AUTOMATED METHODS FOR ESTIMATING BASEFLOW AND GROUND WATER RECHARGE FROM STREAMFLOW RECORDS1
ABSTRACT To quantify and model the natural ground water recharge process, six sites located in the midwest and eastern United States where previous water balance observations had been made were compared to computerized techniques to estimate: (1) base flow and (2) ground water recharge. Results from an existing automated digital filter technique for separating baseflow from daily streamflow records were compared to baseflow estimates made in the six water balance studies. Previous validation of automated baseflow separation techniques consisted only of comparisons with manual techniques. In this study, the automated digital filter technique was found to compare well with measured field estimates yielding a monthly coefficient of determination of 0.86. The recharge algorithm developed in this study is an automated derivation of the Rorabaugh hydrograph recession curve displacement method that utilizes daily streamflow. Comparison of annual recharge from field water balance measurements to those computed with the automated recession curve displacement method had coefficients of determination of 0.76 and predictive efficiencies of 71 percent. Monthly estimates showed more variation and are not advocated for use with this method. These techniques appear to be fast, reproducible methods for estimating baseflow and annual recharge and should be useful in regional modeling efforts and as a quick check on mass balance techniques for shallow water table aquifers.
Article: Improving hydrologic predictions of a catchment model via assimilation of surface soil moisture[show abstract] [hide abstract]
ABSTRACT: This paper examines the potential for improving Soil and Water Assessment Tool (SWAT) hydrologic predictions of root-zone soil moisture, evapotranspiration, and stream flow within the 341 km2 Cobb Creek Watershed in southwestern Oklahoma through the assimilation of surface soil moisture observations using an Ensemble Kalman filter (EnKF). In a series of synthetic twin experiments assimilating surface soil moisture is shown to effectively update SWAT upper-layer soil moisture predictions and provide moderate improvement to lower layer soil moisture and evapotranspiration estimates. However, insufficient SWAT-predicted vertical coupling results in limited updating of deep soil moisture, regardless of the SWAT parameterization chosen for root-water extraction. Likewise, a real data assimilation experiment using ground-based soil moisture observations has only limited success in updating upper-layer soil moisture and is generally unsuccessful in enhancing SWAT stream flow predictions. Comparisons against ground-based observations suggest that SWAT significantly under-predicts the magnitude of vertical soil water coupling at the site, and this lack of coupling impedes the ability of the EnKF to effectively update deep soil moisture, groundwater flow and surface runoff. The failed attempt to improve stream flow prediction is also attributed to the inability of the EnKF to correct for existing biases in SWAT-predicted stream flow components.Research highlights► We test a data assimilation system to integrate soil moisture observations into a catchment model. ► Study is motivated by recent advances in soil moisture remote sensing. ► Both synthetic and real data assimilation experiments are conducted. ► We identify model problems that prevent assimilation from enhancing stream flow predictions.Advances in Water Resources 34(4):526-536. · 2.45 Impact Factor
Conference Proceeding: Evolutionary Regression Modeling with Active Learning: An Application to Rainfall Runoff Modeling.Adaptive and Natural Computing Algorithms, 9th International Conference, ICANNGA 2009, Kuopio, Finland, April 23-25, 2009, Revised Selected Papers; 01/2009
Conference Proceeding: Application of SWAT for sediment yield estimation in a mountainous agricultural basin[show abstract] [hide abstract]
ABSTRACT: The advanced SWAT (soil and water assessment tool) model is based on hydrologic process and needs to be calibrated and validated prior to application. This paper presents a case study conducted in Chaohe river upstream to verify the applicability of SWAT for predicting sediment yields in a semiarid mountainous basin. Utilizing the gage records, the SWAT was deeply explored in the study area. The monthly measured runoff and sediment yields at Dage gage during the period 1985-1987 was used to calibrate the model while data from 1988 to 1990 was used for model validation. First, runoff calibration and validation were performed, and the resulted monthly Nash-Sutcliffe efficiency coefficient (E<sup>NS</sup>) and R<sup>2</sup> were 0.81 and 0.93 for calibration period, respectively, 0.51 and 0.78 for validation period. Then, the sediment calibration and validation were carried out, and the E<sup>NS</sup> and R<sup>2</sup> for calibration and validation were both above 0.70 and 0.75, respectively. Finally, based on the annual sediment yields estimated by the calibrated model, the annual soil loads map was generated and the critical soil loss subbasins dominated by agricultural land were identified. This study revealed that the SWAT could be applied in a rugged mountainous region for erosion control and watershed management.Geoinformatics, 2009 17th International Conference on; 09/2009