Effect Of Precipitation Research Articles

Evaluation of precipitation measurement methods using data from a precision lysimeter network

Abstract. Accurate precipitation data are essential for assessing the water balance of ecosystems. Methods for point precipitation determination are influenced by wind, precipitation type and intensity and/or technical issues. High-precision weighable lysimeters provide precipitation measurements at ground level that are less affected by wind disturbances and are assumed to be relatively close to actual precipitation. The problem in previous studies was that the biases in precipitation data introduced by different precipitation measurement methods were not comprehensively compared with and quantified on the basis of those obtained by lysimeters in different regions in Germany. The aim was to quantify measurement errors in standard precipitation gauges as compared to the lysimeter reference and to analyze the effect of precipitation correction algorithms on the gauge data quality. Both correction methods rely on empirical constants to account for known external influences on the measurements, following a generic and a site-specific approach. Reference precipitation data were obtained from high-precision weighable lysimeters of the TERrestrial ENvironmental Observatories (TERENO)-SOILCan lysimeter network. Gauge types included tipping bucket gauges (TBs), weighable gauges (WGs), acoustic sensors (ASs) and optical laser disdrometers (LDs). From 2015-2018, data were collected at three locations in Germany, and 1 h aggregated values for precipitation above a threshold of 0.1 mm h−1 were compared. The results show that all investigated measurement methods underestimated the precipitation amounts relative to the lysimeter references for long-term precipitation totals with catch ratios (CRs) of between 33 %–92 %. Data from ASs had overall biases of −0.25 to −0.07 mm h−1, while data from WGs and LDs showed the lowest measurement bias (−0.14 to −0.06 mm h−1 and −0.01 to −0.02 mm h−1). Two TBs showed systematic deviations with biases of −0.69 to −0.61 mm h−1, while other TBs were in the previously reported range with biases of −0.2 mm h−1. The site-specific and generic correction schemes reduced the hourly measurement bias by 0.13 and 0.08 mm h−1 for the TBs and by 0.09 and 0.07 mm h−1 for the WGs and increased long-term CRs by 14 % and 9 % and by 10 % and 11 %, respectively. It could be shown that the lysimeter reference operated with minor uncertainties in long-term measurements under different site and weather conditions. The results indicate that considerable precipitation measurement errors can occur even at well-maintained and professionally operated stations equipped with standard precipitation gauges. This generally leads to an underestimation of the actual precipitation amounts. The results suggest that the application of relatively simple correction schemes, manual or automated data quality checks, instrument calibrations, and/or an adequate choice of observation period can help improve the data quality of gauge-based measurements for water balance calculations, ecosystem modeling, water management, assessment of agricultural irrigation needs, or radar-based precipitation analyses.

Study on the Contribution of Land Use and Climate Change to Available Water Resources in Basins Based on Vector Autoregression (VAR) Model

Under the influence of global climate change and urbanization processes, the number of available water resources (AWRs) in basins has become significantly more uncertain, which has restricted the sustainable development of basins. Therefore, it is important for us to understand the relationship between land use (LU) patterns and climate change on AWRs in a basin for sustainable development. To this end, the vector autoregressive (VAR) method was adopted to construct a quantitative model for AWRs in the basin in this study. Taking the Yiluo River Basin (YRB) as an example, the dynamic relationship between the five elements of agricultural land (AD), woodland (WD), grassland (GD), construction land (CD), and annual precipitation (PREP) and AWRs in the basin was studied. The results show the following: (1) The constructed VAR model was stable, indicating that the use of the proposed VAR model to characterize the degree of the effect of LU pattern and PREP on AWRs in the YRB was reasonable and effective. (2) AWRs in the YRB showed a downward trend, and their responses to the change in LU and PREP were delayed. The changes in the AWRs in the YRB tended to occur the year after changes to the LU pattern and PREP occurred. (3) In the long run, the degree of the contribution of each influencing factor to changes to AWRs was 23.76% (AD), 6.09% (PREP), 4.56% (CD), 4.40% (WD), and 4.34% (GD), which meant that the impact of the LU pattern was more than 90%. This study provides new ideas for similar research, water resource allocation, and LU planning in other river basins from a macroscopic perspective.

Impacts of historical droughts on maize and soybean production in the southeastern United States

The trend of yield losses to drought in United States (U.S.) agriculture has increased over the years, in spite of financial investments and technological development to alleviate drought impacts. As climate change threatens to worsen future drought conditions, it is crucial to evaluate drought impacts on crop production for efficient yet robust decision-making at the regional level. This study evaluated the robustness of modified Standardized Precipitation Indices (SPIs) using effective precipitation (EP) and the Standardized Precipitation-Evapotranspiration Index (SPEI) in assessing drought impacts on county-level maize and soybean yields in the southeastern U.S during 1979–2019. The results showed that the modified SPI using the CROPWAT EP formula can be as effective as SPEI in assessing drought impacts on crop production. Assessment of drought impacts on crop yield year-to-year variability was then assessed by fitting linear regression through the yield-drought time series. Probability of yield loss due to drought in the region was estimated by using a copula-based probabilistic model. Results show that drought events occurring during the critical development growth stage had significantly negative impacts on year-to-year yield variability in over 50% of the counties in the study region, though the impact magnitude varied across the region due to different characteristics, historical climatic condition and irrigation infrastructure. On average, an extremely dry event occurring during the critical development growth stage resulted in a region-wide average yield reduction between − 42.7% and − 31.9% for maize and between − 25.4% and − 23.4% for soybean. Moderately wet conditions may increase crop yield, but excessively wet conditions may diminish the benefits for both crops. The average probability of yield loss of the study region under the extremely dry condition is more than 80%. Irrigation may help to reduce the impacts of drought on crop production: maize-producing irrigated counties on average were found to be 50% less sensitive to drought than non-irrigated counties, though this effect is smaller for soybean. As crop production in the region is highly vulnerable to drought, adaptation interventions under are required to adapt to warming climate scenarios.

An Increase in Solar Radiation in the Late Growth Period of Maize Alleviates the Adverse Effects of Climate Warming on the Growth and Development of Maize

Against the background of long-term climate change, quantifying the response of maize growth and development to climate change during critical growth stages will contribute to future decision-making in maize production. However, there have been few reports on the impact of climate change on maize dry matter accumulation and yield formation using long-term field trial data. In this study, field trial data from 13 agricultural meteorological stations in the Beijing–Tianjin–Hebei region from 1981 to 2017 were analyzed using partial correlation analysis and multiple regression models to investigate the effects of climate change on maize growth and yield. The results showed that the average temperature (Tavg) and accumulated effective precipitation (EP) during the maize growing season increased while the accumulated solar radiation (SRD) decreased from 1981 to 2017. During the seedling stage (GS1, VE-V8) and ear development stage (GS2, V8-R1), Tavg increased by 0.34 °C and 0.36 °C/decade, respectively, and EP increased by 1.83 mm and 3.35 mm/decade, respectively. The significant increase in Tavg during GS1 was the main reason for the inhibitory effect of climate change on maize growth, development, and biomass accumulation. However, the increase in SRD during the grain formation stage (GS3, R1–R3) and grain filling stage (GS4, R3–R6) was favorable for yield formation, increasing the grain number per ear (GN) and grain weight (GW) by 5.00% and 2.84%, respectively. SRD significantly increased after the silk stage, partially offsetting the adverse effects of temperature on maize yield formation, but the final result was a 0.18% and 0.94% reduction in maize plant dry weight (TDW) and grain yield (GY), respectively, due to the combined effects of the three climate factors. Spatially, climate change mainly had a negative impact on maize in the eastern and western parts of the central region of Beijing–Tianjin–Hebei, with a maximum GY reduction of up to 34.06%. The results of this study can provide a scientific basis for future decision-making in maize production against the background of climate change.

A wavelet-assisted deep learning approach for simulating groundwater levels affected by low-frequency variability

Groundwater level (GWL) simulations allow the generation of reconstructions for exploring the past temporal variability of groundwater resources or provide the means for generating projections under climate change on decadal scales. In this context, analyzing GWLs affected by low-frequency variations is crucial. In this study, we assess the capabilities of three deep learning (DL) models (long short-term memory (LSTM), gated recurrent unit (GRU), and bidirectional LSTM (BiLSTM)) in simulating three types of GWLs affected by varying low-frequency behavior: inertial (dominated by low-frequency), annual (dominated by annual cyclicity) and mixed (in which both annual and low-frequency variations have high amplitude). We also tested if maximal overlap discrete wavelet transform pre-processing (MODWT) of input variables helps to better identify the frequency content most relevant for the models (MODWT-DL models). Only external variables (i.e., precipitation, air temperature as raw data, and effective precipitation (EP)) were used as input. Results indicate that for inertial-type GWLs, MODWT-DL models with raw data were notably more accurate than standalone models. However, DL models performed well for annual-type GWLs, while using EP as input, with MODWT-DL models exhibiting only minor improvements. Using raw data as input improved MODWT-DL models compared to standalone models; nevertheless, all models using EP performed better for annual-type GWLs. For mixed-type GWLs, while using EP as input, MODWT-DL models performed well, with substantial improvements over standalone models. Using raw data as input, improvement of MODWT-DL models is marginal compared to that of standalone models; nevertheless, they perform better than standalone models with EP. The Shapley Additive exPlanations (SHAP) approach used to interpret models highlighted that they preferentially learned from low-frequency in precipitation data to achieve the best simulations for inertial and mixed GWLs. This study showed that MODWT-based input pre-processing is highly suitable to better simulate low-frequency varying GWLs.

Climatic influence on the expression of strike-slip faulting

Abstract Earthquakes on strike-slip faults are preserved in the geomorphic record by offset land-forms that span a range of displacements, from small offsets created in the most recent earthquake (MRE) to large offsets that record cumulative slip from multiple prior events. An exponential decay in the number of large cumulative offsets has been observed on many faults, and a leading hypothesis is that climate controls the rate of decay. We present offset measurements compiled from 31 studies of strike-slip faults with evidence of multiple paleoearthquakes and corresponding climatic and tectonic information to test this hypothesis. Both the global compilation and numerical landscape evolution modeling reveal that the decay rate in large offsets is negatively correlated with mean annual precipitation. Faults in dry regions with high drainage density more commonly preserve small MRE offsets, and faults in wet regions with lower drainage density more commonly preserve a mix of small MRE and large cumulative offsets. Geomorphology of faults in different climates supports this result and illustrates precipitation's effect on the development and preservation of off-set channels. Our findings imply that current and past climate affect how displacement on strike-slip faults is recorded and interpreted to inform earthquake history.

Assessment of Rainfall Erosivity Index using Lombardi Method for Amritsar, Punjab, India

The erosivity thing with inside the conventional soil loss equation (USLE) affords a powerful approach ofcomparing the erosive energy of rainfall. This study estimated the erosivity factorbased on monthly and yearly periodic rush rainfall data of Amritsar, Punjab State covering a period of 45 year from1971 to 2015using Lombardi system (EI = 1.03 Vd1.51). It was found that early arrived rainfall led high erosive index.The data of seasonal distribution of precipitation illustrated that the most ferocious erosion imminence inthe area can be anticipated in August, especially in the areas that aren’t defended by foliage cover, whichmight be due to climatic change. The average periodic erosivity indicator for the megacity during theperiod of study was 744.6 MJ mm/ hr. The correlation between periodic erosivity indicator andaverageperiodic rush was expressed as Y = 0.0002x + 0.8873. The R2 of 0.79 shows that rush alone contributed 79 %of the corrosion threat within the study period. The knowledge of impact of rainfall on erosivity is essentialin soil erosion threat assessment and for soil and water conservation planning. The information on effect ofprecipitation on erosivity is important in soil disintegration threat evaluation and for planning of waterand soil conservation.

Importance of Fog and Cloud Water Contributions to Soil Moisture in the Andean Páramo

Páramos are particular ecosystems of the Tropical Andes, where fog and low-intensity rainfall such as drizzle are commonly frequent—but the contribution of these water sources to soil water replenishment and discharge is not yet clear, mainly because the development of techniques for separating fog from drizzle and wind-driven rainfall has been challenging. Fog was measured with a cylindrical Juvik gauge and types of precipitation other than fog with a high-resolution disdrometer. Soil moisture was measured at 100 mm depth by means of Water Content Reflectometers, then Effective precipitation (EP) was calculated. We categorized events as two types: fog only (FO) and cloud water (CW). We found that in the case of FO events, only small amounts reached the soil (EP ranged between 0.1 and 0.2 mm); in contrast, greater amounts of EP originated from CW events (maximum value of 4.3 mm). Although we found that FO events are negligible for stream water contribution; they are ecologically important for maintaining high relative humidity, low net radiation, and consequently low evapotranspiration rates. Our research provides new insights into the hydrological role of fog, enabling us to better understand to what extent its input influences the water resources of the Andean páramo.

Evaluating the response of <i>δ</i><sup>13</sup>C in <i>Haloxylon ammodendron</i>, a dominant C<sub>4</sub> species in Asian desert ecosystems, to water and nitrogen addition as well as the availability of its <i>δ</i><sup>13</sup>C as an indicator of water use efficiency

Abstract. Variations in precipitation and atmospheric N deposition affect water and N availability in desert and thus may have significant effects on desert ecosystems. Haloxylon ammodendron is a dominant plant in Asian desert, and addressing its physiological acclimatization to the changes in precipitation and N deposition can provide insight into how desert plants adapt to extreme environments by physiological adjustment. Carbon isotope ratio (δ13C) in plants has been suggested as a sensitive long-term indicator of physiological acclimatization. Therefore, this study evaluated the effect of precipitation change and increasing atmospheric N deposition on δ13C of H. ammodendron. Furthermore, H. ammodendron is a C4 plant; whether its δ13C can indicate water use efficiency (WUE) has not been addressed. In the present study, we designed a field experiment with a completely randomized factorial combination of N and water and measured δ13C and gas exchange of H. ammodendron. Then we calculated the degree of bundle-sheath leakiness (φ) and WUE of the assimilating branches of H. ammodendron. δ13C and φ remained stable under N and water supply, while N addition, water addition and their interaction affected gas exchange and WUE in H. ammodendron. In addition, δ13C had no correlation with WUE. These results were associated with the irrelevance between δ13C and the ratio of intercellular to ambient CO2 concentration (ci / ca), which might be caused by a special value (0.37) of the degree of bundle-sheath leakiness (φ) or a lower activity of carbonic anhydrase (CA) of H. ammodendron. In conclusion, δ13C of H. ammodendron is not sensitive to global change in precipitation and atmospheric N deposition and cannot be used for indicating its WUE.

Relationships of Linear and Non-linear Measurements of Post-stroke Walking Activity and Their Relationship to Weather.

Background: Stroke survivors are more sedentary than the general public. Previous research on stroke activity focuses on linear quantities. Non-linear measures, such as Jensen-Shannon Divergence and Lempel-Ziv Complexity, may help explain when and how stroke survivors move so that interventions to increase activity may be designed more effectively.Objectives: Our objective was to understand what factors affect a stroke survivor's physical activity, including weather, by characterizing activity by step counts, structure, and complexity.Methods: A custom MATLAB code was used to analyze clinical trial (NCT02835313, https://clinicaltrials.gov/ct2/show/NCT02835313) data presented as minute by minute step counts. Six days of data were analyzed for 142 participants to determine the regularity of activity structure across days and complexity patterns of varied cadences. The effect of steps on structure and complexity, the season's effect on steps, structure, and complexity, and the presence of precipitation's effect on steps and complexity were all analyzed.Results: Step counts and regularity were linearly related (p < 0.001). Steps and complexity were quadratically related (r2 = 0.70 for mean values, 0.64 for daily values). Season affected complexity between spring and winter (p = 0. 019). Season had no effect on steps or structure. Precipitation had no effect on steps or complexity.Conclusions: Stroke survivors with high step counts are active at similar times each day and have higher activity complexities as measured through patterns of movement at different intensity levels. Non-linear measures, such as Jensen-Shannon Divergence and Lempel-Ziv Complexity, are valuable in describing a person's activity. Weather affects our activity parameters in terms of complexity between spring and winter.

Groundwater vulnerability assessment in the Grand Est region, France

Groundwater represents the most important freshwater resource. In this paper, we applied a spatial approach based on the Geographical Information Systems (GIS) technology to assess the groundwater vulnerability in the Grand Est region from northeastern France. Aquifers media (AM), potential infiltration map (PIM), pollution load index (PLI), and effective precipitation (EP) were the main parameters used in the calculation of groundwater vulnerability. This study proposes a spatial-temporal analysis including past (1961–1990), near future (2011–2040), and more distant future (2041–2070), thereafter called the 1990s, the 2020s, and the 2050s. To validate the results, groundwater monitoring stations data of Nitrate (NO3−), dated from 2005 to 2012, was used as reference datasets. The validation of the groundwater vulnerability map was based on pixel pair comparison (PPC) method and it indicates 42.85% perfect confidence and 50% good confidence for the groundwater vulnerability map in 2020s period. The high groundwater vulnerability was found in the Rhine, Marne, and Aube Valleys, while the low and very low vulnerability was depicted in the Vosges, Ardennes Mountains, and some territories form the central region for all three periods. Application of the proposed framework indicates increases of vulnerability up to 60% between 1990s and 2020s and up to 80% between 1990s and 2050s scenarios. The output maps and findings could be useful for the future environmental plans of the region and, in addition, could help mitigate the problems related to water resources, considering the climate expectations.

Application of effective drought index (EDI) in characterizing drought periods (case study: Tabriz, Bandar-e Anzali and Zahedan stations)

In this study, drought characteristics of three stations namely Tabriz, Bandar-e Anzali and Zahedan are analyzed from 1951 to 2012 using the effective drought index (EDI). For this purpose daily precipitation records of each station are arranged in a distinct column of excel spreadsheet. Long-term daily average of the day (in daily scale) is substituted for missing data. In this study, effective precipitation index (EPI) is calculated, too. This is accomplished once for dummy duration (365 days) and once again for actual duration. Then daily mean effective precipitation (MEP) for each day of a year is calculated. Moreover, differences between effective precipitation (EP) and MEP are calculated and named DEP. Then standardized values of DEP (shown with SEP) are calculated, too. Precipitation needed for returning to normal condition (shown with PRN) is calculated for every station. At last, the EDI for each station in whole time period is obtained. In this study, time series including: (1) daily EPI (for dummy period of 365 days as well as actual duration), (2) MEP, (3) DEP, (4) SEP, (5) PRN and (6) EDI for every station are plotted. Results showed that years 2007–2008, 2007–2008 and 2001–2002 were known as the driest years in the 60 years time period, respectively, for Tabriz, Bandar-e Anzali and Zahedan stations. Based on the number of dry days occurred for each station it can be calculated that Bandar-e Anzali, Tabriz and Zahedan having the 2407, 1517 and 1338 dry days in the whole time period ranked in the first to third orders.

Modified version for SPEI to evaluate and modeling the agricultural drought severity.

Drought is a climatic phenomenon that can occur in various regions with different climate conditions. Generally, drought has negative impacts on different fields such as environment, rangelands, and water resources. The agricultural section (especially rain-fed agriculture) is one of the parts that is directly affected by different types of drought especially meteorological and agricultural droughts. The standardized precipitation evapotranspiration index (SPEI) is one of the newest and most applied indices to assess drought characteristics. In this paper, a modification is suggested for SPEI with the substitution of observed precipitation (OP) with effective precipitation (EP) to evaluate drought, with an emphasis on consideration of drought effects on agricultural section. To calculate EP, Food and Agriculture Organization of the united nation method (FAO), US Bureau of Reclamation (USBR), the Simplified version of Soil Conservation Service of the US Department of Agriculture method (USDA-SCS simplified), and the CROPWAT version of USDA-SCS method (USDA-SCS CROPWAT) were used. To compare the calculated SPEI based on OP (SPEIOP) and EP (SPEIEP) (based on different EP calculation methods), the correlation coefficients (CC) between SPEIOP and SPEIEP in four synoptic stations with at least 30years of climatic data and annual yield loss (%) in winter wheat (Triticum sativum) (simulated using AquaCrop model) in the suitable reference periods for agricultural drought were used. Results showed, in Fasa, Drodzan, and Zarghan stations, the CC between SPEI based on EP using the USBR method (SPEIUSBR) and annual YL% had the highest values (in 42.11%, 68.42%, and 36.84% of Triticum sativum all reference periods, respectively). In Shiraz station, the CC between SPEI based on EP using the FAO method (SPEIFAO) and annual YL% had the highest values (in 47.37% of all reference periods). In all stations, the SPEIUSBR had the most reference periods with significant CC at 0.05 or 0.01 levels.

Flood Risk Mapping Using GIS and Multi-Criteria Analysis: A Greater Toronto Area Case Study

Given the increase in flood events in recent years, accurate flood risk assessment is an important component of flood mitigation in urban areas. This research aims to develop updated and accurate flood risk maps in the Don River Watershed within the Great Toronto Area (GTA). The risk maps use geographical information systems (GIS) and multi-criteria analysis along with the application of Analytical Hierarchy Process methods to define and quantify the optimal selection of weights for the criteria that contribute to flood risk. The flood hazard maps were generated for four scenarios, each with different criteria (S1, S2, S3, and S4). The base case scenario (S1) is the most accurate, since it takes into account the floodplain map developed by the Toronto and Region Conservation Authority. It also considers distance to streams (DS), height above nearest drainage (HAND), slope (S), and the Curve Number (CN). S2 only considers DS, HAND, and CN, whereas S3 considers effective precipitation (EP), DS, HAND, and S. Lastly, S4 considers total precipitation (TP), DS, HAND, S, and CN. In addition to the flood hazard, the social and economic vulnerability was included to determine the total flood vulnerability in the watershed under three scenarios; the first one giving a higher importance to the social vulnerability, the second one giving equal importance to both social and economic vulnerability, and the third one giving more importance to the economic vulnerability. The results for each of the four flood scenarios show that the flood risk generated for S2 is the most similar to the base case (S1), followed by S3 and S4. The inclusion of social and economic vulnerability highlights the impacts of floods that are typically ignored in practice. It will allow watershed managers to make more informed decisions for flood mitigation and protection. The most important outcome of this research is that by only using the digital elevation model, the census data, the streams, land use, and soil type layers, it is possible to obtain a reliable flood risk map (S2) using a simplified method as compared to more complex flood risk methods that use hydraulic and hydrological models to generate flood hazard maps (as was the case for S1).

An early warning criterion for the prediction of snowmelt-induced soil slope failures in seasonally cold regions

In Hokkaido, Japan, soil slope failures occur frequently during the snow melting season. These slope failures are triggered by the excess amount of water derived from snowmelt and rainfall. For the prediction of snowmelt-induced soil slope failures in seasonally cold regions, an early warning criterion is required. The existing Japanese early warning criteria for sediment disasters, i.e., the relationship between the 60-min cumulative rainfall and the Soil Water Index (SWI), the effective rainfall index etc., consider the influence of rainfall and the time-dependent random moisture of the soil. However, these criteria do not consider the soil moisture contributed by the snowmelt water. In this study, therefore, the applicability of the existing early warning criteria to predict snowmelt-induced soil slope failures is examined. An empirical method to quantify the amount of snowmelt water is presented. Various scenarios of conceptual soil slope failures are studied using numerical simulations under different magnitudes of rainfall and snowmelt water. As a result, a revision is introduced for the SWI and the effective rainfall index, adding the amount of snowmelt water to that of rainfall, and slope failure scenarios are studied. Based on the results, a new early warning criterion, the Effective Precipitation (EP) index, is introduced. It is found that the new failure criterion performs well for the prediction of snowmelt-induced soil slope failures.

Evolution of a Holocene, mixed-process, forced regressive shoreline: The Mitchell River delta, Queensland, Australia

Subtle changes in local accommodation, sediment flux, and wave, tide and fluvial processes can result in significant changes in the depositional style and architecture of coastal depositional systems. The detailed study of modern mixed-process depositional systems provides an opportunity to examine how such forcing factors affect shoreline evolution. The Mitchell River delta is a morphologically complex system that has prograded during a Holocene forced regression in a low accommodation epicontinental seaway. Relatively minor anthropogenic modification of the delta has occurred during the last 200 yr such that the considerable temporal and spatial variability of a mixed-influence coastal system can be observed in a de facto natural state. Of special interest is the link between preserved delta morphology and process change. A recent coastal process classification system was applied to the delta using desktop mapping and field ground-truthing and sedimentological analyses. The distribution and extent of 3400 wave-, tide- and fluvial-derived depositional elements were mapped across over 500 km2. These elements were grouped into 7 distinct progradational Element Complex Sets (ECS), defined by major reorganisations of the shoreline. The process classification of the overall delta system is tide dominated, fluvial influenced, wave affected (Tfw); however, the delta has evolved through three geometrically discrete pulses of delta progradation. The delta has evolved from (i) a symmetrical, wave-dominated, fluvial-influenced, tide-affected (Wft) system (early Holocene), to (ii) a rapidly prograding asymmetrical, tide-dominated, fluvial-influenced, wave-affected (Tfw) system (mid-Holocene), to (iii) an asymmetrical, tide-dominated, wave-influenced, fluvial-affected (Twf) system (at the modern shoreline). When the delta commenced progradation (6 ka BP), high accommodation-to-sediment-supply ratio (A/S) resulted in the deposition of wave formed depositional elements. As sea level fell and effective precipitation (EP) increased, reduced A/S resulted in more rapid progradation of tidal deposits until approximately 2 ka BP. The subsequent decrease in EP (and increased A/S) resulted in reduced rates of delta progradation and prompted multiple channel avulsions. Limited evidence suggests increased progradation rates at the modern channel mouth since 0.2 ka BP, which may be linked to increased sediment supply from anthropogenic catchment disturbance.

Holocene climate change in arid Australia from speleothem and alluvial records

New high-resolution MC-ICPMS U/Th ages and C and O isotopic analyses from a Holocene speleothem in arid south-central Australia provide evidence for increased effective precipitation (EP) relative to present at c. 11.5 ka and c. 8—5 ka, peak moisture at 7—6 ka, and onset of an arid climate similar to present by c. 5 ka. δ18O and δ13C time-series data exhibit marked (&gt;+1‰) contemporaneous excursions over base-line values of −5.3‰ and −11.0‰, respectively, suggesting pronounced moisture variability during the early middle Holocene ‘climatic optimum’. Optically stimulated luminescence and 14C ages from nearby terraced aggradational alluvial deposits indicate a paucity of large floods in the Late Pleistocene and at least five large flood events in the last c. 6 kyr, interpreted to mark an increased frequency of extreme rainfall events in the middle Holocene despite overall reduced EP. Increased EP in south-central Australia during the early to middle Holocene resulted from (1) decreased El Niño-Southern Oscillation (ENSO) variability, which reduced the frequency of El Niño-triggered droughts, (2) the prevalence of a more La Niña-like mean climatic state in the tropical Pacific Ocean, which increased available atmospheric moisture, and (3) a southward shift in the Intertropical Convergence Zone (ICTZ), which allowed tropical summer storms associated with the Australian summer monsoon (ASM) to penetrate deeper into the southern part of the continent. The onset of heightened aridity and apparent increase in large flood frequency at c. 5 ka is interpreted to indicate the establishment of an ENSO-like climate in arid Australia in the late Holocene, consistent with a variety of other terrestrial and marine proxies. The broad synchroneity of Holocene climate change across much of the Australian continent with changes in ENSO behavior suggests strong teleconnections amongst ENSO and the other climate systems such as the ASM, Indian Ocean Dipole, and Southern Annular Mode.

The Comprehensive Realistic Yearly Pit Transient Infilling Code (CRYPTIC): A Novel Pit Lake Analytical Solution

Permitting of open pit mines that intersect the groundwater table necessitates the use of sophisticated numerical models to determine the temporal impact of pit lake hydraulics. However, while mine feasibility and the potential environmental influences of open-pit dewatering can be estimated using conventional screening-level methods, to date there have been few published transient analytical solutions to estimate the pit lake recovery duration and inflow rates. The Comprehensive Realistic Yearly Pit Transient Infilling Code (CRYPTIC) described here is based on the Jacob-Lohman equation, modified to include the pit geometry and effects of precipitation and evaporation from the pit lake surface as well as the input/output of external flows. It assumes that the aquifer is homogeneous and isotropic with laterally extensive horizontal flow but differs from other methods in that it includes transient inflows. CRYPTIC was used to successfully model the Berkeley Pit Lake (Butte, Montana) recovery data and its predictions also compared favorably with results from the Pipeline Pit (north-central Nevada) numerical model. However, while this analytical approach provides useful hydraulic insights at the feasibility stage of mine planning, more detailed analysis is required to determine critical mine permitting requirements. For example, the lateral extent of the drawdown cone, time to maximum extent of dewatering, and temporal effects on springs and seeps require deployment of a full numerical code and substantially more data.

Objective Quantification of Drought Severity and Duration

Common weaknesses of current drought indexes were analyzed. First, most of the current indexes are not precise enough in detecting the onset, end, and accumulated stress of drought. Second, they do not effectively take into account the aggravating effects of runoff and evapotranspiration, which build up with time. Third, they have a limited usefulness in monitoring ongoing drought because they are based on a monthly time step. Fourth, most of them fail to differentiate the effects of drought on surface and subsurface water supply. A new series of indexes are proposed to solve these weaknesses and to improve drought monitoring. In the new indexes, daily, rather than monthly, time steps are used. A new concept, effective precipitation (EP), the summed value of daily precipitation with a time-dependent reduction function, is proposed as a basic tool. Three additional indexes complement EP. The first index is each day’s mean of EP (MEP). This index shows climatological characteristics of precipitation as a water resource for a station or area. The second index is the deviation of EP (DEP) from the MEP. The third index is the standardized value of DEP (SEP). By using these three indexes, consecutive days of negative SEP, which can show the onset, the ending date, and the duration of a water deficit period is categorized. With the duration categorized, four additional indexes that can show drought severity are calculated: 1) accumulation of consecutive negative SEP, which shows the duration and severity of precipitation deficit together ; 2) accumulated precipitation deficit, which shows precipitation departure from the normal during a defined period; 3) precipitation for the return to normal; and 4) effective drought index, a standardized index that can be used to assess drought severity worldwide. The merits and weaknesses of each index are compared. New quantified definitions on drought and its onset, end, and duration are proposed. These indexes were tested in the High Plains region of the United States from 1960 to 1996. The results were compared to historical reports of drought. From this analysis, it was concluded that the new indexes not only advanced objectivity, but also offered a number of advantages in practical use. These are 1) a more precise determination of drought duration, 2) the usefulness in monitoring an ongoing drought, and 3) the variety of ways a drought’s characteristics can be described.

Pollen evidence from tropical Australia for the onset of an ENSO-dominated climate at c. 4000 BP

The Holocene climatic history of tropical northern Australia is re-examined using the recently published pollen record from Groote Eylandt to corroborate and refine previous climatic inter pretations. We identify a four-stage Holocene comprising: (1) a continuous increase in effective precipitation (EP) from the beginning of the Holocene to about 5000 BP; (2) a mid-Holocene EP maximum from about 5000 to about 4000 BP; (3) a marked decline in EP somewhere between 4000-3500 Bp; and (4) an EP recovery in the last &lt;2000 years. The mid-Holocene EP maximum is 1000 years later than Holocene EP maxima from temperate Southern Australia and suggests that the records are decoupled at this time. We focus on pollen evidence of environmental change at c. 4000 BP, which marks a break between a continuously ameliorating (increasing EP) climate but with small mean variation in the earlier Holocene and a steady (no directional trend) but highly variable later Holocene. We believe that this break represents the first evidence from the monsoonal lowlands of northern Australia for the onset of 'modern' ENSO-dominated ocean-atmosphere interactions in the Holocene. A simple conceptual model of trans-Pacific teleconnections is presented to explain this onset and as an hypothesis for testing.