salinity. The soil degradation risk map showed that 38.45% of the study area has a high or very high risk of degradation, which is a significant threat to food production. This study presents an integrated geoinformation approach for time-series soil salinity monitoring and degradation risk mapping that supports future studies by comparing the efficiency of different methods as state of the art. From a practical perspective, the results also provide key information for decision-makers, authorities, and local stakeholders in their efforts to mitigate the environmental impacts of lake drought and sustain the food production to sustain the 7.3 million residents.

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“…Landscape modifications that decrease infiltration will impose changes to river hydrology (Ghunowa et al, 2021;Ashmore, 2015;Taniguchi & Biggs, 2015;Winter, 2001) with a downstream cascading effect on flow regime (Royall, 2013). Human occupation, landscape manipulation, and the generation of impervious surfaces associated with urbanization have the most profound impact on hydrogeomorphic responses, particularly in smaller watersheds (Pasternack, 2013;Royall, 2013).…”

Section: Introductionmentioning

confidence: 99%

Modelling flood frequency and magnitude in glacially conditioned settings: land use matters

Tetford¹,

Desloges²

2023

Preprint

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Abstract. A reliable flood frequency analysis (FFA) requires selection of an appropriate statistical distribution to model historic streamflow data and, where streamflow data are not available (ungauged sites), a regression-based regional flood frequency analysis (RFFA) often correlates well with downstream channel discharge to drainage area relations. However, the predictive strength of the accepted RFFA relies on an assumption of homogeneous watershed conditions. For glacially conditioned fluvial systems, inherited glacial landforms, sediments, and variable land use can alter flow paths and modify flow regimes. This study compares a multi-variate RFFA that considers 28 explanatory variables to characterize variable watershed conditions (i.e., surficial geology, climate, topography, and land use) to an accepted power-law relationship between discharge and drainage area. Archived gauge data from southern Ontario, Canada are used to test these ideas. Mathematical goodness-of-fit criteria best estimate flood discharge for a broad range of flood recurrence intervals, i.e., 1.25, 2, 5, 10, 25, 50, and 100 years. The LN, EV1, LP3, and GEV distributions are found most appropriate in 42.5 %, 31.9 %, 21.7 %, and 3.9 % of cases, respectively, suggesting that systematic model selection criterion is required for FFA in heterogeneous landscapes. Multi-variate regression of estimated flood quantiles with backward elimination of explanatory variables using principal component and discriminant analyses reveal that precipitation provides a greater predictive relationship for more frequent flood events, whereas surficial geology demonstrates more predictive ability for high magnitude, less frequent flood events. In this study, all seven flood quantiles identify a statistically significant two-predictor model that incorporates upstream drainage area and the percentage of naturalized landscape with 5 % improvement in predictive power over the commonly used single-variable drainage area model (p < 2.2e−16). An analysis of variance (ANOVA) further supports the two-predictor model indicating a decrease in the sum of squares of residuals and an F statistic (p < 0.001) that demonstrates very strong evidence in favour of the two-predictor model (i.e., drainage area and land use) when estimating flood discharge in this low-relief landscape with pronounced glacial legacy effects and heterogenous land use.

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Stream power index for networks (SPIN) toolbox for decision support in urbanizing watersheds

Cited by 24 publications

References 101 publications

Vegetation Affecting Water Quality in Small Streams: Case Study in Hemiboreal Forests, Latvia

Vegetation Affecting Water Quality in Small Streams: Case Study in Hemiboreal Forests, Latvia

Impacts of the Urmia Lake Drought on Soil Salinity and Degradation Risk: An Integrated Geoinformatics Analysis and Monitoring Approach

Modelling flood frequency and magnitude in glacially conditioned settings: land use matters

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