Chulsang Yoo

Evaluation of the impact of rainfall on soil moisture variability

The impact of rainfall on the spatial-temporal soil moisture variability is investigated by using a model of the soil moisture dynamics and two rainfall models, the noise-forced diffusive precipitation model and the WGR model. The study shows that the variability of the soil moisture field is impacted during the limited time of the storm period. During the interstorm period, the variability of the soil moisture field is closely related with the soil texture, as supported by the analysis of the Washita 92 data set. As the impact of rainfall on the variability of the soil moisture field is limited to the short time period of precipitation, the role of the rainfall is simplified as a source of water to the soil moisture field without any consideration of its variability and/or organization in space. A simulation study of the soil moisture field temporal evolution also supports this result, i.e. a strong relationship between the soil moisture field and the variability of its medium. Also, larger variabilities of the loss field coefficient result in easier removal of moisture from the soil.

Stochastic Modeling of Multidimensional Precipitation Fields Considering Spectral Structure

A multidimensional stochastic precipitation model with major emphasis on its spectral structure is proposed. As a hyperbolic type of stochastic partial differential equation, this model is characterized by a small set of easily estimable parameters. These characteristics are similar to those of the noise-forced diffusive precipitation model, but the representation of the physical and statistical features of the precipitation field is similar to that of the Waymire–Gupta–Rodriguez-Iturbe (WGR) precipitation model. The derivation was based on the autoregressive process considering advection and diffusion, the dominant statistical and physical characteristics of the precipitation field propagation. The model spectrum showed a good match with the Global Atlantic Tropical Experiment spectrum. This model was also compared with the WGR model and the noise-forced diffusive precipitation model both analytically and through applications such as the sampling error estimation from spaceborne sensors and rain gauges. The sampling error from spaceborne sensors based on the proposed model was similar to that of the noise-forced diffusive precipitation model, but much smaller than that of the WGR model. Similar results were also obtained in the estimation of the sampling error from rain gauges.

Stochastic characterization of space-time precipitation: Implications for remote sensing

Abstract In this paper the characterization of the space-time spectral characteristics of tropical rainfall fields are studied directly from measurements from ground sensors and by using three stochastic models. The characterization of the spatial-temporal spectra is important for the design of satellite missions and to determine the bias in ground truth experiments. To carry out the latter a scheme is used to compare contemporaneous measurements of rain rate from a single-field-of-view estimate, based on a satellite remote sensor such as a microwave radiometer, with those coming from a point raingauge. Using this scheme the errors are computed for several observed rainfall fields, either from the data estimated spectra or from analytically derived and characterized ground measurements. This quantification provides a lower bound to total errors, since perfect instruments are assumed in this work, and it helps in terms of isolating and evaluating typical biases that might be contaminating retrieval algorithms.

Evaluation of Some Ground Truth Designs for Satellite Estimates of Rain Rate

In this paper point gauge measurements are analyzed as part of a ground truth design to validate satellite retrieval algorithms at the field-of-view spatial level (typically about 20 km). Even in the ideal case the ground and satellite measurements are fundamentally different, since the gauge can sample continuously in time but at a discrete point, while a satellite samples an area average but a snapshot in time. The design consists of comparing a sequence of pairs of measurements taken from the ground and from space. Since real rain is patchy, that is, its probability distribution has large nonzero contributions at zero rain rate, the following ground truth designs are proposed. Design 1 uses all pairs. Design 2 uses the pairs only when the field-of-view satellite average has rain. Design 3 uses the pairs only when the gauge has rain. For the nonwhite noise random field having a mixed distribution, the authors evaluate each design theoretically by deriving the ensemble mean and the mean-square error of differences between the two systems. It is found that design 3 has serious disadvantage as a ground truth design due to its large design bias. It is also shown that there is a relationship between the mean-square error of design 1 and design 2. These results generalize those presented recently by Ha and North for the Bernoulli white noise random field. The strategy developed in this study is applied to a real rain rate field. For the Global Atmospheric Program (GARP) Atlantic Tropical Experiment (GATE) data, it is found that by combining 50 data pairs (containing rain) of the satellite to the ground site, the expected error can be reduced to about 10% of the standard deviation of the fluctuations of the system alone. For the less realistic case of a white noise random field, the number of data pairs is about 100. Hence, the use of more realistic fields means that only about half as many pairs are needed to detect a 10% bias.

Effects on Characteristics of Instantaneous Unit Hydrograph by Rainfall Direction

하천유역에서 호우의 방향성은 유출특성의 차이를 발생시 킨다(Niemczynowicz, 1984; Lima and Singh, 2002; 2003). 호우의 방향성은 크게 이동방향과 이동속도로 구분되는데, 이 들 특성은 유역 출구에서 첨두유량, 첨두유량 발생시간, 유출 수문곡선의 형태 등에 큰 영향을 미치는 것으로 알려져 있다 (Yen and Chow, 1969; Surkan, 1974; Townson and Sim, 1974; Sargent, 1981; 1982; Foroud et al., 1984; Anderson et al., 1991; Singh, 1998; 2002; Chang, 2007). 이러한 차이는 사면 과 하천, 그리고 호우의 방향성이 어떤 식으로 결합하느냐에 따라 달라질 수 있다(Zevenbergen and Thorne, 1987; Brierley and Fryirs, 2005). 호우의 방향성에 의한 유출특성 차이를 살펴본 연구들은 크 게 유출모의를 이용한 경우와 모의실험를 통한 경우로 구분 할 수 있다. 먼저, 유출모의를 이용한 사례를 살펴보면, Foroud et al.(1984)은 FH-model(Foroud, 1978)을 이용하여 호우 이동방향과 이동속도에 의한 유출 특성의 변화를 분석 하였으며, 이들은 호우 방향성의 영향력이 첨두유량에 비해 첨두유량 발생시간에서 크게 나타남을 보인 바 있다. Lima Abstract

Evaluating Estimation Method of Sediment Yield Coupling with SCS-CN

토사유출량은 각종 침식(erosion) 중 산사태를 제외한 원인 에 의해 발생한 토사가 퇴적 및 이송 등의 과정을 반복하며 토사발생 지점으로부터 유역출구까지 도달한 토사량을 의미 한다(Son, 2001). 자연 하천유역에서 토양이 침식되는 정도를 추정하고, 유역출구에서 토사유출량을 적절히 추정한다는 것 은 쉬운 일이 아니다. 이는 토양침식의 발생원인이 복잡하고, 유역 출구까지의 토사이동 과정에서 토사의 거동 특성이 다 양한 원인에 의해 변화하기 때문이다(Kim et al., 2001; Lim et al., 2012). 그러나 토양침식량이나 토사유출량을 적절히 추 정하는 것은 수질이나 환경문제뿐만 아니라 토양, 유역관리 등의 문제에 있어서 매우 중요하다(Jain et al., 2005; 2009). 토사유출량 산정을 위한 대표적인 방법은 Wischmeier and Smith(1965)에 의해 개발된 USLE(Universal Soil Loss Equation)를 들 수 있으며, Williams(1976)는 USLE의 강우침 식인자를 토사침식량 지배인자와 유출에너지 인자로 대체하 여 MUSLE(Modified Universal Soil Loss Equation)를 제안 하기도 하였다. 이후에는 Renard et al.(1991)에 의해 USLE에 서 사용되는 인자들을 개선하여 RUSLE(Revised Universal Abstract