Relevant bibliographies by topics / Land Surface Water Index

Academic literature on the topic 'Land Surface Water Index'

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Published: 11 March 2023

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Journal articles on the topic "Land Surface Water Index"

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Christian, Jordan I., Jeffrey B. Basara, Lauren E. L. Lowman, Xiangming Xiao, Daniel Mesheske, and Yuting Zhou. "Flash drought identification from satellite-based land surface water index." Remote Sensing Applications: Society and Environment 26 (April 2022): 100770. http://dx.doi.org/10.1016/j.rsase.2022.100770.

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Li, Li, Qidi Yu, Ling Gao, Bin Yu, and Zhipeng Lu. "The Effect of Urban Land-Use Change on Runoff Water Quality: A Case Study in Hangzhou City." International Journal of Environmental Research and Public Health 18, no. 20 (October 13, 2021): 10748. http://dx.doi.org/10.3390/ijerph182010748.

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The main functions of this research are to guide the proportion of urban land that is used and the layout of the facilities on it, help understand the changes to surface runoff that are caused by land being used in urban development, and thus solve surface runoff pollution. Hangzhou City, China has been selected for the experiment, and the way in which its land is utilized as well as the grading of urban construction projects in the demonstration area are specifically analyzed. This study systematically distinguishes the definitions of impervious area based on the Sutherland equation and analyzes the impact of different impervious area subtypes on surface runoff water quality. Then, we compare the impact of impervious area subtypes with the impact of other land-use patterns on surface runoff water quality. This study shows the relationship between different land-use types and runoff water bodies: Land-use index can affect runoff water quality; Greening activities, impervious surface, and the water quality index are negatively correlated; the effective impervious area rate is positively correlated with the water quality index. The paper suggests that increasing the proportion of green spaces and permeable roads in build-up land reduces the effective impervious area (EIA) and thus controls land runoff pollution and improves runoff water quality.
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Cui, Yaoping, Yiming Fu, Nan Li, Xiaoyan Liu, Zhifang Shi, Jinwei Dong, and Yan Zhou. "A Novel Approach for Automatic Urban Surface Water Mapping with Land Surface Temperature (AUSWM)." Remote Sensing 14, no. 13 (June 25, 2022): 3060. http://dx.doi.org/10.3390/rs14133060.

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The principal difficulty in extracting urban surface water using remote-sensing techniques is the influence of noise from complex urban environments. Although various methods exist, there are still many sources of noise interference when extracting urban surface water, and automatic cartographic methods with long time series are especially scarce. Here, we construct an automatic urban surface water extraction method from the combination of traditional water index, urban shadow index (USI), and land surface temperature (LST) by using the Google Earth Engine cloud computing platform and Landsat imagery. The three principal findings derived from the application of the method were as follows. (i) In comparison with autumn and winter, LST in spring and summer could better distinguish water from high-reflection ground objects, shadows, and roads and roofs covered by asphalt. (ii) The overall accuracy of Automated Water Extraction Index (AWEIsh) in Zhengzhou was 77.5% and the Kappa coefficient was 0.55; with consideration of the USI and LST, the overall accuracy increased to 96.0% and the Kappa coefficient increased to 0.92. (iii) During 1990–2020, the area of urban surface water in Zhengzhou increased, with an evident trend in expansion from 11.51 km2 in 2008 to 49.28 km2 in 2020. Additionally, possible omissions attributable to using 30m-resolution imagery to extract urban water areas were also discussed. The method proposed in this study was proven effective in eliminating the influence of noise in urban areas, and it could be used as a general method for high-accuracy long-term mapping of urban surface water.
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Chowdhury, Tahmid Anam, and Md Saiful Islam. "Assessing and Simulating Impacts of Land Use Land Cover Changes on Land Surface Temperature in Mymensingh City, Bangladesh." Environment and Natural Resources Journal 20, no. 2 (November 26, 2021): 1–19. http://dx.doi.org/10.32526/ennrj/20/202100110.

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Urban developments in the cities of Bangladesh are causing the depletion of natural land covers over the past several decades. One of the significant implications of the developments is a change in Land Surface Temperature (LST). Through LST distribution in different Land Use Land Cover (LULC) and a statistical association among LST and biophysical indices, i.e., Urban Index (UI), Bare Soil Index (BI), Normalized Difference Builtup Index (NDBI), Normalized Difference Bareness Index (NDBaI), Normalized Difference Vegetation Index (NDVI), and Modified Normalized Difference Water Index (MNDWI), this paper studied the implications of LULC change on the LST in Mymensingh city. Landsat TM and OLI/TIRS satellite images were used to study LULC through the maximum likelihood classification method and LSTs for 1989, 2004, and 2019. The accuracy of LULC classifications was 84.50, 89.50, and 91.00 for three sampling years, respectively. From 1989 to 2019, the area and average LST of the built-up category has been increased by 24.99% and 7.6ºC, respectively. Compared to vegetation and water bodies, built-up and barren soil regions have a greater LST each year. A different machine learning method was applied to simulate LULC and LST in 2034. A remarkable change in both LULC and LST was found through this simulation. If the current changing rate of LULC continues, the built-up area will be 59.42% of the total area, and LST will be 30.05ºC on average in 2034. The LST in 2034 will be more than 29ºC and 31ºC in 59.64% and 23.55% areas of the city, respectively.
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Ciężkowski, Wojciech, Sylwia Szporak-Wasilewska, Małgorzata Kleniewska, Jacek Jóźwiak, Tomasz Gnatowski, Piotr Dąbrowski, Maciej Góraj, Jan Szatyłowicz, Stefan Ignar, and Jarosław Chormański. "Remotely Sensed Land Surface Temperature-Based Water Stress Index for Wetland Habitats." Remote Sensing 12, no. 4 (February 14, 2020): 631. http://dx.doi.org/10.3390/rs12040631.

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Despite covering only 2–6% of land, wetland ecosystems play an important role at the local and global scale. They provide various ecosystem services (carbon dioxide sequestration, pollution removal, water retention, climate regulation, etc.) as long as they are in good condition. By definition, wetlands are rich in water ecosystems. However, ongoing climate change with an ambiguous balance of rain in a temperate climate zone leads to drought conditions. Such periods interfere with the natural processes occurring on wetlands and restrain the normal functioning of wetland ecosystems. Persisting unfavorable water conditions lead to irreversible changes in wetland habitats. Hence, the monitoring of habitat changes caused by an insufficient amount of water (plant water stress) is necessary. Unfortunately, due to the specific conditions of wetlands, monitoring them by both traditional and remote sensing techniques is challenging, and research on wetland water stress has been insufficient. This paper describes the adaptation of the thermal water stress index, also known as the crop water stress index (CWSI), for wetlands. This index is calculated based on land surface temperature and meteorological parameters (temperature and vapor pressure deficit—VPD). In this study, an unmanned aerial system (UAS) was used to measure land surface temperature. Performance of the CWSI was confirmed by the high correlation with field measurements of a fraction of absorbed photosynthetically active radiation (R = −0.70) and soil moisture (R = −0.62). Comparison of the crop water stress index with meteorological drought indices showed that the first phase of drought (meteorological drought) cannot be detected with this index. This study confirms the potential of using the CWSI as a water stress indicator in wetland ecosystems.
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Ngandam Mfondoum, A. H., P. G. Gbetkom, R. Cooper, S. Hakdaoui, and M. B. Mansour Badamassi. "IMPROVING THE LAND SURFACE GENERAL DROUGHT INDEX MODEL." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W11 (February 14, 2020): 101–8. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w11-101-2020.

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Abstract. Drought affects all human activities and ecosystems. Nearly 40 percent of the world’s population inhabit Drylands, and they depend on agriculture for their food, security and livelihoods. Among the remote sensing indices developed, the Land Surface General Drought Index (LSGDI) was recently proposed. This paper proposes an improved model of LSGDI to face the issue of drought in semi-arid and arid regions. The experiment was conducted for the Maga’s floodplain, in North-Cameroon. The method uses satellite images of Landsat in 1987, 2003 and 2018, for January and March or April, corresponding to the middle and the end of the dry season. A Vegetation Moisture Index (VMI) and a Normalized Difference Soil Drought Index (NDSoDI) are both developed. On an orthogonal plan, their projections give a drought line that expresses the improved LSGDI (LSGDI2) as the root sum square of the NDSoDI and the VMI. The LSGDI2 results are ranged in [0.09 – 0.14] interval, which is used to define the threshold and ease the qualifiers for drought classes. The visual patterns easily match the sandy areas of the original Landsat images with the highest values, while the vegetation and water areas match the lowest values. Compared with the LSGDI and Second Modified Perpendicular drought Index (MPDI1), the new index reflectance values are higher. Finally, although LSGDI2 curve’s evolution follows the NDSoDI one at 94%, the new spectral index values depends on the both components, helping to map highest values of drought and moisture in Maga’s floodplain, for a sustainable rice culture expansion.
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Marthews, T. R., S. J. Dadson, B. Lehner, S. Abele, and N. Gedney. "A high-resolution global dataset of topographic index values for use in large-scale hydrological modelling." Hydrology and Earth System Sciences Discussions 11, no. 6 (June 12, 2014): 6139–66. http://dx.doi.org/10.5194/hessd-11-6139-2014.

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Abstract. Modelling land surface water flow is of critical importance for simulating land-surface fluxes, predicting runoff and water table dynamics and for many other applications of Land Surface Models. Many approaches are based on the popular hydrology model TOPMODEL, and the most important parameter of this model is the well-knowntopographic index. Here we present new, high-resolution parameter maps of the topographic index for all ice-free land pixels calculated from hydrologically-conditioned HydroSHEDS data sets using the GA2 algorithm. At 15 arcsec resolution, these layers are 4× finer than the resolution of the previously best-available topographic index layers, the Compound Topographic Index of HYDRO1k (CTI). In terms of the largest river catchments occurring on each continent, we found that in comparison to our revised values, CTI values were up to 20% higher in e.g. the Amazon. We found the highest catchment means were for the Murray-Darling and Nelson-Saskatchewan rather than for the Amazon and St. Lawrence as found from the CTI. We believe these new index layers represent the most robust existing global-scale topographic index values and hope that they will be widely used in land surface modelling applications in the future.
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Yang, Liangyan, Jianfeng Li, Zenghui Sun, Jinbao Liu, Yuanyuan Yang, and Tong Li. "Daily actual evapotranspiration estimation of different land use types based on SEBAL model in the agro-pastoral ecotone of northwest China." PLOS ONE 17, no. 3 (March 15, 2022): e0265138. http://dx.doi.org/10.1371/journal.pone.0265138.

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Evapotranspiration (ET) plays a crucial role in hydrological and energy cycles, as well as in the assessments of water resources and irrigation demands. On a regional scale, particularly in the agro-pastoral ecotone, clarification of the distribution of surface ET and its influencing factors is critical for the rational use of water resources, restoration of the ecological environment, and protection of ecological water sources. The SEBAL model was used to invert the regional ET based on Landsat8 images in the agro-pastoral ecotone of northwest China. The results were indirectly verified by monitoring data from meteorological stations. The correlation between ET and surface parameters was analyzed. Thus, the main factors that affect the surface ET were identified. The results show that the SEBAL model determines an accurate inversion, with a correlation coefficient of 0.81 and an average root mean square error of 0.9 mm/d, which is highly suitable for research on water resources. The correlation coefficients of normalized vegetation index, surface temperature, land surface albedo, net radiation flux with daily ET were 0.5830, 0.8425, 0.3428 and 0.9111, respectively. The normalized vegetation index and the net radiation flux positively correlated with the daily ET, while the surface temperature and land surface albedo negatively correlated with the daily ET. The correlation from strong to weak is the net radiation flux > surface temperature > normalized vegetation index > surface albedo. In terms of spatial distribution, the daily ET of water was the highest, followed by woodland, wetland, cropland, built-up land, shrub land, grassland and bare land. However, the SEBAL model overestimates the inversion of daily ET of built-up land.
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Molekoa, Mmasabata, Ram Avtar, Pankaj Kumar, Huynh Thu Minh, Rajarshi Dasgupta, Brian Johnson, Netrananda Sahu, Ram Verma, and Ali Yunus. "Spatio-Temporal Analysis of Surface Water Quality in Mokopane Area, Limpopo, South Africa." Water 13, no. 2 (January 18, 2021): 220. http://dx.doi.org/10.3390/w13020220.

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Considering the well-documented impacts of land-use change on water resources and the rapid land-use conversions occurring throughout Africa, in this study, we conducted a spatiotemporal analysis of surface water quality and its relation with the land use and land cover (LULC) pattern in Mokopane, Limpopo province of South Africa. Various physico-chemical parameters were analyzed for surface water samples collected from five sampling locations from 2016 to 2020. Time-series analysis of key surface water quality parameters was performed to identify the essential hydrological processes governing water quality. The analyzed water quality data were also used to calculate the heavy metal pollution index (HPI), heavy metal evaluation index (HEI) and weighted water quality index (WQI). Also, the spatial trend of water quality is compared with LULC changes from 2015 to 2020. Results revealed that the concentration of most of the physico-chemical parameters in the water samples was beyond the World Health Organization (WHO) adopted permissible limit, except for a few parameters in some locations. Based on the calculated values of HPI and HEI, water quality samples were categorized as low to moderately polluted water bodies, whereas all water samples fell under the poor category (>100) and beyond based on the calculated WQI. Looking precisely at the water quality’s temporal trend, it is found that most of the sampling shows a deteriorating trend from 2016 to 2019. However, the year 2020 shows a slightly improving trend on water quality, which can be justified by lowering human activities during the lockdown period imposed by COVID-19. Land use has a significant relationship with surface water quality, and it was evident that built-up land had a more significant negative impact on water quality than the other land use classes. Both natural processes (rock weathering) and anthropogenic activities (wastewater discharge, industrial activities etc.) were found to be playing a vital role in water quality evolution. This study suggests that continuous assessment and monitoring of the spatial and temporal variability of water quality in Limpopo is important to control pollution and health safety in the future.
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Berhanu, Belete, and Ethiopia Bisrat. "Identification of Surface Water Storing Sites Using Topographic Wetness Index (TWI) and Normalized Difference Vegetation Index (NDVI)." Journal of Natural Resources and Development 8 (September 7, 2018): 91–100. http://dx.doi.org/10.5027/jnrd.v8i0.09.

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Ethiopia is endowed with water and has a high runoff generation area compared to many countries, but the total stored water only goes up to approximately 36BCM. The problem of water shortage in Ethiopia emanates from the seasonality of rainfall and the lack of infrastructure for storage to capture excess runoff during flood seasons. Based on this premise, a method for a syndicate use of topography, land use and vegetation was applied to locate potential surface water storing sites. The steady-state Topographic Wetness Index (TWI) was used to represent the spatial distribution of water flow and water stagnating across the study area and the Normalized Difference Vegetation Index (NDVI) was used to detect surface water through multispectral analysis. With this approach, a number of water storing sites were identified in three categories: primary sources (water bodies based), secondary sources (Swampy/wetland based) and tertiary sources (the land based). A sample volume analysis for the 120354 water storing sites in category two, gives a 44.92BCM potential storing capacity with average depth of 4 m that improves the annual storage capacity of the country to 81BCM (8.6 % of annual renewable water sources). Finally, the research confirmed the TWI and NDVI based approach for water storing sites works without huge and complicated earth work; it is cost effective and has the potential of solving complex water resource challenges through spatial representation of water resource systems. Furthermore, the application of remote sensing captures temporal diversity and includes repetitive archives of data, enabling the monitoring of areas, even those that are inaccessible, at regular intervals.
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Dissertations / Theses on the topic "Land Surface Water Index"

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Gortan, Emmanuelle. "Misura dello stato idrico di fraxinus ornus L. quale biomonitor dell'aridità ambientale in siti diversi del carso triestino." Doctoral thesis, Università degli studi di Trieste, 2008. http://hdl.handle.net/10077/2658.

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2006/2007
L'aridità è una condizione ambientale che comporta una ridotta disponibilità d'acqua per le piante all'interno del suolo. La disponibilità d'acqua rappresenta, unitamente alla temperatura, il fattore ambientale che più di ogni altro condiziona la distribuzione e la produttività primaria della vegetazione. Poiché una prolungata aridità ambientale ha serie conseguenze sulla produttività degli ecosistemi forestali e sulla sopravvivenza di alcune specie vegetali meno competitive di altre in tali condizioni, è di fondamentale importanza quantificare il livello di aridità ambientale per poterne prevedere l'impatto attuale e le tendenze in atto. Il progetto di ricerca si poneva quindi l’obiettivo di individuare e definire un indice di aridità ambientale, che consentisse di rappresentare le relazioni che la pianta contrae con l’acqua presente nell’ambiente in funzione della risposta fisiologica della pianta al variare del contenuto idrico del suolo, attraverso un valore unico a significato ecofisiologico. L'individuazione di un parametro ecofisiologico in grado di stimare in modo affidabile l'impatto dello stress idrico poneva le basi per valutare possibili correlazioni con parametri ottenibili con il telerilevamento. Un'altra finalità del lavoro era, infatti, l'individuazione di un parametro di riferimento mediante l'utilizzo di tecniche di telerilevamento da satellite da applicare nello “scaling up” ecologico, che a partire dallo studio dell'impatto dello stress idrico su singole specie potesse indagare sistemi di vegetazione sempre più grandi nell'ottica di sviluppare una visione olistica di grandi aree in relazione all'aridità ambientale. La specie vegetale che è stata scelta come potenziale biomonitor è Fraxinus ornus L. ossia l'orniello, che è stato selezionato in quanto trattasi di una specie vegetale che si distingue per la notevole capacità di resistenza a condizioni di stress idrico e proprio per questa sua capacità, è una specie diffusa in una grande varietà di ambienti. L'area di studio scelta è stata la provincia di Trieste ed in particolare l'area carsica. Questa zona, infatti, offre l'opportunità di eseguire significativi biomonitoraggi per valutazioni quantitative e qualitative sull'ambiente, in quanto presenta una elevata variabilità di substrati litologici, costituiti da rocce soggette a fenomeni di dissoluzione da parte delle acque meteoriche chimicamente aggressive (rocce carsificabili), a cui sono associati diversi tipi di circolazione idrica. La presenza di una fitta rete di fessure e fratture nei substrati geologici a tratti determina un forte drenaggio dell'acqua all'interno del suolo dovuto a percolamento della stessa verso gli strati più profondi. Nella zona del Carso triestino, sono state selezionate 21 stazioni in base ad un criterio geomorfologico noto come carsificabilità, che misura in modo indiretto e qualitativo la capacità di campo di un suolo, e in modo tale da ricoprire tutto il territorio dell'area carsica all'interno della provincia di Trieste. Al fine di identificare quale fosse il parametro fisiologico o morfologico che meglio si addicesse allo scopo della ricerca, sono stati misurati nel periodo da Maggio a Settembre i parametri relativi alle relazioni pianta-acqua generalmente correlati allo stress idrico e cioè la conduttanza fogliare al vapore d'acqua (gL), il potenziale dell'acqua della foglia (Ψfoglia) e la conduttanza idraulica della foglia (Kfoglia). Contestualmente, sono stati misurati anche i diametri dei vasi xilematici. Grazie all'analisi di questi parametri è stato possibile eseguire uno studio biofisico accurato del comportamento idraulico dell'orniello in condizioni di limitazione della disponibilità d'acqua. Da questi dati emerge che la conduttanza fogliare al vapore d'acqua (gL) è il parametro più affidabile a rappresentare l'indice di aridità ambientale, in quanto è risultato essere il più sensibile alle variazioni nella disponibilità d'acqua. Il tentativo di integrare i dati di campo relativi a gL con quelli ottenuti mediante elaborazione di immagini satellitari non ha portato ai risultati sperati. L'indice ottenuto da dati telerilevati è risultato poco promettente come indice di riferimento per la realizzazione di uno “scaling-up”, in quanto non è risultato essere in grado di rilevare condizioni di stress idrico in aree caratterizzate da forte drenaggio dell'acqua (aree ad alta carsificabilità). L'applicabilità delle tecniche di telerilevamento da satellite nel monitoraggio dell'aridità ambientale risulta quindi fortemente limitata dalla struttura geomorfologica del territorio oggetto di studio.
XX Ciclo
1973
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Muche, Muluken Eyayu. "Surface water hydrologic modeling using remote sensing data for natural and disturbed lands." Diss., Kansas State University, 2016. http://hdl.handle.net/2097/32609.

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Doctor of Philosophy
Department of Biological & Agricultural Engineering
Stacy L. Hutchinson
The Soil Conservation Service-Curve Number (SCS-CN) method is widely used to estimate direct runoff from rainfall events; however, the method does not account for the dynamic rainfall-runoff relationship. This study used back-calculated curve numbers (CNs) and Normalized Difference Vegetation Index (NDVI) to develop NDVI-based CNs (CN[subscript]NDV) using four small northeastern Kansas grassland watersheds with average areas of 1 km² and twelve years (2001–2012) of daily precipitation and runoff data. Analysis indicated that the CN[subscript]NDVI model improved runoff predictions compared to the SCS-CN method. The CN[subscript]NDVI also showed greater variability in CNs, especially during growing season, thereby increasing the model’s ability to estimate relatively accurate runoff from rainfall events since most rainfall occurs during the growing season. The CN[subscript]NDVI model was applied to small, disturbed grassland watersheds to assess the model’s ability to detect land cover change impact for military maneuver damage and large, diverse land use/cover watersheds to assess the impact of scaling up the model. CN[subscript]NDVI application was assessed using a paired watershed study at Fort Riley, Kansas. Paired watersheds were identified through k-means and hierarchical-agglomerative clustering techniques. At the large watershed scale, Daymet precipitation was used to estimate runoff, which was compared to direct runoff extracted from stream flow at gauging points for Chapman (grassland dominated) and Upper Delaware (agriculture dominated) watersheds. In large, diverse watersheds, CN[subscript]NDVI performed better in moderate and overall flow years. Overall, CN[subscript]NDVI more accurately simulated runoff compared to SCS-CN results: The calibrated model increased by 0.91 for every unit increase in observed flow (r = 0.83), while standard CN-based flow increased by 0.506 for every unit increase in observed flow (r = 0.404). Therefore, CN[subscript]NDVI could help identify land use/cover changes and disturbances and spatiotemporal changes in runoff at various scales. CN[subscript]NDVI could also be used to accurately estimate runoff from precipitation events in order to instigate more timely land management decisions.
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Amazirh, Abdelhakim. "Monitoring crops water needs at high spatio-temporal resolution by synergy of optical/thermal and radar observations." Thesis, Toulouse 3, 2019. http://www.theses.fr/2019TOU30101.

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L'optimisation de la gestion de l'eau en agriculture est essentielle dans les zones semi-arides afin de préserver les ressources en eau qui sont déjà faibles et erratiques dues à des actions humaines et au changement climatique. Cette thèse vise à utiliser la synergie des observations de télédétection multispectrales (données radar, optiques et thermiques) pour un suivi à haute résolution spatio-temporelle des besoins en eau des cultures. Dans ce contexte, différentes approches utilisant divers capteurs (Landsat-7/8, Sentinel-1 et MODIS) ont été developpées pour apporter une information sur l'humidité du sol (SM) et le stress hydrique des cultures à une échelle spatio-temporelle pertinente pour la gestion de l'irrigation. Ce travail va parfaitement dans le sens des objectifs du projet REC "Root zone soil moisture Estimates at the daily and agricultural parcel scales for Crop irrigation management and water use impact: a multi-sensor remote sensing approach" (http://rec.isardsat.com/) qui visent à estimer l'humidité du sol dans la zone racinaire (RZSM) afin d'optimiser la gestion de l'eau d'irrigation. Des approches innovantes et prometteuses sont mises en place pour estimer l'évapotranspiration (ET), RZSM, la température de surface du sol (LST) et le stress hydrique de la végétation à travers des indices de SM dérivés des observations multispectrales à haute résolution spatio-temporelle. Les méthodologies proposées reposent sur des méthodes basées sur l'imagerie, la modélisation du transfert radiatif et la modélisation du bilan hydrique et d'énergie et sont appliquées dans une région à climat semi-aride (centre du Maroc). Dans le cadre de ma thèse, trois axes ont été explorés. Dans le premier axe, un indice de RZSM dérivé de LST-Landsat est utilisé pour estimer l'ET sur des parcelles de blé et des sols nus. L'estimation par modélisation de ET a été explorée en utilisant l'équation de Penman-monteith modifiée obtenue en introduisant une relation empirique simple entre la résistance de surface (rc) et l'indice de RZSM. Ce dernier est estimé à partir de la température de surface (LST) dérivée de Landsat, combinée avec les températures extrêmes (en conditions humides et sèches) simulée par un modèle de bilan d'énergie de surface piloté par le forçage météorologique et la fraction de couverture végétale dérivée de Landsat. La méthode utilisée est calibrée et validée sur deux parcelles de blé situées dans la même zone près de Marrakech au Maroc. Dans l'axe suivant, une méthode permettant de récupérer la SM de la surface (0-5 cm) à une résolution spatiale et temporelle élevée est développée à partir d'une synergie entre données radar (Sentinel-1) et thermique (Landsat) et en utilisant un modèle de bilan d'énergie du sol. L'approche développée a été validée sur des parcelles agricoles en sol nu et elle donne une estimation précise de la SM avec une différence quadratique moyenne en comparant à la SM in situ, égale à 0,03 m3 m-3. Dans le dernier axe, une nouvelle méthode est développée pour désagréger la MODIS LST de 1 km à 100 m de résolution en intégrant le SM proche de la surface dérivée des données radar Sentinel-1 et l'indice de végétation optique dérivé des observations Landsat. Le nouvel algorithme, qui inclut la rétrodiffusion S-1 en tant qu'entrée dans la désagrégation, produit des résultats plus stables et robustes au cours de l'année sélectionnée. Dont, 3,35 °C était le RMSE le plus bas et 0,75 le coefficient de corrélation le plus élevé évalués en utilisant le nouvel algorithme
Optimizing water management in agriculture is essential over semi-arid areas in order to preserve water resources which are already low and erratic due to human actions and climate change. This thesis aims to use the synergy of multispectral remote sensing observations (radar, optical and thermal data) for high spatio-temporal resolution monitoring of crops water needs. In this context, different approaches using various sensors (Landsat-7/8, Sentinel-1 and MODIS) have been developed to provide information on the crop Soil Moisture (SM) and water stress at a spatio-temporal scale relevant to irrigation management. This work fits well the REC "Root zone soil moisture Estimates at the daily and agricultural parcel scales for Crop irrigation management and water use impact: a multi-sensor remote sensing approach" (http://rec.isardsat.com/) project objectives, which aim to estimate the Root Zone Soil Moisture (RZSM) for optimizing the management of irrigation water. Innovative and promising approaches are set up to estimate evapotranspiration (ET), RZSM, land surface temperature (LST) and vegetation water stress through SM indices derived from multispectral observations with high spatio-temporal resolution. The proposed methodologies rely on image-based methods, radiative transfer modelling and water and energy balance modelling and are applied in a semi-arid climate region (central Morocco). In the frame of my PhD thesis, three axes have been investigated. In the first axis, a Landsat LST-derived RZSM index is used to estimate the ET over wheat parcels and bare soil. The ET modelling estimation is explored using a modified Penman-Monteith equation obtained by introducing a simple empirical relationship between surface resistance (rc) and a RZSM index. The later is estimated from Landsat-derived land surface temperature (LST) combined with the LST endmembers (in wet and dry conditions) simulated by a surface energy balance model driven by meteorological forcing and Landsat-derived fractional vegetation cover. The investigated method is calibrated and validated over two wheat parcels located in the same area near Marrakech City in Morocco. In the next axis, a method to retrieve near surface (0-5 cm) SM at high spatial and temporal resolution is developed from a synergy between radar (Sentinel-1) and thermal (Landsat) data and by using a soil energy balance model. The developed approach is validated over bare soil agricultural fields and gives an accurate estimates of near surface SM with a root mean square difference compared to in situ SM equal to 0.03 m3 m-3. In the final axis a new method is developed to disaggregate the 1 km resolution MODIS LST at 100 m resolution by integrating the near surface SM derived from Sentinel-1 radar data and the optical-vegetation index derived from Landsat observations. The new algorithm including the S-1 backscatter as input to the disaggregation, produces more stable and robust results during the selected year. Where, 3.35 °C and 0.75 were the lowest RMSE and the highest correlation coefficient assessed using the new algorithm
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4

Elbag, Mark A. "Impact of surrounding land uses on surface water quality." Link to electronic thesis, 2006. http://www.wpi.edu/Pubs/ETD/Available/etd-050306-155834/.

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Thesis (M.S.)--Worcester Polytechnic Institute.
Keywords: Conductivity, pH, Dissolved Oxygen, UV absorbance, Source Water, Surface Water, Dissolved Organic Carbon, Total Organic Carbon, Particle Counts, Turbidity, E. coli, Fecal Coliforms, West Boylston Brook, Wachusett Reservoir, source water protection, surface water protection Includes bibliographical references (p.73-77).
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5

Elbag, Jr Mark A. "Impact of Surrounding Land Uses on Surface Water Quality." Digital WPI, 2006. https://digitalcommons.wpi.edu/etd-theses/665.

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Source water protection is important to maintain public health by keeping harmful pathogens out of drinking water. Non-point source pollution is often times a major contributor of pollution to surface waters, and this form of pollution can be difficult to quantify. This study examined physical, chemical, and microbiological water quality parameters that may indicate pollution and may help to identify sources of pollution. These included measures of organic matter, particles, and indicator organisms (fecal coliforms and E. coli). The parameters were quantified in the West Boylston Brook, which serves as a tributary to the Wachusett Reservoir and is part of the drinking water supply for the Metropolitan Boston area. Water quality was determined over four seasons at seven locations in the brook that were selected to isolate specific land uses. The water quality parameters were first analyzed for trends by site and by season. Then, a correlation analysis was performed to determine relationships among the water quality parameters. Lastly, ANOVA analyses were used to determine statistically significant variations in water quality along the tributary.
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Cheng, Chi Han. "Land use effects on energy and water balance-developing a land use adapted drought index." Doctoral diss., University of Central Florida, 2012. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5160.

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Climate change is expected to increase the frequency, intensity and duration of droughts in all parts of the United States (US). Snow packs are disappearing earlier in the spring and summer, with reduced stream-flow. Lower reservoir levels, higher temperatures, and greater precipitation variability have been observed. Drought events in the US have threatened drinking water supplies for communities in Maryland and Chesapeake Bay as observed in 2001 through September 2002; Lake Mead in Las Vegas in 2000 through 2004; Peace River and Lake Okeechobee in South Florida in 2006; and Lake Lanier in Atlanta, Georgia in 2007. ENSO influences the climate of Florida; where El Nino years tend to be cooler and wetter, while La Nina years tend to be warmer and drier than normal in the fall through the spring, with the strongest effect in the winter. Both prolonged heavy rainfall and drought potentially have impacts on land uses and many aspects of Florida's economy and quality of life. Drought indices could integrate various hydrological and meteorological parameters and quantify climate anomalies in terms of intensity, duration, and spatial extent, thus making it easier to communicate information to diverse users. Hence, understanding local ENSO patterns on regional scales and developing a new land use drought index in Florida are critical in agriculture and water resources planning and managements. Current drought indices have limitations and drawbacks such as calculation using climate data from meteorological stations, which are point measurements. In addition, weather stations are scarce in remote areas and are not uniformly distributed. Currently used drought indices like the PDSI and the Standardized Precipitation Index (SPI) could not fully demonstrate the land use effects. Other limitations include no single index that addresses universal drought impact. Hence, there is a renewed interest to develop a new "Regional Land Use Drought Index (RLDI) that could be applied for various land use areas and serve for short term water resources planning. In this study, the first and second research topics investigated water and energy budgets on the specific and important land use areas (urban, forest, agriculture and lake) in the State of Florida by using the North American Regional Reanalysis (NARR) reanalysis data. NARR data were used to understand how drought events, EI Nino, La Nina, and seasonal and inter-annual variations in climatic variables affect the hydrologic and energy cycle over different land use areas. The results showed that the NARR data could provide valuable, independent analysis of the water and energy budgets for various land uses in Florida. Finally, the high resolution land use (32km x 32km) adapted drought indices were developed based on the NARR data from 1979 to 2002. The new regional land use drought indices were developed from normalized Bowen ratio and the results showed that they could reflect not only the level of severity in drought events resulting from land use effects, but also La Nina driven drought impacts.
ID: 031001561; System requirements: World Wide Web browser and PDF reader.; Mode of access: World Wide Web.; Title from PDF title page (viewed August 26, 2013).; Thesis (Ph.D.)--University of Central Florida, 2012.; Includes bibliographical references.
Ph.D.
Doctorate
Civil, Environmental, and Construction Engineering
Engineering and Computer Science
Civil Engineering
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7

Decker, Mark Ryan. "IMPROVING THE HYDROLOGICAL CYCLE IN LAND SURFACE CLIMATE MODELS." Diss., The University of Arizona, 2010. http://hdl.handle.net/10150/195627.

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The hydrological components of land surface climate models have increased greatly in complexity over the past decade, from simple bucket models to multilayer models including separate and distinct soil water and ground water components. While the parameterizations included in these models have also increased in complexity, the fundamental ability of the numerical solution for the vertical movement of soil water in the Community Land Model (or other land surface models) to simply maintain the hydrostatic solution of the original partial differential equation has yet to be determined.Also, the ability of current generation reanalysis products to simulate near surface quantities as gauged by flux tower measurements has yet to be determined.This study demonstrates that the numerical solution as used in CLM3.5 cannot maintain the hydrostatic state. An alternate form of the equation, titled the Modified Richards equation is presented so that the numerical solution maintains steady statesolutions. Also, an improved and simple bottom boundary condition is derived that itself doesn't destroy hydrostatic initial conditions. The new solution is demonstrated to be as accurate as proven numerical solutions while being one to three orders more computationally efficient. The Modified Richards equation together with the new bottom boundary condition is shown to improve the ability of CLM to simulate soil water, water table depth, and near surface turbulent fluxes.Comparison with flux tower observations shows that ERA-Interim better simulates near surface temperature and wind speed than other current generation reanalysis products. Reanalysis products are able to reproduce the flux tower observations on monthly timescales, and the errors between the products and the measurements are primarily due to biases. However, at six hourly timescales the errors are not only larger but also caused primarily by a lack of correlation with the observations.
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Chingombe, Wisemen. "Effects of land-cover - land-use on water quality within the Kuils - Eerste River catchment." Thesis, University of Western Cape, 2012. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_5893_1373463134.

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The most significant human impacts on the hydrological system are due to land-use change. The conversion of land to agricultural, mining, industrial, or residential uses significantly alters the hydrological characteristics of the land surface and modifies pathways and rates of water flow. If this occurs over large or critical areas of a catchment, it can have significant short and long-term impacts, on the quality of water. While there are methods available to quantify the pollutants in surface water, methods of linking non-point source pollution to water quality at catchment scale are lacking. Therefore, the research presented in this thesis investigated modelling techniques to estimate the effect of land-cover type on water quality. The main goal of the study was to contribute towards improving the understanding of how different land-covers in an urbanizing catchment affect surface water quality. The aim of the research presented in this thesis was to explain how the quality of surface runoff varies on different land-cover types and to provide guidelines for minimizing water pollution that may be occurring in the Kuils-Eerste River catchment. The research objectives were
(1) to establish types and spatial distribution of land-cover types within the Kuils-Eerste River catchment, (2) to establish water quality characteristics of surface runoff from specific land-cover types at the experimental plot level, (3) to establish the contribution of each land-cover type to pollutant loads at the catchment scale. Land-cover characteristics and water quality were investigated using GIS and Remote Sensing tools. The application of these tools resulted in the development of a land-cover map with 36 land classifications covering the whole catchment. Land-cover in the catchment is predominantly agricultural with vineyards and grassland covering the northern section of the catchment. Vineyards occupy over 35% of the total area followed by fynbos (indigenous vegetation) (12.5 %), open hard rock area (5.8 %), riparian forest (5.2 %), mountain forest 
 
(5 %), dense scrub (4.4 %), and improved grassland (3.6 %). The residential area covers about 14 %. Roads cover 3.4 % of the total area. Surface runoff is responsible for the transportation of large quantities of pollutants that affect the quality of water in the Kuils-Eerste River catchment. The different land-cover types and the distribution and concentration levels of the pollutants are not uniform. Experimental work was conducted at plot scale to understand whether land-cover types differed in their contributions to the concentration of water quality attributes emerging from them. Four plots each with a length of 10 m to 12 m and 5 m width were set up. Plot I was set up on open grassland, Plot II represented the vineyards, Plot III covered the mountain forests, and Plot IV represented the fynbos land-cover. Soil samples analyzed from the experimental plots fell in the category of sandy soil (Sa) with the top layer of Plot IV (fynbos) having loamy sand (LmSa). The soil particle sizes range between fine sand (59.1 % and 78.9 %) to coarse sand (between 7 % and 22 %). The content of clay and silt was between 0.2 % and 2.4 %. Medium sand was between 10.7 % and 17.6 %. In terms of vertical distribution of the particle sizes, a general decrease with respect to the size of particles was noted from the top layer (15 cm) to the bottom layer (30 cm) for all categories of the particle sizes. There was variation in particle size with depth and location within the experimental plots.Two primary methods of collecting water samples were used
grab sampling and composite sampling. The quality of water as represented by the samples collected during storm events during the rainfall season of 2006 and 2007 was 
used to establish  
water quality characteristics for the different land-cover types. The concentration of total average suspended solids was highest in the following land-cover types, cemeteries (5.06 mg L-1), arterial roads/main roads (3.94 mg L-1), low density residential informal squatter camps (3.21 mg L-1) and medium density residential informal townships (3.21 mg L-1). Chloride concentrations were high on the following land-cover types, recreation grass/ golf course (2.61 mg L-1), open area/barren land (1.59 mg L-1), and improved grassland/vegetation crop (1.57 mg L-1). The event mean concentration (EMC) values for NO3-N were high on commercial mercantile (6 mg L-1) and water channel (5 mg L-1). The total phosphorus concentration mean values recorded high values on improved grassland/vegetation crop (3.78 mg L-1), medium density residential informal townships (3mgL-1) and low density residential informal squatter camps (3 mg L-1). Surface runoff may also contribute soil particles into rivers during rainfall events, particularly from areas of disturbed soil, for example areas where market gardening is taking place. The study found that different land cover types contributed differently to nonpoint source pollution. A GIS model was used to estimate the diffuse pollution of five pollutants (chloride, phosphorus, TSS, nitrogen and NO3-N) in response to land cover variation using water quality data. The GIS model linked land cover information to diffuse nutrient signatures in response to surface runoff using the Curve Number method and EMC data were developed. Two models (RINSPE and N-SPECT) were used to estimate nonpoint source pollution using various GIS databases. The outputs from the GIS-based model were compared with recommended water quality standards. It was found that the RINSPE model gave accurate results in cases where NPS pollution dominate the total pollutant inputs over a given land cover type. However, the N-SPECT model simulations were too uncertain in cases where there were large numbers of land cover types with diverse NPS pollution load. All land-cover types with concentration values above the recommended national water quality standard were considered as areas that needed measures to mitigate the adverse effects of nonpoint pollution. The expansion of urban areas and agricultural land has a direct effect on land cover types within the catchment. The land cover changes have adverse effect which has a potential to contribute to pollution.

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9

De, Chiara Giovanna. "Satellite remote sensing for surface soil water content estimation." Doctoral thesis, Universita degli studi di Salerno, 2010. http://hdl.handle.net/10556/125.

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2008 - 2009
Satellite remote sensing is a useful source of observations of land surface hydrologic variables and processes and could be a practical substitution of conventional in-situ monitoring. Most of hydrological dynamic processes change not only throughout the years but also within weeks or months and their monitoring requires frequent observations. The most prominent advantage of the remote sensing technologies is that they offer a synoptic view of the dynamics and spatial distribution of phenomena and parameters, often difficult to monitor with traditional ground survey, with a frequent temporal coverage. Many of the variables in the land surface water balance can now be observed with satellite techniques thanks to an extensive development over the last decades. Often the problem connected to the use of remotely sensed data is their accuracy that, according to the sensor used and to the application considered, can ranges from moderate to excellent. The objective of this thesis has been to evaluate the use of satellite remote sensing techniques for the monitoring of two variables useful for hydrology applications: water body extension and soil moisture monitoring. The capability to map water surface is important in many hydrological applications, in particular accurate information on the extent of water boundary is essential for flood monitoring and water reservoir management. Often, this information is difficult to retrieve using traditional survey techniques because water boundaries can be fast moving as in floods or may be inaccessible. In this PhD thesis, an artificial basin for which in-situ information about the water extension are available is used as case study. The area extension recorded daily by the dam owner is compared to the one retrieved by using satellite images acquired from SAR and TM/ETM+ sensors. The outcomes of the analysis show that satellite images are able to map water body surfaces with a good accuracy. The analysis also highlighted the factor to be taken into account while using types of sensors. Soil moisture is recognized as a key variable in different hydrological and ecological processes as it controls the exchange of water and heat energy between land surface and the atmosphere. Despite the high spatial variability of this parameter it has been demonstrated that many satellite sensors are able to retrieve soil moisture information of the surface layer at catchment scale. Among other sensors, the Scatterometer is very useful for climatic studies and modelling analysis thanks, respectively, to the temporal frequency, global coverage and to the long time series availability. Even though the ERS Scatterometer has been designed to measure the wind over the ocean surface, in recent years it has been pointed out that backscattering measurements have high potentiality for soil moisture retrieval. The second task of this PhD thesis, concerning the use of satellite data for soil moisture monitoring, has been developed at Serco S.p.A. in the framework of the Advanced Scatterometer Processing System (ASPS) project developed by ESA (European Space Agency) to reprocess the entire ERS Scatterometer mission. Since the beginning of the ERS-1 Scatterometer mission in 1991 a long dataset of C-band backscattering signal from the Earth surface is available for studies and researches. This is a very consistent dataset, but in particular for climatology studies it is important to have high quality and homogeneous long term observation as also stated in the key guidelines included in the Global Climate Observing System (GCOS) from the World Meteorological Organization (WMO). The main goal of this task has been the generation of the new Scatterometer ASPS products with improved data quality and spatial resolution. This achievement required a long preparation activity but represents an important contribution to the C-band Scatterometer dataset available to the scientific community. In order to evaluate the usage of the re-processed Scatterometer data for soil moisture estimation, the backscattering measurements derived in the new ASPS products have been then compared to in-situ volumetric soil moisture data and the relationship between radar backscattering and soil moisture measurements has been investigated under different conditions: angle of incidence, angle of azimuth, data measurements resolution, season of the year. Analysis results show that a relationship between the C-band backscattering coefficient and the in-situ volumetric soil moisture exists and takes into account the incidence and azimuth angles and the vegetation cover. [edited by author]
VIII n. s.
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Wang, Shusen. "Modelling water, carbon, and nitrogen dynamics in CLASS, Canadian Land Surface Scheme." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape2/PQDD_0008/NQ59692.pdf.

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Books on the topic "Land Surface Water Index"

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Canada. Environment Canada. Inland Waters Directorate. Surface water data reference index: Canada. Ottawa: Environment Canada. Inland Waters Directorate, 1991.

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Simon, Standing, and Wells Liz 1948-, eds. Surface: Land/water and the visual arts. Bristol, U.K: University of Plymouth Press, 2005.

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Evoy, Barbara. Surface and groundwater management in surface mined-land reclamation. Sacramento, CA: Dept. of Conservation, Division of Mines and Geology, 1989.

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Evoy, Barbara. Surface and groundwater management in surface mined-land reclamation. Sacramento, CA: Dept. of Conservation, Division of Mines and Geology, 1989.

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C, Gandara S., Jones R. E, and Geological Survey (U.S.), eds. Index of stations: Surface-water data-collection network of Texas, September 1993. Austin, Tex: U.S. Dept. of the Interior, U.S. Geological Survey, 1995.

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C, Gandara S., Jones R. E, and Geological Survey (U.S.), eds. Index of stations: Surface-water data-collection network of Texas, September 1993. Austin, Tex: U.S. Dept. of the Interior, U.S. Geological Survey, 1995.

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Gandara, S. C. Index of stations: Surface-water data-collection network of Texas, September 1998. Austin, Tex: U.S. Dept. of the Interior, U.S. Geological Survey, 1999.

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C, Gandara S., Jones R. E, and Geological Survey (U.S.), eds. Index of stations: Surface-water data-collection network of Texas, September 1993. Austin, Tex: U.S. Dept. of the Interior, U.S. Geological Survey, 1995.

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K, Ruby N., Geological Survey (U.S.), and Wyoming State Engineer's Office, eds. Index of surface-water discharge, water-quality, sediment, and biological records through September 30, 1990, for Wyoming. Cheyenne, Wyo: U.S. Geological Survey, 1991.

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K, Ruby N., Geological Survey (U.S.), and Wyoming State Engineer's Office, eds. Index of surface-water discharge, water-quality, sediment, and biological records through September 30, 1990, for Wyoming. Cheyenne, Wyo: U.S. Geological Survey, 1991.

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Book chapters on the topic "Land Surface Water Index"

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Desjardins, R. L., and J. I. MacPherson. "Water Vapor Flux Measurements from Aircraft." In Land Surface Evaporation, 245–60. New York, NY: Springer New York, 1991. http://dx.doi.org/10.1007/978-1-4612-3032-8_14.

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Schmugge, Thomas J., and F. Becker. "Remote Sensing Observations for the Monitoring of Land-Surface Fluxes and Water Budgets." In Land Surface Evaporation, 337–47. New York, NY: Springer New York, 1991. http://dx.doi.org/10.1007/978-1-4612-3032-8_20.

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Bonan, Gordon. "Processes Determining Land Surface Climate." In Handbook of Weather, Climate, and Water, 135–40. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2004. http://dx.doi.org/10.1002/0471721603.ch11.

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Tillman, James E. "In Situ Water Vapor Measurements in the Lyman-alpha and Infrared Spectrum: Theory and Components." In Land Surface Evaporation, 313–35. New York, NY: Springer New York, 1991. http://dx.doi.org/10.1007/978-1-4612-3032-8_19.

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Hall, Forrest G., and Yann H. Kerr. "Remote Sensing and Land-surface Experiments." In Vegetation, Water, Humans and the Climate, 207–12. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18948-7_19.

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Liang, Shunlin, Xiaotong Zhang, Zhiqiang Xiao, Jie Cheng, Qiang Liu, and Xiang Zhao. "Leaf Area Index." In Global LAnd Surface Satellite (GLASS) Products, 3–31. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-02588-9_2.

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Sorooshian, Soroosh. "The Trials and Tribulations of Modeling and Measuring in Surface Water Hydrology." In Land Surface Processes in Hydrology, 19–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-60567-3_2.

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Das, P., V. Pandey, and Dipanwita Dutta. "Land Surface Water Resource Monitoring and Climate Change." In Mapping, Monitoring, and Modeling Land and Water Resources, 311–26. First edition. | Boca Raton : CRC Press, 2021.: CRC Press, 2021. http://dx.doi.org/10.1201/9781003181293-20.

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Bastidas, Luis A., Hoshin V. Gupta, Kuo-lin Hsu, and Soroosh Sorooshian. "Parameter, structure, and model performance evaluation for land-surface schemes." In Water Science and Application, 229–37. Washington, D. C.: American Geophysical Union, 2003. http://dx.doi.org/10.1029/ws006p0229.

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McIntyre, Neil, Fitsum Woldemeskel, Supattra Visessri, and Ashish Sharma. "Quantifying Surface Water Supplies under Changing Climate and Land Use." In Sustainable Water Resources Management, 337–73. Reston, VA: American Society of Civil Engineers, 2017. http://dx.doi.org/10.1061/9780784414767.ch13.

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Conference papers on the topic "Land Surface Water Index"

1

Wang, Wen, Zhong-Zhong Zhang, Xiao-Gang Wang, and Hui-Min Wang. "Evaluation of using the modified water deficit index derived from MODIS vegetation index and land surface temperature products for monitoring drought." In IGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2012. http://dx.doi.org/10.1109/igarss.2012.6352253.

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Ciezkowski, Wojciech, Jacek Jozwiak, Sylwia Szporak-Wasilewska, Piotr Dabrowski, Malgorzata Kleniewska, Maciej Goraj, and Jaroslaw Chormanski. "Water Stress Index for Bogs and Mires Based on UAV Land Surface Measuremnts and Its Dependency on Airborne Hyperespectral Data." In IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2018. http://dx.doi.org/10.1109/igarss.2018.8518184.

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GHERASIM, Paul Marian, Mihai DIMA, and Ioana AGAPIE (MEREUȚĂ). ""Studing LST and NDVI Values for Suhi Non-Suhi Occupied by Constructions and Buildings: a Case Study of Iasi. "." In Air and Water – Components of the Environment 2022 Conference Proceedings. Casa Cărţii de Ştiinţă, 2022. http://dx.doi.org/10.24193/awc2022_11.

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In this paper we tried to study the values of radiant temperatures (Land Surface Temperature) and NDVI (Normalized Difference Vegetation Index) for areas occupied by buildings and green spaces. The area affected by the Urban Heat Island (UHI) was also determined. Study Area, Iasi, the largest city in eastern Romania, is geographically situated on latitude 47°12'N to 47°06'N and longitude 27°32'E to 27°40'E. LST is an estimate of ground temperature and is important to identify change in environment. An important parameter in global climate change is rapid urbanization which leads to an increase in Land Surface Temperature (LST). The urban heat island (UHI) represents the phenomenon of higher atmospheric and surface temperatures occurring in urban area or metropolitan area than in the surrounding rural zones due to urbanization. It also been found that night UHI is more powerful than day. At night the LST values for SUHI varies between 24.5°C-25.9°C, and during the day between 35°C-38.7°C. With the development of remote sensing technology, it has become an important approach to urban heat island research. MODIS and Landsat data were used to estimate the LST and NDVI. From the analysis of the images it can be seen that the temperatures in SUHI are lower where there are green spaces around the buildings, and temperatures are higher in the non-UHI area, where inside or around the green spaces there are surfaces built or covered with concrete. Statistical data show very average temperatures for areas affected by UHI, 37.8°C for daytime and 24.6°C for night.
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MAGYARI-SÁSKA, Zsolt, and Ștefan DOMBAY. ""Experimental Method to Assess the Looseness or Compactness in Climate Changing for Several Major Cities of Hungary."." In Air and Water – Components of the Environment 2022 Conference Proceedings. Casa Cărţii de Ştiinţă, 2022. http://dx.doi.org/10.24193/awc2022_12.

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In this paper we tried to study the values of radiant temperatures (Land Surface Temperature) and NDVI (Normalized Difference Vegetation Index) for areas occupied by buildings and green spaces. The area affected by the Urban Heat Island (UHI) was also determined. Study Area, Iasi, the largest city in eastern Romania, is geographically situated on latitude 47°12'N to 47°06'N and longitude 27°32'E to 27°40'E. LST is an estimate of ground temperature and is important to identify change in environment. An important parameter in global climate change is rapid urbanization which leads to an increase in Land Surface Temperature (LST). The urban heat island (UHI) represents the phenomenon of higher atmospheric and surface temperatures occurring in urban area or metropolitan area than in the surrounding rural zones due to urbanization. It also been found that night UHI is more powerful than day. At night the LST values for SUHI varies between 24.5°C-25.9°C, and during the day between 35°C-38.7°C. With the development of remote sensing technology, it has become an important approach to urban heat island research. MODIS and Landsat data were used to estimate the LST and NDVI. From the analysis of the images it can be seen that the temperatures in SUHI are lower where there are green spaces around the buildings, and temperatures are higher in the non-UHI area, where inside or around the green spaces there are surfaces built or covered with concrete. Statistical data show very average temperatures for areas affected by UHI, 37.8°C for daytime and 24.6°C for night.
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Ajtai, Iulia, Marius Oprea, Cristian Malos, Andrei Radovici, and Camelia Botezan. "THE VULNERABILITY ANALYSIS OF A MOUNTAIN RIVER ECOSYSTEM ASSOCIATED TO ANTHROPIC ACTIVITIES, IN A TOURISTIC AREA IN ROMANIA." In 22nd SGEM International Multidisciplinary Scientific GeoConference 2022. STEF92 Technology, 2022. http://dx.doi.org/10.5593/sgem2022/3.1/s12.25.

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The population and economy growth in the past years, and subsequently the increased demand for freshwater, led to an increased pressure on water resources. The quality of surface water is affected by anthropogenic factors, such as: domestic sewage, industrial activities, agricultural activities, recreational activities, land use change, urbanization. Therefore, the impact on surface water vulnerability is higher in large urban areas or in urban areas with intense touristic activities. The analysis of water vulnerability in such areas is important in order to develop sustainable water resources management strategies. In this paper, a vulnerability assessment index was developed in order to analyze the surface water vulnerability on a section of Prahova River (from source to Breaza city). The urban areas located in this section of the river are characterized by intense touristic activities, with a large influx of people. The vulnerability index was developed using GIS tools and analyzing specific indicators such as: different types of land use and in particular urban areas, length of the roads in the study area, resident population, influx of tourists, animals, slope and sinuosity of the river. The river was divided into sectors and a vulnerability index was calculated for each sector. Moreover, a comparison analysis was done, considering a second scenario for the year 2020 in which the number of tourists was highly reduced, in order to investigate the impact of this indicator on the water vulnerability. The results, represented by the vulnerability map showed that the most vulnerable sectors of the river are situated in proximity to urban areas and furthermore, the touristic activities increase the impact on surface water resources.
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Koné, Alassane, Allyx Fontaine, and Samira El Yacoubi. "COUPLING CELLULAR AUTOMATA WITH MEDALUS ASSESSMENT FOR THE DESERTIFICATION ISSUE." In International Conference on Emerging Trends in Engineering & Technology (IConETech-2020). Faculty of Engineering, The University of the West Indies, St. Augustine, 2020. http://dx.doi.org/10.47412/vqgh6804.

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Desertification is one of the major problems affecting our environment in the 21st century. Indeed, it threatens more than 1.5 million people worldwide and affects a quarter of the land in less than 100 countries, it spreads over half a billion hectares per year and reduces the surface water and groundwater. Thus, according to a report by the Food and Agriculture Organisation written in 1993, the direct and visible impacts of desertification are the damage on crops, on livestock, on the electricity productivity, etc. Indirect impacts are lack of food production, poverty, social upheaval, rural exodus to cities. In this paper, our work consists in modelling the degradation process of land whose advanced level leads to the desertification. The first step consists in assessing the degradation of land with the MEDALUS model developed by the MEDALUS project of the commission of the European Union. This model assesses desertification by its sensitivity index which is the geometric mean of four quality factor indexes of soil, vegetation, climate and management (land use). This assessment method uses the major part of the parameters influencing the land degradation process. The second step is to model the land degradation process using cellular automata (CA) approach. For that purpose, the study area will be divided into a regular grid of cells. Initially, each cell has a state (desertification sensitivity index) whose evolution at each discrete time step depends on the states of its neighbours through a built transition function. As a result, this study allows to introduce a dynamical process in MEDALUS model. Indeed, from an initial configuration of an area, the model can predict its evolution over time and space according to a continuous state transition function that extend the classical CA approach and fit to the MEDALUS model parameters.
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Ramamurthy, Adinarayanane, and Anusha Roy. "Green and blue infrastucture to regulate thermal comfort in high density city planning. A case of Navi Mumbai, India." In 55th ISOCARP World Planning Congress, Beyond Metropolis, Jakarta-Bogor, Indonesia. ISOCARP, 2019. http://dx.doi.org/10.47472/amfc5106.

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Cities create an environment that is clearly distinct from their surrounding areas. Urban structures alter the surface energy budget, modify the vertical profile of various atmospheric properties, interact with both local and regional circulation, and introduce anthropogenic heat. As a result, the climate conditions in the urban environment significantly differ from their rural system. Sustainability in planning is a topic of high interest among urban planners, urbanist and policy makers yet lack of scientific knowledge in the field leads to low impact in evolving urban planning decisions. Urban climatic map, as a tool provides a visual and spatial information platform using Geographic Information System (GIS). Increase in vegetation and water surfaces, known as green and blue infrastructure (GBI), is of particular interest due to their multiple functionality and benefits for the urban environment, such as increasing urban biodiversity and improving air quality in case of urban vegetation. The urban climatic, environmental and planning parameters, as well as their impact, are considered to synthesize and comprehensively evaluate the physical urban environment with regard to thermal load and dynamic potential. The parameters considered to evaluate Thermal load include: Topography; Population Density; Land Surface Temperature; Air Temperature and Dynamic potential are: Normalized difference Built up Index; Normalized difference Vegetation Index; Normalized difference Water Index and Prevailing Wind of the study region. Study concludes with planning decisions to develop urban climatology-based map for GBI to enhance cooling effects and thereby undertaking measures to regulate thermal comfort in the city through green and blue infrastructure.
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Ferrer Pont, Esther, Blanca Botey Sánchez de Rojas, Francisco Cabrera Tosas, and Gisela Lorán Benavent. "Eines i indicadors per a la mesura del grau de sostenibilitat en la planificació territorial i urbanística." In International Conference Virtual City and Territory. Barcelona: Centre de Política de Sòl i Valoracions, 2009. http://dx.doi.org/10.5821/ctv.7538.

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En aquest article es presenten un seguit d’eines i indicadors ambientals emprats habitualment per l’equip de Taller d’Enginyeria Ambiental, SL. en els estudis d’avaluació ambiental del planejament territorial i urbanístic. Els indicadors ambientals poden ser utilitzats per valorar alguns dels efectes derivats de la implementació d’un determinat pla sobre el territori, comparar els efectes ambientals probables generats per les diferents alternatives de zonificació i/o d’ordenació plantejades i, en darrera instància, poden contribuir a justificar la selecció de l’alternativa d’ordenació més sostenible des del punt de vista ambiental. L’article presenta diferents exemples d’eines i d’indicadors relacionats amb l’ús racional del sòl (l’índex d’ocupació urbana del sòl, l’índex de dispersió urbana, l’índex de fragmentació del paisatge i l’índex de conca visual lliure d’impacte), l’ús dels recursos naturals (l’índex d’ús d’aigües regenerades i la utilitat dels estudis d’assolellament en l’ús eficient de l’energia), i la prevenció de certs riscos ambientals (mesura del percentatge de superfícies inundables i el nombre de persones o habitatges exposats a nivells sonors alts). Es comparen els resultats obtinguts d’alguns d’aquests indicadors per a diferents models de desenvolupament urbanístic, considerant models més dispersos i altres de compactes. En darrer lloc, es valora la seva utilitat en el procés de selecció d’alternatives d’ordenació territorial i urbanística i la seva idoneïtat per valorar el grau de compliment d’objectius ambientals, tenint en compte la interpretació dels resultats obtinguts. In this article there are presented a set of tools and environment indicators habitually used by the Taller d’Enginyeria Ambiental, S.L in the environmental studies over the land and urban planning. These indicators may be used to value some of the effects of the implementation of some specific plan over the territory, to compare the environmental effects of different zoning or/and ordering alternatives, and finally, to justify the most environmentally sustainable alternative of ordering. The article presents some examples of these tools and indicators related with the rational use of the territory (index of the urban occupation of the land, index of urban dispersal, index of landscape fragmentation, index of visual basin free of impact), use of natural resources (index of the use of recycled water, and insolation’s studies usefulness) and the prevention of environmental risks (measurements of surfaces affected by water floods, and number of people and homes affected by high noise levels). The results of some of these indicators applied to different models of urban development are compared considering scattered and compact urban models. Finally, indicators’ utility in the process of alternatives selection of urban planning is valued, as well as its suitability to value the achievement of environmental objectives, according to the obtained results’ interpretation.
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Roy, S., D. Pujari, and M. Saraswat. "ASSESSMENT OF URBAN ECOSYSTEMS: A STRUCTURED APPROACH TOWARDS BUILDING RESILIENCE TO CLIMATE CHANGE IN INDIAN TOWNS AND CITIES." In The 5th International Conference on Climate Change 2021 – (ICCC 2021). The International Institute of Knowledge Management, 2021. http://dx.doi.org/10.17501/2513258x.2021.5103.

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The fast-urbanizing Indian cities are grappling with rising ecological challenges. Pollution, water insecurity, urban heat, and flooding have increased the vulnerability of the urban population. There is a need to look at urban settlements as a functioning natural ecosystem delineated by administrative boundaries and to evaluate their health regularly through a comprehensive, easy to adopt, structured approach. This study aims to track and evaluate the ecosystem health of three different categories of urban settlements: a group of metropolitan wards, a growing peripheral city, and an emerging town, through adaption of Pressure- State-Response (PSR) framework developed by the Organisation for Economic Co-operation and Development (OECD)’. The methodology includes indices-driven change detection of ecosystem components and pressure points on the same, by using spatial and non-spatial data, developing an impact matrix, and prioritized eco plans for action. Increasing built-up surfaces in the peripheral city (11%) and the metropolitan wards (23%) show increased pressure on their ecosystem in the form of reducing pervious surfaces. Increasing water turbidity, land surface temperatures, and aerosol content in the air depict pressure hotspots requiring mitigative, restorative, and preventive action. A significant decrease observed in heavy vegetation in the metropolitan wards (58% in the last 5 years) and an increase in industrial activities and aerosol is observed in conjunction with increasing air temperatures and this points towards an impending change in its livability index due to anthropogenic pressures and climate change. The study concludes that a structured approach can aid in agile and sustainable management of our towns and cities and nature-based solutions provide an opportunity to restore the ecosystem balance. Keywords: Urban Assessment Nature-based solutions, Ecosystem Health, Urban Ecosystem, Urban management
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Toll, David L., Jared K. Entin, and Paul R. Houser. "Land surface heterogeneity on surface energy and water fluxes." In International Symposium on Remote Sensing, edited by Manfred Owe and Guido D'Urso. SPIE, 2002. http://dx.doi.org/10.1117/12.454209.

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Reports on the topic "Land Surface Water Index"

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Research Institute (IFPRI), International Food Policy. Global Hunger Index The challenge of hunger: Ensuring sustainable food security under land, water, and energy stresses. Washington, DC: International Food Policy Research Institute, 2012. http://dx.doi.org/10.2499/9780896299429.

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Russell, H. A. J., and S. K. Frey. Canada One Water: integrated groundwater-surface-water-climate modelling for climate change adaptation. Natural Resources Canada/CMSS/Information Management, 2021. http://dx.doi.org/10.4095/329092.

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Canada 1 Water is a 3-year governmental multi-department-private-sector-academic collaboration to model the groundwater-surface-water of Canada coupled with historic climate and climate scenario input. To address this challenge continental Canada has been allocated to one of 6 large watershed basins of approximately two million km2. The model domains are based on natural watershed boundaries and include approximately 1 million km2 of the United States. In year one (2020-2021) data assembly and validation of some 20 datasets (layers) is the focus of work along with conceptual model development. To support analysis of the entire water balance the modelling framework consists of three distinct components and modelling software. Land Surface modelling with the Community Land Model will support information needed for both the regional climate modelling using the Weather Research & Forecasting model (WRF), and input to HydroGeoSphere for groundwater-surface-water modelling. The inclusion of the transboundary watersheds will provide a first time assessment of water resources in this critical international domain. Modelling is also being integrated with Remote Sensing datasets, notably the Gravity Recovery and Climate Experiment (GRACE). GRACE supports regional scale watershed analysis of total water flux. GRACE along with terrestrial time-series data will serve provide validation datasets for model results to ensure that the final project outputs are representative and reliable. The project has an active engagement and collaborative effort underway to try and maximize the long-term benefit of the framework. Much of the supporting model datasets will be published under open access licence to support broad usage and integration.
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Bloomsburg, G., J. Finnie, D. Horn, B. King, and J. Liou. Abstracts and parameter index database for reports pertaining to the unsaturated zone and surface water-ground water interactions at the Idaho National Engineering Laboratory. Office of Scientific and Technical Information (OSTI), May 1993. http://dx.doi.org/10.2172/10103992.

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Lamb, Peter. "Workshop to Promote and Coordinate U.S.A. Contributions to AMMA on Land Surface, Water Cycle, Aerosol and Radiation Budget Issues". Office of Scientific and Technical Information (OSTI), May 2008. http://dx.doi.org/10.2172/957988.

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Broussard, Whitney, Glenn Suir, and Jenneke Visser. Unmanned Aircraft Systems (UAS) and satellite imagery collections in a coastal intermediate marsh to determine the land-water interface, vegetation types, and Normalized Difference Vegetation Index (NDVI) values. Engineer Research and Development Center (U.S.), October 2018. http://dx.doi.org/10.21079/11681/29517.

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Becker, Sarah, Megan Maloney, and Andrew Griffin. A multi-biome study of tree cover detection using the Forest Cover Index. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/42003.

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Tree cover maps derived from satellite and aerial imagery directly support civil and military operations. However, distinguishing tree cover from other vegetative land covers is an analytical challenge. While the commonly used Normalized Difference Vegetation Index (NDVI) can identify vegetative cover, it does not consistently distinguish between tree and low-stature vegetation. The Forest Cover Index (FCI) algorithm was developed to take the multiplicative product of the red and near infrared bands and apply a threshold to separate tree cover from non-tree cover in multispectral imagery (MSI). Previous testing focused on one study site using 2-m resolution commercial MSI from WorldView-2 and 30-m resolution imagery from Landsat-7. New testing in this work used 3-m imagery from PlanetScope and 10-m imagery from Sentinel-2 in imagery in sites across 12 biomes in South and Central America and North Korea. Overall accuracy ranged between 23% and 97% for Sentinel-2 imagery and between 51% and 98% for PlanetScope imagery. Future research will focus on automating the identification of the threshold that separates tree from other land covers, exploring use of the output for machine learning applications, and incorporating ancillary data such as digital surface models and existing tree cover maps.
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Bitew, Menberu, and Rhett Jackson. Characterization of Flow Paths, Residence Time and Media Chemistry in Complex Landscapes to Integrate Surface, Groundwater and Stream Processes and Inform Models of Hydrologic and Water Quality Response to Land Use Activities; Savannah River Site. Office of Scientific and Technical Information (OSTI), February 2015. http://dx.doi.org/10.2172/1171150.

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Raymond, Kara, Laura Palacios, Cheryl McIntyre, and Evan Gwilliam. Status of climate and water resources at Saguaro National Park: Water year 2019. Edited by Alice Wondrak Biel. National Park Service, December 2021. http://dx.doi.org/10.36967/nrr-2288717.

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Climate and hydrology are major drivers of ecosystems. They dramatically shape ecosystem structure and function, particularly in arid and semi-arid ecosystems. Understanding changes in climate, groundwater, and water quality and quantity is central to assessing the condition of park biota and key cultural resources. The Sonoran Desert Network collects data on climate, groundwater, and surface water at 11 National Park Service units in south-ern Arizona and New Mexico. This report provides an integrated look at climate, groundwater, and springs conditions at Saguaro National Park (NP) during water year 2019 (October 2018–September 2019). Annual rainfall in the Rincon Mountain District was 27.36" (69.49 cm) at the Mica Mountain RAWS station and 12.89" (32.74 cm) at the Desert Research Learning Center Davis station. February was the wettest month, accounting for nearly one-quarter of the annual rainfall at both stations. Each station recorded extreme precipitation events (>1") on three days. Mean monthly maximum and minimum air temperatures were 25.6°F (-3.6°C) and 78.1°F (25.6°C), respectively, at the Mica Mountain station, and 37.7°F (3.2°C) and 102.3°F (39.1°C), respectively, at the Desert Research Learning Center station. Overall temperatures in WY2019 were cooler than the mean for the entire record. The reconnaissance drought index for the Mica Mountain station indicated wetter conditions than average in WY2019. Both of the park’s NOAA COOP stations (one in each district) had large data gaps, partially due to the 35-day federal government shutdown in December and January. For this reason, climate conditions for the Tucson Mountain District are not reported. The mean groundwater level at well WSW-1 in WY2019 was higher than the mean for WY2018. The water level has generally been increasing since 2005, reflecting the continued aquifer recovery since the Central Avra Valley Storage and Recovery Project came online, recharging Central Arizona Project water. Water levels at the Red Hills well generally de-clined starting in fall WY2019, continuing through spring. Monsoon storms led to rapid water level increases. Peak water level occurred on September 18. The Madrona Pack Base well water level in WY2019 remained above 10 feet (3.05 m) below measuring point (bmp) in the fall and winter, followed by a steep decline starting in May and continuing until the end of September, when the water level rebounded following a three-day rain event. The high-est water level was recorded on February 15. Median water levels in the wells in the middle reach of Rincon Creek in WY2019 were higher than the medians for WY2018 (+0.18–0.68 ft/0.05–0.21 m), but still generally lower than 6.6 feet (2 m) bgs, the mean depth-to-water required to sustain juvenile cottonwood and willow trees. RC-7 was dry in June–September, and RC-4 was dry in only September. RC-5, RC-6 and Well 633106 did not go dry, and varied approximately 3–4 feet (1 m). Eleven springs were monitored in the Rincon Mountain District in WY2019. Most springs had relatively few indications of anthropogenic or natural disturbance. Anthropogenic disturbance included spring boxes or other modifications to flow. Examples of natural disturbance included game trails and scat. In addition, several sites exhibited slight disturbance from fires (e.g., burned woody debris and adjacent fire-scarred trees) and evidence of high-flow events. Crews observed 1–7 taxa of facultative/obligate wetland plants and 0–3 invasive non-native species at each spring. Across the springs, crews observed four non-native plant species: rose natal grass (Melinis repens), Kentucky bluegrass (Poa pratensis), crimson fountaingrass (Cenchrus setaceus), and red brome (Bromus rubens). Baseline data on water quality and chemistry were collected at all springs. It is likely that that all springs had surface water for at least some part of WY2019. However, temperature sensors to estimate surface water persistence failed...
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Nagabhatla, Nidhi, Panthea Pouramin, Rupal Brahmbhatt, Cameron Fioret, Talia Glickman, K. Bruce Newbold, and Vladimir Smakhtin. Migration and Water: A Global Overview. United Nations University Institute for Water, Environment and Health, May 2020. http://dx.doi.org/10.53328/lkzr3535.

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Global migration has been increasing since the 1990s. People are forced to leave their homes in search of safety, a better livelihood, or for more economic opportunities. Environmental drivers of migration, such as land degradation, water pollution, or changing climate, are acting as stronger phenomena with time. As millions of people are exposed to multiple water crises, daily needs related to water quality, lack of provisioning, excess or shortage of water become vital for survival as well for livelihood support. In turn, the crisis can transform into conflict and act as a trigger for migration, both voluntary and forced, depending on the conditions. Current interventions related to migration, including funding to manage migration remain focused on response mechanisms, whereas an understanding of drivers or so-called ‘push factors’ of migration is limited. Accurate and well-documented evidence, as well as quantitative information on these phenomena, are either missing or under-reflected in the literature and policy discourse. The report aims to start unpacking relationships between water and migration. The data used in this Report are collected from available public sources and reviewed in the context of water and climate. A three-dimensional (3D) framework is outlined for water-related migration assessment. The framework may be useful to aggerate water-related causes and consequences of migration and interpret them in various socioecological, socioeconomic, and sociopolitical settings. A case study approach is adopted to illustrate the various applications of the framework to dynamics of migration in various geographic and hydrological scenarios. The case studies reflect on well-known examples of environmental and water degradation, but with a focus on displacement /migration and socioeconomic challenges that apply. The relevance of proxy measures such as the Global Conflict Risk Index, which helps quantify water and migration interconnections, is discussed in relation to geographic, political, environmental, and economic parameters. The narratives presented in the Report also point to the existing governance mechanisms on migration, stating that they are fragmented. The report examines global agreements, institutions, and policies on migration to provide an aggerated outlook as to how international and inter-agency cooperation agreements and policies either reflected or are missing on water and climate crises as direct or indirect triggers to migration. Concerning this, the new directives related to migration governance, i.e., the New York Declaration and the Global Compact for Migration, are discussed. The Report recommends an enhanced focus on migration as an adaptation strategy to maximize the interconnectedness with the Sustainable Development Goals (SDGs). It calls for the migration discourse to look beyond from a preventative and problematic approach to a perspective emphasizing migration as a contributor towards achieving sustainable development, particularly SDGs 5, 6, 13, and 16 that aim strengthening capacities related to water, gender, climate, and institutions. Overall, the synthesis offers a global overview of water and migration for researchers and professionals engaged in migration-related work. For international agencies and government organizations and policymakers dealing with the assessment of and response to migration, the report aims to support the work on migration assessment and the implementation of the SDGs. The Report may serve as a public good towards understanding the drivers, impacts, and challenges of migration, for designing long-term solutions and for advancing migration management capabilities through improved knowledge and a pitch for consensus-building.
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Kirby, Stefan M., J. Lucy Jordan, Janae Wallace, Nathan Payne, and Christian Hardwick. Hydrogeology and Water Budget for Goshen Valley, Utah County, Utah. Utah Geological Survey, November 2022. http://dx.doi.org/10.34191/ss-171.

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Goshen Valley contains extensive areas of agriculture, significant wetlands, and several small municipalities, all of which rely on both groundwater and surface water. The objective of this study is to characterize the hydrogeology and groundwater conditions in Goshen Valley and calculate a water budget for the groundwater system. Based on the geologic and hydrologic data presented in this paper, we delineate three conceptual groundwater zones. Zones are delineated based on areas of shared hydrogeologic, geochemical, and potentiometric characteristics within the larger Goshen Valley. Groundwater in Goshen Valley resides primarily in the upper basin fill aquifer unit (UBFAU) and lower carbonate aquifer unit (LCAU) hydrostratigraphic units. Most wells in Goshen Valley are completed in the UBFAU, which covers much of the valley floor. The UBFAU is the upper part of the basin fill, which is generally less than 1500 feet thick in Goshen Valley. Important spring discharge at Goshen Warm Springs issues from the LCAU. Relatively impermeable volcanic rocks (VU) occur along much of the upland parts of the southern part of Goshen Valley. Large sections of the southwest part of the Goshen Valley basin boundary have limited potential for interbasin flow. Interbasin groundwater flow is likely at several locations including the Mosida Hills and northern parts of Long Ridge and Goshen Gap in areas underlain by LCAU. Depth to groundwater in Goshen Valley ranges from at or just below the land surface to greater than 400 feet. Groundwater is within 30 feet of the land surface near and north of Goshen, in areas of irrigated pastures and wetlands that extend east toward Long Ridge and Goshen Warm Springs, and to the north towards Genola. Groundwater movement is from upland parts of the study area toward the valley floor and Utah Lake. Long-term water-level change is evident across much of Goshen Valley, with the most significant decline present in conceptual zone 2 and the southern part of conceptual zone 1. The area of maximum groundwater-level decline—over 50 feet—is centered a few miles south of Elberta in conceptual zone 2. Groundwater in Goshen Valley spans a range of chemistries that include locally high total dissolved solids and elevated nitrate and arsenic concentrations and varies from calcium-bicarbonate to sodium-chloride-type waters. Overlap in chemistry exists in surface water samples from Currant Creek, the Highline Canal, and groundwater. Stable isotopes indicate that groundwater recharges from various locations that may include local recharge, from the East Tintic Mountains, or far-traveled groundwater recharged either in Cedar Valley or east of the study area along the Wasatch Range. Dissolved gas recharge temperatures support localized recharge outside of Goshen. Most groundwater samples in Goshen Valley are old, with limited evidence of recent groundwater recharge. An annual water budget based on components of recharge and discharge yields total recharge of 32,805 acre-ft/yr and total discharge of 35,750 acre-ft/yr. Most recharge is likely from interbasin flow and lesser amounts from precipitation and infiltration of surface water. Most discharge is from well water withdrawal with minor spring discharge and groundwater evapotranspiration. Water-budget components show discharge is greater than recharge by less than 3000 acreft/yr. This deficit or change in storage is manifested as longterm water-level decline in conceptual zone 2, and to a lesser degree, in conceptual zone 1. The primary driver of discharge in conceptual zone 2 is well withdrawal. Conceptual zone 3 is broadly in balance across the various sources of recharge and discharge, and up to 1830 acre-ft/yr of water may discharge from conceptual zone 3 into Utah Lake. Minimal groundwater likely flows to Utah Lake from zones 1 or 2.
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