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Characterization of the climatic drought indices application to the Mellah catchment, North-East of Algeria

Bendjema Lina, Baba-Hamed Kamila, Bouanani Abderrazak

Journal of Water and Land Development

2019

no. 43

28--40

Drought is one of the important phenomena resulting from variability and climate change. It has negative effects on all economic, agricultural and social sectors. The objective of this study is to rapidly detect climate dryness situations on an annual scale at the Mellah catchment (Northeast Algeria) for periods ranging from 31 years through the calculation of: the standardized precipitation index (SPI), the standardized Streamflow index (SSFI), the standardized temperature index (STI). Calculations made it possible to locate periods of drought more precisely by their intensity, duration and frequency, and detect years of breaks using the tests of Pettitt, rang, Lee and Heghinian, Hubert and Buishand. The use of the statistical tests for the rainfall series analyzed show all breaks, the majority of which are in 1996/1997 and 2001/2002. For the temperatures the breaks are situated in 1980/1981.

Susza jest jednym z ważnych zjawisk wywoływanych zmianami klimatu. Wywiera ujemny wpływ na gospodarkę, rolnictwo i społeczeństwo. Celem przedstawionych badań było śledzenie sytuacji suszy klimatycznej w skali roku w zlewni Mellah (północnowschodnia Algieria) w ciągu 31 lat przez obliczenia: standaryzowanego wskaźnika opadu (SPI), standaryzowanego wskaźnika przepływu (SSFI) i standaryzowanego wskaźnika temperatury (STI). Obliczenia z zastosowaniem testów Petitta, rang, Lee i Heghiniana oraz Huberta i Buishanda umożliwiły dokładniejsze ustalenie okresów suszy przez analizę intensywności, czasu trwania i częstotliwości, umożliwiły też wykrycie lat przerw w ciągach suszy. Dzięki testom statystycznym dla serii analizowanych opadów wykazano okresy przerw, głównie w latach 1996/1997 i 2001/2002. Dane temperaturowe wskazywały na okresy przerw w latach 1980/1981.

Suspended sediment discharge modeling during flood events using two different artificial neural network algorithms

Bouguerra Hamza, Tachi Salah-Eddine, Derdous Oussama, Bouanani Abderrazak, Khanchoul Kamel

Acta Geophysica

2019

Vol. 67, no. 6

1649--1660

This paper presents modeling of artificial neural network (ANN) to forecast the suspended sediment discharges (SSD) during flood events in two different catchments in the Seybouse basin, northeastern Algeria. This study was carried out on hourly SSD and water discharge data during flood events from a period of 31 years in the Ressoul catchment and of 28 years in the Mellah catchment. The ANNs were trained according to two different algorithms: the Levenberg–Marquardt algorithm (LM) and the Quasi-Newton algorithm (BFGS). Seven input combinations were trained for the SSD prediction. The performance results indicated that both algorithms provided satisfactory simulations according to the determination coefficient (R2) and root mean squared error (RMSE) performance criteria, with priority to the BFGS algorithm; the coefficient of determination using the LM algorithm varies between 51.0 and 90.2%, whereas using the BFGS algorithm it varies between 54.3 and 93.5% in both studied catchments, with calculated improvement for all seven developed networks with the best improvement in the Ressoul catchment presented in ANN06 with ΔR2 4.23% and ΔRMSE 1.74‰, and with the best improvement presented in ANN05 with ΔR2 6.07% and ΔRMSE 0.71‰ in the Mellah catchment. The analysis showed that the use of Quasi-Newton method performed better than the Levenberg–Marquardt in both studied areas.