Slopewash,surface runoff and fine-litter transport in forest and landslide scars in humid-tropical steeplands,luquillo experimental forest,Puerto Rico

Rainfall, slopewash (the erosion of soil particles), surface runoff and fine-litter transport steepland sites in the Luquillo Experimental Forest, Puerto Rico (18° 20’ N, 65° 45’ W) were measured from 1991 to 1995. Hillslopes underlain by (1) Cretaceous tuffaceous sandstone and silstone in subtropical rain (tanonuco) forest with vegetation recovering from Hurricane Hugo (1989), and (2) Tertiary quartz diorite in subtropical lower mantone wet (colorado and dwarf) forest with undisturbed forest canopy were compared to recent landslide scars. Monthly surface runoff on these very steep hillslopes (24° to 43°) was only 0·2 to 0·5 per cent of monthly rainfall. Slopewash was higher in sandy loam soils whose parent material is quartz diorite (averaging 46 g m⁻² a⁻¹) than in silty clay loam soils derived from tuffaceous sandstone and siltstone where the average was 9 g m⁻² a⁻¹. Annual slopewash of 100 to 349 g m⁻² on the surfaces of two recent, small landslide scars was measured initially but slopewash decreased to only 3 to 4 g m⁻² a⁻¹ by the end of the study. The mean annual mass of fine litter (mainly leaves and twigs) transported downslope at the forested sites ranged from 5 to 8 g m⁻² and was lower at the tabonuco forest site, where post-Hurricane Hugo recovery is still in progress. Mean annual fine-litter transport was 2·5 g m⁻² on the two landslide scars. Copyright © 1999 John Wiley & Sons, Ltd.     

Testing a model for predicting the timing and location of shallow landslide initiation in soil‐mantled landscapes

The growing availability of digital topographic data and the increased reliability of precipitation forecasts invite modelling efforts to predict the timing and location of shallow landslides in hilly and mountainous areas in order to reduce risk to an ever‐expanding human population. Here, we exploit a rare data set to develop and test such a model. In a 1·7 km² catchment a near‐annual aerial photographic coverage records just three single storm events over a 45 year period that produced multiple landslides. Such data enable us to test model performance by running the entire rainfall time series and determine whether just those three storms are correctly detected. To do this, we link a dynamic and spatially distributed shallow subsurface runoff model (similar to TOPMODEL) to an in?nite slope model to predict the spatial distribution of shallow landsliding. The spatial distribution of soil depth, a strong control on local landsliding, is predicted from a process‐based model. Because of its common availability, daily rainfall data were used to drive the model. Topographic data were derived from digitized 1 : 24 000 US Geological Survey contour maps. Analysis of the landslides shows that 97 occurred in 1955, 37 in 1982 and ?ve in 1998, although the heaviest rainfall was in 1982. Furthermore, intensity–duration analysis of available daily and hourly rainfall from the closest raingauges does not discriminate those three storms from others that did not generate failures. We explore the question of whether a mechanistic modelling approach is better able to identify landslide‐producing storms. Landslide and soil production parameters were ?xed from studies elsewhere. Four hydrologic parameters characterizing the saturated hydraulic conductivity of the soil and underlying bedrock and its decline with depth were ?rst calibrated on the 1955 landslide record. Success was characterized as the most number of actual landslides predicted with the least amount of total area predicted to be unstable. Because landslide area was consistently overpredicted, a threshold catchment area of predicted slope instability was used to de?ne whether a rainstorm was a signi?cant landslide producer. Many combinations of the four hydrological parameters performed equally well for the 1955 event, but only one combination successfully identi?ed the 1982 storm as the only landslide‐producing storm during the period 1980–86. Application of this parameter combination to the entire 45 year record successfully identi?ed the three events, but also predicted that two other landslide‐producing events should have occurred. This performance is signi?cantly better than the empirical intensity–duration threshold approach, but requires considerable calibration effort. Overprediction of instability, both for storms that produced landslides and for non‐producing storms, appears to arise from at least four causes: (1) coarse rainfall data time scale and inability to document short rainfall bursts and predict pressure wave response; (2) absence of local rainfall data; (3) legacy effect of previous landslides; and (4) inaccurate topographic and soil property data. Greater resolution of spatial and rainfall data, as well as topographic data, coupled with systematic documentation of landslides to create time series to test models, should lead to signi?cant improvements in shallow landslides forecasting. Copyright © 2003 John Wiley & Sons, Ltd.     

Rainfall thresholds for shallow landsliding derived from pressure‐head monitoring: cases with permeable and impermeable bedrocks in Boso Peninsula,Japan

Rainfall thresholds for shallow landslide initiation were determined for hillslopes with two types of bedrock, permeable sandstone and impermeable mudstone, in the Boso Peninsula, Japan. The pressure‐head response to rainfall was monitored above a slip scarp due to earlier landslides. Multiple regression analysis estimated the rainfall thresholds for landsliding from the relation between the magnitude of the rainfall event and slope instability caused by the increased pressure heads. The thresholds were expressed as critical combinations of rainfall intensity and duration, incorporating the geotechnical properties of the hillslope materials and also the slope hydrological processes. The permeable sandstone hillslope has a greater critical rainfall and hence a longer recurrence interval than the impermeable mudstone hillslope. This implies a lower potential for landsliding in sandstone hillslopes, corresponding to lower landslide activity. Copyright © 2007 John Wiley & Sons, Ltd.     

A regime shift in sediment export from a coastal watershed during a record wet winter,California: Implications for landscape response to hydroclimatic extremes

Small, steep watersheds are prolific sediment sources from which sediment flux is highly sensitive to climatic changes. Storm intensity and frequency are widely expected to increase during the 21st century, and so assessing the response of small, steep watersheds to extreme rainfall is essential to understanding landscape response to climate change. During record winter rainfall in 2016–2017, the San Lorenzo River, coastal California, had nine flow peaks representing 2–10‐year flood magnitudes. By the third flood, fluvial suspended sediment showed a regime shift to greater and coarser sediment supply, coincident with numerous landslides in the watershed. Even with no singular catastrophic flood, these flows exported more than half as much sediment as had a 100‐year flood 35 years earlier, substantially enlarging the nearshore delta. Annual sediment load in 2017 was an order of magnitude greater than during an average‐rainfall year, and 500‐fold greater than in a recent drought. These anomalous sediment inputs are critical to the coastal littoral system, delivering enough sediment, sometimes over only a few days, to maintain beaches for several years. Future projections of megadroughts punctuated by major atmospheric‐river storm activity suggest that interannual sediment‐yield variations will become more extreme than today in the western USA, with potential consequences for coastal management, ecosystems, and water‐storage capacity. The occurrence of two years with major sediment export over the past 35 years that were not associated with extremes of the El Niño Southern Oscillation or Pacific Decadal Oscillation suggests caution in interpreting climatic signals from marine sedimentary deposits derived from small, steep, coastal watersheds, to avoid misinterpreting the frequencies of those cycles. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.     

Hydrologic impact of regional climate change for the snowfed and glacierfed river basins in the Republic of Tajikistan: hydrological response of flow to climate change

The warming of the Earth's atmosphere system is likely to change temperature and precipitation, which may affect the climate, hydrology and water resources at the river basins over the world. The importance of temperature change becomes even greater in snow or glacier dominated basins where it controls the snowmelt processes during the late‐winter, spring and summer months. In this study hydrologic responses of streamflow in the Pyanj and Vaksh River basins to climate change are analysed with a watershed hydrology model, based on the downscaled atmospheric data as input, in order to assess the regional climate change impact for the snowfed and glacierfed river basins in the Republic of Tajikistan. As a result of this analysis, it was found that the annual mean river discharge is increasing in the future at snow and glacier dominated areas due to the air temperature increase and the consequent increase in snow/ice melt rates until about 2060. Then the annual mean flow discharge starts to decrease from about 2080 onward because the small glaciers start to disappear in the glacier areas. It was also found that there is a gradual change in the hydrologic flow regime throughout a year, with the high flows occuring earlier in the hydrologic year, due to the warmer climate in the future. Furthermore, significant increases in annual maximum daily flows, including the 100‐year return period flows, at the Pyanj and Vaksh River basins toward the end of the 21st century can be inferred from flood frequency analysis results. Copyright © 2012 John Wiley & Sons, Ltd.     

A sensitivity analysis of lake water level response to changes in climate and river regimes

Lake water level regimes are influenced by climate, hydrology and land use. Intensive land use has led to a decline in lake levels in many regions, with direct impacts on lake hydrology, ecology and ecosystem services. This study examined the role of climate and river flow regime in controlling lake regimes using three different lakes with different hydraulic characteristics (volume-inflow ratio, CIR). The regime changes in the lakes were determined for five different river inflows and five different climate patterns (hot-arid, tropical, moderate, cold-arid, cold-wet), giving 75 different combinations of governing factors in lake hydrology. The input data were scaled to unify them for lake comparisons. By considering the historical lake volume fluctuations, the duration (number of months) of lake volume in different ‘wetness’ regimes from ‘dry’ to ‘wet’ was used to develop a new index for lake regime characterisation, ‘Degree of Lake Wetness’ (DLW). DLW is presented as two indices: DLW₁, providing a measure of lake filling percentage based on observed values and lake geometry, and DLW₂, providing an index for lake regimes based on historical fluctuation patterns. These indices were used to classify lake types based on their historical time series for variable climate and river inflow. The lake response time to changes in hydrology or climate was evaluated. Both DLW₁ and DLW₂ were sensitive to climate and hydrological changes. The results showed that lake level in high CIR systems depends on climate, whereas in systems with low CIR it depends more on river regime.