Impact of Spatial Discretization of Hydrologic Models on Spatial Distribution of Nonpoint Source Pollution Hotspots

Abstract

The soil and water assessment tool (SWAT) was used to investigate the effects of hydrologic response unit (HRU) thresholds (0-20%) on predictions of multiple variables by calibrated and uncalibrated models in a 10.4-km 2 urban watershed in the U.S. Mid-Atlantic region. Surface runoff, discharge, sediment yield, and nutrient yield were simulated in stream and on land, and used to spatially identify hotspots for each constituent. SWAT2012 was able to produce accurate discharge and nitrogen estimates that were not sensitive to HRU thresholds. HRU thresholds significantly affected sediment and phosphorus predictions in calibrated and uncalibrated models. Constituent hotspots identified by an uncalibrated model with a 0% HRU threshold were found to be acceptable for the urban watershed under study, except for sediment. Hotspots identified with calibrated models, with HRU thresholds of 5% or less, fit with the identification of on-land sediment and nutrient hotspots. These findings suggest that researchers should carefully consider HRU thresholds when predicting on-land variables of small urban watersheds similar to the watershed in this study when using SWAT.

Identification of Suitable Hydrologic Response Unit Thresholds for Soil and Water Assessment Tool Streamflow Modelling

“…Generally, average streamflow was not greatly affected by HRU threshold (measured by RE), which agrees with the results of Her et al (2015) and Wang et al (2016). In addition, various HRU thresholds had little effect on monthly R 2 and NS values.…”

“…A SWAT model is spatially distributed and therein the watershed is partitioned into a number of sub-watersheds connected by stream networks using digital elevation model (DEM) data before further subdivision into multiple hydrologic response units (HRUs) by overlaying spatial datasets including slope, land-use, and soil maps to represent the spatial heterogeneity of the watershed (Savvidou et al, 2014;Luo et al, 2019). Model computational time is nearly proportional to the number of HRUs, since HRU is the basic calculation unit (Wang et al, 2016). In some cases, HRU numbers exceeded the computational limits on the model partly due to the large watershed scale or high level of discretisation (Chiang and Yuan, 2015).…”

Assessment of Three Long-Term Gridded Climate Products for Hydro-Climatic Simulations in Tropical River Basins

“…For instance, the NCEP-CFSR data performed poorly in both basins, regardless of size and flow characteristics, while the APHRODITE precipitation resulted in the best performance for both basins. We also note that differences in sub-basin and/or HRU delineations, while not investigated in this study, typically do not impact SWAT streamflow and other hydrologic outputs as discussed in a previous review of SWAT literature [48] and reported in several subsequent SWAT applications [92][93][94][95].…”

Avaliação dos efeitos hidrológicos da aplicação de cenários propostos pelo poder público

“…Na presente pesquisa, optou-se em definir HRU múltiplas em função das faixas de corte padrão recomendadas por Neitsch et al (2009) de 10% para tipo de solo e 20% para tipo de uso e ocupação do solo e para declividade. Justifica-se essa escolha em razão do modelo SWAT não apresentar melhora significativa dos índices de desempenho de estimativa de vazão com o aumento do número de HRU (FITZHUGH;MACKAY, 2000;MULETA;NICKLOW;BEKELE, 2007;WANG et al, 2016).…”