Time series analysis of wind speed using VAR and the generalized impulse response technique

Abstract. Lowland rivers and shallow aquifers are closely coupled and their interactions are crucial for maintaining healthy stream ecological functions. In order to explore river–aquifer interactions and lowland hydrological system in three Belgian catchments, we apply a combined approach of baseflow separation, impulse response modelling and time series analysis over a 30–year study period at catchment scale. Baseflow from hydrograph separation shows that the three catchments are groundwater-dominated. The recursive digital filter methods generate a smoother baseflow time series than the graphical methods, and yield more reliable results than the graphical ones. Impulse response modelling is applied with a two–step procedure. The first step where groundwater level response is modelled shows that groundwater level in shallow aquifers reacts fast to the system input, with most of the wells reaching their peak response during the first day. There is an overall trend of faster response time and higher response magnitude in the wet (October–March) than the dry (April–September) periods. The second step of baseflow response modelling shows that the system response is also fast and that simulated baseflow can capture some variations but not the peaks of the separated baseflow time series. The time series analysis indicates that components such as interflow and overland flow, contribute significantly to stream flow. They are somehow included as part of the separated baseflow, which is likely to be overestimated from hydrograph separation. The impulse response modelling approach from the groundwater flow perspective can be an optional method to estimate the baseflow, since it considers some level of the physical connection between river and aquifer in the subsurface. Further research is however recommended to improve the simulation, such as giving more weight to wells close to the river and adding more drainage dynamics to the model input.

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Weather Forecasting in Coastal Districts of Odisha and Andhra Pradesh by Using Time Series Analysis

International Journal of Emerging Research in Management and Technology ◽

10.23956/ijermt.v6i8.122 ◽

2018 ◽

Vol 6 (8) ◽

pp. 85

Author(s):

Naresh Patnaik ◽

F Baliarsingh

Keyword(s):

Time Series ◽

Wind Speed ◽

Relative Humidity ◽

Solar Radiation ◽

Time Series Analysis ◽

Andhra Pradesh ◽

Maximum Temperature ◽

Climatic Parameters ◽

Series Analysis ◽

Annual Maximum Temperature

Climate change in world is always one of the most important topics in Water Resources. Now the issue is so predominant that it is gradually restricting out social life, peace and harmony. Climate change is a change in the statistical distribution of weather pattern of an area, when such changes occur for a long period of time. Weather is the state of atmosphere at a particular place and time. Climate is the long term statistical expression of short term weather. This study presents a comprehensive assessment of the future climate pattern/weather prediction by taking different climatic parameters such as temperature, precipitation, solar radiation, wind speed and relative humidity by using time series analysis. The study area of research work covers the coastal districts of Odisha and some parts of Andhra Pradesh. The climatic parameters are collected over last 20 years (1993-2013) from the selected 10 stations and the prediction is made using Time Series Analysis (ARIMA Model). The annual maximum temperature, solar radiation of all districts indicates a statistically significant increase in trend, whereas in the case of wind speed and relative humidity indicates significant deceasing trend. The annual rain fall shows an increasing trend of 2.69 mm/year in all station except Srikakulam, Khordha, Jagatsinghpur and Balasore which shows a decreasing trend of 1.94, 1.29, 0.56 and 1.18 mm/year respectively. As a whole the annual maximum temperature and solar radiation shows an increase trend of 0.16 ⁰C and 0.073 MJ/m² per year respectively. Further the wind speed and relative humidity of all stations indicates a decreasing trend of 0.056 m/s and 0.003(Units in fraction) per year respectively.

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