Modelling the effect of irrigation on the hydrological output from a small prairie watershed

Rahbeh, Michel; Chanasyk, D. S.; Miller, Jim J.

doi:10.1080/07011784.2013.849856

Cited by 10 publications

(5 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The animal population densities were calculated using the animal populations divided by the amount of grassland in the watershed. Runoff and sediment in small irrigated watershed in the Canadian prairie was investigated by Rahbeh et al [94] using SWAT. The irrigation activity did not change the water partitioning among the existing hydrological pathways but had temporal effects on the magnitudes of runoff and, more importantly, deep percolation and the subsequent groundwater discharge in the main reach.…”

Section: Soil and Water Assessment Tool (Swat)mentioning

confidence: 99%

Effects of Grazing Management on Spatio-Temporal Heterogeneity of Soil Carbon and Greenhouse Gas Emissions of Grasslands and Rangelands: Monitoring, Modelling and Upscaling

Wang¹

2019

Preprint

View full text Add to dashboard Cite

The sustainability of grazing lands lies in the nexus of human consumption behavior, livestock productivity, and environmental sustainability. Due to fast growing global food demands, many grazing lands have suffered from overgrazing, leading to soil degradation, air and water pollution, and biodiversity losses. Multidisciplinary efforts are required to understand how grazing lands can be better monitored, assessed and managed to attain predictable outcomes of optimal benefit to society. This paper synthesizes our understanding based on previous work done on impacts of grazing on ecosystem goods and services, identifies current knowledge gaps, and formulates a plan forward. We review the impacts of two contrasting grazing systems, continuous and multi-paddock rotational grazing, on soil carbon (C), nutrient cycling and greenhouse gas emissions (GHGs). We then extend our review to explore challenges of incorporating spatial heterogeneity and temporal variability into monitoring and modelling C and nutrient cycling in grazing lands. We revisit two process-based models (i.e., DNDC and DayCent) and two watershed models (i.e., SWAT and VIC) widely used to simulate C, nutrient and water cycles of these lands. Finally we identify research directions for improving the knowledge base which is essential to conserve grazing lands and maintain their ecosystem goods and services.

show abstract

Section: Soil and Water Assessment Tool (Swat)mentioning

confidence: 99%

Effects of Grazing Management on Spatio-Temporal Heterogeneity of Soil Carbon and Greenhouse Gas Emissions of Grasslands and Rangelands: Monitoring, Modelling and Upscaling

Wang¹

2019

Preprint

View full text Add to dashboard Cite

show abstract

“…Irrigation caused surface runoff and also recharged the aquifer. Both runoff and the aquifer discharge contributed to the return flow in the channel (Rahbeh et al 2013). Return flow likely caused channel erosion and exacerbated soil erosion.…”

Section: Source Apportionment Overall Source Apportionmentmentioning

confidence: 99%

Determining sources of fine-grained sediment for a reach of the Lower Little Bow River, Alberta, using a colour-based sediment fingerprinting approach

et al. 2017

Self Cite

View full text Add to dashboard Cite

Identifying the predominant sources of sediment is a key requirement for soil erosion control within watersheds. A 4 yr study from 2009 to 2012 was conducted to apportion sediment sources in a subcatchment of the Lower Little Bow River watershed, AB, Canada. This study catchment lies along a 6 km reach of the river, having an upstream inlet and downstream outlet; as such, it represents the first application of the sediment fingerprinting technique in a reach setting. Six monitoring stations were established along this reach of river to collect sediments using passive time-integrated sediment samplers. Source material samples were collected throughout the study catchment. Reflectance spectra of source and sediment samples were determined using a diffuse reflectance spectrometer. Source materials were classified into five sources using canonical discriminant analysis. Following the normality test, analysis of variance and stepwise discriminant function analysis, four colour coefficients were selected and fitted to the Bayesian mixing model of stable isotope analysis in R. The results indicated that the unknown upstream sediment source was the single largest (37.4%) contributor of sediments, suggesting that there is sediment coming from a significant source or sources not represented within the study catchment. Irrigation return flow channels were the second largest contributor (25.6%), while the third largest contributor, agricultural land, had a minimal contribution (9.2%). Source contribution had a small spatial but large temporal variation. The results indicated that identifying the origin of secondary sediment sources of upstream and irrigation flow channels is a critical step for soil erosion control in the study subwatershed.Key words: colour coefficient, fingerprinting, MixSIAR, sediment sources.Résumé : Identifier les sources principales de sédiments est une exigence capitale lorsqu'on veut combattre l'érosion du sol dans un bassin hydrographique. De 2009 à 2012, les auteurs ont entrepris une étude visant à établir les sources de sédimentation d'un bassin versant secondaire de la Lower Little Bow River, en Alberta. Le bassin en question se situe le long d'un tronçon de six kilomètres de la rivière et compte une entrée en amont ainsi qu'un exutoire en aval. En tant que telle, l'étude correspond à la première application d'une technique de cartographie des sédiments dans un bief. Six postes de surveillance ont été aménagés le long du bief et les sédiments ont été recueillis au moyen de systèmes d'échantillonnage passif intégré dans le temps. Les échantillons de matériaux d'origine ont été glanés à la grandeur du bassin versant à l'étude. Le spectre de réflectance des échantillons prélevés à la source et des sédiments a été établi avec un spectromètre à réflectance diffuse. Les matériaux d'origine ont été répartis entre cinq sources par analyse discriminante canonique. À partir des résultats du test de normalité, de l'analyse de la variance et de l'analyse discriminante des fonctions pas à pas, les ...

show abstract

“…This approach is simple to implement, but makes the unrealistic assumption that all farmers irrigate all crops on the same day across the entire catchment. Spatial variability limited to different crop types. Examples of this approach include models that assume irrigation practices largely follow technical reports of crop water use (Cheema et al, ; Li et al, ), models based on crop types and observations of precipitation and AET (Rahbeh et al, ), and models that disaggregate measured catchment irrigation volume based solely on crop type and season (Githui et al, ). These approaches allow for spatial variability in irrigation schedules, but retain the unrealistic assumption that all areas with the same crop type will be irrigated on the same day. Spatial variability represented at the discretization scale of the hydrological model, most often at the scale of hydrological response units (HRUs).…”

Section: Introductionmentioning

confidence: 99%

“…Spatial variability limited to different crop types. Examples of this approach include models that assume irrigation practices largely follow technical reports of crop water use (Cheema et al, 2014;Li et al, 2009), models based on crop types and observations of precipitation and AET (Rahbeh et al, 2013), and models that disaggregate measured catchment irrigation volume based solely on crop type and season (Githui et al, 2012). These approaches allow for spatial variability in irrigation schedules, but retain the unrealistic assumption that all areas with the same crop type will be irrigated on the same day.…”

Section: Introductionmentioning

confidence: 99%

“…“Irrigation schedule” models are often used to simulate the timing and depth of irrigation at various locations in a catchment, because irrigation data are seldom available at the small spatial scale required for inputs into distributed hydrological models such as SWAT. Irrigation schedule models can incorporate a range of information, including irrigation depths and intervals based on Best Management Practices (BMPs), planting dates recommended in technical reports of crop management (e.g., Cheema et al, ; Sun & Ren, ), meteorological conditions such as rainfall and actual evapotranspiration (AET) (Rahbeh et al, ), and local measurements of irrigation water use at larger spatial scales (e.g., at the scale of the entire catchment, Baubion et al, ; Chiew & McMahon, ; Githui et al, ). For example, BMPs for perennial pastures in Victoria, Australia, recommend irrigating when the difference between AET and precipitation is 50 mm, which typically occurs every 7 days in summer but less frequently during spring and autumn when actual evapotranspiration (AET) is lower (Greenwood et al, ; Lawson & Hildebrand, ).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The Importance of Spatiotemporal Variability in Irrigation Inputs for Hydrological Modeling of Irrigated Catchments

McInerney

Thyer

Kavetski

et al. 2018

Water Resources Research

View full text Add to dashboard Cite

Irrigation contributes substantially to the water balance and environmental condition of many agriculturally productive catchments. This study focuses on the representation of spatiotemporal variability of irrigation depths in irrigation schedule models. Irrigation variability arises due to differences in farmers’ irrigation practices, yet its effects on distributed hydrological predictions used to inform management decisions are currently poorly understood. Using a case study of the Barr Creek catchment in the Murray Darling Basin, Australia, we systematically compare four irrigation schedule models, including uniform versus variable in space, and continuous‐time versus event‐based representations. We evaluate simulated irrigation at hydrological response unit and catchment scales, and demonstrate the impact of irrigation schedules on the simulations of streamflow, evapotranspiration, and potential recharge obtained using the Soil and Water Assessment Tool (SWAT). A new spatially variable event‐based irrigation schedule model is developed. When used to provide irrigation inputs to SWAT, this new model: (i) reduces the over‐estimation of actual evapotranspiration that occurs with spatially uniform continuous‐time irrigation assumptions (biases reduced from ~40% to ~2%) and (ii) better reproduces the fast streamflow response to rainfall events compared to spatially uniform event‐based irrigation assumptions (seasonally adjusted Nash‐Sutcliffe Efficiency improves from 0.15 to 0.56). The stochastic nature of the new model allows representing irrigation schedule uncertainty, which improves the characterization of uncertainty in simulated catchment streamflow and can be used for uncertainty decomposition. More generally, this study highlights the importance of spatiotemporal variability of inputs to distributed hydrological models and the importance of using multivariate response data to test and refine environmental models.

show abstract

Modelling the effect of irrigation on the hydrological output from a small prairie watershed

Cited by 10 publications

References 26 publications

Effects of Grazing Management on Spatio-Temporal Heterogeneity of Soil Carbon and Greenhouse Gas Emissions of Grasslands and Rangelands: Monitoring, Modelling and Upscaling

Effects of Grazing Management on Spatio-Temporal Heterogeneity of Soil Carbon and Greenhouse Gas Emissions of Grasslands and Rangelands: Monitoring, Modelling and Upscaling

Determining sources of fine-grained sediment for a reach of the Lower Little Bow River, Alberta, using a colour-based sediment fingerprinting approach

The Importance of Spatiotemporal Variability in Irrigation Inputs for Hydrological Modeling of Irrigated Catchments

Contact Info

Product

Resources

About