Hydrological Drought Forecasting Using Modified Surface Water Supply Index (SWSI) and Streamflow Drought Index (SDI) in Conjunction with Artificial Neural Networks (ANNs)

Abstract

Hydrological drought in upper Tana River basin adversely affects water resources. In this study, a hydrological drought was forecasted using a Surface Water Supply Index (SWSI), a Streamflow Drought Index (SDI) and an Artificial Neural Networks (ANNs). The best SWSI involved combinations of rainfall and the index values integrated into ANNs. The best forecasts with SDI entailed composite functions of rainfall, stream flow and SDI. Different ANN models for both SWSI and SDI with lead times of 1 to 24 months were tested at hydrometric stations. Results show that the forecasting ability of all the networks decreased with the increase in lead-time. The best ANNs with specific architecture performed differently based on forecasting lead-time. SWSI drought forecasts were better than those of the SDI for all lead-times. The SWSI and SDI depicted R values of 0.752 and 0.732 for station 4AB05 for one-month lead-time. The findings are useful as an effective hydrological-drought early warning for viable mitigation and preparedness approaches to minimize the negative effects of drought.

Spatial Evaluation of Droughts Using Selected Satellite-based Indices in the Upper Tana River Watershed, Kenya

“…When the mapping of dry events in the region using the Soil Water Supply Index, [51] made similar observations. Correspondingly, using the [52], also observed the same.…”

“…This gives no time for the study region to recover from the impacts of drought. The highlands showed more resilience to drought than the lowlands that seemed to be more susceptible to drought since the highlands are characterised by humid and semi-humid climate and the lowlands are categorised as semi-arid climate [51,52]. This is evident with the increasing trends of moderate to severe droughts from SPI and NDVI values in the lowlands [3].…”

Comparing surface water supply index and streamflow drought index for hydrological drought analysis in Ethiopia

“…The surface water supply index (SWSI) is one of the hydrological drought indicators which gives a wide range of drought characterization than SDI. It is applicable for basin-level drought analysis and it was developed based on PDSI algorism [ 58 , 59 ]. For this work without altering the algorism, the equation is modified to make it easy to compare with the SDI value.…”

Hydrological Drought across Peninsular Malaysia: Implication of drought index

“…For instance, the three-month drought index (SDI-3) reflects seasonal water condition, providing vital information for irrigation in agricultural sectors (Akbari et al, 2015). The six-month drought index (SDI-6) can depict drought conditions over a half-year period (Wambua, 2019). The drought index for 12 months (SDI-12) is excellent for assessing the effect of climate change on regional water supplies (Tabari et al, 2013).…”