Improved Representation of Flow and Water Quality in a North-Eastern German Lowland Catchment by Combining Low-Frequency Monitored Data with Hydrological Modelling
Achievements of good chemical and ecological status of groundwater (GW) and surface water (SW) bodies are currently challenged mainly due to poor identification and quantification of pollution sources. A high spatio-temporal hydrological and water quality monitoring of SW and GW bodies is the basis...
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description | Achievements of good chemical and ecological status of groundwater (GW) and surface water (SW) bodies are currently challenged mainly due to poor identification and quantification of pollution sources. A high spatio-temporal hydrological and water quality monitoring of SW and GW bodies is the basis for a reliable assessment of water quality in a catchment. However, high spatio-temporal hydrological and water quality monitoring is expensive, laborious, and hard to accomplish. This study uses spatio-temporally low resolved monitored water quality and river discharge data in combination with integrated hydrological modelling to estimate the governing pollution pathways and identify potential transformation processes. A key task at the regarded lowland river Augraben is (i) to understand the SW and GW interactions by estimating representative GW zones (GWZ) based on simulated GW flow directions and GW quality monitoring stations, (ii) to quantify GW flows to the Augraben River and its tributaries, and (iii) to simulate SW discharges at ungauged locations. Based on simulated GW flows and SW discharges, NO3-N, NO2-N, NH4-N, and P loads are calculated from each defined SW tributary outlet (SWTO) and respective GWZ by using low-frequency monitored SW and GW quality data. The magnitudes of NO3-N transformations and plant uptake rates are accessed by estimating a NO3-N balance at the catchment outlet. Based on sensitivity analysis results, Manning’s roughness, saturated hydraulic conductivity, and boundary conditions are mainly used for calibration. The water balance results show that 60–65% of total precipitation is lost via evapotranspiration (ET). A total of 85–95% of SW discharge in Augraben River and its tributaries is fed by GW via base flow. SW NO3-N loads are mainly dependent on GW flows and GW quality. Estimated SW NO3-N loads at SWTO_Ivenack and SWTO_Lindenberg show that these tributaries are heavily polluted and contribute mainly to the total SW NO3-N loads at Augraben River catchment outlet (SWO_Gehmkow). SWTO_Hasseldorf contributes least to the total SW NO3-N loads. SW quality of Augraben River catchment lies, on average, in the category of heavily polluted river with a maximum NO3-N load of 650 kg/d in 2017. Estimated GW loads in GWZ_Ivenack have contributed approximately 96% of the total GW loads and require maximum water quality improvement efforts to reduce high NO3-N levels. By focusing on the impacts of NO3-N reduction measures and best agricultur |
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A high spatio-temporal hydrological and water quality monitoring of SW and GW bodies is the basis for a reliable assessment of water quality in a catchment. However, high spatio-temporal hydrological and water quality monitoring is expensive, laborious, and hard to accomplish. This study uses spatio-temporally low resolved monitored water quality and river discharge data in combination with integrated hydrological modelling to estimate the governing pollution pathways and identify potential transformation processes. A key task at the regarded lowland river Augraben is (i) to understand the SW and GW interactions by estimating representative GW zones (GWZ) based on simulated GW flow directions and GW quality monitoring stations, (ii) to quantify GW flows to the Augraben River and its tributaries, and (iii) to simulate SW discharges at ungauged locations. Based on simulated GW flows and SW discharges, NO3-N, NO2-N, NH4-N, and P loads are calculated from each defined SW tributary outlet (SWTO) and respective GWZ by using low-frequency monitored SW and GW quality data. The magnitudes of NO3-N transformations and plant uptake rates are accessed by estimating a NO3-N balance at the catchment outlet. Based on sensitivity analysis results, Manning’s roughness, saturated hydraulic conductivity, and boundary conditions are mainly used for calibration. The water balance results show that 60–65% of total precipitation is lost via evapotranspiration (ET). A total of 85–95% of SW discharge in Augraben River and its tributaries is fed by GW via base flow. SW NO3-N loads are mainly dependent on GW flows and GW quality. Estimated SW NO3-N loads at SWTO_Ivenack and SWTO_Lindenberg show that these tributaries are heavily polluted and contribute mainly to the total SW NO3-N loads at Augraben River catchment outlet (SWO_Gehmkow). SWTO_Hasseldorf contributes least to the total SW NO3-N loads. SW quality of Augraben River catchment lies, on average, in the category of heavily polluted river with a maximum NO3-N load of 650 kg/d in 2017. Estimated GW loads in GWZ_Ivenack have contributed approximately 96% of the total GW loads and require maximum water quality improvement efforts to reduce high NO3-N levels. By focusing on the impacts of NO3-N reduction measures and best agricultural practices, further studies can enhance the better agricultural and water quality management in the study area.</description><identifier>ISSN: 2071-1050</identifier><identifier>EISSN: 2071-1050</identifier><identifier>DOI: 10.3390/su12124812</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Agricultural practices ; Agriculture ; Base flow ; Boundary conditions ; Calibration ; Chemical oxygen demand ; Computer simulation ; Environmental monitoring ; Evapotranspiration ; Fertilizers ; Flow velocity ; Groundwater ; Hydrologic data ; Hydrology ; Land use ; Loads (forces) ; Modelling ; Nitrogen ; Nitrogen dioxide ; Outlets ; Pollution monitoring ; Pollution sources ; Precipitation ; Quality assessment ; Quality control ; Quality management ; River catchments ; River discharge ; River flow ; Rivers ; Sensitivity analysis ; Surface water ; Surface-groundwater relations ; Sustainability ; Topography ; Tributaries ; Water balance ; Water discharge ; Water management ; Water pollution ; Water quality ; Water quality assessments ; Water quality management</subject><ispartof>Sustainability, 2020-06, Vol.12 (12), p.4812</ispartof><rights>2020. This work is licensed under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c295t-f5e0fa32f475291a1b9031fd72ade79c814b5bbc352ffb5843a5be005f9a856d3</citedby><cites>FETCH-LOGICAL-c295t-f5e0fa32f475291a1b9031fd72ade79c814b5bbc352ffb5843a5be005f9a856d3</cites><orcidid>0000-0002-3984-5786 ; 0000-0003-0777-6971 ; 0000-0001-5830-817X ; 0000-0001-9442-5664</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27923,27924</link.rule.ids></links><search><creatorcontrib>Waseem, Muhammad</creatorcontrib><creatorcontrib>Schilling, Jannik</creatorcontrib><creatorcontrib>Kachholz, Frauke</creatorcontrib><creatorcontrib>Tränckner, Jens</creatorcontrib><title>Improved Representation of Flow and Water Quality in a North-Eastern German Lowland Catchment by Combining Low-Frequency Monitored Data with Hydrological Modelling</title><title>Sustainability</title><description>Achievements of good chemical and ecological status of groundwater (GW) and surface water (SW) bodies are currently challenged mainly due to poor identification and quantification of pollution sources. A high spatio-temporal hydrological and water quality monitoring of SW and GW bodies is the basis for a reliable assessment of water quality in a catchment. However, high spatio-temporal hydrological and water quality monitoring is expensive, laborious, and hard to accomplish. This study uses spatio-temporally low resolved monitored water quality and river discharge data in combination with integrated hydrological modelling to estimate the governing pollution pathways and identify potential transformation processes. A key task at the regarded lowland river Augraben is (i) to understand the SW and GW interactions by estimating representative GW zones (GWZ) based on simulated GW flow directions and GW quality monitoring stations, (ii) to quantify GW flows to the Augraben River and its tributaries, and (iii) to simulate SW discharges at ungauged locations. Based on simulated GW flows and SW discharges, NO3-N, NO2-N, NH4-N, and P loads are calculated from each defined SW tributary outlet (SWTO) and respective GWZ by using low-frequency monitored SW and GW quality data. The magnitudes of NO3-N transformations and plant uptake rates are accessed by estimating a NO3-N balance at the catchment outlet. Based on sensitivity analysis results, Manning’s roughness, saturated hydraulic conductivity, and boundary conditions are mainly used for calibration. The water balance results show that 60–65% of total precipitation is lost via evapotranspiration (ET). A total of 85–95% of SW discharge in Augraben River and its tributaries is fed by GW via base flow. SW NO3-N loads are mainly dependent on GW flows and GW quality. Estimated SW NO3-N loads at SWTO_Ivenack and SWTO_Lindenberg show that these tributaries are heavily polluted and contribute mainly to the total SW NO3-N loads at Augraben River catchment outlet (SWO_Gehmkow). SWTO_Hasseldorf contributes least to the total SW NO3-N loads. SW quality of Augraben River catchment lies, on average, in the category of heavily polluted river with a maximum NO3-N load of 650 kg/d in 2017. Estimated GW loads in GWZ_Ivenack have contributed approximately 96% of the total GW loads and require maximum water quality improvement efforts to reduce high NO3-N levels. By focusing on the impacts of NO3-N reduction measures and best agricultural practices, further studies can enhance the better agricultural and water quality management in the study area.</description><subject>Agricultural practices</subject><subject>Agriculture</subject><subject>Base flow</subject><subject>Boundary conditions</subject><subject>Calibration</subject><subject>Chemical oxygen demand</subject><subject>Computer simulation</subject><subject>Environmental monitoring</subject><subject>Evapotranspiration</subject><subject>Fertilizers</subject><subject>Flow velocity</subject><subject>Groundwater</subject><subject>Hydrologic data</subject><subject>Hydrology</subject><subject>Land use</subject><subject>Loads (forces)</subject><subject>Modelling</subject><subject>Nitrogen</subject><subject>Nitrogen dioxide</subject><subject>Outlets</subject><subject>Pollution monitoring</subject><subject>Pollution sources</subject><subject>Precipitation</subject><subject>Quality assessment</subject><subject>Quality control</subject><subject>Quality management</subject><subject>River catchments</subject><subject>River discharge</subject><subject>River flow</subject><subject>Rivers</subject><subject>Sensitivity analysis</subject><subject>Surface water</subject><subject>Surface-groundwater relations</subject><subject>Sustainability</subject><subject>Topography</subject><subject>Tributaries</subject><subject>Water balance</subject><subject>Water discharge</subject><subject>Water management</subject><subject>Water pollution</subject><subject>Water quality</subject><subject>Water quality assessments</subject><subject>Water quality management</subject><issn>2071-1050</issn><issn>2071-1050</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNpNUdtKxDAQLaLgovviFwR8E6q5NNv2UereYFUUxccybZPdLG2yJqlLv8cfNcsKOi8zcM6cM8yJoiuCbxnL8Z3rCSU0yQg9iUYUpyQmmOPTf_N5NHZui0MxRnIyGUXfy25nzZdo0KvYWeGE9uCV0chINGvNHoFu0Ad4YdFLD63yA1IaAXoy1m_iKbiAaDQXtgONVmbfHvgF-HrTBSlUDagwXaW00usDHM-s-OyFrgf0aLTyxgbnB_CA9spv0GJorGnNWtXQBkIj2jYsXkZnElonxr_9InqfTd-KRbx6ni-L-1Vc05z7WHKBJTAqk5TTnACpcsyIbFIKjUjzOiNJxauqZpxKWfEsYcArgTGXOWR80rCL6PqoGz4SjnS-3Jre6mBZ0oSwLElZMgmsmyOrtsY5K2S5s6oDO5QEl4ccyr8c2A9nuX0X</recordid><startdate>20200601</startdate><enddate>20200601</enddate><creator>Waseem, Muhammad</creator><creator>Schilling, Jannik</creator><creator>Kachholz, Frauke</creator><creator>Tränckner, Jens</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>4U-</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><orcidid>https://orcid.org/0000-0002-3984-5786</orcidid><orcidid>https://orcid.org/0000-0003-0777-6971</orcidid><orcidid>https://orcid.org/0000-0001-5830-817X</orcidid><orcidid>https://orcid.org/0000-0001-9442-5664</orcidid></search><sort><creationdate>20200601</creationdate><title>Improved Representation of Flow and Water Quality in a North-Eastern German Lowland Catchment by Combining Low-Frequency Monitored Data with Hydrological Modelling</title><author>Waseem, Muhammad ; 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A high spatio-temporal hydrological and water quality monitoring of SW and GW bodies is the basis for a reliable assessment of water quality in a catchment. However, high spatio-temporal hydrological and water quality monitoring is expensive, laborious, and hard to accomplish. This study uses spatio-temporally low resolved monitored water quality and river discharge data in combination with integrated hydrological modelling to estimate the governing pollution pathways and identify potential transformation processes. A key task at the regarded lowland river Augraben is (i) to understand the SW and GW interactions by estimating representative GW zones (GWZ) based on simulated GW flow directions and GW quality monitoring stations, (ii) to quantify GW flows to the Augraben River and its tributaries, and (iii) to simulate SW discharges at ungauged locations. Based on simulated GW flows and SW discharges, NO3-N, NO2-N, NH4-N, and P loads are calculated from each defined SW tributary outlet (SWTO) and respective GWZ by using low-frequency monitored SW and GW quality data. The magnitudes of NO3-N transformations and plant uptake rates are accessed by estimating a NO3-N balance at the catchment outlet. Based on sensitivity analysis results, Manning’s roughness, saturated hydraulic conductivity, and boundary conditions are mainly used for calibration. The water balance results show that 60–65% of total precipitation is lost via evapotranspiration (ET). A total of 85–95% of SW discharge in Augraben River and its tributaries is fed by GW via base flow. SW NO3-N loads are mainly dependent on GW flows and GW quality. Estimated SW NO3-N loads at SWTO_Ivenack and SWTO_Lindenberg show that these tributaries are heavily polluted and contribute mainly to the total SW NO3-N loads at Augraben River catchment outlet (SWO_Gehmkow). SWTO_Hasseldorf contributes least to the total SW NO3-N loads. SW quality of Augraben River catchment lies, on average, in the category of heavily polluted river with a maximum NO3-N load of 650 kg/d in 2017. Estimated GW loads in GWZ_Ivenack have contributed approximately 96% of the total GW loads and require maximum water quality improvement efforts to reduce high NO3-N levels. By focusing on the impacts of NO3-N reduction measures and best agricultural practices, further studies can enhance the better agricultural and water quality management in the study area.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/su12124812</doi><orcidid>https://orcid.org/0000-0002-3984-5786</orcidid><orcidid>https://orcid.org/0000-0003-0777-6971</orcidid><orcidid>https://orcid.org/0000-0001-5830-817X</orcidid><orcidid>https://orcid.org/0000-0001-9442-5664</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Agricultural practices Agriculture Base flow Boundary conditions Calibration Chemical oxygen demand Computer simulation Environmental monitoring Evapotranspiration Fertilizers Flow velocity Groundwater Hydrologic data Hydrology Land use Loads (forces) Modelling Nitrogen Nitrogen dioxide Outlets Pollution monitoring Pollution sources Precipitation Quality assessment Quality control Quality management River catchments River discharge River flow Rivers Sensitivity analysis Surface water Surface-groundwater relations Sustainability Topography Tributaries Water balance Water discharge Water management Water pollution Water quality Water quality assessments Water quality management |
title | Improved Representation of Flow and Water Quality in a North-Eastern German Lowland Catchment by Combining Low-Frequency Monitored Data with Hydrological Modelling |
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