Total Annual Precipitation Research Articles

Comparison of RegCM4.7.1 Simulation with the Station Observation Data of Georgia, 1985–2008

The global climate change, driven by natural processes and increasing human activities, is especially significant for Georgia. The region is experiencing increases in temperature, desertification, redistribution of precipitation, and a rise in the frequency and severity of extreme weather events. Georgia’s complex topography and its proximity to the Black and Caspian seas make it essential to employ high-resolution regional climate models to evaluate future climate change risks. In this study, we examine the results of a high-resolution simulation of mean and extreme precipitation and temperature using the Abdus Salam International Centre for Theoretical Physics Regional Climate Model version 4.7.1 for the period 1985–2008, providing an initial evaluation of the model’s performance for the territory of Georgia. The model domain (1524 km; 2388 km) encompasses the entirety of Georgia’s territory and surrounding regions. The simulation, conducted at a 12 km horizontal grid spacing using ERA5 data as boundary conditions, indicates that the least discrepancy between observed and modeled average annual temperatures and precipitation, falling within a −1 to 1 °C and −200 to 200 mm range, respectively, was observed at most stations of eastern Georgia. The largest disparities between the model and observed average annual precipitation totals were noted along the Black Sea coast, in the Kolkheti Lowland, and in some high mountain stations in western Georgia. The most significant differences in average annual temperatures between the model and observations were observed in Ambrolauri, Mt. Sabueti, and Dedoplistskaro. For Georgia territory, such a long run with such a high resolution using ERA5 as boundary conditions was conducted for the first time. Overall, the modeling results are quite satisfactory, providing a solid basis for the successful utilization of the regional climate model RegCM4.7.1 with the selected parameterization for modeling monthly mean and extreme temperatures and precipitation in Georgia.

The Impact of “Hot Models” on a CMIP6 Ensemble Used by Climate Service Providers in Canada: Do Global Constraints Lead to Appreciable Differences in Regional Projections?

Abstract Canadian climate service providers offer projections from the Coupled Model Intercomparison Project (CMIP6) to help inform climate change mitigation and adaptation decisions. CMIP6 includes several “hot” climate models whose sensitivity to greenhouse gas forcings exceeds the likely range inferred from multiple lines of evidence. Global warming estimates assessed in the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) were reduced by applying observational constraints on the historical rate of warming to the CMIP6 ensemble. This study assesses whether globally constrained CMIP6 projections for Canada are appreciably different from unconstrained projections. Two constraints are considered: one that removes models whose transient climate response lies outside the AR6 assessed range (TCRlikely), and the other that weights models to match the assessed distribution of equilibrium climate sensitivity (ECSall). Both constraints lead to appreciably cooler and drier projections than the unconstrained ensemble, with the strongest reductions seen in the upper end of the ensemble range, high-emissions scenario, end-of-century time period, and northern regions of Canada. In this case, constrained projections of annual mean temperature are 2°–3°C cooler than the unconstrained projections, whereas projections of annual total precipitation are typically 20%–40% drier. Appreciable differences are also detected in the ensemble median of temperature extreme indices. Based on these results, it is recommended that a constrained ensemble be considered for regional projections to avoid the “hot model” problem. Alternatively, projections can be communicated conditional on a specified level of global warming, with global constraints then used to inform the timing of the warming level exceedance.

A new diagram for performance evaluation of complex models

In the latest years the capacity and complexity of climate and environmental modeling has increased considerably. Therefore, tools and criteria for model performance evaluation are needed to ensure that different users can benefit from model selection. Among graphical tools, Taylor’s diagram is widely used to provide evaluation and comparison of model performances, with particular emphasis on climate models. Taylor’s diagram accounts for different statistical features of model outputs and observations, including correlation, variability and centered root mean square error. Not included is model bias, which is an essential feature for climate model evaluations, and it is usually calculated separately to complement the information embedded in Taylor’s diagram. In this paper a new diagram is proposed, referred to as Aras’ diagram, which allows for visual assessments of the correspondence between model outputs and reference data in terms of total error, correlation, as well as bias and variability ratios through an easy-to-interpret two-dimensional (2D) plot, allowing for proper weighting of different model features. The strengths of the new diagram are exemplified in a case study of performance evaluation of EURO-CORDEX historical experiment over Southern Italy using E-OBS as reference dataset, for three hydrological variables (i.e. daily precipitation, daily surface minimum temperature, and daily maximum surface temperature), and four popular climate indices (i.e. total annual precipitation, annual maxima of daily precipitation, annual minima of daily minimum temperatures, and annual maxima of daily maximum temperatures). The proposed diagram shows interesting properties, in addition to those already included in Taylor’s diagram, which may help promoting climate model evaluations based on their accuracy in reproducing the climatological patterns observed in time and space.

Application of Arc-SWAT Model for Water Budgeting and Water Resource Planning at the Yeralwadi Catchment of Khatav, India

Every facet of life, including human habitation, economic development, food security, etc., depends on water as a valuable resource. Due to the burgeoning population and rapid urbanization, water availability needs to be simulated and measured using hydrologic models and trustworthy data. To fulfill this aim, the SWAT model was processed in this work. The SWAT model was formulated to estimate the hydrological parameters of Yeralwadi using meteorological data from IMD (India Meteorological Department) for the period 1995-2020. The observed discharge data was collected from the HDUG Nasik group and used in the calibration and validation of the Model. The SWAT model was corrected & validated through the SUFI-II algorithm in SWAT-CUP to get a better result. The model’s sensitivity is checked by using statistical parameters like Nash-Sutcliffe Efficiency (NSE) and a coefficient of determination (R2). NSE values were 0.72 and 0.80 in calibration and validation, and R2 were 0.80 & 0.76 in calibration and validation, respectively, indicating the acceptance of the model. Results show that 40.6% of the total yearly precipitation was lost by evapotranspiration. The estimated total discharge from the Yeralwadi catchment was 55.6%, out of which 41.2% was surface runoff and 14.4% was baseflow. The other 17.8% was made up of percolation into confined and unconfined aquifers, which served as soil and groundwater storages. The surface runoff is influenced by Curve number (CnII), SOL_AWC, ESCO, and base flow was influenced by ALPHA-BF and GW_REVAP. This study will be useful to water managers and researchers to develop sustainable water resource management and to alleviate the water scarcity issues in the study basin.

Trend analysis of hydro-climatic variables in the Great Lakes Depression region of Mongolia

Abstract Arid and semi-arid regions are the first to be affected by hydro-climatic changes. The Great Lakes Depression Basin in western Mongolia is the most notable example of such a region. Therefore, analyzing hydro-climatic changes in the Great Lakes Depression region is essential for future climate, hydrological, eco-hydrological processes, and ecosystem studies in similar areas and basins. In this study, Mann–Kendall (MK), innovative trend analysis method (ITAM), and Sen's slope estimator test (SSET) were used to determine the interrelationship between climate and river discharge changes and lake water level changes through statistical analysis. During the last 30 years, the air temperature has increased by 1.2 °C (Z = 1.16). Total annual precipitation decreased by 23.44 mm, resulting in 134.16 mm (Z = −0.79). The river discharge of the major rivers, such as Khovd River (Z = −3.51) and Zavkhan River (Z = −6.01), has significantly decreased. In Uvs (Z = 0.30) and Khyargas (Z = 2.03) lakes, the water level has also dropped. This study confirms that the increase in air temperature in the depression area of the Great Lakes reduces the amount of precipitation, and the decrease in precipitation affects the decrease in river discharge, which further affects the water level of the inflowing lakes.

Integrative approach for landscape demography analysis of Plakad-Pa Pak-Tawan-Ok (Betta siamorientalis): Deciphering genetic and environmental factors in Eastern Thailand's conservation efforts

In recent decades, a global acceleration of urbanization has been observed, leading to significant habitat loss and fragmentation. Economic development in eastern Thailand has been promoted, but this has often coincided with unsustainable exploitation of natural resources. The expansion of urban and industrial areas in the region puts many organisms at risk of extinction owing to habitat loss. Plakad-Pa Pak-Tawan-Ok (Betta siamorientalis) is an endemic species found only in the eastern Thailand. In this study, the genetic diversity and population structure of 17 B. siamorientalis populations were analyzed using microsatellite genotyping. High genetic variability was observed. The STRUCTURE plot reveals large, distinct gene pools in the lower Prachin River and Phra Prong River Part 2. Migration analyses showed that the estimated gene flow between populations aligned with the dominant water flow in the flooding direction toward the mouth of the Bang Pakong River on the western side of eastern Thailand. Thus, this area must be considered a vital genetic resource. The pairwise fixation index values were statistically significant for all populations, including those within the same sub-watershed, indicating genetic differentiation among populations. This suggests relatively low gene flow between ecologically divergent populations. Mean annual total precipitation was also significantly correlated with genetic diversity. We propose the need for careful consideration and awareness of the planning and implementation of industrial development within eastern Thailand. Resource allocation in management efforts may be most effective when directed toward the preservation of habitat suitability, specifically in relation to precipitation and water resources, rather than prioritizing enhancements in landscape connectivity for B. siamorientalis.

Human-induced intensification of terrestrial water cycle in dry regions of the globe

Anthropogenic climate change (ACC) strengthens the global terrestrial water cycle (TWC) through increases in annual total precipitation (PRCPTOT) over global land. While the increase in the average global terrestrial PRCPTOT has been attributed to ACC, it is unclear whether this is equally true in dry and wet regions, given the difference in PRCPTOT changes between the two climatic regions. Here, we show the increase in PRCPTOT in dry regions is twice as fast as in wet regions of the globe during 1961–2018 in both observations and simulations. This faster increase is projected to grow with future warming, with an intensified human-induced TWC in the driest regions of the globe. We show this phenomenon can be explained by the faster warming and precipitation response rates as well as the stronger moisture transport in dry regions under ACC. Quantitative detection and attribution results show that the global increase in PRCPTOT can no longer be attributed to ACC if dry regions are excluded. From 1961–2018, the observed PRCPTOT increased by 5.63%~7.39% (2.44%~2.80%) over dry (wet) regions, and as much as 89% (as little as 5%) can be attributed to ACC. The faster ACC-induced TWC in dry regions is likely to have both beneficial and detrimental effects on dry regions of the globe, simultaneously alleviating water scarcity while increasing the risk of major flooding.

Blocking Events in East Antarctica: Impact on Precipitation and their Association with Large-Scale Atmospheric Circulation Modes

Abstract This study, utilizing ERA5 data from 1979 to 2021, identifies a prevalent occurrence of blocking events in East Antarctica, particularly in the region extending from Wilkes Land to Dronning Maud Land. The genesis of these blocking highs is typically facilitated by the intensification of Rossby waves within the circumpolar westerlies. By classifying the circulation patterns causing the blocking events, the blocking events in East Antarctica are divided into five categories. On the western flank of the blocking high, we observe the transportation of warm and humid air into inland Antarctica, instigating regional snowfall. High precipitation levels are observed in different regions based on the specific location of the blocking high. We also demonstrate that the contribution of atmospheric blockings to total annual precipitation and extreme precipitation events increases from coastal to inland. Over the East Antarctic plateau, the blockings are responsible for at least 15% of total accumulated snowfall and 30% of extreme precipitation events. Finally, we find a significant relationship between the interannual variability in East Antarctic blocking frequency and the phase variability of the Southern Annular Mode (SAM). A positive phase of the SAM inhibits an increase in blocking frequency, while a negative phase favors an increase. However, the two Pacific–South American patterns (PSA-1 and PSA-2), characterized by wave trains originating in the tropical Pacific that extend across the Southern Hemisphere extratropics, do not significantly influence the interannual variability in East Antarctic blocking frequency.

Performance Evaluation of High-resolution Reanalysis Datasets Over North-central British Columbia

abstract Version 2.1 of Environment and Climate Change Canada’s Canadian Surface Reanalysis (CaSR), based on the Regional Deterministic Reforecast System (RDRS), was implemented in 2022 to provide temporally complete meteorological data over 1980–2018 covering Canada at 10 km spatial resolution. Similarly, the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis-Land (ERA5-Land) dataset at ∼9 km spatial resolution became available. To assess their performance in complex topography, this paper undertakes spatiotemporal inter-comparisons between the RDRS and ERA5-Land reanalysis products with station-based data across British Columbia’s Skeena and Nechako watersheds for 1980–2018. Results reveal persistent cold biases, ranging from −6.2°C to −1.6°C basin-wide, in reanalysis mean annual air temperatures relative to observations, but biases vary in both space and time. Conversely, reanalysis total annual precipitation shows wet biases, ranging from 25% to 59% basin-wide. Analyses generally show wetting trends for observations and ERA5-Land while RDRS exhibits drying trends. Reanalysis datasets achieve better agreement overall with observations over the Nechako Watershed, likely due to its denser network of meteorological stations and less complex terrain than the Skeena Watershed. Despite some deficiencies, the RDRS and ERA5-Land reanalyses remain particularly useful products to assess regional climate variability and climatic change given their generally skilful representation of spatial patterns and temporal trends in meteorological variables across the Nechako and Skeena watersheds.

Divergent trajectories of future global gross primary productivity and evapotranspiration of terrestrial vegetation in Shared Socioeconomic Pathways

Understanding the future trends of carbon and water fluxes between terrestrial ecosystems and the atmosphere is crucial for predicting Earth's climate dynamics. This study employs an advanced numerical approach to project global gross primary productivity (GPP) and evapotranspiration (ET) from 2001 to 2100 under various climate scenarios based on Shared Socioeconomic Pathways (SSPs). To improve predictions of vegetation dynamics, we introduce a novel model (CoLM-PVPM), an enhancement of the Common Land Model version 2014 (CoLM2014), incorporating a prognostic vegetation phenology model (PVPM). Compared to CoLM2014 that relies on satellite-based leaf area index (LAI) inputs, CoLM-PVPM predicts LAI time series using climate variables. Model validation using historical data from 2001 to 2010 demonstrates PVPM in capturing spatiotemporal variations in satellite LAI. Our modeling results indicate that annual averaged LAI and total GPP increase under SSP1–2.6 but decrease under SSP2–4.5, SSP3–7.0, and SSP5–8.5 by 2100. By comparison, annual total ET consistently increases under all SSP scenarios by 2100. Global annual averaged LAI is highly correlated with annual total GPP in all scenarios, while its correlation with annual total ET weakens in SSP2–4.5, SSP3–7.0, and SSP5–8.5. Global annual total vapor pressure deficit (VPD) and precipitation are highly correlated with annual total ET in all scenarios. As emission levels increase, the negative correlation between annual total VPD and GPP strengthens, while the correlation between annual total precipitation and GPP weakens. This research presents an improved model for predicting terrestrial vegetation processes and underscores the importance of low carbon emission scenarios in maintaining carbon-water balances in specific regions.

Drought analysis based on SPI and RDI drought indices in the Burdur Basin

Drought is the most complex of the recurrent extreme weather events and is defined as a natural disaster with severe environmental, economic, and agricultural impacts resulting from a significant decrease in the average rainfall recorded in an area and the average rainfall recorded in the same place. Droughts have become more frequent and severe in many parts of the world, including Türkiye, due to global warming and climate change (increasing temperatures and changing precipitation patterns). Water resources and the agricultural sector are most severely affected by droughts. In this study, drought analyses of the Burdur Basin, located in the Aegean region, one of Türkiye's seven geographical regions, were carried out. For drought analysis, annual average total precipitation, annual maximum temperature, annual minimum temperature, and annual average temperature data of 17238 Burdur and 17892 Tefenni meteorological observation stations were used. Both meteorological and agricultural drought analyzes are included in the analysis of droughts. Standard Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) methods were used to determine meteorological and agricultural drought, respectively. SPI and RDI values were obtained for 1-, 3-, 6- and 12-month time periods, and the severity, size, and distribution of dry and humid periods were determined for both stations separately. When the results of both methods were examined, severe droughts were observed in the study area in 1973, 1978, 1981, and 2017.

Determination of relations between plant species diversity and productivity in Brutian pine stands

This study examines the relationship between Brutian pine productivity and plant species diversity, focusing on its potential as a valuable resource. Data was collected from 101 natural Brutian pine stands in Muğla and Antalya through inventory studies. Age and height values were recorded for three selected Brutian pine trees in each plot, along with plant species diversity using the Braun-Blanquet scale. Site index values were used to assign productivity scores between 1 and 5 for each plot. Diversity values were adjusted to a scale of 1 to 9 according to Westhoff and Maarel (1973) to calculate alpha diversity indices (Shannon and Simpson) using BİÇEB software. Environmental variables such as elevation, slope, radiation index, annual mean temperature, and annual precipitation were also collected for further analysis. The Kolmogorov-Smirnov normality test was first applied to the data matrix. Since it was determined that the normality assumption was not met (p<0.05), the Kruskal-Wallis test, which is a non-parametric method, was used to determine whether there is a significant difference between the diversity values for the site index groups. Results indicated a statistically significant difference (p<0.05) in diversity values among these groups. Then, diversity values and environmental variables were correlated using principal component analysis method (PCA). At the same time, site index groups were also included in the PCA as class data. As a result, it was revealed that Shannon and Simpson diversity values have a negative relationship with elevation and slope and a positive relationship with total annual precipitation.

Annual Mean Total Precipitation Reconstruction of the Elmacık Mountain and Its Surroundings for 1858-2015 Using Scotch Pine Tree Rings

Annual Mean Total Precipitation Reconstruction of the Elmacık Mountain and Its Surroundings for 1858-2015 Using Scotch Pine Tree Rings

Agroclimatic mapping for olive cultivation in Brazil: pinpointing optimal growing regions.

This research aimed to identify the agroclimatic zones in Brazil, excluding Rio Grande do Sul, that are suitable for olive (Olea europaea L.) cultivation, considering both climatic and topographical factors. Olives require specific conditions: moderate winter temperatures (7-15 °C), warmer summers (25-35 °C) and sufficient water during growth and fruit maturation. They can endure some drought, making them a viable option for agricultural diversification. Using daily meteorological data from 1989 to 2023 from NASA-POWER, this study analyzed variables like air temperature (minimum and maximum) and rainfall. Key climate variables were the mean air temperature in winter (T_w), spring (T_s), summer (T_su) and autumn (T_a) and total annual precipitation (Prec). Criteria for suitability included: T_w between 5 and 20 °C, T_s between 15 and 23 °C, T_su between 15 and 30 °C, T_a between 15 and 22 °C, annual precipitation over 900 mm and altitude below 900 m. Geographic information system software and Python 3.8 were employed for data analysis and zoning. Results indicated that only 1.92% of the analyzed area, mainly in Minas Gerais, was suitable for olive cultivation. High temperatures and low rainfall in Brazil, particularly in the North and Midwest, make 59.56% of the country unsuitable for olive farming. Additionally, 18.58% of the land, mainly in the Northeast, faces challenges due to extreme heat (T_w) and insufficient water supply. © 2023 Society of Chemical Industry.

Water cycle changes in Czechia: a multi-source water budget perspective

Abstract. The water cycle in Czechia has been observed to be changing in recent years, with precipitation and evapotranspiration rates exhibiting a trend of acceleration. However, the spatial patterns of such changes remain poorly understood due to the heterogeneous network of ground observations. This study relied on multiple state-of-the-art reanalyses and hydrological modeling. Herein, we propose a novel method for benchmarking hydroclimatic data fusion based on water cycle budget closure. We ranked water cycle budget closure of 96 different combinations for precipitation, evapotranspiration, and runoff using CRU TS v4.06, E-OBS, ERA5-Land, mHM, NCEP/NCAR R1, PREC/L, and TerraClimate. Then, we used the best-ranked data to describe changes in the water cycle in Czechia over the last 60 years. We determined that Czechia is undergoing water cycle acceleration, evinced by increased atmospheric water fluxes. However, the increase in annual total precipitation is not as pronounced nor as consistent as evapotranspiration, resulting in an overall decrease in the runoff. Furthermore, non-parametric bootstrapping revealed that only evapotranspiration changes are statistically significant at the annual scale. At higher frequencies, we identified significant spatial heterogeneity when assessing the water cycle budget at a seasonal scale. Interestingly, the most significant temporal changes in Czechia occur during spring, while the spatial pattern of the change in median values stems from summer changes in the water cycle, which are the seasons within the months with statistically significant changes.

Projected Changes in Temperature and Precipitation over Canada in the 21st Century

Climate change is one of the most urgent and challenging issues in Canada. In this study, high-resolution climate projections over Canada have been developed through the WRF model. The spatial and temporal variations of Canada’s temperature and precipitation in the 21st century have been comprehensively analyzed. It is found that the annual mean temperature over Canada is projected to increase by [1.53, 1.98], [2.51, 3.86], and [2.94, 6.19]°C in the 2030s, the 2050s, and the 2080s under RCP4.5 and RCP8.5 respectively, with the largest increase in winter. The annual total precipitation is projected to increase by [16.33, 68.96], [64.80, 121.62], and [123.62, 184.33] mm in three future periods under RCP4.5 and RCP8.5 respectively. It is also found that sea surface temperatures (SST) anomalies and 500 hPa geopotential height (GPH) have strong impacts on Canada’s annual and seasonal precipitations. The results can provide valuable information for mitigation and adaptation of climatic changes in a Canadian context.

Estimation of Groundwater Storage Change and Groundwater Recharge Using GRACE data in Jedeb Watershed Under the Application of Google Earth Engine

Over exploitation of Ground Water (GW) has resulted in lowering of water table in the Jedeb watershed. In this study, water storage changes with GRACE satellite data and total annual precipitation with CHIRPS data in the Google Earth Engine system were investigated for the Jedeb watershed during 2003–2017. The groundwater recharge is estimated from a time series of groundwater storage using the water table fluctuation method. According to the results obtained from the GRACE satellite data on the fluctuations of annual water storage between 2003 and 2017, it was found that the biggest annual increase in water levels (15 cm) occurred in 2008, 2013, and 2015, and the biggest annual decrease (12.5 cm) occurred in 2012. The obtained net recharge rate varied from 18 to 25 cm/year for a 14-year period, and the average was 21 cm/year. This study indicates that the GRACE-based estimation of groundwater storage changes is skilled enough to provide monthly updates on the trend of groundwater storage changes for resource managers and policymakers in the Jedeb watershed.

The relationship between forest cover loss and annual rainfall in the departments of Peru, 2013-2022

Forest masses participate in the hydrological cycle and precipitation patterns. Therefore, the loss of these forest masses has significant implications for atmosphere-surface dynamics. The objective of this article is to determine the influence of forest cover loss on annual rainfall in the departments of Peru during the period 2013-2022. The methodology was quantitative, longitudinal non-experimental design, with panel data and a random-effects model was estimated. The results reveal a positive and statistically significant relationship between tree cover loss and total annual precipitation, specifically, a 1% increase in deforestation is related to an average increase of 0.186% in annual rainfall. The findings contrast with most previous evidence documenting reductions in precipitation due to deforestation, however, they are consistent with some studies. The research concluded that there is a positive relationship between the loss of forest cover and annual rainfall in the departments of Peru during the period studied.

Characterization of landuse and landcover dynamics and their impact on runoff generation patterns in dam catchments of Northern Ghana

Landuse alteration is a critical factor that exerts influence over hydrological mechanisms and the oversight of water resources across the globe. Northern Ghana is characterized by erratic rainfall, leading to the intense construction of small dams and dugouts. This study investigated historical landuse/cover (LULC) changes and physical factors associated with surface runoff generation within eight (8) sub-catchments namely; Guno, Gbahali, Sambu, Duago, Denugo, Kwisini, Sandu, and Nyeko, with areas of 29.5, 110, 38.5, 106.04, 67.81, 2.59, 10.56 and 120.65 km2, respectively, located in four (4) regions of northern Ghana. For LULC change detection, historical satellite imagery and geospatial data were used with the aid of remote sensing and applying supervised maximum likelihood classification to Landsat images of 1995, 2005, 2015, and 2023. Runoff factors and depths were identified based on LULC classes, hydrologic soil groups, and precipitation conditions prevailing in the areas, based on the curve number (CN) method. With regards to LULC, the results from the overall analysis gave an insight into the rampant conversion, where grassland/mix vegetation witnessed significant declines, with decreases ranging from 150 to 395.25% in different catchments. Agricultural and arable lands emerged as the dominant landuse category, indicating a remarkable expansion of 11.61–51.17 km2, from 1995 to 2023 respectively, followed by built-up areas. While grassland decreased in all catchments over the same period, in some places, open tree (savannah woodland) increased, which confirmed the implementation of the afforestation policy. The CN values offered essential insights into the hydrological characteristics of each catchment. In addition to the impact of LULC and watershed characteristics on runoff, the observed variations in runoff patterns can be attributed to interannual variability in total annual precipitation which is critical driver of runoff. The findings hold significant importance for developing effective strategies and integrated watershed management policies to contribute to better water resource management and inform sustainable landuse planning in the face of changing environmental conditions.

Overview of Marginal Lands in Henan Province, China and Evaluation of Development Potential of Biomass-To-Liquid Fuels

Developing marginal lands to plant energy crops and then develop biomass-to-liquid fuels is an effective way to ease the energy crisis, promote greenhouse gas emission reduction, and protect the natural ecological environment. Taking Henan Province, China as a research object, the research obtained spatial distributions and areas of marginal lands in the province by processing remote-sensing data for land use using software ArcGIS. Marginal lands in Henan Province were classified into the first-class, second-class, and third-class ones by selecting key natural conditions including the soil thickness, slope, soil texture (sand volume fraction), accumulated temperature above 10 °C, organic matter content, and total annual precipitation as indices. The research showed that the total area of marginal lands in the province is 1.68×104 km2, including 0.62×104 km2 of first-class marginal lands, 0.83×104 km2 of second-class marginal lands, and 0.23×104 km2 of third-class marginal lands. Taking production of bioethanol with sugar grass as an example, 8.92×107 t of sugar grass can be harvested on the marginal lands in Henan Province, which can be converted into 5.80×106 t of bioethanol, equivalent to 6.96×106 t of standard coal. The research can provide reference for realizing energy structure optimization and consolidating energy security in Henan Province.