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[Abstract:] Hydrological and sediment dynamics have changed considerably on the Chinese Loess Plateau during the last six decades due to large scale land use changes and numerous water regulation actions. Understanding the mechanism of sediment transport change and its effects is of great importance to food and environmental security. Numerical approaches are useful to map and assess spatio-temporal patterns in sediment dynamics. This study evaluates monthly and annual sediment connectivity in the Wei River Basin (134,800 km2) at the basin and sub-basin scales using the aggregated index of sediment connectivity (AIC). For the first time, this index is applied on this relatively large regional scale. The two objectives were to (1) evaluate the performance of the AIC at the regional scale, addressing substantial differences among areas, and (2) analyze how each AIC sub-factor co-determines the monthly sediment and connectivity patterns. Results show that AIC has strong or moderate positive correlation with sediment yield from 15 out of 23 stations in the Wei and Jing sub-basin. The Jing sub-basin has the highest sediment connectivity due to degraded vegetation, while the Beiluo sub-basin has the lowest sediment connectivity on average due to better ecological restoration. Within the year, sediment connectivity is highest in April and lowest in January, due to the rainfall regime and intra-annual land cover variations. Among the AIC factors, the rainfall factor has the highest effect on sediment connectivity, implying that functional connectivity (graded by rainfall and soil cover) determines sediment dynamics more than structural connectivity (mainly determined by topography and soil permeability). This study provides one of the first large-scale estimates of spatial and temporal sediment connectivity from hillslopes to river stream and including large reservoirs, which can be further employed to implement regional ecological construction works and environmental catch

Scenarios serve science by testing the sensitivity of a system and/or society to adapt to the future. In this study, we present a new land use scenario methodology called ScenaLand. This methodology aims to develop plausible and contrasting land use and management (LUM) scenarios, useful to explore how LUM (e.g. soil and water conservation techniques) may affect ecosystem services under global change in a wide range of environments. ScenaLand is a method for constructing narrative and spatially explicit land use scenarios that are useful for end-users and impact modellers. This method is innovative because it merges literature and expert knowledge, and its low data requirement makes it easy to be implemented in the context of inter-site comparison, including global change projections. ScenaLand was developed and tested on six different Mediterranean agroecological and socioeconomic contexts during the MASCC research project (Mediterranean agricultural soil conservation under global change). The method first highlights the socioeconomic trends of each study site including emerging trends such as new government laws, LUM techniques through a qualitative survey addressed to local experts. Then, the method includes a ranking of driving factors, a matrix about land use evolution, and soil and water conservation techniques. ScenaLand also includes a framework to develop narratives along with two priority axes (contextualized to environmental protection vs. land productivity in this study). In the context of this research project, four contrasting scenarios are proposed: S1 (business-as-usual), S2 (market-oriented), S3 (environmental protection), and S4 (sustainable). Land use maps are then built with the creation of LUM allocation rules based on agroecological zoning. ScenaLand resulted in a robust and easy method to apply with the creation of 24 contrasted scenarios. These scenarios come not only with narratives but also with spatially explicit maps that are potentially

Healthy soils are fundamental for sustainable agriculture. Soil Improving Cropping Systems (SICS) aim to make land use and food production more sustainable. To evaluate the effect of SICS at EU scale, a modelling approach was taken. This study simulated the effects of SICS on two principal indicators of soil health (Soil Organic Carbon stocks) and land degradation (soil erosion) across Europe using the spatially explicit PESERA model. Four scenarios with varying levels and combinations of cover crops, mulching, soil compaction alleviation and minimum tillage were implemented and simulated until 2050. Results showed that while in the scenario without SICS, erosion slightly increased on average across Europe, it significantly decreased in the scenario with the highest level of SICS applied, especially in the cropping areas in the central European Loess Belt. Regarding SOC stocks, the simulations show a substantial decrease for the scenario without SICS and a slight overall decrease for the medium level scenario and the scenario with a mix of high, medium and no SICS. The scenario with a high level of SICS implementation showed an overall increase in SOC stocks across Europe. Potential future improvements include incorporating dynamic land use, climate change and an optimal spatial allocation of SICS.

Wildfires have become an increasing threat for Mediterranean ecosystems, due to increasing climate change-induced wildfire activity and changing land management practices. In addition to the initial risk, wildfires can alter the soil in various ways—depending on fire severity—and cause enhanced post-fire erosion. Usually, post-fire erosion studies focus on a short time window and lack the attention for sediment dynamics at larger spatial scales. Yet, these large spatial and temporal scales are fundamental for a better understanding of long-term destructive effects of multiple recurring wildfires on post-fire erosion processes and catchment sediment dynamics. In this study the landscape evolution model LAPSUS was used to simulate erosion and deposition in the 404 km2 Águeda catchment in north-central Portugal over a 41-year (1979–2020) timespan, including eight wildfires each burning >1000 ha. To include variation in fire severity and its impact on the soil, four burn severity classes, represented by the difference normalized burn ratio (dNBR), were parameterized. Although model calibration was difficult due to lack of spatial and temporal measured data, the results show that long-term post-fire net erosion rates were significantly higher in the wildfire scenarios (5.95 ton ha−1 yr−1) compared to those of a non-wildfire scenario (0.58 ton ha−1 yr−1). Furthermore, erosion values increased with burn severity and multiple wildfires increased the overall catchment sediment build-up. Simulated erosion patterns showed great spatial variability, with large deposition and erosion rates inside streams. This variability made it difficult to identify land uses that were most sensitive for post-fire erosion, because some land uses were located in more erosion-sensitive areas (e.g. streams, gullies) or were more affected by high burn severity levels than others. Despite these limitations, LAPSUS performed well on addressing spatial sediment processes and can contribute to pre-fir