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

نویسندگان

  • Ari Posner
  • Konstantine Georgakakos
  • Eylon Shamir
چکیده

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. OPEN ACCESS Remote Sens. 2014, 6 10836

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Accounting for Pliem-Xiu and NOAH Module to Simulate Dust: A Case of Western Areas of Ahwaz

Extended abstract 1- INTRODUCTION In the arid and semi-arid areas of Asia, dust storms occur frequently. Much progress has been made in the monitoring modeling and prediction of Asian dust storms. Dust emission is caused by wind erosion in the sensitive areas. Wind erosion is described as the transportation of soil particles by means of the wind. Soil Surface moisture is one of the most i...

متن کامل

Improving Soil Moisture Estimation with a Dual Ensemble Kalman Smoother by Jointly Assimilating AMSR-E Brightness Temperature and MODIS LST

Uncertainties in model parameters can easily result in systematic differences between model states and observations, which significantly affect the accuracy of soil moisture estimation in data assimilation systems. In this research, a soil moisture assimilation scheme is developed to jointly assimilate AMSR-E (Advanced Microwave Scanning Radiometer-Earth Observing System) brightness temperature...

متن کامل

Variational Assimilation of Remote Sensing Data for Land Surface Hydrologic Applications

Soil moisture plays a major role in the global hydrologic cycle. Most importantly, soil moisture controls the partitioning of available energy at the land surface into latent and sensible heat fluxes. We investigate the feasibility of estimating large-scale soil moisture profiles and related land surface variables from low-frequency (L-band) passive microwave remote sensing observations using w...

متن کامل

Disaggregation of SMAP radiometric soil moisture measurements at catchment scale using MODIS land surface temperature data

Satellite soil moisture observations often require the enhancement of spatial resolution prior to being used in climatic and hydrological studies. This study employs the thermal inertia theory to downscale the 36 km radiometric data of the NASA’s Soil Moisture Active/Passive Mission (SMAP) into 1 km resolution. Regressions between daily temperature difference and daily mean soil moisture were e...

متن کامل

Downscaling GLDAS Soil Moisture Data in East Asia through Fusion of Multi-Sensors by Optimizing Modified Regression Trees

Soil moisture is a key part of Earth’s climate systems, including agricultural and hydrological cycles. Soil moisture data from satellite and numerical models is typically provided at a global scale with coarse spatial resolution, which is not enough for local and regional applications. In this study, a soil moisture downscaling model was developed using satellite-derived variables targeting Gl...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Remote Sensing

دوره 6  شماره 

صفحات  -

تاریخ انتشار 2014