Detection of spatial and temporal precipitation patterns using remotely sensed data in the Paranapanema River Basin, Brazil from 2000 to 2021

Abstract

Abstract Precipitation is the major input of the hydrological cycle in tropical regions. Changes in the spatial and temporal patterns of precipitation should be investigated in order to provide in-time information for both water and land use planning. Climate and land use changes have been influencing modification in the water cycle, demanding adaptations and increasing the vulnerability of water-dependent systems. This study investigated spatial and temporal changes in precipitation patterns in the Paranapanema River Basin (PPRB), Brazil. The PPRB region is an important agricultural and hydroelectric power generation hub and has been suffering from water crises in recent years, and more intensely in the last 5–10 years. The analysis used remote sensing precipitations data from September 2000 to August 2021 (summing up twenty-one hydrological years) at 0.1° resolution. Exploratory Spatial and Temporal Data Analysis (ESTDA) were applied to verify spatial local autocorrelation and hot/cold spots clusters, and temporal trends, homogeneity, and change points in the time series at Hydrological Planning Unit (HPU) scale level. The significant results were discussed based on statistical tests and land use cover change data. There is a strong presence of precipitation spatial patterns in the PPRB. Also, the PPRB presented modifications in the precipitation regime over the analyzed period, with significant change points around 2015—2017. Further monitoring is recommended in order to confirm these results in the long term, however, the provided information can already be used as an award to local and regional water bodies installed in the river basin, supporting informative water management.

Keywords

• IMERG/GPM
• ESTDA
• Spatial clustering
• Trend analysis
• Change point detection