What Did Really Improve Our Mesoscale Hydrological Model? A Multidimensional Analysis Based on Real Observations

Modelers can improve a model by addressing the causes for the model errors (data errors and structural errors). This leads to implementing model enhancements (MEs), for example, meteorological data based on more monitoring stations, improved calibration data, and/or modifications in process formulations. However, deciding on which MEs to implement remains a matter of expert knowledge. After implementing multiple MEs, any improvement in model performance is not easily attributed, especially when considering different objectives or aspects of this improvement (e.g., better dynamics vs. reduced bias). We present an approach for comparing the effect of multiple MEs based on real observations and considering multiple objectives (MMEMO). A stepwise selection approach and structured plots help to address the multidimensionality of the problem. Tailored analyses allow a differentiated view on the effect of MEs and their interactions. MMEMO is applied to a case study employing the mesoscale hydro-sedimentological model WASA-SED for the Mediterranean-mountainous Is\ue1bena catchment, northeast Spain. The investigated seven MEs show diverse effects: some MEs (e.g., rainfall data) cause improvements for most objectives, while other MEs (e.g., land use data) only affect a few objectives or even decrease model performance. Interaction of MEs was observed for roughly half of the MEs, confirming the need to address them in the analysis. Calibration and increasing the temporal resolution showed by far stronger impact than any of the other MEs. The proposed framework can be adopted in other studies to analyze the effect of MEs and, thus, facilitate the identification and implementation of the most promising MEs for comparable cases

Spatial variability of the relationships of runoff and sediment yield with weather types throughout the Mediterranean basin

Soil degradation by water is a serious environmental problem worldwide, with specific climatic factors being the major causes. We investigated the relationships between synoptic atmospheric patterns (i.e. weather types, WTs) and runoff, erosion and sediment yield throughout the Mediterranean basin by analyzing a large database of natural rainfall events at 68 research sites in 9 countries. Principal Component Analysis (PCA) was used to identify spatial relationships of the different WTs including three hydro-sedimentary variables: rainfall, runoff, and sediment yield (SY, used to refer to both soil erosion measured at plot scale and sediment yield registered at catchment scale). The results indicated 4 spatial classes of rainfall and runoff: (a) northern sites dependent on North (N) and North West (NW) flows; (b) eastern sites dependent on E and NE flows; (c) southern sites dependent on S and SE flows; and, finally, (d) western sites dependent on W and SW flows. Conversely, three spatial classes are identified for SY characterized by: (a) N and NE flows in northern sites (b) E flows in eastern sites, and (c) W and SW flows in western sites. Most of the rainfall, runoff and SY occurred during a small number of daily events, and just a few WTs accounted for large percentages of the total. Our results confirm that characterization by WT improves understanding of the general conditions under which runoff and SY occur, and provides useful information for understanding the spatial variability of runoff, and SY throughout the Mediterranean basin. The approach used here could be useful to aid of the design of regional water management and soil conservation measures