Abstract. Event-based landslide inventories are important for analyzing the relationship between the intensity of the trigger (e.g. rainfall, earthquake) and the density of the landslides in a particular area, as a basis for the estimation of the landslide probability and the conversion of susceptibility maps into hazard maps required for risk assessment. They are also crucial for the establishment of local rainfall thresholds that are the basis of Early Warning Systems, and for evaluating which land use/land cover changes are related to landslide occurrence. The completeness and accuracy of event-based landslide inventories are crucial aspects to derive at reliable results or the above types of analysis. In this study we generated a relatively complete landslide inventory for the 2018 Monsoon landslide event in the state of Kerala, India, based on two inventories that were generated using different methods: one based on Object Based Image Analysis (OBIA) and the other on field surveys of damaging landslides. We used a collaborative mapping approach based on the visual interpretation of pre-and post-event high-resolution satellite images available in Google Earth, adjusted the two inventories and digitize landslides that were missed in the two inventories. The reconstructed landslide inventory database contains 4728 landslides consisting of 2477 landslides mapped by OBIA method, 973 landslides mapped by field survey, 422 landslides mapped both by OBIA and field method and an additional 856 landslides mapped using the visual image (GE) interpretation. The dataset is available at https://doi.org/10.17026/dans-x6c-y7x2 (van Westen, 2020). Also, the location of the landslides was adjusted, based on the image interpretation, and the initiation points were used to evaluate the land use/land cover changes as a causal factor for the 2018 Monsoon landslides. A total of 45 % of the landslides that damaged buildings occurred due to cut-slope failure while 34 % of those impacting on roads were due to road cut-slope failures. The resulting landslide inventory is made available for further studies.

Increased sedimentation is the main problem that affects dam efficiency by reducing storage capacity. Planning for dam construction and maintenance requires design strategies that heavily depend on integrated basin models, properly identifying principal sediment origins within the watershed and qualifying the sediment production rate. In this research work, the physically-based watershed SWAT model, defined as the Soil and Water Assessment Tool, was used to estimate the rate of sediment production for future dams in the Tata basin, located in southeast Morocco. The model was calibrated and tested for uncertainty by the employment of the algorithm Sequential Uncertainty Fitting-2. The outputs were used for assessing critical sediment source areas. Calibration and validation of the model were performed by monthly data. The values for Nash–Sutcliffe efficiency coefficient, Percent bias coefficient and determination coefficient (R2), respectively, during the calibration period 1990–1998 (0.96, −13% and 0.96) and the validation period 1999–2006 (0.77, + 11% and 0.93) indicate the accordance with the results obtained for the measured flow and the simulated flow values. The annual sediment yield of the Tata basin extends from 0 to 11 t/ha/y with a mean of 2.3 t/ha/y. The spatial distribution of these sediments varies from upstream to downstream. The downstream basin generated more sediment to the river per unit area, though it was less than the total amount of the basin for the upstream area. This variation is influenced by the increased downstream surface runoff and also by other characteristics of the basin such as slope and lithology. The low erosion places correspond to areas with lithological formations that are more resistant to erosion.

The backwater of Veli-Akkulam, adjoining the Arabian Sea in the south-west part of Indian Peninsula, is a coastal wetland system and forms an integral part of the local ecosystem. In addition to the usual marine interactions, this water body is subjected to anthropogenic interference due to their proximity to the Thiruvananthapuram City urban agglomeration. This paper showcases how an urban agglomeration alters wetland system located within a tropical monsoonal environment. Water samples from this lake together with different feeder streams reveal that the lake is under the threat to eutrophication. A spatio-temporal analysis has shown that the lake and adjacent wetlands are shrinking in a fast pace. Over a period of about seven decades, the lake has shrunk by 28.05 % and the wetlands by 37.81 %. And hence, there is a pressing requirement of ecomanagement practices to be adopted to protect this lake.

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