Stability of Soil Moisture Patterns Retrieved at Different Temporal Resolutions in a Tropical Watershed

Abstract

Above and underground hydrological processes depend on soil moisture (SM) variability, driven by different environmental factors that seldom are well-monitored, leading to a misunderstanding of soil water temporal patterns. This study investigated the stability of the SM temporal dynamics to different monitoring temporal resolutions around the border between two soil types in a tropical watershed. Four locations were instrumented in a small-scale watershed (5.84 km 2) within the tropical coast of Northeast Brazil, encompassing different soil types (Espodossolo Humilúvico or Carbic Podzol, and Argissolo Vermelho-Amarelo or Haplic Acrisol), land covers (Atlantic Forest, bush vegetation, and grassland) and topographies (flat and moderate slope). The SM was monitored at a temporal resolution of one hour along the 2013-2014 hydrological year and then resampled a resolutions of 6 h, 12 h, 1 day, 2 days, 4 days, 7 days, and 15 days. Descriptive statistics, temporal variability, time-stability ranking, and hierarchical clustering revealed uneven associations among SM time components. The results show that the time-invariant component ruled SM temporal variability over the time-varying parcel, either at high or low temporal resolutions. Time-steps longer than 2 days affected the mean statistical metrics of the SM time-variant parcel. Additionally, SM at downstream and upstream sites behaved differently, suggesting that the temporal mean was regulated by steady soil properties (slope, restrictive layer, and soil texture), whereas their temporal anomalies were driven by climate (rainfall) and hydrogeological (groundwater level) factors. Therefore, it is concluded that around the border between tropical soil types, the distinct behaviour of time-variant and time-invariant components of SM time series reflects different combinations of their soil properties.

Dynamic groundwater recharge simulations based on cosmic‐ray neutron sensing in a tropical wet experimental basin

“…Surrounding the CRNS, the soil moisture varied from 0.056 to 0.296 cm 3 cm −3 . The spatial variation was likely influenced by the uneven vegetation cover, implying also an average soil bulk density smaller than that found at four points within the experimental catchment by Barbosa et al (2019). Additionally, the total bound water content summed up 0.009 cm 3 cm −3 in the near-surface, which, alongside with soil moisture and soil bulk density, led the dry neutron count rate parameter N 0 to be equal to 550 cph.…”

“…The soil in GEB originated from crystalline basement erosion during the Late Quaternary, which constitutes massive deposits of friable sands (Rossetti et al., 2012). The soil texture in the experimental basin is mainly composed of coarse sand (∼46%), fine sand (∼52%), and silt and clay (∼2%), belonging to the haplic acrisol and carbic podzol soil types encompassing the study area (Barbosa et al., 2019; IUSS Working Group WRB, 2015).…”

Spatial variability modeling of soil fertility for improved nutrient management in Northwest Ethiopia

“…Soil properties vary with time (Awe et al 2015a(Awe et al , b, 2020aBarbosa et al 2019;Reichert et al 2020) and space (Secco et al 2009;Marins et al 2018;Appel Neto et al 2020) due to the cumulative effect of biophysical and chemical factors. Understanding of soil properties' spatial variability (Silva et al 2003;Guan et al 2017) and developing site-specific recommendations (Guan et al 2017;Rosemary et al 2017) are vital for optimizing nutrient use, improving crop productivity, and minimizing environmental hazards (Panday et al 2018).…”