Using a spatio-temporal dynamic state-space model with the EM algorithm to patch gaps in daily riverflow series, with examples from the Volta Basin, West Africa

International audienceA spatio-temporal linear dynamic model has been developed for patching short gaps in daily river runoff series. The model was cast in a state-space form in which the state variable was estimated using the Kalman smoother (RTS smoother). The EM algorithm was used to concurrently estimate both parameter and missing runoff values. Application of the model to daily runoff series in the Volta Basin of West Africa showed that the model was capable of providing good estimates of missing runoff values at a gauging station from the remaining series at the station and at spatially correlated stations in the same sub-basin

Effect of seasonal dynamics of vegetation cover on land surface models: a case study of NOAH LSM over a savanna farm land in eastern Burkina Faso, West Africa

International audienceThe sensitivity of the land surface model of the National Centers for Environmental Prediction (NCEP), the Oregon State University, the Air Force and the Hydrologic Research Lab (NOAH LSM) was evaluated with respect to the seasonal dynamics of the vegetation cover in the savanna area under intensive agriculture in the eastern part of Burkina Faso, West Africa. The data collected during the first long-term measurement of the surface fluxes in this mentioned region was used for this purpose. The choice of NOAH LSM was motivated by the fact that it has already been tested in different environments in West Africa, especially in Ghana. The sensitivity was tested by comparing the simulated surfaces fluxes using a fixed values of the roughness length for momentum as a standard in the model and the true seasonal value of this variable. The results show that NOAH LSM was not sensitive to the change of the roughness length for momentum neither on a seasonal basis nor on a daily basis, which was found to be abnormal. The formulation of the coefficient (Bc) coupling the dry canopy transpiration to the atmosphere was found to be the main reason for this. An improved formulation for this coefficient was given to solve this insensitivity and to improve the performance of the model. Recommendations are also given to enhance the performance of the model in the West African savanna environment

Critical scales to explain urban hydrological response: An application in Cranbrook, London

Rainfall variability in space and time, in relation to catchment characteristics and model complexity, plays an important role in explaining the sensitivity of hydrological response in urban areas. In this work we present a new approach to classify rainfall variability in space and time and we use this classification to investigate rainfall aggregation effects on urban hydrological response. Nine rainfall events, measured with a dual polarimetric X-Band radar instrument at the CAESAR site (Cabauw Experimental Site for Atmospheric Research, NL), were aggregated in time and space in order to obtain different resolution combinations. The aim of this work was to investigate the influence that rainfall and catchment scales have on hydrological response in urban areas. Three dimensionless scaling factors were introduced to investigate the interactions between rainfall and catchment scale and rainfall input resolution in relation to the performance of the model. Results showed that (1) rainfall classification based on cluster identification well represents the storm core, (2) aggregation effects are stronger for rainfall than flow, (3) model complexity does not have a strong influence compared to catchment and rainfall scales for this case study, and (4) scaling factors allow the adequate rainfall resolution to be selected to obtain a given level of accuracy in the calculation of hydrological response

The Influence of Rainfall and Catchment Critical Scales on Urban Hydrological Response Sensitivity

Interactions between spatial and temporal variability of rainfall and catchment characteristics strongly influence hydrological response. In urban areas, where runoff generation is fast due to high imperviousness degree, it is especially relevant to capture the high spatiotemporal rainfall variability. Significant progress has been made in the development of spatially distributed rainfall measurements and of distributed hydrological models, to represent the variability of catchment's characteristics. Interactions between rainfall and basin scales on hydrological response sensitivity, however, needs deeper investigation. A previous study investigated the hydrological response in the small urbanized catchment of Cranbrook (8 km2, London, UK) and proposed three dimensionless “scale factors” to identify if the available rainfall resolution is sufficient to properly predict hydrological response. We aim to verify the applicability of these scale factors to larger scales, with a distinct physiographic setting, in Little Sugar Creek (111 km2, Charlotte, USA), to identify the required rainfall resolution and to predict model performance. Twenty-eight events were selected from a weather radar data set from the National Weather Radar Network, with a resolution of 1 km2 and 15 min. Rainfall data were aggregated to coarser resolutions and used as input for a distributed hydrological model. Results show that scale factors and associated thresholds are generally applicable for characterization of urban flood response to rainfall across spatiotemporal scales. Additionally, application of scale factors in observation-based analysis supports identification of event characteristics that are poorly captured and critical improvements that need to be made before the model can benefit from high-resolution rainfall

Using a spatio-temporal dynamic state-space model with the EM algorithm to patch gaps in daily riverflow series

A spatio-temporal linear dynamic model has been developed for patching short gaps in daily river runoff series. The model was cast in a state-space form in which the state variable was estimated using the Kalman smoother (RTS smoother). The EM algorithm was used to concurrently estimate both parameter and missing runoff values. Application of the model to daily runoff series in the Volta Basin of West Africa showed that the model was capable of providing good estimates of missing runoff values at a gauging station from the remaining time series at the station and at spatially correlated stations in the same sub-basin

Tree rainfall interception measured by stem compression

A method for measuring whole-tree interception of precipitation is presented which employs mechanical displacement sensors to measure trunk compression caused by the water captured by the tree. This direct and nondestructive method is demonstrated to be sensitive to less than 5 kg of interception field tests in Netherlands and Ghana.Keywords: tree mass change, interception, vegetation waterKeywords: tree mass change, interception, vegetation wate

A distributed stream temperature model using high resolution temperature observations

International audienceDistributed temperature data are used as input and as calibration data for an energy based temperature model of a first order stream in Luxembourg. A DTS (Distributed Temperature Sensing) system with a fiber optic cable of 1500 m was used to measure stream water temperature with 1 m resolution each 2 min. Four groundwater inflows were identified and quantified (both temperature and relative discharge). The temperature model calculates the total energy balance including solar radiation (with shading effects), longwave radiation, latent heat, sensible heat and river bed conduction. The simulated temperature is compared with the observed temperature at all points along the stream. Knowledge of the lateral inflow appears to be crucial to simulate the temperature distribution and conversely, that stream temperature can be used successfully to identify sources of lateral inflow. The DTS fiber optic is an excellent tool to provide this knowledge

Citizen science flow – an assessment of simple streamflow measurement methods

Wise management of water resources requires data. Nevertheless, the amount of streamflow data being collected globally continues to decline. Generating hydrologic data together with citizen scientists can help fill this growing hydrological data gap. Our aim herein was to (1) perform an initial evaluation of three simple streamflow measurement methods (i.e., float, salt dilution, and Bernoulli run-up), (2) evaluate the same three methods with citizen scientists, and (3) apply the preferred method at more sites with more people. For computing errors, we used midsection measurements from an acoustic Doppler velocimeter as reference flows. First, we (authors) performed 20 evaluation measurements in headwater catchments of the Kathmandu Valley, Nepal. Reference flows ranged from 6.4 to 240&thinsp;L&thinsp;s−1. Absolute errors averaged 23&thinsp;%, 15&thinsp;%, and 37&thinsp;% with average biases of 8&thinsp;%, 6&thinsp;%, and 26&thinsp;% for float, salt dilution, and Bernoulli methods, respectively. Second, we evaluated the same three methods at 15 sites in two watersheds within the Kathmandu Valley with 10 groups of citizen scientists (three to four members each) and one “expert” group (authors). At each site, each group performed three simple methods; experts also performed SonTek FlowTracker midsection reference measurements (ranging from 4.2 to 896&thinsp;L&thinsp;s−1). For float, salt dilution, and Bernoulli methods, absolute errors averaged 41&thinsp;%, 21&thinsp;%, and 43&thinsp;% for experts and 63&thinsp;%, 28&thinsp;%, and 131&thinsp;% for citizen scientists, while biases averaged 41&thinsp;%, 19&thinsp;%, and 40&thinsp;% for experts and 52&thinsp;%, 7&thinsp;%, and 127&thinsp;% for citizen scientists, respectively. Based on these results, we selected salt dilution as the preferred method. Finally, we performed larger-scale pilot testing in week-long pre- and post-monsoon Citizen Science Flow campaigns involving 25 and 37 citizen scientists, respectively. Observed flows (n=131 pre-monsoon; n=133 post-monsoon) were distributed among the 10 headwater catchments of the Kathmandu Valley and ranged from 0.4 to 425&thinsp;L&thinsp;s−1 and from 1.1 to 1804&thinsp;L&thinsp;s−1 in pre- and post-monsoon, respectively. Future work should further evaluate uncertainties of citizen science salt dilution measurements, the feasibility of their application to larger regions, and the information content of additional streamflow data.</p