506
G. Romanescu and I. Minea
a continuous 12-month period, selected in such a way that the overall changes in the
storage are minimal so that carryover is reduced to a minimum. The average year
(normal year) represents the year for which the observed hydrological or meteorological quantity, approximately equals the long-term average of that quantity. The
normal hydrological year is the year when the mean annual flow has a value close to
the multiannual mean for this variable (±10%) [53]. For it to be representative, the
mean multi-annual value of mean annual flows is calculated for a long period, generally covering, at least, thirty consecutive years of observations. Such forecasting is
highly valid if the period analyzed is long. If the string of data is reduced, the degree
of error increases. The estimated flow may be higher or lower than 1: supraunitary
value if a certain interval is richer (>1); subunitary value if the interval is poorer (<1).
Runoff coefficient (η o ) represents the ratio of runoff depth (Y 0 ) to a precipitation
depth (P 0 ), both expressed in equivalent heights of water, within the same period
[31]:
η 0 =
Y 0
P 0
∗ 100 [%].
(15.1)
This parameter measures the hydrological productivity of transforming precipitations into the mean total precipitations. The module coefficient of mean total runoff
(K i ) represents the ratio of the mean annual runoff to the mean multi-annual runoff:
K i =
Q 01
Q 0
=
q 0i
q 0
=
V 0i
V 0
=
Y 0i
Y 0
[−].
(15.2)
The module coefficient of mean total runoff may exceed or may be lower than one.
Thus, expressing whether a certain interval is richer (>1) or poorer (<1), compared to
the average (normal) hydrological year. Depending on necessities, the relations can
be established between the different parameters. The most common of such relation
is determined between Y 0 and q 0 :
Y 0 =
V 0
10 3 ∗ F
=
31.56 ∗ 10
6
∗ Q 0
10 3 ∗ F
= 31.56 ∗ 10
3
∗
Q 0
F
= 31.56 ∗ q 0 (15.3)
To increase the estimated degree, one can consider the value of the minimum flow
(low-water mark). In this case, errors are reduced to around 10%. Unfortunately, the
model only approximates reality, the reason for which, it is not being considered.
Forecasting error represents the difference between a forecast and the observed
value. The probability event 1/n corresponds to an average return period of n years.
The drought index is the computed value which is related to some of the cumulative
effects of a prolonged and abnormal moisture deficiency. An index of hydrological
drought corresponding to the levels below the mean, in streams, lakes, reservoirs,
and the likes. However, an index of agricultural drought must relate to the cumulative
effects of either an absolute or an abnormal transpiration deficit. The probability of
forecast is the chance of occurrence of a quantified assessment (in real time) of future
G. Romanescu and I. Minea
a continuous 12-month period, selected in such a way that the overall changes in the
storage are minimal so that carryover is reduced to a minimum. The average year
(normal year) represents the year for which the observed hydrological or meteorological quantity, approximately equals the long-term average of that quantity. The
normal hydrological year is the year when the mean annual flow has a value close to
the multiannual mean for this variable (±10%) [53]. For it to be representative, the
mean multi-annual value of mean annual flows is calculated for a long period, generally covering, at least, thirty consecutive years of observations. Such forecasting is
highly valid if the period analyzed is long. If the string of data is reduced, the degree
of error increases. The estimated flow may be higher or lower than 1: supraunitary
value if a certain interval is richer (>1); subunitary value if the interval is poorer (<1).
Runoff coefficient (η o ) represents the ratio of runoff depth (Y 0 ) to a precipitation
depth (P 0 ), both expressed in equivalent heights of water, within the same period
[31]:
η 0 =
Y 0
P 0
∗ 100 [%].
(15.1)
This parameter measures the hydrological productivity of transforming precipitations into the mean total precipitations. The module coefficient of mean total runoff
(K i ) represents the ratio of the mean annual runoff to the mean multi-annual runoff:
K i =
Q 01
Q 0
=
q 0i
q 0
=
V 0i
V 0
=
Y 0i
Y 0
[−].
(15.2)
The module coefficient of mean total runoff may exceed or may be lower than one.
Thus, expressing whether a certain interval is richer (>1) or poorer (<1), compared to
the average (normal) hydrological year. Depending on necessities, the relations can
be established between the different parameters. The most common of such relation
is determined between Y 0 and q 0 :
Y 0 =
V 0
10 3 ∗ F
=
31.56 ∗ 10
6
∗ Q 0
10 3 ∗ F
= 31.56 ∗ 10
3
∗
Q 0
F
= 31.56 ∗ q 0 (15.3)
To increase the estimated degree, one can consider the value of the minimum flow
(low-water mark). In this case, errors are reduced to around 10%. Unfortunately, the
model only approximates reality, the reason for which, it is not being considered.
Forecasting error represents the difference between a forecast and the observed
value. The probability event 1/n corresponds to an average return period of n years.
The drought index is the computed value which is related to some of the cumulative
effects of a prolonged and abnormal moisture deficiency. An index of hydrological
drought corresponding to the levels below the mean, in streams, lakes, reservoirs,
and the likes. However, an index of agricultural drought must relate to the cumulative
effects of either an absolute or an abnormal transpiration deficit. The probability of
forecast is the chance of occurrence of a quantified assessment (in real time) of future