Modeling the Impacts of Spatial Heterogeneity in the Castor Watershed on Runoff, Sediment, and Phosphorus Loss Using SWAT: I. Impacts of Spatial Variability of Soil Properties

Abstract

Spatial accuracy of hydrologic modeling inputs influences the output from hydrologic models. A pertinent question is to know the optimal level of soil sampling or how many soil samples are needed for model input, in order to improve model predictions. In this study, measured soil properties were clustered into five different configurations as inputs to the Soil and Water Assessment Tool (SWAT) simulation of the Castor River watershed (11-km2 area) in southern Quebec, Canada. SWAT is a process-based model that predicts the impacts of climate and land use management on water yield, sediment, and nutrient fluxes. SWAT requires geographical information system inputs such as the digital elevation model as well as soil and land use maps. Mean values of soil properties are used in soil polygons (soil series); thus, the spatial variability of these properties is neglected. The primary objective of this study was to quantify the impacts of spatial variability of soil properties on the prediction of runoff, sediment, and total phosphorus using SWAT. The spatial clustering of the measured soil properties was undertaken using the regionalized with dynamically constrained agglomerative clustering and partitioning method. Measured soil data were clustered into 5, 10, 15, 20, and 24 heterogeneous regions. Soil data from the Castor watershed which have been used in previous studies was also set up and termed “Reference”. Overall, there was no significant difference in runoff simulation across the five configurations including the reference. This may be attributable to SWAT's use of the soil conservation service curve number method in flow simulation. Therefore having high spatial resolution inputs for soil data may not necessarily improve predictions when they are used in hydrologic modeling.

Spatial variation of crop rotations and their impacts on provisioning ecosystem services on the river Drava alluvial plain

“…Such heterogeneity can be connected with a high share of rocks and preferential water flows (Easton et al, 2008;Boluwade and Madramootoo, 2013). Uncertainty also occurs in the model framework as a catchment scale model was calibrated and validated to the soil water content.…”

“…Eco-hydrological models are regularly used in the research community for assessing the impacts of management practices and soil properties on water quality and plant growth. The impact of soil properties and their proper representation due to high spatial heterogeneity is gaining the importance, which is caused by the improvement of soil sampling and laboratory analysis procedures, use of pedotransfer functions and upgrading model algorithms (Deliberty and Legates, 2003;Mapfumo et al, 2004;Bossa et al, 2012;Williams et al, 2012;Boluwade and Madramootoo, 2013). Usually models like SWAT are reconceptualised and improved to achieve better representation at the HRU level (Post et al, 2007;Easton et al, 2008;White and Arnold, 2009;Arnold et al, 2010;Fu et al, 2014;Rathjens et al, 2014).…”

Variation of soil hydraulic properties with alpine grassland degradation in the eastern Tibetan Plateau

“…Knowledge of how FC and K s vary and of their influencing factors is essential for a better understanding of soil hydrological processes. FC and K s are also key parameters in most hydrological, climate and land surface models (Boluwade et al, 2013;Reszler and Fank, 2016;Tatsumi and Yamashiki, 2015). Therefore, understanding the effects of vegetation changes on FC and K s is necessary for model parameterization and for reducing the uncertainty of simulations (Sun et al, 2016).…”

Modelling the impacts of spatial heterogeneity in soil hydraulic properties on hydrological process in the upper reach of the Heihe River in the Qilian Mountains, Northwest China

“…At the watershed scale, different models have been used to simulate the impacts of spatial variability of soil hydraulic properties on the hydrological process (e.g. the Institute of Hydrological Distributed Model or IHDM, Calver, ; Soil and Water Assessment Tool or SWAT, Boluwade and Madramootoo, ; and Block‐wise use of TOPMODEL together with the Muskingum‐Cunge or BTOPMC, Wang et al ., ). Loague and Kyriakidis () found a high relevance of the spatial variability of saturated hydraulic conductivity for the description of infiltration processes in R‐5 catchment near Chickasha, Oklahoma, USA.…”