Abstract
This study provides a comprehensive evaluation of streamflow and water quality simulated by a hydrological model using three different Satellite Precipitation Products (SPPs) with respect to observations from a dense rain gauge network over the Occoquan Watershed, located in Northern Virginia, suburbs to Washington, D.C., U.S. Eight extreme hydrometeorological events within a 5-year period between 2008 and 2012 are evaluated using SPPs, TMPA 3B42-V7, CMORPH V1. 0, and PERSIANN-CCS, which are based on different retrieval algorithms with varying native spatial and temporal resolutions. A Hydrologic Simulation Program FORTRAN (HSPF) hydrology and water quality model was forced with the three SPPs to simulate output of streamflow (Q), stream temperature (TW), and concentrations of total suspended solids (TSS), orthophosphate phosphorus (OP), total phosphorus (TP), ammonium-nitrate (NH4-N), nitrate-nitrogen (NO3-N), dissolved oxygen (DO), and biochemical oxygen demand (BOD) at six evaluation points within the watershed. Results indicate fairly good agreement between gauge- and SPP-simulated Q for TMPA and CMORPH, however, PERSIANN-simulated Q is lowest among SPPs, due to its inability to accurately measure stratiform precipitation between intense periods of precipitation during an extreme event. Correlations of water quality indicators vary considerably, however, TW has the strongest positive linear relationship compared to other indicators evaluated in this study. SPP-simulated TSS, a flow-dependent variable, has the weakest relationship to gauge-simulated TSS among all water quality indicators, with CMORPH performing slightly better than TMPA and PERSIANN. This study demonstrated that the spatiotemporal variability of SPPs, along with their algorithms to estimate precipitation, have an influence on water quality simulations during extreme hydrometeorological events.
Highlights
Understanding the spatiotemporal behavior of hydrometeorological events is of critical importance for water resource management including flood mitigation and response, ecosystem restoration, river and water supply reservoir recharge, and water quality impacts
Results indicate fairly good agreement between gaugeand Satellite Precipitation Products (SPPs)-simulated Q for TMPA, whereas PERSIANN-simulated Q is generally lowest among SPPs, due to its inability to accurately measure stratiform precipitation between intense periods of precipitation during an event
SPP-simulated total suspended solids (TSS), a flow-dependent variable, has the weakest relationship to gauge-simulated TSS among all water quality indicators, with CMORPH performing slightly better than TMPA and PERSIANN
Summary
Understanding the spatiotemporal behavior of hydrometeorological events is of critical importance for water resource management including flood mitigation and response, ecosystem restoration, river and water supply reservoir recharge, and water quality impacts. Especially with long-term and climate change studies, have shifted to the use of standardized indices to allow for consistency between studies. These indices include the Expert Team on Climate Change Detection and Indices (ETCCDI), the Standardized Precipitation Index (SPI), the Standardized Precipitation, and Evapotranspiration Index (SPEI), and the Palmer Drought Severity Index (PDSI) which measure aspects of frequency (e.g., days above fixed thresholds), intensity (e.g., wettest day, average daily intensity), and duration (e.g., consecutive wet and dry days) based on daily precipitation measurements from in situ, satellite, and/or reanalysis datasets (Alexander et al, 2019; Qin et al, 2019)
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