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The establishment, development and abandonment and/or destruction of ancient civilizations were catalytically controlled by geomorphic features such as lakes and rivers and the climate. This paper examined the possible influence of tectonism and climate on six habitations of the ancient Vaigai River Basin civilization in South India, using multiple proxies such as grain size, geochronology and geochemistry of the sedimentary archives. The tectonic setting of the basin changed between the active margin and passive margin; the discriminant diagrams suggested varying provenance and changing climatic conditions over the mid‐ and‐late Holocene. Tectonic activism and quiescence, base‐level change in the channel morphology led to the burial/marooning of the first habitation surface. Overall, arid conditions were punctuated with catastrophic flooding and peak discharge (flood) destroyed the second, third and fourth habitation sites. These flooding events were characterized by moderate weathering (CIA) and high values of Al, Fe and Rb/Sr and low Ca/Mg in the sediment records. The abandonment/destruction of the fifth habitation also occurred during an arid interval (droughts), possibly caused by weak monsoon. Along with the interactions between tectono‐climatic and fluvial geomorphic factors, the new results provided avenues to (a) check and recognize the archives for 8.2 and 4.2 ka‐like events in this part of the world, and (b) the utility of integrated analyses to constrain on the civilizational histories of the mankind. [ABSTRACT FROM AUTHOR]

This paper presents a validation of outputs from some GCMs of the CMIP6 project when used to assess climate projection and hydrological flows at a catchment scale for the case study area of the Lombardy region (Northern Italy). The modeling chain consists of (i) a choice of climatic scenarios from 10 GCMs of the CMIP6, (ii) the application of a stochastic downscaling procedure to make projections usable at the local scale, and (iii) the use of a semi-distributed physically based hydrological model Poli-Hydro for the generation of hydrological scenarios. Data on observed precipitation and temperature were collected from automatic weather stations, and the hydrological budget of four target catchments within the study area was assessed using Poli-Hydro. An ex-post (back-casting) analysis was performed upon the control data series from the GCMs by comparing statistics of relevant climate variables and model-simulated discharges against observed counterparts during the historical period 2002–2014. Then, during 2015–2021, the goodness of projections was assessed using confidence intervals. Our results show that the accuracy of GCMs in representing regional climate is not always reflected in a credible evaluation of local hydrology. The validation of climate patterns provides somewhat poor results; thus, the interaction among climate and hydrology needs to be explored carefully to warrant the credibility of hydrological scenarios. Overall, the spatial and temporal consistency of GCM projections, as explored here climatically and hydrologically, provides a clue about their dependability for basin scale management. [ABSTRACT FROM AUTHOR]

Xinjiang, located in the arid region of the northwest, is one of the areas most sensitive to global changes. The Kaidu River Basin, situated in the heart of Xinjiang, is one of the sources of China's largest inland river—the Tarim River. The Kaidu River not only bears the responsibility for supplying water for industrial use and agricultural production and people's daily life in the basin, but also plays a crucial role in ecological water supply to the Tarim River. Studying and analyzing the characteristics and trends of meteorological condition in the future under climate change can provide important references and a basis for a deeper understanding of changes in the hydrological process and water resources in the basin. Therefore, this paper selects seven precipitation bias correction methods and four temperature bias correction methods to adjust the precipitation and temperature output data of eight general circulation models of the Sixth Coupled Model Intercomparison Project (CMIP6) within the Kaidu River Basin. The applicability of different bias correction methods in the study area is evaluated, and based on the corrected future meteorological data and calculated extreme meteorological index, the trends of meteorological data (precipitation, temperature) in the future period (2025–2050) under four SSP scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5) in the Kaidu River Basin are analyzed. The results show that: (1) Different types of bias correction methods have different correction focus and effects; their reflections on evaluation indicators are also different. (2) In the future period (2025–2050), the annual precipitation and average temperature in the Kaidu River Basin are higher than those in the historical period (1975–2014). The average annual temperature shows an upward trend in the future, but the annual precipitation shows a downward trend in the future except for the SSP2-4.5 scenario. (3) Compared with the historical period, the extreme precipitation in the future period under the SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios is higher than that in the historical period, and the number of rainless days decreases. In the future, under the SSP1-2.6 and SSP5-8.5 scenarios, the probability of meteorological drought events occurring due to high temperatures in the basin may further increase, while under the SSP2-4.5 scenario, the situation of high temperatures and heavy rain in the basin may continue to increase. [ABSTRACT FROM AUTHOR]

In recent years, global climate change causes more extreme precipitation events in Lancang-Mekong River Basin (Lancang-Mekong Basin). It leads to the increase of rainstorm and flood risk, which poses a threat to the flood control safety of Lancang-Mekong Basin. Based on the precipitation data of four global climate models of CMIP6, this paper selected six indexes, including PRCPTOT and R10, to study the change characteristics of the extreme precipitation indexes in the Lancang-Mekong Basin during 1980–2020 and predicted the development trend of the extreme precipitation indexes in the Lancang-Mekong Basin during 2021–2050. The results show that from 1980 to 2020, the extreme precipitation events in regions I and IV showed an increasing trend, while those in regions II and III showed a decreasing trend. From 2021 to 2050, the extreme precipitation events in all regions of the Lancang-Mekong River show an upward trend, and most indexes increased compared with the historical period. The extreme precipitation indexes in most regions increases the most under the scenario of SSP5-8.5, while the increase is small under the scenario of SSP2-4.5; The six extreme precipitation indexes selected in the paper can better reflect the trend of extreme precipitation events and floods. The trend of extreme precipitation indexes in the Lancang-Mekong River basin in the future is more significant, which indicates that it may be affected more frequently by extreme precipitation events and floods. [ABSTRACT FROM AUTHOR]

Henan Province is the birthplace of Chinese civilization and one of the earliest human settlements, which means that the area has an important national cultural heritage. Traditional villages are an important facet of this cultural heritage, and studying their spatiotemporal characteristics in different periods has important theoretical and practical significance for the sustainable development and protection of cultural heritage in the region. This paper takes the traditional villages of the Yellow River basin in Henan Province that were formed before 1919 as the research object. Information on the ancient river was obtained through a literature search as well as via field research, and the important tributaries of the Yellow River in different periods were mapped using ArcGIS 10.0 software. The nearest neighbor index, kernel density estimation, standard deviation ellipse and other methods were adopted to analyze the spatiotemporal characteristics of the traditional villages. The factors that influenced the evolution of traditional villages were explored in depth by combining changes in the course of the river and water conservancy projects. The results show that the formation of traditional villages along the Yellow River in Henan Province has experienced a historical track of growth, contraction, growth and prosperity and stability. The traditional villages along the Yellow River in Henan Province generally show a clustered pattern, forming a dense concentration of traditional villages in the middle reaches of the Yellow River. The center of gravity shows a migration trend from southeast to northwest. In terms of influencing factors, the spatiotemporal evolution of the relationship between villages and their distance to water is closely related to climatic fluctuations, changes in channel, water conservancy projects and social and cultural factors. This paper deepens our understanding of the relationship between traditional village evolution and watersheds by improving the consistency between village spatial distribution and historical geography and provides a useful theoretical reference for the sustainable development of China's traditional villages. [ABSTRACT FROM AUTHOR]

The Iberian Peninsula is a climate change hotspot, where the temperature is increasing faster than the global annual mean surface temperature, with the largest reduction of precipitation. Consequently, freshwater availability is expected to decrease substantially. In this context, freshwater systems are especially vulnerable in terms of meeting the water demands and ecosystem requirements we know today. In this paper, we present an extension of the eco-engineering decision scaling (EEDS) method to explore trade-offs in agricultural and ecologic metrics at the catchment scale across a range of unknown future hydrological and climate states. The extended EEDS method evaluates current water resource management rules focusing on agricultural and ecologic objectives, identifies climate hazards that make the system fail and assesses climate risk in three time horizons for the design of adaptation measures. The case study is the Serpis River basin, Spain, where 72% of available water is used for agricultural purposes. [ABSTRACT FROM AUTHOR]

Flood events have caused huge disasters with regard to human life and economic development, especially short-term flood events that have occurred in recent years. Gravity Recovery and Climate Experiment (GRACE) satellites can directly detect the spatiotemporal characteristics of terrestrial water storage anomalies (TWSA), which play an important role in capturing flood signals. However, the monthly resolution of GRACE-derived TWSA limits its application in monitoring sub-monthly flood events. Therefore, this paper first reconstructs the daily TWSA based on a statistical model with near real-time precipitation and temperature as input variables, and then three daily flood monitoring indexes are developed based on the reconstructed TWSA. Furthermore, these indexes are employed to evaluate the temporal and spatial characteristics of the 2016 short-term flood event in the Haihe River basin (HRB), including the flood potential index (FPI), water storage deficit index (WSDI), and combined climate deviation index (CCDI). In contrast to previous studies, the temporal resolution of TWSA-based indexes is improved from the monthly scale to the daily scale, which largely improves the temporal characterization of flood monitoring. Results demonstrate that (1) among ten kinds of "Temperature-Precipitation" combinations, the reconstructed TWSA based on CN05.1-CN05.1 match well with the GRACE TWSA, as well as publicly available daily TWSA datasets with a Nash-Sutcliffe efficiency coefficient (NSE) of 0.96 and 0.52 ~ 0.81 respectively. (2) The short-term flood characteristics can be better characterized by the reconstructed daily TWSA based on CN05.1-CN05.1, reaching the peak of 216.19 mm on July 20 in the flood center. Additionally, the spatial characteristics of the equivalent water height (EWH) are detected to evolve from southwest to northeast during the short-term flood. (3) FPI, WSDI, and CCDI are proven to be effective in monitoring flood events in the HRB, which validates the reliability of the reconstructed daily TWSA. Moreover, compared to the 56% and 66% coverage of damage quantified by FPI and CCDI, the 45% damage coverage of the flood mapped by WSDI is more consistent with the governmental reports within the HRB. This paper is expected to provide a valuable reference for the assessment of short-term events caused by extreme climate change. [ABSTRACT FROM AUTHOR]

Recent research has revealed that the dynamics of autumn phenology play a decisive role in the inter-annual changes in the carbon cycle. However, to date, the shifts in autumn phenology (EGS) and the elements that govern it have not garnered unanimous acknowledgment. This paper focuses on the Yellow River Basin (YRB) ecosystem and systematically analyzes the dynamic characteristics of EGS and its multiple controls across the entire region and biomes from 1982 to 2015 based on the long-term GIMMS NDVI3g dataset. The results demonstrated that a trend toward a significant delay in EGS (p < 0.05) was detected and this delay was consistently observed across all biomes. By using the geographical detector model, the association between EGS and several main driving factors was quantified. The spring phenology (SGS) had the largest explanatory power among the interannual variations of EGS across the YRB, followed by preseason temperature. For different vegetation types, SGS and preseason precipitation were the dominant driving factors for the EGS in woody plants and grasslands, respectively, whereas the explanatory power for each driving factor on cultivated land was very weak. Furthermore, the EGS was controlled by drought at different timescales and the dominant timescales were concentrated in 1–3 accumulated months. Grasslands were more significantly influenced by drought than woody plants at the biome level. These findings validate the significance of SGS on the EGS in the YRB as well as highlight that both drought and SGS should be considered in autumn fall phenology models for improving the prediction accuracy under future climate change scenarios. [ABSTRACT FROM AUTHOR]

Rainfall is considered a major input in designing stormwater management measures, especially for any low-impact development (LID) control design. With the impact of climate change, rainfall frequency and its patterns are changing continuously. Quantification of these changes and their impact on the performance of LID design becomes crucial. This paper presents a methodology to quantify the change in rainfall patterns using the Coupled Model Intercomparison Project 5 (CMIP5) climate model and to select the most feasible LID for a catchment with haphazard development. Interconnected decentralization-based LID controls are evaluated with the objective of emulating a pre-urbanized scenario. The overall analyses indicated that green roof (GR) followed by infiltration trenches (IT), rooftop disconnection (RTD), and permeable pavement (PP) showed better performance. Furthermore, a combination of IT, PP, and RTD accomplishes better efficiency for extreme rainfall events. Implementation of the most feasible combination will provide the additional benefit of water recycle and reuse. [ABSTRACT FROM AUTHOR]

This paper investigates how hydrological drought affected suspended sediment yield (SSY) in the Mediterranean Ofanto River basin, southern Italy, and in its five sub-basins from 1951 to 1989. The Standardized Precipitation Evaporation Index over a scale of 12 months (SPEI12) has been used to compute the hydrological drought in the investigated span of time. SPEI12, mean and maximum monthly discharge (Qmean and Qmax), monthly rainfall erosivity, monthly simple daily intensity index and monthly SSY were used to assess the relationships between dry/wet cycles, streamflow and SSY through the Pearson correlation matrix. Qmean and Qmax are significantly correlated with SSY, while SPEI12 and rainfall intensity do not show good correlation with SSY. Furthermore, from the overall analyses it emerges that sediment yield estimations were higher mainly during the wet period following a period of drought or during a drought period. [ABSTRACT FROM AUTHOR]

The subject of the research paper is the use of remote sensing in monitoring and analyzing the impact of climate change on the occurrence of extreme precipitation, and the causeand-effect occurrence of floods in the area of the Sana River Basin in Bosnia and Herzegovina. The goal is to process the "product" of remote sensing to identify the time intervals of occurrence of extreme precipitation, to assess their impact on water levels, and to map potential floods in space. Spatial identification of zones that are at risk of flooding is an integral part of the aforementioned goal. Precipitation monitoring was performed by processing Climate Hazards Group InfraRed Precipitation with Station Data through the Google Earth Engine platform. The observed 30-year period (1992-2022) was compared with the average precipitation for 2017, 2018 and 2019. The impact of extreme precipitation on the water level of the Sana River was analyzed. Flooding periods have been identified: February and December 2017, March 2018 and May 2019. Mapping of flooded areas was carried out by pre-processing and post-processing of Sentinel-1 radar satellite images. The total flooded area is: 710.38 ha (February 2017), 496.79 ha (December 2017), 417.86 ha (March 2018) and 422.42 ha (May 2019). Based on the identified flooded areas, a flood risk map was created on the main course of the Sana River. The research contributes to a better understanding of the changes that occur in the area under the influence of climate change, and the data presented are important for numerous practical issues in the field of water resource management and flood protection. [ABSTRACT FROM AUTHOR]

This review paper focuses on the question of what will happen to the future water resource system of Grand Renaissance Dam of Ethiopia based on the projected hydrology of the Upper Blue Nile River basin. For this, the hydrological extremes, the baseline hydrological trends, and projected hydrological extremes of the Upper Blue Nile River basin were reviewed from various published and unpublished sources. Changes in the future hydrology of the Upper Blue Nile River basin due to climate change or any other natural or manmade modification of the river basin deserve concerted attention in the future water resources system of the Grand Renaissance Dam of Ethiopia, because the water resources of the dam mainly depend on the water potential nature of the Upper Blue Nile River basin. [ABSTRACT FROM AUTHOR]

The Dongting Lake Basin is an important hydrological regulation and flood storage area in the Yangtze River Basin, which plays an important role in maintaining regional ecological security. The watershed vegetation and its carbon sequestration capacity have changed dramatically due to climate change and human activities in the last two decades. In this paper, the monthly and annual vegetation net primary productivity (NPP) of the Dongting Lake basin during 2000 to 2020 was firstly estimated using the improved Carnegie-Ames-Stanford Approach (CASA) model. Then the multi-year NPP change trend and its significance were analyzed based on Theil-Sen median and Mann-Kendall method. Subsequently, the Hurst index was used to simulate the vegetation NPP persistence in the study area. Finally, the driving mechanisms of vegetation NPP changes in the study area were explored using partial correlation coefficients and residual analysis. The results demonstrated that: 1) The annual average NPP in the basin showed a fluctuating and increasing trend from 273.54 to 718.30 g C/m2·yr1 during 2000 to 2020, and except for autumn, all seasons (spring, summer, winter) and annual NPP series showed an upward trend. The spatial distribution of vegetation NPP is characterized by an asymmetrical horseshoe shape in general, with high values in the west, south and east parts, and low values in the Lake area; 2) During the study years, about 84.38 % of the basin area showed a significant and extremely significant increase of NPP; 3) The future trend of vegetation NPP in the basin shows that the area of decrease (22.79 %) is more than the area of increase (11.35 %). The Chang-Zhu-Tan urban agglomeration will generally show a continuous and extremely significant reduction trend, while parts of Dongting Lake will show a continuous and extremely significant increase trend; 4) The correlation between solar radiation and NPP is stronger than the other two meteorological factors (precipitation and temperature). Temperature has a significant inhibitory effect on NPP, solar radiation has a significant promoting effect on NPP, and the effect of precipitation on NPP was relatively complicated. The relative importance of meteorological factors on vegetation NPP was ranked as follows: solar radiation > precipitation > temperature. The impacts of both climate change and human activities on NPP changes showed great spatial variability, and the positive contributions (89.81 % for climate change and 82.87 % for human activities) were both greater than the negative contributions. [ABSTRACT FROM AUTHOR]

This paper focused on regional climate change impacts on hydro-meteorological variables in the Upper Chao Phraya River basin located in northern Thailand. The five global climate models were used with a number of 15 experiments to assess near future water resources over the period 2026-2040. The impacts of climate change were quantified in percentages relative to a retrospective period (1986- 2000). On average, the surface temperature tends to increase by 1.45, 1.48, and 1.80 °C under the lowest (RCP2.6), intermediate (RCP4.5), and highest (RCP8.5) CMIP5 greenhouse gas emission scenarios, respectively. Mathematical model called H08 was used, the coupling of three modules did a very good job on mimicking river discharge with high Nash-Sutcliffe and Index of Agreement. The projections of rainfall and its response to surface runoff and groundwater recharge exhibit relatively uneven distributions. The upper basin tends to face extremely heavy rainfall and taking place of serious flood, while the lower areas are expected to cope with drought. Based upon ensemble averages over the entire area, relative changes of -1.7% (-6.4%), -0.1% (-5.2%), and -2.0% (-9.3%) in the mean annual rainfall (groundwater recharge) are shown under the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively. This study included a groundwater recharge assessment indicating potential available groundwater use, which is considered to be a key resource for climate change adaptation. Based on these findings, implementing such an artificial groundwater recharge system is needed in order to harvest surplus water and making for coping with water stress in the dry season. [ABSTRACT FROM AUTHOR]

High Mountain Asia (HMA), with its high altitude, widely distributed snow and frozen soil, influences the climate of the northern hemisphere and even the world through thermal balance and the water vapor cycle and is also an indicator of global climate change. The influence of HMA snow cover on its surrounding areas has always been a research hotspot. Taking the Yangtze River Basin (YRB) of China as an example, this paper analyzes the relationship between winter snow depth in HMA and drought and flood in spring and summer in the YRB in the recent 40 years by using Singular Value Decomposition (SVD). The results show that the influence of snow cover on drought and flood in spring is inversely different between eastern and western parts of HMA, while the effect in summer is consistent. When the snow depth is larger (smaller) in the east and smaller (larger) in the west in winter, the YRB is drier (wetter) in spring. When the overall snow depth in HMA is larger (smaller) in winter, the northern part of the middle and lower reaches of the YRB is drier (wetter) in summer. The results provide support for understanding the impact of HMA snow cover on the surrounding climate and some important indicators for drought and flood prediction in the YRB. [ABSTRACT FROM AUTHOR]

The Mara River Basin of Africa has a world-famous ecosystem with vast vegetation, which is home to many wild animals. However, the basin is experiencing vegetation degradation and bad climate change, which has caused conflicts between people and wild animals, especially in dry seasons. This paper studied the vegetation greenness (VG), vegetation greenness trends (VGT), and their responses to climate change in dry seasons in the Mara River Basin, Africa. Firstly, based on Google Earth Engine (GEE) platform and Sentinel-2 images, the vegetation distribution map of the Mara River Basin was drawn. Then dry seasons MODIS NDVI data (January to February and June to September) were used to analyze the VGT. Finally, a random forest regression algorithm was used to evaluate the response of VG and VGT to temperature and precipitation derived from ERA5 from 2000 to 2019 at a resolution of 250 m. The results showed that the VGT was fluctuating in dry seasons, and the spatial differentiation was obvious. The greenness increasing trends both upstream and downstream were significantly larger than that of in the midstream. The responses of VG to precipitation were almost twice larger than temperature, and the responses of VGT to temperature were about 1.5 times larger than precipitation. The climate change trend of rising temperature and falling precipitation will lead to the degradation of vegetation and the reduction of crop production. There will be a vegetation degradation crisis in dry seasons in the Mara River Basin in the future. Identifying the spatiotemporal changes of VGT in dry seasons will be helpful to understand the response of VG and VGT to climate change and could also provide technical support to cope with climate-change-related issues for the basin. [ABSTRACT FROM AUTHOR]

Research on precipitation regularity in the past 120 years is an important link in analyzing the precipitation characteristics of watersheds. This paper systematically analyzes the characteristic changes of centennial precipitation data in the Haihe River basin with the help of CRU data, PCI, SPI, and the Pearson type III curve. The results show that the spatial and temporal distribution of precipitation in the Haihe River basin has a more obvious inconsistency. The temporal distribution shows the characteristics of relatively stable in the early period and increasing fluctuation in the later period, the concentration of precipitation gradually decreases, and the overall drought level decreases. The spatial distribution shows a general pattern of gradually decreasing from southwest to northeast, the overall trend of summer precipitation changes from stable to north–south extremes, and the distribution probability of extreme precipitation events in the basin decreases from southeast to northwest, while the drought-prone area transitions from the northeast to the west and southwest of the basin. Under the influence of both climate change and human activities, the seasonal distribution of precipitation tends to be average, the area affected by extreme precipitation rises, and the arid area shifts to the inland area. [ABSTRACT FROM AUTHOR]

Arid area is very sensitive to global warming and are extremely vulnerable to climate change. Moreover, the water resources system in the arid area is fragile and will undergo tremendous changes with climate change. Therefore, the interaction of climate and hydrology in arid area has an important impact on the formation of regional microclimate and hydrological changes. Daihai Lake is a typical closed inland lake in arid area of China, and a key area for ecological protection in North China. In this paper, WRF-Hydro model is used to simulate the climate hydrological coupling situation of Daihai Basin from 1980 to 2020, and the coupling results are verified and calibrated by meteorological statistics, runoff calculation and remote sensing analysis. Based on the synopsis of climate and hydrology in the past 40 years, the causes and future trends of the hydrological elements in Daihai Basin are analyzed. Through the analysis, it is found that the interannual variation of precipitation in Daihai Basin is sharp, with 401.75 mm as the average from 1980 to 1994; and drastic fluctuations from 1995 to 2011, with a difference of nearly 400 mm between the interannual maximum and minimum; From 2012 to 2020, the fluctuation is small. Although the interannual variation of evaporation fluctuated, it showed an upward trend with a slope of 8.855 mm/year. The annual average temperature showed an obvious upward trend with a slope of 0.040 °C/year. From 1980 to 2020, the inflow of Daihai Lake shows a downward trend; Since 2013, the runoff into the lake has tended to be flat. Climate change and human activities are the decisive factors leading to the change of water quantity in Daihai, among which human activities play a greater role. Cultivated land irrigation and industrial water use are highly correlated with the lake discharge, and these two factors have a great influence on the lake discharge. If the current agricultural and industrial water consumption does not increase, Daihai still has a lifespan of nearly 120 years. If human activities do not change and any protective measures are not taken in time, under the background of global climate change, the flow of the Daihai Lake into the lake will be reduced to zero in 2025, and the Daihai Lake will completely dry up in 2031–2033. The study of climate hydrological coupling of long time series in Daihai Basin can not only make up for the lack of runoff data, but also provide the basis for water resources management, disaster prevention and mitigation. [ABSTRACT FROM AUTHOR]

Arid area is very sensitive to global warming and are extremely vulnerable to climate change. Moreover, the water resources system in the arid area is fragile and will undergo tremendous changes with climate change. Therefore, the interaction of climate and hydrology in arid area has an important impact on the formation of regional microclimate and hydrological changes. Daihai Lake is a typical closed inland lake in arid area of China, and a key area for ecological protection in North China. In this paper, WRF-Hydro model is used to simulate the climate hydrological coupling situation of Daihai Basin from 1980 to 2020, and the coupling results are verified and calibrated by meteorological statistics, runoff calculation and remote sensing analysis. Based on the synopsis of climate and hydrology in the past 40 years, the causes and future trends of the hydrological elements in Daihai Basin are analyzed. Through the analysis, it is found that the interannual variation of precipitation in Daihai Basin is sharp, with 401.75 mm as the average from 1980 to 1994; and drastic fluctuations from 1995 to 2011, with a difference of nearly 400 mm between the interannual maximum and minimum; From 2012 to 2020, the fluctuation is small. Although the interannual variation of evaporation fluctuated, it showed an upward trend with a slope of 8.855 mm/year. The annual average temperature showed an obvious upward trend with a slope of 0.040 °C/year. From 1980 to 2020, the inflow of Daihai Lake shows a downward trend; Since 2013, the runoff into the lake has tended to be flat. Climate change and human activities are the decisive factors leading to the change of water quantity in Daihai, among which human activities play a greater role. Cultivated land irrigation and industrial water use are highly correlated with the lake discharge, and these two factors have a great influence on the lake discharge. If the current agricultural and industrial water consumption does not increase, Daihai still has a lifespan of nearly 120 years. If human activities do not change and any protective measures are not taken in time, under the background of global climate change, the flow of the Daihai Lake into the lake will be reduced to zero in 2025, and the Daihai Lake will completely dry up in 2031–2033. The study of climate hydrological coupling of long time series in Daihai Basin can not only make up for the lack of runoff data, but also provide the basis for water resources management, disaster prevention and mitigation. [ABSTRACT FROM AUTHOR]

Vegetation is a key indicator of the health of most terrestrial ecosystems and different types of vegetation exhibit different sensitivity to climate change. The Yarlung Zangbo River Basin (YZRB) is one of the highest basins in the world and has a wide variety of vegetation types because of its complex topographic and climatic conditions. In this paper, the sensitivity to climate change for different vegetation types, as reflected by the Normalized Difference Vegetation Index (NDVI), was assessed in the YZRB. Three machine learning models, including multiple linear regression, support vector machine, and random forest, were adopted to simulate the response of each vegetation type to climatic variables. We selected random forest, which showed the highest performance in both the calibration and validation periods, to assess the sensitivity of the NDVI to temperature and precipitation changes on an annual and monthly scale using hypothetical climatic scenarios. The results indicated there were positive responses of the NDVI to temperature and precipitation changes, and the NDVI was more sensitive to temperature than to precipitation on an annual scale. The NDVI was predicted to increase by 1.60–4.68% when the temperature increased by 1.5 °C, while it only changed by 0.06–0.24% when the precipitation increased by 10% in the YZRB. Monthly, the vegetation was more sensitive to temperature changes in spring and summer. Spatially, the vegetation was more sensitive to temperature increases in the upper and middle reaches, where the existing temperatures were cooler. The time-lag effects of climate were also analyzed in detail. For both temperature and precipitation, Needleleaf Forest and Broadleaf Forest had longer time lags than those of other vegetation types. These findings are useful for understanding the eco-hydrological processes of the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

The Yangtze River Basin (YRB), a key biodiversity area and a major economic zone in China, the biodiversity of the area is confronted with severe challenges. In this paper, we analyzed species distribution patterns based on a dataset with 18,538 seed plant species to identify hotspots and evaluate conservation effectiveness and gaps of the YRB. We calculated distribution patterns of species richness with the top 5% richness algorithm and complementarity algorithm, and reconstructed a phylogenetic tree and elucidated spatial phylogenetics. There were 214 hotspot grid cells covering only 6.8% of the study region, but containing 88% seed plant species. Then, we conducted correlation analysis on distribution patterns of different algorithms and species categories, which showed moderate or weak correlations between the top 5% richness algorithm and complementary algorithm. Conservation effectiveness analysis indicated there were 116 hotspot grid cells (accounting for 73.6% of the total species) protected by current conservation networks and there are many conservation gaps remaining. Finally, we used the maximum entropy model (MaxEnt) to predict suitable habitat areas of threatened species under current and future climate scenarios. Prediction analysis results indicated future expansion of suitable habitat to the southeast, and reduction in the central and western portions of the study area. When we considered anthropogenic areas, the suitable habitat was severely decreased, indicating the importance of optimizing the layout of conservation networks and comprehensive biodiversity conservation planning in the YRB. [ABSTRACT FROM AUTHOR]

Frequent drought disasters have significant impacts on socio-economic and ecosystems, and it is crucial to explore the propagation characteristics of drought for disaster prevention and mitigation. In this paper, based on 0.25° × 0.25° grid-point Meteorological hydrological and large-scale climate factor data, the start-to-start, peak-to-peak, and end-to-end drought propagation times, and the periods and rates of drought development and recovery were estimated for 11 regions in the Luanhe River Basin under stationary and non-stationary conditions. The Generalized Additive Model for Location, Scale and Shape (GAMLSS) framework was used to construct stationary and non-stationary models to capture the stationary and non-stationary drought characteristics respectively, and then the drought development and recovery patterns, and drought propagation times were assessed. The results showed that under the influence of climate factors, severe drought events occurred in most study areas, the duration of meteorological drought was prolonged by 0.1–0.6 months, and the peak intensity was increased by about 0.05. The severity of hydrological drought increased by 0.2–0.8, and the peak intensity decreased by 0.1–0.2. The rate of development and recovery of hydrological drought was accelerated by 0.1–0.2 per month. The propagation time of start-to-start was shortened by 0.2 months, and the propagation time of end-to-end was extended by 1–2 months. These mean that water resource control authorities need to propose responses to droughts more quickly. • The non-stationary drought indices considering climatic factors were constructed. • The drought propagation time was calculated from start to start, peak to peak, and end to end. • Quantification of the effects of climate change on drought propagation [ABSTRACT FROM AUTHOR]

Climate change led an increase in the frequency of severe droughts, the effects of which are exacerbated by a lack of water storage. Despite increasing research on global-scale total water storage (TWS) change and drought prediction, basin-scale long-term hydrological drought, TWS change, and El Nino–Southern Oscillation (ENSO) influence in East Africa (EA) remain unexplored. In this paper, we used multiple approaches, of ensemble machine learning (ML) and weighted averaging, to conduct a basin-scale exploratory analysis of future hydrological drought and TWS change for the period 2025–2099. Climate change will affect future hydrological conditions in the basins, with maximum severity values of −90.3, −726.6, and −2567.7 Gt in the Tana, Turkana, and Victoria basins, respectively, under RCP6.0. Similarly, we found maximum severities of −187.5 and −277.7 Gt in the Abaya-Chamo and Tanganyika basins, respectively, under RCP 2.6. The most severe El Nino drought and exceptional La Nina conditions in the basins were found under both RCP scenarios. To ensure future water security in EA, sustainable water resource management strategies that can mitigate the impacts of extreme climate events in the future are urgently needed. [ABSTRACT FROM AUTHOR]

Climate change has intensified the effects of habitat fragmentation in many ecosystems, particularly exacerbated in riparian habitats. Therefore, there is an urgent need to identify keystone connectivity spots to ensure long-term conservation and sustainable management of riparian systems as they play a crucial role for landscape connectivity. This paper aims to identify critical areas for connectivity under two contrasting climate change scenarios (RCP 4.5 and RCP 8.5 models) for the years 2030, 2050 and 2100 and to group these critical areas by similar connectivity in keystone spots for sustainable management. A set of analyses comprising climate analysis, drainage network analysis, configuration of potential riparian habitats, riparian habitat connectivity, data clustering, and statistical analysis within a Spanish river basin (NW Spain) were applied. The node and link connectivity would be reduced under the two climate change scenarios (≈2.5 % and 4.4 % reduction, respectively), intensifying riparian habitat fragmentation. Furthermore, 51 different clusters (critical areas) were obtained and classified in five classes (keystone spots) with similar connectivity across the different scenarios of climate change. Each keystone spot obtained by hierarchical classification was associated with one or more climate scenarios. One of these keystone spots was especially susceptible to the worst climate change scenario. Key riparian connectivity spots will be crucial for the management and restoration of highly threatened riparian systems and to ensure long-term biodiversity conservation. • Connectivity importance was reduced under different climate change scenarios. • Critical area detection for connectivity conservation is threatened by climate change. • Critical areas were classified with similar connectivity keystone spots against climate change. • Keystone spots with high PC index will be priority for conservation management. [ABSTRACT FROM AUTHOR]

The paper presents an assessment of the rates of erosion and sedimentation in hollows of the Temeva Rechka small dry valley catchment, dominated by forest-steppe gray forest soils (Luvic Retic Greyzemic Phaeozems), over the past 55–60 years with the use of the radiocesium technique. This catchment is located in the Myosha River basin (Republic of Tatarstan, European Russia). The hollows have been grouped by the catchment's slope aspects, hollow length, hollow bottom gradient, and shape of the thalweg profile of the hollow bottoms; origin and age, as well as by the specifics of erosion/sedimentation processes. Short agrogenic hollows with a small catchment area on relatively steep western slopes of the Temeva Rechka small dry valley, probably formed after human deforestation, have been identified. The shape of their catchments contributes to the formation of surface runoff, sufficient for the erosion of a significant part of their bottoms at a rate of about 2–4 t/ha per year. Older, polygenetic, and relatively long hollows with a slightly sloping bottom and larger catchments serve as sediment transit zones between plowed areas and the Temeva Rechka small dry valley bottom. They are characterized by alternating areas of soil erosion and sediment accumulation. The average rate of soil erosion in these landforms is 0.8 t/ha per year. In some hollows, when several small tributaries (smaller hollows) flow into their lower parts, soil erosion loss increases to 3 t/ha per year. The average soil erosion loss is 6 t/ha per year on short slopes of the hollows; in their upper parts, it can reach 11 t/ha per year. There is a general decrease in the rates of soil erosion and accumulation of eroded material in recent decades due to changes in climate and land use. [ABSTRACT FROM AUTHOR]

Due to a changing climate, likely changes to a hydrological regime are one of the primary sources of uncertainty to consider in managing water resources. In Slovakia, a decline in the country's water resources, combined with a change in the seasonality of runoff and an increase in the extremeness of floods and droughts, represents a potential threat. The objective of the paper was to explore trends in the components of the long-term hydrological balance of various river basins to detect the impacts of changing climate conditions along the Western Carpathians. The proposed method is a comparative exploratory analysis of the hydrological balance of the selected river basins. Temporal changes in the catchments' average air temperatures, precipitation, runoff, and their differences (considered as an index of the actual evapotranspiration), were estimated for 49 years of data; two non-overlapping sub-periods (25 and 24 years) in the seven river basins were also compared. This work also aims at evaluating the applicability of gridded inputs from the CarpatClim database for modelling the hydrological balance over an extended period. The results document the impact of the rising air temperature and, in part, local physiographic factors on the changes in runoff and actual catchment evapotranspiration. [ABSTRACT FROM AUTHOR]

This paper presents the first study to identity, in historical records, regional changes in the mechanisms of extreme water available for runoff (W). We used a quality‐controlled Snowpack Telemetry data set (1979–2017) combined with the nonparametric regional Kendall test to examine changes in annual maximum W under four hydrometeorological conditions (melt only/rain‐on‐snow/all melt/all melt plus rainfall) over the mountainous regions of the western United States. Under a warming climate, our analyses indicated significant declining trends in annual maximum W at regional scale under all four conditions. The annual maximum of all melt plus rainfall decreased significantly by 15% in the southwestern United States, while the frequency of rain‐on‐snow events increased significantly by 32% in the northwestern United States. The annual maximum snowmelt only decreased significantly by 21% across the entire western United States. Our results confirmed that interaction between regional humidity and solar radiation with warming temperature helps drive these changes. Plain Language Summary: In the western United States, mountain snowmelt generates about 50% of the region's streamflow and plays a critical role in sustaining water resources. It is important to understand how snowpack are changing under warming, as risks related to these changes involve trillions of dollars. This paper presents the first study to identify, in historical records, large‐scale changes in the mechanisms of extreme water available for runoff (W). We used a regional trend analysis to examine spatiotemporal changes in rain‐on‐snow (ROS) frequency and the mechanisms of extreme W from 1979 to 2017, based on our newly developed quality‐controlled observed snow and precipitation data set. We found that, under a significant warming trend, annual maximum W from snowmelt only (not including ROS) has been decreasing by 21% across the western United States. The northwestern United States showed significant increasing trends in ROS frequency by 32%, but the rate of annual maximum ROS showed nonsignificant trends (i.e., more frequent but similar in magnitude). The annual maximum W from all conditions (melt plus rain) has been decreasing significantly by 15% in the southwestern United States. Decreasing trends in the mechanisms of extreme W may have significant ramifications for water management relative to flood risk and public safety. Key Points: Annual maximum snowmelt (not including rain‐on‐snow) decreased significantly by 21% averaged across the snowy regions of the western United StatesThe frequency of rain‐on‐snow events increased significantly by 32% averaged in the higher humidity snowy regions of the northwestern United StatesAnnual maximum water available for runoff (melt + rain) decreased significantly by 15% in the snowy regions of the southwestern United States [ABSTRACT FROM AUTHOR]

• The impact of precipitation, slope, and swamp wetland ratio on water yield is not affected by spatial scale and watershed. • Identifying key areas for ecosystem services combined with multiple scenarios can help to take ecological restoration. • The water yield in the Baihe basin is more sensitive on climate change, while the water yield in the Heihe basin is more easily affected by land use changes. • The economic development and ecosystem services can both be ensured by wetland ecological restoration. Water supply is one of the core ecosystem services functions for wetland. Due to the important status of Zoige wetland, assessment of water supply in Zoige wetland is significant for ecological security all over the world. In this paper, Heihe and Baihe basins in Zoige wetland were taken as research objects, the water yield module of the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model was used to spatially quantify water supply, with the aims of revealing the driving mechanism of water supply under different basins and spatial scale. We observed the spatial pattern change of water yield under baseline and eleven future scenarios and used the ANOVA of repeated measures and multiple linear regression model to explore the patterns and driving factors of water supply in Heihe and Baihe rivers basins. The research results were as follow. (1) The precipitation is main factor to improve water yield, but this intensity is different in different basins and spatial scale. Topography, climate, vegetation, and percentage of wetland conditions have important impacts on water yield services. However, the impacts of these conditions on water yield were various significantly across different watersheds and spatial scales (excluding factors such as precipitation, slope, and percentage of swamp wetland). (2) The spatial pattern of water yield main was affected by land use change and the amount of water yield main was affected by future climate change. (3) Water yield in the Baihe basin was more sensitive to climate change, while the Heihe basin is more sensitive to land use changes. Wetland ecological restoration strategies can effectively improve regional water yield, especially in the Heihe basin. (4) In all scenarios, the southeast regions of the study region were both the main hot spots of water yield. Wetland ecological restoration strategies have added hot spots in the north regions of the Baihe river basin, reduced hot spots in the middle-south regions of the Heihe basin. [ABSTRACT FROM AUTHOR]

[Display omitted] • We develop a framework to estimate future Flood Regulation Service (FRS) dynamics. • The framework considers the joint impacts of both climate change and urbanization. • Future FRS supply–demand imbalance will continue to intensify. • Future impacts of climate change in Baiyangdian Lake Basin cannot be ignored. • Cities should actively adapt to climate change to reduce flood risks in the future. Estimating the supply–demand relationship's future dynamics and trend of Flood Regulation Service (FRS) is important for preventing flood risks and choose an appropriate future development path. Less attention has been given to assessing the future trends in this relationship under the joint influence of climate change and urbanization. This paper aims to quantify future trends in the FRS supply–demand relationship under the joint impacts of climate change and urbanization. To this end, we took the Baiyangdian Lake Basin as an example and developed a "Climate Change-Urbanization-FRS supply and demand" framework by combining future climate scenarios from the ScenarioMIP (Scenario Model Intercomparison Project) dataset and socioeconomic data from the SSPs (Shared Socioeconomic Pathways) to estimate the FRS supply and demand dynamics during the period from 2020 to 2050. The results show that the framework has a reasonable ability to estimate the FRS supply–demand relationship. The correlation coefficients between estimated supply–demand ratios and the historical values exceeded 0.9. The average FRS supply–demand ratio among the four scenarios shows a significantly downward trend between 2020 and 2050. The FRS is expected to decrease by 0.159 (36.6 %), resulting in the imbalanced area increasing from 38.3 km2 (4.1 % of the whole basin) to 11049.7 km2 (36.2 %). We believe that although urbanization is the dominant factor contributing to the intensified imbalance trend (with a contribution of 71.2 %), influences from climate change also cannot be ignored (with a contribution of 28.8 %). Therefore, adaptation actions to climate change should be actively taken to reduce urban flood risks in the future. [ABSTRACT FROM AUTHOR]

The Términos Lagoon is a 2000-km 2 wide coastal lagoon linked to the largest river catchment in Mesoamerica. Economic development, together with its ecological importance, led the Mexican government to pronounce the Términos Lagoon and its surrounding wetlands as a Federal protected area for flora and fauna in 1994. It is characterized by small temperature fluctuations, but with two distinct seasons (wet and dry) that control the biological, geochemical, and physical processes and components. This paper presents a review of the available information about the Términos Lagoon. The review shows that the diversity of benthic communities is structured by the balance between marine and riverine inputs and that this structuration strongly influences the benthic metabolism and its coupling with the biogeochemistry of the water column. The paper also presents many specific drivers and recommendations for a long-term environmental survey strategy in the context of the expected Global Change in the Central American region. [ABSTRACT FROM AUTHOR]

Characterizing the response of temperature variables to agricultural irrigation is expected to be an important challenge for understanding the full impact of water management on regional climate change. In this paper, the trend analysis and abrupt change test were applied to detect the global warming effect. Then, the quantitative irrigation-induced cooling effects on temperature variables between April and August from 1970 to 2010 in the Lhasa River basin were estimated using historical time series of gridded meteorological records and a map of the area equipped for irrigation. Trends in the maximum temperature (Tmax) were statistically positive, and a significant increasing trend for the minimum temperature (Tmin) was detected at the 0.01 and 0.05 confidence levels. No abrupt changing point of warming was detected in the time series for Tmax. The abrupt changes in Tmin in the irrigation concentration period took place in 1995, 5 years later than the corresponding change in April. Affected by global warming, the increase in temperature was the largest in July and August, when the irrigation-induced cooling effect was also the most significant. The irrigation-induced cooling effect for Tmax and Tmin in April–August (except for June) ranged from − 0.017 to − 0.009 °C/decade and from − 0.011 to − 0.001 °C/decade, respectively, and the cooling effect for diurnal temperature range (DTR) ranged from − 0.011 to 0 °C/decade. The cooling effect on temperature reached above 0.01 °C in July and August, but for the growing seasons, the effect was weak, only 0.001 °C. The Tmax and Tmin trends during the whole growing seasons decreased by both 0.002 °C/decade, respectively, with a 10% increase in irrigation land proportion. Even in July and August, the trends were expected to decrease by about 0.005 °C/decade with a 10% increase in irrigation land proportion. The irrigation-induced cooling effect could partially slow global warming. [ABSTRACT FROM AUTHOR]

Cold region hydrology is very sensitive to the impacts of climate warming. Impacts of warming over recent decades in western Canada include glacier retreat, permafrost thaw, and changing patterns of precipitation, with an increased proportion of winter precipitation falling as rainfall and shorter durations of snow cover, as well as consequent changes in flow regimes. Future warming is expected to continue along these lines. Physically realistic and sophisticated hydrological models driven by reliable climate forcing can provide the capability to assess hydrological responses to climate change. However, the provision of reliable forcing data remains problematic, particularly in data-sparse regions. Hydrological processes in cold regions involve complex phase changes and so are very sensitive to small biases in the driving meteorology, particularly in temperature and precipitation, including precipitation phase. Cold regions often have sparse surface observations, particularly at high elevations that generate a large amount of runoff. This paper aims to provide an improved set of forcing data for large-scale hydrological models for climate change impact assessment. The best available gridded data in Canada are from the high-resolution forecasts of the Global Environmental Multiscale (GEM) atmospheric model and outputs of the Canadian Precipitation Analysis (CaPA), but these datasets have a short historical record. The EU WATCH ERA-Interim reanalysis (WFDEI) has a longer historical record but has often been found to be biased relative to observations over Canada. The aim of this study, therefore, is to blend the strengths of both datasets (GEM-CaPA and WFDEI) to produce a less-biased long-record product (WFDEI-GEM-CaPA) for hydrological modelling and climate change impact assessment over the Mackenzie River Basin. First, a multivariate generalization of the quantile mapping technique was implemented to bias-correct WFDEI against GEM-CaPA at 3 h ×0.125∘ resolution during the 2005–2016 overlap period, followed by a hindcast of WFDEI-GEM-CaPA from 1979. The derived WFDEI-GEM-CaPA data are validated against station observations as a preliminary step to assess their added value. This product is then used to bias-correct climate projections from the Canadian Centre for Climate Modelling and Analysis Canadian Regional Climate Model (CanRCM4) between 1950 and 2100 under RCP8.5, and an analysis of the datasets shows that the biases in the original WFDEI product have been removed and the climate change signals in CanRCM4 are preserved. The resulting bias-corrected datasets are a consistent set of historical and climate projection data suitable for large-scale modelling and future climate scenario analysis. The final historical product (WFDEI-GEM-CaPA, 1979–2016) is freely available at the Federated Research Data Repository at 10.20383/101.0111 (Asong et al., 2018), while the original and corrected CanRCM4 data are available at 10.20383/101.0162 (Asong et al., 2019). [ABSTRACT FROM AUTHOR]

In the New Zealand landscape, the mahika kai sites (resource gathering areas) are marked through place names, which act as central reference points (whai take) for a wider ecosystem catchment area and indicate changes over time. The traditional ecological knowledge, awakened through place names, informs and influences the way Māori realise cultural, social, environmental, and economic aspirations and practices (past and present). This paper will draw from a research project in Te Wai Pounamu (South Island), New Zealand that utilises traditional ecological knowledge (TEK) surrounding the place name, Matainaka, which indicate places where Kāi Tahu (South Island Māori tribal group) gathered whitebait (īnaka, Galaxias maculatus): an important fresh water species. A major focus of the research project is the knowledge around socio-cultural tipping points that will impact directly on the future cultural, social and economic sustainability within a specific catchment location, the Waikōuaiti River. The river has spawning and fishing sites for the īnaka mahika kai and comes under the mana whenua (recognised traditional authority) of the Māori tribal group, Kāti Huirapa Rūnaka ki Puketeraki. Traditional ecological knowledge kōrero (speech) explains the importance of Matainaka and its contribution to the surrounding catchment area, and - in contemporary times - works alongside that of scientific knowledge. The project merged TEK and science to find ways to improve future planning and adaptation for habitat restoration and modification, and to lessen impacts on īnaka spawning sites from the expected impacts of climate change. [ABSTRACT FROM AUTHOR]

The time at which climate change signal can be clearly distinguished from noise is known as time of emergence (ToE) and is typically detected by a general circulation model (GCM) signal-to-noise ratio exceeding a certain threshold. ToE is commonly estimated at large scales from GCMs, although management decisions and adaptation strategies are implemented locally. This paper proposes a methodology to estimate ToE for both precipitation and temperature at local scales (i.e., river basin). The methodology considers local climatic conditions and unbiased GCM projections to estimate ToE by using the statistical power to find when the climate significantly differs from the historical one. The method suggests that ToE for temperature already occurred in three Chilean basins (Limarí, Maipo, and Maule). However, in terms of precipitation, an earlier ToE is clearly identified for the Maule basin, indicating that risk assessment and adaptation measures should be implemented first in this basin. [ABSTRACT FROM AUTHOR]

• A single year was divided into three different seasons. • The impact of human activities and climate change on runoff were quantified. • The main factors of runoff changes caused by human activities were analyzed. The Yongding River has ceased to flow due to the impact of human activities and climate change, inducing environmental degradation. Analyzing the driving factors is vital for environmental restoration and water resources allocation, but it is challenging especially at seasonal scale. In this paper, the monthly abcd model was constructed for the Yongding River basin and two sub-basins, namely Yanghe and Sangganhe, to quantify the relative contribution of climate change and human activities to runoff decrease. The results show that the annual runoff in the basin has been declining significantly since the 1980s, up to 30 mm/year. Human activities are the main influencing factors, with 108% contribution in the entire Yongding River basin, 122% and 98% in Yanghe and Sanggan sub-basins, respectively. The impact of human activities on runoff varies in different seasons, which is highest in the wet season, followed by irrigation season and dry season. The impact of human activities is more pronounced in July-September due to water withdrawal for irrigation and operation rules of reservoirs, which is twice as much as that in April-June. A stricter management system can alleviate the impact of human activities on runoff change. [ABSTRACT FROM AUTHOR]

The objective of this paper is to understand how the natural dynamics of a time-varying catchment, i.e. the rainfall pattern, transforms the random component of rainfall and how this transformation influences the river discharge. To this end, this paper develops a rainfall–runoff modelling approach that aims to capture the multiple sources and types of uncertainty in a single framework. The main assumption is that hydrological systems are nonlinear dynamical systems which can be described by stochastic differential equations (SDE). The dynamics of the system is based on the least action principle (LAP) as derived from Noether’s theorem. The inflow process is considered as a sum of deterministic and random components. Using data from the Ouémé River basin (Benin, West Africa), the basic properties for the random component are considered and the triple relationship between the structure of the inflowing rainfall, the corresponding SDE that describes the river basin and the associated Fokker-Planck equations (FPE) is analysed.EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR D. Gerten [ABSTRACT FROM PUBLISHER]

The energy-water-land nexus represents a critical leverage future policies must draw upon to reduce trade-offs between sustainable development objectives. Yet, existing long-term planning tools do not provide the scope or level of integration across the nexus to unravel important development constraints. Moreover, existing tools and data are not always made openly available or are implemented across disparate modeling platforms that can be difficult to link directly with modern scientific computing tools and databases. In this paper, we present the Nexus Solutions Tool (NEST): a new open modeling platform that integrates multi-scale energy-water-land resource optimization with distributed hydrological modeling. The new approach provides insights into the vulnerability of water, energy and land resources to future socioeconomic and climatic change and how multi-sectoral policies, technological solutions and investments can improve the resilience and sustainability of transformation pathways while avoiding counterproductive interactions among sectors. NEST can be applied at different spatial and temporal resolutions, and is designed specifically to tap into the growing body of open access geospatial data available through national inventories and the earth system modeling community. A case study analysis of the Indus River Basin in South Asia demonstrates the capability of the model to capture important interlinkages across system transformation pathways towards the United Nations' Sustainable Development Goals, including the intersections between local and regional transboundary policies and incremental investment costs from rapidly increasing regional consumption projected over the coming decades. [ABSTRACT FROM AUTHOR]

This paper studies the Upper Tigris River (UTR) drainage basin in Turkey for climate change impacted runoff estimations. Statistical downscaling method (SDM) is used by taking into consideration spatial dependence function (SDF) for the scenario precipitation projections at a set of available meteorology stations. Temporal adjustment between the climate scenarios and precipitation record time series is achieved by the white Markov (WM) stochastic process. Although various climate research center scenario data are considered, herein, only the general circulation model (GCM) A2 scenario data are adapted from the Hadley Center, England. The precipitation and runoff results are presented in decadal groups starting from 2001 to 2050 as cumulative monthly precipitation (CMP) and cumulative monthly runoff (CMR) graphs. It is observed that after 2021, precipitation decreases at about 12.5% and after 2030, it is 26%. Runoff projections indicate that they may decrease at about 30% especial after 2040. [ABSTRACT FROM AUTHOR]

Freshwater resources are of high societal relevance and understanding their past variability is vital to water management in the context of current and future climatic change. This study introduces a global gridded monthly reconstruction of runoff covering the period from 1902 to 2014. In-situ streamflow observations are used to train a machine learning algorithm that predicts monthly runoff rates based on antecedent precipitation and temperature from an atmospheric reanalysis. The accuracy of this reconstruction is assessed with cross-validation and compared with an independent set of discharge observations for large river basins. The presented dataset agrees on average better with the streamflow observations than an ensemble of 13 state-of-the art global hydrological model runoff simulations. We estimate a global long-term mean runoff of 37 419 km3 yr−1 in agreement with previous assessments. The temporal coverage of the reconstruction offers an unprecedented view on large-scale features of runoff variability also in regions with limited data coverage, making it an ideal candidate for large-scale hydro-climatic process studies, water resources assessments and for evaluating and refining existing hydrological models. The paper closes with example applications fostering the understanding of global freshwater dynamics, interannual variability, drought propagation and the response of runoff to atmospheric teleconnections. The GRUN dataset is available from the ETHZ Research Collection at https://doi.org/10.3929/ethz-b-000324386 (Ghiggi et al., 2019). [ABSTRACT FROM AUTHOR]

Conventional piped drainage systems are currently being challenged by climate change and urbanization, leading to pluvial flooding, with negative consequences for people's properties and lives. Sustainable stormwater management has been suggested as an alternative, but implementation of its infrastructures is often limited to demonstration zones. Governance factors are among the main reasons for the slow pace. A literature review analyzing 44 peer-reviewed papers was conducted to examine the challenges from a governance perspective. The challenges identified were summarized based on actors, resources, rules of the game, and discourses. Challenges such as unclear leadership and responsibilities, lack of funding, lack of cost data on sustainable stormwater management solutions, lack of space and knowledge, lack of uniform guidelines, and lack of stakeholder participation were found to be the most prominent reasons. Suggested solutions to overcoming these challenges include e.g., researchers acting as knowledge brokers, the involvement of social capital among local stakeholders, re-using vacant land, establishing uniform guidelines, and increasing market incentives to engage stakeholders. The governance structures of stormwater management were categorized as hierarchical, closed and open co-governance arrangements, while open co-governance arrangement was suggested as a useful governance structure. The difference is that the latter structure engages stakeholders, which is of benefits to increased sustainable stormwater management implementation. More research on social-economical aspects is suggested. These findings can improve understanding among decision makers and other relevant actors of challenges related to implementing sustainable stormwater management as a primary solution to the current climate and urbanization challenges. [ABSTRACT FROM AUTHOR]

The Yangtze River has been subject to heavy flooding throughout history, and in recent times severe floods such as those in 1998 have resulted in heavy loss of life and livelihoods. Dams along the river help to manage flood waters, and are important sources of electricity for the region. Being able to forecast high-impact events at long lead times therefore has enormous potential benefit. Recent improvements in seasonal forecasting mean that dynamical climate models can start to be used directly for operational services. The teleconnection from El Niño to Yangtze River basin rainfall meant that the strong El Niño in winter 2015/16 provided a valuable opportunity to test the application of a dynamical forecast system. This paper therefore presents a case study of a real-time seasonal forecast for the Yangtze River basin, building on previous work demonstrating the retrospective skill of such a forecast. A simple forecasting methodology is presented, in which the forecast probabilities are derived from the historical relationship between hindcast and observations. Its performance for 2016 is discussed. The heavy rainfall in the May-June-July period was correctly forecast well in advance. August saw anomalously low rainfall, and the forecasts for the June-July-August period correctly showed closer to average levels. The forecasts contributed to the confidence of decision-makers across the Yangtze River basin. Trials of climate services such as this help to promote appropriate use of seasonal forecasts, and highlight areas for future improvements. [ABSTRACT FROM AUTHOR]

The ability of hydrological models to deal with changing conditions should not be taken for granted: it is an unfortunate but well-known problem of hydrology that the model structure and/or parameters optimized for certain conditions may not be transferable in time. Consequently, it is essential that, for application under changing conditions (e.g. in climate change impact studies), models be thoroughly assessed for their extrapolation capacity using adequate protocols. This editorial provides an overview of the Special Issue ofHydrological Sciences Journalcompiled after a workshop on this theme held during the General Assembly of the International Association of Hydrological Sciences (IAHS) in Gothenburg (Sweden) in 2013. The Workshop participants had been invited to apply a calibration and evaluation protocol to their own models on a given set of changing basins. The results show that this protocol is an appropriate and instructive way of assessing the suitability of hydrological models to be applied under changing conditions. This special issue also includes papers following alternative testing methodologies, as well as an opinion paper on the definition of non-stationarity. [ABSTRACT FROM AUTHOR]

This paper introduces a Special Issue ofHydrological Sciences Journalcontaining 10 research papers which present current applications of the Soil and Water Assessment Tool (SWAT) for water resources assessment. First, an overview of selected, recently published papers with application of SWAT is given. The papers address the following topics: nutrients and related best management practices (BMPs); sediments and related BMPs; impoundment and wetlands; irrigation; bioenergy crops; climate change impact; and land-use change impacts. Then, papers from this Special Issue are briefly described, covering the themes: surface runoff and sediments; nonpoint-source pollution; surface water and groundwater; impacts of climate and land-use change; and large-scale SWAT applications. The presented model applications of SWAT were conducted across a variety of spatial scales, physiographic regions and climatic zones. This collection of papers demonstrates that applications of SWAT for water resources assessment are growing in number and cover drainage basins in many regions worldwide.Editor M. Acreman; Associate editor Xi Chen [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the multi-sectoral and distributional economic impacts of rainfall shocks in the Awash river basin in Ethiopia. Using novel disaggregated data on crop production, we estimate the direct impacts of rainfall shocks on agriculture and then use a Computable General Equilibrium model to simulate how these rainfall shocks propagate through the wider economy of the basin under three different climate change scenarios. The basin's economy and expanding agricultural sector are highly vulnerable to the impacts of rainfall shocks. A rainfall decrease scenario could lead to a 5% decline in the basin's GDP, with agricultural GDP standing to drop by as much as 10%. All sectors benefit from greater rainfall amounts. Distributional impacts depend on income group, with poor households accruing greater benefits relative to non-poor households under a scenario of additional rainfall and suffering proportionally lower income losses under a scenario of rainfall decrease. [ABSTRACT FROM AUTHOR]

The Arctic freshwater budget is critical for understanding the climate in the northern regions. However, the hydrology of the Arctic circumpolar tundra region (ACTR) and the largest pan-Arctic rivers are still not well understood. In this paper, we analyze the spatiotemporal variations in the terrestrial water storage (TWS) of the ACTR and three of the largest pan-Arctic river basins (Lena, Mackenzie, Yukon). To do this, we utilize monthly Gravity Recovery and Climate Experiment (GRACE) data from 2002 to 2016. Together with global land reanalysis, and river runoff data, we identify declining TWS trends throughout the ACTR that we attribute largely to increasing evapotranspiration driven by increasing summer air temperatures. In terms of regional changes, large and significant negative trends in TWS are observed mainly over the North American continent. At basin scale, we show that, in the Lena River basin, the autumnal TWS signal persists until the spring of the following year, while in the Mackenzie River basin, the TWS level in the autumn and winter has no significant impact on the following year. As expected global warming is expected to be particularly significant in the northern regions, our results are important for understanding future TWS trends, with possible further decline. [ABSTRACT FROM AUTHOR]

The fluvial archives in the upper-reach Yellow River basins provide important information about drainage history of the northeastern Tibetan Plateau (TP) associated with geomorphologic evolution and climate change. However, the Pliocene fluvial strata within this region have not been studied in detail, hence limiting the understanding of the late Cenozoic development of regional fluvial systems. In this paper, we present the results of a study of the geochronology, sedimentology, and provenance of the fluvial sequence of the Wuquan Formation in the Lanzhou Basin in the northeastern TP. Magnetostratigraphic and cosmogenic nuclide burial ages indicate that the Wuquan Formation was deposited during 3.6–2.2 Ma. Furthermore, sedimentary facies, gravel composition, paleocurrent data, and detrital zircon U Pb age spectra reveal that the fluvial sequence resembles the terraces of the Yellow River in terms of source area, flow direction, and depositional environment. Our results indicate that a paleo-drainage system flowing out of the northeastern TP was established by ca. 3.6 Ma and that the upstream parts of the Yellow River must have developed subsequently from this paleo-drainage system. The late Pliocene drainage system fits well with the dramatic uplift of the northeastern TP, an intensified Asian summer monsoon, and global increase in erosion rates, which may reflect interactions between geomorphic evolution, tectonic deformation, and climate change. [ABSTRACT FROM AUTHOR]

A flow duration curve (FDC) is widely used for predicting water supply, hydropower, environmental flow, sediment load, and pollutant load. Among different methods of constructing an FDC, the entropy-based method, developed recently, is appealing because of its several desirable characteristics, such as simplicity, flexibility, and statistical basis. This method contains a parameter, called entropy parameter M, which constitutes the basis for constructing the FDC. Since M is related to the ratio of the average streamflow to the maximum streamflow which, in turn, is related to the drainage area, it may be possible to determine M a priori and construct an FDC for ungauged basins. This paper, therefore, analyzed the characteristics of M in both space and time using streamflow data from 73 gauging stations in the Brazos River basin, Texas, USA. Results showed that the M values were impacted by reservoir operation and possibly climate change. The values were fluctuating, but relatively stable, after the operation of the reservoirs. Parameter M was found to change inversely with the ratio of average streamflow to the maximum streamflow. When there was an extreme event, there occurred a jump in the M value. Further, spatially, M had a larger value if the drainage area was small. [ABSTRACT FROM AUTHOR]

This work describes a mountain meteorological network that was in operation from 1999 to 2014 in a mountain range with elevations ranging from 1104 to 2428 m in Central Spain. Additionally, some technical details of the network are described, as well as variables measured and some meta information presented, which is expected to be useful for future users of the observational database. A strong emphasis is made on showing the observational methods and protocols evolution, as it will help researchers to understand the sources of errors, data gaps and the final stage of the network. This paper summarizes mostly the common sources of errors when designing and operating a small network of this kind, so it can be useful for individual researchers and small size groups that undertake a similar task on their own. Strengths and weaknesses of some of the variables measured are discussed and some basic calculations are made in order to show the potential of the database and to anticipate future deeper climatological analyses over the area. Finally, the configuration of an automatic mountain meteorology station is suggested as a result of the lessons learned and the the common state of the art automatic measuring techniques. [ABSTRACT FROM AUTHOR]

In coastal catchments, rainfall events primarily drive bacterial inputs to the sea by causing land runoff, surface leaching and sewer overflow. Under semi-arid climate, extensive dry periods are interspersed with extreme precipitation. This paper aims to assess the impact of intense summer rainstorms events on Fecal Indicator Bacteria loadings to Mediterranean seawaters. Firstly, explanatory relationships were derived between an Antecedent Precipitation Index and the loads of thermo-tolerant coliforms and intestinal enterococci measured at three catchment outlets in the Gulf of Aigues-Mortes (southern France). Secondly, fecal bacterial loadings were simulated during summer season from 2006–2016, with a confidence interval arising from measurements uncertainties. On average, more than two rainstorms per summer season elevate bacterial loads at least by one order of magnitude, potentially leading to the degradation of bathing and fishing water quality observed in regulatory monitoring data. The results highlight the crucial importance of considering hydrological conditions in coastal water quality management. [ABSTRACT FROM AUTHOR]