Effects of antecedent soil moisture on runoff modeling in small semiarid watersheds of southeastern Arizona

Zhang, Y.; Wei, Haiyan; Nearing, M. A.

doi:10.5194/hess-15-3171-2011

Cited by 47 publications

(26 citation statements)

References 36 publications

(31 reference statements)

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“…Therefore, understanding the factors affecting the spin-up process and its behaviour is highly important for modelling communities. The 5 effect of initial conditions in hydrological models have been investigated by several researchers (Goodrich et al, 1994;Senarath et al, 2000;Castillo et al, 2003;Zehe et al, 2005;Berthet et al, 2009;Nikolopoulos et al, 2011;Zhang et al, 2011;Minet et al, 2011). However, these studies were done highlighting either an event-scale or short-term response.…”

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confidence: 99%

Seasonality of hydrological model spin-up time: a case study using the Xinanjiang model

Rahman

Kyi

2016

Preprint

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Abstract. The internal adjustment process of a hydrological model followed by an unusual initial condition is known as the model spin-up. And the time required for a complete adjustment is termed as the model spin-up time. Model results for the duration of this spin-up progression are greatly impacted by the initial conditions, and often impractical or erroneous.The speed of this adjustment process is affected by the characteristics of the input data sets and their persistence. This study discusses the variability and seasonality of hydrological model spin-up time against the aridity of the river basin using multi-

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confidence: 99%

Seasonality of hydrological model spin-up time: a case study using the Xinanjiang model

Rahman

Kyi

2016

Preprint

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“…Thus, the assessment of soil moisture and rainfall in semiarid regions is crucial to understanding the variability in these areas and to support actions to mitigate the effects of water scarcity. Various studies have been conducted evaluating different semiarid regions of the world (Small and Kurc, 2002;Aina et al, 2007;Fischer et al, 2009;Asare et al, 2011;Mupangwa et al, 2011;Pathak et al, 2011;Zhang et al, 2011;Badel et al, 2013;He et al, 2014;Barbosa et al, 2015;Paredes et al, 2015;Barbosa and Lakshmi Kumar, 2016).…”

Section: Introductionmentioning

confidence: 99%

Impact of Soil Moisture on Crop Yields over Brazilian Semiarid

Rossato

Alvalá

Marengo

et al. 2017

Front. Environ. Sci.

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The objective of this work was to investigate the relationship between soil water content and rainfall with rice, beans, cassava and corn yields in the semiarid region of Northeast Brazil. Precipitation and modeled soil water content were compared to yields recorded at the county levels in this region. The results were also integrated over the area of the nine States that lie within the officially recognized region of semiarid climate in Brazil. The influence of water balance components was quantified by calculating their correlation coefficient with yields of the different crop species over the municipalities of the region. It was found that rainfall had higher correlation to crop yields over most of the region, while soil water content had lower values of correlation. This result is consistent with the fact that average root depth is 40 cm, lower than the layer of soil used in the model used to estimate soil water content (100 cm). Plants respond better to the precipitation in the top layers of soil, while the water storage in the deep layer of soil might be important only in other temporal and spatial scales of the hydrological cycle.

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“…1). Specifically, two catchments in central Italy (Niccone, 137 km² and Assino, 165 km² [2]), one in South Italy (Fiumarella, 33 km² [8]), Luxembourg (Bibeschbach, 12 km² [4]), France (Valescure, 3.7 km² [9]), and US (Lucky Hills, 0.001 km² [10]) are analyzed. For sake of brevity, the reader is referred to the cited references for more details about the characteristics of the catchments and of the available hydrometeorological data.…”

Section: Study Catchmentsmentioning

confidence: 99%

Assimilation of satellite soil moisture data into rainfall-runoff modelling for several catchments worldwide

Brocca¹,

Moramarco²,

Dorigo³

et al. 2013

2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS

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The assimilation of satellite soil moisture data into rainfallrunoff modelling represents an important issue not only for research purposes but also for hydrological application addressing flood forecasting. Notwithstanding the large effort made in the last three decades, only few studies demonstrated a benefit deriving from the use of satellite soil moisture data in hydrology. This matter can be ascribed to the differences in the quality of the assimilated data, in the climatic conditions and in the data assimilation techniques that have been adopted. Based on that, this study compares different satellite soil moisture products in different catchments worldwide to shed light about the more suitable products and climatic conditions that should be employed for improving runoff prediction. The results reveal that the employed soil moisture products can be conveniently used to improve runoff prediction. However, reliability differs according to the climatic region and the accuracy of satellite retrievals.

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Effects of antecedent soil moisture on runoff modeling in small semiarid watersheds of southeastern Arizona

Cited by 47 publications

References 36 publications

Seasonality of hydrological model spin-up time: a case study using the Xinanjiang model

Seasonality of hydrological model spin-up time: a case study using the Xinanjiang model

Impact of Soil Moisture on Crop Yields over Brazilian Semiarid

Assimilation of satellite soil moisture data into rainfall-runoff modelling for several catchments worldwide

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