Characteristics of Duwet Karst Spring Based on Baseflow Index Assessment and its Potential in Fresh Water Supply

<p><em>This study aims to determine the potential of Duwet springs and their availability for supplying fresh water to the surrounding community. we use hydrographs to analyze aquifer characteristics. To analyze the hydrographs, we use water level and spring discharge data. Automatic Water Level Record (AWLR) records water level data for 1 dry season and 1 rainy season every 15 minutes. We use the volumetric method to measure the spring discharge 14 times. We compare the base flow and demand over a year to analyze the potential for fresh water. The results show that the Stage discharge rating curve y = 0.0002e5,453x with R² value of 0.87. Duwet Springs is a perennial spring that has a small discharge (class VI). The largest discharge ever recorded was 0.69 L/s (March 7, 2020) and the smallest recorded was 0.12 L/s (August 21, 2020). BFI value varied between 0.05 and 1 with mean 0.801. The total base flow is 2490675.734 L (rainy season) and 1563419.873 L (dry season). These springs are sufficient for 75% of the rainy season and 84% in the dry season. This indicates that the existence of Duwet springs is very important for the surrounding community.</em></p>

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Rancang Bangun Monitoring Level Muka Air Tanah Di Perkebunan Lahan Gambut Menggunakan SMS Sebagai Pengirim Informasi Data Berbasis Mikrokontroler

Jurnal SPEKTRUM ◽

10.24843/spektrum.2019.v06.i01.p09 ◽

2019 ◽

Vol 6 (1) ◽

pp. 62

Author(s):

I Wayan Eka Prastia ◽

I Wayan Arta Wijaya ◽

I Wayan Sukerayasa

Keyword(s):

Water Level ◽

Groundwater Level ◽

Oil Palm ◽

Rainy Season ◽

Ground Level ◽

Dry Season ◽

Level Data ◽

Water Level Data ◽

Level Monitoring ◽

Water Level Monitoring

The fires of peatlands on oil palm plantations are very vulnerable to occur in the dry season. Fires will arise due to a decrease in the surface of the water resulting in the top layer of peatland becoming dry. Manually monitoring ground level is very difficult. The solution is to make a remote water level monitoring prototype in order to be able to regulate irrigation on peat land and make the system open and close the irrigation door during the dry season and when the rainy season arrives. The design of groundwater level monitoring uses a program installed on the Arduino Uno microcontroller.Water level data is sent by prototype via GSM SIM 800L network, 8 level conditions that have been determined from a depth of 15 cm multiples of five so on to 55 cm. HC-SR04 Ultrasonic Sensor is a detector for water level. Data can be accessed at any time via SMS by sending "Check" to the prototype. The results of the tests performed indicated that the tool can function in accordance with the design and send information as well as receive monitoring orders.

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MODEL SEDERHANA 2-DIMENSI ARAH PERGERAKAN SEDIMEN DI SUNGAI PORONG JAWA TIMUR

JURNAL GEOLOGI KELAUTAN ◽

10.32693/jgk.9.3.2011.209 ◽

2016 ◽

Vol 9 (3) ◽

pp. 175

Author(s):

Huda Bachtiar ◽

Franto Novico ◽

Fitri Riandini

Keyword(s):

Numerical Model ◽

Water Level ◽

River Mouth ◽

Sediment Concentration ◽

Dry Season ◽

Observation Data ◽

Wet Season ◽

Level Data ◽

Water Level Data ◽

Mike 21

Model numerik MIKE 21 modul transport sedimen digunakan untuk mengetahui respon pergerakan lumpur Sidoarjo pada saat musim hujan dan musim kemarau dan pengaruh tanggul yang berada di muara Sungai Porong. Data yang digunakan adalah pasang surut muka air laut, kedalaman air, debit sungai, arus dan konsentrasi sedimen. Simulasi dilakukan dengan membuat dua skenario, yaitu pada saat kondisi musim hujan dan pada saat musim kemarau. Hasil simulasi model hidrodinamika di verifikasi dengan data lapangan untuk mendapatkan nilai korelasi. Verifikasi meliputi data muka air dan kecepatan arus baik arah â€“x maupun â€“y. Berdasarkan hasil verifikasi didapatkan nilai korelasi muka air sebesar 0.8641 sementara arus bernilai 0.1493 untuk sumbu â€“x dan 0.1917 untuk sumbu â€“y. Selanjutnya hasil simulasi model menunjukkan konsentrasi sedimen pada tanggal 27 November 2007 merupakan puncak tertinggi dengan nilai 3.2x10-3 kg/m3 untuk musim hujan sementara untuk musim kemarau konsentrasi sedimen bernilai 0.0x10-3 kg/m3. Kata kunci : Model Numerik, Pergerakan Lumpur, Sungai Porong. Numerical model of MIKE 21 sediment transport module was applied to recognize the response of mud flow respective in rainy and dry season and also to get information of dike effect at the river mouth. Data that used in this simulation was tide, water depth, river discharge, current and sediment concentration. The simulations were created for two scenarios, therefore dry season and wet season. The result of the simulation model verified with observation data to see the correlation value. The verification are covering water level data and current magnitude of â€“x and â€“y axis. Based on the verification result, the correlation value of water level has a value 0.8641 meanwhile for the current the correlation value have magnitude 0.1493 of x-axis and 0.1917of y-axis. Moreover, the maximum value of sediment concentration could be seen at November 27th 2007 with 3.2x10-3 kg/m3 at the wet season and 0.0x10-3 kg/m3 for dry season. Keywords: Numerical Model, Mud Movement, Porong River

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USING TIME SERIES OF SENTINEL-1 IMAGES TO PRODUCE DRY BATHYMETRY OF RIVERS

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-v-3-2020-387-2020 ◽

2020 ◽

Vol V-3-2020 ◽

pp. 387-394 ◽

Cited By ~ 1

Author(s):

P. Maillard

Keyword(s):

Time Series ◽

Water Level ◽

Cross Section ◽

Cross Sections ◽

Discharge Data ◽

River Bank ◽

Manual Intervention ◽

Optical Images ◽

Level Data ◽

Water Level Data

Abstract. A method is presented to produce river cross section profiles from a time series of Sentinel-1 images paired with water level data. Four programs are presented that generate river width data and cross section profiles from SAR or optical images. The programs generate a river bank and island width database with minimum manual intervention. Water level data from in situ stations are interpolated to match the width data and create elevation points from which the cross section profiles are produced. The method is fully described and tested on the São Francisco River in Brazil. The width data are plotted against discharge data to compare their progression. Over 1700 cross sections were produced and classified by their shape. Potential and limitations are presented.

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Monitoring Water Levels in Fresh Water Tank Using The Concept of IoT (Internet of Think)

PROSIDING POLITEKNIK ILMU PELAYARAN MAKASSAR ◽

10.48192/prc.v1i4.333 ◽

2021 ◽

Vol 1 (4) ◽

pp. 120-126

Author(s):

Edi Kurniawan ◽

Heri Sularno ◽

I'ie Suwondo ◽

Anak Agung Istri S.W

Keyword(s):

Water Level ◽

Fresh Water ◽

Water Levels ◽

The Internet ◽

Water Tank ◽

Level Data ◽

Water Level Data ◽

The Right ◽

User Friendly ◽

Height Data

Fresh water generator is one of the most important auxiliary aircraft on ships to produce fresh water. The efficient use of fresh water can extend the life of the fresh water generator and save electricity usage. Efficient use of fresh water can be done by remotely monitoring the level of fresh water in the tank in real time.The system for knowing the water level in real time is built with an ultrasonic sensor to transmit data to the Wemos in the form of height data. Wemos converts freshwater level data into the volume of water in the tank. The volume and water level data is then displayed on the LCD and the Wemos sends data on the volume of fresh water to the internet in the form of a website with a design that is easy to understand (user friendly) and the website can be accessed anywhere. It can be seen that the system can work properly because the highest error reading is only 5%, namely in 4 liters with a tilt position og 20 right . Meanwhile, the biggest difference between sendor readings and real when testing 5 liters with a slope of 30 to the right is 0.23 liters. The best average result occur when testing flat conutions.

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