Publications

Deliry, SI; Pekkan, E; Avdan, U (2022). GIS-Based Water Budget Estimation of the Kizilirmak River Basin using GLDAS-2.1 Noah and CLSM Models and Remote Sensing Observations. JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING, 50(7), 1191-1209.

Abstract
Satellite remote sensing products are becoming increasingly important in water resources management. Monitoring water availability and demand within a basin is a primary requirement of effective and sustainable river basin management. In this study, monthly and annual water budget components of the Kizilirmak River Basin were estimated from satellite observations and GLDAS-2.1 Noah and CLSM models for the hydrological years 2014 and 2015. Precipitation (P), evapotranspiration (ET), terrestrial water storage (TWS), and runoff (R) datasets were taken from different sources (GPM IMERG, CHIRPS, MODIS, SSEBop, GRACE, CLSM, Noah, and streamflow gauge). Since R is not directly available from remote sensing observations, it was inferred from the water balance equation as a residual. The datasets were processed, analyzed, and intercompared. The performance of satellite remote sensing in water budget estimation was evaluated, and the consistency of spatial patterns between satellite data and earth system-modeled data was analyzed. As a result of the analysis, remotely sensed P showed good consistencies; however, ET and TWS change showed large uncertainties. Inferred runoff from remote sensing and model outputs showed significant differences from the observed streamflow measurements; nevertheless, Noah demonstrated better consistency with the gauge observations. Our study revealed the strengths and limitations of satellite-based remote sensing and GLDAS-2.1 CLSM and Noah models in estimating water budget. Caution should be exercised when using remote sensing and modeled data in ungauged regions because human influence is not included in such datasets. Despite the uncertainties in GLDAS and remote sensing datasets, such data can be quite useful for evaluating seasonal and interannual changes in water components and river basin management, particularly in data-sparse regions.

DOI:
10.1007/s12524-022-01522-x

ISSN:
0974-3006