Relationships Between Water Table and Model Simulated ET

Jayakody, Priyantha; Parajuli, Prem B.; Sassenrath, Gretchen F.; Ouyang, Ying

doi:10.1111/gwat.12053

Cited by 17 publications

(7 citation statements)

References 20 publications

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“…Because previous research has demonstrated strong relationships between ET and groundwater (Ajami et al, 2011;Jayakody et al, 2013;Nachabe et al, 2005;Pandey et al, 1997), the BSRW model was analyzed to see any hydrological connections between the two hydrological parameters. The model was also simulated under 10 crop rotation scenarios, which are a combination of the four dominant crop types of corn, soybean, cotton, and rice.…”

Section: Model Analysis and Scenariosmentioning

confidence: 99%

“…It should be noted that the scheduled irrigation in the model does not necessarily reflect the actual irrigation applications practiced by farmers in the BSRW from year to year. It has been reported that the farmers in the Mississippi Delta irrigate based primarily on plant observation, which may lead the farmers to either under irrigate or over irrigate their crops (Jayakody et al, 2013). This can cause considerable spatial and temporal variations of irrigation practices throughout the watershed, especially when considering varying weather conditions.…”

Section: Et and Groundwater Interactionsmentioning

confidence: 99%

“…Also, converting groundwater recharge rates at the HRU level to the cell level may not be feasible at the watershed scale due to expensive computational requirements. In another SWAT groundwater modeling study, it was possible to only use SWAT to calibrate and validate a model for changes in water table depths (Jayakody et al, 2013). This was accomplished by calculating evapotranspiration, percolation, and groundwater discharge to develop an empirical relationship with water table fluctuations that was able to predict 64% of the water table variation (Jayakody et al, 2013).…”

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confidence: 99%

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Evaluating the impacts of crop rotations on groundwater storage and recharge in an agricultural watershed

Dakhlalla

Parajuli

Ouyang

et al. 2016

Agricultural Water Management

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The Mississippi River Valley Alluvial Aquifer, which underlies the Big Sunflower River Watershed 7 (BSRW), is the most heavily used aquifer in Mississippi. Because the aquifer is primarily used for irrigating crops such as corn, cotton, soybean, and rice, the water levels have been declining rapidly over the past few decades. The objectives of this study are to analyze the relationship and interactions between evapotranspiration and groundwater recharge rates in the BSRW, and model the effects of various crop rotation practices on groundwater storage and recharge. The model performed well during the calibration period (R 2 = 0.53 to 0.68 and NSE = 0.49 to 0.66) and validation period (R 2 = 0.55 to 0.75 and NSE = 0.49 to 0.72) for daily streamflow, which was 14 achieved by the SUFI-2 auto-calibration algorithm in the SWAT-CUP package. The model also performed well in simulating seasonal water table depth fluctuations during calibration (R 2 = 0.76 and NSE = 0.71) 16 and validation (R 2 = 0.86 and NSE = 0.79). This study demonstrated a seasonal relationship between 17 evapotranspiration and groundwater storage and recharge in the BSRW SWAT model. In general, groundwater storage decreased during the summer months while ET rates were high, and increased during the winter and spring months when ET rates were low. The crop rotation scenarios that include 20 rice planting resulted in the lowest groundwater storage (down to-10.7%) compared to the baseline crop scenario, which is due to the high irrigation rates of the rice crop. However, the rice crop rotations resulted in the highest increases of groundwater recharge rates (up to +60.1%), likely because of the 23

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Section: Model Analysis and Scenariosmentioning

confidence: 99%

Section: Et and Groundwater Interactionsmentioning

confidence: 99%

mentioning

confidence: 99%

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Evaluating the impacts of crop rotations on groundwater storage and recharge in an agricultural watershed

Dakhlalla

Parajuli

Ouyang

et al. 2016

Agricultural Water Management

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“…Arnold et al [47] reported that input parameters in SWAT are process-based and should be set in a reasonable uncertainty range. Based on the previous studies conducted by Dakhlalla et al [41] and Jayakody et al [51] in BSRW, five hydrological parameters were selected for calibration. They were the Manning's roughness coefficient for the main channel (CH_N2), soil conservation service curve number (CN2), surface runoff lag time (SURLAG), saturated hydraulic conductivity of the soil layers (SOL_K), and the threshold depth of water in the shallow aquifer (GWQMN).…”

Section: Model Calibration and Validation Methodsmentioning

confidence: 99%

Assessment of Surface Water Resources in the Big Sunflower River Watershed Using Coupled SWAT–MODFLOW Model

Gao

Feng

Han

et al. 2019

Water

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The groundwater level in the Big Sunflower River Watershed (BSRW) in the U.S. has declined significantly in the past 30 years. Therefore, it is imperative to assess surface water resources (SWR) availability in BSRW to mitigate groundwater use for irrigation. This research applied the coupled Soil and Water Assessment Tool–Modular Groundwater Flow model (SWAT–MODFLOW) to assess SWR in BSRW. This study aimed at: (1) Assessing the reliability of SWAT–MODFLOW in BSRW, (2) analyzing temporal and spatial variations of SWR, and (3) assessing the potential availability of SWR in BSRW. Calibration and validation results showed that SWAT–MODFLOW can well simulate streamflow and groundwater levels in BSRW. Our results showed that BSRW had lower average monthly total stream resources (MSR = 8.8 × 107 m3) in growing seasons than in non-growing seasons (MSR = 11.0 × 107 m3), and monthly pond resources (MPR from 30,418 to 30,494 m3) varied less than stream resources. The proportion of sub-basins in BSRW with stream water resources greater than 700 mm was 21% in dry years (229 to 994 mm), while this increased to 35% in normal years (296 to 1141 mm) and 57% in wet years (554 to 991 mm). The Water Stress Index (WSI) ranged from 0.4 to 2.1, revealing that most of the sub-basins in BSRW have net SWR available for irrigation. Our results suggested that surface water resources might be supplementary irrigation sources to mitigate the water resources scarcity in this region.

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“…Pemodelan hidrologis, yang mendeterminasi kelembapan tanah pada berbagai solum dan fluktuasi muka air tanah pada lapisan lebih dalam pada suatu lahan terus dikembangkan dalam upaya konservasi tanah dan air yang berkaitan dengan upaya pengelolaan lahan ramah lingkungan dan berkesinambungan pada lahan perkebunan kelapa sawit. Pada awal pemodelan, neraca air yang merupakan satu kesatuan sistem yang meliputi aspek atmosfer, vegetasi di permukaan tanah, dan kondisi fisik tanah di permukaan maupun pada lapisan yang lebih dalam, telah mampu mendeterminasi perilaku kelembapan tanah di lapisan permukaan dan lapisan-lapisan lain di bawahnya (Harahap, 1999;Rosa et al, 2002;Jayakody et al, 2013;dan Iwalewa et al, 2016). Seperti diketahui bahwa ada korelasi yang kuat antara kondisi kelembapan tanah dengan produksi tanaman (Singh, 2012).…”

Section: Pendahuluanunclassified

Assessment of Water Table Model on Oil Palm Area in a Hilly Land

Harahap

Lubis

2017

J. Penelitian Kelapa Sawit

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Iman Yani Harahap dan M. Edwin Syahputra Lubis ASSESSMENT MODEL MUKA AIR TANAH PADA PERTANAMAN KELAPA SAWIT DI LAHAN BERBUKIT ASSESMENT OF WATER TABLE MODEL ON OIL PALM AREA IN A HILLY LANDyang relatif tinggi pada puncak bukit diduga mereduksi air infiltrasi sehingga mengurangi inflow air. Sedangkan pada area lereng dan kaki bukit, inflow air dari area puncak yang berasal dari run-off, meningkatkan air infiltrasi pada kedua area tersebut, sehingga pengukuran aktual lebih tinggi dari keluaran model. Penyesuaian parameter laju run-off dan gradien potensi hidrolik pada area lereng dan perbukitan dapat meningkatkan akurasi keluaran model. Kata kunci : kelapa sawit, model muka air tanah, sumur pantau, kelerengan, puncak bukit, kaki bukit, gradien potensial hidrolik Abstract The aim of this research is to assess performance of developed water table model on oil palm area in a hilly land. The model requires some data of initiatial condition, input model, and physical parameters of the soils and crops. Initial data includes leaf area index, latitude geography position, initial water table, and the deep of impermeable soil layer. Input model includes daily weather data (rainfall, temperature, solar radiation, and wind speed). Soil physic parameters includes bulk volum density at each soil layers, and run-off of the soil surface. The crop parameters includes rainfall interception of crown and stem plants. Daily water table measurement was carried out at 3 points of wells located in one line hilly catena (30 -70 m above sea level) with slope about of 15% (top, middle, and foot). The area was the 20 years old oil palm planting area, soil type was Typic Hapludult with coarse to fine soil texture, hydraulic conductivity was classified as fast. The water table in this area was located in unconfined aquifer zone. The results showed that outputs of the model were 3 -4% higher than the * *

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Relationships Between Water Table and Model Simulated ET

Cited by 17 publications

References 20 publications

Evaluating the impacts of crop rotations on groundwater storage and recharge in an agricultural watershed

Evaluating the impacts of crop rotations on groundwater storage and recharge in an agricultural watershed

Assessment of Surface Water Resources in the Big Sunflower River Watershed Using Coupled SWAT–MODFLOW Model

Assessment of Water Table Model on Oil Palm Area in a Hilly Land

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