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Nagaoka University of Technology (2015)

Characterizing Soil Moisture Memory Timescale and the Xinanjiang Model Spin-up time by Basin Scale Hydro-climatic Data

Mohammad Mahfuzur Rahman

Titre : Characterizing Soil Moisture Memory Timescale and the Xinanjiang Model Spin-up time by Basin Scale Hydro-climatic Data

Auteur : Mohammad Mahfuzur Rahman

Université de soutenance : Nagaoka University of Technology

Grade : Doctor of Engineering 2015

Présentation

The persistence characteristics of soil moisture is known as soil moisture memory (SMM). Knowledge of SMM is important for both land surface and hydrological modelling exercises. SMM information can improve hydro-climatic prediction effciency as well as provides useful insight about the speed of model spin-up process. Despite these advantages, SMM studies are restricted in certain regions due to the scarcity of observed soil moisture data. To overcome this limitation, this study explains the variability of SMM with respect to the dryness of a river basin and shows a way to predict basin scale SMM timescale using annual observed precipitation and potential evapotranspiration information only. Later, the linkage between the SMM and the model spin-up time has been investigated using the Xinanjiang (XAJ) model as a case study.

The study presents the basin average SMM timescale that indicates the duration of significant autocorrelations at 95% confidence intervals. The soil moisture autocorrelations were calculated using observed precipitation, potential evapotranspiration, stream ow and soil moisture data sets (soil moisture data was simulated using the XAJ model), for 26 river basins across the USA. The SMM timescale is highly influenced by precipitation variability and exhibits strong seasonality. Dry basins tend to show the highest memory during the winter months (December to February) and lowest in late spring (May). In contrast, wet basins have the lowest memory during winter and early spring (December to April) and highest in the late summer and early autumn (July to September). The analysis suggests that SMM timescale holds an exponential relationship with the basin aridity index.

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Page publiée le 15 octobre 2016