Runoff characteristics of headwater catchments in a young volcanic region

Zang, Chao; Sugita, Michiaki; Okita, Atsushi; Bi, Shiming

doi:10.1016/j.jhydrol.2023.129350

Cited by 3 publications

(9 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The minimum lag at deeper depths may be attributed to the formation of soil cracks during drought years, allowing rainwater to move quickly to deeper depths by passing the shallow depths. Our previous findings also reported higher preferential flow at 60 and 90 cm depths during drought than in normal years at the P301 catchment of KREW (Nanda & Safeeq, 2023). However, we observed higher percentage of occurrence of anticlockwise class IV loop (discharge peaked before SM) in normal years (83%) compared to drought years (67%) at the catchment scale.…”

Section: Spatial Variability In the Hysteresis Relationssupporting

confidence: 63%

“…ASM storage and peak rainfall intensity (I peak ) were found to be major governing factors of HI across all scales. However, we found discharge as a controlling factor at 60 and 90 cm depths of US and 60 cm depth of LS topographic positions which may be linked to the higher subsurface flow at those soil depths (Nanda & Safeeq, 2023). The peakto-peak lag was close to zero for higher catchment storage (Figure A3)…”

Section: Controls Of Himentioning

confidence: 75%

“…The antecedent soil moisture (ASM) storage can be defined as SM storage in the top 1 m soil depth at the beginning of a rainfall event. We used the following equation to calculate SM storage (Nanda & Safeeq, 2023;Safeeq et al, 2022).…”

Section: Spatiotemporal Variability In Storage-discharge Hysteresismentioning

confidence: 99%

“…We did not consider events having total event rainfall of less than 5 mm in the analysis. The end of an event was identified as the end of runoff with no further rainfall in the next 6 h. Snow events were segregated from rain events when ambient air temperature dropped below 0 C for more than 40% of the total event duration (Nanda & Safeeq, 2023). We identified 33 hydrological events (mainly rainfall-driven events) in the P301 catchment for analysing the storage-discharge relationship.…”

Section: Hydro-meteorological Datamentioning

confidence: 99%

See 3 more Smart Citations

Nonlinear storage–discharge dynamics of forested headwater catchment: A hysteresis index approach

Nanda,

Safeeq

2024

Hydrological Processes

View full text Add to dashboard Cite

The relationship between catchment storage and discharge is nonlinear. The dynamicity of this relationship is dependent on the distance of the storage measurement from the stream, the depth of the soil moisture (SM) measurement, antecedent SM storage, and precipitation characteristics. Understanding the relative influence of these factors is critical for interpreting runoff generation processes and predicting discharge. In this study, we used a hysteresis index approach and analysed the nonlinear dynamics of catchment storage–discharge relationship across points, hillslope and catchment scales, and their controlling factors. A small headwater forested catchment located in the southern part of the Sierra Nevada region, California, was selected as a case study. In this Mediterranean catchment, the anticlockwise class IV hysteresis loop, indicating an earlier discharge peak than SM, was observed as a prevalent hysteresis class across all the scales, irrespective of seasons (i.e., dry vs. wet) and years (i.e., normal vs. drought). A few clockwise hysteresis loops were observed at the shallow depths (10 and 30 cm) of upslope and lower slope topographic positions. Further, we found a shorter lag time between SM peak to discharge peak at 60 and 90 cm soil depths during the wet season, and during the drought period. The shorter lag at the deeper depth was due to the presence of subsurface flow during high antecedent SM storage conditions and preferential flow through the soil pores during the drought periods. The variability in hysteresis at catchment and hillslope scales was controlled by peak rainfall intensity and antecedent SM storage. However, rainfall characteristics (intensity and depth) were major governing factors for most of the point scale locations. Overall, the current study highlighted the role of SM sensor's location in characterizing storage–discharge behaviour.

show abstract

Section: Spatial Variability In the Hysteresis Relationssupporting

confidence: 63%

Section: Controls Of Himentioning

confidence: 75%

Section: Spatiotemporal Variability In Storage-discharge Hysteresismentioning

confidence: 99%

Section: Hydro-meteorological Datamentioning

confidence: 99%

See 2 more Smart Citations

Nonlinear storage–discharge dynamics of forested headwater catchment: A hysteresis index approach

Nanda,

Safeeq

2024

Hydrological Processes

View full text Add to dashboard Cite

show abstract

“…We proposed a process‐based explanation for observed recharge dynamics based on spatial variations in weathered bedrock thickness and plant water use. Although a number of studies have explored threshold mechanisms for recharge and runoff generation at hillslope and catchment scales (Ali et al., 2015; Lapides et al., 2022; Nanda & Safeeq, 2023; Scaife & Band, 2017; Tromp‐van Meerveld & McDonnell, 2006; van Meerveld et al., 2015, e.g. ), few have leveraged direct observations of storage dynamics throughout the entire weathering profile to definitively attribute groundwater recharge fluxes (and subsequent flow generation) to storage dynamics in the overlying soil and bedrock vadose zone (Hahm et al., 2022; McNamara et al., 2005; Oshun et al., 2016; Rempe & Dietrich, 2018; Salve et al., 2012).…”

Section: Discussionmentioning

confidence: 99%

Inferring Hillslope Groundwater Recharge Ratios From the Storage‐Discharge Relation

Dralle

Hahm

Rempe

2023

Geophysical Research Letters

View full text Add to dashboard Cite

Accurate observation of hillslope groundwater storage and instantaneous recharge remains difficult due to limited monitoring and the complexity of mountainous landscapes. We introduce a novel storage‐discharge method to estimate hillslope recharge and the recharge ratio—the fraction of precipitation that recharges groundwater. The method, which relies on streamflow data, is corroborated by independent measurements of water storage dynamics inside the Rivendell experimental hillslope at the Eel River Critical Zone Observatory, California, USA. We find that along‐hillslope patterns in bedrock weathering and plant‐driven storage dynamics govern the seasonal evolution of recharge ratios. Thinner weathering profiles and smaller root‐zone storage deficits near‐channel are replenished before larger ridge‐top deficits. Consequently, precipitation progressively activates groundwater from channel to divide, with an attendant increase in recharge ratios throughout the wet season. Our novel approach and process observations offer valuable insights into controls on groundwater recharge, enhancing our understanding of a critical flux in the hydrologic cycle.

show abstract