Flow Trend Analysis in the Rouge River Watershed and the Effect of Temporal Resolution on Trend Detection

Author(s):  
C. A. Rohrer ◽  
C. L. Hughes
2002 ◽  
Vol 2002 (2) ◽  
pp. 1053-1078
Author(s):  
Kelly A. Cave ◽  
Nancy J. Andrews ◽  
James W. Ridgway

2004 ◽  
Vol 2004 (4) ◽  
pp. 1645-1670
Author(s):  
Colleen Hughes ◽  
Joe Rathbun ◽  
Edward Kluitenberg ◽  
Kelly Cave ◽  
Chris Catalfio

2020 ◽  
Author(s):  
Kokeb Zena ◽  
Tamene Adugna ◽  
Fekadu Fufa

Abstract Background: Trend and variability analysis of precipitation and stream flow series provides valuable information to understand hydrological changes associated with climate variability. In this study, annual and seasonal trends of precipitation and stream flow series and their relationship was investigated over the Modjo river watershed. The Mann-Kendall test and Sen’s slope estimator were used for trend analysis and evaluation of its magnitude respectively, with an approach that corrects the serial correlation. The Pearson correlation analysis was also applied to evaluate the relationships between river flow and precipitation series.Results: the mean and maximum stream flow series showed downward trends at the annual and kiremt time series, whereas no significant trend was observed for the minimum flow over the Modjo watershed. The study indicated that the mean annual and kiremt (monsoon) stream flow decreased significantly at a rate of 8.262 and 6.528 m3s-1per year respectively. In contrary to the river flow, there is no positive or negative trend in the annual and seasonal precipitation series although the tendency was towards increasing trends. It was evidenced that the annual, and kiremt season river flow series was affected abruptly since 2000, however for the same analysis period there was no evidence of changes in precipitation events, which is also not related significantly with the variability of river flow during the analysis period.Conclusions: the river flow decreased dramatically in the Modjo watershed during the analysis period (1981-2015), however it was not primarily associated significantly with climate variability (precipitation & temperature). The result suggests the need of considering the unplanned water extraction and the poor land use management practices to sustain and restore river flow trend observed in the watershed.


2017 ◽  
Author(s):  
Marcos R. C. Cordeiro ◽  
Jason A. Vanrobaeys ◽  
Henry F. Wilson

Abstract. Lack of long-term datasets in fine temporal resolution hinders environmental studies and modelling efforts; to address this issue in the La Salle River watershed, in Canada, long-term weather (1990–2013), hydrometric (1990–2013 except years with no or poor data), and water chemistry (2009–2013) datasets were developed. The weather variables consisted of temperature, relative humidity, wind speed, solar radiation, and precipitation in an hourly time-step, which is required for physically-based modelling. The only hydrometric variable included in the dataset was stream discharge in a daily time-step, which is the usual time-frame for summarizing the results of long-term studies. The water chemistry data consisted of total nitrogen (TN), total dissolved nitrogen (TDN), total phosphorus (TP) and total dissolved phosphorus (TDP). Samples were collected weekly during the open water season at the same site as they hydrometric gauging station (05OG008) starting in August 2009 until October 2012 with some gaps (i.e. Fall 2011, Spring 2012, September 2012). In 2013 the frequency of sampling was increased to daily or sub-daily during high stream discharge and weekly during low stream discharge. An overview of the data indicates that values and trends are within ranges reported in the literature for the region. Mean annual, winter, and summer temperatures were 3.5 °C–10.7 °C and 17.2 °C, respectively. Annual relative humidity averaged 73.1 % but tended to be higher and more homogenous in cold seasons. Wind speed was very similar over the different seasons with annual average of 4.3 m/s. Solar radiation followed the typical curve reported for western Canada, with peak daily average values around 250 W/m2 in July. The precipitation records were mostly comprised of dry hours and the characteristic precipitation pattern of the Canadian Prairies with high frequency of small precipitation events as observed, with 75.3 % of the hourly precipitation being equal or less than 2 mm/h. The hydrometric characteristics of the dataset were also typical of the Canadian Prairies; the average peak discharge over the entire period was larger in April (2.3 m3/s) due to large amounts of snowmelt runoff. The average concentrations of TN, TDN, TP and TDP of 1.54, 1.35, 0.56, and 0.49 mg/L, respectively, were in agreement with values found in previous studies at the same location. The datasets for weather (https://doi.org/10.23684/ODI-2017-00957), discharge (https://doi.org/10.23684/ODI-2017-00959) and water chemistry (https://doi.org/10.23684/ODI-2017-00958) are accessible through the Government of Canada's Open Data portal (http://open.canada.ca).


2021 ◽  
Author(s):  
Nejc Bezak ◽  
Pasquale Borrelli ◽  
Panos Panagos

Abstract. Despite recent developments in modelling global soil erosion by water, to date no substantial progress has been made towards more dynamic inter- and intra-annual assessments. In this regard, the main challenge is still represented by the limited availability of high temporal resolution rainfall data needed to estimate rainstorms rainfall erosivity. As this data scarcity is likely to characterize the upcoming years, the suitability of alternative approaches to estimate global rainfall erosivity using satellite-based rainfall data was explored. For this purpose, the high spatial and temporal resolution global precipitation estimates obtained with the NOAA CDR Climate Prediction Center MORPHing technique (CMORPH) were used. Alternatively, the erosivity density (ED) concept was used to estimate global rainfall erosivity as well. The obtained global estimates of rainfall erosivity were validated against the pluviograph data included in the Global Rainfall Erosivity Database (GloREDa). Overall, results indicated that the CMORPH estimates have a marked tendency to underestimate rainfall erosivity when compared to the GloREDa estimates. The most substantial underestimations were observed in areas with the highest rainfall erosivity values. At continental level, the best agreement between annual CMORPH and interpolated GloREDa rainfall erosivity map was observed in Europe. Worse agreement was detected for Africa and South America. Further analyses conducted at monthly scale for Europe revealed seasonal misalignments, with the occurrence of underestimation of the CMORPH estimates in the summer period and overestimation in the winter period compared to GloREDa. The best agreement between the two approaches to estimate rainfall erosivity was found for autumn, especially in Central and Eastern Europe. Conducted analysis suggested that satellite-based approaches for estimation of rainfall erosivity appear to be more suitable for low-erosivity regions, while in high erosivity regions and seasons (> 1,000–2,000 MJ mm ha−1 h−1 yr−1), the agreement with estimates obtained from pluviograph data such as GloREDa is lower. Concerning the ED estimates, this second approach to estimate rainfall erosivity yielded better agreement with GloREDa estimates compared to CMORPH. The application of a simple-linear function correction of the CMORPH data was applied to provide better fit to the GloREDa and correct systematic underestimation. This correction improved the performance of the CMORPH but in areas with the highest rainfall erosivity rates the underestimation was still observed. A preliminary trend analysis of the CMORPH rainfall erosivity estimates was also performed for the 1998–2019 period. According to this trend analysis, increasing and statistically significant trend was more frequently observed than decreasing trend.


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