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Pathfinding is an essential part of many applications, including video games and robot navigation. A pathfinding algorithm usually finds a path from the given starting point to the endpoint. Many different implementations of pathfinding solutions exist in the industry. One of the most known and used of these algorithms is A*. A* will find the shortest path from the starting point to the endpoint. Classic A* algorithm can guarantee the shortest path to the desired destination which was introduced in 1968 by Hart, Nilsson, and Raphael. A* is widely used in the game industry to solve the shortest path problem. The A* algorithm utilizes two data structures. A* explores the nodes in the graph from the start position one by one and assign them a value of F which is the sum of G cost and H cost. G Cost is the actual cost of exploring the node from the starting position to the current node, and H cost is the estimation of the cost of from the current node to the goal node. The Open List keeps all of the nodes that are not explored at each iteration of the algorithm. In each iteration, the algorithm removes the node with the least value of F cost and run the algorithm. If the node is not the goal, it will be added to the closed list. Interactions with the open list, which are insert (current node) and remove Min, are the costliest part of the algorithm. It is well known that using a priority queue will increase the performance of this algorithm. A number of priority queues have been used to implement A* and improve the performance of this algorithm. We propose to use a Lazy binary heap and evaluate its performance compared to other data structures. We expect that due to decreasing the size of the current open list, it will outperform other binary heaps.

International audience

International audience

Hydrological models have been widely used to assess changes in stream discharges by climate change; however, concern might arise on the accurateness of the model predictions under the changed conditions particularly during low flow periods. In this study, two spatially distributed hydrological models MIKE SHE and WetSpa, each representing a different model complexity in terms of process description, data needs, parameter space, degree of calibration, were compared in their estimation of the climate change impact on the flow regimes in a medium-sized catchment in Belgium. The fully integrated, physically based MIKE SHE model, comprising a three-dimensional groundwater flow and river model, was applied to better understand the groundwater flow and groundwater–river interactions under changed climate conditions. Both models were able to capture the flow dynamics very well with high efficiencies and simulated the flow extremes very accurately. The groundwater heads in MIKE SHE and their seasonal variation had a high model performance. The two models simulated similar changes to future flows because of climatic changes. Peak flows were expected to increase or decrease depending, taking the large uncertainty in future climate trends into account. The model structural uncertainties on these high flow predictions were rather limited. Low flows were expected to reduce because of drier conditions by future climate change, indicating elevated low flow risks for Belgium. However, the projected low flow changes differed significantly over the models and even exceeded the uncertainty by the expected climate trends. Smaller impact was predicted by considering the groundwater physics and river interaction in the MIKE SHE model. These changes to the surface water regimes were verified by the changes in groundwater heads. Future groundwater conditions also point towards drier conditions with a small decrease in heads for future summer and autumn periods. Projected variations in winter heads depend on the climate scenario.

Potential effects of climate change on streamflow and soil moisture in Vermilion basin, Illinois, USA, are investigated using a spatial distributed hydrological model (WetSpa). The model results show a good agreement between observed and simulated discharge at Leonore gauge station and soil moisture at Stelle soil moisture recording site. Climate scenarios are derived by statistical downscaling of regional climate predictor variables for two climate scenarios and four time periods. The downscaled local climate variables are used as inputs to the WetSpa model. The results of the hydrological simulations show that streamflow in the Vermilion basin may decrease substantially, especially in summer as a result of less precipitation but mainly due to increased evapotranspiration. Predictions also indicate that reduced precipitation in summer combined with a substantial increase in evaporative demand may lead to soil moisture deficits in the fall, which could have a negative impact on the natural vegetation and rainfed crop growth.

Spatial and temporal variations in soil water content have important effects in different hydrological processes as flood forecasting, plant water availability, groundwater recharge, etc. This study investigates the ability of Water and Energy Transfer between Soil, Plant and Atmosphere (WetSpa) model for prediction of soil moisture in a catchment. WetSpa is applied on the Vermilion catchment, Illinois for which soil moisture was continuously monitored at a particular site. We used WetSpa in 3 cases: (1) the model was first calibrated for a 2 years period by comparing observed and simulated daily hydrographs, (2) the model was validated using 4 years daily data, and (3) soil moisture was simulated at the measuring site and compared to total observed soil water content in the 80 cm root zone. The model simulated daily stream flows with a Nash-Sutcliffe efficiency of 0.79 during calibration, and 0.73 for the validation period. The performance of the model to predict soil moisture was quantified by 3 statisticalparameters, i.e. a mean absolute error of 26.8 mm, a root mean square error of 30.2 mm, and an index of agreement of 0.84. This shows that measured and simulated soil moisture are in a good accordance and model results are promising.