Impacts of incorporating dominant crop rotation patterns as primary land use change on hydrologic model performance

Gao, Jungang; Sheshukov, Aleksey Y.; Yen, Haw; Kastens, Jude H.; Peterson, D. L.

doi:10.1016/j.agee.2017.06.019

Cited by 22 publications

(13 citation statements)

References 43 publications

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“…Hydrological modeling of the water cycle in basins with speed response to rainfall such as small watersheds or distributed watersheds is necessary for water resource management 15 . The most widely used tools, such as the Soil and Water Assessment Tool (SWAT) has been successfully implemented for simulating streamflow under varying land use and climate conditions in numerous watersheds throughout the world 16 – 20 . The SWAT model has numerous parameters that can be reduced for regionalization objectives, meanwhile preserving prediction skills 14 , 21 , 22 .…”

Section: Introductionmentioning

confidence: 99%

Fuzzy clustering and distributed model for streamflow estimation in ungauged watersheds

Mosavi

Golshan

Choubin

et al. 2021

Sci Rep

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This paper proposes a regionalization method for streamflow prediction in ungauged watersheds in the 7461 km2 area above the Gharehsoo Hydrometry Station in the Ardabil Province, in the north of Iran. First, the Fuzzy c-means clustering method (FCM) was used to divide 46 gauged (19) and ungauged (27) watersheds into homogenous groups based on a variety of topographical and climatic factors. After identifying the homogenous watersheds, the Soil and Water Assessment Tool (SWAT) was calibrated and validated using data from the gauged watersheds in each group. The calibrated parameters were then tested in another gauged watershed that we considered as a pseudo ungauged watershed in each group. Values of R-Squared and Nash–Sutcliffe efficiency (NSE) were both ≥ 0.70 during the calibration and validation phases; and ≥ 0.80 and ≥ 0.74, respectively, during the testing in the pseudo ungauged watersheds. Based on these metrics, the validated regional models demonstrated a satisfactory result for predicting streamflow in the ungauged watersheds within each group. These models are important for managing stream quantity and quality in the intensive agriculture study area.

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Section: Introductionmentioning

confidence: 99%

Fuzzy clustering and distributed model for streamflow estimation in ungauged watersheds

Mosavi

Golshan

Choubin

et al. 2021

Sci Rep

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“…Most of the basin does not overlay large deep groundwater resources (KWO, 2009), and the stream network is extensively fragmented by small dams. Soils in this area are generally silt loam and clay loam with a mean permeability of 0.5 cm/hr (Gao, Sheshukov, Yen, Kastens, & Peterson, 2017;Gao, Sheshukov, Yen, & White, 2017;Sheshukov, Siebenmorgen, & Douglas-Mankin, 2011). Dominant land uses in the watershed are cultivated cropland and grazing land (NASS-CDL, 2014).…”

Section: Study Areamentioning

confidence: 99%

“…Corn is typically irrigated in the western part of the watershed and rotated yearly with winter wheat and fallow, whereas grain sorghum and winter wheat are non-irrigated. As typical for the Central Great Plains region of the United States, most crops are rotated annually (Gao, Sheshukov, Yen, Kastens, et al, 2017). Research Service for hydrologic modelling of watersheds (Arnold et al, 2012).…”

Section: Study Areamentioning

confidence: 99%

Projected climate change impacts on hydrologic flow regimes in the Great Plains of Kansas

Chatterjee

Daniels

Sheshukov

et al. 2018

River Research & Apps

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Alteration of flow regimes due to change in climate and its potential impact on habitat and species has become a major cause of concern for riverine ecosystems. Areas that are more vulnerable to such changes are semiarid river systems or regions experiencing intermittent flow and cyclic droughts. Although ecological changes are expected to occur with flow regime alterations, the biological changes cannot be predicted until the flow in such regions is analysed. This study addresses this concern by providing an analysis of flow for a semiarid river basin in the Central Great Plains from a 50 and 100‐year projection climate data. The projected data for these two periods are then compared with 30‐year historical data to determine changes in flow. Five major components of flow regime, magnitude, duration, and timing of annual extreme water conditions, frequency and duration of high and low pulses, and rate and frequency of water condition changes, were examined with respect to climate change for their impact on the ecology of the basin. This analysis strongly suggests that inter‐ and intra‐annual changes in flow regimes will result in the intensified drying of the basin represented by the increased number of low flow periods followed by higher occurrences of high flow events of shorter duration with expected changes in climate.

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“…The SWAT model incorporates crop rotation and its management at the level of the Hydrological Response Unit (HRU) within a sub-basin (Neitsch et al, 2002). It is represented as a sequence of planting and harvesting operations within the same HRU supplemented with management operations (Gao et al, 2017). The representation of agricultural management is done through a separate management file by specifying the planting, harvesting, tillage, irrigation, fertilizer and pesticide application by heat units or month and date (Arnold et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Representation of seasonal land-use dynamics in SWAT+ for improved assessment of blue and green water consumption

Msigwa

Chawanda

Komakech

et al. 2021

Preprint

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Abstract. In most (sub)-tropical African cultivated regions, more than one cropping cycle exists following the (one or two) rainy seasons. During the dry season, an additional cropping cycle is possible when irrigation is applied, which could result in 3 cropping seasons. In most agro-hydrological model applications such as SWAT+ in Africa, only one cropping season per year is represented. In this paper, we derived dynamic and static trajectories from seasonal land-use maps to represent the land- use dynamics following the major growing seasons, for the purpose of improving simulated blue and green water consumption from simulated evapotranspiration (ET) in SWAT+. This study builds upon earlier research that proposed an approach on how to incorporate seasonal land use dynamics in the SWAT+ model but mainly focused on the temporal pattern of LAI and tested the approach in a small catchment (240 km2). Together with information obtained from the cropping calendar, we implemented agricultural management operations for the dominant trajectory of each agricultural land-use class for the Kikuletwa basin (6650 km2 area coverage) in Tanzania. A comparison between the default SWAT+ (with static land use representation) set up, and a dynamic SWAT+ model (with seasonal land use representation) is done by spatial mapping of the evapotranspiration (ET) results. The results show that ET with seasonal representation is closer to remote sensing estimations, giving higher performance than default: the Root Mean Squared Error decreased from 181 to 69 mm/year; the percent bias decreased from 20 % to 13 % and Nash Sutcliffe Efficiency increased from −0.46 to 0.4. It is concluded that representation of seasonal land-use dynamics produces better ET results which provide better estimations of blue and green agricultural water consumption.

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Impacts of incorporating dominant crop rotation patterns as primary land use change on hydrologic model performance

Cited by 22 publications

References 43 publications

Fuzzy clustering and distributed model for streamflow estimation in ungauged watersheds

Fuzzy clustering and distributed model for streamflow estimation in ungauged watersheds

Projected climate change impacts on hydrologic flow regimes in the Great Plains of Kansas

Representation of seasonal land-use dynamics in SWAT+ for improved assessment of blue and green water consumption

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