File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1038/s41598-021-86412-x
- Scopus: eid_2-s2.0-85103393101
- PMID: 33767320
Supplementary
- Citations:
- Appears in Collections:
Article: Spatial–temporal characterization of rainfall in Pakistan during the past half-century (1961–2020)
Title | Spatial–temporal characterization of rainfall in Pakistan during the past half-century (1961–2020) |
---|---|
Authors | |
Issue Date | 2021 |
Citation | Scientific Reports, 2021, v. 11, n. 1, article no. 6935 How to Cite? |
Abstract | Spatial–temporal rainfall assessments are integral to climate/hydrological modeling, agricultural studies, and water resource planning and management. Herein, we evaluate spatial–temporal rainfall trends and patterns in Pakistan for 1961–2020 using nationwide data from 82 rainfall stations. To assess optimal spatial distribution and rainfall characterization, twenty-seven interpolation techniques from geo-statistical and deterministic categories were systematically compared, revealing that the empirical Bayesian kriging regression prediction (EBKRP) technique was best. Hence, EBKRP was used to produce and utilize the first normal annual rainfall map of Pakistan for evaluating spatial rainfall patterns. While the largest under-prediction was estimated for Hunza (− 51%), the highest and lowest rainfalls were estimated for Malam Jaba in Khyber Pakhtunkhwa province (~ 1700 mm), and Nok-kundi in Balochistan province (~ 50 mm), respectively. A gradual south-to-north increase in rainfall was spatially evident with an areal average of 455 mm, while long-term temporal rainfall evaluation showed a statistically significant (p = 0.05) downward trend for Sindh province. Additionally, downward inter-decadal regime shifts were detected for the Punjab and Sindh provinces (90% confidence). These results are expected to help inform environmental planning in Pakistan; moreover, the rainfall data produced using the optimal method has further implications in several aforementioned fields. |
Persistent Identifier | http://hdl.handle.net/10722/349549 |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ali, Ghaffar | - |
dc.contributor.author | Sajjad, Muhammad | - |
dc.contributor.author | Kanwal, Shamsa | - |
dc.contributor.author | Xiao, Tingyin | - |
dc.contributor.author | Khalid, Shoaib | - |
dc.contributor.author | Shoaib, Fariha | - |
dc.contributor.author | Gul, Hafiza Nayab | - |
dc.date.accessioned | 2024-10-17T06:59:16Z | - |
dc.date.available | 2024-10-17T06:59:16Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | Scientific Reports, 2021, v. 11, n. 1, article no. 6935 | - |
dc.identifier.uri | http://hdl.handle.net/10722/349549 | - |
dc.description.abstract | Spatial–temporal rainfall assessments are integral to climate/hydrological modeling, agricultural studies, and water resource planning and management. Herein, we evaluate spatial–temporal rainfall trends and patterns in Pakistan for 1961–2020 using nationwide data from 82 rainfall stations. To assess optimal spatial distribution and rainfall characterization, twenty-seven interpolation techniques from geo-statistical and deterministic categories were systematically compared, revealing that the empirical Bayesian kriging regression prediction (EBKRP) technique was best. Hence, EBKRP was used to produce and utilize the first normal annual rainfall map of Pakistan for evaluating spatial rainfall patterns. While the largest under-prediction was estimated for Hunza (− 51%), the highest and lowest rainfalls were estimated for Malam Jaba in Khyber Pakhtunkhwa province (~ 1700 mm), and Nok-kundi in Balochistan province (~ 50 mm), respectively. A gradual south-to-north increase in rainfall was spatially evident with an areal average of 455 mm, while long-term temporal rainfall evaluation showed a statistically significant (p = 0.05) downward trend for Sindh province. Additionally, downward inter-decadal regime shifts were detected for the Punjab and Sindh provinces (90% confidence). These results are expected to help inform environmental planning in Pakistan; moreover, the rainfall data produced using the optimal method has further implications in several aforementioned fields. | - |
dc.language | eng | - |
dc.relation.ispartof | Scientific Reports | - |
dc.title | Spatial–temporal characterization of rainfall in Pakistan during the past half-century (1961–2020) | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1038/s41598-021-86412-x | - |
dc.identifier.pmid | 33767320 | - |
dc.identifier.scopus | eid_2-s2.0-85103393101 | - |
dc.identifier.volume | 11 | - |
dc.identifier.issue | 1 | - |
dc.identifier.spage | article no. 6935 | - |
dc.identifier.epage | article no. 6935 | - |
dc.identifier.eissn | 2045-2322 | - |