{"title":"识别和评估基于 MOR 的 CMIP6 模型的新方法,用于无测站流域的水文分析","authors":"Dibyandu Roy, Anirban Dhar, Venkappayya R. Desai","doi":"10.1002/hyp.15293","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>The identification of the onset and retreat dates of the monsoon season is a crucial and intricate phenomenon, given its annual spatiotemporal variability. The monsoon season contributes significantly to rainfall, replenishing water sources and hydrological systems but causes hydrological extremes, especially for the high-altitude watersheds in Southeast Asia. Global Circulation Model (GCM)-Coupled Model Intercomparison Project Phase 6 (CMIP6)-based rainfall and temperature data are helpful for adequately representing present and future climate scenarios. However, the usability of uncorrected GCM-CMIP6 datasets needs to be assessed regionally. This study focuses on identifying the best-suited GCM-CMIP6 based on the monsoon onset (<i>M</i><sub>O</sub>) and retreat (<i>M</i><sub><i>R</i></sub>) dates along with other climatological temporal parameters. A numerical definition for <i>M</i><sub>O</sub> and <i>M</i><sub>R</sub> has been formulated to find the best-suited GCM-CMIP6 (i.e., CMCC-ESM2). In this context, runoff simulation is carried out using the meteorological inputs of the monsoon onset-retreat (MOR)-based best-suited GCM to evaluate its usability. A multi-model simulation approach has been carried out for runoff estimation based on observed datasets to find a better-suited hydrological model. The proposed overall methodology is tested in a hydrological extreme-prone ungauged watershed (i.e., Ranikhola). CMCC-ESM2 and SSP2-4.5 has been identified as best-suited SSP based on statistical evolution (<i>R</i><sup>2</sup> [0.693], NSE [0.662] and RSR [0.581]) for future daily runoff prediction. Future hydrological analysis shows that the average monsoon peak runoff magnitude will increase from the calibrated period (2015–2020) by 18.01% in the coming years (2021–2049).</p>\n </div>","PeriodicalId":13189,"journal":{"name":"Hydrological Processes","volume":"38 10","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Novel Approach for Identifying and Assessing MOR-Based CMIP6 Model for Hydrological Analysis in an Ungauged Watershed\",\"authors\":\"Dibyandu Roy, Anirban Dhar, Venkappayya R. Desai\",\"doi\":\"10.1002/hyp.15293\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>The identification of the onset and retreat dates of the monsoon season is a crucial and intricate phenomenon, given its annual spatiotemporal variability. The monsoon season contributes significantly to rainfall, replenishing water sources and hydrological systems but causes hydrological extremes, especially for the high-altitude watersheds in Southeast Asia. Global Circulation Model (GCM)-Coupled Model Intercomparison Project Phase 6 (CMIP6)-based rainfall and temperature data are helpful for adequately representing present and future climate scenarios. However, the usability of uncorrected GCM-CMIP6 datasets needs to be assessed regionally. This study focuses on identifying the best-suited GCM-CMIP6 based on the monsoon onset (<i>M</i><sub>O</sub>) and retreat (<i>M</i><sub><i>R</i></sub>) dates along with other climatological temporal parameters. A numerical definition for <i>M</i><sub>O</sub> and <i>M</i><sub>R</sub> has been formulated to find the best-suited GCM-CMIP6 (i.e., CMCC-ESM2). In this context, runoff simulation is carried out using the meteorological inputs of the monsoon onset-retreat (MOR)-based best-suited GCM to evaluate its usability. A multi-model simulation approach has been carried out for runoff estimation based on observed datasets to find a better-suited hydrological model. The proposed overall methodology is tested in a hydrological extreme-prone ungauged watershed (i.e., Ranikhola). CMCC-ESM2 and SSP2-4.5 has been identified as best-suited SSP based on statistical evolution (<i>R</i><sup>2</sup> [0.693], NSE [0.662] and RSR [0.581]) for future daily runoff prediction. Future hydrological analysis shows that the average monsoon peak runoff magnitude will increase from the calibrated period (2015–2020) by 18.01% in the coming years (2021–2049).</p>\\n </div>\",\"PeriodicalId\":13189,\"journal\":{\"name\":\"Hydrological Processes\",\"volume\":\"38 10\",\"pages\":\"\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2024-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Hydrological Processes\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/hyp.15293\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Environmental Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hydrological Processes","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/hyp.15293","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Environmental Science","Score":null,"Total":0}
A Novel Approach for Identifying and Assessing MOR-Based CMIP6 Model for Hydrological Analysis in an Ungauged Watershed
The identification of the onset and retreat dates of the monsoon season is a crucial and intricate phenomenon, given its annual spatiotemporal variability. The monsoon season contributes significantly to rainfall, replenishing water sources and hydrological systems but causes hydrological extremes, especially for the high-altitude watersheds in Southeast Asia. Global Circulation Model (GCM)-Coupled Model Intercomparison Project Phase 6 (CMIP6)-based rainfall and temperature data are helpful for adequately representing present and future climate scenarios. However, the usability of uncorrected GCM-CMIP6 datasets needs to be assessed regionally. This study focuses on identifying the best-suited GCM-CMIP6 based on the monsoon onset (MO) and retreat (MR) dates along with other climatological temporal parameters. A numerical definition for MO and MR has been formulated to find the best-suited GCM-CMIP6 (i.e., CMCC-ESM2). In this context, runoff simulation is carried out using the meteorological inputs of the monsoon onset-retreat (MOR)-based best-suited GCM to evaluate its usability. A multi-model simulation approach has been carried out for runoff estimation based on observed datasets to find a better-suited hydrological model. The proposed overall methodology is tested in a hydrological extreme-prone ungauged watershed (i.e., Ranikhola). CMCC-ESM2 and SSP2-4.5 has been identified as best-suited SSP based on statistical evolution (R2 [0.693], NSE [0.662] and RSR [0.581]) for future daily runoff prediction. Future hydrological analysis shows that the average monsoon peak runoff magnitude will increase from the calibrated period (2015–2020) by 18.01% in the coming years (2021–2049).
期刊介绍:
Hydrological Processes is an international journal that publishes original scientific papers advancing understanding of the mechanisms underlying the movement and storage of water in the environment, and the interaction of water with geological, biogeochemical, atmospheric and ecological systems. Not all papers related to water resources are appropriate for submission to this journal; rather we seek papers that clearly articulate the role(s) of hydrological processes.