Available Water Supply Research Articles

Seasonal water-level perturbations beneath the high plains of the Llano Estacado

Study regionThe Llano Estacado is a vast elevated plain located at the southern end of the Great Plains of North America. The Llano Estacado region is favorably situated above the southernmost extension of the Ogallala Aquifer, which provides groundwater for a highly productive irrigated agricultural system. Study focusA method was developed to compute the average deviation of the groundwater level from a nonstationary annual-average water level. New hydrological insights for the regionGroundwater is pumped from the Ogallala Aquifer during each growing season, which induces seasonal and long-term changes in observed groundwater levels. Recorder wells, maintained by the Texas Water Development Board, track these changes and provide a wealth of hydrologic data. Of special interest here are seasonal water-level perturbations induced by nearby actively pumped wells. Groundwater levels are observed to follow a regular pattern of declining water levels during the growing season followed by a recovery after irrigation systems are shut down. In areas with limited groundwater, farmers may shut off irrigation systems when soil moisture is adequate or when the supply of available water becomes critically low. As a result, one can often detect periods during the growing season when irrigation is paused and the water table is allowed time to partially recover. Such hydrographic deviations appear to correlate closely with periods of abundant rainfall. In areas where groundwater supplies are more plentiful, irrigation breaks are less evident. This suggests that farmers with adequate groundwater may be less inclined to shutdown irrigation systems to conserve water despite adequate rainfall.

Efecto del uso de aguas provenientes de la producción petrolera en actividades agrícolas y pecuarias

La oferta total de agua en el país es de 2,01 billones de metros cúbicos. De este volumen, la industria del petróleo tiene concesionado un total de 67,5 millones, que equivalen al 0,00336 % de la oferta total de agua en Colombia. Todo ese consumo esta formalizado mediante concesiones otorgadas por autoridades ambientales. Por otra parte, el petróleo que se extrae de la tierra sale mezclado con aguas conocidas como aguas de producción, que hacen parte de los fluidos naturales de los reservorios. En Colombia, por cada barril de petróleo se producen, en promedio, 13 barriles de agua. Las aguas de producción pueden ser tratadas y reinyectadas en la misma formación, para mantener la presión de los yacimientos y aumentar el factor de recobro; ser tratadas y vertidas a cuerpos
 de aguas superficiales o al suelo, o ser reinyectadas en los yacimientos, como estrategia de disposición final. Las aguas de producción de los yacimientos de la Orinoquia tienen un contenido relativamente bajo de sales y solidos disueltos, y no poseen elementos radioactivos. Esta condición permite que, una vez que sean tratadas, puedan reusarse en actividades productivas, en predios rurales que se encuentren en el área de influencia de los proyectos petroleros. Por estas razones, la Corporación Colombiana de Investigacion Agropecuaria (Corpoica) desarrollo una serie de trabajos de investigación, dirigidos a evaluar opciones de utilización de estas aguas de producción tratadas, para la irrigación de cultivos y pastos, así como el consumo de ganado y aves de corral. Se determinó el efecto de la aplicación de aguas de producción tratadas en diferentes componentes del ecosistema y en sistemas de producción agrícola y pecuario. El estudio se desarrolló en el departamento del Meta, en el predio denominado Área Sostenible Agroenergética (ASA) (03°53’06” N y 73°35’04” O) y en el Centro de Investigacion La Libertad (04°03’32” N y 73°27’59” O), ubicados en los municipios de Acacias y Villavicencio, respectivamente. El agua de producción tratada que se utilizó provenía de los campos de Castilla y Apiay. Se seleccionó un conjunto de variables de suelos, agua, cultivos y animales, que fueron monitoreadas y analizadas entre los años 2011 y 2015. Los resultados de esta investigación indican que la utilización de estas aguas y su aplicación al suelo no presentaron efectos significativos en las propiedades físicas y químicas del suelo. Tampoco se evidenciaron consecuencias significativas en la calidad de las aguas superficiales y subterráneas, ni en la salud de animales y cultivos.

Participatory Management of Irrigation System in North Eastern Region of India

The demand of water by various competing sectors, such as industry, power, drinking and irrigation, is increasing while the supply of available fresh water remains the same. This calls for efficient use of water in all sectors especially irrigation, which consumes the highest amount of water in India. Due to recurrence of drought and flood India suffered from famine, so after the Independence the government has rigorously pursued the construction of irrigation dams to increase agricultural production and meet the increasing demand of food. Construction of dams was given priority than management of irrigation projects. But due to a large gap between irrigation potential created and irrigation potential utilized, there was a paradigm shift in the irrigation sector. As a result, the concept of participatory irrigation management (PIM) was widely spread through seminars, National Water Policies and specific irrigation Command Area Development (CAD) programme. The first National Water Policy in 1987 and the subsequent policies had provisions for involvement of farmers in irrigation management for efficient use of irrigation water. Many states in India implemented PIM Act under the policy. It also applies to the northeastern region (NE region) of India. This region has a traditional irrigation system such as bamboo drip irrigation in Meghalaya, water conservation among the Apatanis of Arunachal Pradesh, zabo system of Nagaland and dong irrigation among the Bodos of Assam which are traditionally managed by the farmers. This article examines the farmers’ participation in irrigation management in the NE region. It attempts to highlight the changes of PIM policies, involvement of farmers or the Water Users’ Associations (WUAs) in irrigation management, constraints and suggest ways to strengthen them for efficient use of irrigation water in the NE region of India.

On the use of the GRACE normal equation of inter-satellite tracking data for estimation of soil moisture and groundwater in Australia

Abstract. An accurate estimation of soil moisture and groundwater is essential for monitoring the availability of water supply in domestic and agricultural sectors. In order to improve the water storage estimates, previous studies assimilated terrestrial water storage variation (ΔTWS) derived from the Gravity Recovery and Climate Experiment (GRACE) into land surface models (LSMs). However, the GRACE-derived ΔTWS was generally computed from the high-level products (e.g. time-variable gravity fields, i.e. level 2, and land grid from the level 3 product). The gridded data products are subjected to several drawbacks such as signal attenuation and/or distortion caused by a posteriori filters and a lack of error covariance information. The post-processing of GRACE data might lead to the undesired alteration of the signal and its statistical property. This study uses the GRACE least-squares normal equation data to exploit the GRACE information rigorously and negate these limitations. Our approach combines GRACE's least-squares normal equation (obtained from ITSG-Grace2016 product) with the results from the Community Atmosphere Biosphere Land Exchange (CABLE) model to improve soil moisture and groundwater estimates. This study demonstrates, for the first time, an importance of using the GRACE raw data. The GRACE-combined (GC) approach is developed for optimal least-squares combination and the approach is applied to estimate the soil moisture and groundwater over 10 Australian river basins. The results are validated against the satellite soil moisture observation and the in situ groundwater data. Comparing to CABLE, we demonstrate the GC approach delivers evident improvement of water storage estimates, consistently from all basins, yielding better agreement on seasonal and inter-annual timescales. Significant improvement is found in groundwater storage while marginal improvement is observed in surface soil moisture estimates.

Modelling the water energy nexus: should variability in water supply impact on decision making for future energy supply options?

Abstract. Many countries, like South Africa, Australia, India, China and the United States, are highly dependent on coal fired power stations for energy generation. These power stations require significant amounts of water, particularly when fitted with technology to reduce pollution and climate change impacts. As water resources come under stress it is important that spatial variability in water availability is taken into consideration for future energy planning particularly with regards to motivating for a switch from coal fired power stations to renewable technologies. This is particularly true in developing countries where there is a need for increased power production and associated increasing water demands for energy. Typically future energy supply options are modelled using a least cost optimization model such as TIMES that considers water supply as an input cost, but is generally constant for all technologies. Different energy technologies are located in different regions of the country with different levels of water availability and associated infrastructure development and supply costs. In this study we develop marginal cost curves for future water supply options in different regions of a country where different energy technologies are planned for development. These water supply cost curves are then used in an expanded version of the South Africa TIMES model called SATIM-W that explicitly models the water-energy nexus by taking into account the regional nature of water supply availability associated with different energy supply technologies. The results show a significant difference in the optimal future energy mix and in particular an increase in renewables and a demand for dry-cooling technologies that would not have been the case if the regional variability of water availability had not been taken into account. Choices in energy policy, such as the introduction of a carbon tax, will also significantly impact on future water resources, placing additional water demands in some regions and making water available for other users in other regions with a declining future energy demand. This study presents a methodology for modelling the water-energy nexus that could be used to inform the sustainable development planning process in the water and energy sectors for both developed and developing countries.

Waterbird Habitat in California's Central Valley Basins Under Climate, Urbanization, and Water Management Scenarios

Abstract California's Central Valley provides critical, but threatened habitat and food resources for migrating and wintering waterfowl, shorebirds, and other waterbirds. To assist in conservation planning, the Central Valley Joint Venture identified nine basins in the Valley. The basins vary in composition and extent of habitats, which primarily include croplands and wetlands that rely on water supplies shared with other competing human and environmental uses. Changes in climate, urban development, and water supply management are uncertain and could reduce future availability of water supplies supporting waterbird habitats and limit effectiveness of wetland restoration planned by the Central Valley Joint Venture to support wintering waterbirds. We modeled 17 plausible scenarios including combinations of 3 climate projections, 3 urbanization rates, and 5 water-supply management options to promote agricultural and urban water uses, with and without wetland restoration. Our research examines the reduction in quantity and quality of habitats during the autumn migration–wintering period by basin under each scenario, and the efficacy of planned wetland restoration to compensate for reductions in flooded areas of wetland habitats. Scenario combinations of projected climate, urbanization, and water-supply management options reduced availability of flooded cropland and wetland habitats during autumn–winter and degraded the quality of seasonal wetlands (i.e., summer irrigation for improved forage production), though the extent and frequency of impacts varied by basin. Planned wetland restoration may substantially compensate for scenario-related effects on wetland habitats in each basin. However, results indicate that Colusa, Butte, Sutter, San Joaquin, and Tulare basins may require additional conservation to support summer irrigation of seasonal wetlands and winter flooding of cropland habitats. Still further conservation may be required to provide sufficient areas of flooded seasonal and semipermanent wetlands in San Joaquin and Tulare basins during autumn–winter. The main objective of this research was to provide decision support for achieving waterbird conservation goals in the valley and to inform Central Valley Joint Venture's regional conservation planning.

Studying the Impact of Water Supply on Wheat Yield by using Principle Lasso Radial Machine Learning Model

Wheat plays a vital role in the food production as it fulfills 60% requirements of calories and proteins to the 35% of the world population. Owing to wheat importance in food, wheat demand is increasing continuously. Wheat yield is committed to the availability of water supply. Due to climatic and environmental variations of different countries, water supply is not available in constant and desire quantity that is necessary for better wheat yield. So, there is a strong relationship and dependency that exists between water supply and wheat yield. Therefore, water supply is becoming an issue because it directly effects wheat yield. In this research, a Principle Lasso Radial (PLR) model is proposed using Machine Learning technique to measure the effect of water supply on wheat yield. In this Principle Lasso Radial (PLR) model, various experiments are conducted with respect to the performance metrics, i.e. relative water contents, waxiness, grain per spike and plant height. Principle Lasso Radial (PLR) model’s produced reduced dimensional data with respect to performance metrics. That data is provided to Radial Basis Neural Network (RBNN), and it showed regression values R under different water supply conditions. Principle Lasso Radial (PLR) model achieved an accuracy of 89% among variance Machine Learning techniques.

A joint-probabilistic programming method for water resources optimal allocation under uncertainty: a case study in the Beiyun River, China

Abstract In recent years, the lower reaches of the Beiyun River have suffered from growing water resource shortages due to the reduction of upstream water resource and drying up of the stream channel. More reasonable and scientifically based water allocation plans should be developed and implemented; however, uncertainties exist regarding the determination of water supply availability and spillage of extra water. To assess and manage regional water shortage, the combined effects of multiple water supply sources as well as the joint probability of typical events should be considered. The joint probability of water supply, considering upstream and local water supplies, was estimated through the copula functions. A multi-objective optimization model was then developed and solved by improved genetic algorithms to plan water resources allocation within a multi-source environment containing multiple competitive users. The framework is demonstrated, and represents a range of different water supply scenarios in terms of different probabilities of occurrence and constraint violations. The results showed that water allocation was greatly influenced by uncertainties, especially in upstream-local water supply. In addition, violating water-allocation constraint posed an extra uncertainty. This study facilitates the proposition of adaption allocation plans for uncertain environments, aiming to balance the shortage, economy, and reliability.

Characterising alluvial aquifers in a remote ephemeral catchment (Flinders River, Queensland) using a direct push tracer approach

The availability of reliable water supplies is a key factor limiting development in northern Australia. However, characterising groundwater resources in this remote part of Australia is challenging due to a lack of existing infrastructure and data. Here, direct push technology (DPT) was used to characterise shallow alluvial aquifers at two locations in the semiarid Flinders River catchment. DPT was used to evaluate the saturated thickness of the aquifer and estimate recharge rates by sampling for environmental tracers in groundwater (major ions, 2H, 18O, 3H and 14C). The alluvium at Fifteen Mile Reserve and Glendalough Station consisted of a mixture of permeable coarse sandy and gravely sediments and less permeable clays and silts. The alluvium was relatively thin (i.e. < 20 m) and, at the time of the investigation, was only partially saturated. Tritium (3H) concentrations in groundwater was ∼1 Tritium Unit (TU), corresponding to a mean residence time for groundwater of about 12 years. The lack of an evaporation signal for the 2H and 18O of groundwater suggests rapid localised recharge from overbank flood events as the primary recharge mechanism. Using the chloride mass balance technique (CMB) and lumped parameter models to interpret patterns in 3H in the aquifer, the mean annual recharge rate varied between 21 and 240 mm/yr. Whilst this recharge rate is relatively high for a semiarid climate, the alluvium is thin and heterogeneous hosting numerous alluvial aquifers with varied connectivity and limited storage capacity. Combining DPT and environmental tracers is a cost-effective strategy to characterise shallow groundwater resources in unconsolidated sedimentary aquifers in remote data sparse areas.

A remote sensing method for estimating regional reservoir area and evaporative loss

Evaporation from the water surface of a reservoir can significantly affect its function of ensuring the availability and temporal stability of water supply. Current estimations of reservoir evaporative loss are dependent on water area derived from a reservoir storage-area curve. Such curves are unavailable if the reservoir is located in a data-sparse region or questionable if long-term sedimentation has changed the original elevation-area relationship. We propose a remote sensing framework to estimate reservoir evaporative loss at the regional scale. This framework uses a multispectral water index to extract reservoir area from Landsat imagery and estimate monthly evaporation volume based on pan-derived evaporative rates. The optimal index threshold is determined based on local observations and extended to unobserved locations and periods. Built on the cloud computing capacity of the Google Earth Engine, this framework can efficiently analyze satellite images at large spatiotemporal scales, where such analysis is infeasible with a single computer. Our study involves 200 major reservoirs in Texas, captured in 17,811 Landsat images over a 32-year period. The results show that these reservoirs contribute to an annual evaporative loss of 8.0 billion cubic meters, equivalent to 20% of their total active storage or 53% of total annual water use in Texas. At five coastal basins, reservoir evaporative losses exceed the minimum freshwater inflows required to sustain ecosystem health and fishery productivity of the receiving estuaries. Reservoir evaporative loss can be significant enough to counterbalance the positive effects of impounding water and to offset the contribution of water conservation and reuse practices. Our results also reveal the spatially variable performance of the multispectral water index and indicate the limitation of using scene-level cloud cover to screen satellite images. This study demonstrates the advantage of combining satellite remote sensing and cloud computing to support regional water resources assessment.

Multiple Cropping after the Rice Harvest in Rainfed Rice Cropping Systems in Khon Kaen Province, Northeast Thailand

(ProQuest: ... denotes non-US-ASCII text omitted.)IntroductionIn rainfed rice fields in Northeast Thailand, only a single crop of rice is commonly planted in the rainy season. Moreover, the yield of rice is generally low, averaging 1.7 t/ha. The low productivity coupled with low and fluctuating prices and high input costs severely limits the profitability of rice production and keeps many farmers trapped in poverty. Cropping intensification through multiple cropping could be a way to increase productivity and boost rural incomes.In the past, multiple cropping was rarely practiced in Northeast Thailand due to the limited biophysical resources (e.g., low and erratic rainfall, infertile sandy soils, limited availability of surface water supplies, serious problem of insect pests, long duration of the rice crop) (Terd et al. 1976a; 1976b; 1978a; 1978b; Aran et al. 1977a; 1977b; 1977c; KKU-Ford Cropping System Project 1982; Rambo 1991; Viriya 2001). Even when experimental multiple cropping systems were agronomically successful, farmers did not adopt them (Vichain and Aran 1990), mostly due to social and economic constraints, including limited markets for crops, labor competition, and lack of capital and knowledge (Rigg 1985; Vichain and Aran 1990). Although the factors limiting the adoption of multiple cropping were well understood in the context of rainfed agriculture in the 1980s, the situation in the Northeast has undergone rapid change since then. The context for multiple cropping is now quite different from what it was in the past. Key changes include the widespread adoption of the drought-tolerant RD6 glutinous rice variety and use of diesel pumps to provide supplementary irrigation water from newly dug farm ponds, which have helped to stabilize rice yields in years of low rainfall. The resulting higher and more stable yields of glutinous rice have allowed farmers to plant a larger share of their land with non-glutinous KDML105, which is raised as a cash crop, providing rural households with a new source of income. Agricultural intensification is occurring to an extent unimaginable just a few years ago. Relying on remittances sent back to their families by migrant workers, as well as cash earned by engaging in off-farm employment in new factories and service jobs in local urban centers, Isan farmers have been rapidly adopting modern agricultural technology, including increased use of chemical fertilizers, pesticides, and farm machinery (Grandstaff et al. 2008). Multiple cropping and cultivation of high-value crops to supply growing urban markets are also more commonly practiced (Rambo 2012).In Khon Kaen Province, farmers now employ a variety of locally developed double cropping systems to grow cash crops after the rice harvest and thus raise farm incomes. Some farmers grow high-value vegetable crops after the rice harvest, such as Chinese radish (Patcharaporn and Orawan 2011), tomato for seed production (Prapatsorn and Wareerat 2010), glutinous corn (Uraiwan et al. 2010), and various green vegetables, which provided a net income of USD7,727-12,733 per hectare per season. Even though some examples of multiple cropping after rice have been reported, there have been no detailed studies on the localities, planted areas, types of crops, and number of households adopting these systems; nor has there been any detailed analysis of the factors associated with the occurrence of each system of multiple cropping. This research, therefore, was undertaken in order to identify localities, planted areas, types of crops, and number of households growing crops after the harvest of rainfed rice in Khon Kaen Province and to identify physical, social, and economic factors associated with the occurrence of these cropping systems.MethodologyStudy AreaThe study area was the whole of Khon Kaen Province, Northeast Thailand. It is located between latitude 15°40' to 17°5'N and longitude 101°45' to 103°45'E. …

Efficient crop model parameter estimation and site characterization using large breeding trial data sets

Scientists have estimated that global crop production needs to double by 2050 to supply the demand for food, feed, and fuel. To reach this goal, novel methods are needed to increase breeding potential yield rates of gain as well as on-farm yields through enhanced management strategies. Both of these tasks require the ability to predict plant performance in multiple, dynamic environments based on a knowledge of cultivar characteristics (critical short day lengths, maximum leaf photosynthetic rates, pod fill durations, etc.) that are ultimately linked to genetics. Because of this linkage, we refer to such traits as genotype-specific parameters (GSP's). Using industry-provided yield and weather data from 353 site-years, we estimated seven primary CROPGRO-Soybean GSP's for each of 182 varieties. The data set had two shortcomings. First, no planting dates were supplied, rendering unknowable the environment actually experienced by the crop. Second, soil data were provided only for the top 20cm, which is inadequate to specify the root environment and water supply availability. Therefore, additional edaphic information was acquired. A novel optimization algorithm was developed that simultaneously estimates GSP's and planting dates, while tuning layered soil water-holding properties. The optimizer, which we have named the holographic genetic algorithm (HGA), uses both externally supplied constraints and its own analysis of data structure to reduce what would otherwise be a search over 2000 dimensions to a much smaller number of overlapping 1- to 3-D problems. Two types of runs were performed. The first was preceded by an independent component analysis (ICA) of published GSP's. The subsequent training sought good component scores rather than the GSP's themselves. The second, separate factor (SF) approach allowed all GSP's to vary separately. This makes parameters unconstrained and more evenly distributed. Results showed that HGA works quite well with the CROPGRO-Soybean model to estimate the cultivar and site-specific parameters from breeding trial data. The quality of the calibrations and evaluations were similar across both run types with RMSE values being ca. 5.6% of the maximum yields. Moreover, the GSP's for a variety can be used to predict its yield in trials not used in that cultivar's calibration. Finally, despite high dimensionality, the GSP's, planting dates, and soil properties for all lines and sites converged concurrently in <58 iterations, demonstrating great utility for use with big data sets.

Priority of Water Supply Service for Community in Gresik City, East Java Province

Water supply is one of important aspect and a priority in urban planning. The fulfillment of a water supply necessity for Gresik City is still not optimized. Gresik City consists of 2 districts, namely Gresik District and Kebomas District. Based on ministerial regulation 14/2010, coverage of water supply service at Gresik City was classified as bad with water supply service rate less than 50%. Hence, for the sake of optimizing and equity of water supply service at Gresik City, the identification of water supply service ratio of Gresik City and community's perception of water supply service was needed. The research objective was to identify water supply service priority for community at Gresik City. The ratio analysis was done by calculation method based on water supply necessity and availability standard. While, the analysis of water supply service based on community's perception was done by descriptive statistical analysis. The results showed that the highest ratio of water supply service was on Kroman Sub-District and the lowest ratio of water supply service was on Tenggulunan Sub-District. Based on community's perception analysis, there are 93% of Gresik District residents and 75% of Kebomas District residents that haven't used PDAM (local water supply company) water supply service. Furthermore, water supply service wasn't optimized yet in term of water quality, quantity, continuity, so that the handling of water supply service was focused on sub-district with lowest water supply service ratio.

Development of soil water regime under spruce stands

Abstract The aim of this paper is to analyse the water regime of soils under spruce ecosystems in relation to long-lasting humid and drought periods in the growing seasons 1991-2013. The dominant interval humidity in observing growing seasons is semiuvidic interval with soil moisture between hydro-limits maximal capillary capacity (MCC) and point of diminished availability (PDA). Gravitationally seepage concentrated from accumulated winter season, water from melting snow and existing atmospheric precipitation occurs in the soil only at the beginning of the growing season. The supplies of soil water are significantly decreasing in the warm climate and precipitant deficient days. The greatest danger from drought threatens Norway spruce during the summer months and it depends on the duration of dry days, water supply at the beginning of the dry days, air temperature and the intensity of evapotranspiration. In the surface layers of the soil, with the maximum occurrence of active roots, the water in semiarid interval area between hydro-limits PDA and wilting point (WP) decreases during the summer months. In the culminating phase occurs the drying to moisture state with capillary stationary and the insufficient supply of available water for the plants. Physiological weakening of Norway spruce caused by set of outlay components of the water balance is partially reduced by delivering of water by capillary action from deeper horizons. In extremely dry periods, soil moisture is decreasing also throughout the soil profile (0-100 cm) into the bottom third of the variation margin hydro-limits MCC-PDA in the category of capillary less moving and for plants of low supply of usable water (60-90 mm). The issue of deteriorated health state of spruce ecosystems is considered to be actual. Changes and developments of hydropedological conditions which interfere the mountain forests represent the increasing danger of the drought for the spruce.

A GIS Based Design of Groundwater Level Monitoring Network Using Multi-Criteria Analysis and Geostatistical Method

Groundwater systems are dynamic and hence, an effective and optimally designed groundwater level (GWL) monitoring network is very essential to minimize monitoring, time and long term expenses. Groundwater scarcity is a big challenge in regions where excessive extraction takes place and GWL monitoring from observation wells (OWs) is the principal source of information. Hence, proper observation and management is necessary to ensure continual availability of water supplies. This study proposes a new and simplified approach using multi-criteria analysis (weighted overlay, analytical hierarchical process, fuzzy) and geostatistical (ordinary kriging) method to design GWL monitoring network of the Wainganga sub-basin, India. Several parameters considered for the analysis include command area (CA) and non command area (NCA), geology, geomorphologic unit, land use/land cover (LU/LC), lineament density, Groundwater level fluctuation (GWLF), recharge, slope and soil media. The study identifies representative or priority zones using multi-criteria analysis and optimum number of OW was determined within the representative zones using geostatistical method. Combination of two approaches helps overcome shortcomings of previously suggested methods of which analytical hierarchical process (AHP)-geostatistical approach gives more accurate results. Sensitivity analysis was carried out to identify importance of each parameter considered for analysis. The study concludes that minimum 80 wells are required for proper monitoring of GWL in the study area. It also reveals that a combination of these two approaches is effective and easy to implement in the regions where data availability is not constrained.

Innovative Approaches to Collaborative Groundwater Governance in the United States: Case Studies from Three High-Growth Regions in the Sun Belt.

Groundwater is an increasingly important source of freshwater, especially where surface water resources are fully or over-allocated or becoming less reliable due to climate change. Groundwater reliance has created new challenges for sustainable management. This article examines how regional groundwater users coordinate and collaborate to manage shared groundwater resources, including attention to what drives collaboration. To identify and illustrate these facets, this article examines three geographically diverse cases of groundwater governance and management from the United States Sun Belt: Orange County Water District in southern California; Prescott Active Management Area in north-central Arizona; and the Central Florida Water Initiative in central Florida. These regions have different surface water laws, groundwater allocation and management laws and regulations, demographics, economics, topographies, and climate. These cases were selected because the Sun Belt faces similar pressures on groundwater due tohistorical and projected population growth and limited availability of usable surface water supplies. Collectively, they demonstrate groundwater governance trends in the United States, and illustrate distinctive features of regional groundwater management strategies. Our research shows how geophysical realities and state-level legislation have enabled and/or stimulated regions to develop groundwater management plans and strategies to address the specific issues associated with their groundwater resources. We find that litigation involvement and avoidance, along with the need to finance projects, are additional drivers of regional collaboration to manage groundwater. This case study underscores the importance of regionally coordinated and sustained efforts to address serious groundwater utilization challenges faced by the regions studied and around the world.

Water availability in Water-economic basins in Kazakhstan and their Anthropogenic transformation

Water is one of the most important natural resources. The water availability and scarcity depend on various natural and anthropogenic factors. On the basis of generalization and analyses of the numerous cartographic materials, the water-economic basins (WEBs) in Kazakhstan were classified in order to identify the basin affected by human activities the most. Additionally, the water supply (availability) in the WEBs was determinated by share (%) of water resources (rivers, lakes, water reservoirs). The Zhaiyk-Caspian WEB has the highest share (94%) of river water. By water resource (43.8 km3), the Ertis WEB is the most water-rich basin. A significant anthropogenic transformation was observed in the Aral-Syrdarya and Esil WEBs. Both basins are characterized by water pollution and a deteriorated water quality.

Water supply as a constraint on transmission expansion planning in the Western interconnection

Consideration of water supply in transmission expansion planning (TEP) provides a valuable means of managing impacts of thermoelectric generation on limited water resources. Toward this opportunity, thermoelectric water intensity factors and water supply availability (fresh and non-fresh sources) were incorporated into a recent TEP exercise conducted for the electric interconnection in the Western United States. The goal was to inform the placement of new thermoelectric generation so as to minimize issues related to water availability. Although freshwater availability is limited in the West, few instances across five TEP planning scenarios were encountered where water availability impacted the development of new generation. This unexpected result was related to planning decisions that favored the development of low water use generation that was geographically dispersed across the West. These planning decisions were not made because of their favorable influence on thermoelectric water demand; rather, on the basis of assumed future fuel and technology costs, policy drivers and the topology of electricity demand. Results also projected that interconnection-wide thermoelectric water consumption would increase by 31% under the business-as-usual case, while consumption would decrease by 42% under a scenario assuming a low-carbon future. Except in a few instances, new thermoelectric water consumption could be accommodated with less than 10% of the local available water supply; however, limited freshwater supplies and state-level policies could increase use of non-fresh water sources for new thermoelectric generation. Results could have been considerably different if scenarios favoring higher-intensity water use generation technology or potential impacts of climate change had been explored. Conduct of this exercise highlighted the importance of integrating water into all phases of TEP, particularly joint management of decisions that are both directly (e.g., water availability constraint) and indirectly (technology or policy constraints) related to future thermoelectric water demand, as well as, the careful selection of scenarios that adequately bound the potential dimensions of water impact.

Hyperspectral sensing to detect the impact of herbicide drift on cotton growth and yield

Yield loss in crops is often associated with plant disease or external factors such as environment, water supply and nutrient availability. Improper agricultural practices can also introduce risks into the equation. Herbicide drift can be a combination of improper practices and environmental conditions which can create a potential yield loss. As traditional assessment of plant damage is often imprecise and time consuming, the ability of remote and proximal sensing techniques to monitor various bio-chemical alterations in the plant may offer a faster, non-destructive and reliable approach to predict yield loss caused by herbicide drift. This paper examines the prediction capabilities of partial least squares regression (PLS-R) models for estimating yield. Models were constructed with hyperspectral data of a cotton crop sprayed with three simulated doses of the phenoxy herbicide 2,4-D at three different growth stages. Fibre quality, photosynthesis, conductance, and two main hormones, indole acetic acid (IAA) and abscisic acid (ABA) were also analysed. Except for fibre quality and ABA, Spearman correlations have shown that these variables were highly affected by the chemical. Four PLS-R models for predicting yield were developed according to four timings of data collection: 2, 7, 14and28daysafter the exposure (DAE). As indicated by the model performance, the analysis revealed that 7 DAE was the best time for data collection purposes (RMSEP=2.6andR2=0.88), followed by 28 DAE (RMSEP=3.2andR2=0.84). In summary, the results of this study show that it is possible to accurately predict yield after a simulated herbicide drift of 2,4-D on a cotton crop, through the analysis of hyperspectral data, thereby providing a reliable, effective and non-destructive alternative based on the internal response of the cotton leaves.

Using and abusing a torrential urban river: the Wien River before and during industrialization

The Wien River is the largest tributary of the Viennese Danube and was a center of urban production during industrialization. It’s highly dynamic flow regime with small average discharge as well as recurrent big, fast floods posed challenges to its use. In this study we focus on the role of this urban watercourse for supplying water to crafts and industries and for wastewater discharge in the 19th century. Animal slaughtering, tanning, dyeing, textile printing, beer brewing, and chemical industry as main water demanding and polluting crafts were investigated. Their location in the catchment was determined and they were systematized by their needs of water and types of pollutants released into the river. Spatial distribution patterns of these industries from the end of the 18th to the end of the 19th century show a complex picture in terms of water supply and waste water discharge. We found very distinct patterns for different sections of the river as well as for different crafts and could observe a change over the time period investigated. Only few types of businesses lied close to the Wien River which can, to some extent, be explained with the high risk of flooding. Groundwater played a more important role for water supply while the main function of the river was wastewater discharge. Spatial distribution of crafts and industries, and changes in locations resulted from an interplay of environmental and social factors. Availability of surface waters, water supply, and discharge infrastructure (wells, pipelines, sewers) seem to have been important for the choice of location for production sites. Regulations concerning the exertion of industries, economic factors and technological innovation also played a role in the development of the observed spatial pattern.