Reversing hydrology:quantifying the temporal aggregation effect of catchment rainfall estimation using sub-hourly data

Inferred rainfall sequences generated by a novel method of inverting a continuous time transfer function show a smoothed profile when compared to the observed rainfall however streamflow generated using the inferred rainfall is almost identical to that generated using the observed rainfall (Rt2 = 95%). This paper compares the inferred effective and observed effective rainfall in both time and frequency domains in order to confirm that, by using the dominant catchment dynamics in the inversion process, the main characteristics of catchment rainfall are being captured by the inferred effective rainfall estimates. Estimates of the resolution of the inferred effective rainfall are found in the time domain by comparison with aggregated sequences of observed effective rainfall, and in the frequency domain by comparing the amplitude spectra of observed and inferred effective rainfall. The resolution of the rainfall estimates is affected by the slow time constant of the catchment and the rainfall regime, but also by the goodness-of-fit of the model, which incorporates the amount of other disturbances in the data

Millennial scale control of European climate by the North Atlantic Oscillation from 12,500 BP: the Asiul speleothem record

Contemporary climate in Europe is strongly influenced by the North Atlantic Oscillation (NAO), the atmospheric pressure dipole between Iceland and the Azores1. Under positive NAO conditions winter storm tracks associated with the Atlantic Westerly Jet (AWJ) migrate northwards, leading to wetter and warmer winter conditions in north-western Europe and dry conditions in southern Europe; including the Iberian Peninsula. Under the negative NAO phase, storm tracks weaken and shift southwards reversing the pattern1. Existing proxy records of the NAO suggest that this atmospheric process only began to dominate European climate at approximately 8000 years BP, related to the final breakup of the Laurentide ice shelf2. However, here we present evidence of precipitation changes from a high-resolution speleothem δ18O record from northern Iberia, which indicates NAO-like forcing extending throughout the Holocene and into the Younger Dryas (YD) at 12,500 years BP. These variations in precipitation delivery relate to an underlying millennial scale cycle in NAO dynamics. The speleothem δ18O is strongly correlated to existing records of North Atlantic Ocean ice rafted debris (IRD)3, indicating an NAO-like connection with oceanic circulation during the Holocene2. These large-scale atmospheric processes have dramatically influenced the delivery of precipitation to northern Iberia and may have played a decisive role in environmental and human development in the region, throughout the Holocene

North Atlantic forcing of moisture delivery to Europe throughout the Holocene

Century-to-millennial scale fluctuations in precipitation and temperature are an established feature of European Holocene climates. Changes in moisture delivery are driven by complex interactions between ocean moisture sources and atmospheric circulation modes, making it difficult to resolve the drivers behind millennial scale variability in European precipitation. Here, we present two overlapping decadal resolution speleothem oxygen isotope (δ18O) records from a cave on the Atlantic coastline of northern Iberia, covering the period 12.1–0 ka. Speleothem δ18O reveals nine quasi-cyclical events of relatively wet-to-dry climatic conditions during the Holocene. Dynamic Harmonic Regression modelling indicates that changes in precipitation occurred with a ~1500 year frequency during the late Holocene and at a shorter length during the early Holocene. The timing of these cycles coincides with changes in North Atlantic Ocean conditions, indicating a connectivity between ocean conditions and Holocene moisture delivery. Early Holocene climate is potentially dominated by freshwater outburst events, whilst ~1500 year cycles in the late Holocene are more likely driven by changes internal to the ocean system. This is the first continental record of its type that clearly demonstrates millennial scale connectivity between the pulse of the ocean and precipitation over Europe through the entirety of the Holocene

Nierji reservoir flood forecasting based on a Data-Based Mechanistic methodology

The Nierji Basin, in the north-east of China, is one of the most important basins in the joint operation of the entire Songhua River, containing a major reservoir used for flood control. It is necessary to forecast the flow of the basin during periods of flood accurately and with the maximum lead time possible. This paper presents a flood forecasting system, using the Data Based Mechanistic (DBM) modeling approach and Kalman Filter data assimilation for flood forecasting in the data limited Nierji Reservoir Basin (NIRB). Examples are given of the application of the DBM methodology using both single input (rainfall or upstream flow) and multiple input (rainfalls and upstream flow) to forecast the downstream discharge for different sub-basins. Model identification uses the simplified recursive instrumental variable (SRIV) algorithm, which is robust to noise in the observation data. The application is novel in its use of stochastic optimisation to define rain gauge weights and identify the power law nonlinearity. It is also the first application of the DBM methodology to flood forecasting in China. Using the methodology allows the forecasting with lead times of 1-day, 2-day, 3-day, 4-day, 5-day with 98%, 97%, 96%, 96% and 93% forecast coefficient of determination respectively, which is sufficient for the regulation of the reservoirs in the basin

Tropical montane forest conversion is a critical driver for sediment supply in East African catchments

Land use change is known to affect suspended sediment fluxes in headwater catchments. There is however limited empirical evidence of the magnitude of these effects for montane catchments in East Africa. We collected a unique 4‐year high‐frequency data set and assessed seasonal sediment variation, waterpathways, and sediment response to hydrology in three catchments under contrasting land use in the Mau Forest Complex, Kenya's largest tropical montane forest. Annual suspended sediment yield was significantly higher in a smallholder agriculture‐dominated catchment (131.5 ± 90.6 t km−2 yr−1) than in a tea‐tree plantation catchment (42.0 ± 21.0 t km−2 yr−1) and a natural forest catchment (21.5 ± 11.1 t km−2 yr−1) (p < 0.05). Transfer function models showed that in the natural forest and the tea‐tree plantations subsurface flow pathways delivered water to the stream, while in the smallholder agriculture shallow subsurface and surface runoff were dominant. There was a delayed sediment response to rainfall for the smallholder agriculture and the tea‐tree plantations. A slow depletion in sediment supply suggests that the wider catchment area supplies sediment, especially in the catchment dominated bysmallholder farming. In contrast, a fast sediment response and depletion in sediment supply in the natural forest suggests a dominance of temporarily stored and nearby sediment sources. This study shows that the vegetation cover of a forest ecosystem is very effective in conserving soil, whereas catchments with more bare soil and poor soil conservation practices generated six times more suspended sediment yield. Catchment connectivity through unpaved tracks is thought to be the main explanation for the difference in sediment yield

Does the Establishment of Sustainable Use Reserves Affect Fire Management in the Humid Tropics?

Tropical forests are experiencing a growing fire problem driven by climatic change, agricultural expansion and forest degradation. Protected areas are an important feature of forest protection strategies, and sustainable use reserves (SURs) may be reducing fire prevalence since they promote sustainable livelihoods and resource management. However, the use of fire in swidden agriculture, and other forms of land management, may be undermining the effectiveness of SURs in meeting their conservation and sustainable development goals. We analyse MODIS derived hot pixels, TRMM rainfall data, Terra-Class land cover data, socio-ecological data from the Brazilian agro-census and the spatial extent of rivers and roads to evaluate whether the designation of SURs reduces fire occurrence in the Brazilian Amazon. Specifically, we ask (1) a. Is SUR location (i.e., de facto) or (1) b. designation (i.e. de jure) the driving factor affecting performance in terms of the spatial density of fires?, and (2), Does SUR creation affect fire management (i.e., the timing of fires in relation to previous rainfall)? We demonstrate that pre-protection baselines are crucial for understanding reserve performance. We show that reserve creation had no discernible impact on fire density, and that fires were less prevalent in SURs due to their characteristics of sparser human settlement and remoteness, rather than their status de jure. In addition, the timing of fires in relation to rainfall, indicative of local fire management and adherence to environmental law, did not improve following SUR creation. These results challenge the notion that SURs promote environmentally sensitive fire-management, and suggest that SURs in Amazonia will require special attention if they are to curtail future accidental wildfires, particularly as plans to expand the road infrastructure throughout the region are realised. Greater investment to support improved fire management by farmers living in reserves, in addition to other fire users, will be necessary to help ameliorate these threats

A simple transfer-function-based approach for estimating material parameters from terahertz time-domain data

A novel parametrically efficient approach to estimating the spectra of short transient signals is proposed and evaluated, with an application to estimating material properties, including complex refractive index and absorption coefficient, in the terahertz (THz) frequency range. This technique includes uncertainty analysis of the obtained spectral estimates, allowing rigorous statistical comparison between samples. In the proposed approach, a simple, few-parameter continuous-time transfer function model explains over 99.9% of the measured signal. The problem, normally solved using poorly numerically defined Fourier transform deconvolution methods, is reformulated and cast as a time-domain dynamic-system estimation problem, thus providing a true time-domain spectroscopy tool

Mathematical modelling of the reaction latency. Part III : a model of avoidance reaction latency and avoidance learning.

The linear-dynamic-stochastic model of a reaction latency as applied to avoidance experiment is presented. Reactions are classified on the basis of the model into following classes: escape, avoidance, late avoidance, three types of inter-trial responses and "no reaction". The experimental latency distribution is split into latency distributions of the escape, avoidance and late avoidance responses, providing a new insight into latency distribution. The results of fitting the model to latency measurements obtained in the avoidance conditioning experiment are presented. The same processes of the parameter changes as in the escape conditioning are discovered, one causing a latency to decrease and the other causing a latency to increase during learning. The first process affects a latency stronger than the second and, consequently, the latency decreases during learning. The second process is responsible for a decay of inter trial-responses during experiment. The value of the correlation coefficient between the threshold of avoidance reaction and the threshold of escape reaction was also estimated. Negative values of this coefficient were obtained, therefore, on the average, the greater the avoidance reaction threshold the smaller the escape one. In the course of learning the correlation coefficient tends to be equal to - 1, i.e., as a result of training, both thresholds became dependent in a functional (non-random) way. This result may provide an objective index of the "state of learning". The model provides a new tool for analysis of results of latency-based experiments