An approach for assessing impact of land use and biophysical conditions across landscape on recharge rate and nitrogen loading of groundwater

Li, Qiang; Qi, Junyu; Xing, Zisheng; Li, Sheng; Jiang, Yefang; Danielescu, Serban; Zhu, Hangyong; Wei, Xiaohua; Meng, Fan‐Rui

doi:10.1016/j.agee.2014.06.028

Cited by 40 publications

(19 citation statements)

References 23 publications

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“…For example, several hydrological models have been applied to test the effects of spatial distribution of a hydrological variable (e.g. specific discharge, soil moisture, or groundwater recharge) (Erickson et al, 2005;Gómez-Plaza et al, 2001;Li et al, 2014). However, the effects of topography alone on hydrology are not usually addressed in those studies.…”

Section: Q LI Et Al: Topography Significantly Influencing Low Flowsmentioning

confidence: 99%

“…By this trial and error process, the final models with only significant TIs to flow variables were determined. The detailed procedure can also be found in Li et al (2014). Then, the R package "relaimpo" was used to quantify the relative contributions of the selected TIs to each flow variable (Gromping, 2006).…”

Section: Relative Contributions Of Each Ti To Flow Variablesmentioning

confidence: 99%

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Topography significantly influencing low flows in snow-dominated watersheds

Wei

Yang

et al. 2018

Hydrol. Earth Syst. Sci.

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Abstract. Watershed topography plays an important role in determining the spatial heterogeneity of ecological, geomorphological, and hydrological processes. Few studies have quantified the role of topography in various flow variables. In this study, 28 watersheds with snow-dominated hydrological regimes were selected with daily flow records from 1989 to 1996. These watersheds are located in the Southern Interior of British Columbia, Canada, and range in size from 2.6 to 1780 km 2 . For each watershed, 22 topographic indices (TIs) were derived, including those commonly used in hydrology and other environmental fields. Flow variables include annual mean flow (Q mean ), Q 10 % , Q 25 % , Q 50 % , Q 75 % , Q 90 % , and annual minimum flow (Q min ), where Q x % is defined as the daily flow that occurred each year at a given percentage (x). Factor analysis (FA) was first adopted to exclude some redundant or repetitive TIs. Then, multiple linear regression models were employed to quantify the relative contributions of TIs to each flow variable in each year. Our results show that topography plays a more important role in low flows (flow magnitudes ≤ Q 75 % ) than high flows. However, the effects of TIs on different flow magnitudes are not consistent. Our analysis also determined five significant TIs: perimeter, slope length factor, surface area, openness, and terrain characterization index. These can be used to compare watersheds when low flow assessments are conducted, specifically in snow-dominated regions with the watershed size less than several thousand square kilometres.

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Section: Q LI Et Al: Topography Significantly Influencing Low Flowsmentioning

confidence: 99%

Section: Relative Contributions Of Each Ti To Flow Variablesmentioning

confidence: 99%

Topography significantly influencing low flows in snow-dominated watersheds

Wei

Yang

et al. 2018

Hydrol. Earth Syst. Sci.

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“…The purposes of the stepwise regression models 150 were: 1) to further exclude those TIs that were insignificantly related to flow variables; and 2) to quantify the relative contributions of selected TIs to each flow variable in each year. The detailed procedure can be found in Li et al (2014). The R package "relaimpo" was used to quantify the relative contributions of the selected TIs to each flow variable (Gromping, 2006).…”

Section: Relative Contributions Of Each Ti To Flow Variables 145mentioning

confidence: 99%

“…For example, several hydrological models have been applied to test the effect of the spatial distribution of a hydrological variable (e.g. specific discharge, soil moisture, or groundwater 70 recharge) (Erickson et al, 2005;Gómez-Plaza et al, 2001;Li et al, 2014). However, the effects of topography alone on hydrology are not usually addressed in those studies.…”

Section: Introductionmentioning

confidence: 99%

Topography significantly influencing low flows in snow-dominated watersheds

Li¹,

Wei²,

Yang³

et al. 2017

Preprint

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and other environmental fields. Flow variables include annual mean flow (Qmean), Q10%, Q25%, Q50%, Q75%, Q90%, and annual minimum flow (Qmin), where Qx% is defined as flows that at the percentage (x) occurred in any given year. Factor analysis (FA) was first adopted to exclude some redundant or repetitive TIs. Then, stepwise regression models were employed to quantify the relative contributions of TIs to each flow variable in each year. Our results show that topography plays a more important 30 role in low flows than high flows. However, the effects of TIs on flow variables are not consistent.Our analysis also determines five significant TIs including perimeter, surface area, openness, terrain characterization index, and slope length factor, which can be used to compare watersheds when low flow assessments are conducted, especially in snow-dominated regions. 35

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“…The study was carried out in the Black Brook Watershed (BBW), located in the northwest New Brunswick (NB, 47 • 05 -47 • 09 N, 67 • 43 -67 • 48 W), Canada (Figure 1). The watershed has been studied extensively for evaluating the impact of agriculture on soil erosion and water quality for near 30 years [19,20]. The watershed covers an area of 14.5 km 2 , with 65% of its land use is in agriculture, 21% in forest, and 14% in residential areas and wetlands [21].…”

Section: Study Areamentioning

confidence: 99%

Hydrological Evaluation of Flow Diversion Terraces Using Downhill-Slope Calculation Method for High Resolution and Accuracy DEMs

Liang

et al. 2018

Sustainability

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Slope is an important topographical parameter in hydrological models. Dramatic changes in slope are produced due to micro variations of topography in flow diversion terrace (FDT) systems. Assessing the effectiveness of FDT on soil conservation yields different results using different slope calculation methods with different resolution and accuracy digital elevation models (DEMs). In this study, the ArcGIS built-in average-neighborhood-slope (ANS) method and a downhill-slope (DHS) method were used to calculate slopes for a small agricultural watershed in New Brunswick, Canada. Six DEMs were used, i.e., 1, 5 and 10 m resolution DEMs generated with conventional photogrammetric techniques, and 1, 5, and 10 m resolution DEMs derived from light detection and ranging (LiDAR) data. Calculated slopes were summarized for the whole watershed, a patch of FDT systems, and grassed flow channels in front of embankments in the patch. Results indicated that the DHS method produced smaller slopes than the ANS method with LiDAR-1m DEM along grasses flow channels. Furthermore, the mean L-factor derived from the DHS method was smaller than that derived from the ANS in terraces and grassed flow channels for the LiDAR-1m DEM. Finally, soil loss estimated from the DHS method using RUSLE was more consistent with measurement for the watershed than that from the ANS method when the LiDAR-1m DEM was used. The DHS method can provide accurate slopes along grassed flow channels and can be used to assess FDT systems using USLE-based models with high resolution and accuracy DEMs.

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An approach for assessing impact of land use and biophysical conditions across landscape on recharge rate and nitrogen loading of groundwater

Cited by 40 publications

References 23 publications

Topography significantly influencing low flows in snow-dominated watersheds

Topography significantly influencing low flows in snow-dominated watersheds

Topography significantly influencing low flows in snow-dominated watersheds

Hydrological Evaluation of Flow Diversion Terraces Using Downhill-Slope Calculation Method for High Resolution and Accuracy DEMs

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