Groundwater level assessment and prediction in the Nebraska Sand Hills using LIDAR-derived lake water level

The spatial variability of groundwater levels is often inferred from sparsely located hydraulic head observations in wells. The spatial correlation structure derived from sparse observations is associated with uncertainties that spread to estimates at unsampled locations. In areas where surface water represents the nearby groundwater level, remote sensing techniques can estimate and increase the number of hydraulic head measurements. This research uses light detection and ranging (LIDAR) to estimate lake surface water level to characterize the groundwater level in the Nebraska Sand Hills (NSH), an area with few observation wells. The LIDAR derived lake groundwater level accuracy was within 40 cm mean square error (MSE) of the nearest observation wells. The lake groundwater level estimates were used to predict the groundwater level at unsampled locations using universal kriging (UK) and kriging with an external drift (KED). The results indicate unbiased estimates of groundwater level in the NSH. UK showed the influence of regional trends in groundwater level while KED revealed the local variation present in the groundwater level. A 10-fold cross-validation demonstrated KED with better mean squared error (ME) [–0.003, 0.007], root mean square error (RMSE) [2.39, 4.46], residual prediction deviation (RPD) [1.32, 0.71] and mean squared deviation ratio (MSDR) [1.01, 1.49] than UK. The research highlights that the lake groundwater level provides an accurate and cost-effective approach to measure and monitor the subtle changes in groundwater level in the NSH. This methodology can be applied to other locations where surface water bodies represent the water level of the unconfined aquifer and the results can aid in groundwater management and modeling

Representing past and future hydro-climatic variability over multi-decadal periods in poorly-gauged regions: the case of Ecuador

Cette thèse évalue des méthodes pour représenter la variabilité spatio-temporelle hydro-climatique passée et future dans les régions peu jaugées. Elle propose une procédure complète et reproductible appliquée à l'Équateur et s'appuyant sur des données hydro-climatiques observées et simulées en vue de représenter la variabilité passée et de projeter l'impact potentiel des changements climatiques sur les écoulements à la fin du 21ème siècle. Un état de l'art a permis d'identifier plusieurs techniques qui ont été intégrées dans une chaîne méthodologique pour obtenir des séries spatio-temporelles continues de température, de précipitation et de débit sur les périodes multi-décennales passées et futures. Trois chapitres centraux sont consacrés à cet objectif selon les thèmes suivants : (1) régionalisation de la température et des précipitations à partir de mesures in situ en comparant des techniques déterministes et géostatistiques avec une prise en compte de corrections orographiques; (2) reconstruction du débit dans différents bassins versants à l'aide de modèles hydrologiques conceptuels utilisés selon une approche multimodèle et multiparamétrique; et (3) projections hydro-climatiques basées sur des simulations de modèles climatiques sous contrainte d'un scénario marqué d'émission de gaz à effet de serre. La régionalisation du climat a révélé l'importance de caler les paramètres de spatialisation et d'évaluer les champs interpolés par rapport à des stations ponctuelles indépendantes et via des analyses de sensibilité hydrologique. La reconstruction des débits a été possible grâce aux simulations combinées de trois modèles hydrologiques évalués dans des conditions climatiques contrastées, et forcés par les variables climatiques régionalisées. Des simulations de changements hydro-climatiques à moyen terme (2040-2070) et à long terme (2070-2100) ont ensuite été analysées avec des intervalles de confiance de 95 %, en utilisant des scénarios de neuf modèles climatiques et en transférant les paramètres hydrologiques calibrés pour la reconstruction des débits. L'analyse de la variabilité hydro-climatique montre une légère augmentation des températures sur la période 1985-2015, tandis que la variabilité des précipitations est liée aux principaux modes des phases El Niño et La Niña à l'échelle inter-annuelle et au déplacement de la zone de convergence inter-tropicale (ZCIT) à l'échelle saisonnière. Une augmentation générale de la température (+4,4 °C) et des précipitations (+17 %) est attendue d'ici à la fin du 21ème siècle, ce qui pourrait entraîner une augmentation de +5 % à +71 % du débit annuel moyen selon les bassins versants. Ces résultats sont discutés en termes d'importance pour la gestion de l'eau, avant de suggérer de futures recherches hydrologiques telles que la régionalisation du débit des cours d'eau, une meilleure quantification des incertitudes et une évaluation de la capacité à satisfaire les futurs besoins en eau.This thesis investigates methods to represent the past and future hydro-climatic variability in space and over time in poorly-gauged regions. It proposes a complete and reproducible procedure applied to the continental Ecuador to deal with observed and simulated hydro-climatic data in order to represent past variability and project the potential impact of climate change on water resources by the end of the 21st century. Up-to-date techniques were identified in a literature review and were integrated in a chain protocol to obtain continuous space-time series of air temperature, precipitation and streamflow over past and future multi-decadal periods. Three central chapters are dedicated to this objective according to the following topics: (1) regionalization of air temperature and precipitation from in situ measurements by comparing deterministic and geostatistical techniques including orographic corrections; (2) streamflow reconstruction in various catchments using conceptual hydrological models in a multi-model, multi-parameter approach; and (3) hydro-climate projections using climate model simulations under a high range emission scenario. Climate regionalization revealed the importance of calibrating parameters and of assessing interpolated fields against independent gauges and via hydrological sensitivity analyses. Streamflow reconstruction was possible with the regionalized climate inputs and the combined simulations of three hydrological models evaluated in contrasting climate conditions. Future medium term (2040-2070) and long term (2070-2100) hydro-climatic changes were analysed with confidence intervals of 95% using scenarios from nine climate models and transferring the model parameters calibrated for streamflow reconstruction. Analysis of hydro-climatic variability over the period 1985-2015 showed a slight increase in temperature, while precipitation variability was linked to the main modes of El Niño and La Niña phases at inter-annual scale and to the displacement of the inter-tropical convergence zone (ITCZ) at seasonal scale. Under climate change, a general increase in temperature (+4.4 °C) and precipitation (+17%) is expected by the end of the 21st century, which could lead to between +5% and 71% increase in mean annual streamflow depending on the catchments. These results are discussed in terms of significance for water management before suggesting future hydrological research such as regionalizing streamflow, better quantifying uncertainties and assessing the capacity to meet future water requirements

Balancing water availability and water demand in the Blue Nile : A case study of Gumara watershed in Ethiopia

Ethiopia suffers from economic water scarcity that makes its water utilization difficult. In-depth understanding of the hydrological processes is important for balancing availability and demand. As part of this basin-wide and national concern, this study examines the water balance and water availability on farm and watershed scales in different scenarios. The objectives of the study were (1) to evaluate water use and water productivity of a small-scale irrigation scheme, (2) to evaluate methods for filling gaps in climatic data, (3) to adopt the Soil and Water Assessment Tool (SWAT) hydrological model for modeling hydrological processes using different modeling setups, and (4) to simulate water demand and water stress status for a period up to 2050 using different land-use and demographic scenarios. The Gumara watershed (1520 km2), a tributary of Lake Tana and source of the Blue Nile in Ethiopia, was selected for this study. A case study at a small-scale irrigation scheme shows that there was high water loss during water conveyance and application. At the same time, water stress was observed during irrigation at the scheme level, as the applied water did not match the water needs of different crops. Environmental modeling requires complete climate data sets, which are rarely available. Therefore, different gap-filling methods were applied and tested. Considering data from neighboring climate stations, the methods arithmetic mean and coefficient of correlation weighting methods gave better daily rainfall estimation than the normal ratio and inverse distance weighting methods. Multiple linear regression methods performed well when filling daily air temperature gaps using data from neighboring stations. After seasonal categorization of daily data and optimization of parameters, procedures using maximum and minimum temperature for simulating solar radiation and relative humidity gave promising performances. For process analysis, SWAT was applied for the watershed with an acceptable performance when simulating river flow. The effect of data availability on model performance was analyzed using different numbers of climate stations. Using four and six stations resulted in better SWAT water flow modeling performance as compared to two stations. Penman-Monteith and Hargreaves procedures for potential evaporation calculation resulted in comparable river flow modeling in SWAT. Therefore, the Hargreaves method that needs only air temperature can be used for modeling when other climatic data are not available. Selected watershed management practices shift surface runoff to sub-surface and groundwater flows. An irrigation project planned in the watershed and the watershed management practices shift surface discharge to base flow and evapotranspiration. It will be hard to satisfy the basic human water requirements in 2050 if the existing water management and water productivity conditions pertain. Better green water management and non-consumptive water use options (e.g. hydro power, fishery) can minimize the blue water stress at the Nile basin level

Catchment Water Balance In Data-Scarce Environments- What Insights Does The Budyko Curve Provide? Model- and data-based considerations to assess water balances on the western slopes of the Peruvian Andes and their relationship to the Budyko curve

Wasser in von essentieller Bedeutung für die menschliche Entwicklung und Ökosysteme. Das Verstehen von Wasserbilanzen in Flusseinzugsgebieten ist eine Grundvoraussetzung für Entscheidungen im Wasserressourcenmanagement, insbesondere in wasserknappen Regionen. Neben der Wasserknappheit durch trockenes Klima sowie eine rasante demographische Entwicklung, erschweren eine limitierte Datenlage die Bedingungen in einigen Ländern des globalen Südens. Die vorliegende Arbeit konzentriert sich auf Methoden, die hydrometeorologische Datenlage zu verbessern, um Herausforderungen bei Wasserbilanzschätzungen sowie Modellkalibrierungen entgegenzutreten. Um trotz des Mangels an Abflussdaten in nicht bepegelten Einzugsgebieten hydrologische Modelle zu kalibrieren, können Ähnlichkeitsansätze Abhilfe leisten. Die Budykokurve, ein verbreiteter Ähnlichkeitsansatz, der Klima- und Abflussähnlichkeit auf langen Zeitskalen miteinander verbindet, schätzt die stationäre Wasserbilanz (ETa/P) als Funktion der klimatischen Aridität (ETp/P). Dieser Ähnlichkeitsansatz schien ein nützliches Tool in einer datenarmen Region und wird in der vorliegenden Arbeit angewandt, getestet und analysiert- vor allem in Bezug auf Abweichungen von der Budykokurve (sog. Budyko Offsets). Während manche Fragen allgemeingültiger behandelt werden, liegt der geografische Schwerpunkt dieser Arbeit auf Einzugsgebieten der westperuanischen Anden, insbesondere des Chillón und Lurín. Das Untersuchungsgebiet weist ein saisonales Kima auf, mit Jahresniederschlägen, die entlang eines steilen topografischen Gradienten stark abfallen innerhalb der Einzugsgebiete. Als Basis für Ariditäts- und Wasserbilanzbetrachtungen in den peruanischen Einzugsgebieten werden Methoden entwickelt und angewandt, die Gebietsniederschlag sowie potentielle Verdunstung schätzen. CovVar wird eingeführt, ein simpler und robuster Ansatz zur Regionalisierung von punktuellen Niederschlagsmessungen in datenarmen Gebirgsregionen. Die Methode basiert auf statistischen Zusammenhängen zwischen Höhe und Monatsniederschlägen, in Kombination mit einer gewichteten Regionalisierung der Fluktuation an einer Bezugsstation. CovVar wies gute Performanzmetriken auf, auch im direkten Vergleich mit dem landesweiten Niederschlagsprodukt PISCO. Unterschiede zeigten sich vor allem im Bereich des Gebietsniederschlags im Lurín Einzugsgebiet, welches über kein Niederlags-Monitoring in den feuchtesten Kopfeinzugsgebieten verfügte. Um längere historische Zeitreihen für die potentielle Verdunstung zu generieren, wird der Hargreaves-Samani Koeffizient in der Region kalibriert, auf Grundlage von kurzen Zeitreihen gut ausgestatteter Wetterstationen. Beide Datensätze wurden erfolgreich in einem hydrologischen Modell eingesetzt. Ausgehend von hydrologischer Ähnlichkeit und der Budykokurve als Wasserbilanz-Orientierungspunkt, wurde ein gekoppelter Einzugsgebiets -Modellieransatz angewandt, um ein hydrologisches Modell (mHM) für den Lurín aufzusetzen und einen passenden Parametersatz abzuleiten. Dabei diente das benachbarte, besser beobachtete Chillón Einzugsgebiet als Referenz und Parameter-Spender. Durch die Einzugsgebiets-Kopplung konnte die Qualität der verschiedenen Forcing-Datensätze evaluiert werden. Diese hatten einen starken Einfluss auf beobachtete und simulierte Wasserbilanzen im Lurín. Im Vergleich zum PISCO-Datensatz, lieferte CovVar Ariditätsindizes und Wasserbilanzen für den Lurín, die sowohl mit dem als ähnlich angenommenen Nachbareinzugsgebiet als auch mit der Budykokurve deutlich besser übereinstimmen, was auf realistischere Schätzungen schließen lässt. Das Gewicht der Variabilität der verschiedenen Datensätze überstieg bei Weitem das der verschiedenen Modell-Parametersätze. Der Parametertransfer lieferte dennoch funktionale Parametersätze für den Lurín, die mit direkten Lurín-Kalibrierungen vergleichbar waren. Die Analyse wurde auf 17 ähnlich angeordnete Einzugsgebiete im Untersuchungsgebiet erweitert, um deren Wasserbilanzähnlichkeit und Budyko offsets zu untersuchen. Eine lineare Korrelationsanalyse wurde durchgeführt, um den Einfluss von subskaligen klimatischen und Einzugsgebietseigenschaften auf Wasserbilanz und Budyko offset zu beleuchten. Die Analyse zeigte sowohl eine systematische Überschätzung der Budykokurve als auch eine enorm hohe Variabilität zwischen den Einzugsgebieten, für die vor der Analyse mehr Ähnlichkeit erwartet wurde. Die individuellen Bestimmtheitsmaße blieben bei diesem recht einfachen, linearen Ansatz erwartungsgemäßig niedrig, dennoch gab es Signale für klimatische Heterogenität, Schneebedeckung sowie Abflusssaisonalität als Proxy für sämtliche Speichervorgänge im Einzugsgebiet. Während diese Einflüsse im Hinblick auf physikalische Vorgänge sowie Literaturinformationen diskutiert werden, werden Gründe für Restvarianz sowie den systematischen Trend bei Einflüssen wie dem Bodenspeicher, potentiell in Kombination mit saisonalen Effekten, vermutet. Aufgrund der inkonsistenten Wasserbilanzen in der Region sowie der steilen andinen Topographie in Kombination mit dem semiariden Klima, untersucht eine Modellstudie gezielt den Einfluss des Bodenspeichers. Der aus der Literatur bekannte Einfluss der Bodenspeicherkapazität auf die mittlere Wasserbilanz steht seiner schweren Quantifizierbarkeit auf Einzugsgebietskale gegenüber. Aus diesem Grund wurden mehrere Einzugsbebiete als realitätsnahe Systeme für ein "virtuelles Experiment" ausgewählt. Sowohl Bodenspeicher in Form von freiem Porenraum als auch ein kapillaritätsgesteuerter Anteil wurden im Modell variiert und die resultierenden Wasserbilanzen analysiert. Die Ergebnisse bestätigen die bedeutende Rolle des Bodenspeichers für die mittlere Wasserbilanz und potentiellen Budyko Offsets. Sowohl der Gesamtbodenspeicher als auch die kapillaritätsbeeinflusste Teil erwiesen sich als sensitive Größen. Durch Variation des Bodenspeichers erreichte fast jedes System die Budykokurve, mit einem erkennbaren Clustering bei Speichergrößen von etwa 5-15% des mittleren Jahresniederschlags -was in der Natur vorkommenden Werten entspricht- bevor die Wasserbilanzen ein quasi-asymptotisches Level erreichen

Wadi Flash Floods

This open access book brings together research studies, developments, and application-related flash flood topics on wadi systems in arid regions. The major merit of this comprehensive book is its focus on research and technical papers as well as case study applications in different regions worldwide that cover many topics and answer several scientific questions. The book chapters comprehensively and significantly highlight different scientific research disciplines related to wadi flash floods, including climatology, hydrological models, new monitoring techniques, remote sensing techniques, field investigations, international collaboration projects, risk assessment and mitigation, sedimentation and sediment transport, and groundwater quality and quantity assessment and management. In this book, the contributing authors (engineers, researchers, and professionals) introduce their recent scientific findings to develop suitable, applicable, and innovative tools for forecasting, mitigation, and water management as well as society development under seven main research themes as follows: Part 1. Wadi Flash Flood Challenges and Strategies Part 2. Hydrometeorology and Climate Changes Part 3. Rainfall–Runoff Modeling and Approaches Part 4. Disaster Risk Reduction and Mitigation Part 5. Reservoir Sedimentation and Sediment Yield Part 6. Groundwater Management Part 7. Application and Case Studies The book includes selected high-quality papers from five series of the International Symposium on Flash Floods in Wadi Systems (ISFF) that were held in 2015, 2016, 2017, 2018, and 2020 in Japan, Egypt, Oman, Morocco, and Japan, respectively. These collections of chapters could provide valuable guidance and scientific content not only for academics, researchers, and students but also for decision-makers in the MENA region and worldwide

Development and assessment of an integrated largescale hydrological modelling tool for water resources management in the Cauvery Catchment, India.

Doctoral Degree. University of KwaZulu-Natal, Pietermaritzburg.Economic development and population growth in southern India have resulted in rapid changes to land use, land management and water demand, significantly impacting and degrading water resources. The significant anthropogenic influences across the catchment have contributed to changes in hydrological functioning. Focussing on the highly contentious inter-state Cauvery River Catchment, this study aims to address the key scientific challenges faced within this catchment. The study was designed to develop an integrated large-scale hydrological model to improve water resource assessments in a highly heterogeneous and data-scarce region whilst considering the primary water resource challenges facing the Cauvery Catchment. The Upper Cauvery region, located in the Western Ghats, acts as the water tower of the catchment. The rainfall in the region is monsoonal, the topography is complex, and the rain gauge network is sparse, resulting in the estimation of rainfall being particularly challenging. The scarce rainfall data available in the Western Ghats region is hindering the understanding of the regional weather system, and the accepted rainfall dataset for India, Indian Meteorological Department rainfall grids, are known to have inaccurate estimations within the Western Ghats. The current knowledge of the meteorology and hydrology of the Upper Cauvery is limited. Additionally, the anthropogenic impact on local hydrological processes, such as streamflow, groundwater recharge and evapotranspiration, is poorly constrained. The current understanding of how these diverse local changes cumulatively impact water availability at the broader catchment scale is minimal. Small-scale rural water management and urban heterogeneity may strongly affect water resource availability across southern India. However, how such fine-scale factors propagate to the river catchment is largely unclear. The Global Water Availability Assessment (GWAVA) model was applied initially to the Upper Cauvery region to determine the suitability and compare model results from other modelling tools applied in the region. Two new versions of the GWAVA model were then developed. The first aimed to include small-scale runoff harvesting interventions (SSRHIs) into the model and quantify their impact on catchment water resources to address a renewed scientific interest in assessing their effectiveness in improving local water resources and the effects at a catchment scale. The second aimed to enhance the representation of groundwater and large operational dams whilst maintaining the model’s applicability to regions with low-data availability. The Indian Meteorological Department (IMD) gridded rainfall was compared to available gauges and selected remotely sensed datasets within the Upper Cauvery region. GWAVA will be utilised to assess the applicability of the remotely sensed data for a catchment rainfall estimation. GWAVA was determined to be a suitable tool to represent the Cauvery Catchment; however, the importance of an accurate spatial representation of rainfall for input into hydrological models and that comprehensive dam functionality is paramount to obtaining good results in this region was highlighted. Furthermore, the average GWAVA, VIC and SWAT ensemble provided a better predictive ability in catchments with dams than the individual models. The average ensemble offset uncertainty in input data and poor dam operation functionality within individual models. The inclusion of SSRHIs demonstrated that farm bunds appear to have a negligible effect on the average annual simulated streamflow. In contrast, tanks and check dams have a more significant and time-varying impact. The open water surface of the SSRHIs contributed to an increase in evaporation losses across the sub-catchment. The change in simulated groundwater storage with the inclusion of SSRHIs was not as significant as sub-catchmentscale literature, and field studies suggest. Including groundwater processes into GWAVA improved streamflow simulation in the headwater sub-catchments and the representation of the baseflow component such that low-flow model skill increased approximately 33-67% in the Cauvery and 66-100% in the Narmada. The existing dam routine was extended to account for large, regulated dams with two calibratable parameters. The routine improved streamflow simulation in sub-catchments downstream of major dams, where the streamflow was largely reflective of dam releases. The model performance was improved between 15 and 30% in the Cauvery and 7-30% in the Narmada when the regulated dams were considered. The model provides a more robust representation of the annual outflow volume from major dams, reducing the average bias from -17% to -1% in the Cauvery and from 14% to 3% in the Narmada. The daily dam releases were significantly improved in the Cauvery, approximately 26-164%. The improvement of the groundwater and dam routines in GWAVA proved successful in improving the overall model performance, the low-flow model skill and bias, and the inclusions allowed for improved traceability of simulated water balance components. It was found that the IMD rainfall within the high-altitude regions of the Western Ghats is underestimated, resulting in the under-simulation of streamflow in the Upper Cauvery. CHIRPS 0.25- and 0.05- degree, MSWEP and PERSIANN remotely sensed rainfall datasets were applied within this region. None of the individual rainfall datasets provided a more accurate representation of the rainfall than the commonly utilised IMD grids. However, using an ensemble of remotely sensed rainfall datasets, primarily the average ensemble, improved the accuracy of rainfall estimation in the catchment. The ‘off-the-shelf’ remotely sensed rainfall products provided a high variation in performance against the in-situ rain gauge data. The IMD grids provided the most accurate representation of rainfall compared to the individual remotely sensed rainfall datasets, despite underestimating the rainfall depths at high altitudes. In the case of the Upper Cauvery, the average ensemble provided a more accurate representation of the rainfall. An integrated large-scale hydrological model was developed to improve water resources assessments in a highly heterogeneous and data-scarce region whilst considering the major water resource challenges facing the Cauvery Catchment. The effects of runoff harvesting interventions, accounting for hard-rock aquifer groundwater processes and the impact of major dams were represented. The inclusion of these features improved the model performance throughout the Cauvery Catchment

Flood modellling approaches for large lowland tropical catchments.

Flooding is increasing in tropical regions, where millions of people are at risk, and challenges exist in providing reliable predictions and warnings. This research responds to this challenge by identifying and applying physics-based and data-based hydrological modelling approaches for large-scale flood modelling in lowland tropical regions. First, a distributed hydrological model was developed to accurately represent catchment conditions and processes in the model. Second, empirical data from nested catchments were analysed using statistical scaling relationships to complement the accuracy of peak discharge estimates. Finally, the effects of uncertainty propagation and interactions were quantified to increase the reliability of model results. The research was conducted in the Grijalva catchment area (57 958 km²) southeast of Mexico. A large-scale model with a 2 x 2 km grid cell resolution was developed using the SHETRAN hydrological model and run enforced with 3-hour input rainfall data. Geostatistical techniques were used to quantify and reduce errors in input data, and all diverted flows were accounted for to optimise simulations. For the first time, the application of the Scaling theory of floods was applied in the study area to improve the estimation of peak discharge. A Monte Carlo technique was used to propagate and quantify rainfall and parameter uncertainties through a coupled hydrologic and hydraulic model and into model results. Although the model under-predicted the magnitude of peak discharge, calibration results showed satisfactory model performance (NSCE = 0.72, CC = 0.74, Bias = –0.44% and RMSE 139.56 mm) and validation results were good (NSCE = 0.56, CC = 0.60, Bias = –6.3% and RMSE 62.59 mm). A statistical log-log relationship between intercepts (α) and peak discharge, from the smallest nested catchment, was used to complement the simulation of peak discharge magnitudes. It was observed that given rainfall uncertainties of ±71%, ranging from 63 to 73%; the model generates discharge with uncertainties of ± 46%, ranging from 45 to 49% and errors of ±46% ranging from 45 to 46%. The propagated uncertainties resulted in flood inundation extents of ±4.34 km² varying from 1.66 to 7.02 km² Thus, flood modelling in large tropical regions can be achieved by optimally integrating several datasets with the best combination of the model parameter, input and output datasets based on uncertainty and error quantification and removal approaches.PhD in Water, including Desig