Utilization of Global Precipitation Datasets in Data Limited Regions: A Case Study of Kilombero Valley, Tanzania

Abstract

This study explored the potential for bias correction of global precipitation datasets (GPD) to support streamflow simulation for water resource management in data limited regions. Two catchments, 580 km 2 and 2530 km 2 , in the Kilombero Valley of central Tanzania were considered as case studies to explore three GPD bias correction methods: quantile mapping (QM), daily percentages (DP) and a model based (ModB) bias correction. The GPDs considered included two satellite rainfall products, three reanalysis products and three interpolated observed data products. The rainfall-runoff model HBV was used to simulate streamflow in the two catchments using (1) observed rain gauge data; (2) the original GPDs and (3) the bias-corrected GPDs as input. Results showed that applying QM to bias correction based on limited observed data tends to aggravate streamflow simulations relative to not bias correcting GPDs. This is likely due to a potential lack of representativeness of a single rain gauge observation at the scale of a hydrological catchment for these catchments. The results also indicate that there may be potential benefits in combining streamflow and rain gauge data to bias correct GPDs during the model calibration process within a hydrological modeling framework.

Comparing Remotely-Sensed Surface Energy Balance Evapotranspiration Estimates in Heterogeneous and Data-Limited Regions: A Case Study of Tanzania’s Kilombero Valley

“…Readers are recommended to refer to Schultz [99] for more details on the opportunities and challenges of the utilization of RS in hydrological modeling. Appropriate technical skills on how to utilize secondary data from RS to calibrate or infer model parameters have enabled various researchers to improve the robustness of their respective hydrological models [88,101,102].…”

Analysis of Agricultural Drought Using Remotely Sensed Evapotranspiration in a Data-Scarce Catchment

“…Using standardized precipitation index in the east coast of Tanzania, Hassan et al [5] also found that this region has recently been experiencing more than one drought episode per year. Because TDD shows an average of 2 to 6 months, and the dry period in the Kilombero catchment is usually between June and October [21,[53][54][55], this implies that sometimes drought spells might coincide with dry periods (as shown in Figure 4d).…”

Correction: Koutsouris et al. Utilization of Global Precipitation Datasets in Data Limited Regions: A Case Study of Kilombero Valley, Tanzania. Atmosphere, 2017, 8, 246

“…The authors would like to correct the published article [1], following the detection of editorial mistakes by the main author, as explained below. Table 5 should now be considered as Table 6.…”