Masahiko Hasebe

Analysis Of Hydrologic Characteristics From Runoff Data - A Hydrologic Inverse Problem

Abstract In this paper, the characteristics of hydrologic basins as well as rainfall are derived only from daily runoff data. This is a sort of inverse hydrologic problem. First, time series of daily runoffs are separated into components of surface flow, inter-flow and groundwater flow by numerical filters whose cut-off infrequencies are deter-mined from the order of magnitude comparison ofAR (autoregressive) coefficients of runoff data and confirmed by the coherence gap in rainfall-runoff data. By assuming the daily rainfall to be of white noise, the time series of each component thus separated are fitted to the AR model from which the hydrologic impulse response characteristics (unit hydrographs for each subsystem) are determined. Time series of the daily rainfall are inversely generated from the original time series of the daily runoff and the coefficients of AR model determined as above. The estimated time series of rainfalls agree relatively well with the real, but screened, rainfall data. Finally, a nonlinear separation law of effective rainfall into several rainfall components is estimated.

Identification and prediction of nonlinear hydrologic systems by the filter-separation autoregressive (AR) method: Extension to hourly hydrologic data

Abstract In this paper, our method — from the hydrologic inverse detection method originally proposed for daily runoff data analysis — is extended to hourly hydrologic data analysis. A few modifications of the original inverse method (filter separation and autoregressive (AR) method) are necessary in order to apply it to hourly data. 1. (1) The cut-off frequency to separate the total runoff time series into component runoffs was determined by the slope of the semi-logarithmic plot of the recession curve. 2. (2) Coefficients of the autoregressive moving average (ARMA) model applied to each of the subsystems were determined by the least-squares criterion from the recession period data when rainfall stopped; thus the ARMA model is reduced to the AR model with a white-noise error. A remaining coefficient to be multiplied by the rainfall (input) is obtained by the continuity condition of effective rainfall and runoff. The conclusions of this analysis are as follows: 1. (1) Nonlinear hourly hydrologic systems are easily and precisely identified and predicted by the present method. 2. (2) Each subsystem of surface runoff, interflow and groundwater runoff is linear; the nonlinearity of the rainfall-runoff system is caused mainly by the nonlinearity of the separation of rainfall into component rainfalls. The nonlinear separation rule of rainfall into rainfall components is derived from inversely estimated rainfalls. 3. (3) Time series of hourly rainfalls can be inversely estimated from hourly runoff by this method and it compares well with the observed effective precipitation time series regardless of the size of watershed.

Separation of a storm hydrograph into runoff components by both filter-separation AR method and environmental isotope tracers

Abstract The purpose of this paper is to separate the total storm runoff into runoff components of overland flow, interflow and groundwater flow. The hourly storm hydrograph is separated into runoff components by the following two methods and the results are compared with each other: 1. (1) The first method is to separate the time series of the total flow into overland flow, interflow, and groundwater flow by using numerical filters determined by the slope of the semi-logarithmic plot of the recession curve. 2. (2) The second one is to separate the total storm runoff, using the geochemical data, into each component by the simultaneous solution of the mass balance equations describing the fluxes of water and the tracer isotope in the stream. 3. (3) Both results compare relatively well with each other.

Flood forecasting by the filter separation AR method and comparison with modeling efficiencies by some rainfall-runoff models

Abstract In this paper, the authors firstly propose a flood forecasting system with and without rainfall data, applying the filter separation AR method. The runoff time series are separated sequentially into two runoff components. Since each hydrologic subsystem is expressible by linear input-output relationships, the rainfall components are inversely estimated from the ARX model or from the response function type model. Future runoff is computed by the ARX or the response function type model utilizing the inversely estimated effective past rainfalls and the extrapolated future rainfalls as input, and, as for the shorter-period runoff, using also the past rainfall data. Secondly, we calculate and compare modeling efficiencies for four rainfall-runoff models. The four models are (1) the filter separation AR model, (2) and (3) two l inds of the generalized storage function model (Prasad model and Hoshi model) to which Karman filtering theory is applied, and (4) the tank model. The generalized storage function method contains the nonlinearity in the runoff equation itself and the single component nonlinear model. The filter separation AR method is composed of linear subsystems, and the nonlinearity of the total system is explained by the nonlinearity of the rainfall separation process into subsystems and the multicomponent model.

Estimation of snowmelt volume using air temperature and wind speed

Abstract Heat flux (the product of air temperature and wind speed) plays an important role in the melting process of snow. The relationship between wind speed and the exchange volume of sensible heat can be considered using the vortex correlation method. Accordingly, a near linear relationship can be shown between the ratio of the volume of snowmelt water to the air temperature and wind speed. This paper proposes a new snowmelt runoff model considering heat flux (the product of mean daily air temperature and mean wind speed) and spectral analysis. The results of the application of this model indicate that the volume of snowmelt water can be better estimated than previously.

Response Characteristics of Two Tropical River Basins

In this paper, we extend our method (Hino and Hasebe, 1979, 1981) of hydrologic inverse detection originally for runoff data analysis to the hydrologic basin in tropical zone.

Estimation of volume of snowmelt from temperature of snow line and residual snow amount

Abstract The relation between snowmelt and cumulative air temperature or cumulative areal air temperature has been analysed in accordance with the degree-day method applied to hydrological data for the Okutadami basin. On occasion, the volumes of snowmelt obtained by the conventional degree-day method were found to be unsatisfactory. In this paper, a new snowmelt runoff model is proposed involving not only the volume of snowmelt and cumulative air temperature but also residual snow amount. The resultant formula is applicable to an area where the effect of direct sunshine is negligible, i.e., either the weather is cloudy or the mountain slopes northward (in the northern hemisphere).

RUNOFF ANALYSIS IN A LOW-LYING BASIN AND RUNOFF PREDICTION AFTER PADDY FIELD CONSOLIDATION

The concept of the diffusive tank model is that, as the water level of drainage channels changes very slowly due to a backwater effbct inalowing-lying drainage basin, the unsteady flow in the channel can be simplified to a nonunifbrm flow.This paper applies the diffusive tank model to runoff analysis in a low-lying drainage basin which is about 1.7km2, and to investigate the hydrological characteristics of low-lying basin by runoff prediction after the paddy field consolidation. The results are summarized as fbllows;(1) The results of flood routing analysis by the diffusive tank model show a good coincidence with observed hydrographs.(2) After the paddy field consolidation of low-lying areas, herunoff prediction in future is performed.

The characteristics of sound from Flowing water in the river and the experiment of open channel by FFT analysis

The purpose of this study is to find the characteristics of sound of flowing water in the river and in the channel of experiment from frequency analysis by FFT. In the area of river improvement and river conservation works have tended to put importance to landscape from visual approach. But, in the future, it is necessary that the basic idea of acoustic approach called soundscape compared with visual approach is disscused in the river design.

The Characteristics of Fluctuation of Sound of Flowing Water in the River from the Viewpoint of Soundscape

The purpose of this study is to find the characteristics of sound environment from point of view of OM fluctuations in the river space, that is, the physiolbgical effect of environmental sound on man. In the area of river improvement and river conservation work have tended to put importance to landscape from visual approach. But, in the future, it is necessary that the basic idea of acoustic approached called soundscape compared with visual approach is discussed in the river design.