Assessing the performance of a physically-based soil moisture module integrated within the Soil and Water Assessment Tool

2018 ◽  
Vol 109 ◽  
pp. 329-341 ◽  
Author(s):  
Junyu Qi ◽  
Xuesong Zhang ◽  
Gregory W. McCarty ◽  
Ali M. Sadeghi ◽  
Michael H. Cosh ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Assessment Tool ◽  
Physically Based ◽  
Water Assessment ◽  
Soil And Water

scholarly journals Simulasi Arahan Penggunaan Lahan di DAS Limboto dalam Rangka Pengendalian Kekeringan

2019 ◽  
Vol 33 (2) ◽  
pp. 87
Author(s):  
Sri Rahayu Ayuba ◽  
Munajat Nursaputra ◽  
Tisen Tisen
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Input Data ◽  
Assessment Tool ◽  
Soil Moisture Deficit ◽  
Moisture Deficit ◽  
Water Assessment ◽  
Soil And Water

Perubahan penggunaan lahan bisa dibilang kekuatan sosioekonomi yang paling meluas mendorong perubahan dan degradasi ekosistem (Wu, 2008). (Kodoatie, 2010) menyatakan bahwa, terganggunya siklus hidrologi telah menimbulkan “3 T” masalah klasik air “too much (yang menimbulkan banjir), “too little (yang menimbulkan kekeringan) dan “too dirty (yang menimbulkan pencemaran air). Berdasarkan data BNPB tahun 1979-2009 terdapat 8 kejadian kekeringan di Provinsi Gorontalo. Penelitian ini bertujuan (1) mengetahui tingkat kerentanan DAS Limboto terhadap kekeringan. (2) menyusun arahan penggunaan lahan pada DAS Limboto berdasarkan penentuan tingkat kerentanan kekeringan. (3) mengsimulasikan arahan penggunaan lahan dalam rangka pengendalian kekeringan di DAS Limboto. Penelitian ini dilaksanakan pada Daerah Aliran Sungai (DAS) Limboto dengan luas DAS 86412,6 ha. Metode yang digunakan adalah Metode SWAT (Soil and Water Assessment Tool) dengan menggunakan software ArcSwat yang terintegrasi SIG. Penelitian ini termasuk dalam penellitian non-eksperimen yakni dengan menggunakan pengamatan langsung di lapangan. Input data SWAT antara lain lereng, jenis tutupan lahan, iklim, dan jenis tanah. Analisis yang digunakan dalam menentukan kerentanan DAS terhadap kekeringan adalah dengan menggunakan Soil Moisture Deficit Index (SMDI) melalui parameter Soil Water (SW). Pada penelitian ini penggunaan output model SWAT melalui ArcSwat, telah mampu menggambarkan kondisi pasokan air pada DAS Limboto, yang secara keseluruhan telah termasuk dalam kategori “Rentan”. Dengan membandingkan luas area yang mengalami kekeringan pada sebelum dan setelah dilakukan simulasi/running arahan penggunaan lahan maka dapat disimpulkan bahwa selisih luas area DAS yang mengalami kekeringan dengan klasifikasi “Rentan” diperoleh 37.513,1 ha atau secara persentasi mengalami penurunan sebesar 43,4 % dari luas DAS.

scholarly journals Evaluation of SWAT Soil Water Estimation Accuracy Using Data from Indiana, Colorado, and Texas

2020 ◽  
Vol 63 (6) ◽  
pp. 1827-1843
Author(s):  
Ahmed A. Hashem ◽  
Bernard A. Engel ◽  
Gary W. Marek ◽  
Jerry E. Moorhead ◽  
Dennis C. Flanagan ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Soil Profile ◽  
Assessment Tool ◽  
Swat Model ◽  
List Type ◽  
Water Assessment ◽  
Soil And Water

HighlightsSWAT soil water assessment was performed using soil water measurements.Dryland SWAT model soil water content was greater than the irrigated SWAT model.Using SWAT soil water estimates for real-time (daily) irrigation management purposes with the existing SWAT soil water subroutines and available soils data is considered risky.The surface layer showed the greatest soil water variability compared to deeper layers.Abstract. Soil water content (SWC) is a challenging measurement at the field, watershed, and regional scales. Soil and Water Assessment Tool (SWAT) soil water estimates were evaluated at three locations: the St. Joseph River watershed (SJRW) in northeast Indiana, the USDA-ARS Conservation and Production Research Laboratory (CPRL) at Bushland, Texas, and the USDA-ARS Limited Irrigation Research Farm (LIFR) at Greeley, Colorado. The soil water estimates were evaluated under two scenarios: (1) for the defined soil profile, and (2) by individual layer. Each site’s soil water assessment was performed based on the existing management conditions during each experiment, whether dryland or irrigated, and for various periods depending on SWC measurement availability at each site. The SWAT soil water was evaluated as follows: the Indiana site was evaluated under dryland conditions using daily soil water observations for one year; the Texas site was evaluated for a ten-year period under irrigated and dryland conditions using weekly soil water observations from four lysimeters; and the Colorado site was evaluated under irrigated conditions for a four-year period. The simulated soil water was evaluated by comparing the model simulations with observed daily and weekly soil water measurements at the three sites. Based on the results, even though all the SWAT models were considered to perform as good models following calibration (streamflow, ET, etc.), the soil water simulations were unacceptable for the defined soil profile and for individual layers at the three sites. Deeper soil layers had observations greater than field capacity values, indicating poor soil parameterization. The dryland model had greater water content than the irrigated model, contradicting the soil water measurements. This greater soil water simulation with the dryland model is a result of SWAT model uncertainties with ET reduction under dryland conditions due to water stress. This study indicated that soil water estimation using the default SWAT soil water equations has many sources of uncertainties. Two apparent sources resulted in the SWAT model’s poor performance: (1) SWAT soil water routines that do not fully represent soil water moving between layers to meet plant demand and (2) uncertainty in soil parameterization. Keywords: Hydrologic modeling, Soil moisture, Soil moisture sensor, Soil water, Soil and Water Assessment Tool.

Evaluation of SWAT Soil Water Estimation Accuracy Using Data from Indiana, Colorado, and Texas

2020 ◽  
Vol 63 (6) ◽  
pp. 1827-1843
Author(s):  
Ahmed A. Hashem ◽  
Bernard A. Engel ◽  
Gary W. Marek ◽  
Jerry E. Moorhead ◽  
Dennis C. Flanagan ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Soil Profile ◽  
Assessment Tool ◽  
Swat Model ◽  
List Type ◽  
Water Assessment ◽  
Soil And Water

HighlightsSWAT soil water assessment was performed using soil water measurements.Dryland SWAT model soil water content was greater than the irrigated SWAT model.Using SWAT soil water estimates for real-time (daily) irrigation management purposes with the existing SWAT soil water subroutines and available soils data is considered risky.The surface layer showed the greatest soil water variability compared to deeper layers.Abstract. Soil water content (SWC) is a challenging measurement at the field, watershed, and regional scales. Soil and Water Assessment Tool (SWAT) soil water estimates were evaluated at three locations: the St. Joseph River watershed (SJRW) in northeast Indiana, the USDA-ARS Conservation and Production Research Laboratory (CPRL) at Bushland, Texas, and the USDA-ARS Limited Irrigation Research Farm (LIFR) at Greeley, Colorado. The soil water estimates were evaluated under two scenarios: (1) for the defined soil profile, and (2) by individual layer. Each site’s soil water assessment was performed based on the existing management conditions during each experiment, whether dryland or irrigated, and for various periods depending on SWC measurement availability at each site. The SWAT soil water was evaluated as follows: the Indiana site was evaluated under dryland conditions using daily soil water observations for one year; the Texas site was evaluated for a ten-year period under irrigated and dryland conditions using weekly soil water observations from four lysimeters; and the Colorado site was evaluated under irrigated conditions for a four-year period. The simulated soil water was evaluated by comparing the model simulations with observed daily and weekly soil water measurements at the three sites. Based on the results, even though all the SWAT models were considered to perform as good models following calibration (streamflow, ET, etc.), the soil water simulations were unacceptable for the defined soil profile and for individual layers at the three sites. Deeper soil layers had observations greater than field capacity values, indicating poor soil parameterization. The dryland model had greater water content than the irrigated model, contradicting the soil water measurements. This greater soil water simulation with the dryland model is a result of SWAT model uncertainties with ET reduction under dryland conditions due to water stress. This study indicated that soil water estimation using the default SWAT soil water equations has many sources of uncertainties. Two apparent sources resulted in the SWAT model’s poor performance: (1) SWAT soil water routines that do not fully represent soil water moving between layers to meet plant demand and (2) uncertainty in soil parameterization. Keywords: Hydrologic modeling, Soil moisture, Soil moisture sensor, Soil water, Soil and Water Assessment Tool.

AN EVALUATION OF BLUE WATER PREDICTION IN SOUTHERN PART OF IRAN USING THE SOIL AND WATER ASSESSMENT TOOL (SWAT)

2016 ◽  
Vol 15 (1) ◽  
pp. 175-188 ◽  
Author(s):  
Mohsen Salarpour ◽  
Milad Jajarmizadeh ◽  
Sobri Harun ◽  
Rozi Abdullah
Keyword(s):  
Assessment Tool ◽  
Blue Water ◽  
Water Assessment ◽  
Soil And Water

Modeling Miscanthus in the Soil and Water Assessment Tool (SWAT) to Simulate Its Water Quality Effects As a Bioenergy Crop

2010 ◽  
Vol 44 (18) ◽  
pp. 7138-7144 ◽  
Author(s):  
Tze Ling Ng ◽  
J. Wayland Eheart ◽  
Ximing Cai ◽  
Fernando Miguez
Keyword(s):  
Water Quality ◽  
Assessment Tool ◽  
Bioenergy Crop ◽  
Water Assessment ◽  
Soil And Water

Can-GLWS: Canadian Great Lakes Weather Service for the Soil and Water Assessment Tool (SWAT) modelling

2020 ◽  
Author(s):  
Narayan K. Shrestha ◽  
Taimoor Akhtar ◽  
Uttam Ghimire ◽  
Ramesh P. Rudra ◽  
Pradeep K. Goel ◽  
...  
Keyword(s):  
Great Lakes ◽  
Assessment Tool ◽  
Water Assessment ◽  
Soil And Water ◽  
Weather Service

scholarly journals Pemodelan Erosi dan Sedimentasi di DAS Bajulmati : Aplikasi Soil dan Water Assesment Tool (SWAT)

2020 ◽  
Vol 18 (2) ◽  
pp. 220-230
Author(s):  
Mohamad Wawan Sujarwo ◽  
Indarto Indarto ◽  
Marga Mandala
Keyword(s):  
Assessment Tool ◽  
Response Unit ◽  
Water Assessment ◽  
Soil And Water

DAS bajulmati merupakan DAS kecil (± 173.4 km2) yang berada di wilayah timur pulau Jawa. DAS bajulmati memiliki iklim yang spesifik yaitu relatif kering dengan musim kemarau yang panjang (8-9 bulan selama setahun). Meskipun kondisi iklim yang kurang mendukung, sebagian besar masyarakat bekerja sebagai petani landang. Adanya perluasan lahan pertanian non irigasi/ladang mengakibatkan tutupan vegetasi semakin berkurang. Oleh karena itu, evaluasi DAS bajulmati diperlukan untuk mengetahui dampak perluasan lahan pertanian terhadap laju aliran dan sedimentasi dengan kondisi iklim yang cukup spesifik (kering). Salah satu model evaluasi pengelolaan DAS terhadap perubahan lahan adalah model SWAT (Soil and Water Assessment Tool). SWAT dapat menggambarkan proses hidrologi (erosi dan sedimentasi) unit lahan. data DEM resolusi (10x10 m) sebagai masukan utama untuk proses delinasi DAS. Data tanah, tutupan lahan, dan kontur digunakan untuk menentukan unit lahan/hydrolocal response unit (HRU) DAS. Data curah hujan dan iklim (suhu, kelembaban rata-rata, intensitas matahari, kecepatan angin) diperoleh dari stasiun yang tersebar di wilayah DAS. Semua data diintegrasikan ke dalam SWAT untuk menghitung proses hidrologi, erosi dan sedimentasi. Debit yang diamati digunakan untuk mengkalibrasi keluaran debit hasil SWAT di outlet DAS. Hasil kalibrasi debit menunjukkan nilai Nash-Sutcliffe Efficiency sebesar 0,53 dan validasi sebesar 0,5 serta koefisien determinasi sebesar 0,58 dan 0,78 (memuaskan) dan model dapat digunakan untuk ilustrasi proses hidrologi dalam DAS bajulmati. Analisis tingkat erosi SWAT menunjukkan bahwa 34,46; 39,19; dan 17,83 menunjukkan tingkat erosi sangat ringan sampai kategori sedang. Oleh karena itu, DAS Bajulmati masih dalam kategori aman karena rata-rata erosi berat dan sangat berat dibawah 10%. Nilai sedimentasi tertinggi pada HRU 512 dan SubDAS 23. Wilayah tersebut merupakan wilayah perkebunan dengan tingkat kemiringan diatas 40%.

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