A decadal record of soil moisture space–time variability over a south‐east Australian catchment. Issue 12 (14th December 2022)

• Record Type: Journal Article
• Authors: Senanayake, Indishe P.; Yeo, In‐Young; Hancock, Gregory R.; Willgoose, Garry R.
• Is Part Of: Hydrological processes. Volume 36:Issue 12(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-12-14
• Subjects: catchment‐scale -- in‐situ observations -- NDVI -- soil moisture -- spatial variability -- temporal variability; Hydrology -- Periodicals; Hydrology -- Research -- Periodicals; Hydrologic models -- Periodicals; Hydrological forecasting -- Periodicals; 631.432
• DOI: 10.1002/hyp.14770
• Languages: English
• ISSNs: 0885-6087

Abstract

Abstract: Semi‐arid to temperate south‐east Australian catchments with agricultural landscapes demonstrate unique hydro‐climatic characteristics. Understanding the behaviour of soil moisture over such catchments and the influence of driving factors are crucial for hydrologic, climatic and agricultural applications. However, this is challenging due the complex, non‐linear relationship between these factors and soil moisture, and the lack of long‐term catchment scale data records. To address this, spatial and temporal patterns of soil moisture over two south‐east Australian river catchments (i.e., Krui and Merriwa) and the influence of soil texture, topography, vegetation and rainfall on soil moisture variability were evaluated using a decadal in‐situ dataset. This unique in‐situ soil moisture monitoring network is established over a semi‐arid to temperate catchment representing typical south‐east Australian agricultural landscape and the data record has captured some major climatic events. Time stability of catchment‐scale soil moisture and the potential of predicting catchment mean soil moisture content using one representative station were also examined using a linear regression model. Soil texture was found as the dominating factor driving the spatial variability of soil moisture in the area. The temporal patterns of soil moisture showed a positive agreement with vegetation dynamics and rainfall at topsoil layers (0–5 cm and 0–30 cm). A higher spatial variability of soil moisture was observed during dry catchment conditions compared to wet catchment conditions. The deeper soil layers (30–60 cm and 60–90 cm) showed highly stable soil moisture values, which might be the driving force of the agriculture in the area. A linear regression based prediction model demonstrated a good potential in estimating spatial mean soil moisture content from one representative station. The results are useful in parameterization of soil moisture variability in land surface, climatic and hydrologic models, agricultural applications and in remote sensing of soil moisture. Abstract : Soil moisture patterns over two adjacent south‐east Australian catchments were evaluated for their spatial and temporal trends and the effects of precipitation, soil texture, vegetation and topography using a long‐term in‐situ data record (SASMAS observations). Soil texture and precipitation were found to be the dominating factors in driving spatial and temporal variability of soil moisture. A linear regression model was developed to predict catchment mean soil moisture using the observations of a single representative monitoring station based on the CASMM site concept.