Observations and model estimates of diurnal water temperature dynamics in mosquito breeding sites in western Kenya

Water temperature is an important determinant of the growth and development of malaria mosquito immatures. To gain a better understanding of the daily temperature dynamics of malaria mosquito breeding sites and of the relationships between meteorological variables and water temperature, three clear water pools (diameter × depth: 0·16 × 0·04, 0·32 × 0·16 and 0·96 × 0·32 m) were created in Kenya. Continuous water temperature measurements at various depths were combined with weather data collections from a meteorological station. The water pools were homothermic, but the top water layer differed by up to about 2 °C in temperature, depending on weather conditions. Although the daily mean temperature of all water pools was similar (27·4–28·1 °C), the average recorded difference between the daily minimum and maximum temperature was 14·4 °C in the smallest versus 7·1 °C in the largest water pool. Average water temperature corresponded well with various meteorological variables. The temperature of each water pool was continuously higher than the air temperature. A model was developed that predicts the diurnal water temperature dynamics accurately, based on the estimated energy budget components of these water pools. The air–water interface appeared the most important boundary for energy exchange processes and on average 82–89% of the total energy was gained and lost at this boundary. Besides energy loss to longwave radiation, loss due to evaporation was high; the average estimated daily evaporation ranged from 4·2 mm in the smallest to 3·7 mm in the largest water pool. Copyright © 2008 John Wiley & Sons, Ltd.     

Flood forecasting with a watershed model: a new method of parameter updating

Abstract

Flood forecasting is of prime importance when it comes to reducing the possible number of lives lost to storm-induced floods. Because rainfall-runoff models are far from being perfect, hydrologists need to continuously update outputs from the rainfall-runoff model they use, in order to adapt to the actual emergency situation. This paper introduces a new updating procedure that can be combined with conceptual rainfall-runoff models for flood forecasting purposes. Conceptual models are highly nonlinear and cannot easily accommodate theoretically optimal methods such as Kalman filtering. Most methods developed so far mainly update the states of the system, i.e. the contents of the reservoirs involved in the rainfall-runoff model. The new parameter updating method proves to be superior to a standard error correction method on four watersheds whose floods can cause damage to the greater Paris area. Moreover, further developments of the approach are possible, especially along the idea of combining parameter updating with assimilation of additional data such as soil moisture data from field measurements and/or from remote sensing.     

Modelling river water temperature using deterministic,empirical, and hybrid formulations in a Mediterranean stream

River water temperature is a common target of water quality models at the watershed scale, owing to its principal role in shaping biogeochemical processes and in stream ecology. Usually, models include physically‐based, deterministic formulations to calculate water temperatures from detailed meteorological information, which usually comes from meteorological stations located far from the river reaches. However, alternative empirical approaches have been proposed, that usually depend on air temperature as master variable. This study explored the performance of a semidistributed water quality application modelling river water temperature in a Mediterranean watershed, using three different approaches. First, a deterministic approach was used accounting for the different heat exchange components usually considered in water temperature models. Second, an empirical approximation was applied using the equilibrium temperature concept, assuming a linear relationship with air temperature. And third, a hybrid approach was constructed, in which the temperature equilibrium concept and the deterministic approach were combined. Results showed that the hybrid approach gave the best results, followed by the empirical approximation. The deterministic formulation gave the worst results. The hybrid approach not only fitted daily river water temperatures, but also adequately modelled the daily temperature range (maximum–minimum daily temperature). Other river water features directly dependent on water temperature, such as river intrusion depth in lentic systems (i.e. the depth at which the river inflow plunges to equilibrate density differences with lake water), were also correctly modelled even at hourly time steps. However, results for the different heat fluxes between river and atmosphere were very unrealistic. Although direct evidence of discrepancies between meteorological drivers measured at the meteorological stations and the actual river microclimate was not found, the use of models including empirical or hybrid formulations depending mainly on air temperature is recommended if only meteorological data from locations far from the river reaches are available. Copyright © 2008 John Wiley & Sons, Ltd.     

Long‐term trend analysis for major climate variables in the Yellow River basin*

Some previous studies have shown that drying‐up of the lower Yellow River resulted from decreasing precipitation and excessive industrial and agricultural consumption of water from the middle and downstream regions of the Yellow River. On the basis of average air temperature, precipitation, and pan evaporation data from nearly 80 gauging stations in the Yellow River basin, the monotonic trends of major climate variables over the past several decades are analysed. The analysis was mainly made for 12 months and the annual means. The isograms for annual and typical months are given in the paper. The result shows that the average temperature in the study area exhibits an increasing trend, mainly because of the increase of temperature in December, January and February. The largest trend is shown in December and the smallest is in August. There are 65 of 77 stations exhibiting a downward trend for annual precipitation. In all seasons except summer, there is a similar trend in the upstream region of the Yellow River, south of latitude 35°N. It is interesting to note that the pan evaporation has decreased in most areas of the Yellow River basin during the past several decades. April and July showed the greatest magnitude of slope, and the area from Sanmenxia to Huayuankou as well as the Yiluo River basin exhibited the strongest declining trend. The conclusion is that the decreasing pan evaporation results from complex changes of air temperature, relative humidity, solar radiation, and wind speed, and both climate change and human activities have affected the flow regime of the Yellow River during the past several decades. Copyright © 2007 John Wiley & Sons, Ltd.     

The response of CO2 flux to rain pulses at a saline desert

As the substantial component of the ecosystem respiration, soil CO₂ flux is strongly influenced by infrequent and unpredictable precipitation in arid region. In the current study, we investigated the response of soil CO₂ flux to rain pulses at a saline desert in western China. Soil CO₂ flux was measured continuously during the whole growing season of 2009 at six sites. We found that there were remarkable changes in amplitude or diurnal patterns of soil CO₂ flux induced by rainfall events: from bimodal before rain to a single peak after that. Further analysis indicated that there is a significant linear relationship (P < 0.001) between soil CO₂ flux and soil temperature (T_soil). However, a hysteresis between the waveform of diurnal course of CO₂ flux and T_soil was observed: with soil CO₂ flux always peaked earlier than T_soil. Furthermore, a double exponential decay function was fitted to the soil CO₂ flux after rainfall, and total carbon (C) releases were estimated by numerical integration for rainfall events. The relative enhancement and total C release, in association with the rain pulses, was linearly related to the amount of precipitation. According to the size and frequency of rainfall events, the total amount of C release induced by rain pulses was computed as much as 7.88 g C·m^–2 in 2009, equivalent to 10.25% of gross primary production. These results indicated that rain pulses played a significant role in the carbon budget of this saline desert ecosystem, and the size of them was a good indicator of rain‐induced flux enhancement. Copyright © 2012 John Wiley & Sons, Ltd.     

A physically constrained wavelet-aided statistical model for multi-decadal groundwater dynamics predictions

A physically constrained wavelet-aided statistical model (PCWASM) is presented to analyse and predict monthly groundwater dynamics on multi-decadal or longer time scales. The approach retains the simplicity of regression modelling but is constrained by temporal scales of processes responsible for groundwater level variation, including aquifer recharge and pumping. The methodology integrates statistical correlations enhanced with wavelet analysis into established principles of groundwater hydraulics including convolution, superposition and the Cooper–Jacob solution. The systematic approach includes (1) identification of hydrologic trends and correlations using cross-correlation and multi-time scale wavelet analyses; (2) integrating temperature-based evapotranspiration and groundwater pumping stresses and (3) assessing model prediction performances using fixed-block k-fold cross-validation and split calibration-validation methods. The approach is applied at three hydrogeologicaly distinct sites in North Florida in the United States using over 40 years of monthly groundwater levels. The systematic approach identifies two patterns of cross-correlations between groundwater levels and historical rainfall, indicating low-frequency variabilities are critical for long-term predictions. The models performed well for predicting monthly groundwater levels from 7 to 22 years with less than 2.1 ft (0.7 m) errors. Further evaluation by the moving-block bootstrap regression indicates the PCWASM can be a reliable tool for long-term groundwater level predictions. This study provides a parsimonious approach to predict multi-decadal groundwater dynamics with the ability to discern impacts of pumping and climate change on aquifer levels. The PCWASM is computationally efficient and can be implemented using publicly available datasets. Thus, it should provide a versatile tool for managers and researchers for predicting multi-decadal monthly groundwater levels under changing climatic and pumping impacts over a long time period.     

Input data resolution‐induced uncertainty in watershed modelling

The temporal‐spatial resolution of input data‐induced uncertainty in a watershed‐based water quality model, Hydrologic Simulation Program‐FORTRAN (HSPF), is investigated in this study. The temporal resolution‐induced uncertainty is described using the coefficient of variation (CV). The CV is found to decrease with decreasing temporal resolution and follow a log‐normal relation with time interval for temperature data while it exhibits a power‐law relation for rainfall data. The temporal‐scale uncertainties in the temperature and rainfall data follow a general extreme value distribution and a Weibull distribution, respectively. The Nash‐Sutcliffe coefficient (NSC) is employed to represent the spatial resolution induced uncertainty. The spatial resolution uncertainty in the dissolved oxygen and nitrate‐nitrogen concentrations simulated using HSPF is observed to follow a general extreme value distribution and a log‐normal distribution, respectively. The probability density functions (PDF) provide new insights into the effect of temporal‐scale and spatial resolution of input data on uncertainties involved in watershed modelling and total maximum daily load calculations. This study exhibits non‐symmetric distributions of uncertainty in water quality modelling, which simplify weather and water quality monitoring and reducing the cost involved in flow and water quality monitoring. Copyright © 2011 John Wiley & Sons, Ltd.     

矿物热电系数及其在地质找矿中的应用

作者的研究表明,在非本征激发区,矿物热电系数随着活化温度的增高而增大;在本征激发区,随活化温度的增高而减小。矿物晶体中所含杂质的种类和含量多少决定矿物的导电类型。矿物热电系数可广泛应用于地质找矿和矿床评价中,以黄铁矿为例,在同一水平面上的含金矿脉,矿脉中黄铁矿热电系数正值高时,其矿石含金量也高。应用黄铁矿热电系数的正高值、混合型和负值可确定矿体和矿体的剥蚀深度。     

SOHM型氢钟在国家授时中心的运行情况分析

上海天文台研制的型号为SOHM-3和SOHM-4的3台氢原子钟在中国科学院国家授时中心(NTSC)已经运行了一年多时间。收集了每个氢原子钟与NTSC主钟的时间比对数据。数据的分析结果给出了这几台氢钟在不同采样间隔上的频率稳定度,也显示出1台氢钟明显的相位跳变,讨论了这种相位跳变的原因。比较了这3台氢钟和从美国进口的Symmetricom公司制造的氢钟的频率稳定度的温度变化效应,指出了上海天文台研究制的氢钟存在的主要问题。     

A modified land surface temperature split window retrieval algorithm and its applications over China

Due to the difficulties in correcting the influences of the atmosphere absorbability and the Earth surface emissivity diversification, the retrieval of LST (land surface temperature) from satellite data is a challenging task. In this paper, a modified Becker's split window LST inversion algorithm is developed for retrieving LST from the NOAA-16/17 AVHRR data. A new set of parameters for Becker's LST algorithm is proposed. The algorithm is developed from a surface brightness temperature dataset generated from the MODTRAN program, which uses a range of surface parameters and atmospheric quantities as inputs. The 10-day composites of the channels 4 and 5 brightness temperature data of NOAA-17 AVHRR (1-km resolution) are used to generate the clear-sky LST. As a validation of the algorithm, the retrieved LST is compared with MODIS LST of same period and area. The two LST products are found to be consistent, with the absolute difference being about 2.5 K for most areas. The NOAA retrieved LST is also compared with in-situ ground surface 0-cm measurements taken from 257 meteorological stations, which cover overall China area for the three periods of satellite observations. The comparison shows that the correlation between the retrieved LST and in-situ measurements is over 0.90 and the RMSE (root mean square error) is about 3.4 K.