TY - JOUR

T1 - Stormflow Response and “Effective” Hydraulic Conductivity of a Degraded Tropical Imperata Grassland Catchment as Evaluated With Two Infiltration Models

AU - Cheng, Zhuo

AU - Zhang, Jun

AU - Yu, Bofu

AU - Chappell, Nick A.

AU - van Meerveld, H. J. (Ilja)

AU - Bruijnzeel, L. Adrian

PY - 2023/5/31

Y1 - 2023/5/31

N2 - Predicting catchment stormflow responses after tropical deforestation remains difficult. We used 5‐min rainfall and storm runoff data for 30 events to calibrate the Green–Ampt (GA) and the Spatially Variable Infiltration (SVI) models and predict runoff responses for a small, degraded grassland catchment on Leyte Island (the Philippines), where infiltration‐excess overland flow (IOF) is considered the dominant runoff process. SVI replicated individual stormflow hydrographs better than GA, particularly for events with small runoff responses or multiple peaks. Calibrated parameter values of the SVI model (i.e., spatially averaged maximum infiltration capacity, Im and initial abstraction, F0) varied markedly between events, but were statistically significant and negatively correlated with (mid‐slope) soil moisture content at 10 cm (SWC10)—as did the “catchment‐wide effective” hydraulic conductivity (Ke) of the GA model. Using SWC10‐based estimates of F0 and Im in SVI yielded satisfactory to good simulations for 11 out of 17 events with runoff coefficients ≥15%, but failed to reproduce the hydrographs for events with very small runoff amounts (0.25–1 mm) and low runoff coefficients (3%–6%). The median field‐measured near‐surface Ksat (2 mm hr−1) was distinctly lower than the median Im (32 mm hr−1) and, to a lesser extent, Ke (∼8 mm hr−1), suggesting an underestimation of the spatially averaged Ksat by the field measurements. Application of SVI is expected to give the most realistic results for situations where IOF is dominant, that is, where surface conditions are degraded and rainfall intensities high.

AB - Predicting catchment stormflow responses after tropical deforestation remains difficult. We used 5‐min rainfall and storm runoff data for 30 events to calibrate the Green–Ampt (GA) and the Spatially Variable Infiltration (SVI) models and predict runoff responses for a small, degraded grassland catchment on Leyte Island (the Philippines), where infiltration‐excess overland flow (IOF) is considered the dominant runoff process. SVI replicated individual stormflow hydrographs better than GA, particularly for events with small runoff responses or multiple peaks. Calibrated parameter values of the SVI model (i.e., spatially averaged maximum infiltration capacity, Im and initial abstraction, F0) varied markedly between events, but were statistically significant and negatively correlated with (mid‐slope) soil moisture content at 10 cm (SWC10)—as did the “catchment‐wide effective” hydraulic conductivity (Ke) of the GA model. Using SWC10‐based estimates of F0 and Im in SVI yielded satisfactory to good simulations for 11 out of 17 events with runoff coefficients ≥15%, but failed to reproduce the hydrographs for events with very small runoff amounts (0.25–1 mm) and low runoff coefficients (3%–6%). The median field‐measured near‐surface Ksat (2 mm hr−1) was distinctly lower than the median Im (32 mm hr−1) and, to a lesser extent, Ke (∼8 mm hr−1), suggesting an underestimation of the spatially averaged Ksat by the field measurements. Application of SVI is expected to give the most realistic results for situations where IOF is dominant, that is, where surface conditions are degraded and rainfall intensities high.

KW - ATMOSPHERIC COMPOSITION AND STRUCTURE

KW - Air/sea constituent fluxes

KW - Volcanic effects

KW - BIOGEOSCIENCES

KW - Climate dynamics

KW - Modeling

KW - Soils/pedology

KW - COMPUTATIONAL GEOPHYSICS

KW - Numerical solutions

KW - CRYOSPHERE

KW - Avalanches

KW - Mass balance

KW - GEODESY AND GRAVITY

KW - Ocean monitoring with geodetic techniques

KW - Ocean/Earth/atmosphere/hydrosphere/cryosphere interactions

KW - Global change from geodesy

KW - GLOBAL CHANGE

KW - Abrupt/rapid climate change

KW - Climate variability

KW - Earth system modeling

KW - Impacts of global change

KW - Land/atmosphere interactions

KW - Oceans

KW - Regional climate change

KW - Sea level change

KW - Solid Earth

KW - Water cycles

KW - HYDROLOGY

KW - Catchment

KW - Infiltration

KW - Overland flow

KW - Soils

KW - Climate impacts

KW - Hydrological cycles and budgets

KW - INFORMATICS

KW - MARINE GEOLOGY AND GEOPHYSICS

KW - Gravity and isostasy

KW - ATMOSPHERIC PROCESSES

KW - Climate change and variability

KW - Climatology

KW - General circulation

KW - Ocean/atmosphere interactions

KW - Regional modeling

KW - Theoretical modeling

KW - OCEANOGRAPHY: GENERAL

KW - Climate and interannual variability

KW - Numerical modeling

KW - NATURAL HAZARDS

KW - Atmospheric

KW - Geological

KW - Oceanic

KW - Physical modeling

KW - Climate impact

KW - Risk

KW - Disaster risk analysis and assessment

KW - OCEANOGRAPHY: PHYSICAL

KW - Air/sea interactions

KW - Decadal ocean variability

KW - Ocean influence of Earth rotation

KW - Sea level: variations and mean

KW - Surface waves and tides

KW - Tsunamis and storm surges

KW - PALEOCEANOGRAPHY

KW - POLICY SCIENCES

KW - Benefit‐cost analysis

KW - RADIO SCIENCE

KW - Radio oceanography

KW - SEISMOLOGY

KW - Earthquake ground motions and engineering seismology

KW - Volcano seismology

KW - VOLCANOLOGY

KW - Volcano/climate interactions

KW - Atmospheric effects

KW - Volcano monitoring

KW - Effusive volcanism

KW - Mud volcanism

KW - Explosive volcanism

KW - Volcanic hazards and risks

KW - Research Article

KW - Green‐Ampt infiltration model

KW - humid tropics

KW - infiltration‐excess overland flow

KW - runoff generation

KW - Spatially Variable Infiltration model

U2 - 10.1029/2022wr033625

DO - 10.1029/2022wr033625

M3 - Journal article

VL - 59

JO - Water Resources Research

JF - Water Resources Research

SN - 0043-1397

IS - 5

M1 - e2022WR033625

ER -