Laboratory for Remote Sensing Prof. KS Cheng

Hydrology and Spatial Modeling (RSLAB)

 

Professor Ke-Sheng Cheng

Dept of Bioenvironmental Systems Engineering &
Master Program in Statistics

National Taiwan University

Email: rslab@ntu.edu.tw

RSLAB_BSE_NTU
No. 1, Section 4, Roosevelt Road
Bioenvironmental Syst. Eng., National Taiwan University

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    • Applied Hydrology
    • Data Computation, Analysis and Visualization Using R
    • 2022 Hydrologic Frequency Analysis
    • Remote Sensing
    • Stochastic Hydroclimatic Modeling & Simulation
    • Stochastic Hydrology
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stochastic hydroclimatic modeling & simulation

 NTU COOL Class Website

 

(This is an English-Medium Instruction (EMI) course)

Introduction 

Hydrology and climatology are two closely related branches of earth science. Almostallvariablesinhydrologicaland/orclimatologicalprocessesexhibitcertain degree of randomness. Either from a scientific or engineering point of view, understanding and characterizing the random nature of hydroclimatic processes enables us to make sound decisions for water management and disaster prevention. In this course, students will learn step by step from characterizing and simulating a single random variable to simulation of a spatiotemporal random field which is composed of many correlated random variables in space and in time. Stochastic simulation will be highly emphasized in class since it is the foundation for probability-based risk assessment. 

The objectives of this course are:

1.   To introduce fundamental concept of stochastic modeling, and their applications.

2.   To demonstrate the stochastic nature of hydroclimatic processes.

3.   To discuss the uncertainty involved in model parameter estimationandintroduce the techniques of stochastic simulation for quantifying uncertainties.

4.   To demonstrate stochastic modeling of hydroclimaticprocesses.

5.   To demonstrate practical applications of stochastic modeling/simulation for water resources management and riskassessment.

 

Prequisits:

  • Entry level hydrology
  • Entry level statistics
  • Capability of coding with R language

 

  • 1. Introduction to hydrological and climatological time series

    • Rainfall data series
      • Temporal scale - 10-minute, hourly, daily, ten-day-period, monthly, annual
      • Spatial scale - at-site, cell-average, basin-average,
      • Extreme rainfall series - annual maximum series (multiple at-site vs basin average)
      • Storm rainfall time series (hyetograph)
    • Flow data series
      • Temporal scale - hourly
      • Basin scale - small subbasin vs large watershed
      • Extreme flood series - annual maximum floods 
      • Flood flow time series
    • Wind speed data series
      • Temporal scale - 10-minute, hourly
  • 2. Time series modeling of hydroclimatic processes  (PPT1, PPT2, PDF1, PDF2)

    • Random process - definition and characteristics
    • Autocorrelation and partial autocorrelation
    • Nonstationarity - trend and periodic variation
    • Stationarity - ARIMA
    • Forecasting and forecasting intervals
    • Spectral analysis - periodogram (PPT, PDF)
    • Non-Gaussian time series (PPT)
      • Gamma autogressive (GAR) time series 
      • Stochastic simulation of the bivariate gamma distribution (SERRA Reference)
    • Real-time forecasting model performance evaluation (MPE) (PDF , SERRA Reference) 
    • Home-1 TSA   
    • Xia_Yun_DailyFlow29.csv  (40-year daily flow series at Xia-Yuan (1964 - 2003))
  • 3. Modeling the time variation of storm rainfalls (Stormrainfall hyetograph modeling) [pdf file]

    Executable code SSGM

  • 4. Spatial covariation of hydroclimatic process

    Stochastic Simulation of Multi-site Event-Max Rainfalls (PDF)

    Gamma random field simulation (PDF)


  • 5. Spatiotemporal covariation of hydroclimatic process

    • Spatiotemporal covariation of 10-day stream flows  (PDF)       
    • Reference: Water shortage risk assessment usingspatiotemporal flow simulation, Geoscience Letters, 2016.

     

  • x. Droughts

RSLAB - NTU

Prof. Ke-Sheng Cheng 


RSLAB_BSE_NTU
No. 1, Section 4, Roosevelt Road
Bioenvironmental Syst. Eng., National Taiwan University