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Water productivity under deficit irrigation using onion as indicator crop

Tadesse Kassahun B., Hagos Eyasu Y., Tafesse Nata T., Dinka Megersa O.

Journal of Water and Land Development

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2020

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no. 45

171--178

EN

Improving water productivity (WP) through deficit irrigation is crucial in water-scarce areas. To practice deficit irrigation, the optimum level of water deficit that maximizes WP must be investigated. In this study, a field experiment was conducted to examine WP of the three treatments at available soil water depletion percentage (Pi) of 25% (reference), 45% and 65% using a drip irrigation system. Treatments were arranged in a randomized complete block design. The water deficit was allowed throughout the growth stages after transplanting except for the first 15 days of equal amounts of irrigations during the initial growth stage and 20 days enough spring season rainfall during bulb enlargement periods. Physical WP in terms of water use efficiency (WUEf) for treatments T1, T2, and T3 was 9.44 kg∙m–3, 11 kg∙m–3 and 10.6 kg∙m–3 for marketable yields. The WUEf and economic water productivity were significantly improved by T2 and T3. The WUEf difference between T2 and T3 was insignificant. However, T2 can be selected as an optimal irrigation level. Hence, deficit irrigation scheduling is an important approach for maximizing WP in areas where water is the main constraint for crop production. The planting dates should be scheduled such that the peak water requirement periods coincide with the rainy system.

2

Predicting future water demand for Long Xuyen Quadrangle under the impact of climate variability

Lee S. K. L., Dang T. A.

Acta Geophysica

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2018

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Vol. 66, no. 5

1081--1092

EN

Long Xuyen Quadrangle is one of the important agricultural areas of the Mekong Delta of Vietnam accounting for 25% of rice production. In recent years, the area faces drought and salinization problems, as part of climate change impact and sea level rise. These are the main causes that led to the crop water deficits for agricultural production. Therefore, this work was conducted to predict crop water requirement (CWR) based on consideration of other related meteorological factors and further redefine the crop planting calendar (CPC) for three main cropping seasons including winter–spring (WS), summer–autumn (SA) and autumn–spring (AS) using the Cropwat crop model based on the current climate conditions and future climate change scenarios. Meteorological data for the baseline period (2006–2016) and future corresponding to timescales 2020s, 2055s and 2090s of Representative Concentration Pathways (RCP)4.5 and RCP8.5 scenarios are used to predict CWR and CPC for the study area. The results showed that WS and SA crops needed more irrigation water than AS crop and the highest irrigation water requirement of the WS and SA crops occurred on developmental stage, while the AW crop appeared on growth, developmental and late stage for the baseline and timescales of RCP4.5 and RCP8.5 scenarios. Calculation results of the shift of CPC indicated that the CWR of the AW crop decreased lowest approximately 6.6–20.6% for timescales of RCP4.5 scenario and 20.6–25.5% for RCP8.5 scenario compared with the baseline.

3

Wykorzystanie archiwalnych zdjęć lotniczych oraz współczesnej ortofotomapy do oceny zmian warunków formowania się opadu efektywnego w Kielcach w latach 1944-2014

Wałek G.

Teledetekcja Środowiska

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2016

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T. 54

5--11

EN

In the paper, results of the effective rainfall conditions changes analysis between 1944 and 2014 in two urban catchments in Kielce is present. The objective was achieved by detailed land cover changes analysis based on archival US Air Force aerial photographs from 1944 and contemporary ortophoto from 2014. In order to identify the hydrological consequences of land cover changes the Soil Conservation Service Runoff Curve Number (CN) method was used. The analysis was conducted using QGIS and SAGA GIS software. Research has shown major land cover changes in both catchments - decline of arable land and significant increase of impermeable surfaces such as roofs, roads, pavements, parking lots and squares (from 7.5 to 44.3 % of total SI-4 catchment area and from 10.6 to 43.3 % of total SI-5 catchment area). Those changes directly influenced the weighted CN value of the SCS method (from 76 to 80 in SI-4 catchment, from 79 to 82 in SI-5 catchment), finally leading to transform up to 50 % of the total design rainfall (0,01 %) in to the effective rainfall in the catchments.

4

Adaptacja modelu Santa Barbara Unit Hydrograph do obliczania hydrogramu przepływów w zurbanizowanej zlewni Potoku Służewieckiego

Barszcz M.

Czasopismo Inżynierii Lądowej, Środowiska i Architektury / Journal of Civil Engineering, Environment and Architecture

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2014

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z. 61, nr 4

21--34

PL

Celem pracy jest przedstawienie procedury obliczeniowej hydrogramu przepływów za pomocą konceptualnego modelu Santa Barbara Unit Hydrograph (SBUH) oraz jej weryfikacja w zlewni cząstkowej Potoku Służewieckiego w Warszawie o powierzchni 14,7 km2. Weryfikacja tej procedury i modelu SBUH polegała na ocenie zgodności przepływów maksymalnych, obliczonych za pomocą modelu i pomierzonych w profilu „Rosoła”. Zakres pracy obejmuje wyznaczenie parametrów modelu (tc, Kr) metodą iteracyjną dla 25 zdarzeń opad-odpływ. Stosując metodę iteracyjną, uzyskano te same wartości dla pomierzonych i symulowanych przepływów maksymalnych. Na podstawie uzyskanych danych opracowano równanie, które umożliwia obliczenie czasu koncentracji (tc) w relacji do maksymalnej intensywności opadu efektywnego. Korelacja między tymi charakterystykami jest silnym związkiem liniowym (R = 0,73). Obliczone za pomocą równania czasy koncentracji wykorzystano do symulacji hydrogramów przepływów modelem SBUH. Wartości najmniejszego i największego błędu względnego (procentowego) ustalone na podstawie pomierzonych i symulowanych przepływów dla analizowanych zdarzeń, wynosiły odpowiednio –0,4 i 71,5%. Średni błąd obliczony przy uwzględnieniu wartości bezwzględnych błędów symulacji dla poszczególnych zdarzeń (zaniedbano znaki minus dla ustalonych błędów względnych) wynosił 17,2%. Do obliczenia opadu efektywnego zastosowano metodę SCS. Wartości parametru CN w tej metodzie wyznaczono dla analizowanych zdarzeń na podstawie danych opad-odpływ. Ustalone wartości wykorzystano do opracowania równania, które umożliwia obliczenie parametru CN na podstawie sumy opadu całkowitego.

EN

The aim of the study was to present the calculation procedure of a flow hydrograph using the conceptual Santa Barbara Unit Hydrograph (SBUH) model and its verification in the Służewiecki Stream sub catchment (A = 14.7 km2) in Warsaw. The verification of this procedure and the SBUH model was based on an assessment of the compatibility of maximum flows, calculated using the model and measured in the “Rosoła” profile. The scope of the work included determining the parameters of the model (tc, Kr) using the iterative method for 25 rainfall-runoff events. When determining the parameters of the model, there were no differences between the measured and simulated maximal flows. The obtained data were used to devise a formula which enabled the time of concentration (tc) to be calculated in relation to the maximum intensity of effective rainfall. The correlation between these characteristics is a strong linear relationship (R = 0.73). The times of concentration calculated using the formula were applied when simulating flow hydrographs by means of the SBUH model. The values of the smallest and the largest relative error (percentage), determined on the basis of measured and simulated flows for the analyzed events, amounted to 0.4 and 71.5%, respectively. The average error, calculated taking into account the absolute values of simulation errors for individual events (neglected minus signs for determined relative errors), amounted to 17.2%. When calculating the effective rainfall there was used the CN-SCS method. The CN parameters values of this method were established for analyzed events based on the rainfall-runoff data. The determined values were used to devise a formula which enabled the CN parameter to be calculated based on the sum of the total rainfall.