Eylon Shamir

Flood Forecasting in Regulated Basins Using the Ensemble Extended Kalman Filter with the Storage Function Method

An ensemble extended Kalman filter (EEKF) formulation is applied to a regulated basin. The existing event-based storage function method for the prediction of flow is enhanced to incorporate continuous soil water accounting and to be suitable for application in large watersheds with several tributaries. The formulation is complemented by EEKF, which utilizes flow and reservoir level observations to update catchment soil water and channel states, and reservoir storage estimates predicted by the model. The formulated forecast is suitable for operational application. Ensemble precipitation predictions are generated to serve as input to the forecast system, and the results are intercompared using two different statistical approaches. These predictions together with parametric uncertainty models constitute the basis of the ensemble flow predictions by the model. A case study is presented that demonstrates the implementation and evaluation of the method with respect to the prediction of large flow events in a 4,...

Surveying flash flood response in mountain streams

During the winter season of 2005, Southern California was besieged by a series of heavy precipitation events that caused widespread flash flooding, mud slides, debris flows, and significant damage. The first event began in December (28 December 2004 to 4 January 2005), triggered mudflows and flooding in the San Bernardino Mountains, and produced a record daily rainfall total for the city of Los Angeles. The second period of heavy rainfall occurred in January (7–12 January 2005) and was widespread, extending from west of Santa Barbara to the San Bernardino Mountains in San Bernardino County and to the south including San Diego County. The peak rainfall total during the January 2005 event exceeded 700 millimeters (30 inches) over the six-day period. Impacts included the disastrous La Conchita landslide in Ventura County, which killed 10 people and destroyed or damaged over 35 homes.

MODIS Inundation Estimate Assimilation into Soil Moisture Accounting Hydrologic Model: A Case Study in Southeast Asia

Abstract: Flash Flood Guidance consists of indices that estimate the amount of rain of a certain duration that is needed over a given small basin in order to cause minor flooding. Backwater catchment inundation from swollen rivers or regional groundwater inputs are not significant over the spatial and temporal scales for the majority of upland flash flood prone basins, as such, these effects are not considered. However, some lowland areas and flat terrain near large rivers experience standing water long after local precipitation has ceased. NASA is producing an experimental product from the MODIS that detects standing water. These observations were assimilated into the hydrologic model in order to more accurately represent soil moisture conditions within basins, from sources of water from outside of the basin. Based on the upper soil water content, relations are used to derive an error estimate for the modeled soil saturation fraction; whereby, the soil saturation fraction model state can be updated given the availability of satellite observed inundation. Model error estimates were used in a Monte Carlo ensemble forecast of soil water and flash flood potential. Numerical experiments with six months of data (July 2011–December 2011) showed that MODIS inundation data, when assimilated to correct soil moisture estimates, increased the likelihood that bankfull flow would occur, over non-assimilated modeling, at catchment outlets for approximately 44% of basin-days during the study time period. While this is a much more realistic representation of conditions, no actual events occurred allowing for validation during the time period.

Stochastic Continuous Storage Function Model with Ensemble Kalman Filtering (II) : Application and Verification

본 연구의 목적은 앙상블 칼만필터 기법과 연속형 저류함수모형을 연계하여 개발한 추계학적 연속형 저류함수모형의 적용성을 평가하고자 하는데 있다. 대상유역은 안동댐과 임하댐을 포함하는 지보 수위관측소 상류유역을 선정하였으며 2006년과 2007년 홍수기에 대해 분석을 수행하였다. 확정론적 모형을 적용한 결과 장기간의 모의기간에 대해 유출해석이 가능한 것을 확인하였다. 앙상블 칼만필터 기법을 적용하기 위해 Monte Carlo 모의기법을 적용하여 모형입력자료와 매개변수들에 대해 앙상블 멤버를 생성하였다. 추계학적 모형과 확정론적 모형의 누적절대오차를 비교한 결과 안동댐과 임하댐의 2007년 사상에서 각각 17.5 %와 18.3 %의 정확도가 향상되고 지보수위관측소에서는 40 % 이상의 정확도가 향상되는 것으로 나타났다. 이상의 결과로부터 관측유량과의 오차가 큰 모의결과에 있어서는 추계학적 모형이 보다 향상된 결과를 도출하는 것을 확인하였다. 【The objective of this study is to evaluate an application of stochastic continuous storage function model with ensemble Kalman filter technique. The case study is performed at the upstream basin of Jibo streamflow gauge including Andong and Imha dam. Test period is for the rainy season during 2006 and 2007. Long term runoff analysis is feasible in the case of using deterministic model. Ensemble members for input data and parameters are generated using Monte Carlo simulation for the purpose of applying ensemble Kalman filter technique. The cumulative absolute errors of stochastic model to the deterministic one are improved for the amount of 17.5 %, 18.3 % and more than 40.0 % for Andong dam, Imha dam and Jibo station, respectively. The results indicate that the stochastic model improves the accuracy of the simulated discharge considerably.】