CN103150615A - Runoff predicting method - Google Patents

Abstract

The invention discloses a runoff predicting method. The method comprises the following steps of: establishing a rainfall runoff yield model; carrying out parameter calibration on the rainfall runoff yield model by adopting rainfall and runoff data of farmland or a region obtained through observation, and determining a runoff yield influence coefficient K of antecedent rainfall and a rainfall initial loss value Id under the condition that no antecedent rainfall exists for a long time; and acquiring the daily rainfall P of a current day and the actual daily rainfall Pi of an antecedent i-th day of the farmland or region, and obtaining surface runoff Q according to the rainfall runoff yield model. The method disclosed by the invention has the advantages that higher surface runoff prediction accuracy is obtained while less monitored data are adopted.

Description

The Runoff Forecast method

Technical field

The present invention relates to the hydrologic(al) prognosis technology, specifically, relate to a kind of Runoff Forecast method.

Background technology

Runoff yield calculates forecast crop flooded stain disaster and formulates measures against flood disaster and has great significance, and is also the basis that quantizes and predict agricultural nonpoint source pollution.Calculating accurately Rainfall-runoff is the key of formulating reply arid, flood and the measure of liquid manure churn management.The model that is used at present prediction farmland and Basin Rainfall runoff yield relation mainly contains lump pattern type and the conceptual model of mechanism, and the former is difficult in the less area application of Monitoring Data due to comparatively complicated.Be widely used with wieldy characteristics and lack with input data of its needs as the conceptual model of representative take the SCS model that water and soil conservation office of United States Department of Agriculture proposes, but the precision of its prediction will be lower than lumped model.In order to improve the precision of SCS modeling runoff, some researchers once made improvements from introducing the aspects such as the gradient and raininess.But because a SCS model handle precipitation affects in early stage is thereby that 3 specified conditions have limited the lifting of these methods to precision from average angular defining.Therefore in order to represent as much as possible the actual conditions of runoff yield, the SCS model should embody the variation of precipitation affects in early stage on time and amount.Yet for do not make the SCS model complicated should be on the basis of existing daily rainfall observed reading on early stage daily rainfall impact again generally change.

Summary of the invention

Technical matters to be solved by this invention is to provide a kind of Runoff Forecast method, and generalization affects rainfall early stage again, and the precision of Runoff Forecast is improved.

Technical scheme of the present invention is as follows:

A kind of Runoff Forecast method comprises: set up rainfall-runoff model; Adopt farmland or regional rainfall and the footpath flow data that observation obtains to carry out parameter calibration to described rainfall-runoff model, the runoff yield influence coefficient K of definite rainfall in early stage and early stage are for a long time without the rainfall spurt value I under condition of raining _dGather described farmland or zone the same day daily rainfall P and early stage the actual daily rainfall P of i days _i, obtain flow path surface Q according to described rainfall-runoff model.

Further: described flow path surface

I wherein _aBe the daily rain amount spurt value, λ is the initial abstraction coefficient.

Further: the daily rain amount spurt value

Further: if the actual daily rainfall P in i days early stage _i〉=early stage is long-time without the rainfall spurt value I under condition of raining _d, the runoff yield in i days early stage effectively affects rainfall Get I _dValue.

Further: if the actual daily rainfall P in i days early stage _i＜early stage is long-time without the rainfall spurt value I under condition of raining _d, the runoff yield in i days early stage effectively affects rainfall

Actual daily rainfall P with i days early stage _iEquate.

Technique effect of the present invention is as follows:

1, method of the present invention has obtained higher flow path surface precision of prediction when adopting less Monitoring Data.

2, method of the present invention has been considered the impact that early stage, rain time changed, and more tallies with the actual situation, and can obtain higher flow path surface precision of prediction.

3, the parameter clear physical concept of the rainfall-runoff model of method of the present invention, can be by experiment or a small amount of observation data obtain.

Description of drawings

Fig. 1 is the comparison diagram of the footpath flow data of wheat-bare area of obtaining of SCS model, method of the present invention and observation;

Fig. 2 is the comparison diagram of the footpath flow data of the Wheat Maize that obtains of SCS model, method of the present invention and observation;

Fig. 3 is the comparison diagram of the footpath flow data of the Wheat-soybean that obtains of SCS model, method of the present invention and observation.

Embodiment

Below with reference to drawings and Examples, the solution of the present invention is described further.

Embodiment

As application of the present invention area, adopts method prediction of the present invention this area wheat-bare area, Wheat Maize and the Wheat-soybean field runoff volume under growing with somewhere, the Huaibei.The step of method of the present invention is as follows:

Step S1: set up rainfall-runoff model.

Rainfall-runoff model of the present invention to set up process as follows:

Suppose that all runoff process are all to occur under the condition of soil drier (there is no for a long time rainfall), and the spurt value that produces is defined as I under this condition _dWater balance equation under this condition and the hypothesis equation that is in equal proportions can be expressed as respectively:

P=I _d+F+Q （1）；

$\frac{Q}{P-I_d}=\frac{F}{S}---\left(2\right);$

Separately, I _d=λ S (3);

Wherein, P is daily rainfall on the same day, mm; F is the actual stagnant amount of holding after runoff yield begins, mm; Q is flow path surface, mm; I _dFor in earlier stage long-time without the rainfall spurt value under condition of raining, mm; S is the stagnant amount of holding of potential maximum after runoff yield begins, mm; λ is the initial abstraction coefficient.

Can be obtained by formula (1)～(3):

$Q=\frac{{(P-I_d)}^2}{(P-\frac{\mathrm{\λ}-1}{\mathrm{\λ}}{I}_d)}---\left(4\right).$

Under the drier condition of soil, if daily rainfall surpasses I _dAfter namely form runoff or infiltrate.Higher than I _dThe continuation rainfall will can not affect the runoff process of next day, namely not directly get the early stage rainfall total amount as the effective rainfall that affects runoff yield.Therefore, surpass I when rainfall amount _dThe time should get I _dThe value conduct affects rainfall, otherwise directly gets rainfall amount as affecting rainfall.In addition, early stage not the rainfall of same date on being different when the impact of daily rainfall, can not be simply after the simple addition of rainfall amount of a few days as affecting rainfall early stage.Therefore introduce variable K _iRepresent that rainfall in i days in early stage is to the influence coefficient of Rainfall-runoff on the same day.Supposition rainfall in early stage simultaneously concentrates on daily rain amount spurt value I the impact of runoff yield _aChange on.Like this under the conventional Rainfall-runoff condition of reality, after considering the impact of rainfall in early stage on Rainfall-runoff on the same day, with daily rain amount spurt value I _aBe defined as:

$I_a=I_d-\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{K}_i\×{\stackrel{\‾}{P}}_i---\left(5\right);$

Wherein, I _aBe daily rain amount spurt value, mm; I _dFor in earlier stage long-time without the rainfall spurt value under condition of raining, mm;

For early stage the runoff yield of i days effectively affect rainfall, mm; K _iFor early stage i days runoff yields effectively affect the influence coefficient of rainfall.

If the actual daily rainfall P in i days early stage _i〉=early stage is long-time without the rainfall spurt value I under condition of raining _d, the runoff yield in i days early stage effectively affects rainfall Get I _dValue.

If the actual daily rainfall P in i days early stage _i＜early stage is long-time without the rainfall spurt value I under condition of raining _d, the runoff yield in i days early stage effectively affects rainfall

Actual daily rainfall P with i days early stage _iEquate.

In order further to reduce the parameter amount, suppose under specific soil and crops condition that the Rainfall-runoff influence coefficient of front 1 day is a definite value K, and the influence coefficient of front i days is with exponential function K ⁱForm successively decrease, formula (5) can be reduced to:

(6); K is the runoff yield influence coefficient of rainfall in early stage.

I is used in composite type (4)～(6) _aReplace I _d, obtain the improvement rainfall runoff relation under normal condition, set up rainfall-runoff model of the present invention, namely

Flow path surface $Q=\frac{{(P-I_a)}^2}{(P-\frac{\mathrm{\λ}-1}{\mathrm{\λ}}{I}_a)}---\left(7\right)$ , wherein,

$I_a=I_d-\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{K}^i\×{\stackrel{\‾}{P}}_i$

Work as P _i〉=I _d, ${\stackrel{\‾}{P}}_i=I_d;$

Work as P _i＜I _d, ${\stackrel{\‾}{P}}_i=P_i.$

In an embodiment of the present invention, at first affected the daily rainfall that rainfall is taken as front 5d early stage, λ gets 0.2, and rainfall-runoff model Chinese style (6) and (7) in the present embodiment can be reduced to respectively:

$Q=\frac{{(P-I_a)}^2}{(P+4I_a)}$ (8); Wherein,

$I_a=I_d-\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{K}^i\×{\stackrel{\‾}{P}}_i.$

Step S2: adopt farmland or the regional rainfall runoff data that observation obtains to carry out parameter calibration to rainfall-runoff model, the runoff yield influence coefficient K of definite rainfall in early stage and early stage are for a long time without the rainfall spurt value I under condition of raining _d

In the present embodiment, gather the annual precipitation and runoff data of this area's wheat-bare area of 2007, Wheat Maize and Wheat-soybean, take the least square fitting error minimum of runoff observed reading and predicted value as target, the calibration parameter K that the rainfall-runoff model of employing formula (8) obtains wheat-bare area, Wheat Maize and Wheat-soybean is 0.3, and I _dBe respectively 9,13 and 23.

Step S3: utilize farmland or zone the same day daily rainfall P and early stage the actual daily rainfall P of i days _i, obtain flow path surface Q according to rainfall-runoff model.

In the present embodiment, gather the rainfall data of the 2008-2009 of this area wheat-bare area, Wheat Maize and Wheat-soybean.With K and the I that obtains in step S2 _dValue is incorporated in rainfall-runoff model of the present invention, and the data such as the table 1 that are obtained flow path surface Q by formula (8) provide its statistics.

The flow path surface Q that table 1 employing method of the present invention obtains and the statistics of actual observed value

The comparative example

In order to verify the precision of method of the present invention, adopt the flow path surface of identical data and traditional SCS model prediction above-mentioned test block, and flow path surface and the actual observed value of two kinds of methods predictions compared.

Use the SCS model, adopt the rainfall runoff data transfer rate of 2007 of this area to make the CN of wheat-bare area, Wheat Maize and Wheat-soybean test block ₂Parameter is respectively 91,88 and 78, and calculates the flow path surface statistics by the daily rain amount data of 2008-2009, and is as shown in table 2.

The flow path surface Q that table 2 employing SCS model obtains and the statistics of actual observed value

As Figure 1-3, be respectively the comparison diagram of the footpath flow data of SCS model, method of the present invention and the observation wheat-bare area, Wheat Maize and the Wheat-soybean that obtain.As seen from the figure, compare with the SCS model, the footpath flow valuve that method of the present invention obtains is more near observed reading, and method of the present invention can simulate the variation of run-off between Different Crop cropping pattern and runoff yield event better.Statistical study (table 1 and 2) by analog result also can find out, under 3 crop planting models, the model efficiency EF of method of the present invention〉0.40 and regression coefficient R ²0.5, apparently higher than the analog value of SCS model.Therefore method of the present invention can obtain more accurate footpath flow valuve.

Claims (5)

1. Runoff Forecast method comprises:

Set up rainfall-runoff model;

Adopt farmland or regional rainfall and the footpath flow data that observation obtains to carry out parameter calibration to described rainfall-runoff model, the runoff yield influence coefficient K of definite rainfall in early stage and early stage are for a long time without the rainfall spurt value I under condition of raining _d

Gather described farmland or zone the same day daily rainfall P and early stage the actual daily rainfall P of i days _i, obtain flow path surface Q according to described rainfall-runoff model.

2. Runoff Forecast method as claimed in claim 1, is characterized in that: described flow path surface

I wherein _aBe the daily rain amount spurt value, λ is the initial abstraction coefficient.

3. Runoff Forecast method as claimed in claim 2, is characterized in that: the daily rain amount spurt value $I_a=I_d-\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{K}^i\×{\stackrel{\‾}{P}}_i.$

4. Runoff Forecast method as claimed in claim 1, is characterized in that: if the actual daily rainfall P in i days early stage _i〉=early stage is long-time without the rainfall spurt value I under condition of raining _d, the runoff yield in i days early stage effectively affects rainfall

Get I _dValue.

5. Runoff Forecast method as claimed in claim 1, is characterized in that: if the actual daily rainfall P in i days early stage _i＜early stage is long-time without the rainfall spurt value I under condition of raining _d, the runoff yield in i days early stage effectively affects rainfall

Actual daily rainfall P with i days early stage _iEquate.

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