Dr Omer Yetemen

Soil water potential (SWP) strongly influences plant productivity and ecosystem functioning, particularly in arid regions characterized by sporadic and pulsed rainfall. This work aims to improve understanding of the response of SWP to varied rainfall pulses, and of the water-use strategies of a widespread C4 shrub (Haloxylon ammodendron, HA) in arid northwestern China. Rainfall manipulation experiments and field measurements on HA were undertaken to explore the response features of SWP and plant physiological status to pulsed rainfall events of varied magnitudes and durations. The physiological state of HA was evaluated by quantifying critical metrics indicative of plant water-use strategies, including leaf water potential, photosynthetic rate and transpiration rate. The response value of SWP increased with rainfall magnitude and was most affected by three vital factors (antecedent SWP, total rainfall and rainfall intensity). Low antecedent SWP amplifies SWP's sensitivity to subsequent events, accelerating its response to smaller rainfalls (<5 mm) compared with larger ones (>15 mm). Small rainfall can increase SWP by 0.5¿2 MPa in the 20-cm layer, sustaining plant physiological activities under high antecedent SWP conditions (>-3.5 MPa), with a maximum average rise in photosynthetic rate of 9.20 ± 0.45 µmol CO2 m-2 s-1, enhancing HA's water use efficiency to 1.79 ± 0.22 µmol CO2 mmol-1 H2O. Therefore, small events play a vital role in maintaining SWP and promoting water use of desert plants. Given the nature of plants' utilization of small rainfall events, re-examining ecologically valid SWP thresholds of HA and other similar desert plants is critical.

The hypersaline Urmia Lake in NW Iran offers unique sedimentary environments sensitive to climate and environmental shifts, fostering coated grain formation and serving as a vital indicator of paleoenvironmental conditions. This study characterizes coated grains within a 25-m sediment core dating back to ~50 cal ka bp, assessing their significance through morphology, internal structures, mineralogy, and geochemistry. Coated grains in Urmia Lake exhibit concentric laminations, primarily calcite and aragonite, revealing alternating light carbonate-rich and dark organic-rich laminations. These reflect seasonal and long-term variations in water chemistry and biogenic production. Dry season algal blooms contribute to lamination, highlighting the interplay between seasonal climate fluctuations and the consequent lake water enrichment in calcium, carbonate, and bicarbonate ions. The diversity and abundance of coated grains indicate three main lake level fluctuation stages in the last ~50 cal ka: a lowering stage with dominant coated grains, a low lake level with dominant terrigenous fragments and minerals, and a high lake level with prominent Artemia urmiana fecal pellets. The role of the brine shrimp A. urmiana in coated grain formation involves absorbing calcium, carbonate, and bicarbonate ions and inhibiting coated grain formation during high lake levels while providing nuclei during lake lowering. An in-depth investigation of coated grains provides a chemical and biological formation framework, highlighting three main episodes in the lake's history.

While the land use-street network nexus is well acknowledged, evidence for the one-way impacts of land-use patterns on street accessibility is still inadequate. The measurements of land-use patterns and street accessibility lack systematic knowledge. Their empirical correlations also lack geographical variability, constraining site-specific land-use practices. Therefore, this study overcame the aforementioned limitations by examining the two-level spatial models to formulate accessibility-oriented land plans, using a well-developed Chinese city as an example. Firstly, two landscape metrics¿Euclidean Nearest-Neighbor Distance (ENN) and Similarity Index (SIMI)¿were used to quantify the intra- and inter-land-use configurations, respectively. Both city-level and local accessibility were measured using spatial design network analysis. Performing both ordinary least squares (OLS) and geographically weighted regression (GWR) models, results identified the statistically significant effects of inter-land-use patterns on two-level street accessibility. An exception was that land-use configurations within residential and industrial regions were irrelevant to street accessibility. We also found GWR was a better-fitting model than OLS when estimating locally-varied accessibility, suggesting hierarchical multiscale land-use planning. Overall, locally heterogeneous evidence in this study can substantialize land use-street network interactions and support the decision-making and implementation of place-specific accessibility-oriented land use.

Drought risk threatens pastoralism in rangelands, which are already under strain from climatic and socioeconomic changes. We examine the future drought risk (2031¿2060 and 2071¿2100) to rangeland productivity across Eurasia (West, Central, and East Asia) using a well-tested process-based ecosystem model and projections of five climate models under three shared socioeconomic pathway (SSP) scenarios of low (SSP1-2.6), medium (SSP3-7.0), and high (SSP5-8.5) warming relative to 1985¿2014. We employ a probabilistic approach, with risk defined as the expected productivity loss induced by the probability of hazardous droughts (determined by a precipitation-based index) and vulnerability (the response of rangeland productivity to hazardous droughts). Drought risk and vulnerability are projected to increase in magnitude and area across Eurasian rangelands, with greater increases in 2071¿2100 under the medium and high warming scenarios than in 2031¿2060. Increasing risk in West Asia is caused by longer and more intense droughts and vulnerability, whereas higher risk in Central and East Asia is mainly associated with increased vulnerability, indicating overall risk is higher where vulnerability increases. These findings suggest that future droughts may exacerbate livestock feed shortages and negatively impact pastoralism. The results have practical implications for rangeland management that should be adapted to the ecological and socioeconomic contexts of the different countries in the region. Existing traditional ecological knowledge can be promoted to adapt to drought risk and embedded in a wider set of adaptation measures involving management improvements, social transformations, capacity building, and policy reforms addressing multiple stakeholders.

As a typical vulnerable ecosystem, alpine steppes can be subject to nonlinear accelerations in degradation, once tipping points are reached or exceeded, and thus far more effort and investment will be needed, to reverse the degraded status of such ecosystems, if effective preventive measures or interventions are not adopted sufficiently early. Thus, detecting early warning signals of tipping events is extremely important for ecosystem protection and recovery, but remains highly challenging. For alpine steppes, coverage or biomass loss and species invasion are both key transitions. Using multi-source data, including ground surveys and remote sensing images with different resolutions, we tried to screen and identify potential early-warning signals for alpine grassland degradation events and analyze their efficacy. The results showed that the degradation levels derived from spatial heterogeneity information combined with a vegetation index were reliable, as was verified by ground surveys, and could illustrate the degradation process of a grassland ecosystem. Six common early-warning signals (variance, skewness, and autocorrelation, from both the spatial and temporal domains) were tested according to degradation degree, and spatial autocorrelation and temporal autocorrelation had the best performances, as they could indicate different degradation levels, and the change trends of temporal autocorrelation could provide early-warning functions. A waved change of spatial variance could reflect a vegetation growth dynamic that might indicate species invasion. In this study, the threshold values of spatial and temporal autocorrelation were 0.7 and 0.2, respectively, and from these, the thresholds of vegetation coverage and biomass were then obtained. However, these signals and thresholds had some limitations during application. These findings provide insights into better understanding of the alpine grassland degradation process, and contribute to a better management approach for vulnerable ecosystems using early-warning methods.

Landscapes evolve through nonlinear interactions between soil, vegetation, and climate. In semi-arid ecosystems, soil moisture variability (SMV) and vegetation variability (VV) can be strongly related to landscape organisation induced by differences in insolation on opposing north-facing slopes (NFS) and south-facing slopes (SFS). Due to its complex interactions with various processes and factors, soil moisture and vegetation exhibit significant variability in both space and time. In this study, the Channel-Hillslope Integrated Landscape Development (CHILD) landscape evolution model (LEM), coupled to a dynamic vegetation model (BGM) and equipped with a spatially distributed solar radiation component is used. The model is used to investigate the implications of various soil, climatic, and geomorphic factors on SMV and VV over landscapes with different characteristics. The analysis of model results indicates that SMV and VV are more sensitive to changes in geomorphic (hillslope diffusion and uplift rate) and climate (solar radiation, precipitation) factors than to soil hydrologic factors (anisotropy, porosity, infiltration capacity, root depth, and pore size distribution) considered in this study. Spatial variability increases with decreases in hillslope diffusion, and with increases in uplift rates and latitude, while temporal variability has the same response to those factors, and also increases with precipitation. All of these factors contribute to larger difference in condition on NFS and SFS, which ultimately is reflected in SMV and VV. Slope-area, soil moisture-area, and vegetation-area relationships revealed that the difference in SMV and VV between NFS and SFS is more pronounced for smaller contributing areas, where NFS are steeper than SFS. They also show that the temporal variability of soil moisture and vegetation is less in SFS than in NFS.

An intricate association between weathering and erosional processes is largely controlled by climate disparities. Weathering as a predisposing process for natural hazards, landform evolution, and sediment mobility, hosts key uncertainties in our understanding of how climate controls differential weathering types and rates. Here, we investigate how weathering is influenced by seasonal changes in precipitation and temperature in badland landscapes. Previous studies have commonly adopted rainfall simulation approach in the field or laboratory, but have simulated only steady climate conditions to understand weathering dynamics. Taking these studies further, we simulated seasonal changes in precipitation and temperature in the laboratory. To understand their weathering response, we exposed samples collected from four different climates over twelve sequential seasons, reflecting a 3-year period. We used pH, electrical conductivity (EC), ion concentrations, and surficial changes as chemical and physical proxies, respectively, to infer types and trends of weathering. Based on the influence of sediment physicochemical properties (especially high sodium absorption ratio (SAR)) on weathering processes, our findings reveal that sinusoidal trends attaining their peak level in spring in Na+ concentration, which overcomes other ions, contribute to an accelerated dispersion degree with concurrently decreasing pH in marly sediments in the Arid region. Moreover, the recurrent pattern of increased Ca2+ levels, especially during winter seasons, can enhance the extent of sediment aggregations within Mediterranean sandy mudstones. In conclusion, consistent with previous studies, wetting¿drying cycles are crucial in physical weathering and regolith behavior, which resulted in cyclic deep crust formations in the spring and summer seasons due to the high swelling capacity of samples. Overall, this study demonstrates how seasonal changes in climate regulate the degree of chemical and physical weathering processes in badland landscapes.

Solar energy is a rapidly growing industry, and the performance analysis and maintenance of solar farms are crucial for ensuring their photovoltaics efficiency and longevity. In this context, many solar farms are established and it is crucial for energy producers to operate these farms efficiently. However, control of solar degradation panels locally takes time and control procedures are a challenge for the producers particularly for large farms. In recent years, the use of unmanned aerial vehicles equipped with thermal imaging sensors has emerged as a promising technique for monitoring solar farms. Herein, degradation inspection and efficiency analyses of the solar panels can be effectively conducted by mapping thermal orthomosaic data. In this study, thermal images were obtained for orthomosaic data production by conducting photogrammetric flights with a real time kinematic enabled unmanned aerial vehicles on a solar farm. The solar panels were divided into segments by the segmentation process and photovoltaics efficiency was calculated for each panel based on solar energy. The photovoltaics efficiency was monitored to vary at most 1.22 % throughout the day with the maximum efficiency reaching 18.25 % in the afternoon, and the minimum efficiency dipping to 17.03 % midday. Close efficiency values were acquired in the morning and afternoon with a difference not exceeding 0.12 %. As such, the damage conditions of panels can be identified by designating the ones with the lowest efficiency. Thus it can be deduced that rapid, cost effective and feasible assessment of solar farms may be possible by unmanned aerial vehicle-based thermal monitoring while bringing forth more sensitive future predictions.

Post-wildfire management actions mainly targeting the removal of salvage logs and burned trees is a common but controversial practice. Although it aims to regain some of the natural and economic value of a forest, it also requires disturbing burned areas, which may have some negative consequences affecting, for instance, the carbon cycle, soil erosion, and vegetation cover. Observations from different geographic settings contribute to this scientific debate, and yet, the spatiotemporal evolution of the post-fire road network developed as part of fire management practices and its influence on vegetation recovery has been rarely examined. Specifically, we still lack observations from Türkiye, though wildfires are a common event. This research examined the evolution of the vegetation cover in relation to post-fire road constructions and the resultant debris materials in areas affected by the 2017 Sapadere fire in Antalya, Türkiye. We used multi-sensor, multi-temporal optical satellite data and monitored the variation in both vegetation cover and road network from the pre-to post-fire periods between 2014 and 2021. Our results showed that fire management practices almost doubled the road network in the post-fire period, from 487¿km to 900¿km. Overall, 7% of the burned area was affected by these practices. As a result, vegetation cover in those areas shows only ~50% recovery, whereas undisturbed areas exhibit ~100% recovery 5¿years after the event. Notably, such spatiotemporal analysis carried out for different burned areas would provide a better insight into the most suitable post-fire management practices. Our findings, in particular, show that the current practices need to be revisited as they cause a delay in vegetation recovery.

A soil moisture data-driven method through inversely solving the Richards' equation was tested, and proved to be a reliable alternative estimator of actual evapotranspiration (ETa) for relatively homogeneous soils in an arid region. Few studies have examined the feasibility of the method using soil moisture for soils with more heterogeneities, which may lead to biased parameters and varied root depths, and thus inaccurate estimates of ETa. We used a genetic algorithm to optimize the parameters most sensitive to ETa estimation, then estimated daily and seasonal ETa using hourly soil moisture data, measured from four sites (from surface to 2-m depth at 20-cm intervals) with different soil textures and crop species in desert-oasis farmlands in northwest China. The seasonal ETa values were 487, 574, 436, and 377 mm at the sites cropped with field maize, spring wheat, seed maize, and seed maize, respectively, in 2018. The daily rates from one site were validated against the eddy-covariance measurements, and the daily rates from all the sites were compared against the estimations from a simple water balance method, and both showed good consistency (R2 = 0.72-0.93). The inverse method has great potential for relatively accurate estimates of ETa in the middle and late growing stages but may induce a slight underestimation in the initial growing season. To determine the minimum monitoring depths of sensors for relatively accurate estimates, ETa values were estimated using soil moisture data at various observation depths, and were compared with eddy-covariance measurements and hypothetical ETa-observed depth curves. The results showed that inaccurate stratification of soil types in the profiles may cause great uncertainty in the estimates, and if texture-contrasting interlayers exist in the profiles, the lowest soil moisture sensor should be placed sufficiently deep, with all the interlayers fully included.

The importance of easy wayfinding in complex urban settings has been recognized in spatial planning. Empirical measurement and explicit representation of wayfinding, however, have been limited in deciding spatial configurations. Our study proposed and tested an approach to improving wayfinding by incorporating spatial analysis of urban forms in the Guangdong-Hong Kong-Macau Great Bay Area in China. Wayfinding was measured by an indicator of intelligibility using spatial design network analysis. Urban spatial configurations were quantified using landscape metrics to describe the spatial layouts of local climate zones (LCZs) as standardized urban forms. The statistical analysis demonstrated the significant associations between urban spatial configurations and wayfinding. These findings suggested, to improve wayfinding, 1) dispersing LCZ 1 (compact high-rise) and LCZ 2 (compact mid-rise) and 2) agglomerating LCZ 3 (compact low-rise), LCZ 5 (open mid-rise), LCZ 6 (open low-rise), and LCZ 9 (sparsely built). To our knowledge, this study is the first to incorporate the LCZ classification system into the wayfinding field, clearly providing empirically-supported solutions for dispersing and agglomerating spatial configurations. Our findings also provide insights for human-centered spatial planning by spatial co-development at local, urban, and regional levels.

The planning of green-blue spaces (GBSs) requires considering the pedestrian needs in their walking routes for improving the walking experience. Incorporating the quantitative spatial characteristics of pedestrian movement is essential for pedestrian-friendly urban planning, which however received insufficient attention. Based on the space syntax theory, this study provided three indicators ¿ accessibility, visibility, and intelligibility ¿ to demonstrate the needs of physical access, visual access, and spatial cognition, respectively, in pedestrian movement. Measuring these three indicators, this study exemplified the planning of pedestrian-friendly GBSs using Guangzhou, China as a case study. Spatial design network analysis was used to quantify heterogeneous values of accessibility, visibility, and intelligibility of each GBS throughout the city. Moreover, we used principal component analysis to identify the leading indicators based on their weightings and then to calculate the scores to compare these three aspects of GBSs. The measurements of accessibility, visibility, and intelligibility of each GBS were then averaged across urban administrative districts for evaluating city-scale GBSs. The findings showed that GBSs in central districts were most accessible and visible but least intelligible. In contrast, the overall intelligibility of GBSs throughout the city was the greatest but the visibility was the least. Furthermore, intelligibility, as a more important factor than accessibility and visibility, should be particularly emphasized in future planning of pedestrian-friendly GBSs. Pedestrians from the central districts of Guangzhou city were most satisfied with the walking experience, in terms of accessing to, viewing, and cognizing the GBSs. 'Yuexiu', 'Huadu', and 'Nansha' districts were found as the key places where improved accessibility, visibility, and intelligibility were particularly needed to improve the GBS pedestrian-friendliness throughout the city. In summary, this study not only demonstrated a human-scale GBS evaluation framework for improving the human walking experience but also provided empirical evidence for building pedestrian-friendly green-blue spaces at the city scale.

Badlands are extremely rugged, outstanding landscapes that can be seen in all ice-free climate regions over erosion-susceptible unconsolidated materials, and they have drawn attention with their spectacular and iconic forms. Unlike nearly all badlands researches conducted at the experimental site and watershed scale, so far, the broader-scale evaluation has been neglected in the analysis of badland distribution, characteristics, and dynamics. Our study provides an integrative new insight into badland landscapes by investigating the distribution, characteristics and controlling factors of Turkish badlands on a broad, regional scale. We inventoried Turkish badlands using aerial imagery and studied their distribution using K-means clustering, an unsupervised machine learning algorithm, based on a set of major conditional geo-environmental factors that control the regional distribution and characteristics of badlands, including tectonics, lithology, topography, climate, and vegetation. Here, we identified, a total of 4494 km2 of badland areas which are non-uniformly distributed across Turkey, substantially clustered in the Central Anatolian Plateau (CAP). According to our regional analyses, we have determined a total of five badland regions comprising three major types classified as Semi-arid, Mediterranean, and Montane (humid), together with two transitional types in-between the Semi-arid and Montane badland regions. Our results indicate that temperature seasonality (0.83), mean annual precipitation (0.83), and precipitation seasonality (0.76) are predominantly assigned to the badlands clusters. The clastic rocks are revealed as the most crucial and inevitable factor for the development of Turkish badlands, which are represented in a wide geologic time-scale (Cretaceous to Quaternary) and diverse lithological units (i.e., lacustrine, volcaniclastics, and terrestrial). Neogene and Paleogene terrestrial clastics (77 %) constitute the majority of the lithologic settings of these badland landscapes. The active and complex tectonic history of Turkey has portrayed the fundamental frame of the identified badland regions, by providing a susceptible environment (i.e., development of sedimentary basins) and promoting badland development through successive base-level changes. Furthermore, tectonically-modulated (i.e., formation of orogenic belts, and uplifting of CAP) climate dynamics outline the distribution pattern and differentiation of the regional characteristics of badlands in Turkey. Overall, our regional-scale approach to badland mapping and regional synthesis may decipher not only the tectonic and climatic conditions of the identified badlands regions, but it may also contribute to the implementation of future effective strategies for the detection and mapping of erosion susceptible and high sediment flux areas in very broad spatial contexts of similar unexplored territories.

Photovoltaic technology plays an important role in the sustainable development of clean energy, and arid areas are particularly ideal locations to build large-scale solar farms, all over the world. Modifications to the energy balance and water availability through the installation of large-scale solar farms, however, fundamentally affect the energy budget, water, and biogeochemical cycles. In-situ field observations, though, fail to draw definitive conclusions on how photovoltaic panels (PVs) affect the ambient environment, or how microclimates and soil moisture evolve under the long-term, continuous, cumulative influence of PVs. Here, we designed a synthetic model, integrating processes of energy budget and water cycle, to quantify the ecohydrological effects of PVs on soil microclimate and moisture regimes at different locations (zones) near individual PVs. Simulations run with a stochastically generated 100-year climate time series were examined to capture the evolutionary trends of soil microclimate and soil moisture. The results indicate that soil moisture content was increased by 59.8% to 113.6% in the Middle and Front zones, and soil temperature was decreased by 1.47 to 1.66 °C in all the sheltered zones, mainly because there was 5¿ 7 times more available water and ~27% less available radiation there, compared with the control zone. On the other hand, if the ground clearance of the PVs is too low, turbulence beneath hot PVs will have a significant influence on not only soil temperature but also soil moisture content. The innovative contribution of this study lies in reinforcing existing theoretical patterns for the development of soil microclimate and moisture dynamics influenced by PVs, and can be used to provide reliable insights into the hydrological and biogeochemical processes on Earth and the sustainable management of large-scale solar farms in arid ecosystems.

Soil water potential (SWP) is vital for controlling the various biological and non-biological processes occurring through and across the soil-plant-atmosphere continuum (SPAC). Although the dynamics and mechanisms of SWP have been investigated for several decades, they are not as widely explored in ecohydrology research as soil moisture, due at least partly to the limitation of field observation methods. This limitation restricts the understanding of the responses of plant physiology and ecological processes to the SWP gradient and the ecohydrological functions of SWP dynamics in different contexts. Hence, in this work, we first briefly revisit the origin and development of the concept of SWP and then analyze the comprehensive factors that influence SWP and the improvement of SWP observation techniques at field scales, as well as strategies for developing new sensors for soil water status. We also propose views of focusing on the response characteristics of plant lateral roots, rather than taproots, to SWP dynamics, and using hormone signaling research to evaluate plant response signals to water stress. We end by providing potential challenges and insights that remain in related research, such as the limitations of the SWP evaluation methods and the future development direction of SWP data collection, management, and analysis. We also emphasize directions for the application of SWP in controlling plant pathogens and promoting the efficiency of resource acquisition by plants. In short, these reflections revisit the unique role of SWP in eco-hydrological processes, provide an update on the development of SWP research, and support the assessment of plant drought vulnerability under current and future climatic conditions.

In this study, we present pollen records together with a multiproxy analysis from a sediment core collected from the Güllük Bay (Bargilya Cove, Mugla, SW Turkey), covering the last 400 years. Pistachio shrubland was occupying around the Güllük Bay between 1613 and 1741 AD. However, after 1741 AD, the vegetation canopy suddenly changed and Turkish pine (Pinus brutia) was established. This supports that the main factor affecting the expansion of Pistacia lentiscus was precipitation rather than temperature after 1741 AD. This change is also indicated by high Sr-Ca values, reflecting arid conditions. Two anthropogenic phases developed in the region. The first phase is marked by Olea europeae between 1613 and 1789 AD. The second is characterized by Plantago, Caryophyllaceae, Cerelia, Rumex, and Sanguisorba minor type suggesting pastoralism and agricultural activities between 1789 and 1964 AD. Macrofaunal communities are also indicative of environmental changes. Abra ovata, Cerastoderma glaucum, Bittium reticulatum, and Skenea catenoides were first settlers between 1572 and 1643 AD. The prominent presence of lagoonal species Abra ovata and Hydrobia ventrosa indicates a lagoonal depositional environment in 1799-1948 AD.

One-size-fits-all approach is common in climate-sensitive urban design due to neglecting spatial heterogeneities in urban form and urban climate. This study explores a spatially-varied climate-sensitive urban design based on the Guangdong-Hong Kong-Macau Greater Bay Area (GBA). Three thermal indices, the Wet Bulb Globe Temperature (WBGT), the Apparent Temperature (AT), and the Universal Thermal Climate Index (UTCI) are used to assess the outdoor thermal environments. The local climate zone (LCZ) classification system is used to map urban form including built and land-cover types. Moreover, incorporating spatial effects, geographically weighted regression (GWR) models are used to account for spatially-varied thermal variations due to urban form changes. Our findings indicate that the large low-rise type (LCZ 8) needs more attention in built-up planning for thermal mitigation, and urban low plants type (LCZ D) should be a more effective nature-based climate mitigation strategy compared with the water bodies (LCZ G). The GWR results show a stronger consistency between UTCI and LCZ 8 and LCZ D, compared with WBGT and AT. UTCI is thus suggested for application in future urban climate studies. More importantly, the spatially-varied relationship between UTCI and urban form specifies the strategies and appropriate locations for thermal mitigation in climate-sensitive urban design.

Groundwater-dependent ecosystems (GDEs) exist all over the world, especially in water-limited regions. To achieve better water management, it is necessary to map and identify GDEs. Central Asia (CA) is one of the most arid regions in the mid-latitudes and one of the major regions with shallow groundwater tables. However, the role of groundwater in the impacts of climate change and regional anthropogenic activities on environmental risks, especially regional desertification, is inadequately understood due to the limited available research on GDEs. In the present study, a remote sensing-based method was used for mapping GDEs in regional CA, and three means¿overlay analysis, correlation analysis, and the water balance method¿were adopted to validate the accuracy of the mapping outcomes. Our results indicated that: 1) GDEs were concentrated around large lakes and in central Kazakhstan (between 46°N and 50°N latitudes), and areas "Very Likely" and "Likely" to be GDEs accounted for 36.89%, and 28.85% of the total natural vegetation areas, respectively; 2) at the watershed scale, the Sarysu Basin had the largest proportion (94.02% of the area) of potential GDEs while the Ysyk-Kol Basin had the lowest proportion (17.84%); 3) all the three validation methods indicated a good performance for our GDE mapping results. We concluded that the remote sensing-based GDE identification method can be considered a potential approach for mapping GDEs regionally. Better recognition of relationships among groundwater availability, ecosystem health and groundwater management policies should be developed by conducting further studies, to protect GDEs and to prevent regional land degradation.

Spatially-invariant land use and cover changes (LUCC) are not suitable for managing non-stationary drought conditions. Therefore, developing a spatially varying framework for managing land resources is necessary. In this study, the Dongjiang River Basin in South China is used to exemplify the significance of spatial heterogeneity in land planning optimization for mitigating drought risks. Using ERA5 that is the 5th major atmospheric reanalysis from the European Centre for Medium-Range Weather Forecast, we computed the Standardized Runoff Index (SRI) to quantify the hydrologic drought during 1992 to 2018. Also, based on Climate Change Initiative land use product, The Geographically Weighted Principal Component Analysis was used to identify the most dominant land types in the same period. Then, we used the Emerging Hot Spots Analysis to characterize the spatiotemporal evolution of historical LUCC and SRI. The spatially varying coefficients of Geographically and Temporally Weighted Regression models were used to reveal the empirical relationships between land types and the SRI. Results indicated that rainfed cropland with herbaceous cover, mosaic tress and shrub, shrubland, and grassland were four land types having statistical correlations with drought conditions over 27 years. Moreover, since 2003, the DRB was becoming drier, and the northern areas generally experienced severer hydrologic drought than the south. More importantly, we proposed region-specific land-use strategies for drought risk reductions. At a basin scale, we recommended to 1) increase rainfed herbaceous cropland and 2) reduce mosaic tree and shrub. At a sub-basin scale, the extents of shrub and grassland were suggested to increase in the northern DRB but to reduce in the south. Region-specific land use planning, including suitable locations, scales, and strategies, will contribute to handling current 'one-size-fits-all' LUCC. Planners are suggested to integrate spatial characteristics into future LUCC for regional hydrologic management.

This paper examines the relationship between land surface properties (e.g. soil, vegetation, and lithology) and landscape morphology quantified by the catchment descriptors: the slope-area (S-A) relation, curvature-area (C-A) relation, and the cumulative area distribution (CAD), in two semi-arid basins in central New Mexico. The first site is composed of several basins located in today's desert elevations with mesic north-facing and xeric south-facing hillslopes underlain by different lithological formations. The second site is a mountainous basin exhibiting vegetation gradients from shrublands in the lower elevations to grasslands and forests at higher elevations. All three land surface properties were found to have significant influences on the S-A and C- A relations, while the power-law exponents of the CADs for these properties did not show any significant deviations from the narrow range of universal scaling exponents reported in the literature. Among the three different surface properties we investigated, vegetation had the most profound impact on the catchment descriptors. In the S-A diagrams of the aspect-controlled ecosystems, we found steeper slopes in north-facing aspects than south-facing aspects for a given drainage area. In elevation-controlled ecosystems, forested landscapes exhibited the steepest slopes for the range of drainage areas examined, followed by shrublands and grasslands in all soil textures and lithologies. In the C-A diagrams, steeper slopes led to a higher degree of divergence on hillslopes and a higher degree of convergence in the valleys than shallower slopes. The influence of functional types of vegetation detected on observed topography provided some initial understanding of the potential impacts of life on the organization of topography. This finding also emphasizes the critical role of climate in catchment development. We suggest that climatic fluctuations that are capable of replacing vegetation communities could lead to highly amplified hydrological and geomorphic responses.

Afyon geothermal district heating system (AFJET) provides heating to 4519 residences, covering an area of 513,683 m2. Due to limitations in reinjection capacity, geothermal waters are released to the Akarcay Stream, detrimentally affecting the environment. Optimum heating load of the system was determined for a given ambient conditions with respect to different outdoor temperatures. Usage of AFJET was found to be higher than the optimum consumption rates. Optimizing the usage of geothermal water will decrease operational cost, increase equipment life-span, and reduce environmental pollution.

The urban heat island (UHI) is a result of urbanization, causing local microclimatologic changes such as increase in ambient temperature. Factors causing the UHI effect are anthropogenic energy release, energy absorption by concrete, tarmac structures and traffic, although the main factor is the replacement of vegetation with man-made structures. These factors cause heating of not only local air but also subsurface and groundwater. Observations of groundwater temperatures from the urban, southern part of Istanbul (Turkey) and the rural, northern part of Istanbul revealed that the urban groundwater temperatures were 3.5°C higher than the rural. Urbanization is a direct consequence of improvements in technology and modern life. However, this comes at the cost of an ever-increasing demand for energy. Exploitation of low-enthalpy geothermal energy is an attractive alternative to fossil fuel based energies. From the environmental point of view, clean and cheap energy is the most preferable, with heat pumps being the best choice for recovery purposes. Usage of elevated groundwater temperature in the heat pumps in urban areas increases the efficiency of the heat pump system and yields more thermal energy than that of rural groundwater. This system may be applicable to Istanbul. © Springer-Verlag 2009.

We investigate the influence of hillslope aspect on landscape morphology in central New Mexico, where differences in soils, vegetation, and landforms are observed between mesic north-facing and xeric south-facing slopes. Slope-area and curvature-area relations, derived from a Digital Elevation Model (DEM), are used to characterize the opposing hillslope morphologies. In all geologies and elevation ranges studied, topographic data reveal significantly steeper slopes in north-facing aspects, and shallower slopes in south-facing aspects. North-facing slope curvatures are also greater than south-facing curvatures. Using a conceptual slope-area model, we suggest that for a given drainage area, steeper north-facing slopes imply lower soil erodibility. We argue that this interpretation, consistent with recent views of ecosystem control on semiarid erosion rates, shows the influence hillslope aspect on topography and its associated vegetation communities. Observed valley asymmetry in the region reinforces this concept and suggests a long-term legacy of aspect-modulated ecogeomorphic proceses. Copyright 2008 by the American Geophysical Union.