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Overview of ground-based generator towers as cloud seeding facilities to optimize water resources in the Larona Basin

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The Larona River Basin which cover an area of 2477 km2, including the three cascading lakes: Matano, Mahalona, and Towuti Lakes, is a strategic watershed which acts as the water resource for three hydropower plants that supply 420 Megawatt of electricity to power a nickel processing plant and its supporting facilities and electricity need of the surrounding communities. The maximum and minimum operating levels of Towuti Lake are 319.6 meters (asl) and 317.45 meters (asl) respectively. Total live storage between these two elevations is 1,231,500 m3. Currently, the operation average outflow from Towuti Lake to the power plants is 130.1 m3/second which is resulting in a total annual outflow volume of 4,103,000 m3. By comparing the outflow volume with the live storage volume, it is obvious that present live storage has a limited capability to carry over the capacity from wet to dry years. During a dry year, the outflow drops to 100 m3/second. Thus, the optimization of water resources management in the Larona Basin is important to fulfil the need to produce the energy sources. To deal with the decrease of the Lakes water level, the Weather Modification Technology in the form of cloud seeding is needed to produce rain that will increase the water volume in the Lakes. The dispersion of cloud seeding material into the targeted clouds can be done by surface seeding using the Ground-Based Generator (GBG) which utilize towers to release cloud seeding materials. The tower locations should be in certain altitude or higher locations and amounts in order to operate effectively with optimum results. The water discharges generated from the process is expected in accordance with the planning. The weather modification process is inefficient when the discharge is overflow the spillway channel. Cost incurred is in approximate of US 11,133,258.36 if the company is utilizing Diesel Power Plant and Steam Power Plant instead of the weather modification technology.
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Overview of ground-based generator towers as
cloud seeding facilities to optimize water
resources in the Larona Basin
Anom Prasetio1*, Bambang L. Widjiantoro1, and Aulia MT Nasution1
1Department of Physics Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia
Abstract. The Larona River Basin which cover an area of 2477 km2,
including the three cascading lakes: Matano, Mahalona, and Towuti Lakes,
is a strategic watershed which acts as the water resource for three
hydropower plants that supply 420 Megawatt of electricity to power a
nickel processing plant and its supporting facilities and electricity need of
the surrounding communities. The maximum and minimum operating
levels of Towuti Lake are 319.6 meters (asl) and 317.45 meters (asl)
respectively. Total live storage between these two elevations is 1,231,500
m3. Currently, the operation average outflow from Towuti Lake to the
power plants is 130.1 m3/second which is resulting in a total annual
outflow volume of 4,103,000 m3. By comparing the outflow volume with
the live storage volume, it is obvious that present live storage has a limited
capability to carry over the capacity from wet to dry years. During a dry
year, the outflow drops to 100 m3/second. Thus, the optimization of water
resources management in the Larona Basin is important to fulfil the need to
produce the energy sources. To deal with the decrease of the Lakes water
level, the Weather Modification Technology in the form of cloud seeding
is needed to produce rain that will increase the water volume in the Lakes.
The dispersion of cloud seeding material into the targeted clouds can be
done by surface seeding using the Ground-Based Generator (GBG) which
utilize towers to release cloud seeding materials. The tower locations
should be in certain altitude or higher locations and amounts in order to
operate effectively with optimum results. The water discharges generated
from the process is expected in accordance with the planning. The weather
modification process is inefficient when the discharge is overflow the
spillway channel. Cost incurred is in approximate of US$ $11,133,258.36
if the company is utilizing Diesel Power Plant and Steam Power Plant
instead of the weather modification technology.
1 Introduction
The Larona River Basin which cover an area of 2477 km2, including the three cascading
lakes: Matano, Mahalona, and Towuti Lakes, is a strategic watershed which acts as the
water resource for three hydroelectric power plants (PLTA) which supply electricity needs
* Corresponding author: Anom.prasetyo@vale.com
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© The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative
Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/).
for PT. Vale Indonesia Tbk’s nickel mining operation and its surrounding areas [1]. The
total installed power in the hydropower plants is 420 MW, consisting of a 3x60 MW from
the Larona power plant, 2x65 MW from the Balambano power plant and a 2x55 MW from
the Karebbe power plant, all of which are in cascade systems [1, 2].
The three hydropower plants operate by utilizing the water resources from the
aforementioned cascading Lakes in the Larona River Basin channeled through the Larona
River to the plants’ turbines (Fig. 1). The drop of the Lakes water volume will affect the
optimal operation of the hydropower to efficiently support PT. Vale Indonesia’s nickel ore
smelting operations in Sorowako. Lower than average rainfall has significantly impacted
the Matano and Towuti Lake’s water volume [1, 3]. Minimum elevation limit of Towuti
Lake for optimal operation of the hydropower plants is 318.00 meters. The drop of the
water level in the Towuti Lake will disrupt the capacity of the three PLTA to serve the need
of nickel production processes. In turn, PT. Vale Indonesia will need to operate alternative
electricity sources, like diesel generators and other sources which drive higher costs [1, 3].
Fig. 1. Three lakes and hydro power plant cascade systems.
To maintain the water level of the Lakes for the PLTA to operate in their optimum
capacity, the company need to utilize Weather Modification Technology (TMC) as an
integrated part in the management of water resources. TMC is terminology for human effort
to modify weather with a specific purpose through cloud seeding, to increase the intensity
of rainfall in a designated area. Seedling materials are fired to the clouds through aircraft or
ground-based seeding facilities known as the Ground-Based Generator (GBG) [4-8].
2 Study of weather modification technology (TMC) using GBG
2.1 Ground-based generator towers
The static weather modification technology system or better known as Ground-Based
Generator (GBG) is an on-surface, static medium or system to disperse seeding material
into clouds which takes advantage of valley winds and slopes topography. GBG technology
in cloud seeding can reduce our reliance on aircraft usage, the most expensive component
in the weather modification operation. This alternative technology has the advantage of
being much cheaper than using an airplane [4-8].
GBG technology is intended primarily for cumulus and orographic cloud seeding
around the mountainous area that cannot be reached by aircraft for safety reasons. The
results of this study have shown that TMC utilizing a static system of GBG is quite useful
to complement the aircraft-based TMC, as long as it meets the geographical requirements
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and the method of cloud growth. The seed ingredients used in GBG technology are
hygroscopic flares that are burned at the top of towers (Fig. 2 and Fig. 3). The particles
from the combustion of hygroscopic flares, carried away by the valley wind, will be
dispersed into the targeted clouds around the tower locations [9].
Fig. 2. GBG towers illustration. Fig. 3. GBG towers PT. Vale Indonesia.
2.2 Geographical conditions
The target area is the Larona River Basin which covers a 2477 km2 area (Fig. 4). The
catchment and lake area are presented in Table 1. Along the Larona River, there are three
large lakes as seen in Fig. 4, i.e. Matano Lake (165.9 km2), Mahalona Lake (23.6 km2), and
Towuti Lake (562.2 km2). Larona watershed is geographically located near the equator and
flanked by the Bone Bay to the West, and Tolo Bay to the East makes this area has
distinctive rainfall characteristics. The Larona River Basin is on a mountainous range with
an altitude of between 500 to 1300 meters above sea level [10].
Fig. 4. Matano, Mahalona, and Towuti Lake as a target area for cloud seeding.
Table 1. Catchment and lake area of Larona River Basin.
Catchment area km2 Lake area km2
Towuti lake outlet 2447 Matano 165.9
Towuti lake outlet to Batubesi Dam 29.9 Mahalona 23.6
Upper catchment to Batubesi Dam 2477 Towuti 562.2
2.3 Natural rain process
Evaporation drives by convection or by the presence of hills or mountains will make the
moisture condense at a certain level. As it is hygroscopic, and when condensation takes
place, the particles will turn into liquid drops (droplets) which then collectively form
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clouds. Provided there is sufficient humidity, especially in the layer below the cloud base,
condensation will turn the droplets to a size of about 30 microns which physically visible in
the form of more clouds. Shall the particles grow more massive, by about 40-50 microns,
the particles will drop faster and act as “collectors” in their way down as they will attract
other smaller liquid drops into much larger drops (the collision process). This process is
reciprocated and propagated to all parts of the cloud and fall like the rain with a drop size of
about 1000 microns or greater [9, 11-17].
2.4 Types of clouds for seeding
Targeted clouds in the TMC activities are active cumulus (Cu) which are characterized by
their cauliflower-like shapes (Fig. 5). The cloud's area formed from convection processes.
The cumulus clouds are divided into three types [11], namely 1) Strato cumulus (Sc), that is
cumulus cloud in the formation process, 2) Cumulus, 3) Cumulonimbus (Cb), that is a huge
Cumulus cloud or several huge cumulus clouds which merge into a gigantic one. The
cauliflower-like Cumulus clouds (Cu) are clouds targeted as seeding clouds in the TMC
activities. These clouds are categorized as low clouds since they have a base height lesser
than 2 km. Cb is a low cloud which grows vertically with peaks reaches high clouds.
Fig. 5. Types of clouds based on characteristics and altitude.
2.5 Hydropower operation
The current operation of the Larona Hydroelectric Facilities relies on the active storage in
Towuti Lake. The maximum and minimum operating levels of Towuti Lake are 319.6
meters (asl) and 317.45 meters (asl) respectively (Fig. 6). Total live storage between these
two elevations is 1,231,500 m3. Currently, the average operation outflow from Towuti Lake
to the power plants is 130.1 m3/second which is resulting in a total annual outflow volume
of 4,103,000 m3 [1, 3]. By comparing the outflow volume with the live storage volume, it is
obvious that present live storage has a limited capability to carry over the capacity from wet
to dry years. Routing studies support this observation. During a dry year, the outflow drops
by 100 m3/second. The total available flow from the Larona Basin in average is 138
m3/second per year, 7.9 m3/second of which is spilled from the Batubesi Dam. An increase
in available storage volume would increase energy production by eliminating or at least
reducing the spill. Thus, an increase in volume will expand the average rate of flow to the
power plant by the ratio of a spill to average flow (7.9/130.1) or 6.07% [1, 3].
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Fig. 6. Matano and Towuti lakes level.
3 TMC implementation
Prior to implementing the weather modification/ cloud seeding technology, some studies
had been carried out such as to locate the towers site and clouds in the target area, to gauge
the rainfall rate and rain prediction, as well as to analyze the economic factors, especially
the incurring operating costs shall the technology fails to be implemented [2, 8].
3.1 Plotting tower location
Fig. 7. Plotting tower location in Larona River Basin.
GBG tower locations are selected according to the aspects of cloud growth potential and
local air circulation system to optimize the operation of seedling materials projected from
the top of the GBG towers into the clouds through the air flow system around the locations.
To select the locations of GBG tower (Fig. 7), during the initial stage (design), the
followings are considered: limited to an area of 2477 km2, the presence of clouds in the area
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with an altitude < 2 km from the ground surface of site locations, the height of the tower
measured from sea level (potentially > 300 meters) [2, 6-8, 18].
3.2 Existence of clouds in target areas
The presence of clouds above the Larona watershed is determined by competent experts on
radar monitoring based on a full day (morning to evening) observations of satellite imagery
and airport radar. Currently, radar monitoring is used for aircraft-based cloud seeding to
identify potential rain-clouds, including the clouds locations, size, and movement.
Meanwhile, GBG Towers operation has not utilized the airport radar. Historical clouds data
will need to be obtained from the Climatology and Geophysics Meteorology Agency to
determine the right location of the GBG Towers. In that way the facilities are situated close
to clouds or be able to trap the clouds and produce sufficient raindrops, to increase the
normal water level feed to the hydropower plants. Here is one example of data from BMKG
regarding cloud conditions (Fig. 8) [6, 11, 15].
Fig. 8. One month accumulated data during March 2010.
3.3 Constraints variable and objective function
The objective function of this research is to optimize the location of the GBG Tower
including the number so that it matches the target of cloud seeding with flares so that the
clouds can rain and fall in the Lake area which serves as a water supplier to the
Hydroelectric Power Plant. Before determining its purpose function, the following are the
equations of the variable and its constraint functions [12].
3.3.1 Larona river basin
Determine the constraint variable for the lake water level and elevation as follows [1]:
a. Limitation of Larona Watershed Area: A < 2477 km2.
b. The expected water level (target elevation) is between the minimum water level of
317.45 m above sea level and a maximum elevation of 319.6 m above sea level or
317.45 m above sea level < Target Elevation < 319.6 m above sea level.
3.3.2 GBG tower and flare material
Determine the variable constraint for 1 GBG Tower capacity and flare material [2]:
a. The area affected by rain with a circular area with r (radius) is: 1 km2.
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b. The number 1 of the GBG Tower contains as many as 8 sticks of flares.
c. Estimated number of 1 flares can produce rainfall of 1-5 mm/hour, if 8 flares, the
resulting rainfall is 8-40 mm/hour.
d. The duration of cloud seeding by GBG Tower for 4 hours.
3.3.3 Coordinate and elevation of tower points
Effective tower location based on topographic conditions and historical cloud data are [2]:
a. Cloud height from the tower point coordinates < 2 km.
b. The elevation of the tower point is > 300 m above sea level.
3.3.4 Constraint function
Some equation functions (constraints) obtained from the constraint variables are [1, 2, 19]:
a. The target elevation is the expected water elevation following the GBG Tower
operations in the Larona river basin area [1].
317.45 < (R.10-3).n + 317.45 < 319.6 (1)
where R = Rainfall (mm), n = Total of GBG Towers.
b. The flare shooting from the GBG Tower will produce rain that fall circularly in the
radius of the towers, so the following equation is used to calculate the impacted areas
which are limited around the Larona river basin [2].
Π. r2 x n < 2,477 (2)
where Π = Phi (22/7), r = Circle radius (km), n = Total of GBG Towers.
c. The volume of water in Towuti Lake derived from the difference between the minimum
and maximum elevations is used in the equations to calculate the addition of rainfall
generated from the GBG towers operations [1, 2]:
A. n. R < V (3)
where A = Area of Towuti Lake (km2), n = Total of GBG Tower, R = Median rainfall flare
seeding for 4 hours (mm), V = Towuti lake volume of between minimum and maximum
elevation (m).
d. Debits generated by towers must be greater than the discharge required by the
hydroelectric power plant [1]:
n. Qtower > Qhydropower (4)
where n = Total of towers, Qtower = Debit 1 tower (m3), Qhydropower = Debit hydropower (m3).
3.4 Objective function
Some constraint variables and constraint functions of the previous equation are concluded
that the objective function can be formulated as follows [2, 4-7]:
F (n) = Max (n. R) (5)
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where F (n) = Function number n GBG Tower, R = Rainfall resulting from flare seeding by
GBG Tower (mm).
4 Results and discussion
Based on the constraint variables, the function of the constraints and objective functions of
the equations above, the number of towers to be installed optimally and adjusted to the
cloud positions can be determined. The amount of additional rainfall will be calculated
using the Weibull program [1-7, 19].
4.1 Total towers
By calculating the known values, such as the radius of the area affected by cloud seeding
via the tower r = 1 km, seeding with 8 flares on 1 tower that produces rainfall (R) between
8-40 mm, 4 hours of seeding duration and the resulting R in estimate of 32-160 mm, the
median value of R is 96 mm. If R-value is included into Eq. 1 and Eq. 3 and the area of
Towuti Lake of 562.2 km2 plus the volume of water between the minimum and maximum
elevations of 1,231,500 m3 is included in Eq. 4, the three equations depicted in the
coordinate diagram will resulted in the number of towers to be installed: n = 21 towers.
4.2 Monitoring additional rainfall
To ensure additional water level (%), cloud seeding result will be presented in the following
formula, considered the number of GBG towers and its location are determined [18]:
Q = ((Qa – Qp)/Qa) x 100% (6)
where Qa = Actual inflow (m3/sec) when there are TMC, Qp = Prediction of inflow
(m3/sec) if there is no TMC, Q = Addition of inflow (%).
Table 2. Prediction inflow (m3/sec) Larona River Basin using by Weibull.
Probability Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
30% 145.81 162.42 235.96 330.05 287.27 246.55 153.88 101.62 74.70 81.31 155.05 178.41
40% 128.31 142.90 207.64 290.45 252.80 216.96 135.41 89.43 65.74 71.55 136.45 157.00
50% 116.65 12.94 188.77 264.04 22.82 197.24 123.10 81.30 59.76 65.05 124.04 142.73
60% 100.32 111.75 162.34 227.08 197.64 169.63 105.87 69.92 51.40 55.94 106.68 122.75
70% 85.15 4.85 137.80 192.75 167.77 143.98 89.86 5.35 43.63 47.48 90.55 104.19
80% 57.16 63.67 2.50 129.38 112.61 96.65 60.32 3.84 29.28 31.87 60.78 69.94
90% 46.66 51.98 75.51 105.62 91.93 78.90 49.24 32.52 23.91 26.02 49.62 57.09
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To predict Inflow if there is no TMC operation, Weibull method is used as seen in Table
2. The Weibull method is used to calculate water inflow prior to TMC operation TMC
operation is usually based on the prediction of lower rainfall (below normal) for the next
few months which will directly impact to reservoir inflow. Based on the calculation, the
predicted inflow during TMC operation is measured with a Weibull method which resulted
in a probability between 70% and 80% (below normal). In theory, cloud seeding operation
with these GBG towers will increase the rate of rainfall by about 10-15% of its natural rate,
which is equivalent to 10-15% addition to its natural inflow (predicted inflow). The number
of additional water thanks to the implementation of TMC with GBG, to the level of
probability of 80% and water addition rate of 15%, will be calculated in Table 3 [14].
Table 3. Inflow prediction, additional inflow, and additional volume inflow with assuming Weibull
prediction 80% and additional inflow 15%.
Description Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Prediction
Inflow (80%)
(m3/sec)
57.16 63.67 2.50 129.38 112.61 96.65 60.32 3.84 29.28 31.87 60.78 69.94
Additional
Inflow (15%)
(m3/sec)
8.57 9.55 0.38 19.41 16.89 14.50 9.05 0.58 4.29 4.78 9.12 10.49
Total Inflow
(m3/sec) 65.73 73.22 2.88 148.79 129.50 111.15 69.37 4.42 33.67 36.65 69.90 80.43
Fig. 9. Scheme of power plant PT. Vale Indonesia Tbk.
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Table 4. Potential loss – thermal steam turbine generator (maximum severity 13 month).
No Description Quantity Unit Remarks
1 Operating time 9,360.00 hrs
2 Avaibility 1.00 %
3 Power setting 40.00 MW
4 Effective power 0.88
5 Average power 329,472.00 MW (1)*(2)*(3)*(4)
6 Gross energy 455.00 MWH
7 Calcine 724,114.29 mt/hr ((5)*1000)/(6)
8 Ni calcine 2.11 %
9
Recovery Ni rkp to Ni
prod 0.89 USD
10 Ni matte 13,565.43 mt/hr (7)*(8)/100*(9)
11 Lbs Ni 29,906,621.04 USD (10)*1000*2.20462
12 LME price 6.39 USD
13 LME factor 0.78
14 Production cost 4.03 USD
15 Benefit/loss margin 0.95 (12)*(13)-(14)
16 Potential additional loss 28,399,327.34 USD (11)*(15)
17 Potential loss/month 3,549,915.92 USD (16)/8
Table 5. Fuel consumption calculation.
Thermal
plant
Power capacities Fuel consumption
Fuel
price Yearly operating
Yearly fuel
consumption
as per
SLA
(a)
Unit Rate
(b) Unit Value
(c) Unit
Physical
avaibility
assumption
(d)
Hour (e) -
(d) + 365
+ 24
as per
SLA
(a)*(b)*(c)
*(e)
Unit
STG 20 MW 2.02 Brl/MWH 73.88 USD 91.08% 7,978.608 23,814,166
USD/
year
MBDG 30 MW 245 Ltr/MWH 0.62 USD 91.08% 7,978.608 36,417,159
USD/
year
CAT 23 MW 270 Ltr/MWH 0.62 USD 91.08% 7,978.608 30,768,784
USD/
year
Total Fuel Price 91,000,109
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5 Conclusions
The drought occurs around the Larona River Basin decreases the water flow which in turn
lower the electrical energy supply to the energy-intensive nickel processing plant. TMC
application in the form of GBG towers installation system is an effective and efficient
approach to accelerate rainfall to increase the expected water inflow. Additional direct
inflow will increase the sufficient electrical power needed nickel production processes. The
calculation table below shows how production loss will potentially occur when the plant is
powered on the thermal plant instead of PLTA. Cost incurred per month is US$
3,549,915.92 + ($ 91,000,109/12) = US$ 11,133,258.36 versus weather modification
technology cost at US$ 122,685 per month [4].
This article is dedicated to the management of PT. Vale Indonesia Tbk, such as Lovro Paulic as Chief
Operating Officer (COO), Andi Suntoro as Director of Maintenance & Utilities, Dr. Bambang L.
Widjiantoro, S.T., M.T., Dr. rer. nat. Ir Aulia M.T. Nasution, M.Sc as our respectful counterpart in
scientific discussions and the whole academic communities of Institute of Technology Sepuluh
November Surabaya, Indonesia.
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INCO, 1975)
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... A ground-based generator is one alternative technology that has been developed and successfully applied in Indonesia. Among recent examples of groundbased seeding, one example was in the Larona Basin, Sorowako, in Sulawesi Indonesia, in 2019 [22] and 2020, which will be discussed in this paper. ...
... Both lakes' water level heights were measured directly from on-site visual observations. The basin's inflow and outflow were calculated from a water balance equation, based on the lakes' water level height and their hydroelectric plant's storage volume change among the parameters of the said equation [22,25]. ...
... Both lakes' water level heights were measured directly from on-site visual observations. The basin's inflow and outflow were calculated from a water balance equation, based on the lakes' water level height and their hydro-electric plant's storage volume change among the parameters of the said equation [22,25]. ...
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Cloud seeding activities have been carried out in the form of experiments and operation activities as part of water resource management in some parts of the world. Recently, a new method of cloud seeding using a ground-based generator (GBG) was introduced in Indonesia. This method is used to seed orographic clouds with the aid of a 50 m GBG tower located in a mountainous area. By taking advantage of the topography and local circulation, the GBG tower will introduce hygroscopic seeding materials into orographic clouds to accelerate the collision and coalescence process within the clouds, increasing the cloud’s rainfall amount. The hygroscopic ground-based cloud seeding was conducted over the Larona Basin in Sulawesi, Indonesia, from December 2019 to April 2020. There were five towers installed around Larona Basin, located over 500 m above sea level. The results show that there was an increase in monthly rainfall amount from the GBG operation period in January, February, and March compared to its long-term average of as much as 79%, 17%, and 46%, respectively. Meanwhile, despite an increase of 0.4% in Lake Towuti water level, it is still not concluded that the GBG cloud seeding operation was involved in the lake water level raise. Therefore, more studies need to be performed in the future to answer whether the cloud seeding affected the lake water level.
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1. Introduction One of the ways to increase rainfall and water production is cloud seeding technology. In this regard, the purpose of this study is to investigate the effect of cloud seeding technology on increasing the water of Khash Basin, the most prone area for climate change projects in Sistan Province as documented in several national and international studies; Considering the scenario of increasing rainfall by about 15 to 25%, the management of water resources was studied on the drinking, agriculture, and industry sectors in this basin. Therefore, the current percentage of meeting the needs of drinking, agriculture, and industry was compared using Water Evaluation And Planning (WEAP) with the future condition considering a 20% increase in rainfall due to the implementation of cloud seeding project. 2. Materials and Methods WEAP is a comprehensive, user-friendly, and flexible model developed for water resources planning. The main advantage of WEAP is the integrated approach in simulating irrigation systems and evaluating the impact of different policies. In the field of hydrological modeling, the WEAP software models all the processes necessary for the quantitative balance of surface water and the interaction of the groundwater aquifer with the river flow. The methods for modeling surface water in the software are 1) soil moisture method, 2) water requirement method (FAO), and 3) standard method (rainfall-runoff). We will use the standard method according to the available data/information. 3. Results and Discussion In the current situation, urban and rural drinking needs are fully met according to the higher priority. Also, the needs of agriculture and industry are met 100% in December, January and February and less than 25% in April to September, which is a significant shortage and management measures must be compensated for this shortage. The reliability of urban and rural drinking needs is 100%, which means that these needs are fully met in all months of the period. This percentage is about 33% for industry needs and about 25% for agriculture needs, which means a lack of proper reliability to meet these needs. The percentage of needs supply in the industry and agriculture sectors has increased with increasing rainfall in March and April. The results show the Effects of weather modification operations on water resources of Khash basin using water evaluation and planning (WEAP) model 4. Conclusion The results showed a 20% increase in precipitation in the Khash area, which was identified as a cloud-prone area; it has a positive effect on the percentage of supply of different needs. Cloud fertility is one of the most cost-effective methods of water supply can be effective as a suitable solution in the management of water resources of basins in various drinking, industry, and agriculture sectors according to various scientific sources Long-term implementation of climate change projects can be a valuable and cost-effective solution to the effects of drought and climate change in the country's basins
Article
Full-text available
Introduction One of the ways to increase rainfall and water production is cloud seeding technology. In this regard, the purpose of this study is to investigate the effect of cloud seeding technology on increasing the water of Khash Basin, as the most prone area for climate change projects in Sistan Province as documented in several national and international studies; Considering the scenario of increasing rainfall by about 15 to 25%, the management of water resources was studied on the drinking, agriculture and industry sectors in this basin. Therefore, the current percentage of meeting the needs of drinking, agriculture and industry was compared using Water Evaluation And Planning (WEAP) with the future condition considering a 20% increase in rainfall due to the implementation of cloud seeding project. Materials and Methods WEAP is a comprehensive, user-friendly, and flexible model developed for water resources planning. The main advantage of WEAP is the integrated approach in simulating irrigation systems and evaluating the impact of different policies. In the field of hydrological modeling, the WEAP software models all the processes necessary for the quantitative balance of surface water and the interaction of the groundwater aquifer with the river flow. The methods for modeling surface water in the software are: 1) soil moisture method, 2) water requirement method (FAO), and 3) standard method (rainfall-runoff). We will use the standard method according to the available data/information. Results and Discussion In the current situation, urban and rural drinking needs are fully met according to the higher priority. Also, the needs of agriculture and industry are met 100% in December, January, and February and less than 25% in April to September, which is a significant shortage, and management measures must be compensated for this shortage. The reliability of urban and rural drinking needs is 100%, which means that these needs are fully met in all months of the period. This percentage is about 33% for industry needs and about 25% for agriculture needs, which means a lack of proper reliability to meet these needs. The percentage of needs supply in the industry and agriculture sectors has increased with increasing rainfall in March and April. The results show the positive effect of implementing climate change projects on water resources in Khash Basin. Conclusion The results showed a 20% increase in precipitation in the Khash area, which was identified as a cloud-prone area; it has a positive effect on the percentage of supply of different needs. Cloud fertility as one of the most cost-effective methods of water supply can be effective as a suitable solution in the management of water resources of basins in various drinking, industry, and agriculture sectors according to various scientific sources, Long-term implementation of climate change projects can be a valuable and cost-effective solution to the effects of drought and climate change in the country's basins.
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The Larona River Basin which covers an area of 2,477 km2, including the three cascading lakes: Matano, Mahalona and Towuti, is a strategic watershed which acts as the water resource for three hydropower plants that supply 420 Megawatt of electricity to power a nickel processing plant and its supporting facilities and electricity need of the surrounding communities. The maximum and minimum operating levels of Lake Towuti are 319.6 meters (asl) and 317.45 meters (asl) respectively. The optimization of water resources management in the Larona Basin is important to fulfil the need to produce the energy sources. Weather Modification Technology in the form of cloud seeding is needed to produce rain which will increase the volume of water in the lake when the lake water level decreased. In the rainy season, spillway operations in all dams must be optimized because the water levels upstream and downstream are continuously monitored to prevent the impact of flooding in both areas.
Article
Full-text available
Introduction One of the ways to increase rainfall and water production is cloud seeding technology. In this regard, the purpose of this study is to investigate the effect of cloud seeding technology on increasing the water of Khash Basin, as the most prone area for climate change projects in Sistan Province as documented in several national and international studies; Considering the scenario of increasing rainfall by about 15 to 25%, the management of water resources was studied on the drinking, agriculture and industry sectors in this basin. Therefore, the current percentage of meeting the needs of drinking, agriculture and industry was compared using Water Evaluation And Planning (WEAP) with the future condition considering a 20% increase in rainfall due to the implementation of cloud seeding project. Materials and Methods WEAP is a comprehensive, user-friendly, and flexible model developed for water resources planning. The main advantage of WEAP is the integrated approach in simulating irrigation systems and evaluating the impact of different policies. In the field of hydrological modeling, the WEAP software models all the processes necessary for the quantitative balance of surface water and the interaction of the groundwater aquifer with the river flow. The methods for modeling surface water in the software are: 1) soil moisture method, 2) water requirement method (FAO), and 3) standard method (rainfall-runoff). We will use the standard method according to the available data/information. Results and Discussion In the current situation, urban and rural drinking needs are fully met according to the higher priority. Also, the needs of agriculture and industry are met 100% in December, January and February and less than 25% in April to September, which is a significant shortage and management measures must be compensated for this shortage. The reliability of urban and rural drinking needs is 100%, which means that these needs are fully met in all months of the period. This percentage is about 33% for industry needs and about 25% for agriculture needs, which means a lack of proper reliability to meet these needs. The percentage of needs supply in the industry and agriculture sectors has increased with increasing rainfall in March and April. The results show the positive effect of implementing climate change projects on water resources in Khash Basin. Conclusion The results showed a 20% increase in precipitation in the Khash area, which was identified as a cloud-prone area; it has a positive effect on the percentage of supply of different needs. Cloud fertility as one of the most cost-effective methods of water supply can be effective as a suitable solution in the management of water resources of basins in various drinking, industry and agriculture sectors and according to various scientific sources Long-term implementation of climate change projects can be a valuable and cost-effective solution to the effects of drought and climate change in the country's basins.
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Telah dilakukan penelitian prediksi cuaca dengan perangkat lunak model cuaca WRF-ARW selama kegiatan Teknologi Modifikasi Cuaca di Sumatera, Sulawesi, dan Jawadalam periode tahun 2010 dan 2011. Data masukan diperoleh dari prediksi global GFS(Global Forecast System) yang dapat diunduh setiap enam jam pada situs NOAA.Dengan WPS (WRF Prepossessing System), data global tersebut akan dipersempitsesuai wilayah yang akan diprediksi. Unsur cuaca yang diprediksi adalah curah hujandan arah angin yang diproses sehari sebelumnya. Hasil prediksi diolah secara spasialdengan program GrADS. Validasi dilakukan dengan mencocokan hasil GrADS dengandata radar atau data satelit. Selain itu, dilakukan juga parameterisasi untuk memperolehhasil prediksi yang lebih akurat dengan mengacu pada metode menggantikan prosesyang terlalu kecil atau kompleks secara fisik yang direpresentasikan dalam model yangdisederhanakan. Diharapkan hasil prediksi cuaca WRF-ARW ini dapat menjadi acuanuntuk menentukan peluang yang paling baik dalam periode harian untuk melakukanpenyemaian awan.Weather prediction with WRF-ARW has been carried out daily for Weather ModificationTechnology activities in Riau and West Sumatra from June 21 – July 21, 2010. The input data obtained from GFS (Global Forecast System), which can be downloaded every six hours from the NOAA website. With WPS (WRF Preprocessing System) global data will be downscaled according to the area that would be predicted. Weather components are predicted rainfall and wind direction is processed the day before. The prediction results are spatially processed with the program Grads. Validation is done by matching the results of Grads and radar data or satellite data. It is expected that the results of WRF-ARW forecast weather can be a reference to determine the best opportunities in conducting cloud seeding.
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This paper presents about the use of WRF modelling to assist weather analysis for cloud seeding operation in the Citarum Catchment Area, West Java, Indonesia. In this study, WRF parameterization was carried out . The parameterized values were used to forecast precipitation during cloud seeding operation. To study the effect of variational run, WRF 3DVAR was run using GDAS data set and doppler weather radar data. The result of this study shows that precipitation can be better predicted by ingesting radar data into 3DVAR run.Makalah ini menyajikan tentang penggunaan pemodelan dengan WRF untuk membantu analisis cuaca yang dipakai dalam operasi penyemaian awan di DAS Citarum, Jawa Barat, Indonesia. Dalam kajian ini telah dilakukan parameterisasi WRF, kemudian nilaiparameter yang diperoleh dipakai untuk mendapatkan prakiraan presipitasi selama operasi penyemaian awan. Untuk mempelajari pengaruh dari run variasional, WRF 3DVAR dijalankan dengan menggunakan data GDAS dan data radar doppler. Hasil dari studi ini menunjukkan bahwa prakiraan presipitasi yang lebih baik dapat diperoleh dengan mengasimilasikan data radar ke dalam run 3DVAR.
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