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Journal of Applied Sciences and Environmental Management
World Bank assisted National Agricultural Research Project (NARP) - University of Port Harcourt
ISSN: 1119-8362
Vol. 13, Num. 2, 2009, pp. 33-35
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Journal of Applied Sciences & Environmental Management, Vol. 13, No. 2, June, 2009, pp. 33-35
Content analysis
of Hydrometeorological Network in the Lower Benue River Basin, Nigeria.
Temi E.
Ologunorisa
Centre for Climate Change and Environmental Research, Osun State University ,Osogbo, Nigeria. E-mail (ologunorisatemi@yahoo.com)
Code Number: ja09019
ABSTRACT
This
study deals with content analysis of hydrometerological networks in the Lower
Benue River Basin, Nigeria. This is with the overall aim of determining the
effectiveness of the network in terms of providing useful data for agricultural
planning. The study examines the type of stations in the river basin, the type
of equipment available in each station, the frequency of observation, and the
range of weather elements measured as well as the utilitarian value of the
networks for agricultural research and environmental panning and management. To
realize this, a total of 30 out of 48 hydrometerological stations in the river
basin were analyzed. The results of the analysis show among other things that,
complete data were very hard to come by, and so much interpolation had to be
done. Thus important hydrometerological information relevant to agricultural
planning are missing. Also that the existing spatial distribution of the
networks has been found to be highly inadequate in some parts of the river
basin. Finally, only the synoptic stations have little relevance of
agricultural production. The study concludes by recommending a wide range of
measures to improve the quality of the networks to ensure sustainable
agricultural production and planning in the region. @ JASEM
A
hydro-meteorological networks is defined as a set of stations at which
observations of hydrologic phenomena are made as a function of time, and they
are meant to provide information to aid in planning, management and decision
making (Dawdy, 1979). A hydro-meteorological network consist not only of the
stations where data are collected but also the analytical models for
extrapolating and interpolating data in time and space (Oguntoyinbo, 1987).
Hydrological data encompasses all data commonly used by the hydrologist, and
the data are not necessarily of a hydrological nature nor need be collected by
an hydrological agency (WMO, 1957). They include data on precipitation, stream
flow and river lake stage, ground water levels, water infiltration and soil moisture.
Others are sediment, transportation and deposition, water quality, evaporation
and evapotranspiration, snow pack, frost penetration, soil temperature,
interception and depression storage. Another set of data are often collected
include topography, river profile and cross section, subterranean
characteristics, soil types and vegetation cover. Others in this second group
include water temperature, air temperature, radiation, wind and humidity.
Different
types of observatories exist for monitoring these phenomena and are graded
according to the types of observations made, frequency of observation and the
status of the observer (Ayoade, 1998). Such stations include synoptic weather
station, agro-meteorological station, climatic station, hydro-meteorological
and rainfall stations.
It
has been observed that majority of the studies carried out on content analysis
of hydro-meteorological networks are restricted to the technologically advanced
countries (Catteral, 1972; Cisleriora, et al 1974; Dawdy, 1979; Dawdy, et al
1972; Eagleson, 1967; Hendrick et al 1970; Hershfield, 1967; Hutchinson, 1967;
Kreuder, 1979; Osborn et al 1965, Osborn et al 1979; Shaw et al 1976; and Stol,
1972). The conclusion from these studies is that most stations in developed
countries are use specific, and they have strategies which reduce political
consideration and interagency conflicts.
Only
a few studies have been reported for the tropics (Oguntoyinbo, 1987). The few
available studies showed that most of the existing stations are not in their
proper location, and their locations have been influenced more by political
considerations and without consideration to how representative they are to the
surrounding area in question and their relationship to existing stations.
Although
the World Meteorological Organisation (1965) has made its recommendation for
the number of rainguages needed in certain areas, research has shown that
modifications are necessary due to various local reasons. In assessing the
content of hydro-meteorological networks therefore, the existing
hydro-meteorological network would be audited to find how effective and
efficient are they. It is in this respect that this study deals with the
content analysis of hydro-meteorological network in the Lower Benue River
Basin, Nigeria in order to assess the utilitarian value of the networks for
agricultural research, planning and enhanced food production.
METHODOLOGY
A
total of 30 hydro-meteorological stations in the Lower Benue River Basin were visited. At all the stations visited, personal observations were made of all
available equipment. Auditing of the stations were carried out in all the
stations visited to determine the actual location of the stations, frequency of
measurement at each hydro-meteorological station, reason why the stations were
established, year of establishment of the stations, and how much of their
objectives have been met, the quality of instruments and maintenance
facilities, qualification of the observatory staff and the frequency of supply
of recording materials.
Also
on the spot reading were made to compare readings with available records in
order to test for consistency. The stations workers were also interviewed and
their and their responses were utilized to form part of the primary data for
this study.
Table
1: Meteorological Stations and the
Equipment available in the Lower Benue River Basin Development Authority.
S/no |
Station |
Temp |
Rainfall |
Evaporation |
Wind
speed |
Isolation |
1.
|
Agogo |
|
* |
|
|
|
2.
|
Akwanga |
|
* |
* |
* |
|
3.
|
Ankpa |
* |
* |
|
|
|
4.
|
Ashige |
|
* |
|
|
|
5.
|
Ayanga |
|
* |
|
|
|
6.
|
Dep |
* |
* |
|
|
|
7.
|
Longkat |
* |
* |
|
|
|
8.
|
Makurdi |
* |
* |
* |
* |
* |
9.
|
Katsin-ala |
* |
* |
* |
* |
* |
10.
|
Okete |
|
* |
|
|
|
11.
|
Doma |
* |
* |
* |
* |
* |
12.
|
Bokkos |
* |
* |
* |
* |
|
13.
|
Heipang
(jos) |
* |
* |
* |
* |
* |
·
Equipment Available
Source: Lower Benue River Basin Development Authority.
S/no
|
River
|
Station
|
Latitude
|
Longitude
|
1.
|
Akwenyi
|
Ouyondu
|
80.341.40
|
80.551.15
|
2.
|
Arikya
|
Arika
|
80.491.50
|
70.401.30
|
3.
|
Arikya
|
Kiguna
|
80.401.20
|
80.541.55
|
4.
|
Ashige
|
Ashige
|
80.341.35
|
80.481.40
|
5.
|
Biku
|
Buku
|
80.561.10
|
80.311.20
|
6.
|
Damsak
|
Chip
damask
|
90.101.50
|
90.221.40
|
7.
|
Dep
|
Gallo
|
80.461.25
|
80.541.40
|
8.
|
Dep
|
Site
1
|
80.371.05
|
80.571.30
|
9.
|
Farin
ruwa
|
Mutu
|
80.571.30
|
80.531.10
|
10.
|
Gwalang
|
Chip
west
|
90.111.30
|
90.221.30
|
11.
|
Gwayaka
|
Alligani
|
80.431.20
|
80.491.30
|
12.
|
Keoloeng
|
Gidda
lifidi
|
90.031.05
|
80.221.05
|
13.
|
Mada
|
Tede
1
|
90.001.28
|
80.131.50
|
14.
|
Mada
|
Tede
2
|
90.531.28
|
80.191.50
|
15.
|
Geina
|
Dma
di
|
80.531.00
|
80.191.50
|
16.
|
Geina
|
Doma
d8
|
80.211.00
|
80.151.00
|
17.
|
Shemankar
|
Dokan
tofa
|
90.031.00
|
90.191.00
|
18.
|
Shemankar
|
Randa
|
90.111.50
|
90.191.45
|
19.
|
Shendan
|
Shendan
|
80.531.10
|
90.251.05
|
20.
|
Tan
|
Ambaka
|
80.561.25
|
80.531.10
|
21.
|
Wowen
|
Women
|
80.511.00
|
80.291.30
|
22.
|
Aini
|
Nassarawa
|
80.131.40
|
80.431.40
|
23.
|
Amba
|
Lafia
|
80.291.30
|
80.301.05
|
24.
|
Awonge
|
B.a.d
|
80.361.58
|
80.211.00
|
25.
|
Gbata
|
Gbata
|
80.561.10
|
80.331.20
|
26.
|
Jida
|
Jida
|
80.511.00
|
80.291.30
|
27.
|
Mada
|
Agam
|
80.061.00
|
80.061.00
|
28.
|
Mada
|
Ginda
ayemu
|
80.101.00
|
80.001.30
|
29.
|
Mada
|
Gudi
bridge
|
90.021.40
|
80.341.50
|
30.
|
Mada
|
Ogobo
|
80.041.00
|
80.021.20
|
31.
|
Mada
|
Rutu
|
80.251.50
|
80.111.30
|
32.
|
Mada
|
Tede
3
|
90.021.40
|
80.341.05
|
33.
|
Oeonda
|
Katsina
|
80.131.00
|
70.201.15
|
34.
|
Wusan
|
Chip
east
|
90.111.35
|
90.231.10
|
35.
|
Wulko
|
Duko
|
80.521.25
|
80.261.05
|
RESULTS AND DISCUSSION
The
hydro-meteorological stations in the study area were established between 1927
and 1983. The frequency of observation was found to be twice daily at 0800 hours
(8.00a.m. local time) and 1600 (4.00p.m local time) except the synoptic station
at the Makurdi airport where observations were made hourly. Also, complete data
was hard to come by and so much interpolation had to be done. In addition, 30
stations visited, interpolation had to be carried out for 93% of the stations.
About 60% of the stations have missing data. The standard size of an
observatory is 20 x 20m but only 15% of the stations met the requirement. Also,
about 20% of the stations were improperly sited. Wind vanes were placed in
shades or beside buildings, and many of the rainguages were improperly sited.
It was observed that 60% of the stations have well maintained Stevensons
screens, while about 30% of the stations duplicate functions. Only the synoptic
station produced the highest quality of information because of the purpose it
was meant to serve which is forecasting of weather.
Apart
from this, 75% of the climatic stations have been upgraded by the government to
agro-meteorological stations. About 63% of the agro-meteorological stations
have at least one sophisticated self-recording equipment. Rainfall stations
located in secondary schools and government ministries do not take record
during holiday. It was observed that 60% of the rainfall stations were
improperly placed, and with records taken by non-professionals. Many of the
hydrological stations still take record of river stage in feet and inches which
may allow for errors in comparison with the metric system. This observation was
made in similar study by Oguntoyinbo (1987) in Southwestern Nigeria. Due to
sand mining on riverbeds, some of the staff gauges are either missing, defaced
or dislocated, and needs replacement. Most of the stations with automatic
equipment especially automatic rainguages have no recording papers. Also that
40% have damaged equipment which have not been replaced. All the stations
depend on the Nigeria Meteorological Services, Oshodi, Lagos for help and
assistance which are not forthcoming. It was also observed that sensitized
cards or papers for sunshine recorders are in short supply, and over 90% of the
30 stations studied required interpolation, 60% of the original data were
missing. And finally, about 25% of the stations studied did not have proper
record keeping and retrieving system, and 90% of the stations are manned by
non-professionals (that is, part-time observers). Oguntoyinbos (1987) study
has also shown that most of the stations in Southwestern Nigeria are grossly
inefficient in terms of their utilitarian values as a large number of the
stations fall short of the internationally standard.
CONCLUSION
The study has
examined the content analysis of hydro-meteorological networks in the Lower River Benu Basin and its implications for agricultural planning. Out of a total of
30 hydro-meteorological stations studied in the river basin, results show that
complete data are very hard to come by, and so much interpolation had to be
done. Also that important hydro-meteorological information relevant for food
production and security were missed. The study concludes that there is need to
improve the quality of the network by addressing some of the problems already
identified in order to ensure sustainable agricultural production in the
region.
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1972 Application of Systems Analysis to Network Design W. M. O Publications.
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Hydrological Data. Water Resources Research, Vol. 15, No. 6.
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