Modeling future hydrological responses through parameter optimization and climate change scenarios in Dirima Watershed, Ethiopia
Purpose Hydrological modeling is an important tool for estimating hydrological responses, not only for current conditions but also for future scenarios by optimizing hydrological parameters. In cases where direct measurements are difficult to obtain, modeling can be used to fill in the gaps and prov...
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description | Purpose
Hydrological modeling is an important tool for estimating hydrological responses, not only for current conditions but also for future scenarios by optimizing hydrological parameters. In cases where direct measurements are difficult to obtain, modeling can be used to fill in the gaps and provide vital information for water resources planning and management. However, it is important to note that hydrological models need to be calibrated and validated to ensure that the parameter values are optimized for the specific watershed being studied.
Materials and methods
The Xinanjiang (XAJ) model have been used to estimate the potential hydrological responses under current and future scenarios. In this study, an attempt was made to optimize the parameters for the Dirima watershed with a total area of 162 km
2
using DEoptim algorithms. In this study, the calibrated parameters were used to simulate the watersheds’ hydrological response for baseline (1996–2009) and three climate change scenarios (SSP2-4.5, SSP3-7.0, and SSP5-8.5) from a CMIP6 multimodel ensemble (2015–2100).
Results and discussion
The study shows that the baseline period of performance measure values is RMSE = 12, NSE = 0.76, PBIAS = 10.5% and R
2
= 0.78, and RMSE = 3.65, NSE = 0.85, PBIAS = 9.9%, and R
2
= 0.85 indicate that the model has performed well in simulating the streamflow in both the calibration and validation periods, respectively. Lower RMSE, higher NSE, and lower PBIAS indicate better model performance and suggest that the model has performed well in all these aspects. In the future (2015–2100) the average Tmax 1.59 , 1.93 and 2.48 °C, and Tmin will raise by 1.83 , 2.33 and 2.85 °C under SSP2-4.5, SSP3-7.0, and SSP5-8.5, respectively. Additionally, the mean annual future hydrological responses in the upper soil layer, including evaporation, soil moisture, and runoff will be 1.72, 1.71, and 1.79 mm, 0.63, 0.62, 0.64 mm, and 1.07, 0.97, and 1.18 mm under SSP2-4.5, SSP3-7.0, and SSP5-8.5. The future projections show an increase in average maximum and minimum temperatures under different SSP scenarios.
Conclusion
The calibrated parameters of the XAJ model were critical to assess the future hydrological responses of the Dirima watershed under the three SSP scenarios. The precipitation and streamflow values are consistently lower than those of ET and temperature across all SSP scenarios. This indicates that future water availability is likely to be under pressure and calls for appro |
doi_str_mv | 10.1007/s40808-023-01817-z |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2918846997</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2918846997</sourcerecordid><originalsourceid>FETCH-LOGICAL-c319t-96acc87074a969ee5a9b3a4767a5b2c8c331013a48d543bcd76e3c7d1d6fcaee3</originalsourceid><addsrcrecordid>eNp9kD1PwzAQhiMEElXpH2CyxErAjlPbGVEpHxKIBcRouc6lcZXawXaGduKn4xIEG9Od7t73Pp4sOyf4imDMr0OJBRY5LmiOiSA83x9lk4IymrOCkOPfHNPTbBbCBmNMWMFYVU2yz2dXQ2fsGjVDHDygdld717m10apDHkLvbICAYuvdsG5Rr7zaQgSPXB_N1uxVNM4iZWukO7NVEZBulV0DChqs8sYFZCy6NT410Xvq-9BCfYmWsTWuN-osO2lUF2D2E6fZ293ydfGQP73cPy5unnJNSRXziimtBce8VBWrAOaqWlFVcsbVfFVooSklmKSKqOclXemaM6Ca16RmjVYAdJpdjHN77z4GCFFu3OBtWimLighRJhw8qYpRpb0LwUMj-8PhficJlgfYcoQtE2z5DVvuk4mOppDE6XX_N_of1xeSjYYA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2918846997</pqid></control><display><type>article</type><title>Modeling future hydrological responses through parameter optimization and climate change scenarios in Dirima Watershed, Ethiopia</title><source>SpringerNature Journals</source><creator>Atanaw, Simir B. ; Zimale, Fasikaw A. ; Ayenew, Tenalem ; Ayele, Gebiaw T.</creator><creatorcontrib>Atanaw, Simir B. ; Zimale, Fasikaw A. ; Ayenew, Tenalem ; Ayele, Gebiaw T.</creatorcontrib><description>Purpose
Hydrological modeling is an important tool for estimating hydrological responses, not only for current conditions but also for future scenarios by optimizing hydrological parameters. In cases where direct measurements are difficult to obtain, modeling can be used to fill in the gaps and provide vital information for water resources planning and management. However, it is important to note that hydrological models need to be calibrated and validated to ensure that the parameter values are optimized for the specific watershed being studied.
Materials and methods
The Xinanjiang (XAJ) model have been used to estimate the potential hydrological responses under current and future scenarios. In this study, an attempt was made to optimize the parameters for the Dirima watershed with a total area of 162 km
2
using DEoptim algorithms. In this study, the calibrated parameters were used to simulate the watersheds’ hydrological response for baseline (1996–2009) and three climate change scenarios (SSP2-4.5, SSP3-7.0, and SSP5-8.5) from a CMIP6 multimodel ensemble (2015–2100).
Results and discussion
The study shows that the baseline period of performance measure values is RMSE = 12, NSE = 0.76, PBIAS = 10.5% and R
2
= 0.78, and RMSE = 3.65, NSE = 0.85, PBIAS = 9.9%, and R
2
= 0.85 indicate that the model has performed well in simulating the streamflow in both the calibration and validation periods, respectively. Lower RMSE, higher NSE, and lower PBIAS indicate better model performance and suggest that the model has performed well in all these aspects. In the future (2015–2100) the average Tmax 1.59 , 1.93 and 2.48 °C, and Tmin will raise by 1.83 , 2.33 and 2.85 °C under SSP2-4.5, SSP3-7.0, and SSP5-8.5, respectively. Additionally, the mean annual future hydrological responses in the upper soil layer, including evaporation, soil moisture, and runoff will be 1.72, 1.71, and 1.79 mm, 0.63, 0.62, 0.64 mm, and 1.07, 0.97, and 1.18 mm under SSP2-4.5, SSP3-7.0, and SSP5-8.5. The future projections show an increase in average maximum and minimum temperatures under different SSP scenarios.
Conclusion
The calibrated parameters of the XAJ model were critical to assess the future hydrological responses of the Dirima watershed under the three SSP scenarios. The precipitation and streamflow values are consistently lower than those of ET and temperature across all SSP scenarios. This indicates that future water availability is likely to be under pressure and calls for appropriate strategic measures to create a more resilient water resource system.</description><identifier>ISSN: 2363-6203</identifier><identifier>EISSN: 2363-6211</identifier><identifier>DOI: 10.1007/s40808-023-01817-z</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Algorithms ; Calibration ; Chemistry and Earth Sciences ; Climate change ; Computer Science ; Earth and Environmental Science ; Earth Sciences ; Earth System Sciences ; Ecosystems ; Environment ; Evaporation ; Hydrologic models ; Hydrology ; Math. Appl. in Environmental Science ; Mathematical Applications in the Physical Sciences ; Modelling ; Optimization ; Original Article ; Parameters ; Physics ; Runoff ; Soil layers ; Soil moisture ; Statistics for Engineering ; Stream discharge ; Stream flow ; Water availability ; Water resources ; Watersheds</subject><ispartof>Modeling earth systems and environment, 2024-02, Vol.10 (1), p.1117-1135</ispartof><rights>The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-96acc87074a969ee5a9b3a4767a5b2c8c331013a48d543bcd76e3c7d1d6fcaee3</citedby><cites>FETCH-LOGICAL-c319t-96acc87074a969ee5a9b3a4767a5b2c8c331013a48d543bcd76e3c7d1d6fcaee3</cites><orcidid>0000-0002-0451-7803</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s40808-023-01817-z$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s40808-023-01817-z$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>315,782,786,27931,27932,41495,42564,51326</link.rule.ids></links><search><creatorcontrib>Atanaw, Simir B.</creatorcontrib><creatorcontrib>Zimale, Fasikaw A.</creatorcontrib><creatorcontrib>Ayenew, Tenalem</creatorcontrib><creatorcontrib>Ayele, Gebiaw T.</creatorcontrib><title>Modeling future hydrological responses through parameter optimization and climate change scenarios in Dirima Watershed, Ethiopia</title><title>Modeling earth systems and environment</title><addtitle>Model. Earth Syst. Environ</addtitle><description>Purpose
Hydrological modeling is an important tool for estimating hydrological responses, not only for current conditions but also for future scenarios by optimizing hydrological parameters. In cases where direct measurements are difficult to obtain, modeling can be used to fill in the gaps and provide vital information for water resources planning and management. However, it is important to note that hydrological models need to be calibrated and validated to ensure that the parameter values are optimized for the specific watershed being studied.
Materials and methods
The Xinanjiang (XAJ) model have been used to estimate the potential hydrological responses under current and future scenarios. In this study, an attempt was made to optimize the parameters for the Dirima watershed with a total area of 162 km
2
using DEoptim algorithms. In this study, the calibrated parameters were used to simulate the watersheds’ hydrological response for baseline (1996–2009) and three climate change scenarios (SSP2-4.5, SSP3-7.0, and SSP5-8.5) from a CMIP6 multimodel ensemble (2015–2100).
Results and discussion
The study shows that the baseline period of performance measure values is RMSE = 12, NSE = 0.76, PBIAS = 10.5% and R
2
= 0.78, and RMSE = 3.65, NSE = 0.85, PBIAS = 9.9%, and R
2
= 0.85 indicate that the model has performed well in simulating the streamflow in both the calibration and validation periods, respectively. Lower RMSE, higher NSE, and lower PBIAS indicate better model performance and suggest that the model has performed well in all these aspects. In the future (2015–2100) the average Tmax 1.59 , 1.93 and 2.48 °C, and Tmin will raise by 1.83 , 2.33 and 2.85 °C under SSP2-4.5, SSP3-7.0, and SSP5-8.5, respectively. Additionally, the mean annual future hydrological responses in the upper soil layer, including evaporation, soil moisture, and runoff will be 1.72, 1.71, and 1.79 mm, 0.63, 0.62, 0.64 mm, and 1.07, 0.97, and 1.18 mm under SSP2-4.5, SSP3-7.0, and SSP5-8.5. The future projections show an increase in average maximum and minimum temperatures under different SSP scenarios.
Conclusion
The calibrated parameters of the XAJ model were critical to assess the future hydrological responses of the Dirima watershed under the three SSP scenarios. The precipitation and streamflow values are consistently lower than those of ET and temperature across all SSP scenarios. This indicates that future water availability is likely to be under pressure and calls for appropriate strategic measures to create a more resilient water resource system.</description><subject>Algorithms</subject><subject>Calibration</subject><subject>Chemistry and Earth Sciences</subject><subject>Climate change</subject><subject>Computer Science</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Earth System Sciences</subject><subject>Ecosystems</subject><subject>Environment</subject><subject>Evaporation</subject><subject>Hydrologic models</subject><subject>Hydrology</subject><subject>Math. Appl. in Environmental Science</subject><subject>Mathematical Applications in the Physical Sciences</subject><subject>Modelling</subject><subject>Optimization</subject><subject>Original Article</subject><subject>Parameters</subject><subject>Physics</subject><subject>Runoff</subject><subject>Soil layers</subject><subject>Soil moisture</subject><subject>Statistics for Engineering</subject><subject>Stream discharge</subject><subject>Stream flow</subject><subject>Water availability</subject><subject>Water resources</subject><subject>Watersheds</subject><issn>2363-6203</issn><issn>2363-6211</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp9kD1PwzAQhiMEElXpH2CyxErAjlPbGVEpHxKIBcRouc6lcZXawXaGduKn4xIEG9Od7t73Pp4sOyf4imDMr0OJBRY5LmiOiSA83x9lk4IymrOCkOPfHNPTbBbCBmNMWMFYVU2yz2dXQ2fsGjVDHDygdld717m10apDHkLvbICAYuvdsG5Rr7zaQgSPXB_N1uxVNM4iZWukO7NVEZBulV0DChqs8sYFZCy6NT410Xvq-9BCfYmWsTWuN-osO2lUF2D2E6fZ293ydfGQP73cPy5unnJNSRXziimtBce8VBWrAOaqWlFVcsbVfFVooSklmKSKqOclXemaM6Ca16RmjVYAdJpdjHN77z4GCFFu3OBtWimLighRJhw8qYpRpb0LwUMj-8PhficJlgfYcoQtE2z5DVvuk4mOppDE6XX_N_of1xeSjYYA</recordid><startdate>20240201</startdate><enddate>20240201</enddate><creator>Atanaw, Simir B.</creator><creator>Zimale, Fasikaw A.</creator><creator>Ayenew, Tenalem</creator><creator>Ayele, Gebiaw T.</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TN</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>L.G</scope><orcidid>https://orcid.org/0000-0002-0451-7803</orcidid></search><sort><creationdate>20240201</creationdate><title>Modeling future hydrological responses through parameter optimization and climate change scenarios in Dirima Watershed, Ethiopia</title><author>Atanaw, Simir B. ; Zimale, Fasikaw A. ; Ayenew, Tenalem ; Ayele, Gebiaw T.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c319t-96acc87074a969ee5a9b3a4767a5b2c8c331013a48d543bcd76e3c7d1d6fcaee3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Algorithms</topic><topic>Calibration</topic><topic>Chemistry and Earth Sciences</topic><topic>Climate change</topic><topic>Computer Science</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Earth System Sciences</topic><topic>Ecosystems</topic><topic>Environment</topic><topic>Evaporation</topic><topic>Hydrologic models</topic><topic>Hydrology</topic><topic>Math. Appl. in Environmental Science</topic><topic>Mathematical Applications in the Physical Sciences</topic><topic>Modelling</topic><topic>Optimization</topic><topic>Original Article</topic><topic>Parameters</topic><topic>Physics</topic><topic>Runoff</topic><topic>Soil layers</topic><topic>Soil moisture</topic><topic>Statistics for Engineering</topic><topic>Stream discharge</topic><topic>Stream flow</topic><topic>Water availability</topic><topic>Water resources</topic><topic>Watersheds</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Atanaw, Simir B.</creatorcontrib><creatorcontrib>Zimale, Fasikaw A.</creatorcontrib><creatorcontrib>Ayenew, Tenalem</creatorcontrib><creatorcontrib>Ayele, Gebiaw T.</creatorcontrib><collection>CrossRef</collection><collection>Oceanic Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><jtitle>Modeling earth systems and environment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Atanaw, Simir B.</au><au>Zimale, Fasikaw A.</au><au>Ayenew, Tenalem</au><au>Ayele, Gebiaw T.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Modeling future hydrological responses through parameter optimization and climate change scenarios in Dirima Watershed, Ethiopia</atitle><jtitle>Modeling earth systems and environment</jtitle><stitle>Model. Earth Syst. Environ</stitle><date>2024-02-01</date><risdate>2024</risdate><volume>10</volume><issue>1</issue><spage>1117</spage><epage>1135</epage><pages>1117-1135</pages><issn>2363-6203</issn><eissn>2363-6211</eissn><abstract>Purpose
Hydrological modeling is an important tool for estimating hydrological responses, not only for current conditions but also for future scenarios by optimizing hydrological parameters. In cases where direct measurements are difficult to obtain, modeling can be used to fill in the gaps and provide vital information for water resources planning and management. However, it is important to note that hydrological models need to be calibrated and validated to ensure that the parameter values are optimized for the specific watershed being studied.
Materials and methods
The Xinanjiang (XAJ) model have been used to estimate the potential hydrological responses under current and future scenarios. In this study, an attempt was made to optimize the parameters for the Dirima watershed with a total area of 162 km
2
using DEoptim algorithms. In this study, the calibrated parameters were used to simulate the watersheds’ hydrological response for baseline (1996–2009) and three climate change scenarios (SSP2-4.5, SSP3-7.0, and SSP5-8.5) from a CMIP6 multimodel ensemble (2015–2100).
Results and discussion
The study shows that the baseline period of performance measure values is RMSE = 12, NSE = 0.76, PBIAS = 10.5% and R
2
= 0.78, and RMSE = 3.65, NSE = 0.85, PBIAS = 9.9%, and R
2
= 0.85 indicate that the model has performed well in simulating the streamflow in both the calibration and validation periods, respectively. Lower RMSE, higher NSE, and lower PBIAS indicate better model performance and suggest that the model has performed well in all these aspects. In the future (2015–2100) the average Tmax 1.59 , 1.93 and 2.48 °C, and Tmin will raise by 1.83 , 2.33 and 2.85 °C under SSP2-4.5, SSP3-7.0, and SSP5-8.5, respectively. Additionally, the mean annual future hydrological responses in the upper soil layer, including evaporation, soil moisture, and runoff will be 1.72, 1.71, and 1.79 mm, 0.63, 0.62, 0.64 mm, and 1.07, 0.97, and 1.18 mm under SSP2-4.5, SSP3-7.0, and SSP5-8.5. The future projections show an increase in average maximum and minimum temperatures under different SSP scenarios.
Conclusion
The calibrated parameters of the XAJ model were critical to assess the future hydrological responses of the Dirima watershed under the three SSP scenarios. The precipitation and streamflow values are consistently lower than those of ET and temperature across all SSP scenarios. This indicates that future water availability is likely to be under pressure and calls for appropriate strategic measures to create a more resilient water resource system.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1007/s40808-023-01817-z</doi><tpages>19</tpages><orcidid>https://orcid.org/0000-0002-0451-7803</orcidid></addata></record> |
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subjects | Algorithms Calibration Chemistry and Earth Sciences Climate change Computer Science Earth and Environmental Science Earth Sciences Earth System Sciences Ecosystems Environment Evaporation Hydrologic models Hydrology Math. Appl. in Environmental Science Mathematical Applications in the Physical Sciences Modelling Optimization Original Article Parameters Physics Runoff Soil layers Soil moisture Statistics for Engineering Stream discharge Stream flow Water availability Water resources Watersheds |
title | Modeling future hydrological responses through parameter optimization and climate change scenarios in Dirima Watershed, Ethiopia |
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