Baseflow characteristics in alpine rivers — a multi-catchment analysis in Northwest China

Gan, Rong; Sun, Lin; Luo, Yi

doi:10.1007/s11629-013-2959-z

Cited by 22 publications

(9 citation statements)

References 35 publications

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“…The relatively high ESCO (0.925) indicates that the soil evaporation probably plays a weaker role in the whole evaporation process, possibly owing to the high vegetation coverage and low air temperature in the upper HRB [ 79 ]. The baseflow recession constant (ALPHA_BF), a direct index of groundwater flow response to changes in recharge, was determined mainly by referring to the works of Huang et al (2004) [ 80 ] and Gan et al (2015) [ 81 ], in which the ALPHA_BF was estimated using the digital filter and historical streamflow records. The ALPHA_BF of 0.002 was very small, indicating slow drainage and large storage in the shallow aquifer of the study basin.…”

Section: Resultsmentioning

confidence: 99%

Hydrological Impacts of Land Use Change and Climate Variability in the Headwater Region of the Heihe River Basin, Northwest China

Zhang

et al. 2016

PLoS ONE

145

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Land use change and climate variability are two key factors impacting watershed hydrology, which is strongly related to the availability of water resources and the sustainability of local ecosystems. This study assessed separate and combined hydrological impacts of land use change and climate variability in the headwater region of a typical arid inland river basin, known as the Heihe River Basin, northwest China, in the recent past (1995–2014) and near future (2015–2024), by combining two land use models (i.e., Markov chain model and Dyna-CLUE) with a hydrological model (i.e., SWAT). The potential impacts in the near future were explored using projected land use patterns and hypothetical climate scenarios established on the basis of analyzing long-term climatic observations. Land use changes in the recent past are dominated by the expansion of grassland and a decrease in farmland; meanwhile the climate develops with a wetting and warming trend. Land use changes in this period induce slight reductions in surface runoff, groundwater discharge and streamflow whereas climate changes produce pronounced increases in them. The joint hydrological impacts are similar to those solely induced by climate changes. Spatially, both the effects of land use change and climate variability vary with the sub-basin. The influences of land use changes are more identifiable in some sub-basins, compared with the basin-wide impacts. In the near future, climate changes tend to affect the hydrological regimes much more prominently than land use changes, leading to significant increases in all hydrological components. Nevertheless, the role of land use change should not be overlooked, especially if the climate becomes drier in the future, as in this case it may magnify the hydrological responses.

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Section: Resultsmentioning

confidence: 99%

Hydrological Impacts of Land Use Change and Climate Variability in the Headwater Region of the Heihe River Basin, Northwest China

Zhang

et al. 2016

PLoS ONE

145

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“…These results can be explained by the fact that the PGMFD temperature data that we used to calibrate and validate the model have lower values than the observed records in high elevation areas, as is described in Section 4.1. The lower temperatures in high-elevation regions reduce the conductivity of the soil [74].…”

Section: Discussionmentioning

confidence: 99%

Investigating Alternative Climate Data Sources for Hydrological Simulations in the Upstream of the Amu Darya River

Sidike

Chen

et al. 2016

Water

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Abstract:The main objective of this study is to investigate alternative climate data sources for long-term hydrological modeling. To accomplish this goal, one weather station data set (WSD) and three grid-based data sets including three types of precipitation data and two types of temperature data were selected according to their spatial and temporal details. An accuracy assessment of the grid-based data sets was performed using WSD. Then, the performances of corrected data combination and non-corrected grid-based precipitation and temperature data combinations from multiple sources on simulating river flow in the upstream portion of the Amu Darya River Basin (ADRB) were analyzed using a Soil and Water Assessment Tool (SWAT) model. The results of the accuracy assessments indicated that all the grid-based data sets underestimated precipitation. The Asian Precipitation Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources (APHRODITE) precipitation data provided the highest accuracy (correlation coefficients (CF) > 0.89, root mean square error (RMSE) < 41.6 mm), followed by the CRUNCEP reanalysis data (a combination of the CRU TS.3.2 data and the National Centers for Environmental Prediction (NCEP) reanalysis data) (CF > 0.5, RMSE < 58.1 mm) and Princeton's Global Meteorological Forcing Dataset (PGMFD) precipitation data (CF > 0.46, RMSE < 62.8 mm). The PGMFD temperature data exhibited a higher accuracy (CF > 0.98, RMSE < 7.1 • C) than the CRUNCEP temperature data (CF > 0.97, RMSE < 4.9 • C). In terms of the simulation performance, the corrected APHRODITE precipitation and PGMFD temperature data provided the best performance. The CF and Nash-Sutcliffe (NSE) coefficients in the calibration and validation periods were 0.96 and 0.92 and 0.93 and 0.83, respectively. In addition, the combinations of PGMFD temperature data and APHRODITE, PGMFD and CRUNCEP precipitation data produced good results, with NSE ≥ 0.70 and CF ≥ 0.89. The combination of CRUNCEP temperature data and APHRODITE precipitation produced a satisfactory result, with NSE = 0.58 and CF = 0.82. The combinations of CRUNCEP temperature data and PGMFD and CRUNCEP precipitation data produced poor results.

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“…However, the various separation methods produce widely varying estimates of baseflow indices (Eckhardt 2008). Gan et al (2015) used automated digital filter method of baseflow separation using historical daily streamflow data and fed by rainfall, snowmelt, and glacier melt, and reported that the baseflow index, with 65% variability, was expressively correlated with catchment climatic factors and aquifer properties.…”

Section: Introductionmentioning

confidence: 99%

Use of baseflow indices to delineate baseflow dominated and rapid response flow dominated watersheds.

Rudra¹,

Ahmed²,

Khan³

et al. 2015

Can. Biosyst. Eng.

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Baseflow characteristics in alpine rivers — a multi-catchment analysis in Northwest China

Abstract: Abstract

Cited by 22 publications

References 35 publications

Hydrological Impacts of Land Use Change and Climate Variability in the Headwater Region of the Heihe River Basin, Northwest China

Hydrological Impacts of Land Use Change and Climate Variability in the Headwater Region of the Heihe River Basin, Northwest China

Investigating Alternative Climate Data Sources for Hydrological Simulations in the Upstream of the Amu Darya River

Use of baseflow indices to delineate baseflow dominated and rapid response flow dominated watersheds.

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