A review of the adaptability of hydrological models for drought forecasting

Zikang Xing,Juan Lv,Peng Yi,Zhicheng Su,Miaomiao Ma,Wenlong Song

doi:10.5194/piahs-383-261-2020

Abstract

Abstract. Drought intensity and frequency are increasing in recent years in multiple regions across the world due to global climate change and consequently drought forecasting research has received more and more attention. Previous studies on drought forecasting mostly focus on meteorological drought based on precipitation and temperature. However, the trend of predicting agriculture and hydrological drought, which consider soil moisture and runoff, have developed rapidly in recent years. Hydrological drought forecasting is based on the hydrological models and the model structure plays a role to improve predictions. This study scrutinized more than 50 hydrological models, including lumped models, semi-distributed models, distributed models, surface water and groundwater coupled models, to explore the adaptability of hydrological models in drought simulation and forecasting. The advantages and disadvantages of typical models, such as DTVGM, GWAVA, and HEC-HMS models were analyzed to provide valuable reference for drought forecasting model development. Future work aims at improving the hydrological models to simulate the drought processes and make better prediction.

Highlights

Drought intensity and frequency are increasing in past and recent years in multiple across the globe due to global climate change (Wilhite and Glantz, 1985)
Previous study of drought forecasting mostly focused on meteorological drought based on precipitation and temperature, while the trend prediction of agriculture and hydrological drought, which consider soil moisture and runoff, have developed rapidly in recent years (Wilhite, 2000; Wanders et al, 2019)
Most of selected lumped models simulate evaporation calculation except CLS model, whereas the XAJ and VM show the powerful function with a three layers evaporation calculation method. 70 % of the selected models simulate soil water moisture with simple equations, while the Sacramento model divides the soil into different layers and calculate soil moisture in each layer

Summary

Introduction

Drought intensity and frequency are increasing in past and recent years in multiple across the globe due to global climate change (Wilhite and Glantz, 1985). In this context, methods to predict drought has received more and more attention (Edwards and McKee, 1997). The second method is the methods based on hydrological models and coupled atmospheric-hydrological models (Mishra and Singh, 2011). For the latter method, the model structure plays a significant role to improve predictions

Methods

Results

Discussion

Conclusion