Evaluating the Timing and Interdependence of Hydrologic Processes at the Watershed Scale Based on Continuously Monitored Data

Antonio Arenas,Larry Weber,Keith Schilling,James Niemeier

doi:10.3390/w10030261

Abstract

A quantitative understanding of the interplay between the different components of the hydrologic cycle at the watershed scale can be gained from analyzing high-frequency hydrologic time series. High-frequency measurements of precipitation, soil water content, shallow groundwater, and streamflow were collected and analyzed in Otter Creek, a 122 km2 watershed located in Northeast Iowa, USA. For selected rainfall events occurring in 2014, it was found that there is at least 4 h of delay between soil water content and water table time series response and streamflow peak. This is true even when the water table was approximately 6.5 m below the ground surface before rainfall started. Data reveal a strong linear dependence between the soil water content and the water table, which suggests the existence of a capillary fringe that extends approximately 2.5 m above the water table. The highest streamflow values in Otter Creek occurred when both the water table was close to the ground surface and the near surface soil (top 65 cm) was close to full saturation. Analyses show that, in the study area, data on depth to water table or deep soil water content have the potential to play a key role in the development of a flood warning system. The transformation of rainfall into streamflow is a complex process that we simplified in this study. Additional analyses using physically based coupled surface-subsurface models or non-linear or stochastic models are recommended for more rigorous analysis.

Highlights

Floods are the most damaging natural disaster in the United States [1]
We evaluated high-resolution hydrologic time series, including rainfall, shallow soil water content (SWC), streamflow, and depth to water table (DWT) at upland locations, collected in an agricultural watershed in northeast Iowa
Based on data collected in an alpine catchment, [26] reports that for soil water content values higher than approximately 40–45% both streamflow and depth to water table drastically rose with small changes in soil water content

Summary

Introduction

Floods are the most damaging natural disaster in the United States [1]. Damages for the 1993 flood in Iowa were estimated to be $152 million and the 1993 and 2008 floods in the Upper Midwest exceeded economic losses of 1 billion dollars [2]. In an agricultural region, such as Iowa, that is characterized by high water tables [4] and runoff from cropped areas, evaluating flood risks warrants increasing attention [5]. Temporal resolution in hydrologic data collection, from the early part of the 20th Century to today, has increased from daily or intermittent values to sub-hourly [6,7]. This allows for better resolution of the timing of various hydrologic processes, including floods. In the U.S, several federal, state, local, and private entities operate high-frequency hydrologic data collection networks [8]. High temporal resolution data are important for developing and calibrating hydrologic models and assessing the dependence and timing among

Objectives

Methods

Results

Discussion

Conclusion