IoT-based data and analytic hierarchy process to map groundwater recharge with stormwater

The sustainable management of groundwater resources in developing countries is often challenging due to limited measurement and monitoring infrastructure to collect data necessary for decision support. To make a contribution towards addressing these challenges, this study investigated the use of Int...

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Main Authors: Miriam Arinaitwe, John Okedi
Format: Article
Language:English
Published: IWA Publishing 2024-02-01
Series:Water Science and Technology
Subjects:
Online Access:http://wst.iwaponline.com/content/89/3/529
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author Miriam Arinaitwe
John Okedi
author_facet Miriam Arinaitwe
John Okedi
author_sort Miriam Arinaitwe
collection DOAJ
description The sustainable management of groundwater resources in developing countries is often challenging due to limited measurement and monitoring infrastructure to collect data necessary for decision support. To make a contribution towards addressing these challenges, this study investigated the use of Internet of Things (IoT) technology and low-cost sensors to collect the required groundwater-level data and develop a model to map the recharge potential with stormwater. The study focused on two stormwater ponds located in a highly urbanised area in Cape Town, South Africa. A combination of Geographic Information System and analytic hierarchy process was integrated to generate a groundwater recharge potential zone map of the study area. The IoT-based data were used to develop and calibrate a numerical groundwater model in MODFLOW. The study determined that retrofitted stormwater ponds are potential groundwater augmentation zones and can provide opportunity for stormwater recharge in urban areas. Overall, this study highlights the potential of IoT to collect hydrogeological data with low-cost sensors. Data can be collected at high temporal resolution, and the spatial scale can be increased due to availability of low-cost sensors. HIGHLIGHTS Internet of Things (IoT)-based data were leveraged to address challenges in groundwater management.; Rapid battery drain powering the IoT system was mitigated by reducing the data collection frequency and dead sleep mechanisms.; Geographic Information System–based analysis and analytic hierarchy process were employed to map the recharge potential in a highly urbanised area in Cape Town.; This study demonstrated that stormwater ponds have the potential to recharge groundwater aquifers through infiltration.;
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spelling doaj.art-6a8a1dc5b6664e408b6f07c4e50301542024-02-15T16:19:24ZengIWA PublishingWater Science and Technology0273-12231996-97322024-02-0189352954710.2166/wst.2024.017017IoT-based data and analytic hierarchy process to map groundwater recharge with stormwaterMiriam Arinaitwe0John Okedi1 Department of Civil Engineering, University of Cape Town, Private Bag X3, Rondebosch, Cape Town 7700, South Africa Department of Civil Engineering, University of Cape Town, Private Bag X3, Rondebosch, Cape Town 7700, South Africa The sustainable management of groundwater resources in developing countries is often challenging due to limited measurement and monitoring infrastructure to collect data necessary for decision support. To make a contribution towards addressing these challenges, this study investigated the use of Internet of Things (IoT) technology and low-cost sensors to collect the required groundwater-level data and develop a model to map the recharge potential with stormwater. The study focused on two stormwater ponds located in a highly urbanised area in Cape Town, South Africa. A combination of Geographic Information System and analytic hierarchy process was integrated to generate a groundwater recharge potential zone map of the study area. The IoT-based data were used to develop and calibrate a numerical groundwater model in MODFLOW. The study determined that retrofitted stormwater ponds are potential groundwater augmentation zones and can provide opportunity for stormwater recharge in urban areas. Overall, this study highlights the potential of IoT to collect hydrogeological data with low-cost sensors. Data can be collected at high temporal resolution, and the spatial scale can be increased due to availability of low-cost sensors. HIGHLIGHTS Internet of Things (IoT)-based data were leveraged to address challenges in groundwater management.; Rapid battery drain powering the IoT system was mitigated by reducing the data collection frequency and dead sleep mechanisms.; Geographic Information System–based analysis and analytic hierarchy process were employed to map the recharge potential in a highly urbanised area in Cape Town.; This study demonstrated that stormwater ponds have the potential to recharge groundwater aquifers through infiltration.;http://wst.iwaponline.com/content/89/3/529analytic hierarchy processcape towngroundwater rechargeiot-based datamodflowstormwater
spellingShingle Miriam Arinaitwe
John Okedi
IoT-based data and analytic hierarchy process to map groundwater recharge with stormwater
Water Science and Technology
analytic hierarchy process
cape town
groundwater recharge
iot-based data
modflow
stormwater
title IoT-based data and analytic hierarchy process to map groundwater recharge with stormwater
title_full IoT-based data and analytic hierarchy process to map groundwater recharge with stormwater
title_fullStr IoT-based data and analytic hierarchy process to map groundwater recharge with stormwater
title_full_unstemmed IoT-based data and analytic hierarchy process to map groundwater recharge with stormwater
title_short IoT-based data and analytic hierarchy process to map groundwater recharge with stormwater
title_sort iot based data and analytic hierarchy process to map groundwater recharge with stormwater
topic analytic hierarchy process
cape town
groundwater recharge
iot-based data
modflow
stormwater
url http://wst.iwaponline.com/content/89/3/529
work_keys_str_mv AT miriamarinaitwe iotbaseddataandanalytichierarchyprocesstomapgroundwaterrechargewithstormwater
AT johnokedi iotbaseddataandanalytichierarchyprocesstomapgroundwaterrechargewithstormwater