Predicting quantiles of water quality from catchment characteristics

Water quality is often highly variable both in space and time, which poses challenges for modelling the more extreme concentrations. This study developed an alternative approach to predicting water quality quantiles at individual locations. We focused on river water quality data that were collected over 25 years, at 102 catchments across the State of Victoria, Australia. We analysed and modelled spatial patterns of the 10th, 25th, 50th, 75th and 90th percentiles of the concentrations of sediments, nutrients and salt, with six common constituents: total suspended solids (TSS), total phosphorus (TP), filterable reactive phosphorus (FRP), total Kjeldahl nitrogen (TKN), nitrate-nitrite (NO_x), and electrical conductivity (EC). To predict the spatial variation of each quantile for each constituent, we developed statistical regression models and exhaustively searched through 50 catchment characteristics to identify the best set of predictors for that quantile. The models predict the spatial variation in individual quantiles of TSS, TKN and EC well (66%–96% spatial variation explained), while those for TP, FRP and NO_x have lower performance (37%–73% spatial variation explained). The most common factors that influence the spatial variations of the different constituents and quantiles are: annual temperature, percentage of cropping land area in catchment and channel slope. The statistical models developed can be used to predict how low- and high-concentration quantiles change with landscape characteristics, and thus provide a useful tool for catchment managers to inform planning and policy making with changing climate and land use conditions.     

Determination of subcatchment and watershed boundaries in a complex and highly urbanized landscape

Urban development significantly alters the landscape by introducing widespread impervious surfaces, which quickly convey surface run‐off to streams via stormwater sewer networks, resulting in “flashy” hydrological responses. Here, we present the inadequacies of using raster‐based digital elevation models and flow‐direction algorithms to delineate large and highly urbanized watersheds and propose an alternative approach that accounts for the influence of anthropogenically modified land cover. We use a semi‐automated approach that incorporates conventional drainage networks into overland flow paths and define the maximal run‐off contributing area. In this approach, stormwater pipes are clustered according to their slope attributes, which define flow direction. Land areas drained by each cluster and contributing (or exporting) flow to a topographically delineated catchment were determined. These land masses were subsequently added or removed from the catchment, modifying both the shape and the size. Our results in a highly urbanized Toronto, Canada, area watershed indicate a moderate net increase in the directly connected watershed area by 3% relative to a topographically forced method; however, differences across three smaller scale subcatchments are greater. Compared to topographic delineation, the directly connected watershed areas of both the upper and middle subcatchments decrease by 5% and 8%, respectively, whereas the lower subcatchment area increases by 15%. This is directly related to subsurface storm sewer pipes that cross topographic boundaries. When directly connected subcatchment area is plotted against total streamflow and flashiness indices using this method, the coefficients of variation are greater (0.93 to 0.97) compared to the use of digital elevation model‐derived subcatchment areas (0.78 to 0.85). The accurate identification of watershed and subcatchment boundaries should incorporate ancillary data such as stormwater sewer networks and retention basin drainage areas to reduce water budget errors in urban systems.     

A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing

ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.     

A land-use mix allocation model considering adjacency,intensity, and proximity

ABSTRACT

Land-Use Mix (LUM) refers to the strategy of integrating complementary functions within a building or area. While LUM has become a dominant approach in urban planning, its actual benefits and vision for spatial planning remain unclear. To clarify this issue, this study discerns the spatial features of land-use patterns depending on the compatibilities among land-use categories. Accordingly, this study introduces three LUM measures – adjacency, intensity, and proximity – to identify differences in the spatial distribution of land-use categories. Based on these measures, a land-use allocation model is developed to specify spatial patterns satisfying the given compatibilities. This model is tested by applying the concept of the neighborhood unit on a case study of normative land-use patterns subject to specified compatibilities. The results describe spatial features of four compatibility sets, including a set exhibiting a compatibility conflict between the same land-use pair and LUM measures when, for example, a given land-use pair is compatible in terms of intensity but incompatible in terms of proximity. Understanding the spatial features of a normative land-use pattern that satisfies various possible compatibilities will facilitate the incorporation of the LUM approach into local planning guidance and zoning ordinances.     

Palaeointensity In the Pelagic Realm: Marine Sediment Data Compared With Archaeomagnetic and Lake Sediment Records

Summary. Four box cores collected from the Ontong—Java plateau during the Eurydice expedition have been used to make relative geomagnetic palaeo-intensity measurements. Rock magnetic measurements on the sediments show that they are characterized by a uniform magnetic mineralogy, and that they are suitable for relative intensity estimates. These are obtained by normalizing the NRM by an ARM imparted in a low DC bias field. the palaeoceanographic event known as the preservation spike is used to establish a crude time-scale for the record so that it may be compared with other data from the same region, and also with global palaeointensity estimates. the marine sediment data are quite similar to Australian intensity data from lake sediments and archaeomagnetic sources, but as might be expected exhibit some obvious differences from the global record.     

Spatial measurements of stream baseflow,a relevant method for aquifer characterization and permeability evaluation. Application to a hard‐rock aquifer,the Oman ophiolite

The structure, functioning and hydrodynamic properties of aquifers can be determined from an analysis of the spatial variability of baseflow in the streams with which they are associated. Such analyses are based on simple low‐cost measurements. Through interpreting the hydrological profiles (Q = f(A)) it is possible to locate the aquifer(s) linked to the stream network and to determine the type of interrelated flow, i.e. whether the stream drains or feeds the aquifer. Using an analytical solution developed for situations with a positive linear relationship, i.e. where the baseflow increases linearly with increasing catchment size, it is also possible to estimate the permeability of the aquifer(s) concerned at catchment scale. Applied to the hard‐rock aquifers of the Oman ophiolite, this method shows that the ‘gabbro’ aquifer is more permeable than the ‘peridotite’ aquifer. As a consequence the streams drain the peridotites and ‘leak’ into the gabbro. The hydrological profiles within the peridotite are linear and positive, and indicate homogeneity in the hydrodynamic properties of these formations at the kilometre scale. The permeability of the peridotite is estimated at 5 · 10^?7 to 5 · 10^?8 m/s. Copyright © 2004 John Wiley & Sons, Ltd.     

莱州湾南岸潍河下游地区咸水入侵灾害成因及特征

通过对莱州湾南岸咸水入侵较严重地潍河下游地区晚更新世以来沉积特征及现代自然环境条件变化的分析，探讨了沉积相对咸水入侵产生及空间范围特征的环境机理。晚更新世以来的三次海平面升降变化造成了潍河下游地区海陆沉积环境交替，形成了巨厚的海陆交互相沉积层。海进时期，大面积的滨海平原被淹没，在近海平原洼地滞留的海水经过蒸发、浓缩变为卤水，成为咸水入侵的物源；海退后陆源碎屑在滨海地区沉积形成了巨厚的古河道砂层。20世纪70年代末期以来，随着对地下淡水的过度开采，淡咸水水头压力差减小．卤水通过古河道砂层快速南侵。通过对潍河下游地区100余个地质钻孔水化学连续监测资料分析，阐明了咸水入侵的特征，有针对性地提出了咸水入侵的防治措施。     

Pollen-based reconstructions of Holocene vegetation and climatic change of Tibetan Plateau

A synthesis of Holocene pollen records from the Tibetan Plateau shows the history of vegetation and climatic changes during the Holocene. Palynological evidences from 24 cores/sections have been compiled and show that the vegetation shifted from subalpine/alpine conifer forest to subalpine/alpine evergreen sclerophyllous forest in the southeastern part of the plateau; from alpine steppe to alpine desert in the central, western and northern part; and from alpine meadow to alpine steppe in the eastern and southern plateau regions during the Holocene. These records show that increases in precipitation began about 9 ka from the southeast, and a wide ranging level of increased humidity developed over the entire of the plateau around 8-7 ka, followed by aridity from 6 ka and a continuous drying over the plateau after 4-3 ka. The changes in Holocene climates of the plateau can be interpreted qualitatively as a response to orbital forcing and its secondary effects on the Indian Monsoon which expanded northwards