WATcycle: Water Analysis Tool for the terrestrial water cycle and water budget

The complexity, uncertainty, and heterogeneity implicit in multisource data and the dilemma in selecting the objective-specific best dataset make the terrestrial water cycle and water budget analyses challenging across scales. Here, we develop a UI/UX based open-access, flexible, and user-friendly Python software, namely  WATcycle (https://github.com/ronikianji/WATcycle). It is useful for varying levels of expertise, reduces the coding overhead, and offers a range of data processing tools. The entire software has six main steps: (1) Data downloading, (2) Data pre-processing, (3) Residual error analysis of water budget components, (4) Validation of datasets with in-situ data, (5) Data plotting, and (6) water budget closure analysis. We test the developed software using a case study on the Amazon basin, which incorporates 79 datasets from various sources, including precipitation, evapotranspiration, surface runoff, TWS, canopy, soil moisture, and groundwater. The spatial plots and trend analysis results correlate with other studies, showing the decreasing trend for precipitation, surface runoff, canopy water storage anomaly, and soil moisture storage anomaly. Meanwhile, evapotranspiration, terrestrial water storage, and groundwater storage anomalies show an increasing trend. Out of these 7 hydrological variables, precipitation and terrestrial water storage anomaly trends are not significant at a 95% significance level. Water budget analysis shows a residual error of -70 to 60 mm/month, which is adjusted using the proportional redistribution water budget closure method. The results show the performance, accuracy, and capabilities of the developed software. It will play a crucial role in skillful inferences for water resource management, risk assessment, and infrastructure planning in the basins globally.